CN118967151A - Precise tracking system for plantation plot activity imprint and GHG emission management method - Google Patents
Precise tracking system for plantation plot activity imprint and GHG emission management method Download PDFInfo
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Abstract
The invention discloses an artificial forest land block activity imprinting accurate tracking system and a GHG emission management method, wherein the system comprises the following components: a storage server, a distributed server, or a set of processors; a database; identifying software; accounting software; the forestry activities implement imprint tracking software; forestry activity energy consumption tracking software; GHG tracking software; carbon credit tracking software in the forest stand operation process; optimizing software; assisting in developing software. The invention can track and analyze the global forestry production emission in a comprehensive and consistent land parcel forestry activity process, and can test the effectiveness of relief methods and package measures suitable for being adopted in different production systems.
Description
Technical field:
the invention relates to the technical field of carbon neutralization, in particular to an artificial forest land block activity imprinting accurate tracking system and a GHG emission management method.
The background technology is as follows:
In recent years, global warming, climate change and china have become key to the realization of global zero-carbon strategic action programs and sustainable development goals. With the rapid popularization and continuous upgrading of energy saving and emission reduction technologies, knowledge of greenhouse gas (Greenhouse Gas, GHG) emissions has penetrated into various areas of economy, environment, society and life. How to cost effectively avoid and/or counteract GHG emissions, optimize energy structures, achieve net zero emissions in countries while coping with climate change, reducing environmental risks, promoting economic transformation and social high quality development is a direction of government, enterprise and personal co-efforts. With the maturation of cross-sector efforts, the effective quantification of data such as "land" digital ecosystems, "land" activity marks, energy consumption, GHG emission and the like will indicate the increase of new energy efficiency, the change of sustainable production modes and the improvement of supply chain toughness, which are the general demands of various departments and industries.
In the current domestic carbon market, forestry carbon sinks are mainly carbon emission quota and CCER forestry carbon exchange offset mechanisms, but are not carbon neutralization services, so that the value of the forestry carbon sinks is not truly embodied, and carbon emission transactions realized by carbon credits of forest product production and management activities and product values of forest ecosystems are lacked. In the prior exploration of forestry activity tracking and emission management systems and methods, the problems of relatively weak monitoring force, lack of supply chain integration of metering verification statistics monitoring information, less carbon credit parameters, lack of procedural systems, non-uniform value standard and the like are faced. Only a method for integrating forestry resources or disaster damage statistical data aiming at a specific forestry service does not exist in a system and a method for managing large data tracing of the history of the "land" forestry activity marks, real-time accurate tracing and GHG emission, and a tool capable of comprehensively and consistently tracing and analyzing the global forestry production emission in the process of the land forestry activity is lacking, so that the effectiveness of a relief method and a package measure suitable for being adopted in different production systems cannot be tested. The method leads the production and supply of forest products to be unable to take a global value chain, and influences the effective traceability, excavation and analysis of data, so that the forest type and operation mode carbon sink/emission reduction function promotion and the forest carbon neutralization service value are unable to be effectively and accurately metered and monitored, the forest carbon sink traffic and carbon neutralization potential are inhibited, the transaction of forest carbon neutralization service is unable to be realized, and the social and economic cost for coping with climate change is also increased.
The invention comprises the following steps:
Aiming at the problems in the prior art, the invention provides the precise tracking system for the activity imprinting of the artificial forest land and the GHG emission management method, which can track and analyze the global and consistent process of the activity of the land forestry, and can test the effectiveness of the relief method and the blanket measures which are suitable for being adopted in different production systems.
In order to achieve the above purpose, the invention provides an artificial forest land activity imprinting accurate tracking system, comprising:
(a) A storage server, a distributed server, or a set of processors; the 'land parcel' level forestry activities can access a storage server, a distributed server or a processor set through an electronic device network, wherein the electronic device comprises a personal PC, a tablet, a portable APP terminal and a mobile phone;
(b) A database of "parcel" forest resource partitions and capital value accounting in communication with a storage server, distributed server, or processor set, the database configured to store artificial parcel, and attribute information, artificial parcel ecosystem product production and service supply information, parcel-level forestry activity footprint information, artificial parcel activity energy consumption information, artificial parcel management activity GHG emission information, and parcel stand management process carbon credit information;
(c) Identification software for the artificial forest "parcel" zones and attributes associated with the storage server, distributed server, or processor set, the identification software configured to be capable of linking, associating, acquiring, mining, and registering artificial forest "parcel" zones and attribute information associated with each of a plurality of forest resources or natural capital or parcel of at least two forest farms;
(d) Accounting software for dynamic accounting of manufactured forest "land" ecosystem product production, service supply, and value associated with the storage server, distributed server, or processor set, the accounting software configured to calculate, store, and track manufactured forest "land" ecosystem product production, service supply, and value dynamic information associated with each of a plurality of forest resources or natural capital or land parcels of the at least two forest farms;
(e) Forestry activity implementation footprint tracking software for "parcel" level forestry activity implementation footprint tracking associated with the storage server, distributed server, or processor set, the forestry activity implementation footprint tracking software configured to trace and register artificial forest "parcel" activity practice process footprint information associated with each of a plurality of forest resources or natural capital or parcel of the at least two forest farms;
(f) Forestry activity energy consumption tracking software for "parcel" level forestry activity energy consumption tracking associated with the storage server, distributed server, or processor set, the forestry activity energy consumption tracking software configured to calculate and track artificial forest "parcel" activity energy consumption information associated with each of a plurality of forest resources or natural capital or parcel of the at least two forest farms;
(g) GHG tracking software of "land parcel" activity associated with the storage server, distributed server, or processor set, the GHG tracking software configured to calculate and track artificial forest "land parcel" operational activity GHG emission information related to each of a plurality of forest resources or natural capital or land parcel of the at least two forest farms;
(h) Stand business process carbon credit tracking software for "parcel" stand business process carbon credit tracking associated with the storage server, distributed server, or processor set, the stand business process carbon credit tracking software configured to calculate and track "parcel" stand business process carbon credit information associated with each of a plurality of forest resources or natural capital or parcel of the at least two forest lands;
(i) Optimization software for manual forest "parcel" activity footprint precision tracking and GHG emission management and cost-benefit optimization associated with said storage server, distributed server or processor set, the optimization software being configured to calculate, track and modify to calculate and track a manual forest "parcel" level operation optimization objective based on any one or more of said manual forest "parcel" ecosystem product production and service supply information, manual forest "parcel" GHG emission information, "parcel" activity energy consumption information and "parcel" stand operation process carbon credit information;
(j) Auxiliary development software for artificial forest "parcel" activity footprint precision tracking and GHG emission management assistance associated with the storage server, distributed server or processor set, the auxiliary development software configured to calculate, predict and replace to assist in developing an artificial forest ecosystem multi-dimensional "parcel" activity optimal implementation based on any one or more of the artificial forest "parcel" region and attribute change information, artificial forest "parcel" ecosystem product production and service supply evolution information, artificial forest "parcel" GHG emission response information, "parcel" activity energy consumption change information and "parcel" stand operation process carbon credit change information;
(k) Aided design software for accurate tracking of artificial forest "parcel" activity imprints and GHG emission management associated with the storage server, distributed server or processor set, the aided design software being configured to be computationally, contextualized and analyzable to calculate, link, trade-off and AI-aided design of a value-enhancing mechanism, ecosystem versatility, synergy and ecological product value implementation for an artificial forest "parcel" level activity value chain based on any one or more of the artificial forest "parcel" region and attribute change information, artificial forest "parcel" ecosystem product production and service supply evolution information, artificial forest "parcel" GHG emission response information, "parcel" activity energy consumption change information and "parcel" stand operation process carbon credit change information.
Further, mapping software associated with the storage server, the distributed server, or the processor set is also included, the mapping software configured to generate a space-time evolution dynamic pattern diagram related to at least one of distributed artificial forest "parcel" ecosystem product production and service provisioning information, distributed "parcel" activity intensity and energy consumption information, distributed "parcel" business activity GHG emissions and business process carbon credits, distributed "parcel" carbon quota information, distributed "parcel" best goal allocation, and distributed "parcel" best practices.
Further, reporting software associated with the storage server, distributed server, or processor set, the reporting software configured to generate reports related to at least one of ecosystem product and service information, "land" activity information, GHG emissions information, energy consumption information, carbon credit information, optimal goals, optimal solutions, is also included.
Further, the reporting software is associated with a client processor, wherein the client processor is configured to allow access, input, query, download and request of reports related to any of the emission information, the energy consumption information, the carbon credit information and the optimal target.
Further, the identification software is configured to calculate and track the business management compartment and attribute information associated with each of the at least two "plots," the method of calculating and tracking including AI big data linking, associating, obtaining, mining and registering associated calculation and identification means.
Further, the identification software is configured to calculate and track a set of forest resource section compositions and attribute information associated with each of the at least two forest sites/locations.
Further, the accounting software is configured to calculate, store and track artificial forest ecosystem product production, service supply and value dynamic information associated with each of the at least two "plots".
Further, the accounting software is configured to calculate and track artificial forest ecosystem product production, service supply, and value dynamic information associated with each of the at least two forest sites or locations.
Further, the forestry activity implementation footprint tracking software is configured to calculate, store, and track artificial forestry "parcel" activity and implementation footprint information associated with each of the at least two "parcels.
Further, the forestry activity implementation footprint tracking software is configured to calculate and track artificial forest "parcel" activity and implementation footprint information associated with each of the at least two forest sites or locations.
Further, the forestry activity energy consumption tracking software is configured to calculate, store, and track artificial forestry "parcel" activity energy consumption information associated with each of the at least two "parcels.
Further, the forestry activity energy consumption tracking software is configured to calculate and track artificial forest "land parcel" activity energy consumption information associated with each of the at least two forest sites or locations.
Further, the GHG tracking software is configured to calculate, store and track artificial forest "parcel" operational activity GHG emission information associated with each of the at least two "parcels".
Further, the GHG tracking software is configured to calculate and track artificial forest "land parcel" operational GHG emission information associated with each of the at least two forest sites or locations.
Further, the stand business process carbon credit tracking software is configured to calculate, store, and track "parcel" stand business process carbon credit information associated with each of the at least two "parcel.
Further, the stand business process carbon credit tracking software is configured to calculate and track "land" stand business process carbon credit information associated with each of the at least two forest sites or zones.
Further, the optimization software is configured to calculate and track optimal targets associated with each of a plurality of forest resources/assets/capital or products/services.
Further, the optimization software is configured to calculate and track optimal targets associated with each of the at least two "plots".
Further, the optimization software is configured to calculate and track optimal goals related to forest sites/locations.
Further, the auxiliary development software is configured to calculate and track an artificial forest ecosystem multidimensional "land parcel" activity best mode associated with each of a plurality of forest resources/assets/capital or products/services.
Further, the auxiliary development software is configured to calculate and track a multi-dimensional "plot" activity optimal implementation of the artificial forest ecosystem associated with each of the at least two "plots".
Further, the auxiliary development software is configured to calculate and track optimal implementations related to forest farms or locations.
Further, the ancillary design software is configured to calculate and track a value enhancement mechanism, ecosystem versatility, synergy, and ecological product value implementation for an artificial forest ecosystem "land" level activity value chain associated with each of a plurality of forest resources/assets/capital or products/services.
Further, the aided design software is configured to calculate and track a value-enhancing mechanism, ecosystem versatility, synergy, and ecological product value implementation of an artificial forest ecosystem "parcel" level activity value chain associated with each of the at least two "parcels".
Further, the aided design software is configured to calculate and track the value-enhancing mechanisms, ecosystem versatility, synergy and ecological product value implementations of the artificial forest ecosystem "land" level activity value chain in relation to the forest farm/zone.
A build forest activity energy consumption and GHG emissions tracking system for a forest farm based on an artificial forest executive/subtotal "land parcel" carbon account network, the system comprising:
(a) A storage server, distributed server, or processor set accessible through a computer or mobile device network;
(b) A forest resource compartment/capital value accounting database in communication with a storage server, distributed server, or processor set, the database configured to store artificial forest ecosystem "land" activity emission information associated with each of a plurality of forest resources/assets/capital or products/services, wherein the "land" activity emission information includes at least activity emission information of a seedling breeding stage, "land" artificial forest product production management stage, and a forest product manufacturing stage; the artificial forest ecological system 'land block' activity energy consumption information related to each of the at least two forest resources/assets/capital or products/services, wherein the 'land block' activity energy consumption information at least comprises activity energy consumption information of fine seed breeding propagation activity, artificial forest 'land block' forestation activity, forest product harvesting, transportation, processing, distribution and the like; carbon credit information of construction forest process activity implementation in the forest product 'land block' production stage, wherein the carbon credit information at least comprises financial carbon credit information;
Emission information associated with each of a plurality of assets of at least two plots; energy consumption information associated with each of a plurality of assets managed by the at least two affiliated stations, the energy consumption information including at least financial energy consumption information; the carbon credit information at least comprises financial carbon credit information;
(c) Cost calculation software associated with the storage server, distributed server, or processor set, the cost calculation software configured to calculate and track financial costs associated with each of a plurality of assets of the at least two sites based on the emission information, the energy consumption information, and the carbon credit information;
(d) Emission calculation software associated with the storage server, distributed server, or processor set, the emission calculation software configured to calculate and track emissions associated with each of the plurality of assets of the at least two sites;
(e) Reporting software associated with the storage server, distributed server, or processor set, the reporting software configured to generate a report related to at least one of the emissions information, the energy consumption information, the carbon credit information, and the financial cost.
(F) The database is configured to store (i) a forest resource section and attribute information associated with each of the at least two "plots"; a forest resource compartment composition and an attribute information set associated with each of the at least two forest sites/locations; (ii) Dynamic information of artificial forest ecosystem product production, service supply and value associated with each of the at least two "plots"; artificial forest ecosystem product production, service supply, and value dynamic information associated with each of the at least two forest sites/locations; (iii) The artificial forest "parcel" activity and implementation imprinting information associated with each of the at least two "parcel" areas; artificial forest "land" activity and implementation imprinting information associated with each of the at least two forest sites/locations; (iv) The artificial forest "land" activity energy consumption information associated with each of the at least two "lands"; artificial forest "land" movement energy consumption information associated with each of the at least two forest sites/locations; (v) Artificial forest "plots" operational GHG emission information associated with each of the at least two "plots"; artificial forest "land" operational GHG emission information associated with each of the at least two forest sites/locations; (vi) The "parcel" stand business process carbon credit information associated with each of the at least two "parcel; "land" stand business process carbon credit information associated with each of the at least two forest sites/locations; (vii) An optimal goal associated with each of a plurality of forest resources/assets/capital or products/services; an optimal target associated with each of the at least two "plots"; calculating and tracking optimal targets related to forest sites/locations; (viii) A multi-dimensional "plot" activity best mode of an artificial forest ecosystem associated with each of a plurality of forest resources/assets/capital or products/services; a multi-dimensional "plot" activity optimal implementation of the artificial forest ecosystem associated with each of the at least two "plots"; preferred embodiments related to forest sites/locations; (x) A value enhancement mechanism, ecosystem versatility, synergy, and ecological product value implementation for an artificial forest ecosystem "land" level activity value chain associated with each of a plurality of forest resources/assets/capital or products/services; a value-enhancing mechanism of an artificial forest ecosystem "land" level activity value chain, an ecosystem versatility, a synergy, and an ecological product value realization associated with each of the at least two "land" blocks; the value of the artificial forest ecological system 'land block' level activity value chain related to the forest farm/zone is improved by a mechanism, the multifunction of the ecological system, the synergy and the ecological product value are realized.
A network-based enterprise energy consumption and emission management system, the system comprising:
(a) A central processor accessible over a computer network;
(b) An asset database in communication with the central processor, the first database configured to store (i) emissions information associated with each of a plurality of assets of at least two sites, wherein the emissions information includes at least financial emissions information; (ii) Energy consumption information associated with each of the plurality of assets at the at least two locations, wherein the energy consumption information includes at least financial energy consumption information; (iii) Carbon credit information, wherein the carbon credit information at least comprises financial carbon credit information;
(c) Cost calculation software associated with the central processor, the cost calculation software configured to calculate and track financial costs associated with each of the plurality of assets of the at least two sites based on the emissions information, the energy consumption information, and the carbon credit information;
(d) Reporting software associated with the central processor, the reporting software configured to generate a report related to at least one of the emissions information, the energy consumption information, the carbon credit information, and the financial cost.
Further, the cost calculation software is configured to calculate and track financial costs associated with each of the at least two sites.
Further, the cost calculation software is configured to calculate and track financial costs associated with the enterprise.
A network-based forestry "parcel" energy consumption and emissions management system, the system comprising:
(a) A central processor accessible over a computer network;
(b) An asset database in communication with the central processor, configured to store asset database (i) emissions information associated with each of a plurality of assets of at least two sites, wherein the emissions information includes at least actual greenhouse gas emissions for each of the plurality of assets; (ii) Energy consumption information associated with each of a plurality of assets in the at least two locations, wherein the energy consumption information includes at least an actual energy consumption cost of each of the plurality of assets; (iii) Carbon credit information associated with each of a plurality of assets in the at least two locations, wherein the carbon credit information includes at least actual carbon credits accumulated by each of the plurality of assets;
(e) Alignment software associated with the central processor, the alignment software configured to: (i) Comparing and calculating the difference between the actual greenhouse gas emissions and the estimated greenhouse gas emissions; (ii) Comparing and calculating the difference between the actual energy consumption cost and the budget energy consumption cost; and (iii) the actual accumulated carbon credits and the budgeted carbon credits.
Further, reporting software associated with the central processor is also included, the reporting software configured to generate a report related to the at least one operational adjustment.
Further, a client processor in communication with the central processor is also included, wherein the client processor is configured to allow access, input, query, download and request of reports related to any of the emission information, the energy consumption information, the carbon credit information and the at least one operational adjustment.
Further, each of the plurality of assets includes an asset interface in communication with the client processor, the asset interface configured to control at least a portion of the asset.
Further, operational software associated with the central processor is also included, the operational software configured to adjust operation of at least one of the plurality of assets through the asset interface of the at least one of the plurality of assets based on the at least one operational adjustment.
A network-based enterprise carbon footprint tracking system, the system comprising:
(a) A central processor accessible over a computer network;
(b) A database in communication with the central processor, the database configured to store (i) manufacturing emission information related to at least one of a plurality of products, services, or assets; (ii) Packaging emissions information related to at least one of a plurality of products, services, or assets; (iii) Transportation emissions information related to at least one of a plurality of products, services, or assets;
(c) Carbon footprint calculation software associated with the central processor configured to calculate and track at least one of the plurality of products, services or assets based on manufacturing emissions information of the at least one of the products, services or assets, packaging emissions information of the at least one of the products, services or assets; and shipping emission information for at least one product, service, or asset.
Further, manufacturing emissions calculation software associated with the central processor is also included, the manufacturing emissions calculation software configured to calculate and track manufacturing emissions of at least one of the plurality of products, services, or assets.
Further, package emissions calculation software associated with the central processor is also included, the package emissions calculation software configured to calculate and track package emissions for at least one of the plurality of products, services, or assets.
Further, there is also included transportation emissions calculation software associated with the central processor, the transportation emissions calculation software configured to calculate and track transportation emissions of at least one of the plurality of products, services, or assets.
A GHG emissions management method comprising the steps of: step S1: establishing the precise tracking system for the movable imprinting of the artificial forest land block;
The method also comprises the following steps:
step S2: activity tracking: the 'land block' operation activity imprinting accurate tracking method specifically comprises the following steps:
(a) The 'land parcel' level forestry activities access a storage server, a distributed server or a processor set through an electronic device network, wherein the electronic device comprises a personal PC, a tablet, a portable APP terminal and a mobile phone;
(b) The database is configured to store manual forest 'land' division and attribute information, manual forest 'land' ecosystem product production and service supply information, manual forest 'land' movable energy consumption information, manual forest 'land' management activity GHG emission information and 'land' stand management process carbon credit information;
(c) The forestry activity implementation imprinting tracking software is configured to trace and register imprinting information of a manual forest 'land block' activity practice process;
Step S3: calculation and tracking of GHG emissions and carbon credits, comprising in particular the steps of:
(a) The GHG tracking software is configured to calculate and track GHG emission information of "land block" management activities of the artificial forest;
(b) The forestry activity energy consumption tracking software is configured to calculate and track forestry activity energy consumption information;
(c) The stand management process carbon credit tracking software is configured to calculate and track carbon credit information of the "land" stand management process;
step S4: management and optimization:
(a) The optimizing software is configured to be modifiable to calculate and track a multi-functional "parcel" level operation optimal target of the artificial forest ecosystem based on any one or more of the artificial forest "parcel" GHG emission information, "parcel" activity energy consumption information, and "parcel" stand operation process carbon credit information;
(b) The auxiliary development software is configured to calculate, track and AI auxiliary development of a multidimensional 'land block' activity optimal implementation of the artificial forest ecological system;
(c) The auxiliary design software is configured to calculate, link, weigh and AI auxiliary design a value lifting mechanism of an artificial forest ecosystem 'land block' level activity value chain, ecosystem versatility, synergy and ecological product value realization.
(D) Comparing and calculating the differences between actual and budgeted productivity and additional active energy consumption costs, land GHG emissions and carbon credits;
(e) At least one operational adjustment to at least one of the plurality of assets/capital or products/services is identified to reduce at least one of the difference between actual energy consumption costs, budgeted energy consumption costs, and GHG emissions, increasing carbon credits.
Compared with the prior art, the invention has the beneficial technical effects that:
1. The invention effectively monitors sustainable forest management and realizes more accurate information tracing of energy consumption and carbon emission cost of the forest industry. The existing emission databases are all secondhand data and cannot reflect intervention measures of the forest farm operators. The 'land block' data collected and uniformly managed by the system can better reflect the production and operation activities of the forest farm, and can reflect actions taken for improving the product inventory of the forest farm in the data, thereby realizing accurate regulation and control.
2. The invention improves the computing framework of the data collection effectiveness and efficiency in life cycle assessment. Life Cycle Assessment (LCA) is the main technology for assessing the influence of the whole life cycle of a product on the environment, and plays a decisive role in the field of environment management at present. This technique is highly data intensive and is virtually impossible without the use of a background unit procedure dataset provided by a lifecycle inventory (LCI) database. A typical product lifecycle contains thousands of unit processes, each of which needs to be described in terms of exchanging data. While the increased availability of LCI databases greatly reduces the effort involved in performing LCAs, the high costs associated with data collection still place significant limitations on the quality of LCAs. These limitations either take the form of uncertain or incomplete background data that must be collected and maintained with great effort, or are too general to represent for highly environment-dependent activities such as forestry construction forest implementation. The present invention improves the efficiency and effectiveness of LCA data collection by allowing automated, site-specific (zoned) generation and assessment of forestry unit process datasets from bassinets to gates, through a novel complementary solution based on a "land" carbon account network-supply chain-industry chain information system.
3. And the method provides possibility for space-accurate forest utilization LCA coupling evaluation and dynamic mapping. LCA is considered the best method for comprehensively evaluating the environmental impact of an activity, but it also has its limitations. The acquisition, manufacture, refining or processing of raw materials, the stage of use of the product under study, transportation and possible end use choices are all included in the life cycle analysis study from cradle to grave. But environmental impact caused by land management measures is often excluded from calculations such as raw material planting. This resulted in the omission of several categories of effects in LCA studies, such as effects on biodiversity and net productivity of soil. Moreover, the omission may lead to errors in calculation of GHG balance for forest utilization and biomass-intensive products or services, and to conclusions that are very different from the actual environmental impact of the activity under investigation. The Life Cycle Assessment (LCA) based on the 'plot' forestry activity imprinting accurate tracking database provided by the invention can accurately assess the environmental impact caused by specific forest land use.
4. Effectively reduces the production cost and improves the popularity of related standards. The 'block' carbon account network and the digital artificial forest ecosystem can be widely communicated with related GHG life cycle accounting information of forest management, forestry industry departments and carbon (C) accounting standards of other countries or regions in China, and provide an easy-to-use tool for forest managers and policy makers for checking the relative advantages (carbon credit income and project cost) of carbon offset projects and the life cycle GHG accounting of the forest departments.
5. The invention can be used to effectively evaluate how the application of innovative techniques affects the different functions of the whole value chain and how much this contributes to the sustainable management of the forestry production sector. These functions include germplasm selection, elite breeding, forest ecosystem monitoring, forest management (soil preparation, tree planting, tending, forest protection), forest harvesting, wood working (reconstruction), quality control, traceability, transportation, distribution, end use of wooden or non-wooden forest products (e.g. medical, energy, packaging, building materials, furniture, etc.), reuse and recycling, waste management, sales, etc. Such as those that allow genetic selection and modification of tree seeds to better accommodate the land and use thereof, or that automate the felling, seeding or fertilizing tasks. However, all of these have in common that a large amount of "land" production record data needs to be managed and it is possible to enrich the information with open data, thereby increasing the possibilities of analysis and evaluation, and thus making better decisions. Meteorological data published from the current forestry, industry and natural resources sector is from a remote sensing monitored map, including forest resource inventory NFI data from rural development, innovation and forestry policy sector. All these are an important basis, and can be combined with the artificial forest 'land parcel' activity data acquired by the system to improve the innovation of the industry.
6. The invention can be used for faster popularization of forestry technical measures capable of providing new products and services, reducing service cost and improving productivity, thereby adopting and popularizing rapid boosting innovative technology, leading a forest value chain and a labor market to generate great change, changing wood requirements, including increasing requirements on high-quality and diversified planting materials and creating requirements on new technical works (such as ecosystem detectors, unmanned aerial vehicle operators, digital ecosystem developers, information communication technology developers, operators and the like), and further creating more income and employment opportunities for forest departments and improving the digital level of forestry.
7. The invention can be used for reducing waste and improving the energy and resource utilization efficiency, thereby improving the profit capability of forest departments and being beneficial to sustainable management of natural forest resources. Accurate "parcel" activity tracking techniques may also limit or avoid collateral environmental damage to the ecosystem (e.g., disaster damage, pollution, destruction of non-target organisms or species). The innovation of the forest product management and production process can open up a new market for certain wood products (such as wood fibers, small-diameter wood or fast-growing tree species, forestry harvest residues and empty saplings), thereby helping to protect natural forests and original forests. The digital technology and system transformation based on the artificial forest 'land block' active carbon account is helpful to strengthen participation, transparency and accountability of forest management, thereby promoting sustainable management of natural resources.
8. The system and the method for accurately tracking the imprint of the forestry activity of the 'land block' and managing the GHG emission are key for effectively integrating the CO 2 removal (CDR) technology and the life cycle evaluation, and provide possibility for the industrial application of the forestry CDR technology and the 'carbon neutralization'.
9. The system and the method for accurately tracking the movable marks of the land parcels and managing the discharge of the GHG can track the accumulation process of production of products, services or assets and the consumption of movable cost in real time, and can be used for integrating the ecological system service of the artificial forest and the environmental influence of the production activity of the forestry to perform sustainable evaluation. The integration method for evaluating the environmental impact of the ecosystem service-production activity has the limitations of time consumption, data intensity, repeated calculation risk and complexity, and has the advantages of simplicity, straightness and rich information. To date, a sustainability evaluation method has not been developed that combines ecosystem service-production campaign environmental impact assessment, and the established artificial forest "land-block" campaign footprint accurate tracking and GHG emissions management system of the present invention can be used to conduct comprehensive sustainability evaluation of system service functions and production processes to identify and represent specific campaign process units that contribute to beneficial and adverse effects (footprints) to the results, to help explain impact results, and to support decisions.
Description of the drawings:
fig. 1 is a flowchart of a construction method of an artificial forest "land block" activity footprint accurate tracking and GHG emission management system provided by the invention.
FIG. 2 is a flow chart of the operation of the energy consumption, cost, emissions, carbon credit, carbon quota tracking and management system of the first embodiment.
Fig. 3 is a block activity tracking and management system configuration diagram according to the second embodiment.
FIG. 4 is a chart of various examples of information collected about asset energy consumption for example two.
FIG. 5 is a diagram of the information of the activities and carbon accounts of the land mass established in the second embodiment.
Fig. 6 is a flow chart of a method for tracking and managing record attributes and collection information for a block management "activity" system of embodiment three.
Fig. 7 is a flow chart of information collection and input into the tracking and management system according to the third embodiment.
FIG. 8 is a flow chart of a method of tracking and managing energy consumption in the field according to the fourth embodiment.
FIG. 9 is a flow chart of a method of processing and balancing a carbon liability bill and a carbon credit account for common resource usage for a fourth "demand response strategy" embodiment.
Fig. 10 is a schematic diagram of associating various types of land activity histories with usage equipment information to explain energy consumption and/or GHG emission trend.
FIG. 11 is a flowchart of a method for identifying a supply chain and entering a material or transmitting a service request according to a fifth embodiment.
Fig. 12 is a flowchart of a method of generating an emission report according to a sixth embodiment.
FIG. 13 is a flow chart of a method of tracking and managing carbon credits in accordance with the seventh embodiment.
Fig. 14 is a flowchart of an embodiment eight of generating an emission report.
FIG. 15 is a flow chart describing a method of tracking a production carbon footprint of a product, service, or asset of embodiment nine.
The specific embodiment is as follows:
The features of the present invention will be further illustrated by way of example only, and not by way of limitation, to the scope of the invention.
Embodiment one:
Referring to fig. 1, a flow chart describing the overall operation of the GHG emissions management method, method and system for managing energy consumption, cost, emissions and/or carbon credits for a forest farm for an artificial forest digital ecosystem. As shown in fig. 2, a forest farm to which the artificial forest digital ecosystem 10 is applied typically has a forest land size of several hundred thousand acres and a land utilization change of several decades, a forest product harvesting utilization, and a forest management tending history. The artificial forest digital ecosystem 10 generally includes (a) at least one type of business and at least one website that calculates and tracks business activity energy consumption (i.e., module 14 in fig. 2), (B) at least one type of business and at least one website that calculates and tracks asset/equipment maintenance costs (module 16), (C) at least one website that calculates and tracks at least one type of business for GHG emissions (module 18), (D) at least one website that calculates and tracks at least one type of business for an associated carbon emission credit (module 20).
The artificial forest digital ecosystem 10 may also include (E) performing a "checkup" process (block 22) that includes primarily metering the emissions footprint, confirming emissions compliance, and checking whether the carbon credit regime requirements are met in order to obtain certain credits, as will be described in further detail below. Or in an alternative application implementation example, the artificial forest digital ecosystem 10 may also (F) calculate and track total economic costs (block 24), i.e., provide total economic costs for at least one of at least one type of business activity based on energy consumption, maintenance costs, GHG emissions, and carbon credits of at least one type of business model. In another example implementation, the artificial forest digital ecosystem 10 may (G) calculate and track a total "real" cost (block 26), i.e., based on energy consumption, asset costs, GHG emissions, and carbon credits for at least one type of business activity, provide a total "real" cost (i.e., an economic, environmental, and even social cost that may include the present invention to describe the activity emissions in further detail) for calculating and tracking at least one type of business activity for at least one location.
In an alternative application example, the artificial forest digital ecosystem 10 may also allow (H) management or optimization of the economic or "real" costs of forest products (blocks 28 and 30), the present invention will be described in further detail in the detailed description; in addition, the artificial forest digital ecosystem 10 may also implement (I) management and/or help develop various land sustainable and stand elastic management policies (blocks 32 and 34), such as for one or more plaques, one or more branch sites, or an entire general forest farm enterprise, as will be described in further detail herein; in an alternative application embodiment, the artificial forest digital ecosystem 10 is used to (J) manage and/or assist in the design of various forest multi-function synergy modes and ecosystem product value implementation mechanisms (modules 36 and 38); in another alternative implementation, the computing and tracking functions described herein may also be used to track and calculate the energy consumption and GHG emissions required over the life of a forest product or service to (K) determine and/or track the "carbon footprint" of the product or service, as will be described in further detail herein. "carbon footprint" as used herein refers to any measure of GHG emissions associated with forest production operations, including, for example, but not limited to, one or more emissions generated during forestation operations, emissions generated during young forest topdressing operations, emissions generated during forest nurturing operations, emissions generated during timber harvesting operations, and/or emissions generated during woodland backup operations, emissions generated during other production operations, and emissions of production of consumable materials used to perform production operations, emissions of use of equipment to support performance of production operations, and the like.
Thus, the calculation and tracking of energy consumption, equipment costs, GHG emissions, and carbon credits for various embodiments described herein may be used in a variety of different ways to track and/or manage the operation of one or more forest products, one or more business cycles, one or more plots, one or more land utilization types, one or more forestation patterns, one or more types of production operations, one or more tending ways, one or more topdressing ways, one or more harvesting ways, one or more backup types, one or more production equipment, one or more areas, one or more division sites, or an entire forest farm enterprise, as will be explained in further detail below.
The activities or sites tracked by the various systems and methods described herein may be any type of asset, product, or parcel used by any entity interested in such tracking, computing, and/or managing as described herein. In one implementation example, the activity and the plurality of sites are devices and/or the plurality of sites of the product entity that utilize one of the systems or methods described herein to track or manage the financial and/or actual (economic, environmental, etc.) operating costs of forest assets at each plot, division site, and overall. A specific, non-limiting example is regional artificial forests, which can utilize one system implementation example described herein to calculate, track and manage the total financial cost and cost components of their production operations at each forest farm/division site, such as forestation, harvesting, tending, under-forest economy, topdressing, etc., as well as fleet vehicles and any other energy consumption, any GHG emissions, or activities that can be tracked and managed in other ways.
Further, non-limiting examples of specific energy consuming activities may include power consuming and/or fossil or hydrocarbon energy (e.g., natural gas or propane) burning devices used by the activity, or any other energy consuming or utility service utilizing devices described herein, including devices that consume, utilize or are powered by electricity. In one embodiment, the apparatus further comprises water. In addition, the devices may include any device that consumes or utilizes forest land facility construction (e.g., road repair) services, high-speed internet services, or any other forest management activity related device that consumes, utilizes or is powered by electronic or energy services.
Embodiment two:
FIG. 3 depicts a schematic diagram of a network-based system for calculating, tracking, and/or managing parameters such as energy consumption, greenhouse gas emissions, cost of ownership, and carbon credits for one or more plots, one or more activities, one or more sites, one or more regions, or an entire enterprise.
As shown in FIG. 3, the system 50 may include a server 52 in communication with a PC terminal 54 and/or a self-service terminal 56 via a network 58. The PC terminal 54 and/or the self-service terminal 56 may be located at one or more of a variety of distributed sites of a distributed forest farm-site, or may be located at other locations, such as a third party site. As used herein, a "PC terminal" refers to any known type of client processor or computer, also referred to as a site processor 54 or site computer 54. The system 50 allows a distributed enterprise to track and/or manage assets, energy consumption, emissions, plots, activity costs, equipment costs, and carbon credits at one or more sites.
The server 52 is in communication with at least one of an activity database 66, a forest resource compartment/capital value accounting database 64, a product/supply chain database 60, and a regulatory database 62. According to one implementation example, forest resource compartment/capital value accounting database 64 contains information about each parcel, such as parcel identification, description, base costs, historical maintenance and supply chain information, or any other type of information related to parcel operations. In addition, the forest resource compartment/capital value accounting database 64 also includes information related to energy consumption information, emission information, and carbon credit information for each plot. The product/supply chain database 60 contains various information about the supply chain. In addition, the regulatory database 62 contains information about various public resources or energy providers that provide public resources or energy to at least one site of the enterprise.
Or various embodiments of the system described herein may have separate databases for various different kinds of asset information, such as an energy consumption database, an emissions database, and a carbon credit database. In another alternative, asset/capital or parcel data, product/supply chain data, regulatory data, energy consumption data, emissions data, and carbon credit data are maintained in a single database.
The server or "parcel" activity practice concentration processor 52 (also referred to herein as a "parcel activity practice concentration processor") may be any computer known to those skilled in the art. In one implementation example, the "parcel" activity-practice centralized processor 52 comprises a website hosted in at least one or more computer servers. It is to be appreciated that any of the systems disclosed herein can have one or more such servers 52, and that each server can include a web server, a database server, and/or an application server, any of which can be operable on a variety of platforms.
The block activity practices central processing server or processors 52 include a storage server, a distributed server or processor set unit ("CPU") and main memory, input/output interfaces for communicating with various databases, files, programs, and networks (e.g., internet of things), and one or more storage devices. The storage device may be a cloud disk, a disk drive device, and/or a CD-ROM device. The parcel activity-practice centralized processor 52 may also have a monitor or other screen device and input device such as a keyboard, mouse, or touch-sensitive screen.
The block activity practices central processor 52 includes software programs or instructions running on a server side to process requests and responses from the client computers 54. These software programs or instructions send information to the client computer 54, perform computing, compiling, and storing functions, send instructions to the client computer 54, or to one or more devices, and generate reports. It should be appreciated that any example of an implementation of the disclosed system for providing data collection, storage, tracking and management may be controlled using software associated with the system. It will be further appreciated that the software used in the various embodiments described herein may be one or more software applications commercially available and commonly used by those skilled in the art, or may be one or more specific applications encoded in a standard programming language.
The software may be any known software for use with the system of the present invention to track, calculate and manage the various parameters of the present invention. For example, as described in further detail herein, various examples of implementations of the system of the present invention may have any one or more of software for tracking energy consumption, maintenance/equipment costs, greenhouse gas emissions, carbon credits, total economic costs, or total real costs (economic, environmental, or even social costs) of one or more products, business models, block business processes, or activity implementations, or software that allows for optimizing any of these parameters.
The block activity practices centralization processor 52 allows the client processor 54 to access various network resources. In one implementation example, the "parcel" active practice concentration processor 52 also has access to an external data source via the network 58 or some other communication link that may be used to maintain the information in the server in a current state. In one implementation, multiple site computers 54 may be connected to a server at any given time, so that multiple facilities or locations of an enterprise may utilize the system simultaneously.
In the system 50, asset/parcel status and activity data (e.g., energy consumption data, emissions data, or carbon credit data) entered into the system 50, typically through a client computer or processor 54 and/or asset/capital/facilities (equipment)/"parcel" activity interface 68, are received by the server 52 and stored in a forest resource compartment/capital value accounting database 64 and an activity database 66. Or it may be stored in any suitable database of the system.
The databases 60, 62, 64 are stored as inputs and information to the management and tracking system 50, which management and tracking system 50 processes the information as described below and generates any one or more of notifications, reports, work orders, predictive analytics, suggested actions, optimization strategies, and/or instructions to the management and business operations users or third party systems that are distributed to a particular parcel.
Databases 60, 62, 64, 66 may be of any type generally known in the art. Databases 60, 62, 64, 66 may be integral to "parcel" activity-practice centralized processor 52 or they may access "parcel" activity-practice centralized processor 52 via a computer network, internet of things, self-service terminal, APP, or other suitable communication link or tool. In one implementation, databases 60, 62, 64, 66 are comprised of a plurality of database servers, some of which are part of "parcel" active practice concentration processor 52 and some of which are remote "parcel" active practice concentration processor 52. Some non-limiting commercial examples of databases that may be used with the various embodiments of the present disclosure include ArcGISDB and similar databases of geographic information.
Forest resource compartment/capital value accounting database 64 includes general asset information associated with each asset in the system and value chain information for each asset, as well as natural capital and ecosystem product supply information for forests as a common resource. In the present invention, forest "assets" are meant to include any forest, land, equipment, facilities, forest or product supply and/or business model information that a forestry enterprise may be interested in tracking or managing. Asset information may include all production-related species information, product information, business scale information, site information, including site location, identification of assets in a site, and other related site information, for the forest farm owning the forest asset. Asset information may also include vendor information, germplasm resource information, and any other relevant information for each asset. If an asset is part of a system that is made up of multiple assets, the asset information may include system information including a system name, a system description, an identification of the asset in the system, a system status, and any other relevant information. The system status options may include, but are not limited to, for example, new forests, young forests, mature forests, intensive forests, mixed forests, continuous and/or supplemental forests, and the like. Ecosystem product status options for natural capital production may include both material and non-material products, wherein material product status options may include, but are not limited to, for example, wood, fruit, and the like; non-material product state options may include, but are not limited to, for example, carbon sink, water and soil conservation, and the like.
Forestry activity database 66 includes general business activity information associated with each parcel in the system and operational flow information for each activity. "forestry activities" refers to best practices management practices, i.e., planting, growing, harvesting, spraying, pruning, or felling removal, in accordance with commonly accepted forest practices and commercial or non-commercial objectives. "forest practice" refers to any activity performed on or directly related to a forest land, as well as any activity related to the planting, harvesting or processing of wood. "forest practice" includes, but is not limited to, construction of roads and walkways, final and medium term harvesting, pre-business intermediate harvesting, resaliming, fertilization, pest control, tree recovery, shrub control, and woodland harvest. The campaign information may also include material provider information, manufacturer information, alternate material and technology information, and any other relevant information for each campaign. The activity information for each parcel may also include parcel utilization system information including a system geographical location, a system name, a system description, an identification of assets in the system, a system status, and any other relevant information. The block activity system status options may include, but are not limited to, for example, staging, composite, and patch repair.
As described above, the forest resource partitioning/capital value accounting database according to one implementation example may also include energy consumption information, emission information, maintenance cost information, and carbon credit information for each plot. Or one or more of the energy consumption information, emission information, maintenance cost information, and carbon credit information may be stored in a separate database as described above.
The energy consumption information includes any energy consumption information related to a forest farm enterprise, a division, and any land block at any place where a spatial position is clear. Furthermore, energy consumption information varies according to the type or category of asset/capital. In one non-limiting implementation example, information collected for various types of assets/capital is shown in FIG. 3, according to one exemplary implementation example of the invention. As shown in FIG. 3, the exemplary asset attributes may be divided into three categories, namely, assets 70, forest resources 72, and "parcel" activity systems 74. The FIG. 3 implementation example further categorizes the asset 70 into an asset value 76, an environmental factor 78, and a risk monitor 80. As shown, the forest resources 72 are further divided into a forest type 82 and an operation type 84; the "land" activity system 74 is further divided into a forestation activity database 86, a topdressing database 88, a tending database 90, a lumber production database 92, a backlog database 94, other production project databases 96, and a disaster risk database 98. Fig. 4,5 further illustrate several exemplary, non-limiting information fields that may be collected for each type of activity.
Emission information includes any emission information related to any activity/equipment of a forest farm enterprise or a division site where GHG is emitted. Such information may include any information regarding emissions generated during the production of a product. In one example, the emissions information may include historical emissions data, including direct, indirect, and unorganized emissions data, field emissions data, and the like. Or the information may include any emission information of any kind. Emissions information may be organized in a forest resource compartment/capital value accounting database 64 (or some individual product, species category, or business category database) and/or a product/supply chain database 60, or may be retrieved from databases 64 and/or 60 based on land parcels, activities, locations, or any other desired parameters. That is, information may be stored or retrieved on a per site, per asset/product, or any other management category basis.
As used herein, "unorganized emissions" refers to any unintended, unplanned, and/or undesired emissions, for example, artificial biological emissions from equipment leakage, forestry processes (e.g., fertilizer, spoilage, fermentation, use of nitrogen fertilizer, etc.), pest control, forest fire protection, etc. For fugitive emissions data, the fugitive emissions data may include worksheet data, such as information related to maintenance of equipment that emits fugitive gases, which may be used to calculate fugitive emissions, such as emissions resulting from road repair, vehicle repair, etc. Any other type of leakage information related to the GHG of the present invention may constitute emission information.
Carbon credit information includes any carbon credit information related to any forest stand asset "parcel" of a forest farm enterprise or division site that emits GHG or otherwise has a carbon footprint. In one example, the "parcel" carbon credit information may include, but is not limited to, historical carbon credit data, or the information may include any carbon credit data of any kind. The carbon credit information may be organized in the forest resource compartment/capital value accounting database 64 and/or the product/supply chain database 60 and the activity database 66 (or another separate self-checking verification database) or may be retrieved from the databases 64, 60 and 66 based on forest assets, type of business, implementation location, plot, time period, or any other desired parameter. That is, information may be stored or retrieved on a per site, per asset/product, or any other basis.
If the asset is a man-made forest, the forestry activity database 66 includes forestation activity information, tending, fertilizing, reform harvest information, construction activity information, and the like. The construction activity information may include technical standards for the type of construction activity. For example, the asset may be eucalyptus artificial forests. Construction activity information may also include operating regulations established by the forest farm in accordance with national standards in combination with the actual forest farm. The protocol requires the vendor's service or material authentication type, dosage, method, type, operational procedures related to the performance of the activity, the work order (including the amount of fertilizer used) being performed on the system, or any equipment information attached to the system, such as a refrigerator or transport system, and any other relevant information. Some options for fertilizer quantity determination methods may include units, metering, manufacturer information, or suggested application ranges, etc.
In addition, database 64 may also contain any additional information known to be useful in asset/capital management.
The administrative database 62 includes information regarding the provision of various public service providers to at least one site of a forest farm enterprise. For example, the goods/services provider may include, but is not limited to, electricity, gas, water, high-speed internet services, and any other electronic or energy service provider. In one implementation, database 62 further includes a contact roster for each service provider, including a service technician for each service provider, according to one implementation. According to one aspect of the invention, database 62 further includes for each service provider a list of cost-related and service-related incentives or any other form provided by the service provider to the customer. For each incentive information, the specific conditions or events that must be met should also be noted and included in the corresponding records of the database.
The product/supply chain database 60 includes general service and/or maintenance provider information and certification information for each supply chain available to maintain an asset and for each maintenance provider available to provide maintenance for the asset. "service" as used herein is intended to encompass any type of repair, maintenance, or any other type of service that may be performed, applied, or otherwise provided on any type of asset. Further, as used herein, a "service provider" refers to any person or entity that provides some type of repair or maintenance or any other known type of service for any type of asset. Such information may include the name, description, address, telephone number, mobile telephone number, fax number, email address, user name and password for logging into the system, one or more technician names, contact information for each technician, and any other relevant information of the service and/or maintenance provider. The authentication information may include a qualification type, a certificate number, a validity period of the certificate, a status, and any other relevant information. According to one implementation example, the authentication information is associated with a technician.
In the implementation example shown in fig. 3, client PC 54 communicates with various processes of an activity through asset/capital/facility (equipment)/"parcel" activity interface 68. The asset/capital/facility (equipment)/"parcel" activity interface 68 may be configured to communicate with the equipment and provide a communication link between the equipment and the enterprise processor 54 or the "parcel" activity-concentration processor 52. In one implementation example, the various interfaces 68 are configured to accept input from direct or unorganized emissions activity records or sensors on various real-time networked device terminals in order to monitor the production process and emissions volume of each emissions source. In one exemplary implementation, the device interface of the emissions sensor is an interface with a continuous emissions monitoring system. Further, in another example implementation, the interface 68 is configured to accept input from one or more power consumptions on a PC or portable mobile recording device with which the interface 68 is associated.
The interface 68 is a local area network wired or wireless network. In one aspect, interface 68 includes software for receiving, converting, and normalizing signals and information received from various types of input devices.
The interface 68 associated with a particular asset/capital/facility (device)/"parcel" activity interface allows information, including distributed real-time information, to be collected directly from that asset/capital/facility (device)/"parcel" activity interface. Furthermore, information collected from the asset or equipment component may then be used in the present system in any of the ways described herein. In one example, the information collected by a particular asset/capital/facility (equipment)/"parcel" activity interface 68 may be used to calculate energy consumption, emissions information, or carbon credit status associated with an activity, asset, parcel, location, business, and supply chain, according to one implementation example. In a further example, the interface 68 may be coupled to a "parcel" activity system to collect various information about the "parcel" activity system, such as, for example, camping activity information, service information, energy consumption information, and/or emissions information (including unorganized emissions information).
As described above, any of the embodiments of the above system may be used to calculate, track and manage at least one of a cycle, a business model, a technology, an alternative model, a product, a class of activities, energy consumption at a site or business, cost, GHG emissions and carbon credits. For example, according to one implementation example, energy consumption of an activity, parcel, venue, or business may be tracked and managed, including identifying and implementing energy consumption parameters for optimal forest management practices. Similarly, in further exemplary implementation examples, one or both of GHG emissions and carbon credits may be tracked, managed, or optimized for a facility, venue, or enterprise. In further examples of implementations relating to the tracking and/or management of carbon credits, the system may also provide a verification process for verifying compliance with previously established emissions reduction objectives, including verification processes required by various carbon credit tracking regimes around the world.
According to other implementation examples, the system allows tracking (and in some implementation examples managing and/or optimizing) a turn-around period, a business model, a technology, an alternative model, a product, a class of activities, a plot, a site, or a total financial cost of an enterprise, wherein the total financial cost includes ownership and/or operational costs, all financial costs associated with GHG emissions, and all financial impacts of carbon credits. In a further example implementation related to tracking total financial costs, the system allows planning, tracking, and/or managing procurement items related to employing one or more activities, all activities of a site, or all activities of an enterprise. Furthermore, in other implementation examples, the system allows tracking of costs or "real" costs of all "parcel" activities of a particular "parcel" activity or enterprise, where these real costs may include all "parcel" production operations and/or forest asset costs, such as all energy consumption costs or environmental costs (including all GHG emissions, etc.), as well as all social costs, i.e., costs related to financial and environmental impact of the asset, venue, or enterprise. In addition, the tracking, management and/or optimization of the total cost can also be used for the items of material purchase, land acquisition and storage, carbon sink forestation, green financing and the like. According to a further alternative implementation example, the system allows tracking, managing and/or optimizing any of the parameters described above for one or more products or services.
According to various embodiments of the disclosed methods and systems, information about at least some forest assets, plots, or activity courses is collected and stored as an initial routine. Such collection or organization of existing information is an initial step in inputting information into various embodiments of the system described herein or capturing such information.
At least one forest asset (e.g., a forest of material) is reviewed and an asset identifier is created for each asset so that it has a trackable identification. This approach may provide a uniform naming convention such that each time the same asset is entered into the system, it may be identified by the same name or identification number. In another example implementation, a set of appropriate data fields is associated with each asset, where each field has a set of acceptable attributes. In this manner, certain information specific to certain types of assets may be collected, and according to certain implementation examples, only appropriate information may be entered into the system.
Once the identifier and data fields are created for each activity, information related to each asset may be collected. That is, certain characteristics or information of each trackable asset may be associated with an identifier. According to one implementation example, the process of collecting and storing information related to assets located at a plot or site is implemented using or in conjunction with a method or system for measuring assets/devices or activities located at a plot, site, or multiple distributed sites.
Embodiment III:
FIG. 6 is a flow chart showing one example of an implementation of a forest asset management activity method 100, the method 100 including collecting and compiling historical forest data for forest farm "land parcel" activities (102), creating an appropriate geospatial and attribute data structure (104) for collecting and storing activity information, entering or importing the normalized historical data into a data structure (106), importing the historical record data of "land parcel" activities and the data structure into a mobile survey device (108), and surveying the site "land parcel" assets to collect relevant information (110). In one implementation example, quality control reviews (112) are performed on the collected survey data.
Regardless of whether a survey method is used, FIG. 7 is a flow chart of an exemplary implementation example of a process of collecting and inputting asset/facility/parcel/activity data 120 according to some implementation examples. As shown in FIG. 7, in some examples of implementation, a user identifies an asset/activity for which information is to be collected (122). In addition, there is no need to identify assets/activities because information is collected at one location for all assets/activities. In some implementations, information corresponding to the identified asset/facility (device)/parcel/activity is collected based on the identified asset/facility (device)/parcel/activity type (124). After asset/activity information is collected, the information is entered into the system and associated with the corresponding asset/facility (device)/parcel/activity (126). In one implementation example, asset/facility (equipment)/parcel/activity information is collected and/or entered into the system periodically.
As described above, with respect to various databases that may be incorporated into various implementation examples of the system, various types of activity process information may be collected and entered into or stored in the system. The information to be collected may depend on the type of material and traffic used during the business activity or the type of forest, the age of the stand, the geographical location in which it is located, the topography, the location or the type of plot. Thus, forest ecosystem asset/activity information may include energy consumption information for each asset/activity, acquisition or maintenance cost information for each asset, GHG emissions information for each asset, and/or carbon credit information for each asset. The information may also be organized on a per forest basis, a per asset basis, a per ground class basis, a per plot basis, a per site basis, a per area basis, a per business basis, or any other logical basis. For example, organizing information on a per site basis allows for consideration of all asset inventory/product supply information on a site and processing that information for purposes described herein. In addition, as described herein, per forest asset, and per ecosystem product value basis, per function basis, per structural composition model basis, per enterprise product supply chain, value chain, or per regional basis organization information may also be incorporated into the system database.
Any of the system implementation examples described herein may be used in an energy management method such as calculating, tracking, and/or managing energy consumption of one or more assets. One exemplary implementation example includes first collecting relevant information related to each energy asset, and then periodically collecting actual energy consumption data for each asset. Using this regularly collected information, the actual energy consumption of each asset can be tracked over time and utilized by the various embodiments of the system described herein to manage the energy consumption of forest assets on each plot, a site, a region, or an entire forest farm enterprise.
The energy consumption information is collected and recorded manually at regular intervals. Or energy sensors or probes are used to collect energy consumption information in real time or in close proximity. For example, these energy sensors may be internet of things devices that need only be connected to the communication network (wired or wireless network) of the site. These network devices then read and send real-time energy consumption data to the network for use in the system for any of the types of tracking, management or optimization discussed herein. In one implementation example, such sensors communicate with the system through a parcel asset/facility/parcel activity interface 68 shown in fig. 3.
Embodiment four:
The present invention contemplates a system having software that can use energy consumption data to track and manage unexpected energy consumption 130. That is, as shown in fig. 8, the system calculates an expected energy consumption curve (134) from the collected facility (equipment) information (132) in addition to collecting information related to the facility (equipment) (132) and collecting actual consumption data (136). The system software then controls the comparison of the actual energy consumption data with the expected energy consumption profile (138). If the actual consumption data exceeds the expected consumption budget and trajectory of the active execution process, the software can immediately instruct the system to take some action to handle the unexpected consumption (140), such as triggering an alarm, generating a report, or sending an instruction to the device or program experiencing the unexpected consumption.
According to certain example implementations for tracking energy consumption, the systems and methods may provide systems and methods for processing bills of one or more public resource usage accounts, where the bills may also provide asset (natural capital) and parcel (ecosystem production) information that may be used to calculate public energy consumption or environmental costs. For example, FIG. 9 depicts one method of processing the public resource usage bill 150 in the following manner. Various system implementation examples described herein allow for the entry and storage of supply and billing information for each site of each public resource provider (152) in a public resource usage responsibility supervision database, such as the supervision database 62 shown in fig. 3. The system of this implementation example further provides for reviewing and approving each bill received from each common resource provider at each site (154). In addition, the system provides for payment of each bill (156) from each public resource provider. According to one implementation example, payment to the provider may be completed using an account of the electronic payment system (e.g., a carbon account).
The bill review and approval process (154) for each account also includes identifying a cost-effective package or cost quote component associated with the bill for each account being reviewed. For example, a server (such as the server or "block" active practice concentration processor 52 shown in FIG. 3) may access a public resource usage supervision database (such as database 62 shown in FIG. 3) to identify any cost-effective packages or cost quote components from the public resource provider that sent the bill under review. The server or "block" active practice concentration processor may then compare the policy combination or offer to the current bill to determine whether the bill meets the conditions of a discount, rebate, or other cost-effective offer. Or the server identifies and transmits the relevant saving package or offer to the user so that the user can determine whether the bill meets the package or offer conditions. If the bill meets the condition, the cost-saving package or cost quotation composition is automatically applied to the bill total, thereby reducing the amount owed; or the user applies a coupon or package to the bill.
Examples of cost-effective packages include the implementation or occurrence of the "consumer energy consumption plan" (2018-2020, national commission for improvement) or "demand response policy mechanism" currently provided by various public resources, energy departments and/or transportation and electric utility companies throughout china, as used herein, refers to any plan where public resources or fuel, electric power suppliers provide green low-carbon consumption incentives for reducing energy consumption or impose accounting-or financial-based restrictions on consumption during peak demand. In one exemplary implementation where the demand response program is an incentive-based program, a common resource, fuel or electricity provider provides discounts or other types of economic incentives to any customer/location/business during the peak demand period, thereby reducing its energy consumption by some predetermined amount during that period. In another example implementation where the demand response program is a necessary restriction program, if the customer/site/business does not reduce its energy consumption by some predetermined amount during the peak of demand, the public resource or power provider assesses a fine or other type of cost to the customer/site/business during this period.
In one demand response example, a utility company, fuel or electricity provider sends alerts or notifications related to incentives or consumption limits during demand peaks. In one implementation, a common resource or power provider is coupled to an implementation of the system described herein through a network such that the common resource or power provider can transmit electronic alerts or notifications directly to the system. In this implementation example, electronic alerts or notifications are received on a server or "parcel" active practice concentration processor 52 and are processed by software configured to receive and process such alerts or notifications. Or to send an alert or notification to the enterprise system user. For example, the alert or notification may be sent via email, telephone, text message, or any other form of communication. In this implementation example, the user then enters the demand response information into the system, via the client PC or portable mobile device, which the software receives and processes. Regardless of whether the alert or notification is received by the system or by a user, the system according to one implementation example has software configured to process the information to identify any assets, devices, sites, or sites that meet the incentive or constraint. The same software, or a different software package, is further configured to provide notification to an appropriate person regarding assets or places meeting incentive or constraints so that the person can decide whether and how to reduce consumption, or to provide notification or suggestion alternatives including recommended implementations (e.g., recommended methods of reducing consumption) that meet incentive/reduction parameters. Or software configured to provide instructions to each activity or site through an asset/device/activity interface (interface 68 as discussed above) may be provided to reduce the appropriate amount of consumption. For example, consumption may be reduced by reducing the output of various scheduled events over a particular period of time (e.g., forestation using self-bred seedlings in one site to reduce the cost of transportation for off-site transportation) or simply reducing the number of cuts over a particular period of time. In another example implementation, the system software may also provide a device that sets the implementation level based on demand-response events, appropriately reduces energy power usage, or is powered using clean green energy.
The system may also provide for settlement, where "settlement" is defined as the comparison and verification of the contracted consumption reduction with the actual reduction. That is, if the demand response event requires the customer/site to voluntarily or promise to reduce consumption, and further requires verification that the customer/site has achieved an agreed reduction consumption, some examples of implementation of the system may include software that compares the agreed reduction consumption with the actual reduction consumption and communicates this information to the user, to a public resource provider, or both, and with reference to a Chinese government purchasing demand management approach, requires the purchaser to reasonably determine demand, strengthens management of purchasing plans and performance, and establishes a government purchasing full flow management mechanism from planning, execution to information release.
In-cycle environment cost pricing may also be utilized by various implementation examples of the present systems and methods. That is, public resources and energy suppliers may change the price of their products (public resources or energy) on an hourly or even every minute basis in the future. Various embodiments of the system of the present invention have the ability to capture and utilize such in-cycle environmental cost pricing to track and manage energy consumption and price in real time.
For example, the system provides real-time information about public resources or energy pricing, and can utilize this information to manage energy consumption as described herein. In this implementation example, as described above, the system server (e.g., the server or "block" active practice concentration processor 52 shown in FIG. 3) has access to external data sources or data sources such as public resources and energy suppliers or other systems of the system through a network or some other communication link. Or the public resource and/or energy provider may have a client computer (client PC shown in fig. 3) in its central location. Thus, space-time environmental cost pricing information is communicated to any system implementation example contemplated by the present invention, either through communication with an external data source or system, or through a client computer, and energy consumption software provided on the system can track these prices, calculate price changes for each affected asset, each affected site, and/or for the entire enterprise, and perform appropriate actions, reducing the impact of environmental cost pricing changes, as described herein.
Various system implementation examples described herein provide a method of calculating the total cost of forest assets/capital/equipment (facilities)/camping activities. That is, the system has software to calculate the total forest assets and forest product production costs for a class of activities, a lot, a piece of equipment (facility), a site, a region, or an entire forest farm enterprise. In one implementation, the software calculates the total economic and environmental costs of an activity, block, facility (facility), site, region, or forest farm enterprise using at least the cost of implementation of the activity, the cost of purchase, transportation, and storage associated with the material, the cost of energy consumption for engineering construction or equipment purchase or maintenance associated with the facility, and the like. Or the software may calculate the total cost of the forest asset, activity, land mass, equipment (facility), location, area or farm enterprise based on any additional parameters that make up the total cost, including, for example, any carbon credits accumulated by the forest asset, land mass, location, area or farm enterprise.
The various systems and methods described herein in connection with the tracking and management of energy consumption further provide for data analysis, including data correlation, decision-making, prediction, and cascade analysis. According to one embodiment, these systems include software that can utilize information stored, absorbed, or used by the system to identify correlations with other information and use these correlations to predict trends. The software may then take appropriate action on the various assets in the form of instructions based on the predicted trend, or the enterprise or user may take appropriate action based on the predicted trend.
Information that may be used for correlation analysis includes energy management information, warehouse depletion information, public resource usage billing information, service information (including maintenance information, total cost information, current and historical weather for the relevant area, precipitation and temperature data, market demand for public resource services, and current rates (unit costs) for public resource services, as described above). In one aspect of the invention, the current and historical weather and temperature data, market demand for common resource services, current rates for common resource services, and any other similar or related data may be included in a database in the system or in a separate database, or may be accessed by the system from another source, such as an external database accessed through a network, magnetic disk, optical disk, or any other data source. According to one implementation example, the public resource billing information is related to service information, herbicide usage, pesticide/herbicide usage, energy usage, total cost information, weather/precipitation/temperature information, public resource service market demand, and current public resource service rates. That is, certain events, details, or trends in the billing information are associated with any other information. Or any of the above information may be associated with any of the other information described above. According to one implementation example, this allows a user or system to correlate changes in a set of parameters, such as billing information, to other parameters as described above. Thus, the relationship between various types of information can be identified.
According to another embodiment, the system also provides predictive analysis and planning based on the above-described correlation data. That is, the system includes software that uses the data correlations described above to predict future trends in the data. The enterprise or user may then take appropriate steps to address any predictive impact of the trend using the predicted trend and the information described above. According to one exemplary implementation example, the predicted weather patterns may be used to predict trends in energy usage and public resource billing and possibly carbon credits. For example, a particularly cold winter or long summer Wen Shaoyu may have been predicted. The system can compare predicted correlations of these extreme climates with past correlations and/or public resource cost bills generated by transportation, storage, etc. with calculated correlations between similar extreme climates versus forestry production management processes. Based on this correlation, the system can predict the impact of extreme weather occurrence periods on the common resource bill and possibly the carbon credit scale of an extreme weather effect of a plot/site or group of plots/sites.
Where each parcel/site has been mapped to a GIS enabled application system. The system can compare predicted extreme weather phenomenon occurrence paths, intensities and scales with the site locations of the plots where the areas are located through map-based interfaces and determine sites/branches/farm enterprise sites of plots that are expected to be directly affected by possible public resource disruptions. The system may further notify one or more users of the possible interruption.
The predicted wind speed, precipitation, temperature peaks and durations across a particular area may be used to predict the expected energy demands (and thus the expected public resource bill and possible carbon credits) associated with traffic, storage, etc.
Other factors related to the predicted weather, precipitation, or temperature event may be considered, such as current market demand and common resource rates in each example. Thus, in this example, competitive demand and rate billing and possibly carbon credit trends may also be considered in formulating an expected market supply-demand and expected rate response for weather, extreme weather, or season-related events or periods.
The precautions are implemented by the system. That is, various examples of implementations of the system allow for data and predictive analysis, including predicting certain trends associated with certain assets or devices, and upon triggering certain events associated with those predictions, electronically communicating or transmitting operational instructions to the associated devices via "land" assets (natural capital and ecosystem)/devices/activity interfaces (such as interface 68 shown in FIG. 3) associated with the devices. Thus, the "land" asset (natural capital and ecosystem)/equipment/activity interface function may be used in conjunction with the data and predictive analysis functions described above to provide precautions or countermeasures against the effects of predictive trends.
In one implementation example, the "parcel" activity interface capability may remotely control the operating parameters of certain energy sources or energy-related systems of a "parcel" in accordance with various system implementation examples described herein to accomplish measures aimed at preventing or reducing any negative impact of the predictive phenomena described above. Thus, various systems allow tracking of various parameters associated with a device at a site or sites, performing data and predictive analysis, and upon triggering of certain events or predicted events associated with those parameters, electronically communicating or transmitting operational instructions to a responsive management terminal device. According to one implementation example, the types of devices that may be remotely controlled in this manner include, but are not limited to, energy sources, transportation, warehousing equipment, and systems.
The system 100 further tracks and manages the loss of fires, insect disasters, geological disasters, extreme climate disasters of forest assets containing a risk land parcel.
Fifth embodiment:
Furthermore, various embodiments of the system of the present invention may also correlate historical operational activity, extreme climate data, and wood quality loss carbon leakage data to account for energy consumption and/or GHG emission trends.
Fig. 10 is a schematic diagram of a database structure 160 that correlates various types of energy consumption and pesticide/herbicide-use equipment information. The database structure 160 is useful in correlating energy consumption data with pesticide/herbicide loss data to account for energy consumption trends. As shown in fig. 10, database structure 160 includes forest farm history work order data 162, specific "land" data 164, customer or enterprise specific data 166, general "public" data 168. The illustrated structure 160 allows for various device categories and attributes to be configured by a particular forest farm enterprise. The worksheet data 162 includes information related to on-site refrigeration circuit repairs for calculating wood quality loss carbon leakage 170.
The structure 160 allows a user to correlate changes in energy consumption and/or GHG emissions 172 with carbon leakage. This allows the user or system to explain the reasons for unexpected energy consumption and/or peak GHG emissions over a specific period of time. This may be achieved, for example, by comparing the energy consumption and/or GHG emissions over a specified period of time with historical operational activity, extreme climate data and wood quality loss data over the same period of time. If a piece of equipment is operated with low levels of wood quality loss carbon leakage, this may account for peaks in energy consumption and/or GHG emissions during that time. Using information related to "plots" and/or GHG emissions, fires, insect disasters, geological disasters, loss of extreme climatic disasters, equipment, and actual energy consumption data collected, a user of the method or system may compare the consumption information with public resource bills to identify potential accounting errors. Also, the user can analyze the leakage information and identify land block risks requiring important protection, improve management measures, and update potential equipment technical investment.
Various examples of implementations of the disclosed systems and methods also provide for tracking and managing any asset services or maintenance requirements. One exemplary implementation example of the system provides a method of repairing and maintaining assets by a supply chain (including third party providers or internal personnel). As shown in FIG. 11, the method 180 generally includes generating a product or service request (at a client computer, portable mobile device, asset interface, or other connection device with the system) (182), receiving the service request at a storage server, distributed server, or processor set (184), automatically identifying an appropriate supply chain in a product/supply chain database using software (186), automatically sending the service request to the supply chain, and any other asset information that may be needed by the service provider (188). In one implementation example, if no response is received within a predetermined period of time, the request is retransmitted (190). Any method of tracking and managing forest asset services and/or maintenance may be used in the system described herein.
Example six:
The "block" business system may track GHG emissions of an asset, site, area, or business. FIG. 12 is a flow chart describing the overall operation of the method and system of tracking emissions 200 according to one implementation example. The system generally includes collecting "parcel" activity data and/or inputting data into the system related to an asset as an emissions source (202), calculating a total amount of emissions (204), and according to some alternative implementation examples, generating a user requested emissions report from stored emissions data (206). The system 200 may track emissions of each emission source of interest. In one implementation example, the system 200 tracks emissions for each source at a particular location. Or the system 200 tracks emissions from each emission source for each activity of the enterprise, each site. According to another aspect, the system 200 may generate a report detailing the amount of emissions produced by one or a group of emissions sources, particularly the amount of GHG produced by each emission source, more particularly the amount of CO 2 and CO 2 equivalents (CO 2 eq) produced.
Any such system tracks all types of emissions from various emissions sources. For example, in one implementation, emissions may include emissions from direct and indirect emission sources. Thus, in one implementation example, the system tracks emissions from direct and indirect sources. Or the system may track emissions from direct emissions sources only or from indirect emissions sources only.
Direct emissions sources refer to emissions sources owned or controlled by the enterprise. In general, direct emission sources include four types: a mobile combustion source, a stationary combustion source, a manufacturing process source, and an unorganized emissions source. For example, a refrigeration/heater for vehicle transportation or storage would be a direct source of emissions. In contrast, indirect emissions sources include emissions sources that produce emissions in whole or in part due to business activity and are owned or controlled by another entity. Indirect emissions sources include, for example, any energy source input from a third party or other GHG emissions source, such as input power, which may also be referred to as a "utility" in the present invention. The input power may include, but is not limited to, any power input from one or more home power companies or other power providers.
Direct emissions sources, mobile combustion sources refer to non-stationary assets that an enterprise produces emissions by burning fuel, including automobiles, motorcycles, trucks, forklifts, boats, aircraft, construction equipment, diesel generators (e.g., backup diesel generators), and the like. A stationary combustion source refers to a stationary asset that an enterprise generates emissions through fuel consumption, including refineries, furnaces, heaters, and the like. Manufacturing process sources include enterprise manufacturing or industrial processes that result in emissions. These sources may include, for example, the manufacture of aluminum, iron, steel, pesticides/herbicides, ammonia, acids, and lime. An unorganized emissions source includes assets of an enterprise that cause emissions to be released by way of unintended release or leakage, such as is common in air conditioning and refrigeration equipment.
While specific examples of emissions sources for each emission type and subtype have been provided, the methods and systems discussed herein contemplate tracking any type of emissions from any emission source. The information collected for the emissions sources may vary depending on the type or class of emissions source. For example, emissions sources can be divided into two categories: direct discharge and indirect discharge (as described above). Or the direct emissions sources may be further divided into four sub-categories according to the four sub-categories described above. The type of information collected and the fields in which the information may be collected may vary depending on the category and/or sub-category of the source. For example, the emissions source information may include any emissions source identification information such as an emissions source identifier and a type and/or subtype of emissions source. Further, the active emissions source information may include any historical emissions data (also referred to herein as "legacy" data) for the source. In addition, the information may include site information related to all sites of the enterprise's active emissions sources, including site location, identification of site emissions sources, and any other relevant site information. If the emissions source is part of a system or group of more than one emissions source, in some examples of implementation, the emissions source information may include group information, including a group name, a description of the group, an identification of the emissions source in the group, and any other relevant information. For example, a group may include all emission sources located at a particular site location. In addition, for example, a group may include all emissions sources of an enterprise.
One general method of collecting indirect or direct emissions includes collecting usage information. In the case of indirect emission sources of public resources, etc., the public resource provider provides an enterprise with invoices relating to the enterprise or public resource usage at a particular location of the enterprise. Thus, the collection of usage information associated with the indirect emission source includes collecting invoice information. According to one implementation example, invoice information is collected by simply receiving a hard copy of the invoice. In addition, invoice information is collected in electronic format by email or other form of electronic communication (including on a website). In one example, the information of interest includes total utility usage. Or may collect usage information through an interface similar to interface 68 described above with respect to fig. 3. In this implementation example, the interface is coupled to an electric energy meter (e.g., an electricity meter or a gas meter) to collect all usage information based on the electric energy meter.
For a direct emissions source, according to one implementation example, active emissions source information may include the total usage of the source during a given period. Thus, collecting information of the direct emission source may also include collecting usage information. For example, the direct emissions source may be a mobile combustion unit, such as a vehicle, and the source information of interest may include the total fuel usage during that time. In one aspect, usage information is collected by manually collecting all fuel invoices related to the source. In addition, fuel invoice information is collected in electronic format via email or other form of electronic communication (including on a website).
In one aspect of the disclosed systems and methods, any invoice or billing information may be managed and entered or processed by a method or system similar to or in cooperation with any of the energy management methods or systems described above.
An example of a method of processing a bill or invoice is shown in fig. 9 as described above. In another example of implementation, billing information for entry and storage may include, but is not limited to, all information provided in each periodic bill or invoice associated with any emissions source, such as fuel bill associated with a direct emissions source or bill from a common resource provider. For example, the billing information may include all fuel billing or other invoice information for any of the enterprise sites related to the operation of one or more direct emissions sources, and/or all invoice information for any of the enterprise sites separately provided by one or more gas suppliers, power suppliers, or any other common resource or energy supplier that causes greenhouse gas emissions. In one implementation example, billing or invoice information is manually entered by a user (e.g., an employee of an enterprise or an employee of a public resource provider) at a client computer or portable mobile terminal, cell phone APP, or other entry point.
Or information is entered electronically. For example, electronic input may be accomplished by scanning a document using a cell phone photograph or any known scanning technique and loading the acquired record information into the system. In another example, information is entered electronically through direct electronic communication between the billing system of an on-network invoice provider and the system of the invention, which is similar to the network described in FIG. 3. In another alternative, the billing information is compiled electronically by an external individual or person, for example, by engaging a third party entity to compile the billing information into a format that can be easily loaded into the system, and then loading the billing information into the system. According to one implementation example, a third party individual compiles historical billing information into an appropriate format for loading into the system. Or a third party individual compiles current billing information on a continuous basis for loading into the system. In another alternative, both the historical and current billing information is compiled into the appropriate format by a third party individual, business employee, or agent.
The bill information collection described in the above paragraphs may also be used to collect bills for energy consumption tracking and management. For the purposes of direct and indirect emissions tracking, in addition to the usage information and any other information related to the amount of emissions generated by the emissions source, the user may also input any other related information including, but not limited to, the site at which the emissions source is located, the group (if any) to which the emissions source is affiliated, and the date on which the information was collected.
The indirect emission source is electricity. In another implementation example, the indirect emission source may be input steam, input heating, input cooling, or any other input energy source that results in any GHG emission. In one implementation example, the collected information includes total energy consumption of the source. For example, if the indirect emission source is electricity, the information to be collected may include the total power usage in kilowatt-hours over a period of time. As described above, this information may be collected or calculated from the power rate invoice. In another example, the indirect discharge source is input steam, heating or cooling. In this example, the information to be collected may include, but is not limited to, total steam, heating or cooling consumption in any suitable unit of measure for a certain period of time.
The direct emission source is a mobile combustion source. In another example implementation, the direct emissions source may be a stationary combustion source, a power plant, a manufacturing plant, or any other type of plant, asset, or equipment used at an enterprise site where any kind of GHG is emitted. In one implementation example, the collected information includes total energy consumption of the source. For example, if the direct-discharge source is a mobile combustion source, the information to be collected may include any or all of the make and model of the source, the type of fuel consumed by the source, the total fuel consumed by the source, and the distance traveled by the source. As described above, such information may be collected or calculated from any or all of the fuel invoice, fuel purchase records, odometer readings, travel inventory, and/or maintenance records. In another example, the direct emissions source is a cogeneration plant as described above, and the collected emissions source information may include fuel input, electricity production, net heat production, and/or plant efficiency. In another example, the direct-emission source is a fixed combustion source, and the collected source information may include the type of fuel consumed by the source and the total fuel consumption of the source. According to one implementation example, this information may also be obtained from a hydroelectric bill.
The direct emissions source is a manufacturing process emissions source and the source information that may be collected includes the total emissions of any measurable gas of interest expressed in any suitable unit of measurement, including, for example, those gases and units of measurement specified in environmental regulations and government legislation.
The time of emission information collection and the number of collections may vary significantly. That is, the collection may be performed daily, weekly, monthly, yearly, or at any other known interval. Or the collection may be performed randomly. The number of data points collected can vary significantly. That is, for a wide range of emissions source categories, the emissions information can only be based on one invoice in one implementation example. Or the information may be based on an invoice for a sub-category of emissions sources. In another alternative, each emission source is monitored individually by a user or a dedicated interface or sensor.
Fugitive emissions may also be tracked. The fugitive emission source may be any of any plot, asset, facility, or equipment that leaks any GHG. In one example, the unorganized emissions source is a refrigeration appliance, and the collectable source information includes the type of appliance, actual and/or calculated leak rate, and/or the quantity and type of pesticide/herbicide used.
For direct or indirect emissions tracking, emissions source information will be entered into the system. In one implementation, the information is entered manually by the user. For example, the user may use a client computer to enter information in the hardcopy invoice into the system, or the information may be entered automatically into the system. For example, the information is provided in an electronic format and is automatically loaded into the system upon receipt or retrieval from an invoice provider.
In alternative implementations, any emissions source information may be input into the system through a device interface similar to the interface discussed above with respect to FIG. 3. The device interface allows the system to automatically track information related to emissions generated by a particular emissions source without requiring any manual input or effort by the user. For example, a stationary combustion source, such as a stack, may be equipped with a device interface that continuously measures the amount of emissions produced by the source, and with a communication link between the source and a storage server, distributed server, or processor set. Any information received by the storage server, distributed server, or processor set from the device interface may then be stored in the database.
The system saves all the information collected into a forest resource compartment/capital value accounting database (or emissions database), for example similar to the database discussed above with respect to fig. 3, so that the system accumulates all the information about emissions generated by each asset.
Returning to FIG. 12, some examples of implementations of a method of tracking active emissions include calculating emissions produced by one or more emissions sources (204). That is, the amount of emissions produced, particularly GHG emissions, and more particularly the amount of CO 2 and CO 2 eq produced by a particular source or group of sources, may be calculated over any desired period of time. In some examples of implementation, the system calculates emissions generated throughout the venue and/or throughout the enterprise. In other examples of implementation, the system automatically performs the calculation and/or reporting of the total active emissions at repeated predetermined intervals (e.g., monthly or yearly).
In one aspect, in the system, the emission amount is calculated by inputting emission information stored in a database and an emission factor corresponding to a source that calculates the emission production amount into an appropriate equation. Reference standards include enterprise carbon footprint verification (ISO 14064), product carbon footprint verification (ISO 14067), lifecycle assessment verification according to ISO 14040 and 14044, and national, industry and local standards. For the purposes of the present application, an "emission factor" is a representative value that relates the amount of emissions emitted to the atmosphere to the activity associated with emission release. These factors are expressed as the weight of the discharge (typically kgCO 2 divided by the unit weight, volume, distance, or duration of activity that produces the discharge). The emission factors may be obtained by various government agencies, databases, or literature, such as the china regional power grid CO 2 emission factor study (2023) and the china product lifecycle greenhouse gas emission coefficient database (CPCD). Because of emissions factor fluctuations, in some implementation examples, they are updated periodically.
An example of an emissions factor is a factor related to an indirect emissions source, such as an emissions source provided by a common resource company. This factor is assigned to an energy provider or public resource company that is affected by the source of the energy source based on the amount of emissions generated by that provider or public resource company. For example, a power provider that uses entirely coal-fired power plants to generate electricity will produce more emissions than a provider that uses entirely windmill electricity, and thus the factors assigned to each provider will reflect the differences in emissions. Thus, the emission factor should be included in any calculation related to the indirect emission source.
In another example of an emission factor, if the emission source is a cogeneration plant or system used by a third party energy source or a utility resource provider (and thus an indirect emission source), one notable emission factor relates to the amount of emission of energy obtained by a computing enterprise from a third party provider using such a cogeneration plant or system. According to one implementation example, a relatively accurate estimate of emissions associated with an electrical energy source utilized by an enterprise (considering that a cogeneration plant or system is producing both electrical power and useful heat), the emissions produced are calculated in the system using the following equation:
E Electric power ＝Consumed Electric power ×EF Electric power (formula 1).
Wherein E Electric power is the power emission [ Metric Ton CO 2eq],Consumed Electric power is the power consumption [ kWh ], EF Electric power is the power emission factor [ Metric Ton CO 2/kWh ].
For another example, if the emissions source is a fixed combustion source consuming natural gas, the system calculates the amount of CO2 produced using the following equation:
E Natural gas ＝Consumed Natural gas ×EF Natural gas (formula 2).
Wherein E Natural gas is the natural gas emission [ Metric Ton CO 2eq],Consumed Natural gas is the natural gas consumption [ Therms ], and EF Natural gas is the natural gas emission factor [ Metric Ton CO 2/Therm ].
The further total emissions may be obtained using any known equation or calculation for determining emissions, any or all of which may be integrated into the software of the system. For example, according to one implementation example, the calculations and equations are integrated into software of a storage server, distributed server, or processor set similar to that described in fig. 3.
Additionally, methods and systems for tracking and/or reporting emissions may include tracking emissions of CH4 and/or N2O from an emissions source. In another example of implementation, the method or system may include converting CH4 and/or N2O emissions to "CO2eq". The conversion is based on the respective Global Warming Potential (GWP) of CH4 and/or N2O emissions for comparing representative values of the ability of different GHGs to capture heat in the atmosphere. The conversion equation is as follows:
e CO2＝ENon-CO2 GHG XGWP (formula 3).
E CO2 is CO 2 emissions [ Metric Tons of CO 2eq],ENon-CO2 GHG is non-CO 2 greenhouse gas emissions [ Metric Tons of Non-CO 2 GHG ], GWP is global warming potential (Table 1).
Table 1 lists global warming potentials (taken from the inter-government climate change Commission 2007IPCC AR4 and ISO 14064) in 1996 and 2001.
According to further embodiments, certain systems and methods described herein may provide for tracking and managing tradeable credits, including carbon credits, associated with greenhouse gases. "carbon credit" in this protocol refers to any tradable commodity that assigns a value to greenhouse gas emissions. It is known that there are currently two carbon credit exchanges, chicago climate exchange and european climate exchange. It is further appreciated that the kyoto protocol and countries around the world have established a certain quota for greenhouse gas emissions that can be produced by the countries and businesses, and that each business can compare its emissions to its quota to determine whether it is credit surplus (because its emissions are below its quota) or credit liabilities (because its emissions exceed its quota), and take action accordingly.
Embodiment seven:
An enterprise 220 is provided with a method and system for tracking and managing carbon credits as shown in fig. 13. It should be appreciated that the method and system may be performed on a site or enterprise-wide basis. Or the method and system may be performed on a site grouping basis, such as all sites in a particular province (municipality) or area. It should also be appreciated that the methods and systems described herein are not limited to tracking and/or managing carbon credits or the climate exchanges described above, and may be used to track and manage any type of credit or other tradable entity associated with active GHG emissions.
First, as shown in FIG. 13, the system calculates the total emissions (222) in a manner similar to the emissions calculations provided at 204 in FIG. 12 and discussed above. The system then provides for comparing the total emissions to a predetermined quota (or other measure as described above) for the site or business and calculating whether the site or business emissions exceed the quota (224). Based on this calculation, the system or method provides a method (226) of calculating carbon credit liabilities or remainders. That is, if a site or business exceeds its emission quota, it has carbon credit liabilities. Conversely, if the site or business emissions are below their quota, then it has a carbon credit surplus.
The system 220 then allows for the purchase, sale, or redistribution of the credit (228) depending on whether there is a surplus or liability. That is, if credit debt exists, the system will calculate how much credit must be purchased to eliminate the debt. In one particular embodiment, the system connects to an external source via a network connection or other communication link, which provides the current market price for the credit, and uses this information to calculate the cost of purchasing the required credit. In another example implementation, the system provides or automatically performs the purchase of the required credit.
If there is a credit surplus, the system 220 calculates the credit surplus (the number of credits that the facility or business has to relinquish since the emission quota has not been exceeded). In another specific implementation example, the system 220 also uses the communication link to calculate the value of the remaining credits. Further, the system prescribes or automatically performs the selling of the remaining credits. Or in an implementation example where system 220 calculates credit surplus for one or more sites of the corporation and further calculates credit debt for one or more other sites of the corporation, the system may provide for calculating each surplus and debt and reallocating credit from the surplus site to the liability site, thereby eliminating at least a portion of the need to purchase additional credit on the market.
The system 220 may also provide for adjustment of current or future emissions based on calculation of credit liabilities or credit margins (230). This adjustment may be achieved by the predictive capability discussed below. In one aspect, the processor in system 220 has software configured to perform the comparisons and calculations described above.
The various systems described herein allow for tracking and verifying carbon credits awarded or otherwise obtained for emissions reduction over a predetermined period of time. Certain GHG emission reduction programs are currently adapted for entities that own GHG emission assets and/or sites, allowing for the accumulation of carbon credits to reduce a predetermined number of GHG emissions for a predetermined period of time (e.g., five or twenty years or any such period of time). In order to obtain a predetermined carbon credit for emission reduction, verification is required. That is, the entity must repeatedly prove that-say every year-emissions continue to decrease by a previously determined amount.
Various system implementation examples described herein have software that tracks GHG emissions described herein, and are further programmed to provide automatic, iterative verification of the sustained reduction of a predetermined amount of GHG emissions. One version is to input and store predetermined emissions reductions in the system, and software provides for automatic verification of actual emissions of the asset, location, area or business of the subject promised to be reduced, and to compare the actual emissions to the predetermined emissions. In one example of implementation, the software is further configured to send a notification to a user, an enterprise, or an authentication principal related to authentication performed by the software.
Certain systems of the present disclosure provide for calculation and tracking of points related to the removal and/or destruction of certain pesticides/herbicides. Certain government projects in china and elsewhere, including projects that may have been or are about to be implemented, provide rewards for removing and/or destroying certain pesticides/herbicides. One such plan provides credit or other types of financial incentives for removing and/or destroying such pesticides/herbicides from a site, region or business. Various system implementations described herein provide software for tracking the pesticide/herbicide and/or pesticide/herbicide containers in a site, area or business. In addition, the software also provides for tracking the removal and/or destruction of such pesticides/herbicides and/or containers and calculating the economic benefits resulting from such removal and/or destruction. Furthermore, the software may provide such information to the user in any useful manner similar to that related to carbon credits. The calculation of credits associated with the removal and/or destruction of pesticides/herbicides may be performed in a manner similar to the calculation of carbon credits described herein.
Or systems according to some embodiments are further configured to replace pesticide/herbicide removal/disposal provider databases containing information related to individuals and entities that are authenticated to be able to remove and/or dispose of the pesticide/herbicide. In such an implementation example, the system may track and record the success and compliance of the pesticide/herbicide removal and disposal according to any applicable regulations. It will be appreciated that such a system can operate in a manner similar to the service or maintenance tracking of assets disclosed in U.S. patent application Ser. In one implementation example, the system has software for automatically accessing a pesticide/herbicide removal/disposal provider database to identify the appropriate personnel or entities for removing the pesticide/herbicide from the asset or location. In addition, the software can access the same database to identify authenticated sites/entities/sites for pesticide/herbicide treatment. Furthermore, the software may be configured to track the completion of the treatment. In one example, the software sends a prompt to the appropriate user or authenticated clearance or disposal provider to confirm successful clearance and/or disposal of the pesticide/herbicide. The software may then send a report to the appropriate user and/or third party (e.g., a government agency overseeing the appropriate regulations) confirming details of successful removal and/or disposal.
Certain systems and methods described herein may provide predictive analysis and planning based on the above-described emissions information and calculations (or based on pesticide/herbicide information in which the pesticide/herbicide is removed and/or destroyed), including predictive analysis and planning based on calculations of credit surplus or liabilities as described above and/or emissions adjustments. The enterprise or user may then take appropriate steps to address any predictive impact of the trend using the predicted trend and the information described above. According to one exemplary implementation example, the predicted abnormal weather pattern may be used to predict a trend of energy usage, thereby predicting GHG emissions. For example, an extreme climate duration may have been predicted. According to one implementation example, the system may compare the predicted extreme climate with past correlations and/or calculated correlations between similar weather stresses and GHG emissions. Based on these correlations, the system can predict the impact of active GHG emissions from a partial plot, site (division of business) or whole enterprise within an area that is subject to extreme climates or extreme weather effects.
In areas, assets and activities that are synchronously tracked based on GIS, the system can compare the predicted path of weather events (such as typhoons, cold flows or heat waves, etc.) with the site location through a map-based interface and identify the enterprise site that is predicted to directly receive the weather effect. The system may further calculate and/or inform one or more users of the predicted GHG emissions. In another example implementation, the predicted temperature peaks across a particular region may be used to predict expected GHG emissions associated with transportation, electricity, warehousing, etc.
The user or business may take precautionary action based on the predictive information provided by the system. In one implementation example, a user takes an action based on predictive information provided by the system. Taking the predicted winter as an example, the user may take steps such as reducing energy consumption, thereby reducing emissions from unaffected sites, as emissions from affected sites are expected to increase, or take any other appropriate action in preparation for the expected emissions increase.
Or precautions are implemented by the system. That is, the system allows data and predictive analysis, including predicting certain trends associated with certain assets or equipment, and upon triggering certain events associated with those predictions, electronically communicating or transmitting operational instructions to the associated equipment via an asset/capital/facility (equipment)/"parcel" activity interface associated with the equipment, similar to the operations described above with respect to FIG. 3. Thus, the asset/capital/facility (equipment)/parcel activity interface function may be used in conjunction with the data and predictive analysis functions described above to provide precautions or countermeasures against the effects of predictive trends.
The asset/capital/facility (equipment)/parcel activity interface function may be used to remotely control the operating parameters of certain energy or energy related systems in the field, as disclosed in further detail in the U.S. application Ser. No. 10/734,725, i.e., no. 10/734,725 mentioned and incorporated above, is intended to take measures to prevent or reduce any negative effects of the above-described predictive phenomena. Thus, a system according to one embodiment allows tracking of various parameters related to plot activity at a site or sites, performing data and predictive analysis, and upon triggering a specific event or predicted event related to these parameters, electronically transmitting operational instructions or communications to the PC or mobile device side to affect GHG emissions in some manner. According to one implementation example, the types of equipment that may be remotely controlled in this manner include, but are not limited to, backup, forestation, fostering, harvesting, infrastructure equipment and systems, or any other GHG emission equipment of any kind.
In examples of predicted extreme climates or extreme weather conditions, the predicted degree of weather anomalies and/or impacts may trigger the system to electronically send instructions to a server or asset plot centralized processor system, and in some implementations, may trigger a plot activity system of unaffected sites to reduce the activity practices of those sites or plots to reduce GHG emissions associated with the plot operation, the apparatus in some implementations: the corporation is allowed to reserve GHG credits in any GHG credit market (carbon credit market as described above) that may be established by an organization or government, and in some implementation examples, the corporation's GHG credits are saved for use in counteracting increased emissions from the affected land areas.
In addition to predicting weather trends, the system may also consider and analyze market demand information and GHG credit information, thereby further affecting the instructions transmitted by the system. According to one implementation example, the predicted weather pattern results in a predicted demand and/or GHG credit rate that triggers instructions transmitted by the system to the relevant device through an appropriate interface or interfaces based on the prediction rate. Or real-time or near real-time rate information may be entered into the system of the present implementation example and based on the GHG credit rate, the system may be triggered to transmit various instructions from the system to the relevant devices through the appropriate interface. For example, in the above example of extreme climates or extreme weather events, the server software may predict a certain GHG credit rate that triggers the transmission of electronic instructions to the affected site or equipment of the site that instruct the server or asset plot central processor system to reduce output by some predetermined percentage during the predicted peak rate to reduce emissions, thereby reducing the cost of GHG credit rate required for those emissions. Thus, market demand and GHG credit information may be considered in providing instructions to related devices, operating branches and/or sites. In another option, the system may be triggered by any number of different parameters to communicate with various devices to implement preventive or remedial measures based on the predicted trend.
The method and/or system may generate an emissions report (206 of fig. 12). In general, the emissions report may include any desired information regarding an identified emissions source or group of emissions sources, including, but not limited to, an activity identification, a parcel identification, an asset identification, a capital identification, an emissions source identifier, a type and/or subtype, a site location, and a total amount of emissions generated. According to one embodiment, the total emissions amount includes an amount of GHG produced. Or the total emissions include the amount of CO 2 and CO 2 e produced (expressed as Metric ton CO 2).
Example eight:
FIG. 14 depicts a method of generating an emissions report 240 according to one embodiment. The particular method includes selecting a time period (242) for which the emission yield is to be calculated, selecting a particular emission source or set of emission sources (244) for which the emission yield is to be calculated, generating an emission report based on the selected time period and the selected emission sources (246), and making the report available for distribution, publication, and aggregation (248). According to one implementation example, reporting of any time period (242) may be requested. For example, a report of emissions may be required to be submitted indicating the amount of emissions produced the day before, the week before, the month before, or the year before. Or may require reporting for any period of time.
Reporting may also be required for any emissions source or any group of emissions sources (244). For example, in some implementation examples, reporting requests may be made for all activities of the enterprise, all emissions sources. Or the report request may be made based on site location, type or subtype of source, or any combination thereof.
Typically, the report request is initiated by a user at a remote site using an enterprise processor or client PC similar to that in fig. 3. Or the request may be initiated by anyone having access to the system. For example, any user accessing the system through the internet may request the request.
At startup, according to one implementation example, the server retrieves the appropriate information from the forest resource section/capital value accounting database using the user-provided parameters and generates a report (246). Emission reports may then be provided for distribution 248. In some implementations, the report is only used by intra-enterprise propagation. For example, the report may be automatically distributed to the intended recipients within the enterprise. Or the report may be provided to individuals or entities outside the enterprise, such as local, municipal, provincial, or national government agencies, in accordance with applicable laws and regulations. In one implementation example, the report is generated and distributed in hard copy form. Or reports may be generated and distributed electronically, such as by email or web page. In a further alternative, the report may be generated in any known form and in any known manner.
The disclosed systems and methods may utilize all activity information related to one or more assets, one or more sites, one or more areas, and the entire enterprise to calculate an overall financial cost, an overall "real" cost, and perform optimization and management operations based on that information.
Various system implementation examples described herein provide a method of calculating the total financial cost of an asset, venue, area or business. As described above, the system has software that calculates the total tax, lease and/or acquisition costs of a device, site, area or enterprise as a whole. In a further implementation, the system also has software to calculate the total financial costs, including the cost of land operations (including energy consumption costs), in combination with the cost of any GHG emissions (e.g., pesticide/herbicide leakage) that need to be replenished, and any carbon credit or profit that is obtained or lost from the operating subject asset or site. In one example implementation, the software may calculate the total activity cost of the asset as described above, add the supplemental cost of any fugitive emissions (e.g., leaked pesticide/herbicide), then access any information about the carbon credit associated with the asset, and add it to the total cost calculation. If the asset accumulates carbon credits and then sells it, the sales amount will be used to reduce the total of the cost of ownership. Or if the asset has exceeded a certain emission level, any carbon credits need to be purchased on the market, the purchase amount will be used to increase the total amount of activity costs.
In one implementation, the software calculates the total financial cost of an activity, parcel, asset, business, location, area, or business using at least the purchase cost of the business investment, the maintenance cost associated with the equipment, and the energy consumption cost of the equipment (including, of course, cost reduction based on any rebates or refunds, etc., as described above). Or the software may calculate the total financial cost of the asset, site, area, or business based on any additional parameters that make up the total financial cost, including, for example, any carbon credits accumulated by the asset, site, area, or business. The software may access all relevant information within the system itself, allowing for automatic and convenient calculation of the total cost in some implementation examples, which may then be transmitted to the user or generated in a report and transmitted to one or more users.
The software may calculate the total financial cost during any desired period, such as one year, five years, or a known lifetime of the asset (or site, etc.). In further examples of implementation, the software may combine the total financial costs of all assets for all plots in a site or area over any desired period. In another example implementation, the software may also utilize the predictive analysis and planning capabilities described herein to provide an estimate of the sustained financial cost of an asset, parcel, or area for some predetermined future period (e.g., the next year, two years, or any other desired period). In this way, the software and system described herein can be used to provide a highly accurate estimate of the cost of a managed block, asset, product produced, site or area. As described in further detail elsewhere in the present disclosure, the system may also be configured to generate and communicate a report of this information to one or more appropriate recipients, thereby allowing the user to make activity enforcement decisions with past total financial costs and/or future total financial costs based on context estimates.
According to further implementation examples, various system implementation examples described herein provide a method of calculating a "real cost" of an asset, venue, area or business. As defined herein, "real costs" refers to the total financial and environmental costs associated with an asset, site, region or enterprise. In a further alternative, the "real cost" may also include the public relationship cost of operation of an asset, site, area, or enterprise. Thus, according to one implementation, one or more systems of the present invention have software that calculates the overall real cost, including the total financial cost (including the cost of activity, energy consumption, total purchase lease costs, and any activity impact of any carbon credits) as well as the total GHG emissions of an asset, site, region, or business. In one example implementation, the software may calculate the total financial cost of the asset as described above and separately calculate the total amount of GHG emissions (which may be used to describe the carbon footprint, carbon performance, or environmental performance of a plot, activity, asset, location, area, or business). The software may also utilize any other computable environmental impact parameter to evaluate the environmental impact of an activity footprint, carbon footprint, or asset, site, area, or enterprise.
As with the total financial cost calculation above, the software for calculating the "real cost" may access all relevant information within the system itself, allowing for easy, and in some implementation examples automatic, calculation of the total real cost, which may then be transmitted to the user or generated in a report and transmitted to one or more users. In one implementation, the report may contain the total financial cost amount and a separate total discharge or some carbon footprint calculation. Or the total real cost may be represented in any suitable form.
The software may calculate the total real cost of the forestry activity during any desired period, such as one year, five years, the turn-around period for each "parcel" stand, the lease period for a parcel, the known life of the forestry facility (equipment) or asset. In further examples of implementation, the software may combine the total real costs of all forest assets for all "plots" within a division (site) or area for any desired period of time. In another example implementation, the software may also utilize the predictive analysis and planning capabilities described herein to provide an estimate of the sustained real cost of an asset, location or area for some predetermined future period, such as the next year, the next two years, a five-year planning period, a rental period, or any other desired period). In this way, the software and system described herein can be used to provide a highly accurate estimate of the true operational costs of a forest asset, site or area. As described in further detail elsewhere in this disclosure, the system may also be configured to generate and transmit a report of this information to the appropriate recipient, thereby allowing the user to make operational decisions with the past total real cost and/or the estimated future total real cost.
Various system implementation examples described herein provide a method of analyzing and/or optimizing one or more operating parameters related to the total financial cost (economic cost) or real cost (including economic cost, environmental cost, social cost, etc.) of an asset, venue, area, or forest farm enterprise. As described above, the system has software that tracks the total financial cost and the total real cost, including all parameters that have an impact on both. Furthermore, various embodiments of the system of the present invention also have software that allows for analysis (including predictive analysis) and/or optimization of desired parameters related to financial and real costs. According to one embodiment, such software tracks the total financial and actual costs and all relevant parameters or inputs and utilizes historical data related to those calculations and parameters, as well as predictive analysis and planning capabilities described elsewhere in the present invention, to provide a highly accurate estimate of the impact of adjusting any inputs (e.g., energy consumption, GHG emissions, etc.) on the total financial (economic) cost or actual (including economic, environmental, social, etc.) cost.
A user or entity may wish to obtain a cost estimate that reduces GHG emissions for a certain class of forest management types or for a certain regional site. The user inputs this predetermined amount into the system, which the analysis software uses to calculate the effect of the GHG emissions reduction on the overall financial costs of the site, including the impact on energy costs and the impact on the overall cost and carbon credits of the forest land, nursery stock, supplies, facility construction, equipment purchase, forest activity implementation, etc. In one example implementation, the software utilizes predictive analysis and planning capabilities described elsewhere in this disclosure to determine the impact on total forest asset operating costs due to any asset (facility/equipment) upgrades, or changes, or any other related increase in forest activity costs required to achieve emissions reduction, while also estimating any profit associated with the increase in the amount of carbon credits accumulated due to emissions reduction. In another example of implementation, the software may also calculate the real cost of GHG emissions reduction.
In woodland feature occupancy feasibility study project reports, a user or entity may wish to obtain an estimate of the cost of increased energy consumption due to changes in one of the sites or augmentation of sites. The user enters predetermined information in the system about the new additional equipment/facilities or assets added due to the extension/addition, which the analysis software uses to calculate an estimate of the impact of this energy consumption cost and total cost of ownership increase on the on-site GHG emissions and carbon credits. In one implementation example, the software utilizes predictive analysis and planning capabilities to determine the impact on GHG emissions due to the addition of new or additional GHG emissions assets in an extended or new site, while also estimating any added costs associated with any carbon credit liabilities resulting from the addition of emissions. In addition, the software also considers any other parameters that may be affected by the change/extension/addition. In another example of implementation, the software may also calculate the true cost of the change/extension/addition.
A particular parcel a activity is powered by a public resource X which charges the enterprise a fee per kwh of rmb. In this example, the emission factor is calculated from the power generation combination of utility X.
Furthermore, in this example, there is also at least one on-site power generation source (e.g., a diesel backup generator, a wind turbine, a solar array, or any other type of power generation source) within the area of land A. Obviously, each on-site power source has financial costs of operation, as well as GHG emissions generated during operation.
In this example, the system has predictive analysis software as described above that uses the energy consumption in the past of the area in which plot a is located to identify the time/season/period that is typically at the highest or lowest consumption, and further to identify the activity or use activity that results in an increase or decrease in power consumption. Thus, the software uses the past data in combination with predictive factors such as ambient temperature or seasonal information to predict the expected price of the common resource X per kilowatt-hour during the expected event (peak usage time, hot waves, seasons or any other event) to predict the expected cost, in combination with the calculation of the expected GHG emissions to provide the carbon impact (and any additional financial costs or benefits associated with carbon credits). Thus, the software may provide the expected financial costs and the expected carbon emission impact, thereby also providing the expected "real" costs as defined by the present invention.
Using the information described in the previous paragraph, certain decisions may be made or altered—decisions relating to any number of operational parameters in the field (e.g., which blocks of forest assets are to operate under which operational activity parameters or which activities are to be performed in the field) may be made automatically by software or manually by a user. These campaign adjustments may be made prior to the occurrence of the event based on predictive analysis. I.e., can adjust the activity parameters based on information provided by predictive analysis software, adjust any adjustable activity parameters related to energy consumption, including any form of energy consumption reduction (based on asset, timing, cycle, etc.). In another example embodiment, the software further includes an optimization component that identifies an optimal level of consumption, cost, or GHG emissions and adjusts various activity parameters described herein to achieve the optimal level.
Any other analysis of this type may also be performed using the analysis software and all available information in the various examples of implementations of the systems and methods described herein.
A user or entity may wish to obtain an estimate of the best combination of operating parameters in order to actively operate a forest asset, site, area or forest farm enterprise in a manner that results in the lowest total financial cost and lowest GHG emissions. In the example of the site, the optimization software uses known information about all forest assets in the site, including all energy consumption information and forest cost information (including any maintenance and other costs), as well as all GHG emissions information and carbon credit information to calculate appropriate operational parameters to optimize costs and emissions. For example, the software may calculate that by reducing the operation of the energy consuming asset at certain times of the day or week, the energy consumption, and thus emissions, may be reduced. Or the software may calculate that increasing consumption in some plots and decreasing consumption in other plots may be the best option to reduce overall cost and emissions. In another example, the software may be based at least in part on demand response and/or compensation or cost savings plans provided by common resources or energy sources, and further based on carbon credits, to determine forest activities for various forest assets according to the plans to reduce costs and emissions, to calculate appropriate consumption. In another example, the software may determine any optimal combination of activity parameters and provide this information in the form of a report that is generated by the system through a report generation process described in further detail herein.
The analysis and optimization software described above may be run with asset/equipment/plot activity interfaces (such as those interfaces 68 shown in fig. 3 and/or those interfaces 68 described elsewhere in the present invention) to transmit operational instructions to forest assets of certain plots to implement optimization strategies or preferred activity operational parameters calculated by the software.
That is, the software may provide appropriate analysis to calculate the total financial and real costs of the purchase item in connection with expansion, change of class, or conversion of forest assets of the forest farm enterprise. In one implementation example, the software allows a user to create a procurement budget based on the block asset operational activity information that is already stored in the system. The procurement budget may be a financial budget and/or an emissions budget. Further, the budget may be a forestation cost, a tending/care budget cost, or a combination of both. That is, all forest land parcel asset information is available, such as cost of purchasing supplies, camping activities, and anticipated emissions, all of which may be contained in the budget. Once the budget has been determined, the software can also track the actual cost as the land mass assets increase and the camping activities begin. In addition, the software may also provide analysis or budget adjustments based on changes in the facility/equipment type and/or operational activity parameters of the parcel forest asset.
A forest farm enterprise may wish to purchase additional land parcels. The user enters the activities required for the block production operations, and the software can use this information to calculate an estimated overall financial budget for the acquisition store and the block production operations, as well as an estimated emissions/carbon footprint budget based on the expected emissions for each block production operation activity. In one implementation example, the software may also calculate an optimal combination of parcel assets and activity parameters to minimize the overall financial budget of the acquisition and storage of additional parcel and parcel production operations. For example, the software may calculate with an additional plot/business activity budget, purchasing a plot that is more expensive, more efficient, and/or emits less GHG than another model may be more cost effective in the long term, e.g., by calculating, reduced energy consumption may reduce the cost required for production operations over time, or reduced emissions may generate more carbon credits that may then be sold to gain profits. Or the analysis software may utilize any parameters and any calculations to optimize the purchasing strategy of the enterprise.
According to various additional implementation examples, the disclosed systems and methods may utilize all of the disclosed operational activity information described above relating to more than one farm enterprise to calculate total energy consumption, total energy cost, total GHG emissions, or any other trackable or computable carbon credit and carbon quota parameters described herein.
Various entities, including government entities (e.g., municipalities, counties, states, and/or countries), may be interested in tracking and calculating the total amount of energy consumption, GHG emissions, or any other information that may be tracked and/or calculated herein for a plurality of businesses. Such a system allows access by one or more appropriate personnel from each entity or business from which information is to be collected. For example, the system may provide a website through which entity or enterprise information may be entered, or the system may provide any access/entry point, such as a client computer or self-service terminal, as described herein.
The system has software and existing information/calculations that can assist and/or prompt the user to enter information. For example, the system may have a website that provides a "drop down" box that provides standard choices for various categories, such as the number of certain assets (vehicles, hvac systems, etc.) and the type of asset (brand, model, etc.). Further, as noted above, with respect to enterprise-level systems, the system has software that calculates the total energy consumption, total energy cost, total GHG emissions, etc. of all participating entities or enterprises within a predefined area.
For example, an regional regulatory body may be interested in determining the total amount of GHG emissions from a forest farm/entity within it. The country may utilize an implementation of the system of the present invention to provide system access to each forest farm/entity. For example, access is provided through a website. Each farm/entity then enters its energy consumption and/or GHG emission information according to the prompts of the system. The system stores this information in a database, which is used by software to calculate the total GHG emissions for the regional forest farm/entity.
Various system implementations described herein also provide for historical activity data analysis of plots as described above, including data correlation and predictive analysis. That is, according to one implementation example, these systems include software that can utilize aggregated information stored, absorbed, or used by the system to identify correlations with other information, and use these correlations to predict trends and provide activity information related to predicted or expected changes in matter energy input, emissions, etc., as described above. More specifically, according to one implementation, such software may track total block management energy consumption, energy consumption costs, GHG emissions, or any other activity parameter, and utilize historical data related to these block calculations and activity parameters, as well as predictive analysis and planning capabilities described elsewhere in the present invention, to provide accurate estimates of the impact of adjusting any input on various block activity parameters (e.g., cost or emissions), such as energy consumption, GHG emissions, and the like.
The system also has software for generating reports related to the summary information and/or analysis described above. That is, the software may automatically generate reports related to the calculated total number of activities, other calculated information, or predicted trends, and communicate such reports or information to an appropriate government agency, forest farm, or user, who may make strategic decisions using such activity emission information and take action based on such decisions.
Examples of implementations of the present system may provide for operational activity emissions accounting, regulation, and optimization operations similar to the forest asset, site, area, forest farm, and/or artificial forest "land parcels" management systems disclosed herein, providing for tracking and emissions calculation similar to the various activity parameters discussed in this document. However, the instant implementation example allows for the input of such information for more than one farm or entity and provides for tracking and calculating the total emissions and variability of the various forest parameters discussed herein. Forestry activities are a complex system of forest construction, forest treatment, forest harvesting, forest product processing and forest product sales. The system boundaries of forestry LCAs can be divided into "bassinet to door", "door to door" and "bassinet to tomb". However, a bassinet boundary in a forest contains many sub-boundaries. For example, a forest production boundary includes sub-boundaries: stand establishment, tending, road construction and harvesting. Further, the institutional boundaries from cradle to cradle can be studied in more detail. For example, the environmental impact of different deforestation systems for short-cycle and large-diameter artificial forests is assessed by LCA. In artificial forests, potential studies of system boundaries from bassinet to bassinet are the elite breeding stage LCA, forest management (weeding, thinning, pruning, pest control) and harvesting activities.
Example nine:
FIG. 15 depicts a method of tracking the production process carbon footprint of any product, service or asset, where "production carbon footprint" as used herein refers to any GHG emissions generated when the product, service or asset is created and/or transported to a destination where the product, service or asset is to be sold. This method can be easily implemented with the various systems described herein. The method generally includes collecting product, service, or asset information (252), such as identification information and other basic information; collecting manufacturing emissions information (254), including any emissions related to the creation and/or packaging of the product, service, or asset; collecting (256) transportation emissions information related to any transportation of the pre-sales product, service or asset; any operational emissions information (258) related to any estimated GHG emissions resulting from operating or using the product, service, or asset is collected, and a carbon footprint for the product, service, or asset is calculated from the collected information.
As countries and the world are increasingly concerned about GHG emissions, the impact of these gases on the environment, and "carbon friendly" products and services, companies and other entities (and their customers) are increasingly interested in knowing the impact of various products, services, and equipment purchased by these entities on the environment (including the carbon footprint). To this end, a company may wish to track the production carbon footprint of the asset or device that the company purchased and used at its location. The company may also want to track the production carbon footprint of products and/or services purchased by the company for sale to customers.
Various embodiments of the system described herein may be used to track the production carbon footprint of a product, service, or asset. Basic product, service, or asset information may be collected (252) and entered into the system via a client computer or any other input method, and manufacturing emissions information (254) and shipping emissions information (256) may also be collected, entered; and/or calculated in a similar manner as the inputs and calculations described above for emission information related to the asset (e.g., via the energy consumption information and formulas discussed above). Further, estimates of operational emissions of the product, service, or asset may also be collected (258) or calculated and input into the system. The system software may then utilize the emissions information to calculate a carbon footprint for the product, service, or asset. According to one implementation example, the production carbon footprint is an estimated emissions number. Or the production carbon footprint may be some type of predetermined score or rating for comparing a product, service, or asset to other products, services, or assets. In a further alternative, the carbon footprint may be determined solely from manufacturing emissions. In another alternative, the carbon footprint may be determined solely from the transportation emissions or business emissions information. In another option, any combination of emissions information may be used to calculate the carbon footprint.
A material is manufactured abroad and then transported to china. In one implementation, basic information about the material, such as a unique identifier and basic information about the material, is entered into the system and stored in a database, and then the transportation emissions are entered into the system. In addition, production emission information is also input. According to one implementation example, production emission information is calculated at the production site from actual emission tracking or from energy consumption calculation emissions, as described above. Or the emissions of the industry may be estimated in some way.
As described above, the transport emission is calculated based on the actual emission of the aircraft or the ship transporting the parts or the emission based on the energy consumption. Or the amount of emissions of transportation may be estimated in some way.
The operational emissions may also be considered in the calculation. In one implementation, the operating emissions are based on historical data for the type of component and an estimate of an estimated life of the component. Or the operational emissions may be calculated in any suitable manner.
The software then uses the emissions information stored above to calculate the total emissions to find the production carbon footprint of the widget. The production carbon footprint may then be provided in a report, or otherwise provide communications to the user. In addition, the production carbon footprint may be utilized in any suitable manner.
The invention is not limited to the above-described embodiments, but it should be noted that it is possible for a person skilled in the art to make several improvements and modifications without departing from the technical principle of the invention, which are also considered as the protection scope of the invention.
Claims (39)
1. Accurate tracking system of artifical woodland block activity seal, its characterized in that includes:
(a) A storage server, a distributed server, or a set of processors; the 'land parcel' level forestry activities can access a storage server, a distributed server or a processor set through an electronic device network, wherein the electronic device comprises a personal PC, a tablet, a portable APP terminal and a mobile phone;
(b) A database of "parcel" forest resource partitions and capital value accounting in communication with a storage server, distributed server, or processor set, the database configured to store artificial parcel, and attribute information, artificial parcel ecosystem product production and service supply information, parcel-level forestry activity footprint information, artificial parcel activity energy consumption information, artificial parcel management activity GHG emission information, and parcel stand management process carbon credit information;
(c) Identification software for the artificial forest "parcel" zones and attributes associated with the storage server, distributed server, or processor set, the identification software configured to be capable of linking, associating, acquiring, mining, and registering artificial forest "parcel" zones and attribute information associated with each of a plurality of forest resources or natural capital or parcel of at least two forest farms;
(d) Accounting software for dynamic accounting of manufactured forest "land" ecosystem product production, service supply, and value associated with the storage server, distributed server, or processor set, the accounting software configured to calculate, store, and track manufactured forest "land" ecosystem product production, service supply, and value dynamic information associated with each of a plurality of forest resources or natural capital or land parcels of the at least two forest farms;
(e) Forestry activity implementation footprint tracking software for "parcel" level forestry activity implementation footprint tracking associated with the storage server, distributed server, or processor set, the forestry activity implementation footprint tracking software configured to trace and register artificial forest "parcel" activity practice process footprint information associated with each of a plurality of forest resources or natural capital or parcel of the at least two forest farms;
(f) Forestry activity energy consumption tracking software for "parcel" level forestry activity energy consumption tracking associated with the storage server, distributed server, or processor set, the forestry activity energy consumption tracking software configured to calculate and track artificial forest "parcel" activity energy consumption information associated with each of a plurality of forest resources or natural capital or parcel of the at least two forest farms;
(g) GHG tracking software of "land parcel" activity associated with the storage server, distributed server, or processor set, the GHG tracking software configured to calculate and track artificial forest "land parcel" operational activity GHG emission information related to each of a plurality of forest resources or natural capital or land parcel of the at least two forest farms;
(h) Stand business process carbon credit tracking software for "parcel" stand business process carbon credit tracking associated with the storage server, distributed server, or processor set, the stand business process carbon credit tracking software configured to calculate and track "parcel" stand business process carbon credit information associated with each of a plurality of forest resources or natural capital or parcel of the at least two forest lands;
(i) Optimization software for manual forest "parcel" activity footprint precision tracking and GHG emission management and cost-benefit optimization associated with said storage server, distributed server or processor set, the optimization software being configured to calculate, track and modify to calculate and track a manual forest "parcel" level operation optimization objective based on any one or more of said manual forest "parcel" ecosystem product production and service supply information, manual forest "parcel" GHG emission information, "parcel" activity energy consumption information and "parcel" stand operation process carbon credit information;
(j) Auxiliary development software for artificial forest "parcel" activity footprint precision tracking and GHG emission management assistance associated with the storage server, distributed server or processor set, the auxiliary development software configured to calculate, predict and replace to assist in developing an artificial forest ecosystem multi-dimensional "parcel" activity optimal implementation based on any one or more of the artificial forest "parcel" region and attribute change information, artificial forest "parcel" ecosystem product production and service supply evolution information, artificial forest "parcel" GHG emission response information, "parcel" activity energy consumption change information and "parcel" stand operation process carbon credit change information;
(k) Aided design software for accurate tracking of artificial forest "parcel" activity imprints and GHG emission management associated with the storage server, distributed server or processor set, the aided design software being configured to be computationally, contextualized and analyzable to calculate, link, trade-off and AI-aided design of a value-enhancing mechanism, ecosystem versatility, synergy and ecological product value implementation for an artificial forest "parcel" level activity value chain based on any one or more of the artificial forest "parcel" region and attribute change information, artificial forest "parcel" ecosystem product production and service supply evolution information, artificial forest "parcel" GHG emission response information, "parcel" activity energy consumption change information and "parcel" stand operation process carbon credit change information.
2. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: mapping software associated with the storage server, the distributed server, or the processor set is also included, the mapping software configured to generate a space-time evolution dynamic pattern diagram related to at least one of distributed artificial forest "parcel" ecosystem product production and service provisioning information, distributed "parcel" activity intensity and energy consumption information, distributed "parcel" business activity GHG emissions and business process carbon credits, distributed "parcel" carbon quota information, distributed "parcel" best goal allocation, and distributed "parcel" best practices.
3. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: reporting software associated with the storage server, distributed server, or processor set for comprehensive metering/verification/evaluation is also included, the reporting software configured to generate reports related to at least one of ecosystem product and service information, "land" activity information, GHG emissions information, energy consumption information, carbon credit information, best objectives, best solutions.
4. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the reporting software is associated with a client processor, wherein the client processor is configured to allow access, input, query, download and request of reports related to any of the emission information, the energy consumption information, the carbon credit information and the optimal target.
5. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the identification software is configured to calculate and track management zones and attribute information associated with each of at least two "plots," the method of calculating and tracking including AI big data linking, associating, acquiring, mining and registering associated calculation and identification means.
6. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the identification software is configured to calculate and track a set of forest resource section compositions and attribute information associated with each of the at least two forest sites/locations.
7. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the accounting software is configured to calculate, store and track artificial forest ecosystem product production, service supply and value dynamic information associated with each of the at least two "plots".
8. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the accounting software is configured to calculate and track artificial forest ecosystem product production, service supply, and value dynamic information associated with each of the at least two forest farms or locations.
9. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the forestry activity implementation footprint tracking software is configured to calculate, store, and track manual forestry "parcel" activity and implementation footprint information associated with each of the at least two "parcel.
10. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the forestry activity implementation footprint tracking software is configured to calculate and track artificial forest "parcel" activity and implementation footprint information associated with each of the at least two forest sites or locations.
11. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the forestry activity energy consumption tracking software is configured to calculate, store, and track artificial forest "parcel" activity energy consumption information associated with each of the at least two "parcel.
12. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the forestry activity energy consumption tracking software is configured to calculate and track artificial forest "land parcel" activity energy consumption information associated with each of the at least two forest sites or locations.
13. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the GHG tracking software is configured to calculate, store and track artificial forest "parcel" operational GHG emission information associated with each of the at least two "parcels".
14. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the GHG tracking software is configured to calculate and track artificial forest "land parcel" operational GHG emission information associated with each of the at least two forest sites or locations.
15. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the stand business process carbon credit tracking software is configured to calculate, store, and track "parcel" stand business process carbon credit information associated with each of the at least two "parcel.
16. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the stand business process carbon credit tracking software is configured to calculate and track "land" stand business process carbon credit information associated with each of the at least two forest sites or locations.
17. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the optimization software is configured to calculate and track optimal goals associated with each of a plurality of forest resources/assets/capital or products/services.
18. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the optimization software is configured to calculate and track optimal targets associated with each of at least two "plots".
19. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the optimization software is configured to calculate and track optimal goals related to forest sites/locations.
20. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the auxiliary development software is configured to calculate and track an artificial forest ecosystem multidimensional "land parcel" activity best mode associated with each of a plurality of forest resources/assets/capital or products/services.
21. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the auxiliary development software is configured to calculate and track a multi-dimensional "plot" activity optimal implementation of the artificial forest ecosystem associated with each of the at least two "plots".
22. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the auxiliary development software is configured to calculate and track optimal implementations related to forest farms or locations.
23. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the ancillary design software is configured to calculate and track a value promotion mechanism, ecosystem versatility, synergy and ecological product value implementation for an artificial forest ecosystem "land" level activity value chain associated with each of a plurality of forest resources/assets/capital or products/services.
24. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the aided design software is configured to calculate and track a value-enhancing mechanism, ecosystem versatility, synergy, and ecological product value implementation of an artificial forest ecosystem "parcel" level activity value chain associated with each of the at least two "parcels.
25. The artificial woodland activity imprinting precision tracking system according to claim 1, wherein: the aided design software is configured to calculate and track the value-enhancing mechanisms, ecosystem versatility, synergy and ecological product value implementations of the artificial forest ecosystem "land" level activity value chain in relation to the forest farm/zone.
26. A system for building forest activity energy consumption and GHG emissions tracking based on an artificial forest executive/subtotal "land parcel" carbon account network for a forest farm, the system comprising:
(a) A storage server, distributed server, or processor set accessible through a computer or mobile device network;
(b) A forest resource compartment/capital value accounting database in communication with a storage server, distributed server, or processor set, the database configured to store artificial forest ecosystem "land" activity emission information associated with each of a plurality of forest resources/assets/capital or products/services, wherein the "land" activity emission information includes at least activity emission information of a seedling breeding stage, "land" artificial forest product production management stage, and a forest product manufacturing stage; the artificial forest ecological system 'land block' activity energy consumption information related to each of the at least two forest resources/assets/capital or products/services, wherein the 'land block' activity energy consumption information at least comprises activity energy consumption information of fine seed breeding propagation activity, artificial forest 'land block' forestation activity, forest product harvesting, transportation, processing, distribution and the like; carbon credit information of construction forest process activity implementation in the forest product 'land block' production stage, wherein the carbon credit information at least comprises financial carbon credit information;
Emission information associated with each of a plurality of assets of at least two plots; energy consumption information associated with each of a plurality of assets managed by the at least two affiliated stations, the energy consumption information including at least financial energy consumption information; the carbon credit information at least comprises financial carbon credit information;
(c) Cost calculation software associated with the storage server, distributed server, or processor set, the cost calculation software configured to calculate and track financial costs associated with each of a plurality of assets of the at least two sites based on the emission information, the energy consumption information, and the carbon credit information;
(d) Emission calculation software associated with the storage server, distributed server, or processor set, the emission calculation software configured to calculate and track emissions associated with each of the plurality of assets of the at least two sites;
(e) Reporting software associated with the storage server, distributed server, or processor set, the reporting software configured to generate a report related to at least one of the emissions information, the energy consumption information, the carbon credit information, and the financial cost.
(F) The database is configured to store (i) a forest resource section and attribute information associated with each of the at least two "plots"; a forest resource compartment composition and an attribute information set associated with each of the at least two forest sites/locations; (ii) Dynamic information of artificial forest ecosystem product production, service supply and value associated with each of the at least two "plots"; artificial forest ecosystem product production, service supply, and value dynamic information associated with each of the at least two forest sites/locations; (iii) The artificial forest "parcel" activity and implementation imprinting information associated with each of the at least two "parcel" areas; artificial forest "land" activity and implementation imprinting information associated with each of the at least two forest sites/locations; (iv) The artificial forest "land" activity energy consumption information associated with each of the at least two "lands"; artificial forest "land" movement energy consumption information associated with each of the at least two forest sites/locations; (v) Artificial forest "plots" operational GHG emission information associated with each of the at least two "plots"; artificial forest "land" operational GHG emission information associated with each of the at least two forest sites/locations; (vi) The "parcel" stand business process carbon credit information associated with each of the at least two "parcel; "land" stand business process carbon credit information associated with each of the at least two forest sites/locations; (vii) An optimal goal associated with each of a plurality of forest resources/assets/capital or products/services; an optimal target associated with each of the at least two "plots"; calculating and tracking optimal targets related to forest sites/locations; (viii) A multi-dimensional "plot" activity best mode of an artificial forest ecosystem associated with each of a plurality of forest resources/assets/capital or products/services; a multi-dimensional "plot" activity optimal implementation of the artificial forest ecosystem associated with each of the at least two "plots"; preferred embodiments related to forest sites/locations; (x) A value enhancement mechanism, ecosystem versatility, synergy, and ecological product value implementation for an artificial forest ecosystem "land" level activity value chain associated with each of a plurality of forest resources/assets/capital or products/services; a value-enhancing mechanism of an artificial forest ecosystem "land" level activity value chain, an ecosystem versatility, a synergy, and an ecological product value realization associated with each of the at least two "land" blocks; the value of the artificial forest ecological system 'land block' level activity value chain related to the forest farm/zone is improved by a mechanism, the multifunction of the ecological system, the synergy and the ecological product value are realized.
27. A network-based enterprise energy consumption and emission management system, the system comprising:
(a) A central processor accessible over a computer network;
(b) An asset database in communication with the central processor, the first database configured to store (i) emissions information associated with each of a plurality of assets of at least two sites, wherein the emissions information includes at least financial emissions information; (ii) Energy consumption information associated with each of the plurality of assets at the at least two locations, wherein the energy consumption information includes at least financial energy consumption information; (iii) Carbon credit information, wherein the carbon credit information at least comprises financial carbon credit information;
(c) Cost calculation software associated with the central processor, the cost calculation software configured to calculate and track financial costs associated with each of the plurality of assets of the at least two sites based on the emissions information, the energy consumption information, and the carbon credit information;
(d) Reporting software associated with the central processor, the reporting software configured to generate a report related to at least one of the emissions information, the energy consumption information, the carbon credit information, and the financial cost.
28. The web-based enterprise energy consumption and emission management system of claim 27, wherein: the cost calculation software is configured to calculate and track financial costs associated with each of the at least two sites.
29. The web-based enterprise energy consumption and emission management system of claim 27, wherein: the cost calculation software is configured to calculate and track financial costs associated with an enterprise.
30. A network-based forestry "parcel" energy consumption and emission management system, comprising:
(a) A central processor accessible over a computer network;
(b) An asset database in communication with the central processor, configured to store asset database (i) emissions information associated with each of a plurality of assets of at least two sites, wherein the emissions information includes at least actual greenhouse gas emissions for each of the plurality of assets; (ii) Energy consumption information associated with each of a plurality of assets in the at least two locations, wherein the energy consumption information includes at least an actual energy consumption cost of each of the plurality of assets; (iii) Carbon credit information associated with each of a plurality of assets in the at least two locations, wherein the carbon credit information includes at least actual carbon credits accumulated by each of the plurality of assets;
(e) Alignment software associated with the central processor, the alignment software configured to: (i) Comparing and calculating the difference between the actual greenhouse gas emissions and the estimated greenhouse gas emissions; (ii) Comparing and calculating the difference between the actual energy consumption cost and the budget energy consumption cost; and (iii) the actual accumulated carbon credits and the budgeted carbon credits.
31. A forestry "parcel" energy consumption and emission management system according to claim 30, wherein: also included is reporting software associated with the central processor, the reporting software configured to generate a report related to the at least one operational adjustment.
32. A forestry "parcel" energy consumption and emission management system according to claim 30, wherein: a client processor in communication with the central processor is also included, wherein the client processor is configured to allow access, input, query, download, and request reports related to any of the emissions information, the energy consumption information, the carbon credit information, and the at least one operational adjustment.
33. A forestry "parcel" energy consumption and emission management system according to claim 30, wherein: each of the plurality of assets includes an asset interface in communication with the client processor, the asset interface configured to control at least a portion of the asset.
34. A forestry "parcel" energy consumption and emission management system according to claim 30, wherein: also included is operational software associated with the central processor, the operational software configured to adjust operation of at least one of the plurality of assets through an asset interface of the at least one of the plurality of assets based on the at least one operational adjustment.
35. A network-based enterprise carbon footprint tracking system, the system comprising:
(a) A central processor accessible over a computer network;
(b) A database in communication with the central processor, the database configured to store (i) manufacturing emission information related to at least one of a plurality of products, services, or assets; (ii) Packaging emissions information related to at least one of a plurality of products, services, or assets; (iii) Transportation emissions information related to at least one of a plurality of products, services, or assets;
(c) Carbon footprint calculation software associated with the central processor configured to calculate and track carbon footprint calculation software for at least one of the plurality of products, services or assets based on manufacturing emission information for the at least one of the products, services or assets, packaging emission information for the at least one of the products, services or assets; and shipping emission information for at least one product, service, or asset.
36. The enterprise carbon footprint tracking system of claim 35, wherein: also included is manufacturing emission calculation software associated with the central processor, the manufacturing emission calculation software configured to calculate and track manufacturing emissions for at least one of the plurality of products, services, or assets.
37. The enterprise carbon footprint tracking system of claim 35, wherein: also included is wrapper emissions calculation software associated with the central processor, the wrapper emissions calculation software configured to calculate and track wrapper emissions for at least one of the plurality of products, services, or assets.
38. The enterprise carbon footprint tracking system of claim 35, wherein: also included is transportation emissions calculation software associated with the central processor, the transportation emissions calculation software configured to calculate and track transportation emissions of at least one of the plurality of products, services, or assets.
39. A method of GHG emissions management comprising the steps of: step S1: establishing the precise tracking system for the activity imprinting of the artificial forest land according to any one of claims 1 to 38;
The method also comprises the following steps:
step S2: activity tracking: the 'land block' operation activity imprinting accurate tracking method specifically comprises the following steps:
(a) The 'land parcel' level forestry activities access a storage server, a distributed server or a processor set through an electronic device network, wherein the electronic device comprises a personal PC, a tablet, a portable APP terminal and a mobile phone;
(b) The database is configured to store manual forest 'land' division and attribute information, manual forest 'land' ecosystem product production and service supply information, manual forest 'land' movable energy consumption information, manual forest 'land' management activity GHG emission information and 'land' stand management process carbon credit information;
(c) The forestry activity implementation imprinting tracking software is configured to trace and register imprinting information of a manual forest 'land block' activity practice process;
Step S3: calculation and tracking of GHG emissions and carbon credits, comprising in particular the steps of:
(a) The GHG tracking software is configured to calculate and track GHG emission information of "land block" management activities of the artificial forest;
(b) The forestry activity energy consumption tracking software is configured to calculate and track forestry activity energy consumption information;
(c) The stand management process carbon credit tracking software is configured to calculate and track carbon credit information of the "land" stand management process;
step S4: management and optimization:
(a) The optimizing software is configured to be modifiable to calculate and track a multi-functional "parcel" level operation optimal target of the artificial forest ecosystem based on any one or more of the artificial forest "parcel" GHG emission information, "parcel" activity energy consumption information, and "parcel" stand operation process carbon credit information;
(b) The auxiliary development software is configured to calculate, track and AI auxiliary development of a multidimensional 'land block' activity optimal implementation of the artificial forest ecological system;
(c) The auxiliary design software is configured to calculate, link, weigh and AI auxiliary design a value lifting mechanism of an artificial forest ecosystem 'land block' level activity value chain, ecological system versatility, synergy and ecological product value realization;
(d) Comparing and calculating the differences between actual and budgeted productivity and additional active energy consumption costs, land GHG emissions and carbon credits;
(e) At least one operational adjustment to at least one of the plurality of assets/capital or products/services is identified to reduce at least one of the difference between actual energy consumption costs, budgeted energy consumption costs, and GHG emissions, increasing carbon credits.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114493213A (en) * | 2022-01-18 | 2022-05-13 | 上海祺鲲信息科技有限公司 | Carbon emission data acquisition and processing method based on Internet of things |
| CN117274012A (en) * | 2023-09-20 | 2023-12-22 | 信华信(苏州)信息技术有限公司 | Product carbon footprint tracking method based on SaaS service |
| CN118014393A (en) * | 2024-02-02 | 2024-05-10 | 中南林业科技大学 | Carbon footprint calculation method and system in the breeding stage of economic forest improved varieties |
| CN118114867A (en) * | 2024-02-27 | 2024-05-31 | 生态环境部南京环境科学研究所 | Ecological performance evaluation system and evaluation method for industrial park |
| CN118278951A (en) * | 2024-04-18 | 2024-07-02 | 北京师范大学 | Carbon emission accounting and planning method and system for zero-carbon campus |
-
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- 2024-07-19 CN CN202410974514.0A patent/CN118967151A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114493213A (en) * | 2022-01-18 | 2022-05-13 | 上海祺鲲信息科技有限公司 | Carbon emission data acquisition and processing method based on Internet of things |
| CN117274012A (en) * | 2023-09-20 | 2023-12-22 | 信华信(苏州)信息技术有限公司 | Product carbon footprint tracking method based on SaaS service |
| CN118014393A (en) * | 2024-02-02 | 2024-05-10 | 中南林业科技大学 | Carbon footprint calculation method and system in the breeding stage of economic forest improved varieties |
| CN118114867A (en) * | 2024-02-27 | 2024-05-31 | 生态环境部南京环境科学研究所 | Ecological performance evaluation system and evaluation method for industrial park |
| CN118278951A (en) * | 2024-04-18 | 2024-07-02 | 北京师范大学 | Carbon emission accounting and planning method and system for zero-carbon campus |
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