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Flash droughts, characterized by their abrupt onset and rapid intensification, are predicted to increase in frequency and severity under global warming. Understanding the incidence and progression of a flash drought and its impact on maize growth is crucial for maize production to withstand flash drought events. This study used the evaporative demand drought index (EDDI) method to evaluate the incidence of summer drought in Liaoning during the period 1961–2020. It examined the incidence and characteristics of summer flash droughts in Liaoning Province in the period of 1961–2020 and evaluated the factors responsible and the impact on maize during the critical development period. The ratio of the number of stations recording a disaster to total number of stations (IOC) curve, i.e., the ratio of the number of stations recording disasters and total stations, for summer flash droughts in Liaoning showed an upward trend during the period of 1961–2020, with large-scale, regional, and local flash droughts occurring in 8, 10, and 31 years, respectively. Summer flash droughts in Liaoning were mainly in the extreme drought category and ranged in frequency from 10% to 20% in most areas. Before the flash drought occurrence in three typical years (1989, 1997, and 2018), a precipitation deficit without large-scale high-temperature events was observed, and the cumulative water deficit caused the flash drought. Regional or large-scale high-temperature events were often accompanied by flash droughts, and the drought intensified rapidly, owing to the influence of heat waves and water deficits. Summer flash droughts caused a reduction in total primary productivity (GPP) of maize by more than 20% in most areas in the three typical years. The yield reduction rate in 1989, 1997, and 2018, was 27.6%, 26.4%, and 5%, respectively. The degree of decline in maize productivity and yield was associated with the onset and duration of the flash drought. The atmospheric conditions of summer flash droughts were characterized by high-pressure anomalies and atmospheric subsidence, which were unconducive for precipitation but conducive to flash drought occurrence. The continuous high-pressure anomaly promoted the maintenance of the flash drought. Full article

The causal relationship between vegetation and temperature serves as a driving factor for global warming in the climate system. However, causal relationships are typically characterized by complex facets, particularly within natural systems, necessitating the ongoing development of robust approaches capable of addressing the challenges inherent in causality analysis. Various causality approaches offer distinct perspectives on understanding causal structures, even when experiments are meticulously designed with a specific target. Here, we use the complex vegetation–climate interaction to demonstrate some of the many facets of causality analysis by applying three different causality frameworks including (i) the kernel Granger causality (KGC), a nonlinear extension of the Granger causality (GC), to understand the nonlinearity in the vegetation–climate causal relationship; (ii) the Peter and Clark momentary conditional independence (PCMCI), which combines the Peter and Clark (PC) algorithm with the momentary conditional independence (MCI) approach to distinguish the feedback and coupling signs in vegetation–climate interaction; and (iii) the Liang–Kleeman information flow (L-K IF), a rigorously formulated causality formalism based on the Liang–Kleeman information flow theory, to reveal the causal influence of vegetation on the evolution of temperature variability. The results attempt to capture a fuller understanding of the causal interaction of leaf area index (LAI) on air temperature (T) during 1981–2018, revealing the characteristics and differences in distinct climatic tipping point regions, particularly in terms of nonlinearity, feedback signals, and variability sources. This study demonstrates that realizing a more holistic causal structure of complex problems like the vegetation–climate interaction benefits from the combined use of multiple models that shed light on different aspects of its causal structure, thus revealing novel insights that are missing when we rely on one single approach. This prompts the need to move toward a multimodel causality analysis that could reduce biases and limitations in causal interpretations. Full article

Global warming and environmental pollution from greenhouse gas emissions are hitting an all-time high consistently year after year. In 2022, energy-related emissions accounted for 87% of the overall global emissions. The fossil fuel-based conventional power systems also need timely upgrades to improve their cycle efficiency and reduce their impact on the environment. Supercritical CO₂ systems and cycles are gaining attention because of their higher efficiencies and their compatibility with varied energy sources. The present work is a detailed overview of the recent developments in supercritical CO₂-based power generation technologies. The supercritical CO₂-based Brayton and Rankine power cycles and their improvisations in industrial applications are also discussed in detail. The advances in heat exchanger technology for supercritical CO₂ systems are another focus of the study. The energy, exergy, and economical (3E) analysis is carried out on various supercritical CO₂ power cycles reported in the literature and the data are concisely and intuitively presented. The review concludes by listing the identified directions for future technology development and areas of immediate research interest. A roadmap is proposed for easing the commercialization of supercritical CO₂ technologies to immediately address the growing challenges and concerns arising from energy-related emissions. Full article

In the continuous growth trend of global energy demand, the energy consumption of building cooling occupies a significant proportion. The utilization of alternative or partially alternative energy-input cooling methods in buildings, for example, the application of radiative cooling technology to building roofs, can effectively achieve better cooling performance. This has a positive impact on reducing energy consumption in the building field and slowing down global warming. This paper uses bibliometric analysis methods to systematically review the application of radiative cooling technology on building roofs. The development trajectory, hotspot issues, cutting-edge trends, and future research prospects in the research field over the past 20 years are analyzed and summarized. This study provides insights for the scaled application of radiative cooling technology in buildings and references for the application of radiative cooling technology in the field of architecture to reduce energy consumption, improve energy efficiency, achieve energy conservation, carbon reduction, and sustainable development. Full article

As global warming intensifies, carbon capture, utilization, and storage (CCUS) technology is widely used to reduce greenhouse gas emissions. CO₂-enhanced oil recovery (CO₂-EOR) technology has, once again, received attention, which can achieve the dual benefits of oil recovery and CO₂ storage. However, flexibly and effectively predicting the CO₂ flooding and storage capacity of potential reservoirs is a major problem. Traditional prediction methods often lack the ability to comprehensively integrate static and dynamic predictions and, thus, cannot fully understand CO₂-EOR and storage capacity. This study proposes a comprehensive deep learning framework, named LightTrans, based on a lightweight gradient boosting machine (LightGBM) and Temporal Fusion Transformers, for dynamic and static prediction of CO₂-EOR and storage capacity. The model predicts cumulative oil production, CO₂ storage amount, and Net Present Value on a test set with an average R-square (R²) of 0.9482 and an average mean absolute percentage error (MAPE) of 0.0143. It shows great static prediction performance. In addition, its average R² of dynamic prediction is 0.9998, and MAPE is 0.0025. It shows excellent dynamic prediction ability. The proposed model successfully captures the time-varying characteristics of CO₂-EOR and storage systems. It is worth noting that our model is 10⁵–10⁶ times faster than traditional numerical simulators, which once again demonstrates the high-efficiency value of the LightTrans model. Our framework provides an efficient, reliable, and intelligent solution for the development and optimization of CO₂ flooding and storage. Full article

It is well established that the reaction cycles involving some halogenated alkanes (so-called ozone-depleting substances—ODSs) contribute to the depletion of ozone in the stratosphere, prompting the Montreal Protocol (initially signed in 1987), and later amendments. The Protocol called for the scheduled phase-out of ODSs, including chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), carbon tetrachloride (CCl₄), halon, methyl chloroform (CH₃CCl₃), methyl chloride (CH₃Cl), and even hydrofluorocarbons (HFCs). In view of the urgent importance of ozone layer protection to the global ecological environment, the Taiwanese government has taken regulatory actions to reduce ODS consumption since 1993, through the joint venture of the central competent authorities. Under the government’s regulatory requirements, and the industry’s efforts to adopt both alternatives to ODSs and abatement technologies, the phase-out of some ODSs (i.e., CFCs, CCl₄, halon, and CH₃CCl₃) was achieved prior to 2010. The consumption of HCFCs and methyl chloride has significantly declined over the past three decades (1993–2022). However, HFC emissions indicated a V-type variation during this period. Due to local production and extensive use of HFCs in Taiwan, the country’s emissions increased from 663 kilotons of carbon dioxide equivalents (CO_2eq) in 1993 to 2330 kilotons of CO_2eq in 2001, and then decreased to 373 kilotons of CO_2eq in 2011. Since then, the emissions of HFCs largely used as the alternatives to ODSs showed an upward trend, increasing to 1555 kilotons of CO_2eq in 2022. To be in compliance with the Kigali Amendment (KA-2015) to the Montreal Protocol for mitigating global warming, the Taiwanese government has taken regulatory actions to reduce the consumption of some HFC substances with high global warming potential (GWP) under the authorization of the Climate Change Response Act in 2023, aiming at an 80% reduction by 2045 of the baseline consumption in 2024. Full article

No matter where we reside, the issue of greenhouse gas emissions impacts us all. Their influence has a disastrous effect on the earth’s climate, producing global warming and many other irreversible environmental impacts, even though it is occasionally invisible to the independent eye. Phase change materials (PCMs) can store and release heat when it is abundant during the day (e.g., from solar radiation), for use at night, or on chilly days when buildings need to be heated. As a consequence, buildings use less energy to heat and cool, which lowers greenhouse gas emissions. Consequently, research on thermally active medium-density fiberboard (MDF) with PCMs is presented in this work. MDF is useful for interior design and furniture manufacturing. The boards were created using pine (Pinus sylvestris L.) and spruce (Picea abies L.) fibers, urea–formaldehyde resin, and PCM powder, with a phase transition temperature of 22 °C, a density of 785 kg m⁻³, a latent heat capacity of 160 kJ kg⁻¹, a volumetric heat capacity of 126 MJ m⁻³, a specific heat capacity of 2.2 kJ kgK⁻¹, a thermal conductivity of 0.18 W mK⁻¹, and a maximum operating temperature of 200 °C. Before resination, the wood fibers were divided into two outer layers (16%) and an interior layer (68% by weight). Throughout the resination process, the PCM particles were solely integrated into the inner layer fibers. The mats were created by hand. A hydraulic press (AKE, Mariannelund, Sweden) was used to press the boards, and its operating parameters were 180 °C, 20 s/mm of nominal thickness, and 2.5 MPa for the maximum unit pressing pressure. Five variants of MDF with a PCM additive were developed: 0%, 5%, 10%, 30%, and 50%. According to the study, scores at the MOR, MOE, IB, and screw withdrawal resistance (SWR) tests decreased when PCM content was added, for example, MOE from 3176 to 1057 N mm⁻², MOR from 41.2 to 11.5 N mm⁻², and IB from 0.78 to 0.27 N mm⁻². However, the results of the thickness swelling and water absorption tests indicate that the PCM particles do not exhibit a substantial capacity to absorb water, retaining the dimensional stability of the MDF boards. The thickness swelling positively decreased with the PCM content increase from 15.1 to 7.38% after 24 h of soaking. The panel’s thermal characteristics improved with the increasing PCM concentration, according to the data. The density profiles of all the variations under consideration had a somewhat U-shaped appearance; however, the version with a 50% PCM content had a flatter form and no obvious layer compaction on the panel surface. Therefore, certain mechanical and physical characteristics of the manufactured panels can be enhanced by a well-chosen PCM addition. Full article

Amidst the escalating threat of global warming, which manifests in more frequent forest fires, the prompt and accurate detection of forest fires has ascended to paramount importance. The current surveillance algorithms employed for forest fire monitoring—including, but not limited to, fixed threshold algorithms, multi-channel threshold algorithms, and contextual algorithms—rely primarily upon the degree of deviation between the pixel temperature and the background temperature to discern pyric events. Notwithstanding, these algorithms typically fail to account for the spatial heterogeneity of the background temperature, precipitating the consequential oversight of low-temperature fire point pixels, thus impeding the expedited detection of fires in their initial stages. For the amelioration of this deficiency, the present study introduces a spatial feature-based (STF) method for forest fire detection, leveraging Himawari-8/9 imagery as the main data source, complemented by the Shuttle Radar Topography Mission (SRTM) DEM data inputs. Our proposed modality reconstructs the surface temperature information via selecting the optimally designated machine learning model, subsequently identifying the fire point through utilizing the difference between the reconstructed surface temperatures and empirical observations, in tandem with the spatial contextual algorithm. The results confirm that the random forest model demonstrates superior efficacy in the reconstruction of the surface temperature. Benchmarking the STF method against both the fire point datasets disseminated by the China Forest and Grassland Fire Prevention and Suppression Network (CFGFPN) and the Wild Land Fire (WLF) fire point product validation datasets from Himawari-8/9 yielded a zero rate of omission errors and a comprehensive evaluative index, predominantly surpassing 0.74. These findings show that the STF method proposed herein significantly augments the identification of lower-temperature fire point pixels, thereby amplifying the sensitivity of forest surveillance. Full article

To limit global warming to 1.5 °C, it is imperative to accelerate the global energy transition. This transition is crucial for solving the climate issue and building a more sustainable future. Therefore, within the loaded capacity curve (LCC) theory framework, this study investigates the effects of digital adaptation, energy transition, export diversification, and income inequality on the load capacity factor (LCF). This study also attempts to investigate the integration effects of digital adaptation and energy transition, and digital adaptation and export diversification, on LCF. Furthermore, we explored how income inequality influences the LCF in economies. For this study, 112 countries were selected based on the data availability. Panel data from 2010 to 2021 were analyzed using the STATA software 13 application utilizing a two-step system generalized method of moments (GMM) approach. First, interestingly, our finding shows that digital adaptation and income significantly affect the LCF. An increase in income increases the LCF among the middle-income group of countries. Therefore, LCC is confirmed in this research. Surprisingly, energy transition, export diversification, and foreign direct investment negatively impact the LCF in the base model. Second, the impact of integrating digital adaptation and energy transition has a positive effect on LCF. Third, a negative correlation was observed between the interaction of export diversification and digital adaptation with the LCF. Fourth, a positive correlation was observed between the interaction of renewable energy and digital adaptation with the LCF. Finally, this study explores the impact of the energy transition, export diversification, and income inequality on the LCF with reference to the Organization of Petroleum Exporting Countries (OPEC). The result shows a negative effect between export diversification and LCF among OPECs at a 10% significance level. To improve the quality of our planet, policymakers must understand the forces causing climate change. By adopting a comprehensive perspective, the study aims to understand how these interrelated factors collaboratively influence the LCF thoroughly. Additionally, this research seeks to provide valuable insights related to energy transition, digital adaptation, and export diversification to policymakers, researchers, and stakeholders regarding possible avenues for cultivating a more joyful and sustainable global community. Full article

Radial tree growth at high-elevation and high-latitude sites is predominantly controlled by changes in summer temperature. This relationship is, however, expected to weaken under projected global warming, which questions the reliability of tree-ring chronologies for climate reconstructions. Here, we examined the growth–climate response patterns of five tree-ring width (TRW) and maximum latewood density (MXD) chronologies of larch (Larix sibirica) from upper-treeline ecotones in the Altai Mountains, which is a key region for developing millennial-long dendroclimatic records in inner Eurasia. The TRW and MXD chronologies exhibited significant year-to-year coherency within and between the two parameters (p < 0.001). While TRW is mostly influenced by temperature changes during the first half of the growing season from June to July (r = 0.66), MXD is most strongly correlated with May–August temperatures (r = 0.73). All seasonal temperature signals are statistically significant at the 99% confidence level, temporally stable back to 1940 CE, the period with reliable instrumental measurements, and spatially representative for a vast area of inner Eurasia between northeastern Kazakhstan in the west, northern Mongolia in the east, southern Russia in the north and northwestern China in the south. Our findings demonstrate the paleoclimatic potential of TRW and especially MXD chronologies and reject any sign of the ´divergence problem´ at these high-elevation, mid-latitude larch sites. Full article

The future of humanity depends on successfully adapting key cropping systems for food security, such as corn (Zea mays L.), to global climatic changes, including changing air temperatures. We monitored the effects of climate change on harvested yields using long-term research plots that were established in 2001 near Fort Collins, Colorado, and long-term average yields in the region (county). We found that the average temperature for the growing period of the irrigated corn (May to September) has increased at a rate of 0.023 °C yr⁻¹, going from 16.5 °C in 1900 to 19.2 °C in 2019 (p < 0.001), but precipitation did not change (p = 0.897). Average minimum (p < 0.001) temperatures were positive predictors of yields. This response to temperature depended on N fertilizer rates, with the greatest response at intermediate fertilizer rates. Maximum (p < 0.05) temperatures and growing degree days (GDD; p < 0.01) were also positive predictors of yields. We propose that the yield increases with higher temperatures observed here are likely only applicable to irrigated corn and that irrigation is a good climate change mitigation and adaptation practice. However, since pan evaporation significantly increased from 1949 to 2019 (p < 0.001), the region’s dryland corn yields are expected to decrease in the future from heat and water stress associated with increasing temperatures and no increases in precipitation. This study shows that increases in GDD and the minimum temperatures that are contributing to a changing climate in the area are important parameters that are contributing to higher yields in irrigated systems in this region. Full article

Among the most debated environmental effects of global warming is sea level rise, whose consequences are believed to exert a large influence on vast coastal areas in the next decades and hence contribute to determining near-future societal developments. The observed variability of the sea level is complex, as it is composed of large inhomogeneous, mostly nonlinear temporal and spatial fluctuations. In the Mediterranean Sea, multiannual as well as multidecadal sea level variability is observed, which has been ascribed to different steric and non-steric phenomena. Possible tipping points, uncertain climate feedback, and future human policies contribute to rendering sea level rise predictability intricate. Here, for the first time, correlations between observed and simulated data demonstrates that, in the Mediterranean Sea, oceanic intrinsic variability merely induced by the steady motion of the water masses inflowing and outflowing the basin is able to produce multiannual, sub-basin SSH variability consistent with altimetrically observed SSH. This study contributes to the recognition of the role played by steadily induced oceanic intrinsic variability in the observed long-term Mediterranean dynamics and paves the way to establish a better constraint to the uncertainties inherent in sea level rise predictability. Full article

The brown marmorated stink bug Halyomorpha halys (Stål, 1855), native to East Asia, is an extremely polyphagous pest that infests more than 300 plant species from 49 families. In Europe and North America, this pest causes enormous damage to the production of economically important crops (tree fruit, vegetables, field crops, and ornamental plants). Global warming favours its spread, as the rise in temperature results in the appearance of further generations of the pest. Halyomorpha halys (nymph and adult) causes damage typical of the Pentatomidae family by attacking host plants throughout their development (buds, stems, fruits, and pods). Ripe fruits are often disfigured, and later suberification and necrotic spots form on the fruit surface, making them accessible to plant pathogens that cause fruit rot and rendering them unmarketable. The increasing global importance of the pest suggests that more coordinated measures are needed to contain its spread. Understanding the biology and ecology of this species is crucial for the development of reliable monitoring and management strategies. Most insecticides available for the control of H. halys have a broad spectrum of modes of action and are not compatible with most integrated pest management systems, so biological control by natural enemies has recently been emphasised. Preventing excessive population growth requires early identification and effective control measures that can be developed quickly and applied rapidly while respecting the environment. This paper presents a comprehensive review of the latest findings on the global distribution of this important pest, its potential spread, biology and ecology, key host plants of economic importance, monitoring methods, and effective biological control strategies, as well as future perspectives for sustainable H. halys control measures. Full article

Carbon use efficiency (CUE) was identified as a pivotal parameter for elucidating the carbon cycle within ecosystems. It signified the efficiency with which light energy was transformed into organic matter by vegetation. In light of the challenges posed by global warming, it was deemed essential to gain a comprehensive understanding of the fluctuations and determinants of CUE. Despite the significance of this topic, the current research on factors influencing CUE remained incomplete, notably lacking in exploration of the impacts of ecological engineering on CUE. The objective of this study is to elucidate the influences of climate change and ecological engineering on CUE, quantifying their effects using residual analysis. Additionally, it aims to analyze the primary factors contributing to the fluctuations in CUE. Our findings indicated an average CUE of 0.8536 (±0.0026) with minor interannual variation. In the Three Rivers Source region, CUE is jointly influenced by ecological engineering (30.88%) and climate change (69.12%). Notably, climatic factors predominantly regulate CUE, accounting for approximately 90.20% of its regional variations, with over 44.70% of areas exhibiting contributions exceeding 80%. Moreover, the impact of evapotranspiration on CUE surpasses that of precipitation and temperature, while factors such as elevation and vegetation types also play significant roles. This study showed the quantification of climate change and ecological engineering effects on CUE, which would hold substantial implications for predicting and evaluating global carbon cycling. Full article

Global warming and climate change cause large temperature oscillations and uneven annual rainfall patterns. The rainy cycles characterized by frequent high-intensity rainfall in the area of the Stubo–Rovni water reservoir, which in 2014 peaked at 129 mm of water in 24 h (the City of Valjevo, the Republic of Serbia), caused major floods in the wider area. Such extremes negatively affect erosion processes, sediment production, and the occurrence of flash floods. The erosion coefficient before the construction of the water reservoir was Z_m = 0.40, while the specific sediment production was about 916.49 m³∙km⁻²∙year⁻¹. A hydrological study at the profile near the confluence of the Jadar and Obnica rivers, i.e., the beginning of the Kolubara river, the right tributary of the Sava (in the Danube river basin), indicates that the natural riverbed can accommodate flows with a 20% to 50% probability of occurrence (about 94 m³/s), while centennial flows of about 218 m³/s exceed the capacities of the natural riverbed of the Jadar river, causing flooding of the terrain and increasing risks to the safety of the population and property. The paper presents the impacts of the man-made Stubo–Rovni water reservoir on the catchment area and land use as the primary condition for preventing erosion processes (specific sediment production has decreased by about 20%, the forest cover increased by about 25%, and barren land decreased by 90%). Moreover, planned and controlled management of the Stubo–Rovni reservoir has significantly influenced the downstream flow, reducing the risks of flash floods. Full article