Dr. Sneha Gautam

On entering the Earth's atmosphere, a large amount of solar radiation gets absorbed and scattered by aerosols, clouds, atmospheric gases, and Earth's surface. In this context, we discuss an approach to characterize the sky conditions using ground-based observations of solar radiation. The proposed approach is applied to the measured solar radiation for the duration 16 October 2018 to 31 December 2019, at Himalayan Clouds Observatory (HCO), which is situated at Swami Ram Tirtha (SRT) Campus (30°34 0 N, 78°41 0 E) Badshahithaul, Tehri Garhwal, Uttarakhand, India. The present work demonstrates the variation in Clearness Index (K T) associated with Global Horizontal Radiation (H a), Extraterrestrial Horizontal Radiation (H o) and associated variability of Aerosol Optical Depth (AOD), Angstrom Exponent (AE) and fine particles (PM 2.5 (lg m-3)) in different sky conditions. Most of the period of 2018 shows clear sky (81.82%) as compared to partially cloudy (4.29%) and cloudy (3.9%) days. Whereas only 20.89% days having clear sky, 38.38% as partially cloudy sky and 34.73% as cloudy sky conditions were observed during 2019. From the variance of H a and K T , we obtained minimum values in the monsoon and winter from which we get cloudier condition in these seasons. AOD and PM 2.5 remains lower in clear sky condition and highest in cloudy condition due to several atmospheric factors. Also, the AE of cloudy cases is marginally lower, implying larger particles, most likely due to swelling in humid conditions. Finally, we observed that the negative correlation between AOD and AE which indicates the swelling particles nearby cloudy region. Similarly, a positive correlation between AOD and PM 2.5 indicates the sources of air pollution can influence aerosol loading for all sky conditions.

The outbreak of the COVID-19 pandemic has significantly increased the demand for personal protective equipment, in particular face masks, thus leading to a huge amount of healthcare waste generated worldwide. Consequently, such an unprecedented amount of newly emerged waste has posed significant challenges to practitioners, policy-makers, and municipal authorities involved in waste management (WM) systems. This research aims at mapping the COVID-19-related scientific production to date in the field of WM. In this vein, the performance indicators of the target literature were analyzed and discussed through conducting a bibliometric analysis. The conceptual structure of COVID-19-related WM research, including seven main research themes, were uncovered and visualized through a text mining analysis as follows: (1) household and food waste, (2) personnel safety and training for waste handling, (3) sustainability and circular economy, (4) personal protective equipment and plastic waste, (5) healthcare waste management practices, (6) wastewater management, and (7) COVID-19 transmission through infectious waste. Finally, a research agenda for WM practices and activities in the post-COVID-19 era was proposed, focusing on the following three identified research gaps: (i) developing a systemic framework to properly manage the pandemic crisis implications for WM practices as a whole, following a systems thinking approach, (ii) building a circular economy model encompassing all activities from the design stage to the implementation stage, and (iii) proposing incentives to effectively involve informal sectors and local capacity in decentralizing municipal waste management, with a specific focus on developing and lessdeveloped countries.

Corona virus diseases-2019 (COVID-19), an infectious disease identified in late December, 2019, in Wuhan city of China, was declared a pandemic by the World Health Organization. Most countries including India have announced some sort of lockdown to reduce the effects of COVID-19 and discontinue the transmission of novel coronavirus. Major negative effects on the social and surrounding environment have been reported due to COVID-19, however positive effects have also been observed with respect to air quality. Secondary results have been taken from National Aeronautics and Space Administration (NASA), indicating significant reduction (50%) in air quality of Indian region. This perspective highlights the effects of the lockdown due to COVID-19 on aerosol optical thickness specifically in India.

Coronavirusdiseases2019(COVID-19)istransmittedworldwideinoveraveryshorttime,asitwasoriginatedinlate2019from Wuhancity,China.ToreducethepossibleeffectsduetoCOVID-19,somesortoflockdownactivitieshavebeenappliedinmany countries. In this regard, the outcomes reported bonus benefits to the natural environment showing a significant decrease in air pollution worldwide due to COVID-19. The National Aeronautics and Space Administration (NASA) and European Space Agency (ESA) released air pollution data for Asian and European countries to assess the significant changes in air quality. The main objective of the study is to compare the air quality data released by international agencies before and after the novel coronavirus pandemic.

Exposure to atmospheric particulate matter is still a serious concern in the developing countries, as the incremental concentrations of PM 10 continues to exceed. Limited literature has been reported on spatial-temporal variability of PM 10 and its relationship with vegetation using remote sensing and Geographical Information Systems (GIS) techniques. The data for the study were collected in four geographically distinct areas (i.e., Adyar, Anna Nagar, Kilpauk and T. Nagar)in the fourth largest urban agglomeration, Chennai city, India during 2013 to 2018. The spatial variability has been identified for PM 10 in selected locations, as well as concentration variation in different seasons was also investigated. It was observed that the levels of PM 10 pollution were higher within vicinity of the industrial zone. However, the seasonal variation especially dry monsoon season effect makes the level higher in concentration. The changes in vegetative cover in the study area were studied using Landsat-8 imageries for the period 2013-2018. The Landsat-8 imageries were used to obtain the normalized difference vegetation index (NDVI), which aids in studying the vegetative cover. The study shows that with increase in NDVI values there is a decrease in the concentration of particulate matter. This shows that measures need to be taken in the study area to increase the vegetative cover, so that the effect of pollutants can be alleviated in the atmosphere.

The landfilling method is one of the best method of final disposal / treatment of solid waste globally. In India, 68.8-million-ton year solid waste are generated and 35% of the solid waste is generally sent to landfills only. By using vector data and remote sensing (RS), the rank algorithm is proposed in this study for identification of possible landfill sites and its expansion in Coimbatore, south India, where 75% of municipal solid waste are dumped without treatment. From the study, it is observed that 17% of the study area was identified as good, moderate and least or unsuitable for landfill expansion. Polygon 6, representing grazing/ agriculture land, is found to be most appropriate for the landfill expansion according to standard deviation from normalized indices, it is ranked 3rd among the 24 polygons in the target area. From this study, it is observed that 25% of the polygons were least suitable and 29% of the total target area was found to more suitable for landfill expansion, as per standard deviation. This method provides comparable results with other decision-making tools. The proposed method is purely based on RS and vector data, moreover its very flexible and if so desired, it can be used by policy makers.

The aim of the study is to estimate the particle concentration variation across different working levels inside an opencast mine. The study was conducted in one of the deep opencast copper mines in India to estimate the distribution of different size of particles emitted from the operations concentrated in deeper parts of the mine. Moreover, with advancement of SPSS (version 25), the analytical techniques were used to identify the exposuretodifferentsizeofparticleduringminingoperations.Weintroducedthespatial statisticandgraphtheoryinthefieldofairpollutiontounderstandtheparticledistribution. The combination of correlation and one-way ANOVA statistical methods were used to estimate the impact of depth of mine as a critical factor on distribution of particle concentration. The outcomes of the study shows that spatial statistics, correlation, onewayANOVAandgraphtheorycanbeusedtounderstandthedistributionpattern(shortestroutetotravel),toestimateconcentrationatdifferentlevel,andtobetterunderstandmine workersexposuretoparticlematter.

The present study quantifies the personal exposure to air pollutants (i.e., PM2.5, PM10, CO2, and CO) and its bound chemical constituents during bonfire activities occurring in rural area of Gujarat, India. The study was performed during the late 2017 and early 2018 winter season, when bonfires are a very common practice. Three major sites, viz., University Reception Area (URA), Workshop Area (WSA), and Hostel Wing-A (HWA) were delineated to reveal discrete patches of personal exposure. Particulate matters, gaseous pollutants, and associated ionic constitutes were analyzed by an air quality monitor and ion chromatography. The concentration profile of PM2.5, PM10, and CO were found in the range between 81–206, 188–282, and 2.8–5.8 µgm−3, respectively, at the study area which are more than the permissible limit. The major ions such as Na+, K+, Ca2+ Mg2+, NH4+, Cl−, Br−, NO2−, NO3−, PO42−, and SO42− were obtained on particulate matter. Based on this observation it is concluded that if personal exposure to these pollutants increases, then metabolic activities may change and lead to severe diseases, viz., asthma, rhinitis, tuberculosis. It is a grave concern for the WHO to improve the human health and eradicate the communal diseases under sustainable development goals. Henceforth, it is mandatory to understand the variations of air pollutants at workplace and the associated exposure to individuals.

A B S T R A C T Bioaerosol is a particulate mixture of solid and semi-solid matter combined with biotic matter like pollens, microbes and their fragments. The present review stresses on a cumulative understanding of sources, components , quantification and distribution of bioaerosols with respect to size, and its significant impacts on human health. The present review will be instrumental in devising strategies to understand and manage bioaerosols and reducing their human exposure and associated health hazards. The present review aims explore the relationship between particle and associated biological agents responsible for behaviours like dispersal, total potential health hazards and toxicology level during exposure to bioaerosol.

In the present study, an integrated fixed-film activated sludge (IFAS) bioreactor was subjected to dissimilar intermittent aeration (IA) cyclic operations, and its effects were investigated on extracellular polymeric substances (EPS) production, sludge characteristics, and specific power consumption. A total of three IAcycles (IA1, 150min aeration on and 30min off; IA2, 120min aeration on and 60min off; IA3, 90min aeration on and 60min off) were evaluated in the present IFAS reactor. Specific EPS production (mg/g of suspended solids) was found to be following the increasing trend with respect to the non-aeration to aeration time ratio, whereas, the sludge production followed the reverse trend. The amount of bound EPS was observed to be much higher (6–10 times) than soluble microbial product (SMP) in each intermittent aeration phase. During all the investigated IA cycles, the pilot was observed to be significantly affected in terms of biomass characteristics, which was also confirmed by increasing trends of sludge volume index (SVI) and filamentous index (FI) values. In-situ monitoring and measurement of reactor operation parameters such as pH, oxidation reduction potential (ORP), and dissolved oxygen (DO) was also done in all IA cycles. A maximum of 27.05% reduction in electrical energy was observed in highest non-aeration period cycle.

Exposure to harmful by-products of combustion arising from the use of biomass fuels for cooking and heating in rural areas of developing countries results in poor air quality and is responsible for millions of deaths yearly. Little formal quantification and measurement of carbon monoxide (CO), one of these harmful air pollutants, have been performed in rural areas of North India. In the current study, we measured exposure to CO from cooking and heating in seven households using biomass and liquid petroleum gas (LPG) in open and closed kitchens. Exposures to CO ranged from 4.81 to 7.01, 0.20 to 1.81, and 0.02 to 0.75 mg m−3 for households cooking with biomass, cooking with LPG, and for households in which no cooking occurred, respectively. It was observed that the CO concentration in biomass-only households is much higher (78%) than in LPG-only households (14%). We found exposures in closed kitchens approximately two times higher than in open kitchens. Location of the kitchen (i.e., open vs. closed) was the most important determinant of exposure of primary cooks to CO in this geography.

The ambient fine particulate matter is a considerable hazard to human health and the surrounding environment of the majority of Chinese cities. This article reviews the status of air pollution, especially  PM2.5, in 21 cities of China, on the basis of their status, chemical characteristics, and regulations data collected from the published literature. The observed results show Zhengzhou, Yulin, Jinan, Qingdao, and Changchun as significantly polluted cities where the annual mean concentration of  PM2.5 was noted to be greater than 120 µg m−3. However, some cities such as Xiamen, Hong Kong, Shenzhen, and Jinchang reported average annual  PM2.5 concentrations less than 40 µg m−3. In general, the results of spatial distribution reported that the cities of the east, north, and northeast China are highly polluted. According to the average mass of  PM2.5 in maximum cities of China, the sum of sulfate, nitrate and ammonium (SNA) and organic matter (OM) contributed over 40 and 35%, respectively. The higher amount of SNA and OM in  PM2.5 results from heavy traffic or vehicle emission and burning solid fuel utilized in most part of China. A proposed systemic approach to address the  PM2.5 in China can improve the quality of ambient atmosphere.

Bioaerosol is a particulate mixture of solid and semi-solid matter combined with biotic matter like pollens, microbes and their fragments. The present review stresses on a cumulative understanding of sources, components, quantification and distribution of bioaerosols with respect to size, and its significant impacts on human health. The present review will be instrumental in devising strategies to understand and manage bioaerosols and reducing their human exposure and associated health hazards. The present review aims explore the relationship between particle and associated biological agents responsible for behaviours like dispersal, total potential health hazards and toxicology level during exposure to bioaerosol.