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Isoprene and monoterpene emissions to the atmosphere are generally dominated by biogenic sources. The oxidation of these compounds can lead to the production of secondary organic aerosol; however the impact of this chemistry in polluted urban settings has been poorly studied. Isoprene and monoterpenes can form secondary organic aerosol (SOA) heterogeneously via anthropogenic–biogenic interactions, resulting in the formation of organosulfate (OS) and nitrooxy-organosulfate (NOS) species. Delhi, India, is one of the most polluted cities in the world, but little is known about the emissions of biogenic volatile organic compounds (VOCs) or the sources of SOA. As part of the DELHI-FLUX project, gas-phase mixing ratios of isoprene and speciated monoterpenes were measured during pre- and post-monsoon measurement campaigns in central Delhi. Nocturnal mixing ratios of the VOCs were substantially higher during the post-monsoon (isoprene: (0.65±0.43) ppbv; limonene: (0.59±0.11) ppbv; α-pinene: (0.13±0.12) ppbv) than the pre-monsoon (isoprene: (0.13±0.18) ppbv; limonene: 0.011±0.025 (ppbv); α-pinene: 0.033±0.009) period. At night, isoprene and monoterpene concentrations correlated strongly with CO during the post-monsoon period. Filter samples of particulate matter less than 2.5 µm in diameter (PM2.5) were collected and the OS and NOS content analysed using ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS2). Inorganic sulfate was shown to facilitate the formation of isoprene OS species across both campaigns. Sulfate contained within OS and NOS species was shown to contribute significantly to the sulfate signal measured via AMS. Strong nocturnal enhancements of NOS species were observed across both campaigns. The total concentration of OS and NOS species contributed an average of (2.0±0.9) % and (1.8±1.4) % to the total oxidized organic aerosol and up to a maximum of 4.2 % and 6.6 % across the pre- and post-monsoon periods, respectively. Overall, this study provides the first molecular-level measurements of SOA derived from isoprene and monoterpene in Delhi and demonstrates that both biogenic and anthropogenic sources of these compounds can be important in urban areas.

PM2.5 pollution in India increases severely during the winter season due to adverse meteorological conditions and shows comparatively higher pollution loading in Indo-Gangetic Plain (IGP). However, investigation of the role of major sources and different states of IGP in local and regional higher PM2.5 pollution for effective formulation of mitigation policies has been limited. In this study, the Weather Research and Forecasting model coupled with chemistry (WRF-Chem v 3.9.1) was used to quantify the contribution of emissions from major source sectors and source regions of IGP to local and regional PM2.5 pollution during winter. The short-term premature mortality and its apportionment has also been estimated. Contributions from seven source states of the IGP to local and regional PM2.5 pollution at eight major cities of the IGP have been investigated. The residential and transport sector emerge as leading contributors with ~40–50% share in ambient PM2.5 pollution over IGP, whereas the contributions of the industrial (~5–20%) and energy sectors (~5–40%) varies significantly across the IGP. While the contributions of local sources were found to dominate in all IGP states, significant contributions were also seen from neighboring IGP states. At megacity Delhi, significant contribution in local PM2.5 pollution was observed by transportation (~49%) and energy (~24%) sectors, and at Kolkata, it was from residential (~48%) and industrial (~24%) sectors. January 2016 mean short-term premature mortality estimates for Delhi and Kolkata are found 61(33–91) and 44(23–64) persons/day, respectively, with local sources contributions of 40(21–58) and 29(15–42) persons/day, respectively.

Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India, has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as a result of anthropogenic activities. Organic aerosols (OAs) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and their processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, where we would expect the apportionment and concentrations to vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need for multisite measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulfate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of volatile organic compounds, black carbon, NOx and CO were performed. Positive matrix factorisation (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OAs (HOAs) related to traffic emissions, biomass burning OAs (BBOAs), cooking OAs (COAs) and secondary OAs (SOAs). A composition-based estimate of PM1 is defined by combining black carbon (BC) and NR-PM1 (C-PM1= BC + NR-PM1). No significant difference was observed in C-PM1 concentrations between sites, OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42- showed a high contribution over pre-monsoon and monsoon seasons, while NO3- and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and Aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls, traffic emission control offers the greatest opportunity. PMF–aerosol mass spectrometer (AMS) mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

The quantitative assessment of health burden of coal power stack emissions is a vital step to frame effective policy measures to achieve emission reductions and corresponding health benefits. A plant-specific stack emission, dispersion, and health risk integrated (SEHRI) model has been proposed to estimate coal power stack emissions, resulting ambient air concentrations and associated health risks in the vicinity of a coal power plant. In this study, we have estimated the health benefits due to closure of Badarpur Thermal Power Station (BTPS), New Delhi. The SEHRI model has been applied to estimate decreased health risks due to particulates (PM2.5) and gaseous (SO2, NOx) stack emissions released from the plant. More than 1050 premature deaths are avoided and 526 life years are saved resulting from reduction in particulate and gaseous stack emissions, respectively, due to closure of the plant. It is expected that environmental engineers, scientists, and air quality managers would find the SEHRI model as a useful tool to study emissions and health impacts related to coal-based power plants and guide an effective control policy for air pollution abatement.

The present study aims to assess the air quality status in the central library of Indian Institute of Technology Roorkee, India. Pollutants concentrations (i.e. PM10, PM2.5, PM1 and TVOC) and comfo...

Sludge treatment and disposal used to be considered part of water and wastewater treatment, rather than a separate subject, but is now seen as an independent field of study, research and development. This book is the first text and reference volume on the subject, aiming to provide a comprehensive coverage of basic principles, methods and the advanced practices of sludge treatment and its safe disposal. The book focuses on those aspects of sludge treatment and disposal, particularly in relation to the environment and economy. Based on its inter-disciplinary approach, comprehensive scope and practical case studies and technical illustrations, this book can be recommended as a resource for students, teachers and practising engineers working in the area of water and wastewater treatment, and sludge treatment and disposal in particular.

The Indian megacity of Delhi suffers from some of the poorest air quality in the world. While ambient NO2 and particulate matter (PM) concentrations have received considerable attention in the city, high ground level ozone (O3) concentrations are an often overlooked component of pollution. O3 can lead to significant ecosystem damage, agricultural crop losses, and adversely affect human health. During October 2018, concentrations of speciated non-methane hydrocarbons volatile organic compounds (C2 – C13), oxygenated volatile organic compounds (o-VOCs), NO, NO2, HONO, CO, SO2, O3, and photolysis rates, were continuously measured at an urban site in Old Delhi. These observations were used to constrain a detailed chemical box model utilising the Master Chemical Mechanism v3.3.1. VOCs and NOx (NO + NO2) were varied in the model to test their impact on local O3 production rates, P(O3), which revealed a VOC-limited chemical regime. When only NOx concentrations were reduced, a significant increase in P(O3) was observed, thus VOC co-reduction approaches must also be considered in pollution abatement strategies. Of the VOCs examined in this work, mean morning P(O3) rates were most sensitive to monoaromatic compounds, followed by monoterpenes and alkenes, where halving their concentrations in the model led to a 15.6 %, 13.1 % and 12.9 % reduction in P(O3), respectively. P(O3) was not sensitive to direct changes in aerosol surface area but was very sensitive to changes in photolysis rates, which may be influenced by future changes in PM concentrations. VOC and NOx concentrations were divided into emission source sectors, as described by the EDGAR v5.0 Global Air Pollutant Emissions and EDGAR v4.3.2_VOC_spec inventories, allowing for the impact of individual emission sources on P(O3) to be investigated. Reducing road transport emissions only, a common strategy in air pollution abatement strategies worldwide, was found to increase P(O3), even when the source was removed in its entirety. Effective reduction in P(O3) was achieved by reducing road transport along with emissions from combustion for manufacturing and process emissions. Modelled P(O3) reduced by ~20 ppb h−1 when these combined sources were halved. This study highlights the importance of reducing VOCs in parallel with NOx and PM in future pollution abatement strategies in Delhi.

Vehicular pollution is one of the major sources of air pollution in urban locales that have reportedly elevated concentrations of air pollutants. This study aims to examine the performance...

Megacities (metropolitan areas with populations over 10 million) and large urban centers present a major challenge for the global environment. Transportation, industrial activities, and energy demand have increased in megacities due to population growth and unsustainable urban development, leading to increasing levels of air pollution that subject the residents to the health risks associated with harmful pollutants, and impose heavy economic and social costs. Although much progress has been made in reducing air pollution in developed and some developing world megacities, there are many remaining challenges in achieving cleaner and breathable air for their residents. As centers of economic growth, scientific advancement, and technology innovation, however, these urban settings also offer unique opportunities to capitalize on the multiple benefits that can be achieved by optimizing energy use, reducing atmospheric pollution, minimizing greenhouse gas emissions, and bringing many social benefits. Realizing such benefits will, however, require strong and wide-ranging institutional cooperation, public awareness, and multi-stakeholder involvement. This is especially critical as the phenomenon of urbanization continues in virtually all countries of the world, and more megacities will be added to the world, with the majority of them located in developing countries. The air quality and emission mitigation strategies of eight megacities—Mexico City, Beijing, Shanghai, Shenzhen, Chengdu, Delhi, Kolkata, and Mumbai—are presented as examples of the environmental challenges experienced by large urban centers. While these megacities share common problems of air pollution due to the rapid growth in population and urbanization, each city has its own unique circumstances—geographical location, meteorology, sources of emissions, human and financial resources, and institutional capacity—to address them. Nevertheless, the need for an integrated multidisciplinary approach to air quality management is the same. Mexico City’s air pollution problem was considered among the worst in the world in the 1980s due to rapid population growth, uncontrolled urban development, and energy consumption. After three decades of implementing successive comprehensive air quality management programs that combined regulatory actions with technological change and were based on scientific, technical, social, and political considerations, Mexico City has made significant progress in improving its air quality; however, ozone and particulate matter are still at levels above the respective Mexican air quality standards. Beijing, Shanghai, Shenzhen, and Chengdu are microcosms of megacities in the People’s Republic of China, with rapid socioeconomic development, expanding urbanization, and swift industrialization since the era of reform and opening up began in the late 1970s, leading to severe air pollution. In 2013, the Chinese government issued the Action Plan for Air Pollution Prevention and Control. Through scientific research and regional coordinated air pollution control actions implemented by the Chinese government authority, the concentration of atmospheric pollutants in several major cities has decreased substantially. About 20% of total megacities’ populations in the world reside in Indian megacities; the population is projected to increase, with Delhi becoming the largest megacity by 2030. The increased demands of energy and transportation, as well as other sources such as biomass burning, have led to severe air pollution. The air quality trends for some pollutants have reduced as a result of emissions control measures implemented by the Indian government; however, the level of particulate matter is still higher than the national standards and is one of the leading causes of premature deaths. The examples of the eight cities illustrate that although most air pollution problems are caused by local or regional sources of emissions, air pollutants are transported from state to state and across international borders; therefore, international coordination and collaboration should be strongly encouraged. Based on the available technical-scientific information, the regulations, standards, and policies for the reduction of polluting emissions can be formulated and implemented, which combined with adequate surveillance, enforcement, and compliance, would lead to progressive air quality improvement that benefits the population and the environment. The experience and the lessons learned from the eight megacities can be valuable for other large urban centers confronting similar air pollution challenges.