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A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO 2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006–2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%–43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia. [Display omitted] • Sulfate emission reduces Indian summer monsoon precipitation through aerosol-radiation and aerosol-cloud interactions. • Over 27% of the summer monsoon rainfall deficit in a normal year are linked to Asian anthropogenic sulfate emissions. • Sulfate-induced rainfall reduction is the maximum for La Niña year. • SO 2 loading increases atmospheric stability and weakens moisture transport to India. [ABSTRACT FROM AUTHOR]

In the past few decades, many urban areas around the world have suffered from severe air pollution and the health hazards that come with it, making gathering real-time air quality and air quality forecasting very important to take preventive and corrective measures. This paper proposes a scalable architecture to monitor and gather real-time air pollutant concentration data from various places and to use this data to forecast future air pollutant concentrations. Two sources are used to collect air quality data. The first being a wireless sensor network that gathers and sends pollutant concentrations to a server, with its sensor nodes deployed in various locations in Bengaluru city in South India. The second source is the real-time air quality data gathered and made available by the Government of India as a part of its Open Data initiative. Both sources provide average concentrations of various air pollutants on an hourly basis. Due to its proven track record of success with time-series data, a Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) model was chosen to perform the task of air quality forecasting. This paper critically analyses the performance of the model in two regions that exhibit a significant difference in temporal variations in air quality. As these variations increase, the model suffers performance degradation necessitating adaptive modelling. [ABSTRACT FROM AUTHOR]

Air pollution control has emerged as one of the key concerns of recent times and business firms are one of the significant stakeholders in deteriorating the quality of the natural environment. The purpose of this paper is to analyse the factors affecting the adoption of air pollution control measures across firms and contribute to the existing knowledge on pollution control among firms in the context of an emerging market. The analysis shows a significant association between enterprise characteristics and the adoption of air pollution control measures and about 44.3 percent firms have reported the adoption of air pollution control measures. Further, the marginal effect analysis indicates that firms older in age, larger in size and having shareholders' equity are more likely to adopt air pollution control measures. Similarly, firms practising lean operations, investing in research & development, availing bank credit, having quality certification and having better capacity utilisation are more likely to adopt air pollution control measures. Finally, firms perceiving obstacles related to business licensing & permits, tax administration, political instability, and business closure due to COVID-19 outbreak are more likely to adopt air pollution control measures. Our study provides useful implications for managers, policymakers and researchers for encouraging air pollution control technologies across business firms. The study also motivates undertaking future research on pollution control measures across various sectors of the economy. [Display omitted] • Air pollution control is becoming a critical agenda across the globe. • About 44.3 percent Indian firms reported the adoption of air pollution control measures. • Firms' characteristics are significantly associated with adopting air pollution control measures. • Business operations, regulatory mechanisms and obstacles influence the adoption of air pollution control measures. • These insights help develop strategies for reducing air pollution by involving managers, policymakers and researchers. [ABSTRACT FROM AUTHOR]

Abstract: Every year during the winter and pre-monsoon periods most of the Indian peninsula, Bay of Bengal and the adjoining Indian Ocean are affected by a polluted regional haze, known as the South Asian Winter Haze (SAWH). This article is the first of a series of three papers collectively anticipated at the central idea of retrieving aerosol component type and effective radius of the SAWH by incorporating experimental data of ground-based solar radiometer into Mie theory, and validation by collocated in-situ measurements. The work presented in this paper provides an approach to retrieve optical depths and their spectral curvature for SAWH at a tropical coastal station, Visakhapatnam (17.7°N, 83.3°E). A dataset comprised of 92 wintertime atmospheric optical depths are obtained from spectral extinction measurements of direct solar flux by means of a Multi-Wavelength Solar Radiometer during the period of October 2002 to February 2004. The inter-channel correlations established a linear relation and the airmass conditions specific to this dataset suggested a two-component linear model; the stable and variable components of which are analysed to obtain the mentioned optical parameters. Results indicate that the spectral curvature is best represented by a Lorentz model with a central wavelength of 0.40425±0.02945μm, a width of 0.40382±0.10253μm, a constant of 0.92623±0.33793, and a wavelength independent component of 0.95778±0.15678. Resonance-like structure of the obtained spectral curvature resembles wavelength dependent extinction characteristic of absorbing soot particles; thereby supports the key findings from INDOEX campaign. [Copyright &y& Elsevier]

Air pollution in the form of particulate matter (PM) is becoming one of the greatest current threats to human health on a global scale. This paper firstly presents a Bayesian space–time hierarch piecewise regression model (BSTHPRM) which can self-adaptively detect the transitions of local trends, accounting for spatial correlations. The spatiotemporal trends of the approximately anthropogenic PM 2.5 removed natural dust (PM 2.5_No Dust) concentrations and the corresponding population's PM 2.5_No Dust exposure (PPM 2.5 E) in the global continent from 1998 to 2016 were investigated by the presented BSTHPRM. The total areas of the high and higher PM 2.5_No Dust -polluted regions, whose spatial relative magnitude of PM 2.5_NoDust pollution to the global continental overall level was between 1.89 and 14.68, accounted for about 13.4% of the global land area, and the corresponding exposed populations accounted for 56.0% of the global total population. The spatial heterogeneity of the global PM 2.5_NoDust pollution increased generally from 1998 to 2016. The areas of hot, warm, and cold spots with increasing trends of PM 2.5_NoDust concentration initially contracted and then later expanded. The local trends of the global continental PM 2.5_NoDust concentrations and PPM 2.5 E can be parted into three changing stages, early, medium, and later stages, using the BSTHPRM. The area proportions of the regions experiencing a decreasing trend of PM 2.5_NoDust concentrations and PPM 2.5 E were greater in the medium stage than in the early and later stages. The local trends of PM 2.5_NoDust concentration and PPM 2.5 E in the two higher PM 2.5_NoDust polluted areas, northern India and eastern and southern China, increased in the early stage and then decreased in the medium stage. In the later stage (recent years), northern India displayed a stronger increasing trend; nevertheless, the follow-up decreasing trend still occurred in eastern and southern China. In the first two stages, more than half of the areas in Europe experienced a decreasing trend of PM 2.5_NoDust concentration and PPM 2.5 E; later, more than half of areas in Europe exhibited increasing trends in the later stage. North America and South America experienced a similar local trend of PPM 2.5 E to Europe. The PPM 2.5 E trend in Africa generally increased during the study period. • First presentation of a Bayesian space-time hierarchy piecewise regression model detecting self-adaptively transitions. • Firstly applies a developed Bayesian space-time model in investigating the global population's exposure to PM 2.5. • Deeply analyses the spatiotemporal trends of the global continental PM 2.5 pollution removed natural dust. • Details the spatiotemporal trends of the global population's exposure to anthropogenic PM 2.5. [ABSTRACT FROM AUTHOR]

Rapid industrialization, urbanization, and motorization lead to hiking of air pollution in various mega cities including Delhi, India. Studies done to analyze pollution suggests that vehicle exhaust emissions are major contributor to the urban air quality along with many other comparable sources. Hence to check instantaneous pollution increment, government aims to reduce vehicle emission. Traditional policies are working at times for holding sudden increase but long-term effects are not seen which need meso-spatial and small temporal policy. For optimizing meso-spatial policies implementation, many intricacies related to moving and stationary sources in near real-time have to be monitored including vehicular emission, itself. Analyzing these moving source emissions on the meso-spatial level is challenging. Therefore, the present study is an attempt to first understand the need of meso-spatial and near real-time checking policy and then leveraging the usage of previous region specific pollutant survey reports to map real-time pollution monitoring parameters. For that, a real-time vehicle monitoring strategy is proposed to map city-wide traffic congestion and emission using crowd-source data of Google Maps. For comparative study of different meso-spatial regions real-time moving source pollutant parameter 'μ' is calculated using a factor 'F'. Also, the different effects of congestion on vehicular emission in two different meso-spatial areas of Delhi is presented using comparative case study. Analysis of case study revealed that Anand Vihar area is more prone to vehicle emission variability in case of congestion fluctuation. Further the discussion of short temporal and spatial emission calculation, for weekly pollution evaluation is presented in the paper. This will be helpful to the authorities in formulating technological, institutional and traffic management policies. • Traditional pollution checking policy and different emission models are discussed for Delhi region. • A methodology to map real-time congestion for city-wide area on small tempo-spatial basis is provided. • A factor 'F' is introduced for relating congestion to vehicular and dust emission. • Vehicle proportionate area specific moving source emission 'μ' is calculated and analyzed by comparative emission study. • Suggestions on checking policy and the methodology to judge their effectiveness for immediate action is provided. [ABSTRACT FROM AUTHOR]

Abstract: This paper uses the 2006 IPCC Guidelines and latest country specific emission factors to estimate Indian methane emissions at sectoral and district level for the years 1990, 1995, 2005 and 2008. The estimates show that while methane emissions have increased steadily over past two decades, their share in India’s aggregate GHG emissions has declined from 31% in 1985 to 27% in 2008 mainly due to relatively higher growth CO2 emissions from the fossil fuels. The estimates for the year 2008 show that: i) agriculture sector, which employed two-thirds of India’s population and contributed 17% of GDP, accounted for 23% of India’s GHG emissions ii) 83% of country’s methane emissions are contributed by enteric fermentation, manure use and rice production, and iii) methane emissions from urban solid waste are steadily rising over the past two decades; their share in aggregate methane emissions has reached 8%. Resting on the disaggregated emissions estimates, the paper argues for using geographical and sectoral flexibilities to develop a roadmap for mitigation of methane emissions for India. [Copyright &y& Elsevier]

Abstract: The choice of domestic fuel is a matter of great concern for households and policy makers in India. This paper investigates the demand for domestic fuels when households face four choices: Fuelwood, Coal, Kerosene and LPG. The study is based on a survey of 500 households in Kolkata, India. The demand estimates are conducted using a two-stage process where the first stage investigates choice and the second the quantity used. Determinants of fuel demand are identified and their relative importance shown. Extending the study, the paper also analyses the choice of the main cooking fuel in terms of the households'' stated rankings of six fuels for five attributes. The policy discussion indicates that subsidies have less potential to reduce polluting fuels such as coal and fuelwood due to weak cross-price elasticities, while increased availability of LPG and potentially also increased awareness of indoor air pollution have greater prospect. [Copyright &y& Elsevier]

The enormity of air pollution has always been a matter of concern due to rapid development and urbanization over a long period. The increasing level of pollutants in ambient air in 2016-2017 has deteriorated the air quality of Delhi at an alarming rate. This brought us to focus our study on air quality in Delhi region. The prediction of future air quality has been carried out by analyzing the pollutants using data analysis techniques. In our previous study, we had analyzed the data from 2011-2015. Detailed analysis from 2009-2017 of air pollutants has been proposed in this extended paper along with the critical observation of 2016-2017 air pollutants trend in Delhi. Descriptive analysis and predictive analysis have been used to study the trends of various air pollutants like sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), suspended particulate matter (PM), ozone (O 3 ) carbon monoxide (CO), benzene, and forecast the future trend. We have observed through data analytics techniques that SO 2 is likely to increase by 1.24ug/m 3 , NO 2 is likely to increase by 16.77ug/m 3 , O3 is likely to increase by 6.11 mg/m 3 , benzene is likely to reduce by 1.33 mg/m 3 and NO 2 is predicted to reduce by 0.169 mg/m 3 in the coming years. [ABSTRACT FROM AUTHOR]

Building an effective clean air action plan for a city's air pollution problem requires an extensive network of monitoring stations to represent spatial and temporal patterns and an understanding of the sources contributing to the problem. In India, the National Clean Air Programme (NCAP) was launched in 2019 to develop clean air action plans for 131 non-attainment cities, which includes conducting source apportionment studies and establishing emission baselines. As of February 2023, only 39 cities have completed the apportionment studies. In this paper, we present the essential resources needed to strengthen the ambient air monitoring networks, for designing a representative airshed size, sampling size, and sampling frequency, to effectively track the progress made in the cities for better air quality. The NCAP cities were grouped into 104 airsheds (5.3% of the national area), collectively representing a total of 164 cities and a total population of 295 million (21% of the national total). Of these airsheds, 73 contain only one city; 18 contain two cities, and nine contain three cities. Four airsheds – Delhi, Mumbai, Indore, and Chandigarh contain 10, 8, 5, and 5 cities respectively. To measure and analyse particulate matter pollution, a total of 2118 sampling sites are recommended for the 104 airsheds. Cities could consider hybrid monitoring networks by complementing existing regulatory monitoring network with a high-density network of low-cost/sensor-grade monitors. An airshed level air quality management plan, an enhanced monitoring network, and consolidation of information on emission sources, are crucial for optimizing the clean air efforts under NCAP. [Display omitted] • Defined 104 airsheds to represent 131 non-attainment cities under NCAP. • Defined the minimum number of monitors required in the airsheds. • Conducted high-resolution meteorological modelling to determine minimum filter sampling frequency per airshed. • Examples of hybrid networks to reduce monitoring costs. [ABSTRACT FROM AUTHOR]

Recently, some high-skilled workers tend to escape from areas with severe air pollution. The phenomenon is more prominent in two emerging economies, China and India, and they are facing the brain drain caused by air pollution. This paper establishes a partial equilibrium model about the relationship of air pollution and the flow of technological innovative professionals (TIP), and for the first time, examines the effect of air pollution on the accumulation of technological innovative human capital based on cross-country data from China and India. We find that air pollution will reduce the stock of TIP in some regions. The estimation results show that a 1% increase in the PM 2.5 concentration of China's cities leads to an approximate 146 people decrease in the stock of TIP, while a 1% increase in the PM 10 concentration of Indian states leads to a 0.127% decrease in the stock of TIP. Further analysis of regional differences indicates that air pollution has a significant negative effect on the stock of TIP in economically developed areas of China, but has little effect on that in underdeveloped areas of China. Moreover, the results of robustness tests prove the stability of the findings in this study. This paper concludes with suggestions on how the country, local governments, enterprises, and research institutions could better deal with air pollution, attract and retain TIP, and effectively reduce brain drain. • Air pollution negatively affects the accumulation of innovative human capital. • Air pollution will reduce the stock of technological innovative professionals (TIP). • A 1% increase in PM 2.5 in China's cities decreases the stock of TIP by 146 people. • A 1% increase in PM 10 in Indian states reduces the stock of TIP by 0.127%. • TIP in economically developed areas are more sensitive to air pollution. [ABSTRACT FROM AUTHOR]

How are citizens experiencing the increase in Air pollution? How can the Social media data be explored and used to develop deeper insights to study citizen’s observations, opinions and experiences? In current research paper, by utilizing micro-blog social media application – Twitter data, these questions are examined. A suitable framework, He a l th P ractice - “ HELP ”, is emerged based on computational analysis and visualizations of the content of the Tweets. [ABSTRACT FROM AUTHOR]

India has more than 100,000 brick kilns producing around 250 billion bricks annually. Indian brick industry is often a small scale industry and third largest consumer of coal in the country. With the growing demand for building materials and characterised by lack of pollution control measures the brick industry has a potential to cause adverse effects on the environment. This paper presents assessment of five brick making technologies based on the measurements carried out at seventeen individual brick kilns. Emissions of PM, SO 2 , CO and CO 2 were measured and these emissions were used to estimate the emission factors for comparing the emissions across different fuel or operating conditions. Estimated emission from brick kilns in South Asia are about 0.94 million tonnes of PM; 3.9 million tonnes of CO and 127 million tonnes of CO 2 per year. Among various technologies that are widely used in India, Zig zag and vertical shaft brick kilns showed better performance in terms of emissions over the traditional fixed chimney Bull's trench kilns. This suggests that the replacement of traditional technologies with Zig zag, vertical shaft brick kilns or other cleaner kiln technologies will contribute towards improvements in the environmental performance of brick kiln industry in the country. Zig zag kilns appear to be the logical replacement because of low capital investment, easy integration with the existing production process, and the possibility of retrofitting fixed chimney Bull's trench kilns into Zig zag firing. [ABSTRACT FROM AUTHOR]

The global burden of disease study estimated 695,000 premature deaths in 2010 due to continued exposure to outdoor particulate matter and ozone pollution for India. By 2030, the expected growth in many of the sectors (industries, residential, transportation, power generation, and construction) will result in an increase in pollution related health impacts for most cities. The available information on urban air pollution, their sources, and the potential of various interventions to control pollution, should help us propose a cleaner path to 2030. In this paper, we present an overview of the emission sources and control options for better air quality in Indian cities, with a particular focus on interventions like urban public transportation facilities; travel demand management; emission regulations for power plants; clean technology for brick kilns; management of road dust; and waste management to control open waste burning. Also included is a broader discussion on key institutional measures, like public awareness and scientific studies, necessary for building an effective air quality management plan in Indian cities. [ABSTRACT FROM AUTHOR]

Coal-fired energy generation is the backbone of India's power sector and considered a driver of its economic development. However, it is associated with detrimental environmental and health impacts in India and its fleet is currently struggling with overcapacity and inefficiency problems. One solution to address these challenges is the early retirement of some of India's coal-fired power plants. In this paper, we introduce multidimensional indices that identify plants for retirement based on comprehensive criteria that include technical and economic characteristics of plants as well as their environmental impacts. We implement an ensemble approach, where we formulate 8008 indices based on all possible combination of seven relevant parameters and rank plants accordingly. This approach facilitates a comprehensive analysis of the plants' performance on different parameters and provides a new outlook on plant retirements that differs from the common approach of retiring plants based solely on technical characteristics such as age, capacity, and heat rate. Our results show that top plants recommended for early retirement are typically 7 years older, 13% more expensive and have around 40% higher population exposure to emissions compared to an average plant in India. We estimate the potential costs saved from the retirement of the worst-performing 50 GW of generating capacity to be $21 billion resulting from shifting ownership towards a cheaper cost of capital and replacing coal by more competitive sources such as solar power. • Identify plants for early retirement based on technical, economic and environmental indicators. • Worst performing 50 GW capacity are older, more expensive to operate and have higher population exposure. • Costs saved from retiring 50 GW capacity and replacing them with solar are $21 billion. • A multidimensional approach is essential for a politically feasible phaseout of coal. [ABSTRACT FROM AUTHOR]

Abstract: The paper describes behavior of surface ozone, its precursor gases, BC along with TOCC, TWVC, AOT1020nm as well as UV and IR radiation intensities observed during the partial solar eclipse of 15th January, 2010 over Udaipur, where 52% solar disc is obscured due to the moon’s shadow. During the beginning to main eclipse phase, the deviation values of several air pollutants concentrations from eclipse to control day values vary in a small range from −9 to −2ppb in case of surface ozone and −180 to −80 ppb for CO. The corresponding change in the values of BC observed from −3.3 to −.5μg/m3. No significant change is found in NO2, NO or in ratio of NO2/NO values during the partial eclipse time. TOCC values decrease from 3 to 5DU along with a reduction in UV radiation intensity from 20 to 35% from starting to the main eclipse phase. The AOT1020nm values are found to increase from .2 to 1.0 along with a reduction in IR radiation intensity order of 50%. However, TWVC values decrease from .22 to .1cm during the eclipse hours. The low level of dilution in surface ozone in eclipse period may be attributed with change in local atmospheric boundary layer dynamic conditions or limited air pollutants dispersion, in term of decreases in planetary boundary layer height, wind speed and hence ventilation coefficient in the same eclipse hours. Thus, present studies support the argument for the leading roles of photochemical reactions with its precursor gases under presence of solar radiation in surface ozone variability. Other possible controlling factors are advection of air pollutants from the polluted region as evident from backward wind trajectories and altering the local meteorological conditions. [Copyright &y& Elsevier]

Abstract: In this second of two companion papers, we quantify for the first time the global impact on premature mortality of the inter-continental transport of fine aerosols (including sulfate, black carbon, organic carbon, and mineral dust) using the global modeling results of (Liu et al., 2009). Our objective is to estimate the number of premature mortalities in each of ten selected continental regions resulting from fine aerosols transported from foreign regions in approximately year 2000. Our simulated annual mean population-weighted (P-W) concentrations of total PM2.5 (aerosols with diameter less than 2.5 μm) are highest in East Asia (EA, 30 μg m−3) and lowest in Australia (3.6 μg m−3). Dust is the dominant component of PM2.5 transported between continents. We estimate global annual premature mortalities (for adults age 30 and up) due to inter-continental transport of PM2.5 to be nearly 380 thousand (K) in 2000. Approximately half of these deaths occur in the Indian subcontinent (IN), mostly due to aerosols transported from Africa and the Middle East (ME). Approximately 90K deaths globally are associated with exposure to foreign (i.e., originating outside a receptor region) non-dust PM2.5. More than half of the premature mortalities associated with foreign non-dust aerosols are due to aerosols originating from Europe (20K), ME (18K) and EA (15K); and nearly 60% of the 90K deaths occur in EA (21K), IN (19K) and Southeast Asia (16K). The lower and higher bounds of our estimated 95% confidence interval (considering uncertainties from the concentration–response relationship and simulated aerosol concentrations) are 18% and 240% of the estimated deaths, respectively, and could be larger if additional uncertainties were quantified. We find that in 2000 nearly 6.6K premature deaths in North America (NA) were associated with foreign PM2.5 exposure (5.5K from dust PM2.5). NA is least impacted by foreign PM2.5 compared to receptors on the Eurasian continent. However, the number of premature mortalities associated with foreign aerosols in NA (mostly occurring in the U.S.) is comparable to the reduction in premature mortalities expected to result from tightening the U.S. 8-h O3 standard from 0.08 ppmv to 0.075 ppmv. International efforts to reduce inter-continental transport of fine aerosol pollution would substantially benefit public health on the Eurasian continent and would also benefit public health in the United States. [Copyright &y& Elsevier]

As the world gets ready to begin the second decade of the twenty-first century, global climate change has been recognized as a real threat to civilization as we know it. The rapid and successful economic growth of developing nations, particularly China and India, is contributing to climate change. The route to initial economic success in China followed that of the developed nations through the development of industries. Unfortunately, China''s environmental protection efforts have not been the same as in developed countries because China is vastly different culturally, socially, economically and, especially, politically from developed nations. When China started to deal with environmental concerns in the late 1970s, it took advantage of the experiences of other countries in establishing environmental standards and regulations, but it did not have a model to follow when it came to implementing these standards and regulations because of the abovementioned differences. Economically, China is transitioning from an agricultural base into an industrial base; however, even now, 60% of the population remains farmers. China has been and still is heavily dependent upon coal for energy, resulting in serious atmospheric particulate pollution. While growing efforts have been expended on the environment, at this juncture of its economic development, China would be well served to revisit the traditional “develop first and clean up later” approach and to find a balance between development and protecting the environment. Against this backdrop, a reflective look of the effort to manage air quality from 1949–2008 (with an emphasis on the past 30years) in China is presented in this paper. The environmental component of the 2008 Olympic Games is examined as a special example to illustrate the current measures being used to improve air quality in China. [Copyright &y& Elsevier]

This paper uses spectral methods to analyze changes in air quality at a single monitoring site in Delhi since 2000. Power spectral density calculations of daily concentration data for particulate matter (PM10), carbon monoxide (CO), oxides of nitrogen (NO x ) and oxides of sulfur (SO x ) reveal the presence of trends and periodic oscillations for all the pollutants. Singular Spectrum Analysis (SSA) is used to decompose daily data into statistically significant non-linear trends, seasonal cycles and other oscillations. Periods of sharp reductions were observed for both SO x and CO concentrations in 2001 and 2002, respectively. NO x concentration trends show a sustained rise from 2000 to 2004, followed by small decline thereafter. PM10 concentration trends remain essentially unchanged over the time period. All pollutants also show strong annual and biannual cycles. The observed trends in CO and NO x likely relate changes in Delhi''s vehicular traffic emissions. The sharp drop in both the trend and amplitude of the seasonal cycle of CO coincides with the switch to Compressed Natural Gas (CNG) as a fuel for Delhi''s public transport fleet. Observed changes in SO x and PM10 concentrations were most likely caused by sources unrelated to vehicular traffic. [Copyright &y& Elsevier]

This paper examines the role of meteorology in linking near surface emissions of particulate matter and associated ambient concentrations in urban areas. The examination is conducted with two models: a steady state model based on urban dispersion models developed earlier, and an unsteady state model that accounts for time varying meteorological and emission inputs. After conducting sensitivity studies with the models, they are applied in Pune, India to (a) check consistency between estimates of surface emissions of particulate matter (with aerodynamic diameters of less than m, referred to as PM and observed ambient concentrations and (b) identify the variables that govern air quality. Results from the modeling exercise indicate that (1) nighttime meteorology governs both hourly as well as 24h averaged concentrations and (2) because the wind speeds in urban areas are typically low, concentration estimates from the steady state model differ substantially from those of the unsteady state model during the nighttime hours both in magnitude and in timing of the peaks; however, the difference between the 24h averaged concentrations from the two models is less than 5% for the cases considered here. Because our understanding of nighttime meteorology in urban areas is limited, there is a need for experimental programs to relate the diurnal variation of concentrations with associated meteorology, especially during the night. [Copyright &y& Elsevier]

Abstract: This paper provides the trends of greenhouse gas (GHG) and local air pollutant emissions of India for 1985–2005. The GHGs covered are six Kyoto gases, namely carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), perfluorocarbons (PFCs), hydrofluorocarbons (HFCs) and sulfur hexafluoride (SF6). The local air pollutants are sulfur dioxide (SO2), nitrogen oxides (NO X ), carbon monoxide (CO) and total suspended particulates (TSP). These estimates incorporate some of the most recent scientific assessments for India. The multigas emissions have varied sectoral and fuel-based dominance, as well as regional distribution patterns. Coal consumption in power sector dominates CO2 and SO2 emissions, while power and road transport equally contribute to NO X emissions. Rice cultivation and livestock-related emissions from the agriculture sector dominate CH4 emissions, while synthetic fertilizer use in the same sector is the major source of N2O emissions. PFC emissions are dominated by C2F6 and CF4 emissions from aluminum production. The majority of HFC emissions are contributed by HFC-23, a by-product during the production of HCFC-22 that is widely used in refrigeration industry. CO emissions have dominance from biomass burning. Particulate emissions are dominated by biomass burning (residential sector), road transport and coal combustion in large plants. These varied emission patterns provide interesting policy links and disjoints, such as—which and where mitigation flexibility for the Kyoto gases, exploring co-benefits of CO2 and SO2 mitigation, and technology and development pathway dependence of emissions. The present inventory assessment is a pointer to the future emission pathways for India wherein local air pollutant and GHG emissions, although connected, may not move in synchronization and therefore would require alignment through well crafted development and environment strategies. [Copyright &y& Elsevier]

Abstract: Chemical simulations in most of the atmospheric chemistry models require surface emissions in a specific form (gridded), which are often not available. Simple interpolation of broader level emissions to obtain gridded data may lead to erroneous results. An attempt has been made in this paper to develop a geographical information system (GIS) based methodology for distributing the emissions from a broader level inventory to finely gridded emission values, considering local micro-level details and activity data. Given the importance of Carbon Monoxide emissions in ozone pollution chemistry over India, an emission inventory for CO from various sources for India has been used to demonstrate the GIS-based gridding methodology. The total CO emissions over India for 2001, which are estimated to be around 69.0Tgyear−1, have been downscaled source-wise (distinguishing between rural and urban bio-fuel, vehicular traffic, coal and biomass burning) from state-level (28 points) to district level (∼500 points) before mapping through a GIS utility and finally gridded to a 1°×1° resolution with a data loss of only about 13%. The final results provide detailed information with emission “hot spots” and the relative contribution of various sources. This article focuses on usage of the GIS based statistical methodology for gridding the inventory and the results obtained thereof are discussed. [Copyright &y& Elsevier]