Article

Application of SIM-AIR modeling tools to assess air quality in Indian cities

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Abstract

A prerequisite to an air quality management plan for a city is some idea of the main sources of pollution and their contributions for a city. This paper presents the results of an application of the SIM-air modeling tool in six Indian cities – Pune, Chennai, Indore, Ahmedabad, Surat, and Rajkot. Using existing and publicly available data, we put together a baseline of multi-pollutant emissions for each of the cities and then calculate concentrations, health impacts, and model alternative scenarios for 2020. The measured annual PM10 (particulate matter with aerodynamic diameter less than 10 micron meter) concentrations in μg m−3 averaged 94.7 ± 45.4 in Pune, 73.1 ± 33.7 in Chennai, 118.8 ± 44.3 in Indore, 94.0 ± 20.4 in Ahmedabad, 89.4 ± 12.1 in Surat, and 105.0 ± 25.6 in Rajkot, all exceeding the annual standard of 60 μg m−3. The PM10 inventory in tons/year for the year 2010 of 38,400 in Pune, 50,200 in Chennai, 18,600 in Indore, 31,900 in Ahmedabad, 20,000 in Surat, and 14,000 in Rajkot, is further spatially segregated into 1 km grids and includes all known sources such as transport, road dust, residential, power plants, industries (including the brick kilns), waste burning, and diesel generator sets. We use the ATMoS chemical transport model to validate the emissions inventory and estimate an annual premature mortality due to particulate pollution of 15,200 for the year 2010 for the six cities. Of the estimated 21,400 premature deaths in the six cities in 2020, we estimate that implementation of the six interventions in the transport and brick kiln sectors, can potentially save 5870 lives (27%) annually and result in an annual reduction of 16.8 million tons of carbon dioxide emissions in the six cities.

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... Only one study has estimated the contribution of MSW burning in air pollution emissions based on a few assumptions. In this study, Guttikunda and Jawahar (2012) 39 have assumed 10-25% of MSW generated per day is burned in the SMC area, but no field-based data has been referred to. Presently, neither city-level nor intracity-level primary data on MSW burning are available for the SMC area, an issue that is critical for developing a clean air action plan. ...
... Contribution of different in-boundary sources for various emissions in SMC in 2010(Source:Guttikunda and Jawahar, 2012) ...
... Based on the data from 2015 to 2019 and the growth trends in the number of flights, the annual growth rate for the aviation sector is projected to be 9.46% for 2025 and 2030. Based on the trends in waste disposed at landfills in the SMC area during2012 -19 (SMC, 2021, an 8% increase is projected in the disposal of waste at the landfill site both for 2025 and 2030. For the refuse sector, the SMC area population growth rate of 4.93% per annum is projected for both 2025 and 2030. ...
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The Ministry of Environment, Forest and Climate Change (MoEFCC), Government of India, launched the National Clean Air Programme (NCAP) as a long-term strategy to tackle the air pollution problem across the country in a comprehensive manner, with targets to achieve 20-30% reduction in PM2.5/10 concentrations by 2024, keeping 2017 as the base year. Under NCAP, 124 non-attainment cities have been identified across the country based on the air quality data from 2014-2018. These cities do not meet the National Ambient Air Quality Standards (NAAQS) and require focused attention on multiple fronts to deal with the rising air pollution. In the state of Gujarat, the cities Ahmedabad, Surat, and Vadodara were identified as non-attainment cities. As per the NCAP targets, the cities that don’t meet the NAAQS standards would have to develop a city-specific clean air action plan detailing the proposed interventions to reduce air pollution emissions from the identified sources in a timebound manner which will serve as a strategy document.
... This leads to an increase in hospitalization and emergency department visits (Kumar et al. 2004;Gupta 2008;Patankar and Trivedi 2011;Maji et al. 2015Maji et al. , 2018. The longer and more intense the exposure greater is the impact on health, ranging from minor eye irritations, cough, wheezing, allergic rhinitis, respiratory symptoms to decreased lung and heart function, tuberculosis, cardiovascular diseases and even premature death (Kumar and Foster 2007;Guttikunda and Jawahar 2012;Guttikunda and Goel 2013;Ghosh and Mukherji 2014;Tobollik et al. 2015;Gawande et al. 2016). ...
... Over the past decades, numerous epidemiological studies and meta-analysis, estimating increased premature mortality due to short-and long-term exposure to PM (Guttikunda and Jawahar 2012;Silva et al. 2013;Ghude et al. 2016). In India, about 0.62 million premature excess number of death cases occurred due to AAP and became the 5 th leading cause of death after high blood pressure, indoor air pollution, tobacco smoking and poor nutrition in 2012 (Maji 2016). ...
... Short-term exposures to ambient particulate and gaseous pollutants have already shown strong associations between chronic obstructive pulmonary disease (COPD) (Chhabra et al. 2001;Agarwal et al. 2006;Patankar and Trivedi 2011), respiratory illnesses (Sagar et al. 2007;Gupta and Elumalai 2017) and higher rates of hospital admission/visit (Pande et al. 2002). While the long-term effects of air pollution have been associated with deficit lung function (Kumar and Foster 2007;Siddique et al. 2010a;Arora et al. 2018), asthma (Sehgal et al. 2015), heart attack (Sehgal et al. 2015), cardiovascular mortality (Tobollik et al. 2015) and premature mortality (Ghose 2009;Guttikunda and Jawahar 2012;Silva et al. 2013;Guttikunda and Kopakka 2014;Guttikunda and Jawahar 2014;Lelieveld et al. 2015;Ghude et al. 2016;Chowdhury and Dey 2016;Dey 2018). Also, particulate matter (PM 2.5 and PM 10 ) is primarily responsible for deleterious health problems, including asthma, bronchitis, chronic obstructive pulmonary disease, pneumonia, upper respiratory tract and lower respiratory tract disorders. ...
Article
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Health effects attributable to short-term and long-term ambient air pollution (AAP) exposure in Indian population are less understood. This study evaluates the effect of short time and long-term exposure to AAP on respiratory morbidity, mortality and premature mortality for the exposed population. A total of 59 studies are reviewed to examine the effects of short-term exposure (n = 23); long-term exposure (n = 18) and premature mortality (n = 18). Short-term exposures to ambient pollutants have strong associations between COPD, respiratory illnesses and higher rates of hospital admission or visit. The long-term effects of AAP, associated with deficit lung function, asthma, heart attack, cardiovascular mortality and premature mortality have received much attention. Particulate matter (PM 2.5 and PM 10) is primarily responsible for respiratory health problems. Out of 18 literature reviewed on premature mortality , most (12 of 18) studies have statistically significant associations between AAP exposure and increased premature mortality risk. ARTICLE HISTORY
... Information was compiled about existing air quality monitoring stations in Ahmedabad, including organizational management, monitor type, parameters monitored, and the availability of monitoring data. Additionally, prior preliminary emissions inventory research in the city had begun to link polluted air to emissions from distinct sources in the city, both stationary and mobile [83]. This past research was analyzed to inform a comprehensive city-wide emissions inventory that was undertaken in 2016-2017 (See Section 3.4.5). ...
... Ahmedabad's inland location, as well as its dry and hot climate, can worsen air pollution in the city. A 2012 study evaluated air quality sources in Ahmedabad and five other Indian cities with a focus on PM 10 [83]. The study found that the major sources for PM 10 in Ahmedabad were road dust (30%), power plants (25%), vehicle exhaust (20%), and industry (15%), with the remainder attributed to domestic cooking and heating, diesel generators, waste burning, and construction activities. ...
... Despite Ahmedabad's high pollution levels, the survey of peer-reviewed literature resulted in few studies specific to the air pollution-related health burden in the city. For example, in 2010, the city was estimated to experience over 4900 premature deaths attributed to excessive ambient air pollution [83]. Moreover, communities living near thermal plants are known to experience higher rates of chronic respiratory illness, asthma, cancer and premature death [122]. ...
Article
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Indian cities struggle with some of the highest ambient air pollution levels in the world. While national efforts are building momentum towards concerted action to reduce air pollution, individual cities are taking action on this challenge to protect communities from the many health problems caused by this harmful environmental exposure. In 2017, the city of Ahmedabad launched a regional air pollution monitoring and risk communication project, the Air Information and Response (AIR) Plan. The centerpiece of the plan is an air quality index developed by the Indian Institute of Tropical Meteorology’s System for Air Quality and Weather Forecasting and Research program that summarizes information from 10 new continuous air pollution monitoring stations in the region, each reporting data that can help people avoid harmful exposures and inform policy strategies to achieve cleaner air. This paper focuses on the motivation, development, and implementation of Ahmedabad’s AIR Plan. The project is discussed in terms of its collaborative roots, public health purpose in addressing the grave threat of air pollution (particularly to vulnerable groups), technical aspects in deploying air monitoring technology, and broader goals for the dissemination of an air quality index linked to specific health messages and suggested actions to reduce harmful exposures. The city of Ahmedabad is among the first cities in India where city leaders, state government, and civil society are proactively working together to address the country’s air pollution challenge with a focus on public health. The lessons learned from the development of the AIR Plan serve as a template for other cities aiming to address the heavy burden of air pollution on public health. Effective working relationships are vital since they form the foundation for long-term success and useful knowledge sharing beyond a single city.
... Reduced life years and life expectancy; and mortalities [52] Evaluation of air quality in six Indian cities to create a knowledge base for multi-pollutant pollution, dispersion modeling of ambient particulate concentrations India Premature mortality [53] Evaluation of the health-related economic externalities of air emissions from particular emission sources or industries that can be used to help emission reduction policy-making. ...
... SIM-air uses the source-receptor transfer matrix (SRTM) to convert emissions of the concentrations, which is an output from a chemical transport model. It provides the necessary information for the policymakers to prioritize their air quality management policies, optimizing options for both public health and costs impacts in order to better adapt to local ambient standards in urban areas [53,137]. AirQ+ software tool for health risk assessment of air pollution is one of the most widely used tools for calculating the possible health impacts of improving air quality. ...
... Multiple benefits (Environmental-health-economic) assessment of the climate change action plans, considering interactions between emissions, dispersion of pollution, impacts, and options for management [53,137]. ...
Article
Full-text available
Air pollution is a major public health problem. A significant number of epidemiological studies have found a correlation between air quality and a wide variety of adverse health impacts emphasizing a considerable role of air pollution in the disease burden in the general population ranging from subclinical effects to premature death. Health risk assessment of air quality can play a key role at individual and global health promotion and disease prevention levels. The Air Pollution Health Risk Assessment (AP-HRA) forecasts the expected health effect of policies impacting air quality under the various policy, environmental and socioeconomic circumstances, making it a key tool for guiding public policy decisions. This paper presents the concept of AP-HRA and offers an outline for the proper conducting of AP-HRA for different scenarios, explaining in broad terms how the health hazards of air emissions and their origins are measured and how air pollution-related impacts are quantified. In this paper, seven widely used AP-HRA tools will be deeply explored, taking into account their spatial resolution, technological factors, pollutants addressed, geographical scale, quantified health effects, method of classification, and operational characteristics. Finally, a comparative analysis of the proposed tools will be conducted, using the SWOT (strengths, weaknesses , opportunities, and threats) method.
... This is a function of fuel burnt which is then converted to emission loads using relevant emission factors. We used the same methodology for similar projects for 10 Indian cities -Pune, Chennai, Ahmedabad, Indore, Surat, Rajkot, Hyderabad, Chennai, Vishakhapatnam, and Delhi ( Guttikunda and Jawahar, 2012;Guttikunda and Calori, 2013;Guttikunda and Kopakka, 2014;; national transport sector (Guttikunda and Mohan, 2014); national power plant sector (Guttikunda and Jawahar, 2014); and Delhi transport sector (Goel and Guttikunda, 2015). We used multiple sources to collate a library of emission factors for transport, industrial, and domestic sectors (CPCB, 2011;Pandey et al., 2014;Sadavarte and Venkataraman, 2014;IIASA, 2015;Goel and Guttikunda, 2015;Sakar et al., 2016). ...
... For CO, the share of emissions is spread equally between vehicle exhaust, domestic cooking and heating, and industries. The level of uncertainty for the emissions inventory is about 20-30% (Guttikunda and Jawahar, 2012). ...
... We used multiple layers of spatial proxies to grid the estimated emissions and create a gridded inventory (Fig. 4). The details of the methodology are described in Guttikunda and Jawahar (2012). We have created the emissions inventory on a GIS platform of 0.01°spatial resolution. ...
Article
Delhi, with a population of 22 million (1.6% of national total) is one of the most polluted capital cities in the world. Nearly 50% of the published literature in India focus on air pollution in Delhi. However, air pollution impacts are not limited only to the capital city. Yet, there is little information and attempt to quantify these impacts for Tier 1 and 2 cities, even though they account for > 30% of India's population. To remedy this vacuum of information, the Air Pollution knowledge Assessments (APnA) city program deliberately focuses on 20 Indian cities, other than Delhi. We established baseline multi-pollutant high-resolution emissions inventory, after colating information from multiple resources detailed in this paper, which was used to estimate spatial concentrations of key pollutants across city's urban airshed using WRF-CAMx chemical transport modeling system. The inventory includes anthropogenic sources, such as transport (road, rail, ship, and aviation), large scale power generation (from coal, diesel, and gas power plants), small scale power generation (from diesel generator sets for household use, commercial use, and agricultural water pumping), small and medium scale industries, dust (road resuspension and construction), domestic (cooking, heating, and lighting), open waste burning, and open fires and non-anthropogenic sources, such as sea salt, dust storms, biogenic, and lightning. The emissions inventory is currently in use for 3-day advance air quality forecasting for public release on an on-going basis. Using meteorological parameters and big data like gridded speed maps from google, the emissions inventory is dynamically updated. The results from this research will be valuable to local and national policy makers - especially the information on source contributions to air pollution.
... Air pollution is being exacerbate by four specific events namely rapid economic development, high levels of energy consumption, expansion of cities and increase in automobiles traffic that typically occur as countries industrialization (Guttikunda and Jawahar, 2012) [1] . An unplanned, instructed and unzoned growth of both industrial and residential areas, as happened with many cities of the developed and developing world, has further enhanced the air pollution problems. ...
... Air pollution is being exacerbate by four specific events namely rapid economic development, high levels of energy consumption, expansion of cities and increase in automobiles traffic that typically occur as countries industrialization (Guttikunda and Jawahar, 2012) [1] . An unplanned, instructed and unzoned growth of both industrial and residential areas, as happened with many cities of the developed and developing world, has further enhanced the air pollution problems. ...
Article
Air pollution has emerged as one of the challenging problems before mankind in the past few decades. The ambient air quality survey was carried out at industrial areas with respect to SPM, SO 2 and NOx. The pollutant concentrations were used to calculate the Air Quality Index. It is observed that most of the predicted pollutants are violating the permissible values. A quantitative analysis on the mean concentration of SO2, NOX, and SPM in four different industrial zones at Shahdol was compared with that of non-exposed to control regions. These attributes were analyzed on the morbidity pattern of the exposed population for eleven various diseases and its hazardous effects are reported in the present study. Source studies of SPM may be carried out to ascertain the sources and put up relevant control measures in place.
... Air pollution can be defined as the presence of toxic chemicals or compounds (including those of biological origin) in the air, at levels that can cause harm to individuals. In the present era, urban air pollution is a serious issue caused by multiple sources ranging from on-road re-suspended dust due to vehicles, vehicular exhaust, construction dust, industrial flumes and many more [1]. Recent studies have shown that approximately 1.1 billion people are breathing unhealthy air and these pollutants in the air are responsible for around 7 billion deaths per year globally [2]. ...
... The other important issue is monitoring such air quality in real-time. For example, 1 if air quality deteriorates beyond a certain threshold, information must be sent to an appropriate authority (e.g. Regional Pollution Control Board) to take necessary actions. ...
Conference Paper
In the era of industrialization, pollutants in the air are increasing at an alarming rate causing serious threats to mankind. This has raised a need of measuring and recording pollution levels to initiate planned actions so as to protect the environment. Internet of Things (IoT) and cloud computing are two of the emerging technologies with enormous potentials that can be utilized for this purpose. Therefore, in this paper we propose an IoT based Air Pollution Monitoring (APM) system whose components are deployed at all critical locations within the city. An upcoming, long-range communication medium LoRa is used as the backbone of our APM system. Our system not only allows passersby to view pollution status of his/her surrounding through an appropriate Android application but also informs the corresponding authorities in case of an emergency. Through real-time data collection and performance evaluation we show how our proposed system satisfies the necessary criteria. Finally, we also provide a detailed comparison of why we prefer LoRa over WiFi (the traditional medium of wireless communication) and how it is beneficial, cost-effective in case of large deployment areas.
... A number of studies have highlighted that construction activities are an important source of PM, combined with sources such as road dust (Pant and Harrison, 2012). A study carried out in six Indian cities showed that 10% of PM emission are sourced from construction activities annually (Guttikunda and Jawahar, 2012;CPCB, 2010). There is a vast scope for carrying out best practices in the construction industry to minimise the PM emissions. ...
... Vacuum cleaners and water sprinklers attached to heavy-duty or light-duty trucks help to suck up dust from the roads, so that the resuspension of any leftover dust is suppressed. Since the road dust accounts for up to 30 to 40% of the PM10 pollution in most cities (CPCB, 2010;Guttikunda and Jawahar, 2012), an instant enforcement of such initiatives in Kolkata will give immediate results of improved air quality. Most of the research initiatives are focused on PM10 and PM2.5. ...
... In most parts of India values exceed the Indian National Ambient Air Quality Standard (CPCB, 2009) of 40 µg m −3 for annual mean PM 2.5 , with values as high as 140 µg m −3 in northern India. Large regions of north, eastern and western India exhibit high PM 2.5 concentrations, which are not just limited to specific urban centres or megacities examined in earlier studies (Jain and Khare, 2008;Guttikunda and Jawahar, 2012;Sharma and Maloo, 2005). Simulations with the REF scenario emissions (Fig. 6b, c), show significant increases in annual mean PM 2.5 concentrations all over India, preserving a similar elevated spatial pattern in the northern and northeastern regions, resulting from significant increases in emissions of primary PM 2.5 and its precursors from their 2015 values. ...
Article
Full-text available
India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015–2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 µg m⁻³). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India's mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from other sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.
... Matematiksel olarak konsantrasyon kütle/hacim olarak tanımlanmaktadır. Bir kentsel çevrede emisyonların, eşit olarak karıştığı, düşük karışım yüksekliğinde yüksek ortam konsantrasyonlarında olduğu farz edilmektedir [14]. ...
... Air pollution in Indian subcontinent has been identified as a critical issue that is having a lasting impact on public health and mortality rates (Ghude et al., 2016;Gurjar et al., 2010;Laumbach & Kipen, 2012;Simon et al., 1998;World Health Organization, 2016). Long-term studies, carried out across different Indian cities, have all reported persistently high values of aerosol (Girolamo et al., 2004;Moorthy et al., 2013;Prasad et al., 2006;Sarkar et al., 2006;Satheesh et al., 2017), PM2.5 and PM10 (Guttikunda & Jawahar, 2012;Sharma et al., 2003;Sharma & Maloo, 2005), and NO x (Badhwar et al., 2006;Ghude et al., 2008). Ascertaining the exact source of air pollution in India is complicated by several factors. ...
Article
Full-text available
Crop residue burning (CRB) is a recurring problem, during October-November, in the northwestern regions (Punjab, Haryana, and western Uttar Pradesh) of India. The emissions from the CRB source regions spread in all directions through long-range transport mechanisms, depending upon the meteorological conditions. In recent years, numerous studies have been carried out dealing with the impact of CRB on the air quality of Delhi and surrounding areas, especially in the Indo-Gangetic Basin (also referred to as Indo-Gangetic Plain). In this paper, we present detailed analysis using both satellite-and ground-based sources, which show an increasing impact of CRB over the eastern parts of the Indo-Gangetic Basin and also over parts of central and southern India. The increasing trends of finer black carbon particles and greenhouse gases have accelerated since the year 2010 onward, which is confirmed by the observation of different wavelength dependent aerosol properties. Our study shows an increased risk to ambient air quality and an increased spatiotemporal extent of pollutants in recent years, from CRB, which could be a severe health threat to the population of these regions. Plain Language Summary This paper shows from multiple evidence increasing effects of crop residue burning on the rest of India. This is the first work of its kind that treats this issue over rest of India at depth based on data from multiple sources and shows the ever increasing menace of biomass burning to air pollution.
... Air pollution in Indian subcontinent has been identified as a critical issue that is having a lasting impact on public health and mortality rates ( Ghude et al., 2016;Gurjar et al., 2010;Laumbach & Kipen, 2012;Simon et al., 1998;World Health Organization, 2016). Long-term studies, carried out across different Indian cities, have all reported persistently high values of aerosol ( Girolamo et al., 2004;Moorthy et al., 2013;Prasad et al., 2006;Sarkar et al., 2006;Satheesh et al., 2017), PM2.5 and PM10 (Guttikunda & Jawahar, 2012;Sharma et al., 2003;Sharma & Maloo, 2005), and NO x ( Badhwar et al., 2006;Ghude et al., 2008). Ascertaining the exact source of air pollution in India is complicated by several factors. ...
Article
Crop residue burning (CRB) is a recurring problem, during October–November, in the northwestern regions (Punjab, Haryana, and western Uttar Pradesh) of India. The emissions from the CRB source regions spread in all directions through long-range transport mechanisms, depending upon the meteorological conditions. In recent years, numerous studies have been carried out dealing with the impact of CRB on the air quality of Delhi and surrounding areas, especially in the Indo-Gangetic Basin (also referred to as Indo-Gangetic Plain). In this paper, we present detailed analysis using both satellite- and ground-based sources, which show an increasing impact of CRB over the eastern parts of the Indo-Gangetic Basin and also over parts of central and southern India. The increasing trends of finer black carbon particles and greenhouse gases have accelerated since the year 2010 onward, which is confirmed by the observation of different wavelength dependent aerosol properties. Our study shows an increased risk to ambient air quality and an increased spatiotemporal extent of pollutants in recent years, from CRB, which could be a severe health threat to the population of these regions.
... On the other hand, in Delhi, Rajarathnam et al. (2011) reported an increase of 0.19% in mortality for every 10 mg/m 3 increase in PM 10 . Multiple studies have used modelling analysis using global concentration-response functions to assess health impacts associated with PM exposure, and in absence of reliable data, a majority of such studies have used modelled PM data (Guttikunda and Jawahar 2012). In some other cases, measured PM data has been used albeit for short durations (e.g. ...
Article
Air pollution poses a critical threat to human health with ambient and household air pollution identified as key health risks in India. While there are many studies investigating concentration, composition, and health effects of air pollution, investigators are only beginning to focus on estimating or measuring personal exposure. Further, the relevance of exposures studies from the developed countries in developing countries is uncertain. This review summarizes existing research on exposure to particulate matter (PM) in India, identifies gaps and offers recommendations for future research. There are a limited number of studies focused on exposure to PM and/or associated health effects in India, but it is evident that levels of exposure are much higher than those reported in developed countries. Most studies have focused on coarse aerosols, with a few studies on fine aerosols. Additionally, most studies have focused on a handful of cities, and there are many unknowns in terms of ambient levels of PM as well as personal exposure. Given the high mortality burden associated with air pollution exposure in India, a deeper understanding of ambient pollutant levels as well as source strengths is crucial, both in urban and rural areas. Further, the attention needs to expand beyond the handful large cities that have been studied in detail.
... SIM-air using ATMOS chemical transport model was used for predicting PM 10 concentrations with in situ emission inventory at 1-km resolution in an urban area [110]. The simulated concentration of PM 10 was found to be satisfactory (P/O = 0.82) when compared with observed values in Indore. ...
Article
Full-text available
Developing countries like India require proper control strategies for reducing the enormous premature mortality associated with air pollution. Air quality models, in addition to helping to understand the severity of air pollution by providing the pollutant concentrations, also give knowledge of the sources. Previous local and regional air quality modeling studies carried out in India are reviewed in this current study with a goal of understanding the current gaps and exploring future directions. Studies carried out in different parts of India during past decade were precisely documented in this study using methodical Scopus, Web of Science, and Google searches. Majority of the air quality studies are concentrated in megacities leaving behind the small cities which require greater attention in future. While most of the modeling studies were carried out in northern India, very few studies concentrated on central region of the country. Review of both local and regional numerical models showed the need for better emission inputs, while the statistical models inferred the need for proper selection of key tracers for source allocation. Irrespective of emission inventory and models used, particulate matter concentrations are under predicted in Delhi, which faces huge air pollution-related issues. Dust and traffic emissions are the major sources of particulate matter in India.
... Air pollution studies in other Indian cities are more limited, but also consistently show significant exceedances of air pollutant concentrations over national and international standards. In 2010, annual average PM 10 concentrations in six Indian cities (Pune, Chennai, Indore, Ahmedabad, Surat, and Rajkot) ranged from 73 to 119 μg m −3 , all above the national standard and corresponding to 15,200 premature deaths per year, with contributions from industrial activities, transportation, and road dust (Guttikunda and Jawahar, 2012). ...
Article
Full-text available
Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or “airsheds,” for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM10 anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM10 increases by 16.34 μg m⁻³, visibility decreases by 0.155 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM2.5 in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 μg m⁻³, or more than 1000% above the 24-h PM2.5 guideline (25 μg m⁻³) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.
... We find that ambient PM2.5 pollution is a pan-India problem with a regional character. which are not just limited to specific urban centres or megacities, examined in earlier studies (Jain and Khare, 2008;Guttikunda et al., 2012;Sharma and Maloo, 2005). ...
Article
Full-text available
India currently experiences degraded air quality, with future economic development leading to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015–2050, under specific pathways of diffusion of cleaner and more energy efficiency technologies. The impacts of individual source-sectors on PM2.5 concentrations were assessed through GEOS-Chem model simulations of spatially and temporally resolved particulate matter concentrations, followed by population-weighted aggregation to national and state levels. PM2.5 pollution is a pan-India problem, with a regional character, not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 standard (40 µg/m³). Future evolution of emissions under current regulation or under promulgated or proposed regulation, yield deterioration in future air-quality in 2030 and 2050. Only under a scenario where more ambitious measures are introduced, promoting a total shift away from traditional biomass technologies and a very large shift (80–85 %) to non-fossil electricity generation was an overall reduction in PM2.5 concentrations below 2015 levels achieved. In this scenario, concentrations in 20 states and six union territories would fall below the national standard. However, even under this ambitious scenario, 10 states (including Delhi) would fail to comply with the national standard through to 2050. Under present day (2015) emissions, residential biomass fuel use for cooking and heating is the largest single sector influencing outdoor air pollution across most of India. Agricultural residue burning is the next most important source, especially in north-west and north India, while in eastern and peninsular India, coal burning in thermal power plants and industry are important contributors. The relative influence of anthropogenic dust and total dust is projected to increase in all future scenarios, largely from decreases in the influence of other PM2.5 sources. Overall, the findings suggest a large regional background of PM2.5 pollution (from residential biomass, agricultural residue burning and power plant and industrial coal), underlying that from local sources (transportation, brick kiln, distributed diesel) in highly polluted areas.
... However, the UTII might also have negative effect on reduce air pollution since the derived demand of consumers, the road dust and other factors that increase air pollution would increase (Guttikunda et al., 2014;Beirão and Cabral, 2007;B€ orjesson et al., 2015;Duran-Fernandez and Santos, 2014;Pant and Harrison, 2012;Guttikunda and Jawahar, 2012). Therefore, it is still a controversial issue for the China's policymaker whether to speed up the UTII or not. ...
Article
Emissions from heavy urban traffic have been the most abundant components of urban air pollution in China. Compared to the fast increasing consumption of automobile, the growth rate of urban traffic infrastructure investment (UTII) is relative low. It is a controversial issue for the policymaker whether promoting the UTII could make a positive impact on reducing air pollution or not. This study is designed to test the relations between the UTII and air quality, using the data of 83 cities from 2000 to 2012. Based on the empirical results from the fixed effect model and dynamic panel data model, increasing the UTII could generally mitigate the air pollution, but the long-run and short-run effects are significantly different. In the short run, the UTII effect on air quality is −0.02, since the urban traffic infrastructure construction might cause more detours and road blockages, which would enhance the fine-particle emissions of the low-speed traffic. In contrast, the UTII could widen the roads and make the traffic system more accessible in the long run, so the estimated positive effect is about 0.05. The robustness tests about different regions and scales of cities are conducted. Policy suggestions are further recommended to reduce air pollution.
... The dominance of fossil fuels now and in future, will pose unique sustainability challenges besides climate change-for energy security and air pollution (Taylor, 2017). Air pollution is a significant problem in Indian cities (WHO, 2014) and vehicular emissions and road dust are major sources of air pollution (Guttikunda and Jawahar, 2012). Transport sector is the largest consumer of oil and its high dependence on imports raises significant concern for energy security. ...
Article
The Paris agreement stresses on concerted efforts to limit global temperature increase to 2 °C and make efforts towards achieving 1.5 °C temperature stabilization. Countries announced actions under the Nationally Determined Contributions outlining domestic mitigation actions to achieve the global target. Understanding the impact of these actions on achieving these ambitions requires an assessment of long term national level scenarios. Limited studies currently exist that model long term scenarios at national level addressing the impacts of Nationally Determined Contributions and the additional actions required, especially at the sectoral level. The paper compares four alternate future scenarios for India spanning till 2050, with a specific focus on the passenger and freight transportation. The analysis is performed using the ANSWER MARKAL model and complemented with methodologies to estimate transportation demand under strong decarbonisation pathways. The results show that 1.5 °C scenario would need immediate actions and deep transformations. Demand side actions would, in addition to infrastructure investments require transforming human behaviour through use of information technology, internet and sharing economy. Clean vehicle technologies need to play a much bigger role and fossil fuel dependence would be moderated with the dominance of electricity, hydrogen and biofuels. The higher share of electricity in transport is complimented with accelerated decarbonisation of electricity. This transformation required for 1.5 °C scenario calls for innovations that would be driven through national and sectoral policies and explicit carbon prices.
... Air pollution is a difficult issue to deal with, which span across multiple sources from vehicular emission, resuspended dust, industrial plumes, construction material, waste burning, domestic heating and cooking. In addition to these reasons, there are various seasonal sources like, burning of agricultural waste, dust storms or sandstorms and sea-salts [1]. Air pollution causes global warming and resultant into the climate change. ...
Conference Paper
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The most vulnerable global challenges faced today are of global warming and its effect on climate with deteriorating air quality. Air pollution is increasing and causing global warming, rise in sea level, change in seasonal patterns, rainfall pattern, extreme summer and winter temperatures, droughts and floods, etc. along with various endemic and epidemic diseases. There is a lack of understanding of air pollution and related health risk. The condition of air quality in India is poor. As many as 54% of Indians live in cities not meeting NAAQS standards on fine particulate matter and none of the cities meeting WHO standards. The whole world, including India, is worried about the degradation of air quality which is affecting every form of life and material; hence there is a need for extensive study on the causes, effects and mitigation of air pollution. A scientific model is proposed to control environmental pollution. The ultimate solution of global warming climate change problem is making the people aware about the causes, consequences, and control of energy consumption through environmental consciousness.
... A few global simulations have included a portion of the AFCID inventory (Shindell et al 2012, Anenberg et al 2012). Some regional inventories explicitly provide some portion of PM 2.5 AFCID as a separate source category (e.g., Pouliot et al 2015) enabling inclusion in regional chemical transport models and air quality models (e.g., Park et al 2010, Guttikunda and Jawahar 2012, Appel et al 2013, Zhang et al 2015. However, the contribution of AFCID sources to PM 2.5 mass remains poorly quantified, especially at the global scale. ...
Article
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Global measurements of the elemental composition of fine particulate matter across several urban locations by the Surface Particulate Matter Network reveal an enhanced fraction of anthropogenic dust compared to natural dust sources, especially over Asia. We develop a global simulation of anthropogenic fugitive, combustion, and industrial dust which, to our knowledge, is partially missing or strongly underrepresented in global models. We estimate 2-16 μg m⁻³ increase in fine particulate mass concentration across East and South Asia by including anthropogenic fugitive, combustion, and industrial dust emissions. A simulation including anthropogenic fugitive, combustion, and industrial dust emissions increases the correlation from 0.06 to 0.66 of simulated fine dust in comparison with Surface Particulate Matter Network measurements at 13 globally dispersed locations, and reduces the low bias by 10% in total fine particulate mass in comparison with global in situ observations. Global population-weighted PM2.5 increases by 2.9 μg m⁻³ (10%). Our assessment ascertains the urgent need of including this underrepresented fine anthropogenic dust source into global bottom-up emission inventories and global models.
... If health externalities of ambient PM pollution are used as input to existing energy models, the total health related externality costs and total energy system costs relative to technology and relocation of plants in the heat and power sector can be decreased by 18% and 4% respectively [17]. The understanding on many aspects of energy efficiency, climate change, air quality and associated health effects has drastically increased in recent years on global [18,19], national [20][21][22] and sub-regional scales [23][24][25][26][27]. ...
Article
Actions to reduce the combustion of fossil fuels often decrease GHG emissions as well as air pollutants and bring multiple benefits for improvement of energy efficiency, climate change, and air quality associated with human health benefits. The China’s cement industry is the second largest energy consumer and key emitter of CO2 and air pollutants, which accounts for 7% of China’s total energy consumption, 15% of CO2, and 14% of PM2.5, respectively. In this study, a state-of-the art modeling framework is developed that comprises a number of different methods and tools within the same platform (i.e. provincial energy conservation supply curves, the Greenhouse Gases and Air Pollution Interactions and Synergies, ArcGIS, the global chemistry Transport Model, version 5, and Health Impact Assessment) to assess the potential for energy savings and emission mitigation of CO2 and PM2.5, as well as the health impacts of pollution arising from China’s cement industry. The results show significant heterogeneity across provinces in terms of the potential for PM2.5 emission reduction and PM2.5 concentration, as well as health impacts caused by PM2.5. Implementation of selected energy efficiency measures would decrease total PM2.5 emissions by 2% (range: 1–4%) in 2020 and 4% (range: 2–8%) by 2030, compared to the baseline scenario. The reduction potential of provincial annual PM2.5 concentrations range from 0.03% to 2.21% by 2030 respectively, when compared to the baseline scenario. 10,000 premature deaths are avoided by 2020 and 2030 respectively relative to baseline scenario. The provinces of Henan and Hubei account for 43% of total avoided premature deaths, followed by Chongqing (9%) and Shanxi (10%), respectively. If only considering the energy saving benefits, 37% of energy efficiency measures are not cost effective. However, the co-benefits (including energy saving, CO2 reduction, and health benefits) are about two times higher than the costs of energy efficiency measures. Hence, this study clearly demonstrates that simultaneous planning of energy and air quality policies creates a possibility of increasing economic efficiency in both policy areas.
... Unreliable electricity supplies can impose a variety of socio-economic costs. Recent studies indicate that unreliable electricity can reduce firm productivity [1], with effects differing across industries [2,3], distort the distribution of firm sizes [4], increase mortality [5], impair birth outcomes [6], reduce household welfare [7,8], motivate purchases of backup power equipment [9,10], and impair air quality [11]. ...
Article
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Unreliable electricity supplies are common in developing countries and impose large socioeconomic costs, yet precise information on electricity reliability is typically unavailable. This paper presents preliminary results from a machine-learning approach for using satellite imagery of nighttime lights to develop estimates of electricity reliability for western India at a finer spatial scale. We use data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Partnership (SNPP) satellite together with newly-available data from networked household voltage meters. Our results point to the possibilities of this approach as well as areas for refinement. With currently available training data, we find a limited ability to detect individual outages identified by household-level measurements of electricity voltage. This is likely due to the relatively small number of individual outages observed in our preliminary data. However, we find that the approach can estimate electricity reliability rates for individual locations fairly well, with the predicted versus actual regression yielding an R 2 > 0.5. We also find that, despite the after midnight overpass time of the SNPP satellite, the reliability estimates derived are representative of daytime reliability.
... However, these are not specific in terms of identifying sources and their relative contributions to ambient pollution levels. For Indian states and cities, there are a few integrated models that collate information at the regional level and there are receptor modeling studies which identified source contributions (Guttikunda and Jawahar, 2012). ...
Conference Paper
The rapid growth of the Indian economy, stimulated by industrial and urban expansion has been accompanied by environmental stresses, particularly in air quality. The current capacity in India in research, education, and operational aspects of air quality measurements, modeling, forecasting and regulatory management needs further enhancement. Atmospheric models are useful for assessment of the nature and magnitude of the air pollution. The model studies help in formulation of innovative emission control policies for protecting human health and the environment. The development of models for air pollution assessment has been identified as an important area for future research.
... We utilized multiple layers of spatial proxies to grid the estimated sectoral emissions to 0.01°g rids. The details of the methodology are described in Guttikunda and Jawahar (2012) and Guttikunda et al. (2019) and the layers of information involved in this step are listed in the Supplementary. For example, for the road transport emissions -layers of road density maps of highway, main arterial roads, feeder roads, and others; population density at the grid level; the urban extent of the grid; information on commercial activity in each of the grids in the form of hotels, hospitals, markets, industrial estates, apartment complexes (this information was gathered from google maps API service) and the vehicle speed data presented in Fig. 5, are used as a proxy to ascertain vehicle density spatially and temporally. ...
Article
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Bengaluru - capital of the state of Karnataka is the original “Silicon Valley” of India. In this paper, we present a comprehensive snapshot of the state of air quality in Bengaluru, along with an emissions inventory for the pollutants necessary for chemical transport modeling at 0.01° grid resolution (approximately 1-km), for an urban airshed covering 60 × 60 grids (4300 km ² ). For 2015, emission estimates for the city are 31,300 tons of PM 2.5 , 67,100 tons of PM 10 , 5300 tons of SO 2 , 56,900 tons of NO x , 335,550 tons of CO, and 83,500 tons of NMVOCs. Overall, transport is the key emission source for Bengaluru - vehicle exhaust and on-road dust resuspension account for a combined 56% and 70% of total PM 2.5 and PM 10 emissions; followed by industries (17.8% including the brick kilns), open waste burning (11.0%), and domestic cooking, heating, and lighting (6.5%), in case of PM 2.5 . We conducted particulate pollution source apportionment of local and non-local sources, using WRF meteorological model and CAMx chemical transport modeling system. A comparison of range of 24-hr average modeled PM 2.5 concentrations (36.5 ± 9.0 μg/m ³ ) and monitored PM 2.5 concentrations (32.3 ± 24.2 μg/m ³ ) by month, shows that the model catches the quantitative ranges and qualitative trends. The modeled source contributions highlight the vehicle exhaust (28%) and dust (including on-road resuspended dust and construction activities) (23%), and open waste burning (14%), as the key air pollution sources. Unless there is an aggressive strategy to improve urban planning and public transport options, pollutant emissions under the business as usual scenario are expected to increase at least 50% in 2030 and doubling the urban area with PM 2.5 annual averages above the national ambient standard of 40 μg/m ³ . © 2019 Turkish National Committee for Air Pollution Research and Control
... For example, emissions from manufacturing and construction, household combustion, road dust, solid waste incineration, industrial emission, vehicular emission, thermal power plants, biomass burning, brick kilns, diesel generator sets, and coal combustion were observed to be the major sources of PM 2.5 concentration in Indo-Gangetic Plains (Kulshrestha et al. 2009;Chakraborty and Gupta 2010;Guttikunda and Jawahar 2014;Villalobos et al. 2015). Western India was observed to be affected due to emissions from waste burning, vehicles, industries, household emissions, thermal power plants, and marine sources (Shah and Nagpal 1997;NEERI 2010;Guttikunda and Kopakka 2014) while in southern India household emissions, vehicles, industries, waste burning, construction activities, diesel generator sets, and marine sources (Guttikunda and Jawahar 2012;Guttikunda and Kopakka 2014) were observed to be the major sources. Meteorological factors such as temperature affect the mixing layer height, which plays an important role in the diurnal variation of pollutants (Holzworth 1972;Schäfer et al. 2006). ...
Article
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This paper estimates the regional contribution of high PM2.5 concentration and associated mortality using HYSPLIT back trajectory analysis in eight Indian cities during 2015–2016. Health risk and mortality estimation were carried out using the Integrated Exposure Response function (IER) which was verified using our previous time series study in Delhi. Risk estimates from IER were observed to be slightly over-predicted (2.14%) when compared to health risk from time series study in Delhi. Health risk in the eight cities across the four seasons indicated higher chronic obstructive pulmonary disease (COPD), lung cancer (LC), ischemic heart disease (IHD), and stroke in the northern (COPD = 1.35, LC = 1.50, IHD = 1.39, Stroke = 2.06) and eastern cities (COPD = 1.27, LC = 1.38, IHD = 1.35, Stroke = 1.93) as compared to in southern or western cities. Risk of stroke was observed to be the highest: North = 1.37–1.52, South = 1.20–1.31, East = 1.40–1.52, and West = 1.24–1.35 times to that of other diseases. Uttar Pradesh was observed to be a major contributor to premature mortality in Delhi, Lucknow, and Patna accounting for 30, 71, and 42% of total premature death due to high PM2.5 concentration during winter. Similarly, high PM2.5 concentration from West Bengal and Bangladesh was responsible for 52% of total premature mortality in Kolkata while the Indian Ocean was a major contributor to premature mortality in western and southern cities during winter. Reduction of both local and regional pollution is required to yield a significant reduction in pollution of all cities except Delhi and Lucknow where regional and local sources respectively are dominant.
... Past air pollution related Indian studies have reported peak concentrations of aerosols (Escuin et al., 2008;Murphy et al., 2008;Singh et al., , 2015Sandhu et al., 2018), PM 2.5 and PM 10 (Gadde et al., 2009;Mittal et al., 2009;Vadrevu et al. 2011;Kulshrestha, 2018, 2019) and NOx (Sharma et al., 2003;Sharma and Maloo 2005;Schepers et al., 2014;Ghude et al., 2016). There are various factors like integration of pollutants in a particular area and transboundary movement of air masses processes Godwin and Kobziar, 2011;Guttikunda and Jawahar, 2012;, increase in vehicular activities (Epting et al., 2005;WHO, 2016), thermal power plant emissions (Gurjar et al., 2010;Moorthy et al., 2013), industrial units which lack proper emissions control measures, biomass burning, and domestic activities (Simon et al., 1998;Satheesh et al., 2017;. ...
Chapter
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Air pollution and its impact on human health is a very mysterical problem in Indian sub-continent (Badarinath et al., 2006; Pradhan, 2001; Sonwani and Kulshrestha, 2016). Past air pollution related Indian studies have reported peak concentrations of aerosols (Escuin et al., 2008; Murphy et al., 2008; Singh et al., 2009, 2015; Sandhu et al., 2018), PM2.5 and PM10 (Gadde et al., 2009; Mittal et al., 2009; Vadrevu et al. 2011; Sonwani and Kulshrestha, 2018, 2019) and NOx (Sharma et al., 2003; Sharma and Maloo 2005; Schepers et al., 2014; Ghude et al., 2016). There are various factors like integration of pollutants in a particular area and transboundary movement of air masses processes (Singh et al., 2009; Godwin and Kobziar, 2011; Guttikunda and Jawahar, 2012; Saxena et al., 2020), increase in vehicular activities (Epting et al., 2005; WHO, 2016), thermal power plant emissions (Gurjar et al., 2010; Moorthy et al., 2013), industrial units which lack proper emissions control measures, biomass burning, and domestic activities (Simon et al., 1998; Satheesh et al., 2017; Saxena and Sonwani, 2019).
... The PM 2.5 emission inventory used in this work was established by the Changsha Environmental Protection Bureau in 2014. Total contamination includes primary particulate matters and secondary PM 2.5 precursors containing sulfur dioxide and nitrogen oxides (Guttikunda and Jawahar, 2012;Liu et al., 2016;Yao et al., 2016). After relevant data sets were acquired (Text S1), regional simulations were conducted to obtain the distribution pattern of PM 2.5 . ...
Article
In China, ambient fine particulate matter (PM2.5) causes a large health burden and raises specific concerns for policymakers. However, assessments of the health effects associated with air pollution from industrial land layouts remain inadequate. This study established a comprehensive assessment framework to quantify the health and economic impacts of PM2.5 exposure at different industrial geographical locations. This framework aims to optimize the spatial distribution of industrial emissions to achieve the lowest public health costs in Changsha, a representative industrial city in China. Health effects were estimated by applying the integrated exposure-response model and a long-range pollution dispersion model (CALPUFF). The value of statistical life (VSL) was used to monetize health outcomes. It was found that implementing an optimal industrial land layout can yield considerable social and financial benefits. Compared with the current industrial space layout, in 2030, the averted contribution by Changsha's industrial sector to PM2.5-related mortality and corresponding economic losses will be 60.8% and 0.69 billion US dollars (USD), respectively. The results of optimization analyses highlighted that population density and emission location are significant factors affecting the health burden. This method can identify the optimal geographical allocation of industrial land with minimal expected health and economic burden. These results will also provide policymakers with a measurable assessment of health risks related to industrial spatial planning and the associated health costs to enhance the effectiveness of efforts to improve air quality.
... The transportation sector contributes about 16% of PM 10 and 27% of PM 2.5 pollution load in Ahmedabad. While in Surat and Rajkot transportation sources accounts for around 30% and 26% of total PM 10 and 42% and 40% of PM 2.5 concentration, respectively (Guttikunda and Jawahar, 2012). In Pune, a major portion of emissions of PM 10 originates from road dust (61%) and vehicular sources (18%).Whereas, the contribution of automobile sources of NO 2 emissions is about 95% (Dahiya et al., 2017). ...
Article
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Road transport is the principal means of transportation for both movements of people and goods in India and has gained importance in the overall transport system. This article elaborates the trends of road transportation growth and its significant influences on air quality and public health in India. The unconditional growth of motor vehicles along with the inadequate development in technology, fuel quality and infrastructure makes the air quality awful. Automobile emissions are multi-characteristics and add a major fraction of pollutants into the atmosphere. Currently, most of the Indian cities are critically polluted by vehicular emissions, which leads to acute and chronic health effects on the exposed population. A series of vehicular pollution control norms were already implemented in India. Despite of several policy measures, there was an overall rise in traffic emissions, constantly. As a result, it requires a comprehensive approach to understand pollution levels and its sources regularly. Improving public transport, limiting the number of polluting vehicles on the road, introducing less polluting vehicles (Electric vehicles), Strict emission regulations and removing dust from roads can be a reliable approach to limit vehicular emissions. These strategies should turn out to be an action plan which is time bound and has targets and penalties.
... Reference material with similar quantities of the sample was used. [35][36][37][38] RESULTS AND DISCUSSION In the laboratory, some physicochemical parameters were analyzed using the standard method. The physical and chemical properties of rice mill effluents are shown in Table-1. ...
... The chemical data assimilation algorithm employed in WRF-Chem for assimilation of MODIS AOD retrievals is based on a 3DVAR scheme of the GSI system (version 3.5), similar to Kumar et al. 19 . The GSI-3DVAR scheme combines information from the MODIS AOD and model background AOD to find optimal analysis state by minimizing the following cost function 11 11 ( ) ( ), 22 ...
Article
Air quality has become one of the most important environmental concerns for Delhi, India. In this perspective , we have developed a high-resolution air quality prediction system for Delhi based on chemical data assimilation in the chemical transport model-Weather Research and Forecasting with Chemistry (WRF-Chem). The data assimilation system was applied to improve the PM2.5 forecast via assimilation of MODIS aerosol optical depth retrievals using three-dimensional variational data analysis scheme. Near real-time MODIS fire count data were applied simultaneously to adjust the fire-emission inputs of chemical species before the assimilation cycle. Carbon monoxide (CO) emissions from biomass burning, an-thropogenic emissions, and CO inflow from the domain boundaries were tagged to understand the contribution of local and non-local emission sources. We achieved significant improvements for surface PM2.5 forecast with joint adjustment of initial conditions and fire emissions.
... As per the Gujarat Ecology Commission's report on, "State of Environment Reports of Gujarat -2012 ″ , Ahmedabad has the highest number of air polluting industries in Gujarat, registered in the Gujarat Pollution Control Board (GPCB) ( Commission, 2012 ) . As per the same report, from 2006 to 2010, SPM and RSPM concentration in all the monitoring stations located in residential areas were in high and critical pollution levels, while in industrial areas; RSPM and SPM concentration were in moderate and high pollution levels as per CPCB standard 2005 ( Guttikunda and Jawahar, 2012 ). The city has almost 3000 industrial units including 855 chemical factories, 511 foundries, and 380 textile plants among others. ...
Article
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Ahmedabad is the 5th biggest city and 7th most populated city in India. It is the largest city in Gujarat. The city is spread over a further 450 sq. km. of area. The study report prepared by the World Health Organisation (WHO) in May 2014 reveals that Ahmedabad is the 9th most air polluted city in the world and 5th most air polluted city in India, based on the concentration of fine particulate matter (PM2.5). In this study, six different ambient air quality monitoring locations are selected in Ahmedabad. A sensor-based continuous ambient air quality monitoring instrument is used to monitor the ambient air quality of selected locations for the summer and winter seasons. The concentration of six pollutants is monitored: respirable suspended particulate matter (PM10), fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). The monitoring data shows that in the summer, the average concentration of all the pollutants at all selected locations is within National Ambient Air Quality Standards (NAAQS), 2009. In the winter, gaseous pollutants; an average hourly concentration of O3 and CO; and 24 hrs. the average concentration of SO2 and NO2 are within NAAQS, 2009 at all the selected locations. In the winter, the average concentration of particulate matter (PM10 and PM2.5) are exceeding the standards at four out of six selected locations during monitoring. So, pollutants concentration is more in winter as compared to summer, this may be due to meteorological parameters. The monitoring data also reveals that in Ahmedabad the major responsible pollutants are particulate matters (PM10 and PM2.5) rather than the gaseous pollutants.The monitoring data are used to determine the National Air Quality Index (NAQI), India, and the fuzzy-based Composite Air Quality Index (CAQI). The two indexing systems are compared. In this research article, determination methods of the National Air Quality Index and the Composite Air Quality Index are discussed. The comparison between the two-indexing system reveals that the CAQI estimates more efficiently the pollutants exposure to the population as compared to the NAQI. The CAQI shows the realistic situation, especially when two or more pollutants are exceeding the standards simultaneously. The composite air quality indexing tool is very useful to inform the citizens and to protect human well-being in an urban area. It can be used as a governmental and administrative tool to make abatement strategies and to take effective measures. The wider range of composite air quality indexes proves the superiority over the national air quality index, India.
... Past air pollution related Indian studies have reported peak concentrations of aerosols (Escuin et al., 2008;Murphy et al., 2008;Singh et al., , 2015Sandhu et al., 2018), PM 2.5 and PM 10 (Gadde et al., 2009;Mittal et al., 2009;Vadrevu et al. 2011;Kulshrestha, 2018, 2019) and NOx (Sharma et al., 2003;Sharma and Maloo 2005;Schepers et al., 2014;Ghude et al., 2016). There are various factors like integration of pollutants in a particular area and transboundary movement of air masses processes Godwin and Kobziar, 2011;Guttikunda and Jawahar, 2012;, increase in vehicular activities (Epting et al., 2005;WHO, 2016), thermal power plant emissions (Gurjar et al., 2010;Moorthy et al., 2013), industrial units which lack proper emissions control measures, biomass burning, and domestic activities (Simon et al., 1998;Satheesh et al., 2017;. ...
Chapter
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Biomass burning occurred during Rabi and Kharif season contributes huge emission of gaseous pollutants and particulate matter in the atmosphere which deteriorate the air quality in almost all regions of the world. Crop residue burning activities emits a number of air pollutants like particulate matter (PM), sulfur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), black carbon (BC), and volatile organic compounds (VOCs) that affect the quality of air and human health. Increase in the concentration of these air pollutants made IGP a worldwide hotspot of toxic airborne pollutants and photochemical smog. Crop residue burning also causes reduced visibility and accelerates the risks of transport-related accidents. Biomass burning also leads to the formation of atmospheric brown clouds in mostly Asian regions which further puts impact on ambient air quality, visibility and earth's radiation budget. In spite of the fact that the problem of bad air quality is rapidly increasing due to crop residue burning, there are still very few review studies which focus on addressing this important issue and their impacts on ambient air quality. Hence, this chapter reviews about the sources and impacts of crop residue burning on Indo-Gangetic Plain (IGP). Moreover, it also discuss about the role of crop residue burning in other regions of India and the factors associated with them which will affect their air quality.
Article
To evaluate uncertainty in the spatial distribution of air emissions over India, we compare satellite and surface observations with simulations from the U.S. Environmental Protection Agency (EPA) Community Multi-Scale Air Quality (CMAQ) model. Seasonally representative simulations were completed for January, April, July, and October 2010 at 36 km × 36 km using anthropogenic emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model following version 5a of the Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants project (ECLIPSE v5a). We use both tropospheric columns from the Ozone Monitoring Instrument (OMI) and surface observations from the Central Pollution Control Board (CPCB) to closely examine modeled nitrogen dioxide (NO2) biases in urban and rural regions across India. Spatial average evaluation with satellite retrievals indicate a low bias in the modeled tropospheric column (−63.3%), which reflects broad low-biases in majority non-urban regions (−70.1% in rural areas) across the sub-continent to slightly lesser low biases reflected in semi-urban areas (−44.7%), with the threshold between semi-urban and rural defined as 400 people per km². In contrast, modeled surface NO2 concentrations exhibit a slight high bias of +15.6% when compared to surface CPCB observations predominantly located in urban areas. Conversely, in examining extremely population dense urban regions with more than 5000 people per km² (dense-urban), we find model overestimates in both the column (+57.8) and at the surface (+131.2%) compared to observations. Based on these results, we find that existing emission fields for India may overestimate urban emissions in densely populated regions and underestimate rural emissions. However, if we rely on model evaluation with predominantly urban surface observations from the CPCB, comparisons reflect model high biases, contradictory to the knowledge gained using satellite observations. Satellites thus serve as an important emissions and model evaluation metric where surface observations are lacking, such as rural India, and support improved emissions inventory development.
Chapter
A large number of trips are made by nonmotorized transport in Indian cites. However, majority of the users of nonmotorized transport are captive users, people who do not have any other choice of travel mode. The current state of infrastructure for nonmotorized transport is very poor, and city governments have paid very little attention to investment in developing appropriate infrastructure for nonmotorized transport. Therefore, with the increase in income and access to other motorized modes, these users will move to other modes of transport such as motorized two-wheelers or cars or bus. Improvement in NMT infrastructure can benefit current NMT users by reducing risk from other motorized vehicles. Improved NMT infrastructure is also expected to attract short trips from motorized two-wheelers and bus resulting in lower vehicular emissions. Increase use of NMT results in health benefits by increasing opportunities for active transport. Overall NMT-friendly infrastructure and policies can play a very important role in achieving sustainable transport – providing safe and clean mobility to all city residents.
Technical Report
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Emission Inventory for Bengaluru city at a resolution of 1X1Km
Conference Paper
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This paper deals with the pollution emitted by the Auto Rickshaws of Kalaburagi city and suggestions to reduce the emission levels by the use of an alternative energy resource. The pollution loads have been calculated and compared by considering usage of the Battery Power (Electrical Power) in place of Liquefied Petroleum Gas (LPG) in the Auto Rickshaws of Kalaburagi city. To carry out this study, the Kalaburagi city was considered and collected the required information such as the total number of Auto Rickshaws, daily kilometres operated by these vehicles. Total fuel consumption every day was also collected. These Auto Rickshaws run on LPG fuel and are responsible for largest emissions and various other pollutants. The pollution loads calculated on the basis of information collected from the Central Pollution Control Board (CPCB), Environment Protection Agency and previous studies carried out in this regard by various important agencies. The use of Alternative Energy Resource i.e., battery power we can reduce reduction in various pollutants in gm/km. By the use of Battery Rickshaws we can reduce The Auto Rickshaws travelling in Kalaburagi city with LPG and if replaced with Battery Rickshaws, then reduction in pollution loads in Ton/Year up to 2020 will be: CO-1885.8236 Ton/Year, HC-477.055 Ton/Year, NOx-44.37232 Ton/Year, CO2-75599.3402 Ton/Year PM-144.21004 Ton/Year.
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The response of the human lungs to exposure to various particles like seen in atmospheric pollution, work place, various gases, have been studied in different populations by various studies. The pollution level in Chennai city is moderate whereas it is quite high in the suburbs of Chennai. Aim: To understand the effect of petrol and diesel vapours on lungs in persons working at petrol pump stations in the suburbs of Chennai through Spirometry. Methods: This study was conducted at 20 Petrol pumps in the suburbs of Chennai. Total participants were 250. Of these, 123 were workers [Group I] and 127 were office employees working in the pump stations [Group II]. Spirometry was successfully performed on 102 workers [GroupI] and on 102 office employees [Group II] who were also used as healthy controls. Result: The Spirometry values were significantly reduced in participants working in the petrol pumps as compared to the controls. The reduction further increased with prolonged duration of exposure. Conclusion: This study concludes that the respiratory function declines in those persons working in petrol pumps due to constant exposure to petrol and diesel fumes and the degree of impairment increases with the duration of exposure.
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Rapid urbanization in large cities around the globe demands for hurried development in transportation sector to meet the mobility needs for both people and goods. In doing so, the excessive transportation activities are required resulting congestion, mobility deficiencies, access inequality, inadequate road safety, excess emission of green house gas and above all unsustainable environmental condition with large carbon footprint than the biological capacity of the cities to absorb this mammoth carbon content. Subsequently, environmentally sustainable transport, in other words; green transport, that has the capability to meet the travel demand, improve air quality, reduce contribution toward climate change from transport sector, is increasingly becoming an important research consideration for transportation planning and policy making. Especially for megacity Dhaka, green transportation has become an emerging option for transportation sustainability, as transportation in Dhaka city is one of the major contributors to environmental degradation by emitting enormous carbon dioxide and other air pollutants. Furthermore, sub-standard public transit facilities, increasing use of private automobile and discouraging situation for pedestrian and non-motorized transport users have created chaos in the city. In this context, this study aims to develop an index for quantitative measure of transportation sustainability considering the environmental factors and find some strategic solutions for eco-friendly transportation development. The main objective of the study is to develop “Green Transport Index (GTI)” based on vehicular emission, walkability, facilities of public and non-motorized transport, at mesoscopic level in selected areas. Consequently, it would allow to determine efficient transport strategies to reduce the problems identified from the green transport index values. In order to achieve the objectives, the study utilizes several methods. For the components of GTI, the study develops scoring system and using weighted indexing all these scores are combined to develop the final index value. Considering vehicular emission the study uses activity based emission model to estimate the level of CO2 emission from vehicles, to make CO2 emission comparable with bio-capacity, the study utilizes the concepts of transportation ecological footprint. Applying mathematical relationship, finally emission and bio-capacity score have been determined. For walkability, the study uses global walkability scoring system. While for public transit, the study utilizes public transit facility score depending on the service coverage, average speed, and service quality of public bus. Additionally, for non-motorized transport, the study used non-motorized transport facility score based on service coverage, access time and parking facilities for rickshaw. Finally, all these scores were combined to develop GTI using equal weight and specialists’ weight. Based on the problems identified from GTI values in study areas, we propose some efficient strategies focusing on the user opinions. In this study, a color code was developed to express the index: green is best and red is worst, while yellow and orange express moderate and bad condition of transportation sector respectively. From the results thus obtained among ten selected sites within Dhaka city (focusing on ten most critical transportation intersections) most of the areas are found to be in a condition that is environmentally unsustainable, with color code of red. While others areas are with color code orange indicating an awful condition. The study also finds that, improving facilities of public transit and introducing high speed as well as high capacity separate lane public bus system would help to de-carbonized. Moreover, signal optimization, taxation on mileage would be other options capable of reducing emission. For energy efficient options like walkability, the study finds removal of obstruction and proper sidewalk design would encourage walking. Besides, for non-motorized transport separate lane beside major roads and providing designated parking are some options to improve transportation condition. In gist, the study provides a quick and easy understanding of transportation situation at different areas indicating the level of sustainability; this in turn would assist the policy makers and transport professionals to set vision and proper planning for environment friendly transportation system in Dhaka city.
Conference Paper
Chapter
Health risk associated with air pollution and its exposure has gained much importance in the recent years. The potential toxicity of air pollutants especially particulate matter (PM) is attributed to its chemical composition and size. Hence, it is imperative to understand the morphology, size, and chemical composition of PM for health risk assessment. Polyaromatic hydrocarbons (PAHs) present in PM have high toxicity and mutagenic potential. Recent advancement in technology such as bioassays for cytotoxicity, oxidative stress, and apoptosis studies using human cell lines has allowed us to comprehend the underlying mechanism of particle toxicity and its impact on human health. This chapter deals with the health risks associated with air pollution and exposure assessment with a focus on chemical toxicity associated with air pollutants, especially PM. Health risks associated with particle-bound chemical compounds in school children are also explained in this chapter.
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Hava kalitesi terimi anlam olarak etrafımızı saran hava kütlesi şeklinde tanımlanmakta olup; hava kalitesinin iyi olması durumu ise temiz, kirlenmemiş bir havayı ifade etmektedir. İyi bir hava kalitesi dünya üzerindeki hassas yaşam düzeninin sürdürülebilmesinde önemli bir etkendir. Hava kalitesinin zayıflığı ise, doğal ve insan eliyle meydana gelen kaynaklardan yayılan emisyonların bir sonucu olarak karşımıza çıkmaktadır. Bu durum da yayılan kirletici konsantrasyonlarının insan ve çevre sağlığına etki edecek derecede yüksek seviyelere ulaştığında dikkatleri çekmektedir. Etrafımızı saran hava kalitesini değerlendirmek için birçok farklı yöntem kullanılsa da bu yöntemler arasında en yaygın olanı hava kalitesi modelleme sistemleridir. Farklı kaynaklardan yayılan ve farklı meteorolojik koşullardan etkilenen kirleticilerin kaynaktan uzaklığa bağlı olarak yer seviyesindeki konsantrasyonlarının tahmin edilmesinde kullanılan bu sistemler; dağılım hesaplamalarında, kaynak özellikleri, meteorolojik veriler, çalışma alanının topografyası gibi bilgilere ihtiyaç duymaktadır. Hava kalitesi modelleme yaklaşımında birçok yöntem kullanılmakla birlikte, yaygın olarak kullanılan yöntemlerden biri matematiksel model temelli bilgisayar programlarıdır. Bu programlar çalışma türüne ve çalışma alanına göre farklı özellikler göstermekte, ayrıca kendilerine özgü avantaj ve dezavantajlara sahip olabilmektedirler. Yapılan bu çalışmada hava kalitesi modelleme sistemleri ve bu sistemlerin çalışma prensipleri hakkında incelemeler yapılmış, dünyada yaygın olarak kullanılan modelleme programları hakkında bilgiler verilmiştir.
Chapter
Air pollution is a vital global public health concern which is generally addressed by collective societal action, particularly to control emissions, i.e. primary air pollutants which are precursors in the formation of secondary air pollutants via different atmospheric chemical reactions. The massive increase in emission of air pollutants in the atmosphere is major cause of human health and environmental problems. According to WHO, it is revealed that particulate matter (PM) exposure is responsible for ~800,000 premature deaths alone each year as compared to other air pollutants. Therefore, more systematic studies for the measurement of various air pollutants are still required to examine the current scenario and their physicochemical characteristics especially focused on PM. This will aid in health risk assessment of air pollutants by using various tools and estimation methods. The present chapter describes the brief introduction of air pollutants and their emission source characteristics along with detailed systematic findings and outcomes of the different studies. In addition, the methods/equations and diverse tools used for risk assessment by scientific community and various researchers have been introduced at regional and global level. Also, the methods and approaches that can be employed for the management of air pollutants (indoor and outdoor) in Indian context have been described. Overall, the chapter gives an idea about the deterioration of air quality due to emission of various pollutants, their formation and management methods along with the concerned health issues. This will serve as an imperative document for the scientific community and policy makers to develop effective mitigation policies with respect to air quality improvement.
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Our health is closely related to our environment, such that a healthy environment brings healthy living and vice versa. Pollution due to air is a prime environmental aspect contributing to the burden of different diseases in human and also has considerable economic impact. The total air pollution accounts approximately 7 million deaths globally. Pollutants produced as combustion of particulate matter have demonstrated a time-series effect on human health. The size of inhalable particulate matter (PM10 and PM2.5) affects the mortality and morbidity upon short- and long-term exposure among all population, with highest effect on elderly individuals. Exposure to these pollutants produces the pathological alteration, such as increased inflammatory response, systemic oxidative stress, cardiovascular stress, and change in pulmonary autonomous nervous system activity. These molecular pathological events trigger several pulmonary and cardiovascular manifestations in human. From epidemiology point of view, it has been explored that among different air pollutants, particulate matter, ozone, carbon monoxide, nitrogen dioxide and sulfur dioxide are the major ones. The highest mortality is mainly observed in Asian populations as compared to Europeans and Americans. The top ten countries with the highest mortality are China, India, Pakistan, Bangladesh, Nigeria, the United States, Russia, Brazil, and Philippines, respectively. In this chapter, we reviewed different PM exposure-based epidemiological studies with more focus on high ambient Total Suspended Particulate (TSP) levels. It has also been found that overall absolute risk for mortality due to PM exposure is higher for cardiovascular compared to pulmonary disorders in case of both acute and chronic exposures.
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A key challenge in controlling Delhi’s air quality is a lack of clear understanding of the impacts of emissions from the surrounding National Capital Region (NCR). Our objectives are to understand the limitations of publicly available data, its utility to determine pollution sources across Delhi-NCR and establish seasonal profiles of chemically active trace gases. We obtained the spatiotemporal characteristics of daily-averaged particulate matter (PM10 and PM2.5) and trace gases (NOX, O3, SO2, and CO) within a network of 12 air quality monitoring stations located over 2000km2 across Delhi-NCR from January 2014 to December 2017. The highest concentrations of pollutants, except O3, were found at Anand Vihar compared with lowest at Panchkula. A high homogeneity in PM2.5 was observed among Delhi sites as opposed to a high spatial divergence between Delhi and NCR sites. The bivariate polar plots and k-means clustering showed that PM2.5 and PM10 concentrations are dominated by local sources for all monitoring sites across Delhi-NCR. A consequence of the dominance of local source contributions to measured concentrations, except to one site remote from Delhi, is that it is not possible to evaluate the influence of regional pollution transport upon concentrations measured at sites within Delhi and the NCR.
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The south Asian counties of India, Pakisthan and Bangaladesh having the megacities of New Delhi, Mumbai, Dhaka, Karachi, Kolkata, Lahore, Bangalore, Chennai now further the emerging mega cities of, Hyderabad and Ahmadabad will be added in 2030. Hence, presently the south Asian economic growth is mega city based industrialization and service sectorial oriented economic development in the particular countries. Further, it attract the rapid migrated population in and around the city areas without satisfying the essential needs of the people. Among the problems, air pollution significant problems with huge vehicle discharges and industrial gases that react in the atmosphere with sunlight to form secondary pollutants. It also combine with the primary emissions to form photochemical smog. It consequences large consumption of energy and other resources, which contributes to the severe air pollution. It leads the Critical air pollutants Sulfur dioxide (SO2), Oxides of nitrogen (NOx), Particulate matter, Polycyclic Aromatic Hydrocarbons (PAH), Carbon monoxide (CO) and Greenhouse gases in the south Asian Mega Cities. Air pollution has a major health and environmental impacts in South Asian mega cities. It affects the sustainable and inclusive economic development of the region. Hence, it is necessary to adopt certain Mitigation Measures such as Natural resources management and greening the megacities, using cleaner fossil fuels, such as natural gas, burning these fuels more efficiently and increasing reliance over renewable sources of energy, transport regulation, encouraging the use of low- carbon forms of transport, introduction of electricity based vehicles, Industrial emissions regulation with Environmental Protection Act, Controlling the Biomass burning, Greening the mega cities, Control the migration by providing diversified enterprise opportunities in the villages and development of Rurban clusters in the villages may directly and indirectly control the air pollution issues in the south Asian mega cities. It leads the economic development and the best ways to control or reduce the air pollution to address the United Nations Sustainable Development Goals (SDGs). Further, creation of innovative ways to reduce the pollution through appropriate research studies and awareness programmes to improve the knowledge level of the people for eradicating the air pollution issues. Finally, the Individual social responsibility is very important to reduce the air pollution in the South Asian megacities.
Chapter
Major anthropogenic sources of these emissions include vehicular transport and industrial activity. The industrial sector accounts for the largest share of delivered energy consumption and is expected to consume over half of the global delivered energy in 2040. 31% of the world energy consumption or 200 quadrillion British Thermal unit (Btu) is consumed in the industrial sector worldwide. This is expected to rise to 307 Btu in 2040. Commensurate with the energy consumption in the world, worldwide energy-related carbon dioxide emissions are expected to increase from 31 billion metric tons to 36 billion metric tons in 2020 and 45 billion metric tons in 2040. Greenhouse gas emissions for 2012 are estimated to be 31.6 Gt (Gt). This paper examines how much carbon dioxide can be attributed to industry and what are the ways to decarbonize industry in the Indian context. While the regulatory mechanism required to reduce energy intensity is in place for the most energy-intensive industrial sectors, the generation of electricity is still primarily dependent of coal. Use of renewable needs to be stepped up and is line with India’s commitment of INDCs.
Technical Report
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The PM pollution in the greater Patna region is often above the national standards and the WHO guidelines. The emissions inventory for the Greater Patna region was developed for total PM in two size fractions (PM10 and PM2.5), sulfur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs), and carbon dioxide (CO2). All the databases, calculations, and interfaces are available as spreadsheets for easy access and model transparency. To assess air quality, a 60km x 30km area was selected, which includes most of the industrial estates and brick kiln clusters in and around Patna. PM2.5 pollution is estimated to result in 2,600 premature deaths, 200,000 asthma attacks, and 1,100 cardiac admissions in 2012 and could reach 4,900 premature deaths, 507,000 asthma attacks, and 2,850 cardiac admissions in 2030, if no control measures are introduced and enforced. We benchmarked the emission sources and following emission reduction strategies were considered (1) Emission control options for the brick kiln manufacturing – technology changes, landuse changes (relocation) and operational changes (raw material) (2) Introduction of cleaner fuel for the in-use vehicle fleet, which currently has access to only Bharat-3 type fuel (3) Improvements in the public- and para- transit systems and introduction of alternative fuel (CNG) for these modes (4) Targeting the diesel generator sets, with thermal power plant in Barh coming online to support the electricity demand in the city (5) Controlling dust resuspension on the roads and (6) Combination all the above five scenarios.
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Indian cities have some of the poorest air quality globally but volatile organic compounds (VOCs)—many of which adversely affect health—and their indoor sources remain understudied in India. In this pilot study we quantified hundreds of VOCs inside and outside 26 homes in Ahmedabad and Gandhinagar, Gujarat, in May 2019 and in January 2020. We sampled in the morning and afternoon/evening to capture temporal variability. Total indoor VOCs were measured at higher concentrations in winter (327.0 ± 224.2 µgm−3) than summer (150.1 ± 121.0 µgm−3) and exceeded those measured outdoors. Using variable reduction techniques, we identified potential sources of compounds (cooking, plastics [with an emphasis on plasticizers], consumer products, siloxanes [as used in the production of consumer products], vehicles). Contributions differed by season and between homes. In May, when temperatures were high, plastics contributed substantially to indoor pollution (mean of 42% contribution to total VOCs) as compared to in January (mean of 4%). Indoor cooking and consumer products contributed on average 29% and 10% to all VOCs indoors in January and 16% and 4% in May. Siloxane sources contributed <4% to any home during either season. Cooking contributed substantially to outdoor VOCs (on average 18% in January and 11% in May) and vehicle-related sources accounted for up to 84% of VOCs in some samples. Overall, results indicate a strong seasonal dependence of indoor VOC concentrations and sources, underscoring the need to better understand factors driving health-harming pollutants inside homes to facilitate exposure reductions.
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Fine particle organic carbon in Delhi, Mumbai, Kolkata, and Chandigarh is speciated to quantify sources contributing to fine particle pollution. Gas chromatography/mass spectrometry of 29 particle-phase organic compounds, including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and levoglucosan along with quantification of silicon, aluminum, and elemental carbon are used in a molecular-marker based source apportionment model to quantify the primary source contributions to the PM2.5 mass concentrations for four seasons in three sites and for the summer in Chandigarh. Five primary sources are identified and quantified: diesel engine exhaust, gasoline engine exhaust, road dust, coal combustion, and biomass combustion. Important trends in the seasonal and spatial patterns of the impact of these five sources are observed. On average, primary emissions from fossil fuel combustion (coal, diesel, and gasoline) are responsible for about 25–33% of PM2.5 mass in Delhi, 21–36% in Mumbai, 37–57% in Kolkata, and 28% in Chandigarh. These figures can be compared to the biomass combustion contributions to ambient PM2.5 of 7–20% for Delhi, 7–20% for Mumbai, 13–18% for Kolkata, and 8% for Chandigarh. These measurements provide important information about the seasonal and spatial distribution of fine particle phase organic compounds in Indian cities as well as quantifying source contributions leading to the fine particle air pollution in those cities.
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A study of the winter time size distribution and source apportionment of total suspended particulate matter (TSPM) and associated heavy metal concentrations have been carried out for the city of Delhi. This study is important from the point of view of implementation of compressed natural gas (CNG) as alternate of diesel fuel in the public transport system in 2001 to reduce the pollution level. TSPM were collected using a five-stage cascade impactor at six sites in the winters of 2005–06. The results of size distribution indicate that a major portion (~40%) of TSPM concentration is in the form of PM0.7 (
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Abstract Fossil fuels account for about 80% of energy consumption in Asia. Because of its abundance and easy recoverability, especially in India and China, coal will remain the fuel of choice in the foreseeable future. If current trends continue, sulfur dioxide emissions from Asia may soon equal the emissions from North America and Europe combined. These trends portend a variety of local, regional, and global environmental impacts. Acid rain damages human health, ecosystems, and built surfaces. Many ecosystems will be unable to absorb these increased acidic depositions, leading to irreversible ecosystem damage with far-reaching implications for health, forestry, agriculture, fisheries, and tourism. RAINS-ASIA is a scenario-generating tool used to estimate the extent of damages caused by acid rain and to review the costs and impacts of alternatives to provide a look into the future. Its use extends from national-, regional-, and city-scale evaluation and inputs for cost-effective options analyses, to international negotiations on transboundary pollution.
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A decentralized emission inventories are prepared for road transport sector of India in order to design and implement suitable technologies and policies for appropriate mitigation measures. Globalization and liberalization policies of the government in 90's have increased the number of road vehicles nearly 92.6% from 1980–1981 to 2003–2004. These vehicles mainly consume non-renewable fossil fuels, and are a major contributor of green house gases, particularly CO2 emission. This paper focuses on the statewise road transport emissions (CO2, CH4, CO, NOx, N2O, SO2, PM and HC), using region specific mass emission factors for each type of vehicles. The country level emissions (CO2, CH4, CO, NOx, N2O, SO2 and NMVOC) are calculated for railways, shipping and airway, based on fuel types. In India, transport sector emits an estimated 258.10 Tg of CO2, of which 94.5% was contributed by road transport (2003–2004). Among all the states and Union Territories, Maharashtra's contribution is the largest, 28.85 Tg (11.8%) of CO2, followed by Tamil Nadu 26.41 Tg (10.8%), Gujarat 23.31 Tg (9.6%), Uttar Pradesh 17.42 Tg (7.1%), Rajasthan 15.17 Tg (6.22%) and, Karnataka 15.09 Tg (6.19%). These six states account for 51.8% of the CO2 emissions from road transport.
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Results from the Model Intercomparison Study Asia Phase II (MICS-Asia II) are presented. Nine different regional modeling groups simulated chemistry and transport of ozone (O3), secondary aerosol, acid deposition, and associated precursors, using common emissions and boundary conditions derived from a global model. Four-month-long periods, representing 2 years and three seasons (i.e., March, July, and December in 2001, and March in 2002), are analyzed. New observational data, obtained under the EANET (the Acid Deposition Monitoring Network in East Asia) monitoring program, were made available for this study, and these data provide a regional database to compare with model simulations. The analysis focused around seven subject areas: O3 and related precursors, aerosols, acid deposition, global inflow of pollutants and precursor to Asia, model sensitivities to aerosol parameterization, analysis of emission fields, and detailed analyses of individual models, each of which is presented in a companion paper in this issue of Atmospheric Environment. This overview discusses the major findings of the study, as well as information on common emissions, meteorological conditions, and observations.
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Cookstoves in developing countries are individually small, but so numerous that, depending on emission factors, they could be significant influences on global and regional carbon monoxide (CO) inventories. This paper presents a new database of CO emission factors for commonly used cookstoves in developing countries. The emission factors were determined using a carbon balance approach for 56 types of fuel/stove combinations in China and India. These include various stoves (e.g., traditional, improved, mud, brick, and metal, with and without chimney) using animal dung, different species of crop residues and wood, root fuel, charcoal, kerosene, and several types of coals and gases. The chosen fuel/stove combinations represent a large fraction of the total in developing countries. Thus, the database can be used to improve estimates of CO emission inventories. The CO emission factors ranged widely, from 3.0 × 10−2 g/kg for the coal gas/traditional stove to 2.8 × 102 g/kg for the charcoal/Angethi stove, nearly 4 orders of magnitude. Since stove efficiencies and fuel energy contents were measured simultaneously, CO emission factors on the basis of a standard cooking task (energy delivered) were also determined and reported in this paper. Task-based emission factors are particularly useful for comparing the air pollution potential of different fuel/stove combinations and assessing the impacts of substitutions.
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Vehicles affect the concentrations of ambient airborne particles through exhaust emissions, but particles are also formed in the mechanical processes in the tire-road interface, brakes, and engine. Particles deposited on or in the vicinity of the road may be re-entrained, or resuspended, into air through vehicle-induced turbulence and shearing stress of the tires. A commonly used term for these particles is road dust . The processes affecting road dust emissions are complex and currently not well known. Road dust has been acknowledged as a dominant source of PM10 especially during spring in the sub-arctic urban areas, e.g. in Scandinavia, Finland, North America and Japan. The high proportion of road dust in sub-arctic regions of the world has been linked to the snowy winter conditions that make it necessary to use traction control methods. Traction control methods include dispersion of traction sand, melting of ice with brine solutions, and equipping the tires with either metal studs (studded winter tires), snow chains, or special tire design (friction tires). Several of these methods enhance the formation of mineral particles from pavement wear and/or from traction sand that accumulate in the road environment during winter. When snow and ice melt and surfaces dry out, traffic-induced turbulence makes some of the particles airborne. A general aim of this study was to study processes and factors underlying and affecting the formation and emissions of road dust from paved road surfaces. Special emphasis was placed on studying particle formation and sources during tire road interaction, especially when different applications of traction control, namely traction sanding and/or winter tires were in use. Respirable particles with aerodynamic diameter below 10 micrometers (PM10) have been the main concern, but other size ranges and particle size distributions were also studied. The following specific research questions were addressed: i) How do traction sanding and physical properties of the traction sand aggregate affect formation of road dust? ii) How do studded tires affect the formation of road dust when compared with friction tires? iii) What are the composition and sources of airborne road dust in a road simulator and during a springtime road dust episode in Finland? iv) What is the size distribution of abrasion particles from tire-road interaction? The studies were conducted both in a road simulator and in field conditions. The test results from the road simulator showed that traction sanding increased road dust emissions, and that the effect became more dominant with increasing sand load. A high percentage of fine-grained anti-skid aggregate of overall grading increased the PM10 concentrations. Anti-skid aggregate with poor resistance to fragmentation resulted in higher PM levels compared with the other aggregates, and the effect became more significant with higher aggregate loads. Glaciofluvial aggregates tended to cause higher particle concentrations than crushed rocks with good fragmentation resistance. Comparison of tire types showed that studded tires result in higher formation of PM emissions compared with friction tires. The same trend between the tires was present in the tests with and without anti-skid aggregate. This finding applies to test conditions of the road simulator with negligible resuspension. Source and composition analysis showed that the particles in the road simulator were mainly minerals and originated from both traction sand and pavement aggregates. A clear contribution of particles from anti-skid aggregate to ambient PM and dust deposition was also observed in urban conditions. The road simulator results showed that the interaction between tires, anti-skid aggregate and road surface is important in dust production and the relative contributions of these sources depend on their properties. Traction sand grains are fragmented into smaller particles under the tires, but they also wear the pavement aggregate. Therefore particles from both aggregates are observed. The mass size distribution of traction sand and pavement wear particles was mainly coarse, but fine and submicron particles were also present. Moottoriajoneuvot päästävät hiukkasia ilmaan pakokaasujen mukana, mutta niitä muodostuu myös mekaanisissa prosesseissa tien pinnan ja renkaan vuorovaikutuksessa, jarruissa ja moottorissa. Lisäksi hiukkaset, jotka ovat laskeutuneet tien pinnalle tai sen lähettyville voivat nousta ilmaan uudelleen ajoneuvojen aiheuttamien ilmavirtojen tai renkaiden nostattamina (resuspensio). Yleistermi näille hiukkasille on katupöly . Katupölyn muodostumiseen ja päästöihin vaikuttavat prosessit ovat monimutkaisia ja tällä hetkellä huonosti tunnettuja. Katupöly muodostaa erityisesti keväisin merkittävän osan keuhkohengitettävistä PM10 hiukkasista maapallon pohjoisilla alueilla kuten Skandinaviassa, Pohjois-Amerikassa ja Japanissa. Korkeat katupölypitoisuuksien on esitetty olevan seurausta lumisista ja jäisistä talviolosuhteista, joiden takia liikenteessä on käytettävä liukkaudentorjuntaa. Liukkaudentorjuntamenetelminä käytetään esimerkiksi talvihiekoitusta ja teiden suolausta. Lisäksi autoissa käytetään joko nastallisia tai nastattomia talvirenkaita (kitkarenkaita), joiden suunnittelussa on erityisesti kiinnitetty huomiota renkaiden pitoon liukkaissa talviolosuhteissa. Useat liukkaudentorjuntamenetelmistä lisäävät mineraalihiukkasten muodostumista tien päällysteen tai hiekoitushiekan kulumatuotteina. Muodostuneet hiukkaset kerääntyvät tieympäristöön talven aikana. Keväällä kun lumi ja jään sulaa ja pinnat kuivuvat, hiukkasia nousee ilmaan merkittäviä määriä mm. liikenteen aiheuttamien ilmavirtauksien nostamina. Yleisenä tavoitteena tutkimuksessa oli selvittää katupölyn muodostumiseen vaikuttavia tekijöitä ja prosesseja päällystetyillä pinnoilla. Erityisenä painopisteenä oli tutkia hiukkasten muodostumista tien pinnan ja renkaan vuorovaikutuksessa, käytettäessä talvirenkaita ja hiekoitusmursketta. Mittausten kohteena olivat keuhkohengitettävät hiukkaset, joiden aerodynaaminen halkaisija on alle 10 mikrometriä (PM10), mutta myös muita hiukkaskokoluokkia tutkittiin. Tutkimuksessa selvitettiin seuraavia kysymyksiä: i) Miten talvihiekoitus ja hiekoitusmateriaalin fysikaaliset ominaisuudet vaikuttivat katupölyn muodostumiseen? ii) Miten nastoitetut talvirenkaat erosivat pölyn muodostumisen osalta nastoittamattomista talvirenkaista (kitkarenkaista)? iii) Mikä oli katupölyn koostumus ja lähteet testiradalla sekä keväisen katupölyepisodin aikana Suomessa? iv) Mikä oli tien ja renkaan vuorovaikutuksessa syntyneiden hiukkasten kokojakauma? Tutkimukset suoritettiin testiradalla ja kaupunkiolosuhteissa. Testiradalla saatujen koetulosten perusteella hiekoitus lisäsi PM10-katupölyn muodostumista ja että päästöt kasvoivat hiekoitusmurskeen määrää lisättäessä. Pölyn muodostumista lisäsivät lisäksi murskeen heikompi iskunkestävyys sekä materiaalin korkea hienoainespitoisuus. Rengastyyppien vertailu koeolosuhteissa osoitti, että pölyä muodostui enemmän nastoitetuilla talvirenkailla kuin nastoittamattomilla, nk. kitkarenkailla. Sama trendi havaittiin myös hiekoitetuissa testeissä. Koeolosuhteissa havaitut hiukkaset olivat pääasiassa mineraaleja ja peräisin päällysteen kiviaineksesta ja/tai hiekoitusmurskeesta. Hiekoitetuissa kokeissa havaittiin nk. hiekkapaperi-ilmiö: hiekoitusmurske hajoaa pienemmiksi partikkeleiksi renkaan alla, mutta syntyneet partikkelit kuluttavat myös päällystettä. Näin ollen pölyssä havaitaan hiukkasia molemmista lähteistä. Myös kaupunkiolosuhteissa talvihiekoituksen havaittiin olevan tärkeä hiukkaslähde. Hiukkasten massakokojakaumassa karkeat hiukkaset muodostavat valtaosan, mutta myös pienhiukkasia (PM2.5) havaittiin.
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This paper explores the adaptation of a regional Lagrangian approach for making long-term simulations of SO2 and sulfate ambient concentrations at the resolution needed for health effects risk assessment in Asian megacities and their surroundings. A Lagrangian trajectory model (UR-BAT) is described which simulates transport and diffusion of sulfur within and near urban areas, originating from area and major point sources. The long-range contribution is accounted for by the ATMOS model, simulating all Asian sources. The model has been applied to Beijing and Bombay, by using preliminary emission figures, and the results have been compared with available monitoring data. The computed concentrations in different cities are in the correct range, indicating the potential use of the model in an integrated assessment framework such as RAINS-Asia.
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Sulfur transport and deposition in Asia, on an annual andseasonal basis, is analyzed using the ATMOS model. Calculationsare performed for two complete years (1990 and 1995). Deposition amounts in excess of 0.5 g S m-2 yr-1 are estimated for large regions in Asia, with values as high as 10 g S m-2 yr-1 in southeastern China. Annual averaged SO2 concentrations in excess of 20 g SO2 m-3 are calculated for many urban and suburban areas ofeastern China and S. Korea, with an average of 5 g SO2 m-3 over most of the emitter regions. Sulfur deposition by major source categories is also studied. Southeast Asia (Indonesia, Malaysia, Philippines, Singapore)receives 25% of its sulfur deposition from shipping activities. Sulfur deposition from bio-fuel burning is significant for most of the underdeveloped regions in Asia. Volcanoes are a major source of sulfur emissions in the PacificOcean, Papua New Guinea, Philippines and Southern Japan. Sulfur deposition is shown to vary significantly throughout the year.The monsoons are found to be the largest factor controlling sulfur transport and deposition in the Indian sub-continent andSoutheast Asia. India receives over 35% of its total depositionduring the summer months. In East Asia, sulfur deposition isestimated to be 10% higher during summer and fall than winterand spring. Model results are compared with observations from a number of monitoring networks in Asia and are found to be generally consistent with the limited observations.
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This study analyze the potential factors influencing the growth of transport sector carbon dioxide (CO2) emissions in selected Asian countries during the 1980–2005 period by decomposing annual emissions growth into components representing changes in fuel mix, modal shift, per capita gross domestic product (GDP) and population, as well as changes in emission coefficients and transportation energy intensity. We find that changes in per capita GDP, population growth and transportation energy intensity are the main factors driving transport sector CO2 emission growth in the countries considered. While growth in per capita income and population are responsible for the increasing trend of transport sector CO2 emissions in China, India, Indonesia, Republic of Korea, Malaysia, Pakistan, Sri Lanka and Thailand; the decline of transportation energy intensity is driving CO2 emissions down in Mongolia. Per capita GDP, population and transportation energy intensity effects are all found responsible for transport sector CO2 emissions growth in Bangladesh, the Philippines and Vietnam. The study also reviews existing government policies to limit CO2 emissions growth, such as fiscal instruments, fuel economy standards and policies to encourage switching to less emission intensive fuels and transportation modes.
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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 (NOX), 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 NOX 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.
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To investigate the potential public health impact of ambient air pollution under various energy scenarios in Shanghai, we estimated the air pollution exposure level of the general population under various planned energy scenarios, and assessed the potential public health impact using the concentration–response functions derived from available epidemiologic studies. The results show that ambient air pollution in relation to various energy scenarios could have significant impact on the health status of Shanghai residents. Compared with base case scenario, implementation of various energy scenarios could prevent 608–5144 and 1189–10,462 PM10-related avoidable deaths (mid-value) in 2010 and 2020, respectively; and it could also decrease substantial cases of relevant diseases. These findings illustrate that an effective energy and environmental policy will play an active role in reduction of air pollutant emissions, improvement of air quality, and public health.
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A comprehensive, spatially resolved (0.25°×0.25°) fossil fuel consumption database and emissions inventory was constructed, for India, for the first time. Emissions of sulphur dioxide and aerosol chemical constituents were estimated for 1996–1997 and extrapolated to the Indian Ocean Experiment (INDOEX) study period (1998–1999). District level consumption of coal/lignite, petroleum and natural gas in power plants, industrial, transportation and domestic sectors was 9411 PJ, with major contributions from coal (54%) followed by diesel (18%). Emission factors for various pollutants were derived using India specific fuel characteristics and information on combustion/air pollution control technologies for the power and industrial sectors. Domestic and transportation emission factors, appropriate for Indian source characteristics, were compiled from literature. SO2 emissions from fossil fuel combustion for 1996–1997 were 4.0 Tg SO2 yr−1, with 756 large point sources (e.g. utilities, iron and steel, fertilisers, cement, refineries and petrochemicals and non-ferrous metals), accounting for 62%. PM2.5 emitted was 0.5 and 2.0 Tg yr−1 for the 100% and the 50% control scenario, respectively, applied to coal burning in the power and industrial sectors. Coal combustion was the major source of PM2.5 (92%) primarily consisting of fly ash, accounting for 98% of the “inorganic fraction” emissions (difference between PM2.5 and black carbon+organic matter) of 1.6 Tg yr−1. Black carbon emissions were estimated at 0.1 Tg yr−1, with 58% from diesel transport, and organic matter emissions at 0.3 Tg yr−1, with 48% from brick-kilns. Fossil fuel consumption and emissions peaked at the large point industrial sources and 22 cities, with elevated area fluxes in northern and western India. The spatial resolution of this inventory makes it suitable for regional-scale aerosol-climate studies. These results are compared to previous studies and differences discussed. Measurements of emission factors for Indian sources are needed to further refine these estimates.
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Asia is undergoing rapid urbanization resulting in increasing air pollution threats in its cities. The contribution of megacities to sulfur emissions and pollution in Asia is studied over a 25-year period (1975–2000) using a multi-layer Lagrangian puff transport model. Asian megacities cover <2% of the land area but emit ∼16% of the total anthropogenic sulfur emissions of Asia. It is shown that urban sulfur emissions contribute over 30% to the regional pollution levels in large parts of Asia. The average contribution of megacities over the western Pacific increased from <5% in 1975 to >10% in 2000. Two future emission scenarios are evaluated for 2020—“business as usual (BAU)” and “maximum feasible controls (MAXF)” to establish the range of reductions possible for these cities. The MAXF scenario would result in 2020 S-emissions that are ∼80% lower than those in 2000, at an estimated control cost of US $87 billion per year (1995 US$) for all of Asia. An urban scale analysis of sulfur pollution for four megacities—Shanghai, and Chongqing in China; Seoul in South Korea; and Mumbai (formerly Bombay) in India is presented. If pollution levels were allowed to increase under BAU, over 30 million people in these cities alone would be exposed to levels in excess of the WHO guidelines.
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A simple model of chemistry and transport, ATMOS-N, has been developed to calculate source–receptor relationships for reactive nitrogen species within Asia. The model is intended to support discussion of energy and environmental issues in Asia, to compare sulfate and nitrate contributions to regional acidification, and to estimate how each nation's acid deposition and air quality relates to domestic versus foreign emissions. ATMOS-N is a Lagrangian “puff” model in which non-interacting puffs of emissions are advected horizontally and mixed between three vertical layers. Results are compared with wet nitrate deposition observations in Asia.On an annual average, the model estimates that long-range transport contributes a significant percentage of total nitrate deposition throughout east Asia. China, the largest emitter of the region, contributes 18% to nitrate deposition in Taiwan, 18% in Japan, 46% in North Korea, and 26% in South Korea. South Korea contributes 12% to nitrate deposition in Japan, due to its close upwind proximity. Compared with total acid deposition (nitrate+sulfate), nitrate contributes 30–50% over northern Japan, 30–60% in India, and 50–90% in southeast Asia where biomass burning emits high levels of NOx. The percentage contribution of nitrate is very low in China, where emissions and deposition of sulfur are extraordinarily high.
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A comprehensive emission inventory for megacity Delhi, India, for the period 1990–2000 has been developed in support of air quality, atmospheric chemistry and climate studies. It appears that SO2 and total suspended particles (TSP) are largely emitted by thermal power plants (∼68% and ∼80%, respectively), while the transport sector contributes most to NOx, CO and non-methane volatile organic compound (NMVOC) emissions (>80%). Further, while CO2 has been largely emitted by power plants in the past (about 60% in 1990, and 48% in 2000), the contribution by the transport sector is increasing (27% in 1990 and 39% in 2000). NH3 and N2O are largely emitted from agriculture (∼70% and ∼50%, respectively), and solid waste disposal is the main source of CH4 (∼80%). In the past TSP abatement to improve air quality has largely focused on traffic emissions; however, our results suggest that it would be most efficient to also reduce TSP emissions by power plants. We also assessed the potential large-scale transport of the Delhi emissions based on 10-day forward trajectory calculations. The relatively strong growth of NOx emissions indicates that photochemical O3 formation in the regional environment may be increasing substantially, in particular in the dry season. During the summer, on the other hand, convective mixing of air pollutants may reduce regional but increase large-scale, i.e. hemispheric effects.
Article
International shipping is a major source of sulfur emissions in Asia. Because the fuel oil used by ships is high in sulfur, the resulting emissions of SO2 are large and contribute as much as 20% to the atmospheric loading in the vicinity of ports and heavily traveled waterways. Because of the rapid growth of Asian economies in the 1980s and early 1990s, it is estimated that shipping trade grew by an average of 5.4% per year between 1988 and 1995; in particular, crude oil shipments to Asian countries other than Japan grew by an average of 11.4% per year. The emissions of SO2 from shipping are estimated to have grown by 5.9% per year between 1988 and 1995, rising from 545 Gg in 1988 to 817 Gg in 1995. This study uses the ATMOS atmospheric transport and deposition model to study the effects of these emissions, both in absolute terms and relative to land-based emissions, on wet and dry deposition of sulfur. Southeast Asia is most heavily affected by emissions from ships, particularly Sumatra, peninsular Malaysia, and Singapore, which routinely receive in excess of 10% of their deposition from ships. A strong seasonal component is also observed, with large areas of Southeast Asia and coastal Japan receiving sulfur deposition that exceeds 10 mg S m−2 season−1. Deposition is at least 25% higher in summer and fall than in winter and spring. Peak values of 25–50 mg S m−2 season−1 are calculated for winter in the Strait of Malacca. This work suggests a need to introduce policies to reduce the sulfur content of marine fuels or otherwise reduce emissions of SO2 from ships in Asian waters.
Article
Since 1950 the world population has more than doubled, and the global number of cars has increased by a factor of 10. In the same period the fraction of people living in urban areas has increased by a factor of 4. In year 2000 this will amount to nearly half of the world population. About 20 urban regions will each have populations above 10 million people.Seen over longer periods, pollution in major cities tends to increase during the built up phase, they pass through a maximum and are then again reduced, as abatement strategies are developed. In the industrialised western world urban air pollution is in some respects in the last stage with effectively reduced levels of sulphur dioxide and soot. In recent decades however, the increasing traffic has switched the attention to nitrogen oxides, organic compounds and small particles. In some cities photochemical air pollution is an important urban problem, but in the northern part of Europe it is a large-scale phenomenon, with ozone levels in urban streets being normally lower than in rural areas. Cities in Eastern Europe have been (and in many cases still are) heavily polluted. After the recent political upheaval, followed by a temporary recession and a subsequent introduction of new technologies, the situation appears to improve. However, the rising number of private cars is an emerging problem. In most developing countries the rapid urbanisation has so far resulted in uncontrolled growth and deteriorating environment. Air pollution levels are here still rising on many fronts.Apart from being sources of local air pollution, urban activities are significant contributors to transboundary pollution and to the rising global concentrations of greenhouse gasses. Attempts to solve urban problems by introducing cleaner, more energy-efficient technologies will generally have a beneficial impact on these large-scale problems. Attempts based on city planning with a spreading of the activities, on the other hand, may generate more traffic and may thus have the opposite effect.
Article
Combustion emissions are a major contributor to degradation of air quality and pose a risk to human health. We evaluate and apply a multiscale air quality modeling system to assess the impact of combustion emissions on UK air quality. Epidemiological evidence is used to quantitatively relate PM(2.5) exposure to risk of early death. We find that UK combustion emissions cause ∼13,000 premature deaths in the UK per year, while an additional ∼6000 deaths in the UK are caused by non-UK European Union (EU) combustion emissions. The leading domestic contributor is transport, which causes ∼7500 early deaths per year, while power generation and industrial emissions result in ∼2500 and ∼830 early deaths per year, respectively. We estimate the uncertainty in premature mortality calculations at -80% to +50%, where results have been corrected by a low modeling bias of 28%. The total monetized life loss in the UK is estimated at £6-62bn/year or 0.4-3.5% of gross domestic product. In Greater London, where PM concentrations are highest and are currently in exceedance of EU standards, we estimate that non-UK EU emissions account for 30% of the ∼3200 air quality-related deaths per year. In the context of the European Commission having launched infringement proceedings against the UK Government over exceedances of EU PM air quality standards in London, these results indicate that further policy measures should be coordinated at an EU-level because of the strength of the transboundary component of PM pollution.