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Nature of air pollution, emission sources, and management in the Indian cities
Abstract
The global burden of disease study estimated 695,000 premature deaths in 2010 due to continued exposure to outdoor particulate matter and ozone pollution for India. By 2030, the expected growth in many of the sectors (industries, residential, transportation, power generation, and construction) will result in an increase in pollution related health impacts for most cities. The available information on urban air pollution, their sources, and the potential of various interventions to control pollution, should help us propose a cleaner path to 2030. In this paper, we present an overview of the emission sources and control options for better air quality in Indian cities, with a particular focus on interventions like urban public transportation facilities; travel demand management; emission regulations for power plants; clean technology for brick kilns; management of road dust; and waste management to control open waste burning. Also included is a broader discussion on key institutional measures, like public awareness and scientific studies, necessary for building an effective air quality management plan in Indian cities.
... A partial lockdown in Rio de Janeiro also resulted in signi cant reductions in NO x and other pollutant concentrations (Dantas et al. 2020). At home, Delhi always experiencing severe air pollution episodes, also witnessed signi cant reductions in Particulate matter (PM 10 : and PM 2.5 ; 57% and 33% respectively) followed by a reduction in NO x (Mahato et al. 2020). Sharma et al., 2020, also indicated a reduction in the Air Quality Index by 32% during the lockdown in cities located in the west zone of India. ...
... The primary data generated from NAMP in the last decade (2010-2019) was used to assess the average air quality over the selected locations. Daily and monthly means of SO 2 , NO x , PM 10 The statuses of the air quality pertaining to exceedances frequency of the pollutants were categorized with respect to the NAAQ standards as given in Table 2. In order to standardize the data, the frequency of exceedances was converted into percentages. ...
... In order to understand the spatio-temporal variability in PM 10 Pre-lockdown: ...
With the advent of industrialization in the world's major metropolitan areas, air pollution has steadily increased. Several strict laws are imposed by the authorities to minimize the impact of pollution in urban dwellings. The lockdown restrictions during COVID-19 pandemic resulted in major air quality improvements worldwide. However, episodic improvements in air quality understates explicit picture of air quality. This merits the cause for spatio-temporal analysis of air quality over two most affected metropolitan regions in west India: Pune and Mumbai, in the past decade. We investigated the air quality by collecting hourly primary data of PM 10 , SPM, SO 2 , and NO x at three locations in Pune while daily data of PM 10 , SO 2 , and NO x was obtained at eleven locations in Mumbai. As the data were copiously available (2010–2020), decadal, inter-intra seasonal analysis was carried out at multi-timescales. This contributed in intensively exploring the variations in 2020 resulting in critical evaluation during the pandemic year. Against the overall deterioration in air quality in the past decade, finer refinement in air quality was witnessed over Pune during the lockdown. At Mumbai, an overall reduction of 59% was observed at all the locations. In both the cities, the pollution behaviour varied on a spatio-temporal scale within the cities. The study, therefore, infers the distinctiveness of pollutant behaviour on a spatial scale within the city rather than overall average for the city. It also recommends strengthening the air monitoring network in urban dwellings to track varied sources and formulate precise urban planning.
... 6,8 Previous studies have estimated a rise in mortality attributable to long-term exposure to ambient PM 2.5 in India associated with a growing population exposed to high PM 2.5 concentrations. 7,9,10 Understanding the sources of PM 2.5 concentrations and their impact on mortality in India and the surrounding region would offer useful information for air quality management strategies. ...
... 15,25 Direct emissions from residential combustion, industry, power generation, agricultural waste burning, and windblown dust are major sources of PM 2.5 in India. 1,5,10 Recent progress has been made in applying chemical transport models to simulate secondary formation of PM 2.5 from reactions between primary gas-phase precursors and to represent the relation of sources with ambient PM 2.5 concentrations. 6,16,26,27 We use the recently developed . ...
Fine particulate matter (PM2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78–1.26) million deaths in South Asia attributable to ambient PM2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%–39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM2.5 (>95 μg/m3). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54–0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.
... "How bad is Delhi's air quality?" and "What are the main sources of Delhi's air pollution problem?" are perennial questions in India, despite Delhi being the most studied city [1][2][3][4][5][6][7][8]. Delhi's air pollution peaks during the winter months starting with Diwali and post-harvest agricultural waste burning and deteriorates further with lower surface temperatures resulting in an increase in demand for space heating [9][10][11]. ...
... These stations measure and reported a mix of pollutants ranging from aerosols such as particulate matter (PM2.5 and PM10 size fractions), to gases such as sulphur dioxide (SO2), nitrogen oxides (NO and NO2), carbon monoxide (CO), ammonia (NH3), and ozone [24,25]. For convenience, the discussion in this paper is limited to PM2.5, which is the most important pollutant often exceeding Indian standards [3,26,27] and also contributes to a large share of estimated health impacts related to the respiratory, heart, and neurological systems [28][29][30][31][32][33][34]. ...
Delhi’s annual average PM2.5 concentration in 2021–22 was 100 μg/m3—20 times more than the WHO guideline of 5 μg/m3. This is an improvement compared to the limited information available for the pre-CNG-conversion era (~30%), immediately before and after 2010 CWG (~28%), and the mid-2010s (~20%). These changes are a result of continuous technical and economic interventions interlaced with judicial engagement in various sectors. Still, Delhi is ranked the most polluted capital city in the world. Delhi’s air quality is a major social and political concern in India, often with questions regarding its severity and primary sources, and despite several studies on the topic, there is limited consensus on source contributions. This paper offers insight by reviewing the influence of Delhi’s urban growth since 1990 on pollution levels and sources and the evolution of technical, institutional, and legal measures to control emissions in the National Capital Region of Delhi.
... Air pollution significantly increased cases of the following diseases: lung and tracheal cancers, lower respiratory infections, bronchitis, ischemic heart disease, and chronic obstructive pulmonary disease. 1 As per World Health Organization, 2 in 2012 air pollution was responsible for one out of every nine fatalities. According to, 3 based on pollutant emissions, with 21 of the top 30 most polluted cities being found, India was placed as the fifth-most polluted nation. ...
The distressing levels of air pollution in India is becoming health hazard to the inhabitants. It's important to note that due to the nation's continued urbanisation and its heavy reliance on coal for electricity generation, air pollution is expected to get worse in some areas of India over the next few decades. Present study aims to address the issue by identifying the sources causing air pollution using Hierarchical Agglomerative Cluster Analysis [HACA]. Two years daily data (2018 and 2019), downloaded from publicly available source Kaggle.com of sixteen selected air pollution monitoring stations was used for the study. The stations were selected based upon diversified environmental conditions and local sources. HACA was successful in grouping the monitoring stations into four clusters based on their average Air Quality Index (AQI) level. These four clusters are named as Low Pollution, Moderate Pollution, High Pollution and Very High Pollution Region [LPR, MPR, HPR and VHPR] with average AQI 96; 135; 173 and 227 respectively. Discriminant Analysis (DA) confirmed the resulting clusters with 100% accuracy. It was found that stations with similar environmental factors, regional sources, and pollution amounts were clustered together. Despite numerous actions taken by the authorities to reduce air pollution, it was noticed that topographical conditions play an essential role in the rise of pollution. This study helps to implement different strategies by the authorities’ concern based on local sources and topographical conditions.
... The air impact assessment study is considered one of the utmost essential factors of transportation projects. Collected field data, modern software tools, and digital measurements by sensors are used in analyzing the current range of air quality in several states and conclude the origin of pollution and method of contamination are intertwined (Guttikunda et al. 2014). Comparing all other segments, emission from the transport sector is the supreme perilous and farthest connected in the systematic, judicial, economic, and institutional framework of the 112 openly available clean air action plans submitted under NCAP and executed a wide-ranging Programme for the prevention, control, and reduction of pollution (Ganguly et al. 2020). ...
The level of air pollution increased in urban areas due to local atmospheric conditions and dispersion of various air pollutants. In this study, the air quality index was carried out in four places in the urban zone and investigated the seasonal variation of PM2.5, PM10, SO2, NO2, and O3 over one year (2021) by considering the meteorological parameters in Coimbatore. Furthermore, fluidyn-PANACHE, a CFD tool, has been used to simulate the dispersion pattern of gaseous pollutants in the selected locations. To track the model, the concentration details of gaseous pollutants were collected and pollutant dispersion under numerous atmospheric conditions (Humidity, Temperature, Pressure). was identified using fluidyn-PANACHE software. From the collected air samples and dispersion pattern, SO2 and O3 show higher concentrations in summer. Particulate matter and NO2 show higher concentrations in winter due to seasonal variations in energy use and atmospheric constancy. Pearson correlation coefficients indicate most pollutants are correlated in Coimbatore except Ozone. Compared to the AQI category given by CPCB, the selected four locations are in the moderate category. However, increased PM10 levels were observed at all the selected zones in winter due to the process of inversion and environmental conditions.
... Air pollutant concentrations are usually monitored in locations that could represent population exposures to determine Air Quality Standards (Chow 1995). The severity of pollution may be high in places with particular sources of anthropogenic polluted air, such as highways, industrial factories, and major immovable emission sources (Guttikunda et al. 2014). As an outcome, defending the communities living in such circumstances may necessitate particular efforts to reduce pollution levels below guideline limits (Krzyzanowski and Cohen 2008). ...
COVID-19 had such a devastating effect on humanity that several governments worldwide were forced to establish regional and national level Lockdowns in an attempt to reduce the severity of the infection. The nationwide lockdown had been implemented on 24 March 2020 in India with the inevitable restrictions. Along with the effect on the population of more than 1.3 billion people, unprecedented variations in air pollution levels across the country have been witnessed. This Geographic Information System (GIS) approach aims to provide a detailed analysis of spatiotemporal variations in pollution levels prior to, during, and after the Lockdown at multiple locations in Delhi using pollution data from ground monitoring stations under the supervision of the Central Pollution Control Board (CPCB). The monthly contributions of toxic pollutants were determined using several statistical methods, among which the exponential averaging method demonstrated the most favorable outcomes. The interpolation techniques were used to estimate the spatial pollution extent. The study reveals that the residential areas and the commercial complexes had a significant reduction in the pollutant levels in the presence of the lockdown and again a sudden increase in pollution after the relaxation of the curbs. Furthermore, a site suitability analysis was utilized to tackle the growing pollutants level by choosing specific points wherein air quality purifiers can be installed.
... Nesamani (2010) estimated emissions during start and running from on-road vehicles in Chennai using International Vehicle Emission (IVE) model, and examined mitigation options and suggested advanced vehicular technology and augmentation of public transit to reduce such emissions. Guttikunda et al., (2014)suggested effective air quality management plan for improving air quality in Indian cities by analysing the emission sources and control options. Mohandas et al., (2009) proposed an internet based congestion control algorithm viz. ...
Road traffic congestion is a major problem worldwide. In old cities of developing nations like India, narrow roads, mixed traffic and mixed land use coupled with rapid urbanization, increased travel demand and use of personal vehicles have increased congestion problems. Congestion reduction may be done by supply or demand management. Supply management involves improving road infrastructures and public transport facilities, which is a major focus of Indian government. However, there are limits of improving infrastructure to match the fast growing pace of travel demand. Demand management through congestion pricing may be used not only to reduce congestion, delays, emissions and accidents but also provide funding for infrastructure maintenance. In this method, usage of road infrastructure is charged to shift demand to less congested areas or to off-peak hours or to high occupancy public transit systems. Cities like Singapore, London, San Diego, Stockholm and Milan have successfully adopted congestion pricing in various formats, like cordon pricing, usage-based and trip-based tolls or implementing High Occupancy Toll (HOT) lanes. However, worldwide, public acceptability of congestion pricing is low, which makes widespread implementation difficult. In India, demand management to reduce congestion is tried in some cities like alternate day permission for odd-even numbered vehicles or preferred bus lanes. Road pricing in form of tolls mostly focus to recover cost of infrastructure rather than to reduce congestion. Very few studies have been done to understand proper method to reduce congestion in Indian context. This paper attempts to provide a thorough review of related literature to understand the appropriateness and effectiveness of various methods adopted worldwide to reduce congestion. Also, possible congestion management strategies are suggested, which may be appropriate in Indian context.
... This study examined a wide range of air pollutants mentioned above and discovered that PM 2.5 was rising globally based on studies of 6743 cities in 117 different nations, causing 1.7 million yearly mortalities in India alone. The top 20 cities with the highest air pollution were 18 Indian cities, illustrating the seriousness of India's air pollution and adverse health effects in the years to come (Gurjar et al., 2016;Guttikunda et al., 2014). ...
Clean air is critical component for health and survival of human and wildlife, as atmospheric pollution is associated with a number of significant diseases including cancer. However, due to rapid industrialization and population growth, activities such as transportation, household, agricultural, and industrial processes contribute to air pollution. As a result, air pollution has become a significant problem in many cities, especially in emerging countries like India. To maintain ambient air quality, regular monitoring and forecasting of air pollution is necessary. For that purpose, machine learning has emerged as a promising technique for predicting the Air Quality Index (AQI) compared to conventional methods. Here we apply the AQI to the city of Visakhapatnam, Andhra Pradesh, India, focusing on 12 contaminants and 10 meteorological parameters from July 2017 to September 2022. For this purpose, we employed several machine learning models, including LightGBM, Random Forest, Catboost, Adaboost, and XGBoost. The results show that the Catboost model outperformed other models with an R2 correlation coefficient of 0.9998, a mean absolute error (MAE) of 0.60, a mean square error (MSE) of 0.58, and a root mean square error (RMSE) of 0.76. The Adaboost model had the least effective prediction with an R2 correlation coefficient of 0.9753. In summary, machine learning is a promising technique for predicting AQI with Catboost being the best-performing model for AQI prediction. Moreover, by leveraging historical data and machine learning algorithms enables accurate predictions of future urban air quality levels on a global scale.
... Das, , 2016S. Das et al., 2016;Goel et al., 2015; R. Gupta et al., 2019; Kaushik et al., 2012; Monga et al., 2012; L. Singh et al., 2020, Pakistan: Rahman et al., 2013; Raza et al., 2014; Raza & Ali, 2021, 2022; Shaikh et al., 2012. and Nepal: Sanjel et al., 2016, 2017. ...
Coal-fired brick kilns have spread rapidly in Bangladesh, where they are one of the largest sources of air pollution. The adverse health impacts of air pollution have been widely documented, yet there is little empirical evidence on the externalities of this important industry. We conducted a field study in Bangladesh to quantify the contribution of brick kilns to fine particulate matter (PM 2.5) and estimate the association with child asthma symptoms, chronic obstructive pulmonary disease (COPD), and general respiratory symptoms. We exploit variation in the timing of brick production, seasonal wind direction, and household proximity to kilns to isolate the effects of brick manufacturing from other sources of air pollution. We find that PM 2.5 is 72.3 lg/m3 (95% CI: 10.2, 134.3) higher in areas 2 km downwind from a brick kiln during the brick production season. We also find 2.2 (95% CI: 1.2, 4.3) greater odds of COPD symptoms among adults over 40 and 4.2 (95% CI: 2.7, 6.8) greater odds of respiratory symptoms among adults over 18. Among children under 5, we found greater odds of respiratory symptoms (2.1, 95% CI: 0.7, 6.0) and asthma symptoms (2.5, 95% CI: 0.1, 96.1), but the results were underpowered for the smaller sample of children. Our findings suggest that existing regulations, which require that kilns be at least 1-2 km from residential areas, schools, and health facilities, are inadequate to protect nearby communities from the substantial health burden brick manufacturing imposes.
... Emission from vehicles is the main cause of polluting the environment as it contains various pollutants such as PM 10 , PM 2.5 , oxides of nitrogen (NO x ), oxides of sulphur (SO x ), carbon dioxide (CO 2 ), carbon monoxide (CO), and hydrocarbons (HCs). The vehicle demand increases with the increasing population (Bathmanabhan and Madanayak, 2010;Guttikunda et al., 2014) and as the vehicle demand goes on increasing, emission in the environment is also increasing (Ghosh, 2015). If there are no regulations, the particulate matter and other pollutants could affect the air quality of cities (Biswas et al., 2008). ...
The objective of this study is to assess the long-term variation in concentrations of Respirable suspended particulate matter (PM10), sulphur dioxide (SO2) and nitrogen dioxide (NO2) in the ambient air of Nagpur (India) during 2011-2018. The pollution data during the above period at three locations, viz., residential (Station-I), industrial (Station-II), and commercial location (Station-III) has been analyzed. The highest daily average concentration of PM10 at residential, industrial, and commercial locations was found 154 μg/m3, 199 μg/m3, and 153 μg/m3, whereas, the average annual concentration at these locations was found 101.87 μg/m3, 115.37 μg/m3 and 98.75 μg/m3, respectively during the above period. The highest daily average concentration of SO2 was found at 18 μg/m3, 22 μg/m3 and 19 μg/m3 and the average annual concentration was 13.25 μg/m3, 13.5 μg/m3, 13 μg/m3 at respective locations. And the highest daily average concentration of NO2 was found 77 μg/m3, 60 μg/m3, 60 μg/m3 and the annual average concentration was 44.125 μg/m3, 41.825 μg/m3 and 40.25 μg/m3 at the respective locations. The exceedance factors for PM10 varied from 'moderate to high' at the residential and commercial locations and from 'high to moderate' at the industrial location. Planetary boundary layer height (PBLH) and ventilation coefficient (VC) were also estimated over the region for 2011-2018. The maximum PBLH and VC observed during the study period was in the summer season, and the minimum was in the post-monsoon season. Annual and Seasonal Air quality index analysis shows that the level of pollution was in the range of SATIFACTORY to MODERATE. A study of seasonal analysis of PM10, SO2 and NO2 showed that the higher concentrations were found in winter relative to summer with the least concentration occurring during the monsoon season. A regression analysis was performed to check PM10's interdependence with other contaminants. A positive association was found between PM10 and SO2 for all seasons. A negative association was found between PM10 and NO2 in summer for all the stations and winter at Station-I and Station-III. Similarly, the correlation between PM10 and meteorological parameters such as wind speed and temperature was found to be negative whereas it was positive for relative humidity.
... Emission from vehicles is the main cause of polluting the environment as it contains various pollutants such as PM 10 , PM 2.5 , oxides of nitrogen (NO x ), oxides of sulphur (SO x ), carbon dioxide (CO 2 ), carbon monoxide (CO), and hydrocarbons (HCs). The vehicle demand increases with the increasing population (Bathmanabhan and Madanayak, 2010;Guttikunda et al., 2014) and as the vehicle demand goes on increasing, emission in the environment is also increasing (Ghosh, 2015). If there are no regulations, the particulate matter and other pollutants could affect the air quality of cities (Biswas et al., 2008). ...
The objective of this study is to assess the long-term variation in concentrations of Respirable suspended particulate matter (PM10), sulphur dioxide (SO2) and nitrogen dioxide (NO2) in the ambient air of Nagpur (India) during 2011-2018. The pollution data during the above period at three locations, viz., residential (Station-I), industrial (Station-II), and commercial location (Station-III) has been analyzed. The highest daily average concentration of PM10 at residential, industrial, and commercial locations was found 154 microgm/m3, 199 microgm/m3, and 153 microgm/m3, whereas, the average annual concentration at these locations was found 101.87 microgm/m3, 115.37 microgm/m3 and 98.75 microgm/m3, respectively during the above period. The highest daily average concentration of SO2 was found at 18 microgm/m3, 22 microgm/m3 and 19 microgm/m3 and the average annual concentration was 13.25 microgm/m3, 13.5 microgm/m3, 13 microgm/m3 at respective locations. And the highest daily average concentration of NO2 was found 77 microgm/m3, 60 microgm/m3, 60 microgm/m3 and the annual average concentration was 44.125 microgm/m3, 41.825 microgm/m3 and 40.25 microgm/m3 at the respective locations. The exceedance factors for PM10 varied from 'moderate to high' at the residential and commercial locations and from 'high to moderate' at the industrial location. Planetary boundary layer height (PBLH) and ventilation coefficient (VC) were also estimated over the region for 2011-2018. The maximum PBLH and VC observed during the study period was in the summer season, and the minimum was in the post-monsoon season. Annual and Seasonal Air quality index analysis shows that the level of pollution was in the range of SATIFACTORY to MODERATE. A study of seasonal analysis of PM10, SO2 and NO2 showed that the higher concentrations were found in winter relative to summer with the least concentration occurring during the monsoon season. A regression analysis was performed to check PM10's interdependence with other contaminants. A positive association was found between PM10 and SO2 for all seasons. A negative association was found between PM10 and NO2 in summer for all the stations and winter at Station-I and Station-III. Similarly, the correlation between PM10 and meteorological parameters such as wind speed and temperature was found to be negative whereas it was positive for relative humidity.
... Promoting reliable, comfortable, and accessible public transportation decreases the demand for automobiles, increases air quality, and eliminates traffic-induced air pollution (Sun et al., 2019). Industrial areas, highways, and waste-disposal areas are sources of both air pollution and emissions (Guttikunda et al., 2014) that should be located away from vulnerable groups' residential areas. Urban ventilation and integration of natural areas into urban settlements are other factors that affect not only air quality by hindering the accumulation of pollutants (Kurppa et al., 2018) but also by providing a natural cooling effect to eliminate the UHI effect (Gago et al., 2013). ...
This study focuses on older adults, who are disproportionately vulnerable to climate change due to their health,
physical, and socioeconomic conditions. On the one
hand, climate change has grown into the most challenging issue on the international agenda for the twenty-first
century due to its adverse impacts. On the other hand,
the global population has been ageing rapidly, especially
in urban areas. The link between these two major concerns is unclear in theory and practice; hence, easy-touse universal guidelines offering possible solutions for
governments, institutions, and communities for irremediable impacts are an urgent necessity. Based on this imperative, this article presents climate change–responsive
age-friendly city domains through a critical literature review. Seven domains are prioritized at various scales to
represent the core planning areas of age-friendliness and
climate-change resilience in urban areas: environmental
safety, information and participation, health and social
services on the city scale, surroundings and transportation
on the neighbourhood scale, outdoor spaces and thermal
comfort, and housing on the housing cluster scale. The
interaction between these two concerns in the framework
provided by this study contributes to raising awareness,
building actions, and directing policies from a global
perspective.
... In India, urbanization and industrialization are booming day by day. Few studies have reported pollutants in air particles and road dust (Guttikunda et al., 2014;Mathur et al., 2016;Sahu et al., 2016;Samiksha et al., 2017). However, information on contaminants of emerging concern such as PFAS associated with road dust in India is still lacking. ...
In India, information on the occurrence and distribution of legacy and emerging per- and polyfluoroalkyl substances (PFAS) is deficient. In the present study, nationwide 79 road dust samples were collected from 12 states and 1 union territory for the analysis of 34 PFAS. Overall, total concentrations of 21 quantified PFAS (∑21PFAS) ranged 23-861 pg/g (median: 116 pg/g), with perfluorooctane sulfonic acid (PFOS) being predominant (median: 19.9 pg/g). Short to long chain perfluoroalkyl carboxylic acids (PFCAs; C4 - C18) were detected, where the concentrations of PFAS decreased with the increase in PFAS carbon chain length. ∑21PFAS was highest in road dust from urban area (n = 27; median: 230 pg/g), followed by suburban (n = 21; median: 126 pg/g) and rural areas (n = 31; median: 76 pg/g), suggesting environmental impacts of industriallization and urbanization on PFAS distribution. PFAS composition in rural road dust was significantly different from those in suburban and urban samples (p < 0.01). Regarding 4 geographical regions of India, PFAS in road dust showed spatial difference where higher concentrations were found in South India compared to other regions. ∑21PFAS were positively associated with city-wise population of India (rs = 0.40, p < 0.01). Strong to moderate positive correlation was observed between ∑21PFAS, fluorotelomer sulfonic acids, and PFCAs (rs = 0.23, 0.30, and 0.28, respectively; p < 0.05) and the total state-wise vehicles in India, suggesting that vehicles exhaust or non-exhaust (e.g., vehicle tire debris and polishing material) might contribute to the PFAS occurrence in Indian road dust. Toddlers (2-5 years) had the highest estimated daily intake of ∑PFAS via road dust ingestion under average-case and worst-case scenarios (0.55 and 1.16 pg/kg bw/day, respectively). This is the first time to evaluate PFAS in Indian road dust nationwide, aiding to provide first-hand data for human exposure to PFAS in India.
... In this research work, Delhi, the capital city of India has been selected as a study area. The city is facing a major problem of air pollution due to rapid increase in the number of motor vehicles (diesel and petrol based), construction activities, road dust and many other commercial activities (Kumar, Chu, and Foster 2007;Pant et al. 2015;Guttikunda, Goel, and Pant 2014). Various studies conducted on air pollution in Delhi have found that Particulate matter (PM) is the most significant air pollutant in ambient air of Delhi (Sharma et al. 2016;Nagar et al. 2017). ...
Delhi, the capital city of India has experienced the problem of the great smog during November since a long time. Adverse meteorological conditions, stubble burning, and the celebration of Diwali were considered as the major responsible factors for the smog episodes. This study was designed to identify the concentration and relative risks associated with the exposure of PM2.5 in ambient air of Delhi during the episodic events.
... Also, in India, PM2.5 levels increase dramatically during the cold-dry months of October -January due to atmospheric conditions and fireworks burnt during the Diwali festival [7]. A study by the global burden of disease estimated 695,000 premature deaths in 2010 due to continued exposure to fine particulate matter in India alone, a number which is expected to grow higher in subsequent years [42]. ...
Despite the proven benefits of natural ventilation (NV) as an effective low-carbon solution to meet growing cooling demand, its effectiveness can be constrained by poor outdoor air quality. Here, we propose a modeling approach that integrates highly granular air pollution data with a coupled EnergyPlus and differential equation airflow model to evaluate how NV potential for space cooling changes when accounting for air pollution exposure (PM2.5). Given the high vulnerability of low-income populations to air pollution and the dearth of energy and thermal comfort research on informal settlements, we applied our model to a typical informal settlement residence in two large Indian cities: New Delhi and Bangalore. Our results indicate that outdoor PM2.5 levels have a significant impact on NV potential especially in highly polluted cities like New Delhi. However, we found that low-cost filtration (MERV 14) increased the NV potential by 25% and protected occupants from harmful exposure to PM2.5 with a minor energy penalty of 6%. We further find that adoption of low-cost filtration is a viable low-carbon solution pathway as it provides both thermal comfort and exposure protection at 65% less energy intensity — energy intensity reduced to 60 kWh/m2 from 173.5 kWh/m2 in case of adoption of potentially unaffordable full mechanical air conditioning. Our work highlights ample opportunities for reducing both air pollution and energy consumption in informal settlements across major Indian cities. Finally, our work can guide building designers and policymakers to reform building codes for adopting low-cost air filtration coupled with NV and subsequently reduce energy demand and associated environmental emissions.
... Prior to lockdown, India had suffered immensely from severe air pollution resulting from recent economic growth, traffic emissions, and land-use changes for decades (World Bank and International report 2020; Fadnavis et al. 2013;Guttikunda et al. 2014;Hama et al. 2020). Such acute pollution resulted in an increase of 2.6 hazy days per year and a death rate of 8.8% (Council & Medical, 2017;IHME, 2019;Thomas, Sarangi, & Kanawade, 2019). ...
Coronavirus cases in India have been steadily increasing since March 2020. COronaVIrus Disease 2019 (COVID-19) has been managed by a variety of preventative measures. A prominent measure by the Government of India to prevent the spread of Coronavirus Disease 2019 (COVID-19) began on March 25, 2020, with a complete suspension of all outdoor activities throughout the country. Such complete lockdown has resulted in a decrease in anthropogenic emissions, which is partly due to restrictions on human activities. Delhi National Capital Region (NCR), a landlocked area, suffers from high amounts of aerosols due to both natural and anthropogenic sources. The present research focuses on changes in Aerosol Optical Depth (AOD) prior to and during lockdown (initial and second lockdown phases) around satellite cities (Faridabad, Ghaziabad, Gautam Budh Nagar and Gurugram) of Delhi using high-resolution MODIS AOD product. With the implementation of lockdown measures in phase I and phase III of the current study region, AOD decreased dramatically, while phase II and phase IV lockdown phases had a higher concentration of aerosol. An unexpected increase in AOD occurred during the second lockdown compared with the initial lockdown and before the lockdown. Overall, the average percentage change from 2019 to 2020 during first lockdown is-4.44%, while the average percentage change from 2020 to 2021 is 27.63%.
... Prior to lockdown, India had suffered immensely from severe air pollution resulting from recent economic growth, traffic emissions, and land-use changes for decades (World Bank and International report 2020; Fadnavis et al. 2013;Guttikunda et al. 2014;Hama et al. 2020). Such acute pollution resulted in an increase of 2.6 hazy days per year and a death rate of 8.8% (Council & Medical, 2017;IHME, 2019;Thomas, Sarangi, & Kanawade, 2019). ...
Coronavirus cases in India have been steadily increasing since
March 2020. COronaVIrus Disease 2019 (COVID-19) has been
managed by a variety of preventative measures. A prominent
measure by the Government of India to prevent the spread of
Coronavirus Disease 2019 (COVID-19) began on March 25, 2020,
with a complete suspension of all outdoor activities throughout
the country. Such complete lockdown has resulted in a decrease
in anthropogenic emissions, which is partly due to restrictions on
human activities. Delhi National Capital Region (NCR), a
landlocked area, suffers from high amounts of aerosols due to
both natural and anthropogenic sources. The present research
focuses on changes in Aerosol Optical Depth (AOD) prior to and
during lockdown (initial and second lockdown phases) around
satellite cities (Faridabad, Ghaziabad, Gautam Budh Nagar and
Gurugram) of Delhi using high-resolution MODIS AOD product.
With the implementation of lockdown measures in phase I and
phase III of the current study region, AOD decreased dramatically,
while phase II and phase IV lockdown phases had a higher
concentration of aerosol. An unexpected increase in AOD occurred
during the second lockdown compared with the initial lockdown
and before the lockdown. Overall, the average percentage change
from 2019 to 2020 during first lockdown is -4.44%, while the
average percentage change from 2020 to 2021 is 27.63%.
... Air pollution led to a significant increase in vehicular traffic compared to other modes of transport. The global burden of disease study estimated 695,000 premature deaths in 2010 due to continued exposure to outdoor particulate matter and ozone pollution for India (Guttikunda et al., 2014). The Indian government has announced new emission standards called Bharat Stage 6 (BS6), which are in effect from April 2020 (Vats et al., 2022). ...
Transportation driven by fossil fuels increases air pollution induced by urbanisation. Heavy metals such as Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Lead (Pb), and Zinc (Zn) are life-threatening elements and their concentration is increasing alarmingly in soil in various countries. Air pollution and associated metals contaminate the environment and affect nature's abiotic and biotic components. The significance of tree species originates from their connection to the effects of pollution and the solution approach to their biological cycle. Nineteen distinct tree species dominate the region, with heavy metals sinking in the range of Cd<0.4, Cr<1, Cu<15, Fe<2, Pb<5, and Zn<2 mg/kg or parts per million. According to the findings of this study, tree species can sink heavy metals. The different trees have distinct metals-sink ratios. The competence results showed the order of heavy metal sink as Delonix Regia-red (4) > Delonix Regia-yellow (4) > Syzygium Cumini (3) > Muntingic Calabura (3) of the trees with the highest sink rates and nine species had absorbed lead metal. The nine tree species were unsuitable for heavy metal absorption or deposition. There, Albizia Lebbeck (T02), Biancaca Decapetela (T05), Brucea Javanica (T06), Ficus Elastica (T09), Ficus Religiosa (T10), Pithecellobium Dulce (T13), Tamarind (T17), Terminalia Catappa (T18), and Thespesia Populnea (T19) were very low, less than 10% of other dominant tree species. Syzygium cumini (T16) is a high-yielding tree species that absorb significant quantities of Lead (Pb) and Copper (Cu). These studies confirm that, tree species can capture several heavy metals simultaneously from the polluted environment.
... Ground-based in situ measurements are considered best suited for monitoring particulate matter. Although there are many studies on the air quality of different locations, only a few data are available on air pollution trends in Indian cities (Guttikunda et al., 2014;Pant et al., 2017Pant et al., , 2019. Megacities have emerged as the hubs of air pollution because of the expansive development and urbanization. ...
The variability of PM2.5 concentrations obtained from the air quality monitoring stations (AQMS) established at six different environments of the Pune Metropolitan Region (PMR), situated in the western part of India, is analyzed for the period 2014–2018. The PM2.5 concentrations showed an increasing trend at almost all locations within the city during the 5 years. Significant features observed were that the green/background location showed a declining trend in PM2.5 concentrations. However, the city's industrial area indicated an increase in PM2.5 concentrations over the years. The seasonal bivariate plot of PM2.5 showed that the winter season has the highest concentration, and also at low wind speeds a high concentration was observed, indicative of the local sources. Concentrated weighted trajectory analysis indicated that regional sources due to long-range transport also played a role in the PM2.5 mass concentration. The wavelet power spectrum of PM2.5 showed 2–4 day oscillations and 30–50 day oscillations associated with Madden-Julian oscillations.
... Fossil fuel-based transportation across the world is amongst the major sources of greenhouse gases (GHG) and other harmful toxic emissions that contribute to environmental degradation and climate change [5]. The harmful chemicals like carbon monoxide (CO), sulphur dioxide (SO2), ozone (O3), and nitrogen oxides (NOx) in air pollutants coming from internal combustion engine vehicles (ICVs) are going beyond the level as prescribed by the National Ambient Air Quality Standards (NAAQS) in the cities of India [6]. These pollutants can be detrimental to individuals' health [7]. ...
India is moving towards electric vehicles. However, the road to the progress of EV adoption does not seem to be smooth and may need effort from the people and the government. With regard to the growth of Electric Vehicles in India, there is a need to find the factors that could hasten its progress. In this paper, we on the basis of the review of the relevant literature from the scientific database are suggesting a range of factors which requires the attention of policymakers and other stakeholders that could contribute to improving electric vehicle adoption in India. The factors are explained in detail along with its implication on electric vehicle adoption.
... Over 10% of the world's burnt clay brick production is produced in India, the second-largest producer in the world. More than 0.1 million brick kilns, which generate around 150-200 billion bricks annually, are said to exist in India (Guttikunda et al., 2014). Industrial brick kilns that burn waste rice husk from agriculture produce much leftover rice when they use the fuel between the columns of the kilns to fire shroud RHA (Jittin et al., 2020). ...
Geopolymer concrete is a sustainable substitute for traditional Portland cement concrete. In addition, rising carbon taxes on carbon emissions and energy intensive materials like cement and lime, impacts the cost of industrial byproducts due to their pozzolanic nature. This research evaluates the compressive strength and flexural strength of geopolymer concrete, and the compressive strength of geopolymer mortar. Geopolymer mortar data were used for the strength assessment employing an analytical approach, and geopolymer concrete data were utilized for the strength and sustainability performances. Using artificial neural networks (ANNs), multi-linear regression (MPR) analysis, and swarm-assisted linear regression, compressive strength models were created based on experimental datasets of geopolymer mortar mixes with variable precursors, alkali-activator percentages, Si/Al, and Na/Al ratios. The strength and sustainability performances of geopolymer concrete blends with various precursors were assessed by considering cost-efficiency, energy efficiency, and eco-efficiency. The work’s originality comes from enhancing sustainable high-performance concrete without overestimating or underestimating precursors. Extensive experimental work was done in the current study to determine the best mix of geopolymer concrete by varying silica fume, ground granulated blast furnace slag (GGBS), and rice husk ash (RHA). A scanning electron microscopic study was conducted to understand the geopolymer matrix’s microstructure further. A comprehensive discussion section is presented to explain the potential role of RHA. The replacement of conventional concrete in all its current uses may be made possible by this sustainable high-performance concrete utilizing RHA.
... In collaboration with the Ministry of Environment and Forestry, CPCB established 43 critically polluted CEPI-based industrial clusters after reviewing the environmental conditions in 88 industrial clusters across India (CPCB 2016). Contributions to vehicle emissions are primarily urban (on-road), but rural areas can also be affected by off-road agricultural sources (Guttikunda et al. 2014). Emissions of primary particulate from residential combustion sectors are more common in rural and low-income urban areas, where people depend more on traditional biomass for cooking and heating. ...
ABSTRACT
The objective of this article is to present comprehensive findings and analysis of studies
performed on air pollutant dispersion in urban environments. It captures India’s rising
environmental pollution due to urbanization, industrialization, and population growth.
Dispersion of pollutants due to the wind in the lower Atmospheric Boundary Layer (ABL) is
a major concern nowadays. The dispersion field around the buildings is a critical parameter
to analyze and it primarily depends on the correct simulation of the wind flow structure.
Therefore, studies performed on this in past years are being reviewed. Additionally, a brief
review of different air dispersion models that are integrated with the Geographic Information
System (GIS) has been studied in this article to assess the exposure. The results of these
studies provide the urban air dispersion model aligning to three sub-models i.e., Emission,
Weather Prediction, and Dispersion models. Various factors like wind speed, wind direction,
cloud cover, traffic emission, disposal of waste, transportation, and others are considered.
This study also captures the problems and risks being faced while creating a model, and its
possible mitigation approaches.
... Clean air is a concern in the mega cities in India, as the content of fine particulates, SO 2 , and NO 2 , are frequently found to exceed the limits of the National Ambient Air Quality Standards (NAAQS). 22 However, many authors claimed that air pollutants like NO 2 and SO 2 , even at low concentrations, may cause harmful effects on human health. [23][24][25] Children are most at risk for health problems related to air pollution. ...
Air quality assessments for NO2 and SO2 levels in indoor and outdoor environments were conducted in three suburban schools in Imphal. Season-wise, the highest NO2 and SO2 concentrations were observed during winter, while the lowest occurred during the monsoon. The concentration of SO2 in the indoor air was comparatively cleaner than in the outdoor air. Similarly, indoor air was found to be cleaner than outdoor air with respect to NO2. The overall concentration obtained for the entire study period for SO2 was 4.9±1.5 µg m-3, and for NO2, it was 9.2±3.0 µg m-3. The concentrations of the two gases obtained during the study were below the NAAQs and WHO permissible limits. Seasonal variation of SO2 concentrations between the pre-monsoon period and monsoon months and also between the monsoon period and winter months (at p<0.001) was significant. For NO2, seasonal variation in the concentrations between the monsoon and winter (at p<0.001) was found significant. The estimated I/O ratios for the two studied gases, which were below one, plus the positive correlation between the classroom and campus environment concentrations of NO2 (r=0.96), and SO2 (r=0.96), reflected the influence of the indoor air quality by outdoor pollution sources. Data on similar studies for the country’s northeastern region, in particular, is scanty, and that’s why it may provide valuable insights to the scientific world.
... Moreover, this regulation will cut 82% of the particulate matter (PM) content [2]. Chennai is one of the metropolitan cities in India, with stupendous industrial sectors, facing 43% of its air pollution from transport and 14% from diesel generator sets [3]. ...
In order to control diesel exhaust emission, CeO2-SnO2/Al2O3 (CTA) mixed oxides were prepared and coated on perforated stainless steel (SS) filter plates, and the catalytic activities were analyzed in this work. The CeO2-SnO2 (different compositions of Ce/Sn—2:8; 1:1; 8:2) composites and Al2O3 were prepared separately via a co-precipitation approach, and CeO2-SnO2/Al2O3 (CTA) mixed oxides were attained by mechanical mixing of 75 wt% CeO2-SnO2 composites with 25 wt% Al2O3. X-ray diffraction (XRD) and Raman spectroscopy were performed for all three CeO2-SnO2/Al2O3 (CTA) mixed oxides; the CeO2-SnO2/Al2O3 (Ce/Sn-1:1) sample confirmed the presence of cubic and tetragonal mixed faces, which enhances the redox nature (catalytic activities). Various characterizations such as high-resolution transmission electron microscopy (HRTEM), Brunauer–Emmett–Teller (BET) analysis, X-ray photoelectron spectroscopy (XPS), and a scanning electron microscope (SEM) were employed on CeO2-SnO2/Al2O3 (Ce/Sn-1:1) sample to investigate the structural, textural, compositional, and morphological properties. The CeO2-SnO2/Al2O3 (Ce/Sn-1:1) sample was coated on a perforated stainless steel (SS) filter plate via a simple, cost-effective, and novel method, and an exhaust emission test for various compression ratios (CR), injection pressure (IP), and load (L) was completed using an AVL Digas analyzer. The CeO2-SnO2/Al2O3 (Ce/Sn-1:1) sample, with a size of 10.22 nm and a high surface area of about 73 m2 g−1, exhibit appreciable catalytic properties.
In the era of the twenty-first century, world population and pollution reached an alarming state, and human lives and this planet are at threatening phase. This is the time to take substantial steps toward the protection and conservation of our environment. The step in the direction of this cause is switching to e-mobility to minimize the use of fossil fuels. This study introduces all types of electric vehicles used by different nations. A negative correlation is found between adoption of electric vehicles (EVs) and greenhouse gas (GHG—CO2, N2O, and methane) across top-20 EV market sharing countries. The chapter examines previous research and synthesizes the factors, incentives, and marketing strategies which different countries are implementing to make their citizen adopt electric vehicles and what India can learn from them to curb their pollution level. The research on the essential barriers such as lack of infrastructure, manufacturers, awareness, and subsidy schemes are addressed for India.
Air pollution is a major risk to health in many developed and developing cities revealed by global environmental studies. Poor air quality is a cause for concern in India and air pollutants including particulate matter (PM), sulphur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), and ozone (O3) often exceed the National Ambient Air Quality Standards (NAAQS). Air pollutants are released into the atmosphere by various sources such as industrialization, rapid urbanization, vehicular pollution, construction activities, mining operations, open garbage burning etc. Construction activities largely produce abundant dust which gets suspended in the air thereby deteriorating the air quality. The construction dust is raised by various debris and demolition activities, site preparation activities, construction processes at construction site. It is the major source of particles and contributes greatly to the PM10 and PM2.5 in the atmospheric environment. Due to strong absorptive capacity of construction dust it is an ideal carrier of bacteria and viruses. It is capable of causing life-threatening diseases, negatively influences the growth of plants, and significantly reduces the visibility. World Health Organization (WHO) reported that 80% of outdoor air pollution-related premature deaths were due to heart disease and strokes, 14% were due to chronic obstructive pulmonary disease or acute lower respiratory infections; and 6% of deaths were due to lung cancer. The contribution of particulate emissions from heavy construction activities depends on several parameters such as type of works, the terrain and its geological texture and composition, meteorological conditions and types of heavy transportation of demolition material. The evaluation of the particulate matter emissions from construction activities becomes important when the standards for particulate matter are being exceeded and the control plans are needed. The amount of dust being generated depends on the seasonal variation. Air quality modeling is a mathematical simulation of how air pollutants disperse and react in the atmosphere to affect ambient air quality based on measured inputs. These models are designed to characterize primary pollutants that are emitted directly into the atmosphere and, in some cases, secondary pollutants too based on inputs of meteorological data and source information like emission rates and stack height etc. So, in order to quantify the impacts of emission sources on ambient air quality and human health it is necessary to evaluate the impact of different emission sources by using efficient air quality prediction tools. Also for air quality management strategies prediction of pollutant concentrations with the aid of regulatory air quality models is an essential part. Models are systematic tools to predict ground level concentrations over a period of time & space from any sources of pollution. The applications of air dispersion models are quite wide such as it can be used for regulatory purpose, urban planning, EIA, source apportionment studies soon & so forth for overall air quality management. However, before implementation of the regulatory model validation is important for which the model is originally developed. The performance of model varies for different source scenarios and climatic conditions thus; a model must be evaluated for the local site conditions prior to its application for predicting and forecasting pollution load.
Real-time detection of hazardous gases in the ambient and indoors has become the prime motive for curbing the problem of air pollution. Keeping the concentration of hazardous gases in control is the main task before human society so as to keep environmental balance. Researchers are concentrating on smart sensors because they can detect and forecast the presence of gas in real-time, provide correct information about gas concentration, and detect a target gas from a mixture of gases. This smart gas sensor system can have applications in the field of military, space, underwater, indoor, outdoors, factories, vehicles, and wearable smart devices. This study reviews recent advances in smart sensor technology with respect to the material structure, sensing technique, and discrimination algorithm. Focus is given on reducing the power consumption and area of a sensor circuitry with the help of different techniques.
Over the past few decades, air pollution and climate change have become major global concerns. In light of this concern about Indian cities, where air pollution and climate change have a significant health impact, this review was conducted. Human health is at risk from the expanding urban areas that experience extreme climate events like high rainfall, extreme temperature, floods, and droughts. Urban residents are experiencing thermal discomfort and a number of health issues as a result of the elevated temperature levels brought on by the intensified heat waves brought on by climate change. The study also looks at the rising levels of air pollution that are higher than what is required for the majority of Indian megacities. The concentrations of PM and aerosols have been investigated, and the potentially harmful effects on human health of particles that enter the respiratory system and are inhaled by humans have also been discussed. Also looked at were the health effects of the COVID-2019 lockdown on Indian cities' air quality. Lastly, the link between urbanization, air pollution, and climate change has been shown because air pollutants like aerosols affect Earth's climate directly (through absorption and scattering) and indirectly (through modifying cloud properties and radiation transfer processes). As a result, the information in this review will act as a starting point for policymakers when it comes to evaluating vulnerable regions and putting into action plans to reduce air pollution. Based on the review, adaptation and mitigation measures can be implemented in Indian cities to mitigate the effects on human health by regularly monitoring air pollution and addressing climate change.
With the spread of COVID-19 pandemic worldwide, the Government of India had imposed lockdown in the month of March 2020 to curb the spread of the virus furthermore. This shutdown led to closure of various institutions, organizations, and industries, and restriction on public movement was also inflicted which paved way to better air quality due to reduction in various industrial and vehicular emissions. To brace this, the present study was carried out to statistically analyze the changes in air quality from pre-lockdown period to unlock 6.0 in South Indian cities, namely, Bangalore, Chennai, Coimbatore, and Hyderabad, by assessing the variation in concentration of PM2.5, PM10, NO2, and SO2 during pre-lockdown, lockdown, and unlock phases. Pollutant concentration data was obtained for the selected timeframe (01 March 2020-30 November 2020) from CPCB, and line graph was plotted which had shown visible variation in the concentration of pollutants in cities taken into consideration. Analysis of variance (ANOVA) was applied to determine the mean differences in the concentration of pollutants during eleven timeframes, and the results indicated a significant difference (F (10,264) = 3.389, p < 0.001). A significant decrease in the levels of PM2.5, PM10, NO2, and SO2 during the lockdown phases was asserted by Tukey HSD results in Bangalore, Coimbatore, and Hyderabad stations, whereas PM10 and NO2 significantly increased during lockdown period in Chennai station. In order to understand the cause of variation in the concentration of pollutants and to find the association of pollutants with meteorological parameters, the Pearson correlation coefficient was used to study the relationship between PM2.5, PM10, NO2, and SO2 concentrations, temperature, rainfall, and wind speed for a span of 15 months, i.e., from January 2020 to March 2021. At a significant level of 99.9%, 99%, and 95%, a significant correlation among the pollutants, rainfall had a major impact on the pollutant concentration in Bangalore, Coimbatore, Hyderabad, and Chennai followed by wind speed and temperature. No significant influence of temperature on the concentration of pollutants was observed in Bangalore station.
Increasing health problems owing to air pollution is the major cause of concern in the present time, especially in regions with exceptionally high particulate matter (PM) namely Indo-Gangetic Plains (IGP). In the ambient PM, polycyclic aromatic hydrocarbons (PAHs) have been reported to be carcinogenic in nature and its dominant sources are diesel emissions, coal combustion, agricultural waste burning, wood, and cow-dung cake burning. The chemical characteristics of particulate-bound PAHs from all the mentioned sources, their intercomparison, and entrainment into the atmosphere have been assessed in this study. High-molecular weight (HMW) PAHs fraction is highest in emissions from coal combustion (∼95%), followed by agricultural waste burning (83%), wood burning (83%) and cow-dung cake (77%) combustion. Among all the PAH compounds, benzo (b,j) fluoranthene (B[bj]F) was found to be predominant (highest in wood combustion ∼20.3%) in all source samples except exhaust from diesel and bio-diesel engine installed with diesel oxidation catalyst (DOC). Dominant PAH compounds contributing to the carcinogenic potential (CP) are benzo (a) pyrene (B[a]P), dibenzo (a,h) anthracene (D[ah]A), benzo (b,j) fluoranthene (B[bj]F), benzo (a) anthracene (B[a]A) and indeno (1,2,3-c,d) pyrene (IP). Wood combustion (CP = 1.4 ± 0.8) emission is observed to be the most carcinogenic followed by coal combustion (0.8 ± 0.2), diesel exhaust emission (0.4 ± 0.3), cow-dung cake burning (0.2), and agricultural waste burning (0.2 ± 0.1). Further, the range of various diagnostic ratios for each of the source samples has been reported that can be utilized in future studies for more comprehensive source apportionment.
The Springer Scopus indexed 4th International Conference on Computer and
Communication Technologies (IC3T) 2022 organized by Department of ECE,
KITSW, was held in Warangal, Telangana, during July 29–30, 2022. Warangal, the
home of a major state university amid pleasant surroundings, was a delightful place
for the conference. The 230 scientific participants, 102 of whom were students,
had many fruitful discussions and exchanges that contributed to the success of
the conference. Participants from eight countries and 14 states of India made the
conference truly international in scope. The 62 abstracts that were presented on the two days formed the heart of the conference and provided ample opportunity for discussion. This change, allowing the conference to end with invited talks from the industry experts, was a departure from the format used at previous IC3T conferences. The abstracts were split almost equally between the five main conference areas, i.e., image processing and communications system, VLSI, wireless networks, Internet of Things (IoT) and machine learning (ML), and the posters were distributed across the days of the conference, so that approximately equal numbers of abstracts in the different areas were scheduled for each day. Of the total number of presented abstracts, 50 of these are included in this proceedings volume, the first time that abstracts have been published by IC3T. There were four plenary lectures covering the different areas of the conference: Dr. Suresh Chandra Satapathy (Professor, KIIT, Bhubaneswar) talked on Social Group Optimization and its applications to Image Processing, Dr. Mathini Sellathurai, (Professor, Heriot-Watt University, UK) on Sustainable 6G: Energy Efficient Auto encoder-Based Coded Modulation Designs for Wireless Networks, Dr. K. Srujan Raju (Professor, CMR Technical Campus, Hyderabad), on optimizing solutions in a variety of disciplines of Computer Science and Engineering, and Dr. K. Ashoka Reddy (Professor, KITS Warangal) on Applications of Biomedical Signal processing in Current Engineering Technologies. Two eminent speakers from industry gave very illuminating public lectures that drew many people from the local area, as well as conference participants: Vijay Kumar Gupta Kopuri (CEO, Kwality Photonics Pvt. Ltd.) on “Manufacturing of LEDs and Compound Semiconductors” and K. Jagadeshwar Reddy (Managing Director, Elegant Embedded Solutions Pvt. Ltd.) on “optimized solutions adopted Preface in Embedded System Design in Current Scenario.” These public talks were very accessible to a general audience. In addition, notably, this was the third conference at KITSW, and a formal session was held the first day to honor the event as well as those who were instrumental in initiating the conference.
Generous support for the conference was provided by Captain V. Lakshmikantha
Rao, Honorable Ex. MP (Rajya Sabha), Former Minister, and Chairman, KITS,
Warangal. The funds were sizeable, timely, greatly appreciated, and permitted us to support a significant number of young scientists (postdocs and students) and persons from developing/disadvantaged countries. Nevertheless, the number of requests was far greater than the total support available (by about a factor of five!), and we had to turn down many financial requests. We encourage the organizers of the next IC3T to seek a higher level of funding for supporting young scientists and scientists from developing/disadvantaged countries. All in all, the Springer Scopus Indexed 4th IC3T 2022 in Warangal was very successful. The plenary lectures and the progress and special reports bridged the gap between the different fields of Computers and Communication Technology, making it possible for non-experts in a given area to gain insight into new areas. Also, included among the speakers were several young scientists, namely postdocs and students, who brought new perspectives to their fields.
The next IC3T will take place in Warangal in 2023 and trend to be continued every
year. Given the rapidity with which science is advancing in all of the areas covered
by IC3T 2022, we expect that these future conferences will be as stimulating as this
most recent one was, as indicated by the contributions presented in this proceedings
volume.
We would also like to thank the authors and participants of this conference, who
have considered the conference above all hardships. Finally, we would like to thank all the reviewers, session chairs and volunteers who spent tireless efforts in meeting the deadlines and arranging every detail to make sure that the conference runs smoothly.
People are altogether dependent on air as a wellspring of energy. Without air, people would die. Inspecting and safeguarding air quality have become one of the most fundamental government exercises in numerous modern and metropolitan regions today. Individuals’ well-being is affected by the release of these hurtful mixtures into the environment, particularly in metropolitan regions. As the total populace extends, deforestation is turning out to be progressively far and wide. The nature of the air will diminish. The climate is turning out to be more dirtied, and the temperature is climbing too. A wide scope of medical conditions has been distinguished. A few strategies have been created. In this examination, information mining approaches are utilized to gage the temperature focus in the climate. The skin and mucous membranes of the eyes, nose, throat, and lungs are affected by the disease.KeywordsDeep learningAir qualityTempPredictionGasses
The rapid growth of the industries, transportation and urbanization is the main cause of increase in ambient air pollution. Air pollutants ultimately deteriorate the health condition of living beings. The major air pollutants like Nitrous Oxides (NOx), Sulphur dioxide (SO 2), Particulate Matter (PM 10) especially Particulate Matter (PM) can be considered as invisible carriers. Secondary data were collected and those data demonstrate the fifteen years annual average concentration of SO 2 , NOx, and Particulate Matter (PM 10) in five major locations of the city. The value of RSPM only exceeds the permissible limit of NAAQ. The results show the locations Gandhi market, Central bus stand and Main guard gate are considered highly polluted area and other Golden Rock and Bishop Heber are less polluted areas. Dirty air or air pollutants enter deep into our lungs, can cause respiratory illness like Chronic Obstructive Pulmonary Disease (COPD), asthma and respiratory allergy. This paper is to assess the air quality status of the city and its health impact. Therefore, it is observed that these areas are classified as vulnerable to respiratory diseases.
Atmospheric transport of iron (Fe) in fine anthropogenic aerosol particles is an important route of soluble Fe supply to remote oceans from continental areas. To investigate Fe properties of aerosol particles over remote oceans, we analyzed atmospheric aerosol particles over the Indian Ocean during the research vessel Hakuho Maru KH-18-6 cruise. Aerosol particles collected using a cascade impactor were analyzed using transmission electron microscopy (TEM) with an energy-dispersive X-ray spectrometry analyzer. The particle shape and composition on the sample stage of 0.3–0.8 μm aerodynamic diameter indicated that most particles collected north of the equator were composed mainly of ammonium sulfate. Regarding the particle number fraction, 0.6–3.0 % of particles contained Fe, which mostly co-existed with sulfate. Of those particles, Fe was found 26 % as metal spheres, often co-existing with Al or Si, regarded as fly ash, 14 % as mineral dust, and 7 % as iron oxide aggregations. Water-dialysis analyses of TEM samples indicated that Fe in spherical fly ash was almost entirely insoluble, whereas Fe in the other morphological-typed particles was partly (65 % Fe mass on average) soluble. Global model simulations mostly reproduce observed Fe mass concentrations in PM2.5 collected using a high-volume air sampler, including their north–south contrast during the cruise. In contrast, a marked difference was found between the simulated mass fractions of Fe mineral sources and the observed Fe types. For example, the model underestimated anthropogenic aluminosilicate Fe contained in matter such as fly ash from coal combustion. Our observations suggest that Fe in particles over remote ocean areas has multiple shapes and minerals, and further suggest that its solubility after aging processes differs depending on their morphological and mineral type. Proper consideration of such Fe types at their sources is necessary for accurate estimation of atmospheric Fe effects on marine biological activity.
Bricks have a long history of being utilized as a construction material across the globe. The production processes involved in the manufacture of bricks have a significant impact on the environment, human health, economy, and society. This study conducts a thematic and bibliometric analysis to provide an in-depth review of the effects of brick kilns on humans and the environment. The PRISMA framework was used to identify relevant articles from the Web of Science database, resulting in the selection and critical review of 348 articles. The bibliometric analysis included an evaluation of historical growth, keywords, citation and co-citation, organizations, and countries. The articles were published in 213 journals, written by 1396 authors from 670 institutions in 66 countries. Thematic analysis revealed that brick kilns have a negative impact on the environment, including soil damage, and cause health problems for kiln workers and animals. Modern slavery and societal issues also persist in developing countries. The current research is focused on finding alternative materials for brick manufacturing, improving industry energy efficiency, managing waste, and technological advancements, such as the implementation of the zigzag or Hoffmann kiln to reduce pollution. In developing countries, utilizing waste from other industries in brick production can effectively lower production costs. While developed countries have embraced advanced technologies for brick production, it is recommended that developing countries adopt awareness campaigns to encourage the upgrading of kilns to cleaner and more sustainable systems. Future research directions should aim to support brick kiln owners in adopting such systems.
Severe air pollution in China and India threatens the health of over one-third of the global population. When it comes to air pollution governance, the two countries have vastly different approaches. China’s approach features centralized target-setting and implementation, with policies enforced primarily through top-down administrative lines. While India’s approach reflects the division of power among central and state governments and relies substantially on legislative and judiciary systems for accountability. We conduct a detailed review of the trends and sources of six air pollutants in China and India, and make a structured comparison of China and India’s air pollution policy frameworks. An extensive literature review is conducted to evaluate the effectiveness of policies in each country. The studies show that China’s policy efforts have achieved significant improvements in air quality, while India’s policies have been largely ineffective. Nevertheless, both approaches have the potential to lead to effective air pollution governance, if a country can build strong political will and clearly defined accountability systems. We further identify key lessons learned from the two countries for air pollution policymaking in developing countries, including taking good advantage of “post-crisis policy window”, and targeting “low-hanging fruits” to make incremental improvements in a cost-effective way.
In Chile, the concept of sacrifice zones corresponds to those land surfaces in which industrial development was prioritized over the environmental impact that it caused. A high number of industries that emit pollutants into the environment are concentrated in these zones. This paper studies the atmospheric component of the Environmental Impact Declaration and Assessment’s (EID and EIA, respectively) environmental assessment instruments of the thermoelectric power plants in northern Chile, based on their consistency with current environmental quality regulations. We specify concepts on air quality, atmospheric emission regulations, and the critical parameters and factors to be considered when carrying out an environmental impact assessment. Finally, we end by presenting possible alternatives to replace the current methodologies and criteria for atmospheric regulation in areas identified as saturated or of environmental sacrifice, with an emphasis on both population health and an environmental approach.
Infrastructure investment plays a key role in steady economic growth. Investment in infrastructure is gradually increasing; however, large-scale infrastructure investment is also associated with efficiency problems and environmental problems, which need to be carefully examined. The entropy weight method and the Super-SBM model are implemented to measure environmental regulation and infrastructure investment efficiency, respectively; and the spatial Durbin model is applied to analyze the influence mechanism and spatial effects of environmental regulation on infrastructure investment efficiency. The results show that spatial agglomeration characteristics exist in both environmental regulation and infrastructure investment efficiency. Besides, environmental regulation can promote infrastructure investment efficiency in general, but it develops an inverted U-shaped relationship as the intensity increases. Lastly, the spillover effects of environmental regulation on infrastructure investment efficiency present a U-shaped relationship. The conclusion is that both environmental regulation and infrastructure investment efficiency in China increased from 2008 to 2020. Besides, moderate environmental regulation is beneficial to infrastructure investment efficiency and restrains spatial spillover, but strict environmental regulation appears to be the opposite. This research expands the literature on environmental regulation and production efficiency and provides a reference basis for formulating effective policies to improve infrastructure investment efficiency from the perspective of the ecological environment.
Our Country India is a developing Country and with the onset of heavy production, urbanization and Industrialization in the recent years has imposed a heavy threat on the Environment, The direct impact of which could be seen in the deteriorating Air Quality. Since air pollution continues to rise at an alarming rate, it affects economies and inhabitants quality of life leading to health emergency situations. This paper presents the Air Quality data interpretation and modelling to study for correlation between different Air Quality Parameters specifically Particulate Matter in Residential and Commercial regions of Lucknow-The Second largest city of Uttar Pradesh. The levels of PM2.5 and PM10 was found to be exceeding than 24 Hrs avg as well as Annual Average value (as set by NAAQS ) in Commercial Region , while in Residential Region the levels of PM2.5 and PM10 were almost in acceptable range as set by NAAQS . Later on studying the comprehensive correlation between the PM2.5 and PM10 by applying various regression models, As per the levels of PM as obtained in commercial region , Compound Curve Regression Model seems to be of highest significance showing 92.1% relation response with highest Standardized Beta Coefficient having value of 2.611 . While for Residential region as per the levels of PM obtained, Cubic Curve Regression Model gave best suited result depicting 77.9% relation response amongst PM2.5 and PM10 with highest Standardized Beta Coefficient Value of 3.028 .
Promoting the use of ethanol gasoline is an important approach for China to achieve sustainable and high-quality development. Based on the daily air quality data of Tianjin, China, from 2013 to 2020, this paper investigates whether the implementation of the ethanol gasoline policy helped improve air quality using regression discontinuity analysis. We find that the implementation of the ethanol gasoline policy had a very limited positive effect on the overall air quality index (AQI) and no obvious effect on the reduction of particulate matter (PM2.5 and PM10). However, the results reveal that the ethanol gasoline policy reduced SO2, NO2, and CO by about 36%, 19%, and 20%, respectively. These findings provide policy insights for other cities in China and other rapidly developing cities in the world to promote the use of ethanol gasoline.
Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO2 and SO2, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO2 and SO2 over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005-2019. IGP experienced an overall increment in AOD (R2 = 0.63) and SO2 (R2 = 0.67) values, with LIGP (AOD, R2 = 0.8 & SO2, R2 = 0.8) experiencing the largest rate of enhancement. The levels of NO2 (R2 = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R2 = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO2 value (3.82 ± 0.98 × 1015 molecules/cm2) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO2 (3.8 ± 1.4 × 1015 molecules/cm2) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO2 level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO2 and NO2, implying no pollution abatement effect on SO2 and NO2 pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.
Near real-time monitoring of major air pollutants, i.e., particulate matter (PM10, PM2.5, PM1), trace gases (O3, CO, NO, NO2, NOx, NH3, CO2, SO2) and Volatile Organic Compounds (VOCs) (benzene, ethylbenzene, m-, p-xylene, o-xylene and toluene) along with climatological parameters was done in eight-cities field campaigns during the rabi (wheat) crop residue burning period in the northwest of Indo-Gangetic Plain (IGP) region. The phase-wise monitoring was done at eight locations representing rural, semi-urban and urban backgrounds. During the whole campaign, the semi-urban site (Sirsa) observed the highest average concentration of PM10 (226 ± 111 μg m⁻³) and PM2.5 (91 ± 67 μg m⁻³). The urban site (Chandigarh) reported the minimum concentrations of all the three size fractions of particulate matter with PM10 as 89 ± 54 μg m⁻³, PM2.5 as 42 ± 22 μg m⁻³ and PM1 as 20 ± 13 μg m⁻³ where the monitoring was done in the early phase of the campaign. The highest VOC concentration was recorded at the semi-urban (Sirsa) site, whereas the lowest was at a rural location (Fatehgarh Sahib). NH3 concentration was observed highest in rural sites (31.7 ± 29.8 ppbv), which can be due to the application of fertilizers in agricultural activities. Visible Infrared Imaging Radiometer Suite (VIIRS) based fire and thermal anomalies, along with HYSPLIT back trajectory analysis, show that major air masses over monitoring sites (22 %–70 %) were from the rabi crop residue burning regions. The characteristic ratios and Principal component analysis (PCA) results show that diverse sources, i.e., emissions from crop residue burning, solid biomass fuels, vehicles and industries, majorly degrade the regional air quality. This multi-city study observed that semi-urban regions have the most compromised air quality during the rabi crop residue burning and need attention to address the air quality issues in the IGP region.
This working paper presents an overview of the evolution of the electronic road pricing system in Singapore since 1998, technical and institutional improvements made over the years, and how a public campaign was carried out for its successful implementation.
Unlike toll road systems in operation in other countries, a road pricing system charges vehicles for usage of the road in accordance with the congestion they are causing. Also termed as “Congestion pricing”, in this practice, the motorists are charged to use a roadway, bridge, or tunnel during periods of the heaviest use. Its purpose is to reduce automobile (car) use during periods of peak congestion, thereby easing traffic and encouraging commuters to walk, bike or take mass transit rail/bus as an alternative. Hence higher rates are charged during the peak (or rush) hours and lower rates or no charges are levied at other times.
The number concentrations of cloud condensation nuclei (CCN) and submicron aerosols (CN), along with their chemical composition and optical properties, have been studied during October 2008, October-November 2009 and November 2010 from an urban (Kanpur) site in the Indo-Gangetic Plain (IGP). The concentrations of CCN and CN and their optical properties vary with primary emission and secondary aerosol formation. The CCN (at 0.38% super-saturation) and CN concentrations varied from ∼3900 to 15,000 cm-3 and ∼23,000 to 99,000 cm-3, respectively. The diurnal variability of CCN and CN show peak concentrations during early morning hours (6:00-9:00 AM) and nighttime (7:00-10:00 PM), attributable to variability in source strength of carbonaceous aerosols and secondary aerosol formation. The CCN and CN concentrations are ∼50% higher during nighttime with simultaneous increase in organic carbon (OC), elemental carbon (EC) and NO3- mass concentrations. However, CCN/CN ratios are similar during day and nighttime suggesting their co-variability with primary and secondary aerosol formation. The CCN/CN ratios are relatively lower (range: 0.11-0.33) than global average value and those over urban areas (with similar chemical composition in China and around the world) suggesting suppressed activation and hygroscopic growth in highly polluted environment of the IGP. The average mass absorption efficiency of EC during daytime (11.7 ± 2.5 m2 g-1) is about factor of two higher than that during nighttime (5.7 ± 1.3 m2 g-1). These results have implications to study morphological features, mixing state and microphysical properties of aerosols under high acidic environment over northern India.
This case study of the brick kiln sector in Chennai shows that workers are in a "mild" situation of debt bondage, have to work for long hours, and very often put their children to work as well. However, they are paid wages that are very close to the rates fixed by the government and the system of advance payment is endorsed by both workers and kiln owners and the former see it as a means to social mobility. Only the coming together of employers, unions, NGOs, public authorities and job brokers can help break the debt bondage.
In the Comparative Risk Assessment (CRA) done as part of the Global Burden of Disease project (GBD-2010), the global and regional burdens of household air pollution (HAP) due to the use of solid cookfuels, were estimated along with 60+ other risk factors. This article describes how the HAP CRA was framed; how global HAP exposures were modeled; how diseases were judged to have sufficient evidence for inclusion; and how meta-analyses and exposure-response modeling were done to estimate relative risks. We explore relationships with the other air pollution risk factors: ambient air pollution, smoking, and secondhand smoke. We conclude with sensitivity analyses to illustrate some of the major uncertainties and recommendations for future work. We estimate that in 2010 HAP was responsible for 3.9 million premature deaths and 4.8% of lost healthy life years (DALYs), ranking it highest among environmental risk factors examined and one of the major risk factors of any type globally.
PM10 concentration was monitored at a receptor site in the Brahmaputra Valley during a unique, local, episodic festive biomass burning called meji burning. Mean mass concentration of PM10 during monitoring was found to be 149 ± 45 μg m− 3 with maximum and minimum concentrations of 293 μg m− 3 and 93 μg m− 3 respectively. Elemental analysis by Energy Dispersive X-ray Spectrometer (EDX) revealed high carbonaceous and Br content in PM10 samples. Particulate carbon showed high significant correlation with PM10 and dominance in samples taken during night time. Back trajectory analysis supported long range transport of carbonaceous aerosol from the Indo-Gangetic Plain (IGP) to the region under study. Prevailing meteorology – thermal inversion and low mixing heights – was found to have a strong influence on PM10 levels in the post festive burning period. Enrichment factors of several elements ranged above thousand which indicated a strong influence of anthropogenic activities and input of aged particulates driven from long distance. Incremental effect of meji burning, which we coined as Meji Burning Induced Enrichments (MBIEs), was calculated. MBIE values supported incremental effects explicitly.
In 2010, the XIX Commonwealth Games (CWG-2010) were held in India for
the first time at Delhi and involved 71 commonwealth nations and
dependencies with more than 6000 athletes participating in 272 events.
This was the largest international multi-sport event to be staged in
India and strict emission controls were imposed during the games in
order to ensure improved air quality for the participating athletes as a
significant portion of the population in Delhi is regularly exposed to
elevated levels of pollution. The air quality control measures ranged
from vehicular and traffic controls to relocation of factories and
reduction of power plant emissions. In order to understand the effects
of these policy induced control measures, a network of air quality and
weather monitoring stations was set-up across different areas in Delhi
under the Government of India's System of Air quality Forecasting And
Research (SAFAR) project. Simultaneous measurements of aerosols,
reactive trace gases (e.g. NOx, O3, CO) and
meteorological parameters were made before, during and after CWG-2010.
Contrary to expectations, the emission controls implemented were not
sufficient to reduce the pollutants, instead in some cases, causing an
increase. The measured pollutants regularly exceeded the National
Ambient Air Quality limits over the games period. The reasons for this
increase are attributed to an underestimation of the required control
measures, which resulted in inadequate planning. The results indicate
that any future air quality control measures need to be well planned and
strictly imposed in order to improve the air quality in Delhi, which
affects a large population and is deteriorating rapidly. Thus, the
presence of systematic high resolution data and realistic emission
inventories through networks such as SAFAR will be directly useful for
the future.
Policy summary - low-carbon mobility in india and the challenges of social inclusion: bus rapid transit (BRT) case studies in india
Nearly 3 billion people worldwide rely on solid fuel combustion to meet basic household energy needs. Resulting exposure to air pollution is estimated to cause 4.5% of the global burden of disease. Large variability and a lack of resources for research and development have resulted in highly uncertain exposure estimates. The objective of this paper is to identify research priorities for exposure assessment that will more accurately and precisely define exposure-response relationships of household air pollution necessary to inform future cleaner-burning cookstove dissemination programs.
As part of a May 2011 international workshop, an expert group characterized the state of the science and developed recommendations for exposure assessment of household air pollution.
The following priority research areas were identified to explain variability and reduce uncertainty of household air pollution exposure measurements: improved characterization of spatial and temporal variability for studies examining both short- and long-term health effects; development and validation of measurement technology and approaches to conduct complex exposure assessments in resource-limited settings with a large range of pollutant concentrations; and development and validation of biomarkers for estimating dose. Addressing these priority research areas, which will inherently require an increased allocation of resources for cookstove research, will lead to better characterization of exposure-response relationships.
Although the type and extent of exposure assessment will necessarily depend on the goal and design of the cookstove study, without improved understanding of exposure-response relationships, the level of air pollution reduction necessary to meet the health targets of cookstove interventions will remain uncertain.
India is used as a case study in reviewing the application of receptor models for source apportionment. India has high concentrations of airborne particulate matter, and the application of effective abatement measures is a high priority, and demands confidence in the results of source apportionment studies. The many studies conducted are reviewed, and reveal a very wide range of conclusions, even for the same city. To some degree these divergences may be the result of using different sampling locations and/or seasons, but to a large extent differences probably arise from methodological weaknesses. The assignment of factors from multivariate receptor models to specific source categories is in many cases highly questionable as factors often include combinations of chemical constituents that are of low plausibility. This ambiguity in terms of presence of tracer elements may be the result of genuine collinearity of diverse sources, or more probably arises from methodological problems. Few studies have used either organic molecular markers or chemical mass balance (CMB) models, and there is a shortage of data on locally-derived emission source profiles, although recent work has begun to remedy this weakness. The conclusions include a number of recommendations for use in design of future studies.
India has recently launched the National Biomass Cookstoves Initiative (NCI) to develop next-generation cleaner biomass cookstoves and deploy them to all Indian households that currently use traditional cookstoves. The initiative has set itself the lofty aim of providing energy service comparable to clean sources such as LPG but using the same solid biomass fuels commonly used today. Such a clean energy option for the estimated 160 million Indian households now cooking with inefficient and polluting biomass and coal cookstoves could yield enormous gains in health and welfare for the weakest and most vulnerable sections of society. At the same time, cleaner household cooking energy through substitution by advanced-combustion biomass stoves (or other options such as clean fuels) can nearly eliminate the several important products of incomplete combustion that come from today's practices and are important outdoor and greenhouse pollutants. Using national surveys, published literature and assessments, and measurements of cookstove performance solely from India, we find that about 570,000 premature deaths in poor women and children and over 4% of India's estimated greenhouse emissions could be avoided if such an initiative were in place today. These avoided emissions currently would be worth more than US$1 billion on the international carbon market. In addition, about one-third of India's black carbon emissions can be reduced along with a range of other health- and climate-active pollutants that affect regional air quality and climate. Although current advanced biomass stoves show substantial emissions reductions over traditional stoves, there is still additional improvement needed to reach LPG-like emission levels. We recognize that the technology development and deployment challenges to meet NCI goals of this scale are formidable and a forthcoming companion paper focuses on what program design elements might best be able to overcome these challenges.
Environmental and occupational risk factors contribute to nearly 40% of the national burden of disease in India, with air pollution in the indoor and outdoor environment ranking amongst leading risk factors. It is now recognized that the health burden from air pollution exposures that primarily occur in the rural indoors, from pollutants released during the incomplete combustion of solid fuels in households, may rival or even exceed the burden attributable to urban outdoor exposures. Few environmental epidemiological efforts have been devoted to this setting, however. We provide an overview of important available information on exposures and health effects related to household solid fuel use in India, with a view to inform health research priorities for household air pollution and facilitate being able to address air pollution within an integrated rural-urban framework in the future.
Epidemiologic and health impact studies of fine particulate matter with diameter < 2.5 microm (PM2.5) are limited by the lack of monitoring data, especially in developing countries. Satellite observations offer valuable global information about PM2.5 concentrations.Objective: In this study, we developed a technique for estimating surface PM2.5 concentrations from satellite observations.
We mapped global ground-level PM2.5 concentrations using total column aerosol optical depth (AOD) from the MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multiangle Imaging Spectroradiometer) satellite instruments and coincident aerosol vertical profiles from the GEOS-Chem global chemical transport model.
We determined that global estimates of long-term average (1 January 2001 to 31 December 2006) PM2.5 concentrations at approximately 10 km x 10 km resolution indicate a global population-weighted geometric mean PM2.5 concentration of 20 microg/m3. The World Health Organization Air Quality PM2.5 Interim Target-1 (35 microg/m3 annual average) is exceeded over central and eastern Asia for 38% and for 50% of the population, respectively. Annual mean PM2.5 concentrations exceed 80 microg/m3 over eastern China. Our evaluation of the satellite-derived estimate with ground-based in situ measurements indicates significant spatial agreement with North American measurements (r = 0.77; slope = 1.07; n = 1057) and with noncoincident measurements elsewhere (r = 0.83; slope = 0.86; n = 244). The 1 SD of uncertainty in the satellite-derived PM2.5 is 25%, which is inferred from the AOD retrieval and from aerosol vertical profile errors and sampling. The global population-weighted mean uncertainty is 6.7 microg/m3.
Satellite-derived total-column AOD, when combined with a chemical transport model, provides estimates of global long-term average PM2.5 concentrations.
Although the deleterious effects of air pollution from fossil fuel combustion have been demonstrated in many Western nations, fewer studies have been conducted in Asia. The Public Health and Air Pollution in Asia (PAPA) project assessed the effects of short-term exposure to air pollution on daily mortality in Bangkok, Thailand, and in three cities in China: Hong Kong, Shanghai, and Wuhan.
Poisson regression models incorporating natural spline smoothing functions were used to adjust for seasonality and other time-varying covariates that might confound the association between air pollution and mortality. Effect estimates were determined for each city and then for the cities combined using a random effects method.
In individual cities, associations were detected between most of the pollutants [nitrogen dioxide, sulfur dioxide, particulate matter < or = 10 microm in aerodynamic diameter (PM(10)), and ozone] and most health outcomes under study (i.e., all natural-cause, cardiovascular, and respiratory mortality). The city-combined effects of the four pollutants tended to be equal or greater than those identified in studies conducted in Western industrial nations. In addition, residents of Asian cities are likely to have higher exposures to air pollution than those in Western industrial nations because they spend more time outdoors and less time in air conditioning.
Although the social and environmental conditions may be quite different, it is reasonable to apply estimates derived from previous health effect of air pollution studies in the West to Asia.
Sponsored by the Hazardous, Toxic, and Radioactive Waste Engineering Committee of the Environmental Council of the Environmental and Water Resources Institute of ASCE Sustainable Solid Waste Management describes basic principles and recent advances for handling solid waste in an environmentally sustainable way. Solid waste poses problems of quantity-the sheer amount is increasing around the world-but also of environmental impact, especially with the introduction of materials harmful to ecosystems. This volume uses a global lens to examine all aspects of the solid waste, including waste minimization, waste as a resource, appropriate disposal, and efficient systems fostered by effective public policy. Written by leading experts, the 22 chapters analyze the critical issues to be considered during the various stages of a waste management program. Topics include: public policies focusing on reducing waste at its source, recycling, and minimizing disposal amounts; technologies for treating and recycling solid waste; safe, efficient treatment and disposal of hazardous and other special wastes; development and maintenance of engineered landfills and landfill mining; and legal frameworks and the use of life-cycle assessment as a tool for the waste management industry. Municipal engineers, environmental managers, researchers, students, policy makers, and planners will find this book to be an essential guide to social and technological issues related to sustainable solid waste management.
The average level of ownership of cars in India, currently 13 per 1,000 population, is expected to grow exponentially. Estimating the average level of ownership in 2025 at 35 per 1,000, this article points out that the growing number of cars has serious implications for energy security, air pollution, road safety, and equitable allocation of road space, and argues that there is an urgent need for India to learn from the experiences of cities that have decoupled car ownership from economic growth, and reduce the rate of growth of car ownership in India.
Atmospheric aerosols are important from a perspective of ambient air pollution and health to humans and other biological receptors as well as for potential effects on local weather and global climate. This review attempts to account for the different research efforts of individual research groups and regulatory agencies in India on the issue of atmospheric aerosols and their effects. The review refers to representative studies reporting the physical characterization (size), chemical composition (organic and inorganic), radiative forcing effects and health effects of aerosols. There are several reports on source apportionment studies identifying sources of aerosols and some focus on specific issues. The review also points out a significant need for more data with a greater spatial and temporal resolution for better understanding of the dynamics of atmospheric aerosols in the Indian context.
Seven years after the National Urban Transport Policy was announced by the central government, the problems identified in it remain the same, or have worsened. Land use planning has not enabled the lower-income groups to live closer to work, road use is more dominated by private vehicles, and there is little money to improve facilities for pedestrians and bicyclists. This paper notes that though much of the basic data on urban transport in India is unreliable, there is enough to show that the challenge is to keep the share of non-personal transport at 70% as incomes increase in our cities. For this, walking and bicycling have to be made safer and public transport more attractive by making it readily available.
Atmospheric heating caused by anthropogenically emitted carbonaceous aerosols contributes to one of the largest uncertainties in climate forcing over south Asia (SA). Past studies have identified the combustion of fossil fuels and residential biofuels as being the dominant emitter of light-absorbing black carbon aerosols over this region. Here, we measure emissions from open-air burning of funeral pyres, a deep-rooted and widely prevalent custom in SA, and find that large amounts (≈98% by mass) of light-absorbing organic carbon (OC) aerosols, optically defined as brown carbon (BrC), are emitted per kilogram of feedstock burned. The emitted OC contributes an average 40% to the smoke particulate matter absorption of the visible solar radiation. We calculate funeral pyres in SA contribute approximately 92 Gg of light-absorbing OC annually, which is equivalent to ≈10 and 23% of the carbonaceous aerosol mass from regional biofuels and fossil fuels, respectively. Our findings underscore the importance of accounting for cultural burning practices as aerosol sources in emission inventories and BrC aerosols in climate models, as well as the development of mitigation strategies.
In India, of the 210 GW electricity generation capacity, 66% is derived from coal, with planned additions of 76 GW and 93 GW during the 12th and the 13th five year plans, respectively. Atmospheric emissions from the coal-fired power plants are responsible for a large burden on human health. In 2010–11, 111 plants with an installed capacity of 121 GW, consumed 503 million tons of coal, and generated an estimated 580 ktons of particulates with diameter less than 2.5 μm (PM2.5), 2100 ktons of sulfur dioxides, 2000 ktons of nitrogen oxides, 1100 ktons of carbon monoxide, 100 ktons of volatile organic compounds, and 665 million tons of carbon dioxide. These emissions resulted in an estimated 80,000 to 115,000 premature deaths and 20.0 million asthma cases from exposure to PM2.5 pollution, which cost the public and the government an estimated INR 16,000 to 23,000 crores (USD 3.2 to 4.6 billion). The emissions were estimated for the individual plants and the atmospheric modeling was conducted using CAMx chemical transport model, coupled with plume rise functions and hourly meteorology. The analysis shows that aggressive pollution control regulations such as mandating flue gas desulfurization, introduction and tightening of emission standards for all criteria pollutants, and updating procedures for environment impact assessments, are imperative for regional clean air and to reduce health impacts. For example, a mandate for installation of flue gas desulfurization systems for the operational 111 plants could reduce the PM2.5 concentrations by 30–40% by eliminating the formation of the secondary sulfates and nitrates.
The simultaneous measurements of brown carbon (BrC) and elemental carbon (EC) are made in ambient aerosols (PM2.5), collected from a site in north-east India during November’09-March’10, representing the atmospheric outflow from the Indo-Gangetic Plain (IGP) to the Bay of Bengal (BoB). The absorption coefficient of BrC (babs), assessed from water-soluble organic carbon (WSOC) at 365 nm, varies from 2 to 21 Mm-1 and exhibits significant linear relationship (P < 0.05) with WSOC concentration (3 – 29 μg m-3). The angstrom exponent (α: 8.3 ± 2.6, where babs ≈ λ-α.) is consistent with that reported for humic-like substances (HULIS) from biomass burning emissions (BBE). The impact of BBE is also discernible from mass ratios of nss-K+/EC (0.2 – 1.4) and OC/EC (3.4 – 11.5). The mass fraction of WSOC (10 – 23 %) in PM2.5 and mass absorption efficiency of BrC (σabs-BrC: 0.5 – 1.2 m2 g-1) bring to focus the significance of brown carbon in atmospheric radiative forcing due to anthropogenic aerosols over the Indo-Gangetic Plain.
Road transport in India plays a vital role in our growing economy. Given an aggressive vehicle sales outlook through 2030, in order to maintain a balance between the energy demand, growing on-road emissions, and overall air quality in the cities, there is a need to implement and enforce Bharat-5 standards (equivalent of Euro-V) nationwide by 2015. Any delay in its implementation or even staggered implementation of the standards will result in a delayed response for improving air quality in the Indian cities.
In Delhi and its satellite cities, vehicle exhaust, industries, waste burning, and construction activities account for the bulk of the particulate (PM) pollution, which between 2008 and 2011, averaged 123±87 μg/m3 for PM2.5 and 208±137 μg/m3 for PM10, both exceeding the national annual ambient standards of 40 μg/m3 and 60 μg/m3, respectively.Amulti-sectoral emissions inventory for 2010 was modeled using the ATMoS dispersion model and local meteorology to estimate health impacts in terms of premature mortality and morbidity effects. For the observed PM levels in the city, the health impacts analysis estimates 7,350–16,200 premature deaths and 6.0 million asthma attacks per year. For six residential and industrial zones, we also modeled the sector contributions to ambient PM2.5 ranging 16–34% for vehicle exhaust, 20–27% for diffused sources, 14–21% for industries, 3–16% diesel generator sets, and 4–17% brick kilns. Finally, we present some thoughts on technological, institutional, and behavioral interventions that might help the Government of Delhi to develop an action plan encompassing multiple sources and include interventions to reduce health impacts in the future years.
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.
In Delhi, between 2008 and 2011, at seven monitoring stations, the daily average of particulates with diameter <2.5 μm (PM2.5) was 123 ± 87 μg m−3 and particulates with diameter <10 μm (PM10) was 208 ± 137 μg m−3. The bulk of the pollution is due to motorization, power generation, and construction activities. In this paper, we present a multi-pollutant emissions inventory for the National Capital Territory of Delhi, covering the main district and its satellite cities – Gurgaon, Noida, Faridabad, and Ghaziabad. For the base year 2010, we estimate emissions (to the nearest 000's) of 63,000 tons of PM2.5, 114,000 tons of PM10, 37,000 tons of sulfur dioxide, 376,000 tons of nitrogen oxides, 1.42 million tons of carbon monoxide, and 261,000 tons of volatile organic compounds. The inventory is further spatially disaggregated into 80 × 80 grids at 0.01° resolution for each of the contributing sectors, which include vehicle exhaust, road dust re-suspension, domestic cooking and heating, power plants, industries (including brick kilns), diesel generator sets and waste burning. The GIS based spatial inventory coupled with temporal resolution of 1 h, was utilized for chemical transport modeling using the ATMoS dispersion model. The modeled annual average PM2.5 concentrations were 122 ± 10 μg m−3 for South Delhi; 90 ± 20 μg m−3 for Gurgaon and Dwarka; 93 ± 26 μg m−3 for North-West Delhi; 93 ± 23 μg m−3 for North-East Delhi; 42 ± 10 μg m−3 for Greater Noida; 77 ± 11 μg m−3 for Faridabad industrial area. The results have been compared to measured ambient PM pollution to validate the emissions inventory.
This study presents data on the size characterization concentration of PM10, PM5.0, PM2.5 and PM1.0. These particulate concentrations were monitored from October-07 to March-09 indoors and outdoors of five roadside and five urban homes using Grimm aerosol spectrometer in Agra, India. Annual average concentrations of coarse particles (PM10) indoor and outdoor were 247 μg m−3 and 255 μg m−3 at roadside houses and 181 μg m−3 and 195 μg m−3 at urban houses. PM5.0 concentrations at roadside houses were 211 μg m−3 and 230 μg m−3 and at urban houses were 145 μg m−3 and 159 μg m−3. For fine particles (PM2.5) the annual mean concentrations were 161 μg m−3 and 160 μg m−3 at roadside houses and 109 μg m−3 and 123 μg m−3 at urban houses. PM1.0 concentrations at roadside houses were 111 μg m−3 and 112 μg m−3 while at urban houses they were 99 μg m−3 and 104 μg m−3. Monthly and seasonal variations of coarse and fine particulate matter have been studied at both the monitoring sites. Significant seasonal variations of particulate pollutants were obtained using the daily average particulate concentrations along with the inter particulate ratios. Particulate indoor/outdoor ratios and concentrations were also linked with meteorological conditions and indoor activities using occupant’s diary entries. The concentration of all sizes of particulate matter was found to be highest in winter season due to increase human activities and more space heating in indoors and due to low windspeed and high humidity in outdoors in comparison with other seasons. There was a strong correlation between indoor and outdoor particulate at both the sites. Health problems in occupants of the houses with higher concentrations of the fine particulate matter were more prominent. Household activities like cooking on stoves, indoor smoking and outdoor vehicular traffic, and garbage burning were found to be the major sources of particulate emissions indoor as well as outdoors.
The concentration of particulate matter (PM)10,
PM5.0, PM2.5, PM1.0, PM0.50, and PM0.25 was measured along
with heavy metals (Fe, Zn, Cu, Cd, Cr, Mn, Ni, and Pb)
collected from settling dust in the indoor–outdoor environment
of roadside and residentially located schools of Agra City, from
January 2008 to May 2009. PM indoor/outdoor ratios at the
roadside and residentially located schools were also determined
by the meteorological parameters like temperature, humidity,
and wind speed and air exchange rate. Metal geoaccumulation
index shows that the contamination of Fe, Cd, Cr, Ni, Pb, and
Mn was in abundant quantity in residential and roadside soil
dust of the schools. The enrichment factor was calculated using
Ca as a reference to the trace metal species to identify the
sources. Three factors in inside and three outside the classrooms
of roadside and residentially located schools were identified.
These factors reflected source soil dust, road dust, vehicle
emissions, industrial emissions, metal processes, and incineration
activities and their contributions were estimated using
principal component analysis. Measurements of such exposure
levels would be helpful in prevention of environmental risks to
schoolchildren at a global level for better and healthy mind of
children studying at schools.
The health and climate impacts of available household cooking options in developing countries vary sharply. Here, we analyze and compare these impacts (health; climate) and the potential co-benefits from the use of fuel and stove combinations. Our results indicate that health and climate impacts span 2 orders of magnitude among the technologies considered. Indoor air pollution is heavily impacted by combustion performance and ventilation; climate impacts are influenced by combustion performance and fuel properties including biomass renewability. Emission components not included in current carbon trading schemes, such as black carbon particles and carbon monoxide, can contribute a large proportion of the total climate impact. Multiple ‘improved’ stove options analyzed in this paper yield roughly equivalent climate benefits but have different impacts on indoor air pollution. Improvements to biomass stoves can improve indoor air quality, which nonetheless remains significantly higher than for stoves that use liquid or gaseous hydrocarbons. LPG- and kerosene-fueled stoves have unrivaled air quality benefits and their climate impacts are also lower than all but the cleanest stoves using renewable biomass.
The global burden of disease due to air pollution is concentrated in the rapidly developing counties of Asia, but a recent
meta-analysis found that relatively few studies on short-term exposure to air pollution and mortality have been performed
in these countries, including India. Local evidence on the effects of short-term exposures to air pollutants on mortality
and cardio-respiratory morbidity in Asia would reduce the uncertainties in current impact estimations and facilitate effective
public policy responses to a deteriorating air pollution situation in South Asia. Here, we report the results from one of
the first of such studies in metropolitan Chennai, India, conducted as part of a co-ordinated multi-city time-series initiative
in India aimed at estimating the effect of short-term exposure to particulate matter ≤10 μm in aerodynamic diameter (PM10) on all-cause mortality. The studies in Indian cities (Chennai, Delhi and Ludhiana) were part of a larger multi-city effort
in Asia, co-ordinated by The Health Effects Institute (Boston, MA, USA) under their program for Public health and Air Pollution
in Asia (PAPA). An important study output included the development of methodological refinements to overcome the limitations
of routinely collected data in terms of missing measurements, small footprints of air pollution monitors and incomplete address
information on death records. We used data on ambient air quality and all-cause mortality collected over the period 2002–2004.
Exposures and health outcomes were disaggregated at the level of individual city zones and subsequently used in quasi-Poisson
generalized additive models with smooth functions of time, temperature and relative humidity. Our model estimated a 0.44%
(95% confidence interval 0.17–0.71) increase in mortality per 10 μg/m3 increase in daily average concentrations of PM10, which is comparable to estimates from other PAPA cities and previous studies in North America and Europe. The results from
PAPA studies in India, while preliminary, serve to strengthen the local evidence base for air pollution-related health effects
that is imminently needed for better air quality management, while adding valuable information from India to the global repository
of evidence.
Abstract Indian megacities are among the most polluted in the world. Air concentrations of a number of air pollutants are much higher than levels recommended by the World Health Organization. In this paper, we focus on Mumbai and Delhi to characterize salient issues in health risks from particulate air (PM10) pollution in Indian cities. We perform a synthesis of the literature for all elements of the causal chain of health risks-sources, exposure, and health effects-and provide estimates of source strengths, exposure levels, and health risks from air pollution in Indian cities. We also analyze the factors that lead to uncertainty in these quantities and provide an overall assessment of the state of scientific knowledge on air pollution in urban India.
A key policy challenge in Indian megacities is to curb high concentrations of PM2.5 and mitigate associated adverse health impacts. Using the Greenhouse Gases and Air Pollution Interactions and Synergies (GAINS) model we carry out an integrated analysis of the air quality regulations across different sectors for the city of Delhi. Our findings show that PM2.5 concentrations for Delhi will not reach the recommended national ambient air quality standards (NAAQS) even by 2030 under the current policies scenario. Adopting advanced control technologies reduces PM2.5 concentrations by about 60% and all-cause mortality by half in 2030. Climate change mitigation policies significantly reduce greenhouse gases, but have a modest impact on reducing PM2.5 concentrations. Stringent policies to control the net flow of air pollution from trans-boundary sources will play a crucial role in reducing pollution levels in Delhi city. Achieving NAAQS requires a stringent policy portfolio that combines advanced control technologies with a switch to cleaner fuels and the control of trans-boundary pollution.
This paper provides an international comparative perspective on non-residential, off-street parking policy in 14 large metropolitan areas in East, Southeast and South Asia. These are regions where parking challenges are widespread and acute. It utilizes a new typology which groups parking policy approaches into ‘conventional’, ‘parking management’ and ‘market-oriented’ categories. Several distinct parking policy orientations are identified among the cities studied. Given their characteristics (most have relatively low car-ownership, high-density development and high usage of public transport) Asian cities might be expected to have off-street parking policies akin to those of many older areas in western cities. Yet, most of the Southeast and South Asian cities studied have parking policies that are surprisingly conventional and promoting of automobile-dependence. It is less surprising that a number of cities, mostly in East Asia, do not have such an auto-centric conventional approach. However, it is a surprise that their parking policies still involve minimum parking requirements and have generally not adopted the most common alternative to the conventional approach (parking management).
We draw two conclusions from this study: 1) The impact of particulate matter on total nontrauma deaths in Delhi, India, is smaller than effects found in the US. This is due to the fact that in Delhi a greater proportion of deaths occurs at younger ages and from causes not associated with air pollution than is the case in the US. Estimating the number of nontrauma deaths associated with air pollution. For a city in a developing country on the basis of US studies may therefore yield misleading results. 2) The impacts of air pollution on deaths by age-group may be very different in developing countries than in the US, where peak effects occur among people aged 65 and older. In Delhi, peak effects occur between the ages of 15 and 44, implying that a death associated with air pollution causes more life-years to be lost. We recognize that our results are based on data representing only 25% of the deaths that occurred in Delhi during the study period. When data for the remainder of the city become available, this study should be replicated to confirm our findings.
China is taking major steps to improve Beijing's air quality for the 2008 Olympic Games. However, concentrations of fine particulate matter and ozone in Beijing often exceed healthful levels in the summertime. Based on the US EPA's Models-3/CMAQ model simulation over the Beijing region, we estimate that about 34% of PM2.5 on average and 35–60% of ozone during high ozone episodes at the Olympic Stadium site can be attributed to sources outside Beijing. Neighboring Hebei and Shandong Provinces and the Tianjin Municipality all exert significant influence on Beijing's air quality. During sustained wind flow from the south, Hebei Province can contribute 50–70% of Beijing's PM2.5 concentrations and 20–30% of ozone. Controlling only local sources in Beijing will not be sufficient to attain the air quality goal set for the Beijing Olympics. There is an urgent need for regional air quality management studies and new emission control strategies to ensure that the air quality goals for 2008 are met.
This paper presents a cost–benefit analysis of the Stockholm congestion charging system, based on the observed rather than on the model-forecasted data. The most important data sources are travel time and traffic flow measurements made in the year before the charges were introduced (during April 2005) and during the first spring with the charges (during April 2006, 4 months after the charges were introduced). Using matrix calibration, effects on the non-observed link flows and travel times are extrapolated, enabling us to calculate the social value of changes in travel times and travel costs. Impacts on traffic safety and emissions are calculated using standard Swedish CBA relationships. The system is shown to yield a significant social surplus, well enough to cover both investment and operating costs, provided that it is kept for a reasonable lifetime: investment and startup costs are “recovered” in terms of social benefits in around 4 years.
The winters in megacity Delhi are harsh, smoggy, foggy, and highly polluted. The pollution levels are approximately two to three times those monitored in the summer months, and the severity is felt not only in the health department but also in the transportation department, with regular delays at airport operations and series of minor and major accidents across the road corridors. The impacts felt across the city are both manmade (due to the fuel burning) and natural (due to the meteorological setting), and it is hard to distinguish their respective proportions. Over the last decade, the city has gained from timely interventions to control pollution, and yet, the pollution levels are as bad as the previous year, especially for the fine particulates, the most harmful of the criteria pollutants, with a daily 2009 average of 80 to 100 μg/m(3). In this paper, the role of meteorology is studied using a Lagrangian model called Atmospheric Transport Modeling System in tracer mode to better understand the seasonality of pollution in Delhi. A clear conclusion is that irrespective of constant emissions over each month, the estimated tracer concentrations are invariably 40% to 80% higher in the winter months (November, December, and January) and 10% to 60% lower in the summer months (May, June, and July), when compared to annual average for that year. Along with monitoring and source apportionment studies, this paper presents a way to communicate complex physical characteristics of atmospheric modeling in simplistic manner and to further elaborate linkages between local meteorology and pollution.
Air quality was a vital concern for the Beijing Olympic Games in 2008. To strictly control air pollutant emissions and ensure good air quality for the Games, Beijing municipal government announced an "Air Quality Guarantee Plan for the 29th Olympics in Beijing". In order to evaluate the effectiveness of the guarantee plan, this study analyzed the air pollutant emission reductions during the 29th Olympiad in Beijing. In June 2008, daily emissions of SO(2), NO(X), PM(10), and NMVOC in Beijing were 103.9 t, 428.5 t, 362.7 t, and 890.0 t, respectively. During the Olympic Games, the daily emissions of SO(2), NO(X), PM(10), and NMVOC in Beijing were reduced to 61.6 t, 229.1 t, 164.3 t, and 381.8 t -41%, 47%, 55%, and 57% lower than June 2008 emission levels. Closing facilities producing construction materials reduced the sector's SO(2) emissions by 85%. Emission control measures for mobile sources, including high-emitting vehicle restrictions, government vehicle use controls, and alternate day driving rules for Beijing's 3.3 million private cars, reduced mobile source NO(X) and NMVOC by 46% and 57%, respectively. Prohibitions on building construction reduced the sector's PM(10) emissions by approximately 90% or total PM(10) by 35%. NMVOC reductions came mainly from mobile source and fugitive emission reductions. Based on the emission inventories developed in this study, the CMAQ model was used to simulate Beijing's ambient air quality during the Olympic Games. The model results accurately reflect the environmental monitoring data providing evidence that the emission inventories in this study are reasonably accurate and quantitatively reflect the emission changes attributable to air pollution control measures taken during the 29th Olympic Games in 2008.
Severe air pollution is threatening human health and the gains of economic growth in Asia's largest cities. This report aims to assist policy makers in the design and implementation of policies, monitoring and management tools to restore air quality in Mumbai (bombay), India's financial and commercial capital.