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

Abstract: 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. [Copyright &y& Elsevier]

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

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