Bottom-up approach to estimate the present and future air emissions under different policy scenarios in Tier-2 non-attainment city in India

Abstract

Air quality degradation in Tier 2 non-attainment Indian cities is a rising concern as the air pollution level is alarmingly increasing, similar to metropolitan cities. Efficient urban air quality management measures in Tier 2 non-attainment cities require a comprehensive emission inventory to support the air pollution abatement strategies. The present study developed a detailed emission inventory of the primary criteria pollutants (PM10, PM2.5, SO2, NOx, CO) and NMVOCs accounting for all the urban anthropogenic sources. The bottom-up emission estimate technique was applied to the Vijayawada metropolitan region, one of India's most polluted tier 2 cities. The emission load of PM10, PM2.5, SO2, NOx, CO, and NMVOCs over Vijayawada were estimated to be 5.65 Gg, 2.13 Gg, 1.38 Gg, 8.91 Gg, 17.17 Gg, and 2.33 Gg respectively in 2021. Road and construction dust accounted for 74% of PM10 and 45% of PM2.5, whereas active motorized vehicular activities significantly contributed to CO (78%) and NOx emissions (69%), and the industrial sector accounted for 96% of the overall SO2 emission load across Vijayawada. Further, various strategies were tested to project the emission load of PM10, PM2.5, SO2, and NOx under the Business as Usual (BAU) and Alternative (ALT) scenarios for 2025 and 2030, respectively, to evaluate the increased and reduced emission potential. Under the BAU scenarios, the key factors for future projections of sectoral activity data are the population and economic growth of Vijayawada. The BAU scenarios indicated an overall emission increase of 12% and 36% in PM10, 4% and 22% in PM2.5, and 5% and 11% in SO2, whereas the overall NOx emissions are estimated to be reduced by 13% and 14% in 2025 and 2030 respectively. Introducing the BSVI emission standards and phasing out older vehicles were the key scenarios for reducing NOx emissions under BAU scenarios. The strategies tested under the ALT scenarios considered the multi-sectoral control actions declared or proposed by national and state governments owing to the potential to reduce air pollution in the study area. Advanced control techniques, coupled with shifting towards cleaner fuels, may show the potential to reduce the overall PM10 emissions by 13% and 15%, PM2.5 by 16% and 23%, SO2 by 24% and 48%, and NOx emission by 20% and 32% in 2025 and 2030 respectively, under ALT scenarios. The study findings provide a comprehensive emission database encompassing pollutants, sources, and area-specific quantitative information for Tier 2 non-attainment cities. The research outcome will also be used as the guiding tool by the scientific community, air quality researchers, and policymakers for designing practical and feasible air pollution abatement strategies and management plans to provide clean air for present and future generations at the city level. Keywords: Emission Inventory, Scenarios development, Urban anthropogenic sources, Mitigation measures, Non-attainment cities