EGU General Assembly 2023
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the Creative Commons Attribution 4.0 License.

Emission Inventories for 76 Cities In India for Clean Air Strategies

Pratima Singh, Anirban Banerjee, Udhaya Kumar, Amishi Tiwari, Hrishikesh Gautam, and Sameer Mishra
Pratima Singh et al.
  • Center for Study of Science, Technology and Policy (CSTEP), Center for Air Pollution Studies (CAPS), India (

Understanding polluting sources, for improving Air Quality (AQ) levels at the city/airshed level is required to solve the air pollution challenge. Scientific evidence like Emission Inventory (EI); identification of efficient technologies; implementation roadmap; and cost and resources required, are needed to develop clean air strategies.

This study considered 76 Non-Attainment (NA) cities in India, for developing EI at an airshed level. Various polluting sectors and activities were identified. Data from various sources and ground surveys were used to generate evidence. The EI was developed for the base year 2019 for 4 pollutants– Particulate Matter (PM10 and PM2.5), Sulphur dioxide (SO2), and oxides of Nitrogen (NOX). Based on the city EI, sector-specific technologies and control measures were identified and prioritized using Techno-Economic Assessment (TEA) and the emission reduction potential. Gap Analysis was conducted to identify sectoral targets for reducing emissions.

The Emission load varied for types of cities (tier I, II, or III) based on landscape, and anthropogenic activities. It was observed that city-level PM2.5 emissions from three sectors - transportation (tailpipe: 30%-50%; road dust: 8%-17%); domestic (14%-30%); and Industries (6%-29%) were high for all the cities. In a few cities, heavy industries within the city boundary dominated the industrial share in the city’s total PM2.5 emission load (34%-88%). Hence, heavy industries were excluded from the analysis to better understand the city's emission level. The study helped to understand the city vs airshed emission load. In 46% of the cities, it was found that the airshed emission load (excluding city emission) was high due to the presence of heavy industries.

Using TEA, the study estimated the associated cost of the identified control measures feasible for implementation at the city level. The required cost was based on the existing gaps in the current infrastructure needs of the city. In tier 2 cities, the transportation sector required heavy infrastructure. Capital investment, for transportation, was estimated between INR 300 – 800 Cr on measures such as a) improving public transportation, b) LNG for freight transport, and c) replacing older vehicles. However, in tier 3 cities increasing LPG connections and strategies to reduce solid fuel usage (advanced chullah’s) were found to be critical interventions, which required investment of less than 50cr. The study also carried out emission reduction scenarios till 2030. In comparison to the business-as-usual scenario, under a high emission reduction scenario, PM2.5 emission reduction for tier 2 cities were up to 45%, and for tier 3 cities up to 54%. The study found that developing clean air strategies need to adopt an airshed approach.

How to cite: Singh, P., Banerjee, A., Kumar, U., Tiwari, A., Gautam, H., and Mishra, S.: Emission Inventories for 76 Cities In India for Clean Air Strategies, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6701,, 2023.