@article{66bda96411664cd390be43d1887de3c6,
title = "Implications of Implementing Promulgated and Prospective Emission Regulations on Air Quality and Health in India during 2030",
abstract = "To improve ambient air quality, India has laid out strict action plans to reduce the increment in emissions over regional to urban scale by the year 2030. This study evaluates policy-induced improvement in air quality and associated health benefits achievable due to reduction in PM2.5 exposure under the adoption of promulgated (S2) and ambitious prospective regulations (S3) with respect to the scenario for Business As Usual (BAU) in 2030. The Weather Research and Forecasting model coupled with online chemistry (WRF-Chem) has been used to simulate ambient PM2.5 exposure to the population under BAU, S2 and S3 emission scenarios. Results show 15% (9 µg m–3) and 49% (32 µg m–3) decreases in all India ambient PM2.5 exposure under S2 and S3 scenarios, respectively, with respect to the BAU scenario. Throughout India, under the S2 and S3 scenarios, 38% and 62% of states would meet the annual National Ambient Air Quality Standard (NAAQS) of 40 µg m–3, respectively. We projected that the S2 emission regulation scenario would prevent 274,000 (8.3%) premature mortalities and improve mean life expectancy by about 0.6 ± 0.2 years in 2030 relative to the BAU scenario. On the other hand, pursuing an ambitious emission scenario, S3 would prevent 775,000 (~23.6%) premature mortality burden and improve mean life expectancy by about 1.9 ± 0.7 years in 2030. Results indicate that ambitious actions beyond the ambitious prospective regulations are vital to gain significant health benefits.",
keywords = "Air quality, Emission scenarios, Particulate matter, Premature mortality, WRF-Chem",
author = "Sreyashi Debnath and Karumuri, {Rama Krishna} and Gaurav Govardhan and Rajmal Jat and Himadri Saini and Akash Vispute and Kulkarni, {Santosh H.} and Chinmay Jena and Rajesh Kumar and Chate, {D. M.} and Ghude, {Sachin D.}",
note = "Funding Information: We thank the Director, IITM, for his encouragement in carrying out the research work. We acknowledge the use of the WRF-Chem preprocessor tools provided by the Atmospheric Chemistry Observations and Modeling Laboratory (ACOM) of NCAR. This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement No. 1852977. The WRF-Chem model simulation was carried out on the HPC System {\textquoteleft}Aditya{\textquoteright} at IITM, India. We would like to thank Prof. Michael Brauer, Institute for Health Metrics and Evaluation, University of Washington for his kind assistance in providing the updated data for the calculation of Relative Risk used in this study (Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Particulate Matter Risk Curves. Seattle, United States of America: Institute for Health Metrics and Evaluation (IHME), 2021, https://doi.org/10.6069/KHWH-2703). Supplementary data contains model mean data and all results for the Indian state per scenario. This work was supported by the National Supercomputing Mission (NSM) program grant to the authors at C-DAC (SK and DMC) and we are grateful to the Executive Director and the Director General of C-DAC. The authors would sincerely thank the anonymous reviewers and the editor of the journal for their insightful comments and valuable suggestions. Publisher Copyright: {\textcopyright} The Author's institution.",
year = "2022",
month = oct,
doi = "10.4209/aaqr.220112",
language = "English (US)",
volume = "22",
journal = "Aerosol and Air Quality Research",
issn = "1680-8584",
publisher = "AAGR Aerosol and Air Quality Research",
number = "10",
}