Air pollution knowledge assessments (APnA) for 20 Indian cities
| Autor: | Puja Jawahar, Sarath K. Guttikunda, K.A. Nishadh |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Atmospheric Science
education.field_of_study 010504 meteorology & atmospheric sciences Airshed business.industry Aviation Geography Planning and Development Environmental resource management Population Air pollution 010501 environmental sciences Environmental Science (miscellaneous) medicine.disease_cause 01 natural sciences Urban Studies Farm water medicine Environmental science Diesel generator business education Baseline (configuration management) Air quality index 0105 earth and related environmental sciences |
| Zdroj: | Urban Climate. 27:124-141 |
| ISSN: | 2212-0955 |
| DOI: | 10.1016/j.uclim.2018.11.005 |
| Popis: | Delhi, with a population of 22 million (1.6% of national total) is one of the most polluted capital cities in the world. Nearly 50% of the published literature in India focus on air pollution in Delhi. However, air pollution impacts are not limited only to the capital city. Yet, there is little information and attempt to quantify these impacts for Tier 1 and 2 cities, even though they account for >30% of India's population. To remedy this vacuum of information, the Air Pollution knowledge Assessments (APnA) city program deliberately focuses on 20 Indian cities, other than Delhi. We established baseline multi-pollutant high-resolution emissions inventory, after collating information from multiple resources detailed in this paper, which was used to estimate spatial concentrations of key pollutants across city's urban airshed using WRF-CAMx chemical transport modeling system. The inventory includes anthropogenic sources, such as transport (road, rail, ship, and aviation), large scale power generation (from coal, diesel, and gas power plants), small scale power generation (from diesel generator sets for household use, commercial use, and agricultural water pumping), small and medium scale industries, dust (road resuspension and construction), domestic (cooking, heating, and lighting), open waste burning, and open fires and non-anthropogenic sources, such as sea salt, dust storms, biogenic, and lightning. The emissions inventory is currently in use for 3-day advance air quality forecasting for public release on an on-going basis. Using meteorological parameters and big data like gridded speed maps from google, the emissions inventory is dynamically updated. The results from this research will be valuable to local and national policy makers - especially the information on source contributions to air pollution. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect