Literature DB >> 28830016

Source apportionment of PM2.5 in North India using source-oriented air quality models.

Hao Guo1, Sri Harsha Kota2, Shovan Kumar Sahu2, Jianlin Hu3, Qi Ying4, Aifang Gao5, Hongliang Zhang6.   

Abstract

In recent years, severe pollution events were observed frequently in India especially at its capital, New Delhi. However, limited studies have been conducted to understand the sources to high pollutant concentrations for designing effective control strategies. In this work, source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with Emissions Database for Global Atmospheric Research (EDGAR) were applied to quantify the contributions of eight source types (energy, industry, residential, on-road, off-road, agriculture, open burning and dust) to fine particulate matter (PM2.5) and its components including primary PM (PPM) and secondary inorganic aerosol (SIA) i.e. sulfate, nitrate and ammonium ions, in Delhi and three surrounding cities, Chandigarh, Lucknow and Jaipur in 2015. PPM mass is dominated by industry and residential activities (>60%). Energy (∼39%) and industry (∼45%) sectors contribute significantly to PPM at south of Delhi, which reach a maximum of 200 μg/m3 during winter. Unlike PPM, SIA concentrations from different sources are more heterogeneous. High SIA concentrations (∼25 μg/m3) at south Delhi and central Uttar Pradesh were mainly attributed to energy, industry and residential sectors. Agriculture is more important for SIA than PPM and contributions of on-road and open burning to SIA are also higher than to PPM. Residential sector contributes highest to total PM2.5 (∼80 μg/m3), followed by industry (∼70 μg/m3) in North India. Energy and agriculture contribute ∼25 μg/m3 and ∼16 μg/m3 to total PM2.5, while SOA contributes <5 μg/m3. In Delhi, industry and residential activities contribute to 80% of total PM2.5.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  CMAQ; Delhi; India; PM(2.5); Source apportionment

Mesh:

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Year:  2017        PMID: 28830016     DOI: 10.1016/j.envpol.2017.08.016

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  10 in total

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2.  Meteorology-normalized variations of air quality during the COVID-19 lockdown in three Chinese megacities.

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3.  Exceedances and trends of particulate matter (PM2.5) in five Indian megacities.

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4.  Spatio-temporal variation and sensitivity analysis of aerosol particulate matter during the COVID-19 phase-wise lockdowns in Indian cities.

Authors: 
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Journal:  Air Qual Atmos Health       Date:  2020-08-12       Impact factor: 3.763

6.  Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world.

Authors:  Mohammad Sarmadi; Sajjad Rahimi; Mina Rezaei; Daryoush Sanaei; Mostafa Dianatinasab
Journal:  Environ Sci Eur       Date:  2021-12-05       Impact factor: 5.893

7.  Respiratory disease burden in India: Indian chest society SWORD survey.

Authors:  Virendra Singh; Bharat Bhushan Sharma
Journal:  Lung India       Date:  2018 Nov-Dec

8.  COVID-19 and its impact on environment: Improved pollution levels during the lockdown period - A case from Ahmedabad, India.

Authors:  Mohammad Adil Aman; Mohd Sadiq Salman; Ali P Yunus
Journal:  Remote Sens Appl       Date:  2020-08-25

9.  Impact of COVID-19 lockdown on NO2, O3, PM2.5 and PM10 concentrations and assessing air quality changes in Baghdad, Iraq.

Authors:  Bassim Mohammed Hashim; Saadi K Al-Naseri; Ali Al-Maliki; Nadhir Al-Ansari
Journal:  Sci Total Environ       Date:  2020-09-01       Impact factor: 7.963

10.  Short-term exposure to ambient air quality of the most polluted Indian cities due to lockdown amid SARS-CoV-2.

Authors:  Susanta Mahato; Krishna Gopal Ghosh
Journal:  Environ Res       Date:  2020-07-02       Impact factor: 6.498

  10 in total

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