Hao Guo

TL;DR: It is found that emission reductions in 2014 and 2015 effectively reduced PM2.5 concentrations by 23.9 and 43.5 μg/m3, respectively, but was partially counteracted by unfavorable meteorology, highlighting the importance of appropriate joint reduction of NOx and VOCs to simultaneously decrease O3 and PM 2.5 for higher air quality.

TL;DR: In this paper, 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, offroad, agriculture, open burning and dust) to fine particulate matter (PM 2.5 ) and its components including primary PM (PPM) and secondary inorganic aerosol (SIA) in Delhi and three surrounding cities, Chandigarh, Lucknow and Jaipur in 2015

TL;DR: In this paper, a year-long simulation was carried out in India to provide detailed information of spatial and temporal distribution of gas species and particulate matter (PM) and its components in 2015 were predicted using Weather Research Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models.

TL;DR: One year‐long concentrations of criteria air pollutants in Beijing were analyzed and Pearson correlation coefficients show that most pollutants are temporally correlated in Beijing except for O3, which can support the research on formation, transport and human health effects of air pollutants.

TL;DR: In this article, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model was used to quantify contributions from nine regions to PM 2.5 in the Sichuan Basin.