Process analysis of a regional air pollution episode over Pearl River Delta Region, China, using the MM5-CMAQ model

Abstract

This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October [10][11][12] 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD. MM5 shows reasonable performance for major meteorological variables (i.e., temperature, relative humidity, wind direction) with normalized mean biases (NMB) of 4.5-38.8% and for their time series. CMAQ can capture one peak of all air pollutant concentrations on October 11, but misses other peaks. The CMAQ model systematically underpredicts the mass concentrations of all air pollutants. Compared with chemical observations, SO 2 and O 3 are predicted well with a correlation coefficient of 0.70 and 0.65. PM 2.5 and NO are significantly underpredicted with an NMB of 43% and 90%, respectively. The process analysis results show that the emission, dry deposition, horizontal transport, and vertical transport are four main processes affecting air pollutants. The contributions of each physical process are different for the various pollutants. The most important process for PM 10 is dry deposition, and for NO x it is transport. The contributions of horizontal and vertical transport processes vary during the period, but these two processes mostly contribute to the removal of air pollutants at Guangzhou city, whose emissions are high. For this high-pressure case, the contributions of the various processes show high correlations in cities with the similar geographical attributes. According to the statistical results, cities in the PRD region are divided into four groups with different features. The contributions from local and nonlocal emission sources are discussed in different groups.Implications: The characteristics of aerosol pollution episodes are intensively studied in this work using the high-resolution modeling system MM5/SMOKE/CMAQ, with special efforts on examining the contributions of different physical and chemical processes to air concentrations for each city over the PRD region by a process analysis method, so as to provide a scientific basis for understanding the formation mechanism of regional aerosol pollution under the high-pressure system over PRD.

City breathability in medium density urban-like geometries evaluated through the pollutant transport rate and the net escape velocity

“…At this scale, due to pollutant accumulation effect, urban air quality depends upon their neighbourhoods and city-scale characteristics [15,16]. Meso-scale modelling is usually employed to investigate regional pollutant transport in which urban areas are treated as roughness elements thus providing boundary conditions for smaller scale studies [17]. Within this framework flow and pollutant dispersion from street-scale to neighbourhood-scale have been widely investigated often coupling wind tunnel/field experiments with computational fluid dynamics (CFD) simulations [5e14,19e23,25e39,43e45].…”

Accessing the Impact of Sea-Salt Emissions on Aerosol Chemical Formation and Deposition over Pearl River Delta, China

“…The emission inventories of point, area and mobile sources were from the work of Feng (2006). It was proved to be suitable for air quality simulations over PRD (Chen et al, 2009;Fan et al, 2013b). These emission inventories were then processed by the SMOKE model.…”

Spatial Correlation of Industrial NOx Emission in China’s 2 + 26 Policy Region: Based on Social Network Analysis

“…Although traditional econometrics could be applied to analyze the spatial association of regional pollution, in view of the possible complex, bidirectional and multithreaded network structure of the associated pollution transport within the Studies have been conducted on spatial correlation of air pollution from different perspectives. Some scholars focused on technological analysis, as employing air quality models for numerical simulation [10,11], which supported the cross-regional transmission of air pollution between different administrative units [12]. Qin et al [13] simulated pollution caused by PM 2.5 in the Pearl River Basin, finding cross-boundary transmission a main reason for the pollution in autumn.…”