Abstract
Abstract. The Pearl River Delta (PRD) of China, which has a population of more than 58 million people, is one of the largest agglomerations of cities in the world and had severe PM2.5 pollution at the beginning of this century. Due to the implementation of strong pollution control in recent decades, PM2.5 in the PRD has continuously decreased to relatively lower levels in China. To comprehensively understand the current PM2.5 sources in the PRD to support future air pollution control strategies in similar regions, we performed regional-scale PM2.5 field observations coupled with a state-of-the-art source apportionment model at six sites in four seasons in 2015. The regional annual average PM2.5 concentration based on the 4-month sampling was determined to be 37 µg m−3, which is still more than 3 times the WHO standard, with organic matter (36.9 %) and SO42- (23.6 %) as the most abundant species. A novel multilinear engine (ME-2) model was first applied to a comprehensive PM2.5 chemical dataset to perform source apportionment with predetermined constraints, producing more environmentally meaningful results compared to those obtained using traditional positive matrix factorization (PMF) modeling. The regional annual average PM2.5 source structure in the PRD was retrieved to be secondary sulfate (21 %), vehicle emissions (14 %), industrial emissions (13 %), secondary nitrate (11 %), biomass burning (11 %), secondary organic aerosol (SOA, 7 %), coal burning (6 %), fugitive dust (5 %), ship emissions (3 %) and aged sea salt (2 %). Analyzing the spatial distribution of PM2.5 sources under different weather conditions clearly identified the central PRD area as the key emission area for SO2, NOx, coal burning, biomass burning, industrial emissions and vehicle emissions. It was further estimated that under the polluted northerly air flow in winter, local emissions in the central PRD area accounted for approximately 45 % of the total PM2.5, with secondary nitrate and biomass burning being most abundant; in contrast, the regional transport from outside the PRD accounted for more than half of PM2.5, with secondary sulfate representing the most abundant transported species.
Highlights
With China’s rapid economic growth and urbanization, air pollution has become a serious problem in recent decades
The secondary sulfate-rich and secondary nitrate-rich factors of positive matrix factorization (PMF) had certain species from primary particulates, such as EC, Zn, Al, K and Fe, among which EC had obvious percentage explained variation (EV) values, i.e., the percent of a species apportioned to the factor, of 18.7 % and 9.7 %; the EV value of OM in the sea salt factor had a high value of 6.4 %, and OM accounted for 37 % of the total mass of this factor; the EV value of SO24− in the fugitive dust factor had a high value of 8.6 %, and the SO24− concentration accounted for 26 % of the total mass of this factor
The average PM2.5 concentration at DP was as high as 28 μg m−3, indicating that the Pearl River Delta (PRD) had a large amount of air pollution transported from outside this region
Summary
With China’s rapid economic growth and urbanization, air pollution has become a serious problem in recent decades. The Chinese government has attached great importance to improving air quality and issued the “Air Pollution Prevention and Control Action Plan” in September 2013, clearly requiring the concentration levels of fine particulate matter in a few key regions, including the Pearl River Delta (PRD), to drop by 2017 from 15 % to 25 % of their values in 2012. The receptor model method (commonly, positive matrix factorization, PMF) in the PRD was applied to perform the source apportionment of PM2.5, which was carried out in several major cities, including Guangzhou (Gao et al, 2013; Liu et al, 2014; Wang et al, 2016), Shenzhen The novel ME-2 model via the SoFi was applied to a comprehensive chemical dataset (including elemental carbon (EC), organic mass (OM), inorganic ions and metal elements) to identify the sources of bulk PM2.5 on the regional scale of the PRD; the spatial locations of the sources were systematically explored using the analysis of weather conditions
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