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Remote Sens. 2017, 9(8), 817; doi:10.3390/rs9080817

Estimation of Satellite-Based SO42 and NH4+ Composition of Ambient Fine Particulate Matter over China Using Chemical Transport Model

1
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2
University of the Chinese Academy of Sciences, Beijing 100049, China
3
School of Computer and Information Engineering, Henan University, Kaifeng 475004, China
*
Authors to whom correspondence should be addressed.
Received: 30 June 2017 / Revised: 4 August 2017 / Accepted: 7 August 2017 / Published: 9 August 2017
(This article belongs to the Special Issue Aerosol Remote Sensing)
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Abstract

Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1 × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of −35.9%, NME of 48.2%, ARB_50% of 53.68% for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42 and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42: −0.61%; NH4+: −0.21%), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004–2007 and 2008–2011, followed by a negative trend over the period 2012–2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO2) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population’s exposure to certain chemical components. View Full-Text
Keywords: PM2.5 chemical components; sulfate; ammonium; satellite-estimated; chemical transport model PM2.5 chemical components; sulfate; ammonium; satellite-estimated; chemical transport model
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Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W. Estimation of Satellite-Based SO42 and NH4+ Composition of Ambient Fine Particulate Matter over China Using Chemical Transport Model. Remote Sens. 2017, 9, 817.

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