Source attribution for mercury deposition with an updated atmospheric mercury emission inventory in the Pearl River Delta Region, China

doi:10.1007/s11783-019-1087-6

Front. Environ. Sci. Eng.

2019, Vol. 13

Issue (1) : 2 https://doi.org/10.1007/s11783-019-1087-6

RESEARCH ARTICLE

Source attribution for mercury deposition with an updated atmospheric mercury emission inventory in the Pearl River Delta Region, China

Jiajun Liu¹, Long Wang¹(

), Yun Zhu¹(

), Che-Jen Lin², Carey Jang³, Shuxiao Wang⁴, Jia Xing⁴, Bin Yu⁵, Hui Xu¹, Yuzhou Pan¹

¹. Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
². Department of Civil and Environmental Engineering, Lamar University, Beaumont, TX 77710, USA
³. US EPA, Office of Air Quality Planning & Standards, Res Triangle Park, NC 27711, USA
⁴. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
⁵. Guangzhou Environmental Monitoring Centre, Guangzhou 510308, China

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Abstract

Estimated anthropogenic Hg emission was 11.9 tons in Pearl River Delta for 2014.

Quantifying contributions of emission sources helps to provide control strategies.

More attentions should be paid to Hg deposition around the large point sources.

Power plant, industrial source and waste incinerator were priorities for control.

A coordinated regional Hg emission control was important for controlling pollution.

We used CMAQ-Hg to simulate mercury pollution and identify main sources in the Pearl River Delta (PRD) with updated local emission inventory and latest regional and global emissions. The total anthropogenic mercury emissions in the PRD for 2014 were 11,939.6 kg. Power plants and industrial boilers were dominant sectors, responsible for 29.4 and 22.7%. We first compared model predictions and observations and the results showed a good performance. Then five scenarios with power plants (PP), municipal solid waste incineration (MSWI), industrial point sources (IP), natural sources (NAT), and boundary conditions (BCs) zeroed out separately were simulated and compared with the base case. BCs was responsible for over 30% of annual average mercury concentration and total deposition while NAT contributed around 15%. Among the anthropogenic sources, IP (22.9%) was dominant with a contribution over 20.0% and PP (18.9%) and MSWI (11.2%) ranked second and third. Results also showed that power plants were the most important emission sources in the central PRD, where the ultra-low emission for thermal power units need to be strengthened. In the northern and western PRD, cement and metal productions were priorities for mercury control. The fast growth of municipal solid waste incineration were also a key factor in the core areas. In addition, a coordinated regional mercury emission control was important for effectively controlling pollution. In the future, mercury emissions will decrease as control measures are strengthened, more attention should be paid to mercury deposition around the large point sources as high levels of pollution are observed.

Keywords Emission inventory Mercury deposition Pearl River Delta (PRD) Source attribution Control strategy

Corresponding Author(s): Long Wang,Yun Zhu

Online First Date: 03 December 2018 Issue Date: 21 December 2018

Cite this article:

Jiajun Liu,Long Wang,Yun Zhu, et al. Source attribution for mercury deposition with an updated atmospheric mercury emission inventory in the Pearl River Delta Region, China[J]. Front. Environ. Sci. Eng., 2019, 13(1): 2.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-019-1087-6
https://academic.hep.com.cn/fese/EN/Y2019/V13/I1/2

Tab.1 Emission factors and Hg speciation of anthropogenic sources

Fig.1 (a) Proportion of different anthropogenic Hg emissions sources, (b) Contribution of different mercury species in various sectors.

Fig.2 Gridded Hg emissions from (a) power plants, (b) industrial boilers, (c) municipal solid waste incineration.

Tab.2 Mercury emission inventory in PRD for 2014

Tab.3 Validation of meteorology results (January, April, July and October in 2014)

Fig.3 Simulated annual average concentration of (a) GEM, (b) GOM and (c) PBM; annual dry deposition of (d) GEM, (e) GOM and (f) PBM; and annual wet deposition of (g) GEM, (h) GOM and (i) PBM in PRD for 2014.

Station	Sampling period	Observation	Model	Relative bias	Reference
Station	Sampling period	TGM/GEM ( $ng/m 3$ )	TGM/GEM ( $ng/m 3$ )	Relative bias	Reference
Wangqingsha, Guangdong	Dec-08	2.9	3.20	10.3%	(^{Wang et al., 2014})
Guangzhou, rural site	Nov-08-Dec-08	2.94	3.42	16.3%	(^{Lin et al., 2010})
Mt.Dinghu, Guangdong	Oct-09-Apr-10	5.0 $±$ 2.89	3.84	-24.2%	(^{Chen et al., 2013})
Guangzhou, urban site	Nov-10-Nov-11	4.6 $±$ 1.36	3.74	-18.5%	(^{Chen et al., 2013})

Tab.4 Comparisons of model results in BASE scenario with observations

Station	Sampling period	Observation/Simulation			Reference
Station	Sampling period	Wet deposition ( $μg/m 2 /yr$ )	Rainfall (mm)	Dry deposition ( $μg/m 2 /yr$ )	Reference
Guangzhou urban site	Jan-10?Dec-12	145.8/148.2	1699/2040	58.6/55.2	^{Huang et al. (2016})
Dinghushan site	Jan-10?-Dec-12	102.4/113.6	1599/2120	54.6/45.6	^{Huang et al. (2016})

Tab.5 Comparisons of simulated mercury deposition in BASE scenario with observations

Fig.4 Verification of annual mercury wet deposition and rainfall.

Fig.5 Source contributions to seasonal and annual averaged (a) total mercury concentrations, (b) total mercury dry depositions and (c) wet depositions.

Fig.6 (a) Model-predicted THg deposition (

μg/m 2 /yr

), difference of THg deposition between (b) BCs, (c) NAT, (d) PP, (e) MSWI, (f) IP scenario and BASE scenario (%).

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