Impact of “ultra low emission” technology of coal-fired power on PM2.5 pollution in the Jing-Jin-Ji Region

Xiao LIU, Zhilin LIU, Weidong JIAO, Xuan LI, Jintai LIN, Anthony KU

PDF(1896 KB)
PDF(1896 KB)
Front. Energy ›› 2021, Vol. 15 ›› Issue (1) : 235-239. DOI: 10.1007/s11708-017-0518-y
RESEARCH ARTICLE

Impact of “ultra low emission” technology of coal-fired power on PM2.5 pollution in the Jing-Jin-Ji Region

Author information +
History +

Abstract

In response to severe haze pollution, the Chinese government has announced a series of policies focusing on controlling emissions from coal consumption. “Ultra-low emission” (ULE) technologies have the potential to dramatically reduce emissions from coal-fired power plants, and have been deployed at some facilities in recent years. This paper estimated the potential environmental benefits of the widespread adoption of ULE in the Jing-Jin-Ji Region. Atmospheric modeling scenarios were analyzed for three cases: a “standard” scenario assuming no ULE deployment, a “best case” scenario assuming complete adoption of ULE across all power plants in the region, and a “natural gas” scenario, assuming emissions factors consistent with natural gas-fired power generation. The simulations show that the widespread adoption of ULE technologies can be an effective and economically competitive option for reducing the impacts of coal-fired power generation on air quality.

Keywords

air quality / atmospheric model / coal / Jing-Jin-Ji Region / PM2.5 / ultra-low emissions

Cite this article

Download citation ▾
Xiao LIU, Zhilin LIU, Weidong JIAO, Xuan LI, Jintai LIN, Anthony KU. Impact of “ultra low emission” technology of coal-fired power on PM2.5 pollution in the Jing-Jin-Ji Region. Front. Energy, 2021, 15(1): 235‒239 https://doi.org/10.1007/s11708-017-0518-y

References

[1]
Wang S X, Zhao B, Cai S Y, Klimont Z, Nielsen C P, Morikawa T, Woo J H, Kim Y, Fu X, Xu J Y, Hao J M, He K B. Emission trends and mitigation options for air pollutants in East Asia. Atmospheric Chemistry and Physics, 2014, 14(13): 6571–6603
CrossRef Google scholar
[2]
Wang S X, Zhao B, Wu Y, Hao J M. Target and measures to prevent and control ambient fine particle pollution in China. Chinese Journal of Environmental Management, 2015, 7(2): 37–43 (in Chinese)
[3]
Cai S, Zhao B, Hao J M, Wang S, Chang X. The impact of the “Air Pollution Prevention and Control Action Plan” on PM2.5 concentrations in Jing-Jin-Ji region during 2012–2020. Science of the Total Environment, 2017, 580(2017): 197–209
[4]
Zhao Y, Wang S, Nielsen C P, Li X, Hao J. Establishment of a database of emission factors for atmospheric pollutants from Chinese coal-fired power plants. Atmospheric Environment, 2010, 44(12): 1515–1523
CrossRef Google scholar
[5]
Zhang Q, Streets D G, Carmichael G R, He K B, Huo H, Kannari A, Klimont Z, Park I S, Reddy S, Fu J S, Chen D, Duan L, Lei Y, Wang L T, Yao Z L. Asian emissions in 2006 for the NASA INTEX-B emission. Atmospheric Chemistry & Physics Discussions, 2009, 9(1): 5131–5153
[6]
Wang Y X, McElroy M B, Jacob D J, Yantosca R M. A nested grid formulation for chemical transport over Asia: applications to CO. Journal of Geophysical Research, 2004, 109: D22307
CrossRef Google scholar
[7]
Chen D, Wang Y, McElroy M B, He K, Yantosca R M, Le Sager P. Regional CO pollution and export in China simulated by the high-resolution nested-grid GEOS-Chem model. Atmospheric Chemistry and Physics, 2009, 9(11): 3825–3839
CrossRef Google scholar
[8]
Wang Y, Zhang Y, Hao J, Luo M. Seasonal and spatial variability of surface ozone over China: contributions from background and domestic pollution. Atmospheric Chemistry and Physics, 2011, 11(7): 3511–3525
CrossRef Google scholar
[9]
Lin J T, Liu Z, Zhang Q, Liu H, Mao J, Zhuang G. Model uncertainties affecting satellite-based inverse modeling of nitrogen oxides emissions and implications for surface ozone simulation. Atmospheric Chemistry and Physics Discussion, 2012, 12(6): 14269–14327
CrossRef Google scholar
[10]
Yan Y, Lin J, Chen J, Hu L. Improved simulation of tropospheric ozone by a global-multi-regional two-way coupling model system. Atmospheric Chemistry and Physics, 2016, 16(4): 2381–2400
CrossRef Google scholar
[11]
Streets D G, Bond T C, Carmichael G R, Fernandes S D, Fu Q, He D, Klimont Z, Nelson S M, Tsai N Y, Wang M Q, Woo J H, Yarber K F. An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. Journal of Geophysical Research, 2003, 108(D21): 8809
CrossRef Google scholar
[12]
Streets D G, Yarber K F, Woo J H, Carmichael G R. Biomass burning in Asia: annual and seasonal estimates and atmospheric emissions. Global Biogeochemical Cycles, 2003, 17(4): 1099
CrossRef Google scholar
[13]
Chen D, Wang Y, McElroy M B, He K, Yantosca R M, Le Sager P. Regional CO pollution and export in China simulated by the high-resolution nested-grid GEOS-Chem model. Atmospheric Chemistry and Physics, 2009, 9(11): 3825–3839
CrossRef Google scholar
[14]
Wang Y X, McElroy M B, Jacob D J, Yantosca R M. A nested grid formulation for chemical transport over Asia: applications to CO. Journal of Geophysical Research, D, Atmospheres, 2004, 109(22): 2285–2311
[15]
Henze D K, Seinfeld J H, Shindell D T. Inverse modeling and mapping US air quality influences of inorganic PM2.5 precursor emissions using the adjoint of GEOS-Chem. Atmospheric Chemistry and Physics Discussion, 2009, 9(16): 5877–5903
CrossRef Google scholar
[16]
Spath P L, Mann M K. Life cycle assessment of a natural gas combined cycle power generation system. British Journal of Sports Medicine, 2000, 42 (4): 300–303

RIGHTS & PERMISSIONS

2021 Higher Education Press
AI Summary AI Mindmap
PDF(1896 KB)

Accesses

Citations

Detail

Sections
Recommended

/