Development of a Multi-Region air quality benefit evaluation tool for PM2.5 based on
RSM-Linear coupled fitting method
Shicheng Long1, Yun Zhu1,*, Carey Jang2, Che-Jen Lin1, 3, Junpin Xie1, JieMa1, Shuxiao Wang4, Bin Zhao 4,
Joshua Fu5
1 College
of Environmental Science & Engineering, South China University of Technology, Guangzhou Higher
Education Mega Center, Guangzhou 510006, China
2
USEPA/Office of Air Quality Planning & Standards, RTP, NC27711, USA
3
Department of Civil Engineering, Lamar University, Beaumont, TX 77710-0024, USA
4
Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084, China
5
Department of Civil & Environmental Engineering, University of Tennessee, Knoxville, TN 37996-2010, USA
ABSTRACT
To real-time analyze the air quality concentrations (especially for PM2.5 and O3) caused by pollutants
emission, U.S. Environmental Protection Agency (U.S. EPA) has developed an innovative policy support tool
based on Response Surface Modeling to address the non-linear relationship between emissions and air quality.
The RSM tool named as RSM-VAT has been applied on evaluating the interaction of emissions between regional
and local area both in USA and China. However, RSM-VAT (regional & local) can’t be used to estimate the
interaction of emissions among adjacent areas (Shanghai, Jiangsu, Zhejiang) in Yangtze River Delta Region,
because it is originally designed to address the interaction of emissions between regional and local area.
PM2.5 as the prime culprit of the regional haze has become the most concerned pollutant in China recently. A
considerable composition of PM2.5 is contributed by primary/direct emission sources, such as power plant,
industrial & domestic, and transportation in addition to the secondary particulates transformed from the pollutants
of SO2, NH3, NOx and VOC through complex photochemical reaction. The primary PM2.5 emission sources have
a linear contribution to air quality concentration, while the secondary particulates have a non-linear relationship
among precursor pollutants. That means we need to develop a new algorithm to treat the non-linear and linear
high-dimensional fitting of PM2.5 sequentially for estimating the interactions of emissions among adjacent areas.
To address this issue, we developed a new RSM-Linear coupled fitting method for PM2.5 simulation. Based on this
method, we update the current air quality benefit evaluation tool RSM-VAT (regional & local) to RSM-VAT
(Multi-Region) for analyzing and evaluating the contribution of adjacent regions emissions on PM2.5
concentration in target area. The results of the case study on PM2.5 evaluation in Yangtze River Delta (YRD) show
that the RSM-VAT (Multi-Region) can replicate the CMAQ simulation results with Normalized Mean Bias (NME)
≤0.649%. The emission control scenario analyses reveal that primary PM2.5 emissions have an obvious
contribution on ambient PM2.5 concentration (e.g. more than 50% contribution of primary emission at some areas).
The RSM-VAT (Multi-Region) can be applied to evaluate air quality benefit for PM2.5 when using all kinds of
emission control scenarios among adjacent regions; it can provide policy makers a near real-time, science-based
analysis for making air pollution control polices.
KEYWORDS
Response surface model, Multi-region, RSM-Linear coupled fitting, PM2.5
ACKNOWLEDGEMENT
Financial support and data source for this work is provided by the U.S. Environmental Protection Agency
(Subcontract Number OR13810-001.04 A10-0223-S001-A02). This work is also partly supported by the funding
of Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control.