Daily estimation of PM2.5 concentrations based on mixed effects model in Beijing-Tianjin-Heibei region
JING Yue1, SUN Yan-ling1, XU Hao2, CHEN Li1, ZHANG Hui1, GAO Shuang1, FU Hong-chen1, MAO Jian1
1. College of Geography and Environment Science, Tianjin Normal University, Tianjin 300387, China;
2. College of Economics and Management, Ningxia University, Yinchuan 750021, China
The predictive performance of mixed effects model with different combinations of parameters was evaluated using the data of 182-day MODIS 3km AOD and ground monitoring concentration of PM2.5 in 2016 year. The explanation capacity was better for temporal variations when explaining the relationship between AOD and PM2.5 than for the spatial variations. Daily AOD-PM2.5 relationship in Beijing-Tianjin-Hebei region was established based on the mixed effects model. The model predictions R2, cross-validations R2, RMSE and MAE were 0.92,0.85,12.30 μg/m3, and 9.73 μg/m3, respectively, indicated that the model showed good performance. The annual average PM2.5 concentration in Beijing-Tianjin-Hebei region was 42.98 μg/m3 in 2016 based on the proposed model. The values for April-October and November-March were 43.35 μg/m3 and 38.52 μg/m3. The differences were 0.59,0.7,5.29 μg/m3, respectively, comparing with the ground monitoring PM2.5 data at the corresponding period. PM2.5 concentrations were higher in the south area and lower in the north area in Beijing-Tianjin-Hebei region with higher concentrations from southwestern to northeastern direction. PM2.5 concentrations in the Beijing-Tianjin-Hebei region could be accurately evaluated based on the daily mixed effects model. The distribution of PM2.5 concentrations estimated by the model could provide basic data support for the prevention and control of regional air pollution.
Hu X, Waller L A, Lyapustin A, et al. Estimating ground-level PM2.5, concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model[J]. Remote Sensing of Environment, 2014,140(1):220-232.
Gupta P, Christopher S A, Wang J, et al. Satellite remote sensing of particulate matter and air quality assessment over global cities[J]. Atmospheric Environment, 2006,40(30):5880-5892.
Karimian H, Li Q, Li C C, et al. Daily estimation of fine particulate matter mass concentration through satellite based Aerosol Optical Depth[J]. 2017,IV-4/W2:175-181.
Lv B, Hu Y, Chang H H, et al. Daily estimation of ground-level PM2.5 concentrations at 4km resolution over Beijing-Tianjin-Hebei by fusing MODIS AOD and ground observations[J]. Science of the Total Environment, 2017,580:235.
[19]
Lee H J, Liu Y, Coull B A, et al. A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations[J]. Atmospheric Chemistry & Physics, 2011,11(11):9769-9795.
[20]
Lee H J, Chatfield R B, Strawa A W. Enhancing the Applicability of Satellite Remote Sensing for PM2.5 Estimation Using MODIS Deep Blue AOD and Land Use Regression in California, United States[J]. Environmental Science & Technology, 2016,50(12):6546.
[21]
Kloog I, Chudnovsky A A, Just A C, et al. A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data[J]. Atmospheric Environment, 2014,95(1):581-590.
[22]
Xie Y, Wang Y, Zhang K, et al. Daily estimation of ground-level PM2.5 concentrations over Beijing using 3km resolution MODIS AOD[J]. Environmental Science & Technology, 2015,49(20):12280.
[23]
Ma Z, Liu Y, Zhao Q, et al. Satellite-derived high resolution PM2.5, concentrations in Yangtze River Delta Region of China using improved linear mixed effects model[J]. Atmospheric Environment, 2016,133:156-164.
[24]
Chu D A, Kaufman Y J, Zibordi G, et al. Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS)[J]. Journal of Geophysical Research Atmospheres, 2003,108(D21):4661.
[25]
Munchak L A, Levy R C, Mattoo S, et al. MODIS 3km aerosol product:applications over land in an urban/suburban region[J]. Atmospheric Measurement Techniques, 2013,6(7):1747-1759.
Zongwei Ma, Xuefei Hu, Andrew M. Sayer, et al. Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations:China, 2004~2013[J]. Environmental Health Perspectives, 2016,124(2):184.
[29]
Ma X, Wang J, Yu F, et al. Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China?[J]. Atmospheric Research, 2016,181:250-256.