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Simulation analysis of spatial distribution of PM2.5
concentration based on LUR model
YANG Mingliang, ZHU Zongjiu
Journal of Atmospheric and Environmental Optics
2022, 17 (3):
347-359.
PM2:5 is one of the important pollutants in the atmosphere, so simulating the spatial distribution of PM2:5
concentration is of great significance to the prevention and control of air pollution. The Land Use Regression (LUR)
model was applied to the heavily polluted Northern Anhui region in Anhui Province, China. Taking the monitoring
points as the center, the buffer zones with radius of 0.5, 1, 1.5, 2, 3, 4 and 5 km were established respectively.
Combined with 105 variables including land use factor, road factor, pollution source factor, meteorological factor,
elevation factor and population factor, a four-season and annual average LUR model for this district was established, and the accuracy of the model was verified by leave-one-out cross validation. The results show that the PM2:5
concentration in the study area is greatly affected by grassland, wetland, rainfall, relative humidity, atmospheric pressure, wind speed, secondary roads, tertiary roads, air-polluting enterprise, and population. The adjusted R2 is 0.828
(spring), 0.731 (summer), 0.831 (autumn), 0.775 (winter) and 0.892 (annual average) respectively. The root mean
square error (RMSE) is 6.34 µg·m−3 (spring), 7.01 µg·m−3 (summer), 6.28 µg·m−3 (autumn), 6.71 µg·m−3 (winter)
and 5.33 µg·m−3 (annual average). The simulation accuracy R2 is 0.825 (spring), 0.730 (summer), 0.834 (autumn),
0.772 (winter) and 0.897 (annual average). The model shows good performance and strong explanatory power. As
can be seen from the simulated spatial distribution of PM2:5 concentration, the spatial distribution characteristics in
the area are obviously different in different seasons, which is related to a large number of pollution particles from
the north, local coal mining, straw burning during autumn tillage and other potential pollution sources.
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