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A Land Use Regression Application into Simulating Spatial Distribution Characteristics of Particulate Matter (PM_(2.5)) Concentration in City of Xi'an, China

机译:土地利用回归应用于中国西安市颗粒物质的空间分布特征(PM_(2.5)浓度

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摘要

Decreasing of PM2.5 concentration in the heating season was not significant in Xi'an. This article determined a land use regression (LUR) model and researched the distribution characteristics of PM2.5 in heating and non-heating seasons in Xi'an. The results showed that: (1) The R-2 of LUR was larger than 0.9, and the simulation results were better than previous studies. (2) The PM2.5 concentration in the heating season was larger than in the non-heating season. In Xi'an, the distribution of PM2.5 concentration was low in the southeast and high in the northwest in the non-heating season and was low in the southeast and high in the main urban region in the heating season. (3) The PM2.5 concentration was affected by temperature, average air pressure, altitude, humidity and precipitation in non-heating season and was influenced by precipitation, altitude, average air pressure, vegetation, and density of roads in heating season. (4) This paper showed some improvements in selection of potential variables for LUR model, and the conclusion can provide a scientific basis for PM2.5 pollution control and a reliable method for simulating PM2.5 concentration in other cities.
机译:在加热季节中的PM2.5浓度下降在西安并不重要。本文确定了土地利用回归(LUR)模型,并研究了西安加热和非加热季节PM2.5的分布特征。结果表明:(1)LUR的R-2大于0.9,仿真结果优于以前的研究。 (2)加热季节中PM2.5浓度大于非加热季节。在西安,在非加热季节的东南部分布在东南部和西北部高,在东南部,在加热季节的主要城市地区,在东南部较低。 (3)PM2.5浓度受到温度,平均气压,湿度,湿度和沉淀的非加热季节的影响,受加热季节中的降水,海拔,平均气压,植被和道路密度的影响。 (4)本文对LUR模型的潜在变量进行了一些改进,结论可以为PM2.5污染控制提供科学依据,以及在其他城市中模拟PM2.5浓度的可靠方法。

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