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Spatio-temporal variation and influence factors of PM2.5 concentrations in China from 1998 to 2014

机译:1998年至2014年中国PM2.5浓度的时空变化及其影响因素

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Based on the remote sensing retrieval of PM2.5 concentration data in the long-time series, both the linear regression and grey system correlation analysis methods were employed to analyze the spatial and temporal pattern, variation trend and the main influencing factors of PM2.5 concentration in China from 1998 to 2014. The results showed that only 16.21%a??24.67% of the land area in China PM2.5 concentrations reached the annual average criterion value of 10????g/m3 set by the World Health Organization (WHO) in 1998a??2014; the PM2.5 concentrations were greater than 95????g/m3 mainly in Xinjiang Taklimakan Desert, west of Tianjin and the central region of Hebei. PM2.5 concentration was less than 10????g/m3 mainly in Tibet, western Sichuan, northeastern Yunnan, Taiwan, northern Xinjiang, northern Inner Mongolia and northwest of Heilongjiang. High PM2.5 concentration in the northwest of China was mainly affected by sand and dust, while it was mainly caused by human activities in the eastern region. Except for Taiwan, low PM2.5 concentration areas were mainly located in the economically backward regions. The positive indicators in highly correlation with PM2.5 concentration include the average temperature, the proportion of primary and secondary industry to GDP, industrial consumption, the proportion of fulfilled amount of investment in real estate development to GDP, SO2 emissions and population density. The negative indicators in highly correlation with PM2.5 concentration include the average precipitation, the average wind velocity, the proportion of the tertiary industry to GDP, and the greening coverage rate of the built-up areas.
机译:基于长期序列中PM2.5浓度数据的遥感反演,采用线性回归和灰色系统相关分析方法分析了PM2.5的时空格局,变化趋势及主要影响因素。从1998年到2014年,中国的PM2.5浓度只有16.21%a≤24.67%的PM2.5浓度达到了世界卫生组织设定的年均标准值10-6?g / m3。组织(WHO),1998年-2014年; PM2.5浓度大于95?g / m3,主要在天津以西和河北中部的新疆塔克拉玛干沙漠中。 PM2.5浓度低于10-6 g / m3,主要在西藏,四川西部,云南东北部,台湾,新疆北部,内蒙古北部和黑龙江西北部。西北地区PM2.5的高浓度主要受沙尘影响,而东部地区的人为活动则是造成PM2.5浓度较高的原因。除台湾外,PM2.5浓度低的地区主要位于经济落后地区。与PM2.5浓度高度相关的积极指标包括平均温度,第一产业和第二产业对GDP的比重,工业消耗,房地产开发投资完成额对GDP,SO2排放量和人口密度的比重。与PM2.5浓度高度相关的负面指标包括平均降水量,平均风速,第三产业占GDP的比重以及建成区的绿化覆盖率。

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