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Spatial–seasonal characteristics and critical impact factors of PM2.5 concentration in the Beijing–Tianjin–Hebei urban agglomeration

机译:京津冀城市群PM2.5浓度的时空变化特征及关键影响因素

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摘要

As China’s political and economic centre, the Beijing–Tianjin–Hebei (BTH) urban agglomeration experiences serious environmental challenges on particulate matter (PM) concentration, which results in fundamental or irreparable damages in various socioeconomic aspects. This study investigates the seasonal and spatial distribution characteristics of PM2.5 concentration in the BTH urban agglomeration and their critical impact factors. Spatial interpolation are used to analyse the real-time monitoring of PM2.5 data in BTH from December 2013 to May 2017, and partial least squares regression is applied to investigate the latest data of potential polluting variables in 2015. Several important findings are obtained: (1) Notable differences exist amongst PM2.5 concentrations in different seasons; January (133.10 mg/m3) and December (120.19 mg/m3) are the most polluted months, whereas July (38.76 mg/m3) and August (41.31 mg/m3) are the least polluted months. PM2.5 concentration shows a periodic U-shaped variation pattern with high pollution levels in autumn and winter and low levels in spring and summer. (2) In terms of spatial distribution characteristics, the most highly polluted areas are located south and east of the BTH urban agglomeration, and PM2.5 concentration is significantly low in the north. (3) Empirical results demonstrate that the deterioration of PM2.5 concentration in 2015 is closely related to a set of critical impact factors, including population density, urbanisation rate, road freight volume, secondary industry gross domestic product, overall energy consumption and industrial pollutants, such as steel production and volume of sulphur dioxide emission, which are ranked in terms of their contributing powers. The findings provide a basis for the causes and conditions of PM2.5 pollution in the BTH regions. Viable policy recommendations are provided for effective air pollution treatment.
机译:作为中国的政治和经济中心,北京-天津-河北(BTH)城市群在颗粒物(PM)浓度方面面临严重的环境挑战,这会在各个社会经济方面造成根本性或无法弥补的损失。本研究调查了BTH城市群中PM2.5浓度的季节和空间分布特征及其关键影响因素。空间插值用于分析2013年12月至2017年5月BTH中PM2.5数据的实时监测,并应用偏最小二乘回归调查2015年潜在污染变量的最新数据。获得了以下重要发现: (1)不同季节的PM2.5浓度之间存在显着差异; 1月(133.10 mg / m 3 )和12月(120.19 mg / m 3 )是污染最严重的月份,而7月(38.76 mg / m 3 (sup>)和8月(41.31 mg / m 3 )是污染最少的月份。 PM2.5浓度呈周期性的U型变化规律,秋季和冬季的污染水平较高,而春季和夏季的水平较低。 (2)就空间分布特征而言,污染最严重的地区位于BTH城市群的南部和东部,而北部的PM2.5浓度明显较低。 (3)实证结果表明,2015年PM2.5浓度的下降与一系列关键影响因素密切相关,包括人口密度,城市化率,道路货运量,第二产业国内生产总值,总体能源消耗和工业污染物,例如钢铁产量和二氧化硫排放量,按其贡献力进行排名。研究结果为BTH地区PM2.5污染的原因和状况提供了依据。提供了可行的政策建议以进行有效的空气污染处理。

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