The spatiotemporal variation and key factors of SO2 in 336 cities across China
The spatiotemporal variation and key factors of SO2 in 336 cities across China
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全国336个城市SO2时空变化特征及关键影响因素
DOI：
10.1016/j.jclepro.2018.11.062
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发表时间：
2019-02-10
影响因子：
11.1
通讯作者：
Chen, Jianmin
中科院分区：
文献类型：
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作者：
Li, Rui;Fu, Hongbo;Chen, Jianmin
二氧化硫（SO2）污染已成为中国的一个严重问题，与人类健康密切相关。本文首先收集了2015年全国336个地级市官方发布的SO2数据，以了解SO2浓度的时空变化规律。从全国范围来看，SO2浓度冬季最高，春季和秋季次之，夏季最低。空间计量经济模型、地理权重回归（GWR）模型和广义加性模型（GAM）随后被应用于研究社会经济因素（例如，国内生产总值（GDP））和气象指标（例如，降水对全国336个城市SO2水平的影响。结果表明，SO2浓度与GDP、降水量、风速、相对湿度呈负相关，与工业生产总值、人口、气温呈正相关。江苏、浙江两省的GDP与SO2浓度呈负相关关系，说明发达地区的产业结构已经发生了调整。GIP对SO2浓度的正效应由西向北逐渐增强，这是因为华北地区集中了大量的能源密集型产业。GAM分析表明，不利气象条件的综合影响（例如，RH = 50-60%）和较高的GIP导致了严重的SO2污染。因此，应减少重工业特别是华北平原地区的SO2排放，并将该地区的高耗能工厂转移到具有良好扩散条件的城市。(C)2018爱思唯尔有限公司版权所有
Sulfur dioxide (SO2) pollution has become a severe concern in China, which is closely linked to human health. Here, the officially released data of SO2 in the 336 prefecture-level cities in 2015 across the whole China were firstly collected to understand the spatiotemporal variation of the SO2 concentration. At a national scale, the SO2 concentration was highest in winter, followed by one in spring and autumn, and the lowest one in summer. The spatial econometric models, the geographical weight regression (GWR) model, and the generalized additive model (GAM) were then applied to examine the interaction of socioeconomic factors (e.g., gross domestic production (GDP)) and the meteorological indicators (e.g., precipitation) on the SO2 level in the 336 cities over China. The results suggested that the SO2 concentration was negatively associated with GDP, precipitation, wind speed (WS), and relative humidity (RH), while it showed the positive relationship with gross industrial production (GIP), population, and temperature. GDP in the Jiangsu and Zhejiang provinces presented the negative correlations with the SO2 concentration, suggesting the adaptation of industrial structure has occurred in the developed region. The positive effect of GIP on the SO2 concentration increased from West China to North China because many energy-intensive industries were concentrated on North China. The GAM analysis suggested that the combined effects of the adverse meteorological condition (e.g., RH = 50-60%) and the higher GIP contributed to severe SO2 pollution. Therefore, the SO2 emission from the heavy industries especially in NCP should be reduced and many energy-intensive plants in the region should be moved to some cities with favorable diffusion condition. (C) 2018 Elsevier Ltd. All rights reserved.