Detecting the causality influence of individual meteorological factors on local PM(2.5) concentration in the Jing-Jin-Ji region.
Detecting the causality influence of individual meteorological factors on local PM(2.5) concentration in the Jing-Jin-Ji region.
复制标题
检测京津冀地区个别气象因素对当地PM2.5浓度的因果影响
DOI：
10.1038/srep40735
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发表时间：
2017-01-27
影响因子：
4.6
通讯作者：
Xie X
中科院分区：
文献类型：
--
作者：
Chen Z;Cai J;Gao B;Xu B;Dai S;He B;Xie X
由于大气环境中相互作用复杂，量化单个气象因子对局部PM2.5浓度的影响仍然具有挑战性。京津冀地区因严重的空气污染而臭名昭著。为改善区域空气质量，应更好地了解PM2.5浓度的特征和气象驱动因素。本研究考察了京津冀地区PM2.5浓度的季节变化，提取了与当地PM2.5浓度密切相关的气象因子。在此基础上，采用收敛交叉映射（CCM）方法量化各气象因子对PM2.5浓度的因果影响。结果表明，CCM方法更容易检测到海市蜃楼相关性，揭示单个气象因子对PM2.5浓度的定量影响。京津冀地区PM2.5浓度越高，气象因子对PM2.5浓度的影响越强。此外，个别气象因子通过与其他气象因子的相互作用，间接影响当地PM2.5浓度。由于当地气象对PM2.5浓度的影响显著，因此应更加重视利用气象手段改善当地空气质量。
Due to complicated interactions in the atmospheric environment, quantifying the influence of individual meteorological factors on local PM2.5 concentration remains challenging. The Beijing-Tianjin-Hebei (short for Jing-Jin-Ji) region is infamous for its serious air pollution. To improve regional air quality, characteristics and meteorological driving forces for PM2.5 concentration should be better understood. This research examined seasonal variations of PM2.5 concentration within the Jing-Jin-Ji region and extracted meteorological factors strongly correlated with local PM2.5 concentration. Following this, a convergent cross mapping (CCM) method was employed to quantify the causality influence of individual meteorological factors on PM2.5 concentration. The results proved that the CCM method was more likely to detect mirage correlations and reveal quantitative influences of individual meteorological factors on PM2.5 concentration. For the Jing-Jin-Ji region, the higher PM2.5 concentration, the stronger influences meteorological factors exert on PM2.5 concentration. Furthermore, this research suggests that individual meteorological factors can influence local PM2.5 concentration indirectly by interacting with other meteorological factors. Due to the significant influence of local meteorology on PM2.5 concentration, more emphasis should be given on employing meteorological means for improving local air quality.