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京津冀内陆平原区PM2.5浓度时空变化定量模拟
摘要点击 2820  全文点击 822  投稿时间:2017-06-29  修订日期:2017-09-19
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中文关键词  PM2.5  气溶胶光学厚度  混合效应模型  十折交叉验证  京津冀内陆平原区
英文关键词  PM2.5  aerosol optical depth(AOD)  mixed effects model  ten-fold cross validation method  the inland plain of the Beijing-Tianjin-Hebei region
作者单位E-mail
郝静 河北师范大学资源与环境科学学院, 石家庄 050024
河北省环境演变与生态建设实验室, 石家庄 050024 
haojing_2015@163.com 
孙成 河北师范大学资源与环境科学学院, 石家庄 050024
河北省环境演变与生态建设实验室, 石家庄 050024 
 
郭兴宇 河北师范大学资源与环境科学学院, 石家庄 050024
河北省环境演变与生态建设实验室, 石家庄 050024 
 
王卫 河北师范大学资源与环境科学学院, 石家庄 050024
河北省环境演变与生态建设实验室, 石家庄 050024 
wangwei@hebtu.edu.cn 
刘方田 河北师范大学资源与环境科学学院, 石家庄 050024
河北省环境演变与生态建设实验室, 石家庄 050024 
 
党海燕 河北师范大学资源与环境科学学院, 石家庄 050024  
中文摘要
      近年来我国京津冀地区霾污染日趋严重,为揭示该地区PM2.5时空变化特征,以京津冀内陆平原为研究区,以MODIS AOD数据作为主要预测因子,采用混合效应模型建立研究区2013~2014年AOD-PM2.5逐日变化的关系模型.利用十折交叉验证法对模型拟合进行验证.结果表明,采用混合效应模型对AOD-PM2.5进行时间上的校准能够提高二者间的相关性,模型拟合的PM2.5质量浓度与地面实测值间的R2为0.78,经过交叉验证后R2为0.70,RMSE、RPE分别为20.80 μg·m-3、28.76%.针对研究区冬季AOD有效值非随机性缺失带来的采样偏差,用校正因子对模型预测的2013~2014年间PM2.5平均浓度进行校正,结果表明研究区内PM2.5平均浓度均高于75 μg·m-3,南部和西部地区的PM2.5浓度相对较高,北部和东部地区PM2.5浓度相对较低,呈现出"南高北低、西高东低"的分布趋势.研究结果表明混合效应模型能够适用于近地面PM2.5监测,也为该区域大气颗粒物污染治理提供了科学依据.
英文摘要
      In recent years, haze pollution in China is becoming increasingly serious, especially in the Beijing-Tianjin-Hebei region. In order to identify the temporal and spatial distributional characteristics of PM2.5 aerosol mass concentration in the region, this study selected the inland plain of the Beijing-Tianjin-Hebei region as the research area, and used MODIS AOD as the main predictor in a mixed effects model to establish the daily relationship of AOD-PM2.5 in the study area, from 2013 to 2014. The model was validated by a ten-fold cross validation method. The results showed that the correlation between AOD-PM2.5 can be improved by daily calibration of the mixed effects model (R2=0.78); the cross-validated R2 was 0.70, and RMSE and RPE were 20.80 μg·m-3 and 28.76%, respectively. Considering the importance of unbiased PM2.5 predictions, the correction factors calculated from the surface PM2.5 measurements were applied to correct the biases in the predicted annual average PM2.5 concentrations introduced by non-stochastic missing AOD measurements. The results showed that the annual average concentration of PM2.5 in the study area was higher than 75 μg·m-3, and the spatial distribution of PM2.5 concentration was higher in the southern and western regions, and lower in the northern and eastern regions. These results suggest that the mixed effects model can be used to monitor ground PM2.5, and also provide a scientific basis for the control of atmospheric particulate pollution in the region.

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