研究报告

  • 黄晓波,殷晓鸿,黄志炯,夏泽群,李泽琨,朱文波,郑君瑜.不同模式对珠三角地区细颗粒物污染模拟效果对比评估[J].环境科学学报,2016,36(10):3505-3514

  • 不同模式对珠三角地区细颗粒物污染模拟效果对比评估
  • Evaluation and intercomparison of PM2.5 simulations by air quality models over Pearl River Delta
  • 基金项目:国家杰出青年科学基金项目(No.41325020);国家科技支撑项目(No.2014BAC21B03);中国科学院战略性先导科技专项子课题(No.XDB05020000)
  • 作者
  • 单位
  • 黄晓波
  • 华南理工大学环境与能源学院, 广州 510006
  • 殷晓鸿
  • 华南理工大学环境与能源学院, 广州 510006
  • 黄志炯
  • 华南理工大学环境与能源学院, 广州 510006
  • 夏泽群
  • 华南理工大学环境与能源学院, 广州 510006
  • 李泽琨
  • 山西省环境科学研究院, 太原 030000
  • 朱文波
  • 华南理工大学环境与能源学院, 广州 510006
  • 郑君瑜
  • 华南理工大学环境与能源学院, 广州 510006
  • 摘要:运用CAMxv5.4、CMAQv4.7.1、CMAQv5.0.2(AEOR5)和CMAQv5.02(AEOR6)模拟2013年12月珠三角地区空气质量,并对比评估不同模式、不同模式版本、不同气溶胶机制在PM2.5模拟上的表现.各模式在PM2.5的模拟上均表现良好,呈现出合理且相似的时空特征,在市区和非超标时段CAMx模式表现最优,而在郊区和超标时段则不存在表现最优的模式.CMAQ系列模式在市区和郊区、超标时段和非超标时段均表现相似,CMAQ4模式表现均优于CMAQ5系列模式,而CMAQ5AE6模式在反映PM2.5的浓度水平的能力上强于CMAQ5AE5模式,但在重现PM2.5小时浓度变化趋势的能力上却劣于CMAQ5AE5模式.边界条件是不同模式PM2.5模拟差异的主要来源之一,且在超标时段边界条件对PM2.5模拟效果的影响大于非超标时段.此外,CAMx模式与CMAQ5AE5模式之间硫酸盐、硝酸盐和有机颗粒的差异导致了其PM2.5模拟表现上差异,CMAQ4模式与CMAQ5AE5模式之间硫酸盐、硝酸盐和铵盐等无机盐组分的差异是导致其PM2.5模拟差异的主要原因,硝酸盐和铵盐的差异是CMAQ5AE5模式与CMAQ5AE6模式之间PM2.5模拟差异的主要因素.
  • Abstract:Comparison among particulate matter (PM2.5) modeling in the Pearl River Delta (PRD) region using CAMxv5.4, CMAQv4.7.1, CMAQv5.0.2 (AEOR5) and CMAQv5.0.2 (AEOR6) were conducted in this study. December 2013 was set up as modeling period for these four models. All four models performed well in simulating the PM2.5 concentrations by comparing with observation. With the same meteorological data, the temporal and spatial distributions of simulated PM2.5 had slight differences in some areas and periods. CAMx performed better in urban areas and during the periods when PM2.5 daily concentration is less than 75 μg·m-3. Among CMAQ models, CMAQ4 performs the best, followed by CMAQ5AE5 and CMAQ5AE6. Compared with CMAQ5AE6, CMAQ5AE5 gave a lower concentration but more reasonable trend in PM2.5 simulation. The differences of PM2.5 simulation might be highly associated with the uncertainty of boundary condition. In addition, the discrepancies in formation of sulfate, nitrate and organic matter also led to the differences in PM2.5 simulation between CAMx and CMAQ. Specifically, formation of sulfate, nitrate and ammonium led to the difference of CMAQ4 and CMAQ5AE5 while those of nitrate and ammonium led to the difference of CMAQ5AE5 and CMAQ5AE6.

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