厘清PM2.5的来源是开展重霾污染防治的前提条件.本研究利用嵌套网格空气质量预报模式系统(NAQPMS)及其耦合的污染来源追踪技术,针对2013年1月我国中东部的重霾污染过程,定量模拟分析京津冀各城市PM2.5浓度的来源和相互贡献.研究结果表明,NAQPMS模式能够合理反映京津冀不同城市PM2.5浓度的变化特征.京津冀各城市近地面PM2.5浓度主要受本地排放影响,本地贡献率介于29.8%~63.7%.而800 m高空层各城市PM2.5浓度以外来贡献为主(69.3%~86.3%).在污染最严重的东南部地区(包括邢台、邯郸、沧州和衡水),PM2.5浓度受区域外的山东和河南的显著影响,贡献率可达25.2%~31.5%.因此,在京津冀区域内进行协同减排控制的同时,需进一步将山东、河南等省份纳入联防联控范围,才能有效防控重霾污染。
Identification of the source regions of PM2. 5and quantification of theircontributions are critical for efficient haze pollution control. In this study,the Nested Air Quality Prediction Model System( NAQPMS) coupled with an online source-tagging module was employed to simulate an extreme severe haze episode over Beijing-Tianjin-Hebei( BTH) area in January 2013. A detailed quantification of the source contributions from different regions was provided. The simulation was validated through comparisonwith surface observations,which suggested that the model could reasonably reproduce the temporal and spatial variations of PM2. 5concentrations during this episode. The results of the source-tagging calculation suggested that local emissions were the dominated sources of the surface PM2. 5,accounting for 29. 8% to 63. 7% contributions of the surface PM2. 5concentrations. On the other hand,PM2. 5at 800 m layer was mainly contributed by the sources of the surrounding areas with the contributed ratio from 69. 3% to 86. 3%. For the most polluted southeast BTH area( including Xingtai,Handan,Cangzhou and Hengshui),emissions from Shandong and Henan provinces had significantcontribution to the PM2. 5pollution with the largest contributions 25. 2% and 31. 5% at surface and 800 m layer,respectively. Therefore,the control of haze pollution over BHT areas should not only focus on the collaborative emission control within BHT areas but also take into account the joint emission control for BHT regions,Shandong and Henan Provinces.