| 成渝地区一次区域重污染过程来源解析及减排效果研究 |
| Source Analysis and Control Effect of a Heavy Pollution Process in Chengdu-Chongqing Region |
| 投稿时间：2019-08-20 修订日期：2019-12-12 |
| DOI：10.19316/j.issn.1002-6002.2020.02.10 |
| 中文关键词: 成渝地区 重污染 天气成因 源解析 减排评估 |
| 英文关键词:Chengdu-Chongqing region heavy pollution weather situation source apportionment emission assessment |
| 基金项目:国家重点研发计划项目(2016YFC0208803) |
| 作者 | 单位 | | 王文丁 | 中国科学院大气物理研究所,大气边界层物理和大气化学国家重点实验室,北京100029 | | 朱怡静 | 中科三清科技有限公司,北京100029 | | 皮冬勤 | 中科三清科技有限公司,北京100029 | | 陈亚飞 | 中科三清科技有限公司,北京100029 | | 张稳定 | 中科三清科技有限公司,北京100029 | | 陈焕盛 | 中国科学院大气物理研究所,大气边界层物理和大气化学国家重点实验室,北京100029 | | 吴剑斌 | 中科三清科技有限公司,北京100029 | | 晏平仲 | 中国科学院大气物理研究所,大气边界层物理和大气化学国家重点实验室,北京100029 |
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| 中文摘要: |
| 基于嵌套网格空气质量预报模式(NAQPMS)及耦合的污染来源追踪模块模拟2017年12月16日至2018年1月3日成渝地区一次区域重污染过程,定量解析成渝地区主要城市PM2.5来源,评估过程中应急减排的成效。结果表明,天气静稳和风向辐合是造成此次重污染过程的重要因素,污染峰值阶段,成渝地区多个城市PM2.5日均质量浓度超过150 μg/m3,达到重度污染级别。污染过程中,成都市PM2.5本地排放的贡献率为42%,眉山和德阳贡献率将近30%；重庆市PM2.5本地排放的贡献率为60%,外来输送以湖北、湖南和其他地区为主,贡献率为24%,成都和重庆市的工业源和交通源的贡献最大。区域联防联控应急减排对成渝各城市空气质量改善效果显著,成渝地区PM2.5浓度降低率为5%～11%,对于未实施应急预警方案的地区(如眉山市)受周边城市减排影响,浓度降低可达6%。 |
| 英文摘要: |
| Chengdu-Chongqing region experienced a continuous heavy pollution process from December 16,2017 to January 4,2018. The Nested Air Quality Prediction Modeling System (NAQPMS) with an online source-tagging module were employed to simulate this process, quantify the sources of PM2.5, and quantitatively evaluate the emergency emission reduction effect in the region. The results showed that stable weather and convergence of wind direction were important factors resulting in pollution. At the peak stage of pollution, daily PM2.5concentration exceeded 150 μg/m3. The contribution of PM2.5 emission of Chengdu was 42%, and external transportation was nearly 30% in Meishan and Deyang. The contribution of PM2.5 emission of Chongqing was 60% in local area, and external transportation was 24% in Hubei, Hunan and other regions. Regional emergency emission reduction had significant effects on air quality improvement in Chengdu-Chongqing region, that PM2.5 concentration reduced between 5% and 11%. In Meishan areas without control measures, the actual emission reduction effect reached 6%. |
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