| 基于模式过程分析技术天津地区PM2.5污染气象成因分析 |
| 摘要点击 1943 全文点击 559 投稿时间：2021-09-02 修订日期：2021-09-26 |
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| 中文关键词 过程分析技术 污染成因 数值模拟 重污染天气 天津 |
| 英文关键词 process analytical technology cause of air pollution numerical simulation heavily polluted weather Tianjin |
| 作者 | 单位 | E-mail | | 郝囝 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074 | 824510059@qq.com | | 蔡子颖 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074
天津市环境气象中心, 天津 300074 | 120078030@163.com | | 韩素芹 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074
天津市环境气象中心, 天津 300074 | | | 杨旭 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074
天津市环境气象中心, 天津 300074 | | | 樊文雁 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074
天津市环境气象中心, 天津 300074 | | | 姚青 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074
天津市环境气象中心, 天津 300074 | | | 邱晓滨 | 天津市气象科学研究所, 天津 300074
中国气象局-南开大学大气环境与健康研究联合实验室, 天津 300074
天津市环境气象中心, 天津 300074 | |
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| 中文摘要 |
| 基于WRF/Chem数值模式，通过过程分析技术和标记法源追踪技术解析水平输送、湍流混合、垂直运动、对流作用和区域输送对天津地区地面PM2.5质量浓度影响，研究2019年6月~2021年5月天津地区重污染天气成因.结果表明，基于上述方法可实现重污染天气气象成因定量描述，从水平输送、湍流混合、垂直运动、对流作用和区域输送角度实现重污染天气成因数值归因分析.天津地区水平输送作用为-2.03μg ·（m3 ·h）-1、垂直平流为-2.24μg ·（m3 ·h）-1、垂直混合为-11.70μg ·（m3 ·h）-1、对流作用为-0.03μg ·（m3 ·h）-1和区域输送贡献36.23%，2019年6月~2021年5月共出现16次重污染过程，除一次沙尘影响和一次烟花爆竹影响外，均可通过建立数值归因方法，以水平输送作用变化速指标（α）、对流作用变化速指标、垂直平流作用变化速指标（φ）和湍流混合作用变化速指标（β）以及区域输送百分率指标（τ），对重污染气象成因进行合理解释，天津重污染天气解析指标为α>-2.0%·h-1、β>-7.7%·h-1、φ>2%·h-1、θ<12%·h-1、τ>50%和PBL （混合层厚度）<250 m.解析指标表明湍流混合能力和混合层厚度降低在近年重污染天气形成中有重要影响，14次过程均可从指标清晰解析出上述成因，水平风场辐合和垂直平流输送在部分重污染天气中会叠加在大气垂直扩散条件下降基础上，进一步触发重污染天气形成，其出现次数分别为6次和4次.基于过程分析技术可建立定量化的大气自净能力评估指标，其与传统的通风系数指标有较好的相关性，数值模式大气自净能力评估指标θ与PM2.5相关系数为0.65，高于传统指标，θ<12%·h-1时，表明大气扩散条件极差，其中81.25%的重污染天气符合该指标，θ>30%·h-1后，大气自净能力超过排放影响，出现污染超标的概率不到1.5%. |
| 英文摘要 |
| Based on the WRF/Chem numerical model, the effects of horizontal transport, turbulent mixing, vertical motion, convection, and regional transport on the surface PM2.5 mass concentration in Tianjin were analyzed using process analysis and labeling source tracing techniques, and the causes of heavy pollution weather in Tianjin from June 2019 to May 2021 were studied. The results showed that the meteorological causes of heavy pollution weather can be assessed using this method; the horizontal transport was -2.03 μg·(m3·h)-1, the vertical advection was -2.24 μg·(m3·h)-1, the vertical mixing was -11.70 μg·(m3·h)-1, the convection was -0.03 μg·(m3·h)-1, and the contribution of regional transport was 36.23%. For 16 heavy pollution processes, except for dust and fireworks, the numerical attribution method could be established. The meteorological causes of heavy pollution could be reasonably explained by the horizontal transport change rate index (α), convection change rate index, vertical advection change rate index (φ), turbulent mixing change rate index (β), and regional transport percentage index (τ). The analytical indexes of heavy pollution weather in Tianjin were as follows:α>-2.0%·h-1, β>-7.7%·h-1, φ>2%·h-1, θ<12%·h-1, τ>50%, and PBL (mixed-layer thickness)<250 m. The analytical index showed that the turbulent mixing capacity and the decrease in the thickness of the mixing layer had an important influence on the formation of heavy pollution weather in recent years. Horizontal wind field convergence and vertical advection transport will be superimposed on the decline of atmospheric vertical diffusion conditions in some heavy pollution weather, which will further trigger the formation of heavy pollution weather; the occurrence times were 6 and 4, respectively. Based on the process analysis technology, a quantitative evaluation index of atmospheric self-purification capacity could be established, which had a good correlation with the traditional ventilation coefficient index. The correlation coefficient between θ and PM2.5 was 0.65, which was higher than the traditional index. A θ value of less than 12%·h-1 indicated that the atmospheric diffusion condition was very poor. A total of 81.25% of the heavy pollution weather accorded with this index, and θ greater than 30%·h-1 indicated that the atmospheric diffusion condition was very poor. The self-purification capacity of the atmosphere exceeded the impact of emissions, and the probability of excessive pollution was less than 1.5%. |
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