基于气象能见度资料估算我国主要特大城市群PM2.5质量浓度历史变化

The recent severe and frequent air pollution in China has aroused unprecedented public concern. Although the Chinese Government has built the nationwide air quality monitoring network, the limited PM2.5 dataset is insufficient to support the research of long-term air quality variation and its influence on climate system. The atmospheric visibility is a direct evaluation of local air quality, and due to its long observation history, the visibility dataset are often used in the field of air pollution. However, the present researches have two main issues. One is the uncertainty of the quantitative relationship between visibility and the mass concentration of PM2.5. The other is the inhomogeneity of the visibility series due to the change of observation methods. In this project, the mass concentration of PM2.5, atmospheric visibility data and other conventional meteorological observations will be used to analysis how well the atmospheric visibility could represent the PM2.5 pollution. The regional inversion model will be built to estimate PM2.5 concentration based on the visibility. The homogeneity of the historical visibility series will be evaluated. And then, the PM2.5 concentration over Jingjinji, Yangtze River Delta and Pearl River Delta region during the recent 30 years will be estimated. This project could fill the gap of the lack of long-term air pollutant dataset to a certain extent, and improve the accuracy and reliability of visibility in air pollution field. It will provide the foundation needed to attribute the air pollution.

空气污染问题已受到社会各界的广泛关注，虽然我国已逐步建成PM2.5等指标的实时监测网，但PM2.5浓度数据长度仍显不足，为空气污染长期变化及其影响研究带来了很大障碍。气象能见度是公众对空气质量最直观的感受，具有很好的历史观测，常被用作研究空气污染的代用资料。但使用能见度数据估算PM2.5浓度目前存在两个主要问题：1) 能见度与PM2.5浓度的定量关系有明显的时空差异；2) 由于观测规范和方式的改变，能见度数据存在明显的不均一性问题。因而，本项目拟利用PM2.5浓度、气象能见度以及其他常规气象资料，建立基于能见度估算京津冀、长三角和珠三角地区等区域PM2.5浓度的模型，评估能见度长期序列的均一性，以此重建PM2.5浓度历史数据集，揭示其长期变化特征。本项目的开展将有利于扩大空气污染数据的时间覆盖度，弥补空气污染研究资料缺乏的不足，从而为进一步研究我国空气污染影响提供有力的数据支撑和科学依据。

近年来我国颗粒物污染严重，但我国的空气质量监测网络从2013年才开始逐步建立，空气质量数据的不足给空气污染成因研究带来了不便，本项目采用能见度数据作为空气质量的代用资料，建立了能见度反演地面PM2.5浓度的物理模型,基于此评估了气象条件对空气质量的影响,为定量评估人为减排效果提供了依据.具体研究成果如下:大气能见度资料在空气污染研究中的适用性评估,指出在洁净干燥的环境中PM2.5可解释50%能 见度的变化，能见度可较好的作为空气质量的代用资料;但在中度污染且湿度较大时，相对湿度则主导能见度的变化，能见度对PM2.5变化不再敏感; 通过分析气象条件对2013-2018年间我国空气质量变化的相对贡献, 指出2017年PM2.5浓度相比2016年同期降低了38%，其中60%可归因于2017年有利的气象条件, 大气水平传输、垂直扩散和边界层混合几个方面导致污染过程瓦解, 揭示了新冠疫情期间在全国 PM2.5浓度显著降低背景下京津冀地区污染物浓度却仍与历史同期持平的物理机制; 以四川盆地为例，研究了1979-2020年间大气扩散条件的长期变化趋势，研究发现，川渝地区近几十年大气扩散条件处于逐渐转好的趋势，静稳天气发生频次降低，大气通风系数逐渐增强，这在一定程度上缓解了人为排放增加导致的空气污染负担.