随着经济的快速发展，环境污染问题越来越受到重视，国务院多次印发文件着重治理空气污染，旨在减少主要大气污染物排放总量，改善我国日益严重的空气质量状况，提升人民的蓝天幸福感。京津冀地区是我国大气污染治理的重点区域之一。目前我国重度及以上的空气污染天气中首要污染物主要为细颗粒物PM_2.5，北京市2035年总规中提出了PM_2.5年均35 μg/m³的目标，即达到世界卫生组织定义的第一阶段过渡性目标。为了更好地考虑气候变化和大气污染排放影响，本文引入政府间气候变化专门委员会（IPCC）面向气候变化评估报告的地球系统模式结果，采用动力降尺度的方法构建了不同气候情景下京津冀2030年未来气象场，结合当前情景下空气质量模式的模拟效果选取适用性较好的京津冀排放清单作为基准排放情景，根据总规目标设计了2030年减排排放情景，通过所构建的BNU-ESM-WRF-SMOKE-CMAQ模式系统模拟多组数值试验，研究京津冀区域2030年的PM_2.5质量浓度状况，分析其在不同未来气候情景和排放情景下的空间分布差异及时间变化，研究气象条件和人为排放条件对京津冀2030年空气质量的贡献关系。主要结论如下：

（1）京津冀区域2030年的空气质量在不同的未来气候情景及不同强度排放情景基础上，PM_2.5质量浓度仍呈现冬季高夏季低的季节性变化特征，且空间分布结果表明污染源排放量较高区域的空气质量相比污染源排放较低地区的空气质量更差，排放强度依然是决定空气污染物浓度空间分布的主导因素。

（2）根据基准排放情景试验组，即采用相同的基准排放清单，仅考虑气候变化因素，由不同未来气候情景（高碳排放RCP8.5、中碳排放RCP4.5和低碳排放RCP2.6）驱动模拟预估的京津冀2030年空气质量结果显示，气候变化对该区域研究时间段内PM_2.5质量浓度空间分布情况和年均结果引起的差异不大，且两者并非呈线性相关。气象条件变化对京津冀2030年空气质量（PM_2.5质量浓度）变化的贡献约为0.7%~5.3%，在不同的未来气候情景下，空间分布差异特征与排放清单的空间分布差异一致。

（3）基于同一碳排放强度RCP4.5气候情景下，采用不同强度排放清单的两组试验结果表明，减排排放情景下模拟预估的京津冀区域及各城市2030年PM_2.5质量浓度峰值、整体区域平均值、城市平均值均显著低于基准排放清单试验的模拟预估结果。减排情景整体区域年均PM_2.5质量浓度相较基准排放情景结果下降约47%，而京津冀具体各个省市下降比例范围在25%~57%。结果表明，在相同气象条件下，不同排放清单对京津冀未来空气质量的影响程度较高，且减排措施对京津冀2030年空气质量状况变化的贡献程度高于气象条件的贡献程度。

With the rapid development of economy, more and more attention has been paid to the problem of environmental pollution. Many documents have been published focusing on the treatment of air pollution by the State Council, aiming to reduce the total emission of major air pollutants, improve the increasingly serious air quality situation in China, and enhance people's happiness on blue sky. Beijing-Tianjin-Hebei region has been one of key areas since the air pollution control. Fine particulate matter (PM_2.5) is the most important pollutant in severe air pollution in China, and the annual average target of 35 μg/m³ of PM_2.5 is put forward in the 2035 master plan of Beijing, that is to achieve the interim target of the first stage set by the World Health Organization. In order to better consider the impact of climate change and air pollution emissions, this paper applied the results of the earth system model for climate change assessment report by the Intergovernmental Panel on Climate Change (IPCC), and used the dynamic downscaling method to build the meteorological field over Beijing-Tianjin-Hebei region in 2030 under different climate scenarios. Based on the simulation performance of the air quality model in the present meteorological field, the Beijing-Tianjin-Hebei emission inventory with better applicability was selected and combined with the 2030 emission scenarios of reduced emission intensity by the 2035 plan target, the BNU-ESM-WRF-SMOKE-CMAQ model system built was utilized to simulate multiple groups of numerical experiments to study the PM_2.5 mass concentration over Beijing-Tianjin-Hebei region in 2030, analyze the spatial distribution and temporal changes under different future climate scenarios and air pollution emission scenarios, and study the contribution of meteorological conditions and anthropogenic emission conditions on the air quality over Beijing-Tianjin-Hebei region in 2030. The following conclusions were obtained:

(1) Based on different future climate scenarios and different emission intensity scenarios, PM_2.5 mass concentration over Beijing-Tianjin-Hebei region in 2030 will vary seasonally which is high in winter and low in summer, and the spatial distribution results show that the air quality over the regions with high air pollution emission will be worse than that over the regions with low air pollution emission, and the emission intensity will still be the dominant factor to determine the spatial distribution of air pollutants concentration in the future.

(2) According to the benchmark emission scenario experiments, that was using the same benchmark emission inventory, considering only climate change factors, and driven by different future climate scenarios (high carbon emission RCP8.5, medium carbon emission RCP4.5 and low carbon emission RCP2.6), the estimated air quality results over Beijing-Tianjin-Hebei region in 2030 show that, climate change will have little effect on the spatial distribution and annual average of PM_2.5 mass concentration in the study period, and the relationship between them is not a complete linear correlation. The contribution of meteorological conditions to the air quality (PM_2.5 mass concentration) change over Beijing-Tianjin-Hebei region in 2030 will be about 0.7% - 5.3%. Moreover, under different future climate scenarios, the spatial distribution difference characteristics are consistent with the spatial distribution difference of emission inventory.

(3) Based on the same carbon emission intensity under RCP4.5 climate scenario, two experiments’ results using different intensity emission inventories show that the peak value, overall regional average value and urban average value of PM_2.5 mass concentration estimated over Beijing-Tianjin-Hebei region and each city in 2030 under the emission reduction scenario will be significantly lower than the simulated results of the benchmark emission inventory. Compared with the benchmark emission scenario, the annual average PM_2.5 mass concentration over the whole Beijing-Tianjin-Hebei region under the emission reduction scenario will decrease by about 47%, while the specific provinces and cities in Beijing, Tianjin and Hebei will decrease by 25% - 57%. The results show that under the same meteorological conditions, different emission inventories will have the strong impact on the air quality over Beijing-Tianjin-Hebei region in the future, and the contribution of emission reduction measures on the air quality over Beijing-Tianjin-Hebei region in 2030 will be higher than that of meteorological conditions.