CCSM4/WRF-CMAQ动力降尺度预估RCP8.5情景下京津冀地区空气质量的潜在变化

目前，针对气候变化对区域空气质量影响的研究相对较少，并且多采用统计降尺度方法对全球气候模式结果进行处理.采用WRF中尺度气象模式对CCSM4气候模式的CMIP5 RCP8.5情景预估结果进行动力降尺度处理，并为CMAQ空气质量模式提供气象场；在2012年清华大学MEIC大气污染物排放清单的基础上，选取2005年作为气候现状代表年、2049-2051年作为未来气候代表年，对京津冀地区典型月份（1月、4月、7月、10月）的气象及空气质量数值模拟结果进行对比，以此预估气候变化背景下京津冀地区空气质量潜在变化.结果表明，在排放情况不变及RCP8.5情景下，未来代表年与现状代表年相比，京津冀地区以典型月份为代表的年均气象因素整体呈现温度升高，风速、相对湿度及大气边界层高度均降低的趋势；年均大气污染物浓度整体呈现升高的趋势，其中，温度升高约0.8℃，风速降低约0.11 m/s，相对湿度降低约2%，大气边界层高度降低约8 m，ρ（PM_2.5）升高约2.4 μg/m3，ρ（SO₂）升高约1.8 μg/m3，ρ（NO_x）升高约1.0 μg/m3；此外，主要的气象条件（温度、风速、相对湿度、大气边界层高度）中，风速及大气边界层高度的降低可能是造成这些大气污染物浓度变化的主要气象因素，并且风速及大气边界层高度的降低与ρ（PM_2.5）降低的相关系数分别约为-0.44和-0.26.研究显示，气候变化会对京津冀地区造成污染物浓度升高的潜在风险，同时由于现阶段缺乏可用于空气质量模式的未来排放情景数据、在线耦合模式日臻完善，在我国气候-空气质量的研究领域亟待进行更深层次的研究. 

Potential Variation of Beijing-Tianjin-Hebei Region's Air Quality in RCP8.5 Scenarios by Dynamic Downscaling Method with CCSM4/WRF-CMAQ Model

Currently, there are few studies on the relationship between climate change and air quality, and most of those which do exist adopt the method of statistical downscaling. Here, we use a dynamic downscaling method to prepare WRF initial and boundary conditions with CCSM4 output under the CMIP5 RCP8.5 scenarios, and choose MEIC 2012 Data as CMAQ input inventory data in the Beijing-Tianjin-Hebei Region. In order to explore the impacts of meteorological conditions on air quality, monthly variation characteristics of PBL height (PBLH), relative humidity (RH), wind velocity, temperature and air pollutant concentrations were analyzed and compared between forecast years (2049, 2050, 2051) and baseline year (2005). The results indicated that in the case of constant emissions and RCP8.5 scenario, the meteorological conditions would become increasingly detrimental to atmospheric pollutant dispersion. In the forecast years:annual average temperature would increase about 0.8℃; annual average wind speed, RH and PBLH would decrease about 0.11 m/s, 2% and 8 m respectively; and annual average concentrations of PM_2.5, SO₂ and NO_x would increase about 2.4, 1.8 and 1.0 μg/m3 respectively. The decline in surface wind speed and lower PBLH should be the main factors influencing the increasing trend of atmospheric pollutants; the correlation coefficients between PM_2.5 concentration and wind speed and PBLH were -0.44 and -0.26 respectively. The results indicate that climate change will affect regional air quality, but the impact intensity is still uncertain due to the lack of future emission scenarios that are used in air quality models. Furthermore, the physical/chemical mechanisms among the mutual influence process between meteorological factors and pollutant dispersion also need to be further studied.