Impact of Climate Change on Aerosol Concentrations in Eastern China Based on Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) Datasets
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摘要: 气候变化引起的地面气溶胶浓度变化与区域空气质量密切相关。本文利用“国际大气化学—气候模式比较计划”(Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP)中4个模式的试验数据分析了RCP8.5情景下2000~2100年气候变化对中国气溶胶浓度的影响。结果显示,在人为气溶胶排放固定在2000年、仅考虑气候变化的影响时,2000~2100年气候变化导致中国北部地区(31°N~45°N, 105°E~122°E)硫酸盐、有机碳和黑碳气溶胶分别增加28%、21%和9%,硝酸盐气溶胶在中国东部地区减少30%。气候变化对细颗粒物(PM2.5)浓度的影响有显著的季节变化特征,冬季PM2.5浓度在中国东部减少15%,这主要是由硝酸盐气溶胶在冬季的显著减少造成的;夏季PM2.5浓度在中国北部地区增加16%,而长江以南地区减少为9%,这可能与模式模拟的未来东亚夏季风环流的增强有关。Abstract: Changes in surface layer aerosol concentrations induced by climate change are important for understanding regional air quality. In this study, the impact of climate change on surface-layer aerosol concentrations over East Asia were investigated using multi-model results from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) under the RCP8.5 scenario during 2000-2100. With anthropogenic emissions of aerosols and aerosol precursors kept at year 2000 levels, the annual mean concentrations of surface-layer sulfate, organic carbon, and black carbon over northern China (31°N-45°N, 105°E-122°E) were simulated to increase by 28%, 21%, and 9%, respectively, owing to climate change over 2000-2100. Compared to that in 2000, annual mean surface-layer nitrate concentration in 2100 over eastern China was simulated to decrease by 30% by climate change alone. The climate-induced changes in fine particulate matter (PM2.5) concentrations were simulated to have large seasonal variation. Due to significant decreases in nitrate concentrations in the winter, wintertime PM2.5 concentrations over eastern China were simulated to decrease by 15% over 2000-2100. Furthermore, the changes in summertime PM2.5 concentrations during 2000-2100 were found to have different patterns in northern and southern China; PM2.5 concentrations in northern China would increase by 16%, while those in southern China would decrease by 9%.
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图 1 中国气象局大气成分观测网站点分布和本文研究区域。三角形代表观测站点位置,研究区域包括中国北部(31°N~45°N, 105°E~122°E)、南部(20°N~31°N, 105°E~122°E)和东部地区(北部+南部,20°N~45°N, 105°E~122°E)
Figure 1. Geographic locations of observational sites (triangles) in China Meteorological Administration Atmosphere Watch Network (CAWNET) and the study domains of northern China (31°N-45°N, 105°E-122°E), southern China (20°N-31°N, 105°E-122°E), and eastern China (20°N-45°N, 105°E-122°E)
图 2 多模式平均的当前气候态下不同季节气溶胶地表浓度(单位:μg m-3)的空间分布:(a)硫酸盐,(b)硝酸盐,(c)铵盐,(d)有机碳,(e)黑碳,(f)PM2.5
Figure 2. The present-day multi-model and seasonal mean surface-layer concentrations (units: μg m-3) of aerosols over East Asia: (a) Sulfate, (b) nitrate, (c) ammonium, (d) organic carbon, (e) black carbon, (f) PM2.5 (fine particulate matter)
图 4 模式模拟的(左列)和NCEP再分析资料的(右列)中国地区年平均(a)温度(单位:℃)、(b)绝对湿度(单位:g kg-1)、(c)降水(单位:mm d-1)和(d)850 hPa风场(单位:m s-1)的分布
Figure 4. Distributions of annual mean (a) surface temperature (units: ℃), (b) specific humidity (units: g kg-1), (c) precipitation (units: mm d-1), and (d) 850-hPa wind (units: m s-1) over China from ACCMIP models (left column) and NCEP data (right column)
图 5 ACCMIP模式模拟的RCP8.5情景下2000~2100年中国季节平均的(a)温度(单位:℃)、(b)绝对湿度(单位:g kg-1)、(c)降水(单位:mm d-1)和(d)850 hPa风场(单位:m s-1)的变化特征。(a)温度和(b)绝对湿度的变化全部通过了95%信度水平检验(t检验),(c)降水变化图中打点区域表示通过了95%信度水平检验
Figure 5. ACCMIP models-simulated changes in seasonal mean (a) surface temperature (units: ℃), (b) specific humidity (units: g kg-1), (c) precipitation (units: mm d-1), and (d) 850-hPa wind (units: m s-1) over China during 2000-2100 under the RCP8.5 scenario. Projected changes in surface temperature in Fig. a and specific humidity in Fig. b are all statistically significant at the 95% confidence level based on the Student's t test. The dotted areas in Fig. c represent statistically significant changes at the 95% confidence level based on the Student's t test
图 6 ACCMIP模式模拟的RCP8.5情景下2000~2100年气候变化导致的中国地区人为气溶胶各季节地表浓度的变化(单位:μg m-3):(a)硫酸盐,(b)硝酸盐,(c)铵盐,(d)有机碳,(e)黑碳,(f)PM2.5。打点区域表示偏差通过了95%信度水平检验(t检验)
Figure 6. ACCMIP models-simulated changes in seasonal mean surface-layer concentrations (units: μg m-3) of aerosols over China during 2000-2100 induced by the projected climate change under the RCP8.5 scenario: (a) Sulfate, (b) nitrate, (c) ammonium, (d) organic carbon, (e) black carbon, (f) PM2.5. The dotted areas represent statistically significant values at the 95% confidence level based on the Student's t test
图 7 ACCMIP模式模拟的2000~2100年气候变化导致的中国地区人为气溶胶年平均地表浓度的变化(单位:μg m-3):(a)硫酸盐,(b)硝酸盐,(c)铵盐,(d)有机碳,(e)黑碳,(f)PM2.5。打点区域表示偏差通过了95%信度水平检验(t检验)
Figure 7. ACCMIP models-simulated changes in annual mean surface-layer concentrations (units: μg m-3) of aerosols over China during 2000-2100 induced by the projected climate change under the RCP8.5 scenario: (a) Sulfate, (b) nitrate, (c) ammonium, (d) organic carbon, (e) black carbon, (f) PM2.5. The dotted areas represent statistically significant values at the 95% confidence level based on the Student's t test
表 1 所选ACCMIP模式的基本信息
Table 1. Description of the ACCMIP (Atmospheric Chemistry and Climate Model Intercomparison Project) models used in this study
研究中心 模式名称 气溶胶成分 分辨率(经度×纬度) 参考文献 GFDL GFDL-AM3 SO4, NO3, BC, POM, SOA, Dust 2°×2.5° Donner et al.(2011) GISS GISS-E2-R SO4, NO3, BC, POM, SOA, Dust 2°×2.5° Koch et al.(2006) UKMO HadGEM2 SO4, BC, POM, SOA, Dust 1.24°×1.87° Collins et al.(2011) NIES MIROC-CHEM SO4, BC, POM, SOA, Dust 2.8°×2.8° Watanabe et al.(2011) 注:SO4、NO3、NH4、BC、POM、SOA、Dust分别代表硫酸盐、硝酸盐、铵盐、黑碳、一次有机气溶胶、二次有机气溶胶和沙尘。GFDL,GISS,UKMO,NIES分别表示美国Geophysical Fluid Dynamics Laboratory,美国Goddard Institute for Space Studies,英国Met Office,日本National Institute for Environmental Studies。 表 2 ACCMIP模式模拟的各成分气溶胶地表浓度以及与观测的相对偏差
Table 2. Surface-layer aerosol concentrations from the models and normalized mean biases relative to observations
模式 硫酸盐浓度 硝酸盐浓度 铵盐浓度 有机碳浓度 黑碳浓度 模拟/μg m−3 归一化平均偏差 模拟/μg m−3 归一化平均偏差 模拟/μg m−3 归一化平均偏差 模拟/μg m−3 归一化平均偏差 模拟/μg m−3 归一化平均偏差 GFDL-AM3 8.07 −67.67% 0.95 −91.49% 4.64 −45.70% 5.94 −75.59% 1.32 −77.87% GISS-E2-R 5.33 −78.64% 3.09 −72.45% 1.88 −77.99% 7.01 −71.19% 1.53 −74.46% HadGEM2 5.70 −77.18% 4.78 −80.34% 2.46 −58.88% MIROC-CHEM 3.69 −85.22% 4.69 −80.74% 1.23 −79.39% 平均 5.70 −77.18% 2.02 −81.97% 3.26 −61.85% 5.60 −76.96% 1.63 −72.65% 注:归一化平均偏差定义为: $\sum\nolimits_{i = 1}^n {\left( {{x_i} - {y_i}} \right)} /\sum\nolimits_{i = 1}^n {{y_i} \times 100\% } $ ,xi和yi分别代表不同站点的模拟值和观测值。 -
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