Construction and Dynamic Method of Soil Fugitive Dust Emission Inventory with High Spatial Resolution in Beijing-Tianjin-Hebei Region
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摘要: 土壤扬尘是我国北方地区广泛存在的颗粒物污染来源，由于其分布广、数量大，活动水平获取困难，难以系统构建区域层面的高时空分辨率排放清单，不利于土壤扬尘源的影响评估与管控策略的制定.以2017年为基准年，通过对Landsat 8卫星的30 m分辨率遥感影像解译获取高空间分辨率的土壤扬尘源活动水平，结合空间差异化的土壤质地与气象资料，构建了京津冀地区2017年各季节高空间分辨率土壤扬尘排放清单，结合气象参数，将各季节清单结果合理分配至逐月，并与环境受体观测数据印证了结果的可靠性.结果表明：①京津冀地区土壤扬尘排放源面积比例呈冬季>春季>秋季>夏季的特征，分别为65%、59%、57%与33%.就全年平均而言，张家口市和承德市较高，分别为64%与58%；北京市和天津市较低，分别为42%与43%；其余城市差异不显著.②京津冀地区2017年土壤扬尘排放PM2.5、PM10和TSP分别为6.5×104、31.0×104和103.4×104 t.③季节尺度上，土壤扬尘排放量呈春季>冬季>秋季>夏季的特征；城市尺度上，邢台市、邯郸市、张家口市及承德市的全年排放较高，廊坊市和秦皇岛市全年排放较低.全年单位面积排放较高值出现在张家口市以及邯郸市和邢台市的西部地区.研究显示，京津冀土壤扬尘排放具有较大时空分布差异，逐月分配清单可为扬尘重点管控月份提供数据支撑，土壤扬尘清单较高的空间分辨率也为城市重点区域差异化管理提供基础.Abstract: Soil fugitive dust is a widespread source of particulate pollution in northern China. Due to its wide distribution, large quantity and difficulty in obtaining activity levels, a regional high-temporal resolution emission inventory is difficult to be systematically constructed, which is not conducive to the development of impact assessment and management and control strategies of soil dust sources. This study obtains high spatial resolution soil dust source activity levels through the interpretation of the 30 m resolution remote sensing image of the Landsat 8 satellite, and combines spatially differentiated soil texture and meteorological data to construct a high-spatial resolution soil fugitive dust emission inventory for each season in the Beijing-Tianjin-Hebei Region in 2017. The emission inventory combines the meteorological parameters, reasonably allocates the results of each season inventory month by month, and confirms the reliability of the results with the environmental receptor observation data. The results show that: (1) The proportion of soil dust emission area in the Beijing-Tianjin-Hebei Region is winter > spring > autumn > summer, which were 65%, 59%, 57% and 33%, respectively. In terms of the annual average state, Zhangjiakou and Chengde are relatively high, with 64% and 58%, Beijing and Tianjin were relatively low, with 42% and 43%, respectively, and the overall gap in the remaining cities is not obvious. (2) The PM2.5, PM10 and TSP emissions from the soil fugitive dust are 6.5×104, 31.0×104 and 103.4×104 t, respectively. (3) On the seasonal scale, the emission of soil dust is spring > winter > autumn > summer. On the urban scale, Xingtai, Handan, Zhangjiakou and Chengde City have higher annual emissions, while Langfang and Qinhuangdao City have lower annual emissions. The highest annual emissions per unit area occur in Zhangjiakou City and the western regions of Handan and Xingtai City. The results show that there is a significant difference in the spatial and temporal distribution of soil dust emissions in the Beijing-Tianjin-Hebei Region. The monthly distribution inventory can provide data support for the control of soil fugitive dust emissions in key months, and the high spatial resolution can also provide a basis for the differentiated management of key urban areas.
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图 1 京津冀地区各城市面积及土壤扬尘排放源面积占比
Figure 1. The urban area and the proportion of soil fugitive dust emission sources in Beijing-Tianjin-Hebei Region
图 2 京津冀地区土壤风蚀指数分布
Figure 2. Distribution of soil wind erosion index in Beijing-Tianjin-Hebei Region
图 3 京津冀地区植被覆盖指数不同区间占比及植被覆盖因子
Figure 3. The percentage of different intervals of the vegetation coverage index and vegetation coverage factor in Beijing-Tianjin-Hebei Region
图 4 2017年京津冀地区全年土壤扬尘PM2.5排放量分布情况
Figure 4. Distribution of annual PM2.5 emission of soil fugitive dust in Beijing-Tianjin-Hebei Region in 2017
图 5 2017年京津冀地区各季节土壤扬尘PM2.5排放量分布情况
Figure 5. Distribution of PM2.5 emissions of soil fugitive dust in each season in Beijing-Tianjin-Hebei Region in 2017
图 6 京津冀地区各城市逐月土壤扬尘PM2.5排放量情况
Figure 6. Monthly PM2.5 emissions of soil fugitive dust in Beijing-Tianjin-Hebei Region
图 7 不同城市、不同季节PM2.5~10浓度与土壤扬尘PM2.5排放强度散点图
Figure 7. Scatter plot of PM2.5-10 concentrations and PM2.5 emission intensity of soil fugitive dust in different cities and seasons
表 1 京津冀地区各季节气候因子值
Table 1. Seasonal climate factors in the Beijing-Tianjin-Hebei Region
10-6 城市 春季 夏季 秋季 冬季 全年 天津市 43 501 937 1 881 4 191 50 510 北京市 14 930 184 1 083 1 949 18 147 唐山市 31 044 620 2 089 1 815 35 568 秦皇岛市 6 299 160 1 259 1 497 9 215 承德市 9 421 134 1 229 842 11 627 张家口市 33 434 1 664 1 381 8 429 44 908 廊坊市 19 368 775 495 1 236 21 874 保定市 12 972 231 366 884 14 453 邢台市 35 334 3 551 14 965 32 432 86 282 沧州市 64 213 1 417 3 238 5 476 74 344 衡水市 19 548 693 404 1 272 21 917 石家庄市 11 053 389 394 2 132 13 968 邯郸市 33 633 2 332 11 118 25 522 72 605 京津冀地区 25 750 1 007 3 069 6 744 36 571 
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表 2 基于气象因素的季度排放量分配系数
Table 2. Distribution coefficient of quarterly emissions based on meteorological factors
城市 春季 夏季 秋季 冬季 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月 1月 2月 天津市 0.26 0.40 0.34 0.92 0.05 0.03 0.42 0.01 0.58 0.34 0.35 0.31 北京市 0.46 0.46 0.08 0.49 0.44 0.07 0.38 0.01 0.61 0.30 0.30 0.40 唐山市 0.27 0.42 0.31 0.56 0.41 0.03 0.42 0.01 0.57 0.42 0.19 0.39 秦皇岛市 0.42 0.55 0.03 0.89 0.04 0.07 0.29 0.03 0.68 0.34 0.36 0.30 承德市 0.32 0.56 0.11 0.46 0.37 0.17 0.37 0.03 0.60 0.30 0.26 0.44 张家口市 0.41 0.54 0.05 0.41 0.27 0.32 0.01 0.01 0.98 0.40 0.29 0.31 廊坊市 0.39 0.42 0.20 0.62 0.10 0.28 0.29 0.01 0.70 0.25 0.27 0.48 保定市 0.18 0.39 0.43 0.83 0.13 0.04 0.35 0.01 0.64 0.39 0.24 0.37 邢台市 0.86 0.09 0.06 0.49 0.07 0.44 0.52 0.01 0.47 0.40 0.20 0.40 沧州市 0.33 0.52 0.15 0.93 0.06 0.01 0.48 0.01 0.51 0.32 0.25 0.43 衡水市 0.35 0.43 0.22 0.70 0.24 0.06 0.40 0.00 0.60 0.43 0.22 0.35 石家庄市 0.59 0.15 0.27 0.87 0.10 0.03 0.56 0.00 0.44 0.45 0.26 0.29 邯郸市 0.87 0.08 0.05 0.45 0.07 0.49 0.34 0.01 0.66 0.36 0.26 0.38
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表 3 京津冀地区各季节土壤扬尘PM2.5排放强度
Table 3. Emission intensity of each city and season in Beijing-Tianjin-Hebei Region
城市 土壤扬尘PM2.5排放强度/(t/km2) 春季 夏季 秋季 冬季 平均值 保定市 0.212 0.001 0.008 0.011 0.058 沧州市 0.642 0.011 0.033 0.048 0.183 承德市 0.198 0.001 0.062 0.017 0.069 邯郸市 0.414 0.016 0.186 0.258 0.218 衡水市 0.179 0.003 0.008 0.013 0.051 廊坊市 0.165 0.004 0.007 0.010 0.046 秦皇岛市 0.087 0.001 0.029 0.019 0.034 石家庄市 0.152 0.002 0.006 0.025 0.046 邢台市 0.457 0.018 0.200 0.323 0.250 张家口市 0.700 0.012 0.069 0.163 0.236 北京市 0.261 0.001 0.042 0.029 0.083 天津市 0.384 0.005 0.021 0.035 0.111 唐山市 0.307 0.000 0.028 0.016 0.088 京津冀地区 0.320 0.006 0.054 0.074 0.113
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