中国主要空气污染物浓度对土地利用类型的响应关系  

The response of major air pollutants concentration to land use types in China

作　　者：刘佳雯 贾若愚 蒋玉颖 徐新良[3] 王媛[1] 孙景宽[4] 乔治[1] LIU Jiawen;JIA Ruoyu;JIANG Yuying;XU Xinliang;WANG Yuan;SUN Jingkuan;QIAO Zhi(School of Environmental Science and Engineering,Tianjin University,Tianjin 300072,China;Beijing Jingwei Hirain Technologies,Beijing 100191,China;State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;Shandong Key Laboratory of Eco-Environmental Science for Yellow River Delta,Binzhou University,Binzhou 256600,China)

机构地区：[1]天津大学环境科学与工程学院,天津300072 [2]北京经纬恒润科技股份有限公司,北京100191 [3]中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京100101 [4]滨州学院山东省黄河三角洲生态环境重点实验室,滨州256600

出　　处：《资源科学》2023年第9期1869-1883,共15页Resources Science

基　　金：国家自然科学基金项目(52270187);天津市自然科学基金项目(21JCYBJC00390);山东省黄河三角洲生态环境重点实验室开放基金。

摘　　要：【目的】人类活动改变下垫面性质,进而对空气污染物浓度的时空变化产生重要影响。探索空气污染物浓度对土地利用面积的响应关系,有利于从土地资源管理视角理解和调控空气污染。【方法】基于广义可加模型与空气污染效应贡献率指数,以10 km×10 km网格化研究2020年全国6大地区土地利用面积比例与4种主要空气污染物(PM_(2.5)、PM_(10)、O_(3)、NO_(2))年平均浓度的非线性响应关系,并对比不同土地利用面积比例对空气污染物浓度的贡献差异。【结果】(1)2020年,PM2.5、PM10区域年平均浓度最高出现在西北地区,最低出现在西南地区;NO_(2)、O_(3)在华东地区的区域年平均浓度最高,分别为25.23μg/m^(3)和102.60μg/m^(3)。(2)空气污染物浓度与网格化土地利用面积比例呈现非线性响应关系。总体上,耕地、建设用地与未利用土地网格化面积比例增加使空气污染物浓度呈上升趋势,而林地、草地则较多表现相反。(3)从空气污染效应贡献率差异来看,在空气污染物低浓度区间林地、草地所表现出的空气污染效应贡献率高,空气污染物高浓度区间耕地、建设用地则表现出较高的空气污染效应贡献率,但水域、未利用土地的空气污染效应贡献率在不同地区表现各异。【结论】在全国范围内基于地区异同进行比较,提出了网格化土地利用面积比例对空气污染可能的总体作用效果,可为研究空气污染区域联防联控及国土空间规划提供参考。[Objective] Human activities change the nature of the underlying surface, which in turn has a significant impact on the spatiotemporal changes in air pollutant concentrations. Exploring the response relationship between air pollutant concentrations and land use area is beneficial for understanding and controlling air pollution from the perspective of land resource management.[Methods] Based on the generalized additive model(GAM), this study investigated the nonlinear response relationship between the proportion of land use areas in 10 km × 10 km grids and the annual average concentrations of four main air pollutants(PM_(2.5), PM_(10), O_(3), and NO_(2)) in 2020 in the six regions of China. The study used the air pollution effect contribution index(APECI) to identify contributions contrasting different land use types to the air pollutants in different pollutant concentration ranges. [Results](1) In 2020, the highest regional annual average concentrations of PM2.5 and PM10 occurred in Northwest China and the lowest in Southwest China;NO_(2) and O_(3) had the highest regional annual average concentrations in East China, which were 25.23 μg/m^(3) and102.60 μg/m^(3), respectively.(2) Air pollutant concentrations showed a nonlinear response relationship with the proportion of grid-based land use area. Generally, the increase in the proportion of the grid areas of farmland, construction land, and unused land led to an upward trend in the air pollutant concentration, while forest land and grassland often showed the opposite.(3)With regard to the differences in APECI, forest land and grassland showed a high APECI in the low air pollutant concentration ranges, while farmland and construction land showed a high APECI in the high air pollutant concentration ranges, but the APECI of water area and unused land varied in different regions. [Conclusion] This study proposed the possible overall effect of gridded land use area proportion on air pollution based on regional differences across China, providing a reference for regi

关 键 词：空气污染物 土地利用 广义可加模型 非线性响应 空气污染效应贡献率 

分 类 号：F301.2[经济管理—产业经济] X51[环境科学与工程—环境工程]