长江中游城市群建成区绿色基础设施对PM2.5的消减效应

研究城市群建成区绿色基础设施对PM_2.5的消减效应,有助于为城市群应对气候变化采取的可持续发展战略提供理论支撑。以长江中游城市群建成区为例,基于2000—2020年建成区面积数据、土地覆盖数据以及PM_2.5数据系统分析城市群PM_2.5浓度的时空演变特征,以林地、草地、耕地、湿地、水体等5种绿色基础设施为驱动因子,采用地理探测器模型中的因子探测与交互作用探测,探索城市群建成区绿色基础设施对PM_2.5浓度的削减效应。同时,结合夜间灯光数据以及约束线方法,进一步剖析城市化水平对建成区绿色基础设施的约束效应。结果表明：(1)2000—2020年期间,长江中游城市群年均PM_2.5浓度在时序上呈现先升后降的“倒U型”趋势,在空间上呈现由西北向东南级差化递减的分异特征。(2)2000—2020年期间,长江中游城市群建成区绿色基础设施对PM_2.5存在削减效应,但历年削减率均不超过4%,其中扩张区的削减效应显著高于老城区。(3)因子探测结果表明,长江中游城市群各绿色基础设施...

Reduction effect of green infrastructure on PM2.5 in the built-up areas of urban agglomerations in the Yangtze River''s middle reaches

Studying the reduction effect of green infrastructure on PM_2.5 can provide theoretical support for sustainable development strategies to address climate change in urban agglomeration. First, taking the built-up areas of urban agglomeration in the Yangtze River''s middle reaches as an example, this study systematically examined the spatiotemporal evolution characteristics of PM_2.5 concentration in urban agglomeration from 2000 to 2020 using built-up area data, land cover data, and PM_2.5 data. Second, we took five types of green infrastructure, including woodland, grassland, cultivated land, wetland, and waters, as driving factors and employed the factor detection and interaction detection functions in the geographic detector model to explore the reduction effects of green infrastructure on PM_2.5 concentration in the built-up area of urban agglomeration. Third, this study further analyzed the constraint effect of urbanization level on green infrastructure in the built-up areas by combining nighttime lighting data and the constraint line method. The results show that:(1) during 2000-2020, the annual average PM_2.5 concentration of the urban agglomeration in the Yangtze River''s middle reaches showed an "inverted U-shaped" trend of rising and then decreasing in time series, and the spatial divergent characteristics of decreasing from the northwest to the southeast. (2) During 2000-2020, the green infrastructure in the built-up areas of the urban agglomeration in the Yangtze River''s middle reaches had a reduction effect on PM_2.5 concentration, and the reduction rate did not exceed 4%. The reduction effect of the expansion area was significantly higher than that of the old urban areas. (3) The results of factor detection showed that in the urban agglomeration in the Yangtze River''s middle reaches, the explanatory power of each green infrastructure factor on PM_2.5 concentration showed a pattern of woodland>grassland>cultivated land>wetland and waters in the old urban area and a law of woodland>grassland>cultivated land and waters>wetland in the expansion area. The results of interaction detection showed that woodland and wetland, woodland and grassland, and woodland and waters were the most significant interaction combinations to reduce PM_2.5 concentration, and their interaction explanatory power reached above 0.5 in both the old urban area and the expansion area. (4) The reduction effect of green infrastructure on PM_2.5 concentration in the built-up areas of the urban agglomeration in the Yangtze River''s middle reaches was constrained by the urbanization level. The shape of the constraint line was exponential in both the old urban area and the expansion area. This study can provide a basis for the implementation of Natural Climate Solutions (NCS) at the urban agglomeration scale.