Multivariate geostatistical methods for analysing the contribution of urban lakes and neighbouring greenery to mitigating PM2.5 under stressor indicators
Han Liu , Wenyu An , Arkadiusz Przybysz , Dingyi Hao , Yimei Sun , Junze Song , Jiayi Sui , Jiahan Sun , Chunyang Zhu
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引用次数: 0
Abstract
Maintaining the ecological integrity and functionality of ecosystems is one of the major challenges faced in the sustainable management of natural capital. Urban areas play a key role in this setting, providing multiple ecosystem services for a rapidly growing urban population worldwide while under constant pressure from several interacting natural and anthropogenic stressors. This paper targets the critical knowledge gap concerning how different stressor indicators – traffic (TD), building density (BD), building height (BH), percentage of impervious surface (PLAND_I) and land surface temperature (LST) – and their interactions affect the removal of particulate matter (PM2.5) by urban blue-green infrastructure at multiple spatial scales. With spatial ranges varying with the area of blue-green infrastructure, the results showed that within the small-scale spatial range (90–450 m) the stressors LST, TD, PLAND_I and their interactions had a significant impact on PM2.5; in the mesoscale spatial range (240–600 m), the stressors LST, TD, BH, PLAND_I, BD and their interactions had a strong impact on PM2.5; while in the large-scale spatial range (390–1200 m), stressors of TD, PLAND_I, LST, BH and their interactions had a significant impact on PM2.5. Additionally, several spatial structures of PM2.5-stressor interactions were found, especially with larger lakes (exceeding 67.6 ha), which were dominated by negative correlations, which is singularity attributed to their greater capacity for PM2.5 accumulation and microclimatic regulation and may mitigate the influence of stress factors. Importantly, this study confirmed that interactive stressors contributed more to the GAM model. Thus, overlooking interactive stressors may lead to an overestimation of PM removal by urban blue-green infrastructure. Regarding the spatial interactions of stressors-PM at multiple scales, spatial range conditions can change the properties of the blue-green infrastructure that determine the effective PM accumulation and identify the crucial stressor indices. A framework was developed to address the stressors’ mode of action and the extent to which the combined stressors affect PM mitigation. It allows the scientific community and relevant stakeholders to evaluate which stressors and their interactions in relation to PM removal share a common spatial pattern, and to assess independently the spatial covariation between stressors and PM removal at different spatial scales. It also demonstrates the possibility of using these stressor indicators as potential predictors of the impacts of land-use intensity on PM mitigation.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.