Downscaling of environmental indicators: A review

• Published in: The Science of the total environment Vol. 916; p. 170251
• Main Authors: Li, Shiting, Xu, Chao, Su, Meirong, Lu, Weiwei, Chen, Qionghong, Huang, Qianyuan, Teng, Yanmin
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.03.2024
• Subjects: climate change; Downscaling methods; energy; environment; environmental management; evolution; Finer-scale environmental indicators; inventories; Life cycle; Scaling transfer; Selection procedures; State of the art; statistics; Life cycle; State of the art; Finer-scale environmental indicators; Selection procedures; Scaling transfer; Downscaling methods
• ISSN: 0048-9697; 1879-1026; 1879-1026
• DOI: 10.1016/j.scitotenv.2024.170251

Environmental indicators at different scales are important for environmental management, daily life, and scientific research. Because of the lack of statistics below a national scale for many environmental indicators, scholars have developed various downscaling methods to obtain finer-scale and diverse forms of data for different environmental indicators. However, the existing downscaling methods for environmental indicators are diverse and fragmented. Here, we reviewed the downscaling methods by reclassifying the environmental indicators from a life cycle perspective into five categories: natural resources use and related attributes; material and energy consumption; environmental discharge; climate change; and environmental footprints. We first provide a general introduction to downscaling theory in the environmental field, including definitions, techniques, and evolution. We then elaborate on downscaling methods and make an inventory of the five categories of environmental indicators. We summarize the downscaling methods commonly applied to specific indicators, scale transformation, the strengths and limitations of corresponding methods, and provide specific examples. Next, we discuss ways to select or construct downscaling methods based on four principles: objective orientation, data accessibility, model feasibility, and model adjustment. Finally, we explore the future direction of downscaling and provide insights for improving downscaling for environmental indicators. In this review, we generalize and clarify the downscaling techniques for environmental indicators, which will help facilitate the appropriate selection of downscaling methods by researchers. [Display omitted] •The downscaling methods (DM) of environmental indicators (EI) are reviewed.•EI is reclassified into five categories based on the life cycle of resources.•The downscaling techniques of the five types of EI are elaborated in details.•The DM includes ratio, proxy, spatial resolution, and empirical coefficient.•Certain tips are given for facilitating the selection of DM for different EI.