Abstract
Land use regression (LUR) models are mainly used for the simulation and prediction of conventional atmospheric pollutants. Whether the LUR models can be expanded to study more toxic and hazardous pollutants (such as heavy metals) remains to be verified. Combined with the factors of road, land use type, population, pollution enterprise, meteorology, and terrain, the LUR models were used to simulate the spatial distribution characteristics of heavy metals in road dust and determine the main influencing factors. Samples of road surface dust were collected from 144 evenly distributed points in Tianjin, China, with 108 modelling points and 36 verification points. The R2 values of the LUR models of Cd, Cr, Cu, Ni, and Pb contents were 0.301, 0.412, 0.399, 0.496, and 0.377, and their error rates were 2.72%, 4.96%, 4.64%, 8.91%, and 4.94%, respectively. The error rates of the kriging interpolation models were 3.33%, 6.50%, 5.14%, 18.30%, and 22.87%, which were all greater than those of the LUR models. The estimation effect of the LUR models was more refined than that of the kriging interpolation models. The contents of most heavy metals (except Ni) in road dust of the central area in Tianjin were generally higher than those of the surrounding areas. The heavy metal contents in road dust of Tianjin were mainly affected by road variables and meteorological variables. The LUR models were suitable for small-scale spatial prediction of heavy metals in urban road dust within urban areas.
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The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
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This work was financially supported by the National Natural Science Foundation of China (NSFC) (Grant No. 41301221).
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BH and XY conceived the idea; BH and TA organized the data and designed the model; JZ and XY performed the data analysis and interpretation; BH, XY, and TA wrote the paper and provided feedback to all authors. All authors read and approved the final manuscript.
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Yuan, X., An, T., Hu, B. et al. Analysis of spatial distribution characteristics and main influencing factors of heavy metals in road dust of Tianjin based on land use regression models. Environ Sci Pollut Res 30, 837–848 (2023). https://doi.org/10.1007/s11356-022-22151-4
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DOI: https://doi.org/10.1007/s11356-022-22151-4