RESUMO
Understanding the soil pollutants' net input fluxes is essential for accurate early warning of regional soil pollution. However, the traditional input-output investigation method for soil pollutants' net input fluxes is often costly, especially at the regional scale. This study first assessed the land-use effects on soil heavy metals around a typical copper smelting area in China. Next, an improved spatial source apportionment receptor model, namely robust absolute principal component scores/robust geographically weighted regression with category land-use information (RAPCS/RGWR-CLU), was proposed to apportion the net source contributions, and its performance was compared with those of RAPCS/RGWR and the traditional absolute principal component scores/multiple linear regression (APCS/MLR). Finally, the net input fluxes of soil heavy metals were determined based on RAPCS/RGWR-CLU, and its performance was compared with that of the traditional input-output investigation method. Results showed that (i) land-use effects are significant for soil As, Cu, Pb, and Zn; (ii) RAPCS/RGWR-CLU achieves higher source apportionment accuracy than RAPCS/RGWR and APCS/MLR; and (iii) the net input fluxes determined by RAPCS/RGWR-CLU have similar accuracy to those determined by the traditional input-output investigation method but with significantly lower costs. Therefore, this study provided a cost-effective solution to determine the net input fluxes of soil pollutants.