Health for the future: spatiotemporal CA-MC modeling and spatial pattern prediction via dendrochronological approach for nickel and lead deposition

Abstract

Nonpoint source pollution (PNS) poses a significant environmental challenge owing to its adverse impacts on public health and ecological sustainability. Knowing the spatial pattern of heavy metals (HMs), one of the toxic substances, in the organization of urban space and the production of zoning decisions, both in the selection of pollution sources and living spaces, is immensely guiding today and in the future. The city of Düzce may be susceptible to public health risks attributed to the accumulation of HMs from escalating urbanization activities. This study aims to reach the reasons of PNS by modeling nickel (Ni) and lead (Pb) concentrations, their spatial distributions, and how they may be spatially in the future. For Ni and Pb toxic substances, accumulation was analyzed based on annual tree rings (ATRs) of the same species, and future predictions were made based on the complex structure of the spatial pattern. The concentrations accumulated in Picea orientalis L. ATRs between 2018 and 2023 were analyzed. Predictions of 2028 were produced according to the low > middle > high classification by dividing the space into 500 × 500 m grids via Geographic Information Systems (GIS). The accuracy of the produced model was determined as R2 = 0.9412 for Ni and R2=0.9882 for Pb. Design strategies at different scales were presented with a novel approach by examining the plan decisions of the area that reflected alarming results.