Grid-Scale Regional Risk Assessment of Potentially Toxic Metals Using Multi-Source Data

Abstract

Understanding the risks posed by potentially toxic metals (PTMs) in large regions is important for environmental management. However, regional risk assessment that relies on traditional field sampling or administrative statistical data is labor-intensive, time-consuming, and coarse. Internet data, remote sensing data, and multi-source data, have the advantage of high speed of collection, and can, thereby, overcome time lag challenges and traditional evaluation inefficiencies, although, to date, they are rarely applied. To evaluate their effectiveness, the current study used multi-source data to conduct a 1 km scale assessment of PTMs in Yunnan Province, China. In addition, a novel model to simulate potentially hazardous areas, based on atmospheric deposition, was also proposed. Assessments reveal that risk areas are mainly distributed in the east, which is consistent with the distribution of mineral resources in the province. Approximately 3.6% of the cropland and 1.4% of the sensitive population are threatened. The risk areas were verified against those reported by the government and the existing literature. The verification exercise confirmed the reliability of multi-source data, which are cost-effective, efficient, and generalizable for assessing pollution risks in large areas, particularly when there is little to no site-specific contamination information.

Keywords

• fine-scale polluted risk assessment
• internet data mining
• cropland vulnerability
• human health
• heavy metals contamination
• management strategies