HUMAN HEALTH RISK ASSESSMENT AS A TOOL FOR IMPROVING THE NATIONAL AIR QUALITY MONITORING SYSTEM

Abstract

Background. The effectiveness of an air quality monitoring network depends on its spatial and temporal representativeness and on the integration of monitoring data with exposure and health-risk assessment.

Aim. To develop a methodological approach for improving the national air quality monitoring system by integrating geospatial analysis, mathematical dispersion modelling, field measurements, and human health risk assessment.

Materials and Methods. The study was conducted in an urban agglomeration in western Ukraine. Industrial emission sources were geocoded in ArcGIS; 1-hour, 24-hour, and annual pollutant concentrations were modelled using ISC-AERMOD; health risks were assessed using standard approaches; and field measurements were performed with a mobile laboratory.

Results. Nine industrial enterprises and 283 emission sources were assessed. The modelling grid contained 1,435 receptor points. Modelled PM2.5 concentrations exceeded the WHO Air Quality Guidelines by 1.1-1.5 times. The total noncarcinogenic hazard index ranged from 1.0 to 1.86, indicating potential concern that requires pollutant- and target-organ-specific interpretation. Field concentrations ranged from 43.22 ± 0.74 to 98.70 ± 0.84 μg/m³ for PM10 and from 26.19 ± 0.54 to 86.38 ± 0.61 μg/m³ for PM2.5. Three reference-grade and three indicative automated monitoring stations were proposed.

Conclusions. Integrating dispersion modelling, field measurements, and health-risk assessment can support evidence-based placement of automated air quality monitoring stations and selection of priority pollutants for continuous monitoring.