Estimating multi-annual PM2.5 air pollution levels using sVOC soil tests: Ashkelon South, Israel as a case study

Abstract

Background and aimsIn most developed countries, air pollution is monitored by stationary networks of air quality monitoring stations (AQMS). Due to high installation and maintenance costs, the number of such stations (especially those measuring particulate matter (PM) is often insufficient, placing limitations on the geographic coverage of air pollution monitoring and the accuracy of exposure assessment studies based on AQMS data. Semi-volatile organic compounds (sVOCs) often spread with PM and contribute to the PM composition when emitted into the atmosphere. As a result, sVOC concentrations in soil can help, as we hypothesize, to estimate average levels of PM air pollution in geographic areas in which PM monitoring by AQMS is sparse or unavailable. MethodsSoil samples taken around the Ashkelon-South industrial area in Israel were tested for the presence of sVOCs compounds using a standard EPA 8270C protocol. PM pollution data obtained from local AQMSs were then mutually compared with sVOC soil contamination levels observed in the same locations, using spatial interpolation methods and multivariate statistical analysis tools. ResultsPM levels in the atmosphere, estimated using sVOC soil concentrations, and adjusted for several locational attributes and average levels of other commonly monitored air pollutants, revealed a reasonably strong association with PM2.5 averages actually recorded by AQMS, helping to explain 86–88% of the observed PM variation (R2-Adj. = 0.859–0.879), depending on the model type. ConclusionsThe study confirms feasibility of obtaining reasonably accurate PM air pollution estimates using sVOC soil testing. While the costs of establishment and maintenance of a dense network of AQMS may be prohibitive, the proposed approach may help to obtain reasonably accurate PM air pollution estimates for geographic areas in which PM monitoring by AQMS is sparse or unavailable.