Towards comprehensive air quality management using low-cost sensors for pollution source apportionment

Abstract

Abstract Successful air quality management and control not only requires measurements of air pollution levels. It also requires information on the sources of air pollution, and their relative magnitudes and importance, to plan and enact cost-effective control measures. This paper provides an important breakthrough towards the wider and more comprehensive use of source apportionment via low-cost techniques. Low-cost sensor measurements, along with the statistical methods of Positive Matrix Factorization (PMF) and k-means clustering, were able to successfully pinpoint and quantify the main sources of pollution in three regulatory important sites (a construction site, a quarry and a roadside). The anticipated levels of pollution, which were dependent on meteorological conditions and temporal variations, were assessed. The analysis provides information crucial for successful air quality management and control at a significantly lower cost than previously achieved. The strengths and weaknesses of the methodologies used are illustrated and discussed.