A new methodology for source apportionment of gaseous industrial emissions

Abstract

Air quality modeling (AQM) is often used to investigate gaseous pollution around industrial zones. However, thismethodology requires accurate emission inventories, unbiased AQM algorithms and realistic boundaryconditions.We introduce a new methodology for source apportionment of industrial gaseous emissions, which is based ona fuzzy clustering of ambient concentrations, along with a standard AQM approach. First, by applying fuzzyclustering, ambient concentration is expressed as a sum of non-negative contributions — each corresponding to aspecific spatiotemporal pattern (STP); we denote this method as FUSTA (FUzzy SpatioTemporal Apportionment).Second, AQM of the major industrial emissions in the study zone generates another set of STP. By comparing bothSTP sets, all major source contributions resolved by FUSTA are identified, so a source apportionment is achieved.The uncertainty in FUSTA results may be estimated by comparing results for different numbers of clusters.We have applied FUSTA in an industrial zone in central Chile, obtaining the contributions from major sourcesof ambient SO2: a thermal power plant complex and a copper smelter, and other contributions from local andregional sources (outside the AQM domain). The methodology also identifies SO2 episodes associated to emis-sions from the copper smelter.