Investigating the Combined Use of Enrichment Factor and Weather Research and Forecasting (WRF) Modelling for Precipitation Sample Source Identification: A Case Study in North Carolina, USA

Pollutants emitted into the air not only have local effect but can also affect areas further from the source. The goal of this study was to assess a method for identifying the sources of element pollution in rainwater using enrichment factors supported by Weather Research and Forecasting (WRF) model. In this study, we collected nineteen rainwater samples at the two locations of Durham and Chimney Ridge in North Carolina, USA in July of 2014. The samples were analyzed for pH, conductivity and levels of major ions and a range of trace elements. These data showed that the pH of precipitation ranged between 3.91 and 6.65, with an average value of 4.98. The average electrical conductivity was 15.58 and 17.7 μS/cm for rainwater collected at Durham and Chimney Ridge, respectively. The lowest concentration of the elements analyzed was for thorium (Th) with an average concentration of 0.002 ppb, whereas the highest elemental concentration was for calcium (Ca) with an average concentration of 980.3 ppb. Enrichment factors for trace elements were assessed within three different groups as: (1) rarely enriched, (2) significantly enriched, and (3) highly enriched. Copper (Cu), zinc (Zn), arsenic (As), molybdenum (Mo), silver (Ag), cadmium (Cd), and lead (Pb) were highly enriched trace elements. The wind fields acquired by the WRF model indicated the probable contamination sources. Source identification indicated that the highest contribution of elements to precipitation was from industry. The results showed that the combined use of enrichment factors and the WRF model can be used to identify the sources of pollutants in precipitation samples.