Chemical Fingerprints and Source Profiles of PM10 and PM2.5 from Agricultural Soil in a Typical Polluted Region of Northwest China

  • Yaochuang Yu
  • , Junji Cao

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Analysis of the chemical source profiles of agricultural soil dust (SD) can help accurately assess and apportion the contribution of agricultural sources to atmospheric particulate matter (PM). This study quantitatively analysed twenty-four elements, eight water-soluble ions, organic carbon (OC) and elemental carbon (EC) in PM10 and PM2.5 samples from agricultural resuspended SD to understand the chemical profiles of agricultural SD in Baoji city, Northwest China. The results showed that the elemental compositions in the PM10 and PM2.5 size fractions contributed 40.18% and 39.6%, respectively, followed by water-soluble ions (3.85% in PM10 and 6.62% in PM2.5) and carbonaceous fractions (3.46% in PM10 and 2.36% in PM2.5). The reconstructed crustal matter estimated from Al, Si, Ca, Ti, and Fe concentrations accounted for 79.58% and 78.8% of the total PM10 and PM2.5, respectively, indicating that crustal matter may be the most significant contributor to agricultural SD PM10 and PM2.5 mass. Agricultural SD was influenced not only by the long-range transport of Asian dust but also by local anthropogenic sources. Higher Sc, As, Ca2+, NO3, and NH4+ in PM2.5 indicated that agricultural SD was strongly influenced by anthropogenic industrial and agricultural activities. The ratios of Si/Al, Ca/Al, K/Al, Fe/Al, and Ti/Fe in Baoji samples are basically consistent with those of Asian dust, indicating that the long-range transport of Asian dust had an important impact on the elemental composition of agricultural SD. Source identification found that higher NH4+/Al, NO3/Ca2+, NO3/SO42– ratios, and OC can be considered possible source indicators.

Original languageEnglish
Article number220419
JournalAerosol and Air Quality Research
Volume23
Issue number6
DOIs
StatePublished - Jun 2023

Keywords

  • Agricultural soil dust
  • Chemical source profiles
  • PM2.5 emission
  • Source tracing and apportionment

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