Cargando…
Identification of heavy metal pollutants and their sources in farmland: an integrated approach of risk assessment and X-ray fluorescence spectrometry
Investigation and assessment of farmland pollution require an efficient method to identify heavy metal (HM) pollutants and their sources. In this study, heavy metals (HMs) in farmland were determined efficiently using high-precision X-ray fluorescence (HDXRF) spectrometer. The potential ecological r...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9288480/ https://www.ncbi.nlm.nih.gov/pubmed/35842500 http://dx.doi.org/10.1038/s41598-022-16177-4 |
Sumario: | Investigation and assessment of farmland pollution require an efficient method to identify heavy metal (HM) pollutants and their sources. In this study, heavy metals (HMs) in farmland were determined efficiently using high-precision X-ray fluorescence (HDXRF) spectrometer. The potential ecological risk and health risk of HMs in farmland near eight villages of Wushan County in China were quantified using an integrated method of concentration-oriented risk assessment (CORA) and source-oriented risk assessment (SORA). The CORA results showed that Cd in farmland near the villages of Liuping (LP) and Jianping (JP) posed a “very high” potential ecological risk, which is mainly ascribed to soil Cd (single potential ecological risk index ([Formula: see text] ) of Cd in villages LP and JP, [Formula: see text] = 2307 and 568 > 320). A “moderate” potential ecological risk was present in other six villages. The overall non-carcinogenic risk (hazard index (HI) = 1.2 > 1) of HMs for children in village LP was unacceptable. The contributions of HMs decrease in the order of Cr > As > Cd > Pb > Ni > Cu > Zn. The total carcinogenic risk (TCR = 2.1 × 10(–4) > 1.0 × 10(–4)) of HMs in village LP was unacceptable, with HMs contributions decreasing in the order of Cr > Ni > Cd > As > Pb. Furthermore, three source profiles were assigned by the positive matrix factorization: F1: agricultural activity; F2: geological anomaly originating from HMs-rich rocks; F3: the natural geological background. According to the results of SORA, F2 was the highest contributor to PER in village LP, up to 64.4%. Meanwhile, the contributions of three factors to HI in village LP were 19.0% (F1), 53.6% (F2), and 27.4% (F3), respectively. It is worth noting that TCR (1.2 × 10(–4)) from F2 surpassed the threshold of 1.0 × 10(–4), with an unacceptable carcinogenic risk level. As mentioned above, the HM pollutants (i.e., Cd and Cr) and their main sources (i.e., F2) in this area should be considered. These results show that an integrated approach combining risk assessments with the determination of HM concentration and identification of HM source is effective in identifying HM pollutants and sources and provides a good methodological reference for effective prevention and control of HM pollution in farmland. |
---|