LI Jun, YANG Yunqin, TAI Xisheng, et al. Contamination evaluation and source apportionment of heavy metals from Kushui Rose growing soils[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(16): 223-234. DOI: 10.11975/j.issn.1002-6819.202306055
    Citation: LI Jun, YANG Yunqin, TAI Xisheng, et al. Contamination evaluation and source apportionment of heavy metals from Kushui Rose growing soils[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(16): 223-234. DOI: 10.11975/j.issn.1002-6819.202306055

    Contamination evaluation and source apportionment of heavy metals from Kushui Rose growing soils

    • Typical agricultural products depend mainly on the accurate identification of the contamination characteristics and their sources of heavy metals in soil. It is of great significance to effectively promote the sustainable development of special crops in the rural revitalization and characteristic industry. This investigation was focused on the rose-growing soils in Kushui Town, Yongdeng County, Lanzhou City, Gansu Province, China. A comparative analysis was performed on the combination of the Nemerow pollution index, pollution load index, and the improved matter-element extension model. The pollution levels were quantified for the eight soil heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn). A positive matrix factorization model was also applied to apportion the sources of soil heavy metal pollution. The results showed that: 1) The mean concentrations of As, Cd, Cu, Ni, Pb, and Zn in the study area exceeded their corresponding soil background values of Lanzhou City and Gansu Province, except for Hg and Cr. Specifically, the average levels of Zn, Cr, Ni, Cu, Pb, As, Cd, and Hg in soils exceeded their soil background values of Lanzhou City by 1.43, 1.04, 1.23, 1.34, 1.19, 1.36, 1.41, and 0.73 fold, respectively, while surpassed their background levels of Gansu Province by 1.16, 0.94, 1.06, 1.22, 1.37, 1.13, 2.08, and 1.02 fold, respectively. However, the concentrations of all the elements were lower than the standard values of the Soil environmental quality Risk control standard for soil contamination of agricultural land (Trial) (GB 15618-2018) (pH value >7.5). 2) The matter-element extension model showed that there were 59 (60.82%) samples with a still clean state, 35 (36.08%) samples with mild pollution, and 3 (3.1%) samples with moderate pollution. Overall, the soils were in a still clean state in the study region. Moreover, the Nemerow integrated pollution index (NPI) values in soils ranged from 0.71 to 2.02 with a mean value of 1.41, indicating slight pollution. Specifically, approximately 4.12% of the sampled sites were warning limit, 94.85% of sites reached slight pollution, and only 1.03% of the sampled sites were moderate pollution. In addition, the pollution load index (PLI) values were between 0.64 and 1.48 with a mean value of 1.17 for the heavy metals in soils, indicating slight pollution. In detail, 11.34% and 88.66% of PLI values were less than 1 and within the scope of 1-2, respectively, indicating a clean and slight pollution. The evaluation with the improved matter-element extension model was basically consistent with that of the NPI and PLI. Nevertheless, the improved matter-element extension model was more practical and instructive. 3) The sources of soil heavy metals were complicated in the study area. Hg was primarily affected by both Industrial-coal-fired activities and traffic emissions; Cd was impacted by agricultural sources; Zn was mainly affected by a mixture of agricultural activities and traffic emissions; and As, Cr, Cu, Ni, and Pb were mainly influenced by the atmospheric deposition originated from industrial activities. The findings can provide a scientific theoretical basis for the risk control of heavy metal contamination in soils, particularly in the high-quality and sustainable development of the Kushui rose industry.
    • loading

    Catalog

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return