Abstract
With the rapid economic development, potentially toxic elements (PTEs) are continuously migrating, transforming, and enriching in farmland through atmospheric deposition and other media, posing threats to food security and human health. At present, there are few quantitative studies on the health risks of PTEs sources in farmland. In this study, absolute principal component score-multiple linear regression (APCS-MLR) receptor model was used to quantify the pollution sources of PTEs in farmland in Suzhou of Yangtze River Delta Economic Zone, China. Combined with geoaccumulation index (Igeo) and health risk assessment model, the source risk of PTEs was further quantified. The results show that Cd has reached the level of unpolluted to moderate polluted (0 < Igeo < 1); the total hazard index (THI) and total carcinogenic risk (TCR) index of PTEs are acceptable for adults, but not for children (THI > 1, TCR > 1 × 10−4). The results of APCS-MLR source apportionment were industrial sources (25.65%), agricultural sources (20.00%), traffic sources (16.81%), and domestic pollution sources (9.71%). The Igeo values of all pollution sources were less than 0, and no ecological risk was caused. The contribution patterns of pollution sources to THI and TCR in adults and children are similar. Industrial pollution sources pose the greatest non-carcinogenic risk to humans, accounting for 47.35% and 47.26% of adults and children, respectively; for carcinogenic risks, domestic pollution sources contribute the most among all identified pollution sources, accounting for 27.71% and 27.73% of adults and children, respectively. In general, this study emphasizes the need to strengthen the supervision of industrial pollution sources and domestic pollution sources in the study area to reduce the health risks to children.
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Burges A, Epelde L, Garbisu C (2015) Impact of repeated single-metal and multi-metal pollution events on soil quality. Chemosphere 120:8–15. https://doi.org/10.1016/j.chemosphere.2014.05.037
Cheng G, Wang M, Chen Y, Gao W (2020) Source apportionment of water pollutants in the upstream of Yangtze River using APCS–MLR. Environ Geochem Health 42:3795–3810. https://doi.org/10.1007/s10653-020-00641-z
China Environmental Monitoring Station (1990) Background Values of Soil Elements in China. China Environmental Science Press
Fei X, Xiao R, Christakos G, Langousis A, Ren Z, Tian Y, Lv X (2019) Comprehensive assessment and source apportionment of heavy metals in Shanghai agricultural soils with different fertility levels. Ecol Indic 106:105508. https://doi.org/10.1016/j.ecolind.2019.105508
Gholizadeh MH, Melesse AM, Reddi L (2016) Water quality assessment and apportionment of pollution sources using APCS–MLR and PMF receptor modeling techniques in three major rivers of South Florida. Sci Total Environ 566–567:1552–1567. https://doi.org/10.1016/j.scitotenv.2016.06.046
Guan Q, Wang F, Xu C, Pan N, Lin J, Zhao R, Yang Y, Luo H (2017) Source apportionment of heavy metals in agricultural soil based on PMF: a case study in Hexi Corridor, northwest China. Chemosphere 193(1):189–197. https://doi.org/10.1016/j.chemosphere.2017.10.151
Guney M, Zagury GJ, Dogan N, Onay TT (2010) Exposure assessment and risk characterization from trace elements following soil ingestion by children exposed to playgrounds, parks and picnic areas. J Hazard Mater 182:656–664. https://doi.org/10.1016/j.jhazmat.2010.06.082
Harel O (2009) The estimation of R2 and adjusted R2 in incomplete data sets using multiple imputation. J Appl Stat 36(10):1109–1118. https://doi.org/10.1080/02664760802553000
Hu Y, Cheng H (2016) A method for apportionment of natural and anthropogenic contributions to heavy metal loadings in the surface soils across large-scale regions. Environ Pollut 214:400–409. https://doi.org/10.1016/j.envpol.2016.04.028
Hu X, Zhang Y, Luo J et al (2011) Bioaccessibility and health risk of arsenic, mercury and other metals in urban street dusts from a mega-city, Nanjing, China. Environ Pollut 159:1215–1221
Jiang Y, Gui H, Chen C, Wang C, Zhang Y, Huang Y, Yu H, Wang M, Fang H, Qiu H (2021) The characteristics and source analysis of heavy metals in the sediment of water area of urban scenic: a case study of the Delta Park in Suzhou City, Anhui Province, China. Pol J Environ Stud 30(3):2127–2136. https://doi.org/10.15244/pjoes/127279
Jin G, Fang W, Shafi M, Wu D, Li Y, Zhong B, Ma J, Liu D (2019) Source apportionment of heavy metals in farmland soil with application of APCS-MLR model: a pilot study for restoration of farmland in Shaoxing City Zhejiang, China. Ecotoxicol Environ Saf 184:109495. https://doi.org/10.1016/j.ecoenv.2019.109495
Latif MT, Ngah SA, Dominick D, Razak IS, Guo X, Srithawirat T, Mushrifah I (2015) Composition and source apportionment of dust fall around a natural lake. J Environ Sci 33:143–155. https://doi.org/10.1016/j.jes.2015.02.002
Li Y, Mei L, Zhou S, Jia Z, Wang J, Li B, Wang C, Wu S (2018) Analysis of historical sources of heavy metals in Lake Taihu based on the positive matrix factorization model. Int J Environ Res Public Health 15:1540. https://doi.org/10.3390/ijerph15071540
Li Y, Zhou S, Liu K, Wang G, Wang J (2020) Application of APCA-MLR receptor model for source apportionment of char and soot in sediments. Sci Total Environ 746(4):141165. https://doi.org/10.1016/j.scitotenv.2020.141165
Li Y, Zhou S, Jia Z, Liu K, Wang G (2021a) Temporal and spatial distributions and sources of heavy metals in atmospheric deposition in western Taihu Lake China. Environ Pollut 284:117465. https://doi.org/10.1016/j.envpol.2021.117465
Li Q, Zhang J, Wen G, Peng S, Han Y, Qiu H, Zhou S (2021b) Geochemical baseline establishment and source-oriented ecological risk assessment of heavy metals in lime concretion black soil from a typical agricultural area. Int J Environ Res Public Health 18:6859. https://doi.org/10.3390/ijerph18136859
Lowenthal DH, Rahn KA (1987) A quantitative assessment of source contributions to inhalable particulate matter pollution in Metropolitan Boston. Atmos Environ 21(1):257–259. https://doi.org/10.1016/0004-6981(87)90290-3
Ma W, Tai L, Qiao Z, Zhong L, Wang Z, Fu K, Chen G (2018) Contamination source apportionment and health risk assessment of heavy metals in soil around municipal solid waste incinerator: a case study in North China. Sci Total Environ 631–632:348–357. https://doi.org/10.1016/j.scitotenv.2018.03.011
Pourret O, Bollinger J, Hursthouse A (2019) Heavy metal: a misused term? Acta Geochim 40(3):466–471. https://doi.org/10.1007/s11631-021-00468-0
Pourret O, Hursthouse A (2019) It's time to replace the term ''heavy metals'' with ''potentially toxic elements'' when reporting environmental research. Int J Environ Res Public Health 16 (22). https://doi.org/10.3390/ijerph16224446
Shao D, Zhan Y, Zhou W, Zhu L (2016) Current status and temporal trend of heavy metals in farmland soil of the Yangtze River Delta Region: field survey and meta-analysis. Environ Pollut 219:329–336. https://doi.org/10.1016/j.envpol.2016.10.023
She S, Hu B, Zhang X, Shao S, Jiang Y, Zhou L, Shi Z (2021) Current status and temporal trend of potentially toxic elements pollution in agricultural soil in the Yangtze River Delta Region: a meta-analysis. Int J Environ Res Public Health 18:1033. https://doi.org/10.3390/ijerph18031033
Shi D, Lu X (2018) Accumulation degree and source apportionment of trace metals in smaller than 63 µm road dust from the areas with different land uses: a case study of Xi’an, China. Sci Total Environ 636:1211–1218. https://doi.org/10.1016/j.scitotenv.2018.04.385
Sofowote UM, McCarry BE, Marvin CH (2008) Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods. Environ Sci Technol 42(16):6007–6014. https://doi.org/10.1021/es800219z
Timofeev I, Kosheleva N, Kasimov N (2019) Health risk assessment based on the contents of potentially toxic elements in urban soils of Darkhan, Mongolia. J Environ Manage 242:279–289. https://doi.org/10.1016/j.jenvman.2019.04.090
USEPA (2001) Risk assessment guidance for superfund: Volume III - Part A, Process for conducting probabilistic risk assessment. Washington DC, USA
USEPA (2011) Exposure factors handbook Edition (Final). US Environmental Protection Agency, Washington
Xu J, Tian Y, Zhang Y, Guo C, Shi G, Zhang C, Feng Y (2013) Source apportionment of perfluorinated compounds (PFCs) in sediments: using three multivariate factor analysis receptor models. J Hazard Mater 260:483–488. https://doi.org/10.1016/j.jhazmat.2013.06.001
Xue S, Shi L, Wu C, Wu H, Qin Y, Pan W, Hartley W, Cui M (2017) Cadmium, lead, and arsenic contamination in paddy soils of a mining area and their exposure effects on human HEPG2 and keratinocyte cell-lines. Environ Res 156:23–30. https://doi.org/10.1016/j.envres.2017.03.014
Yang Y, Christakos G, Guo M, Xiao L, Huang W (2017) Space-time quantitative source apportionment of soil heavy metal concentration increments. Environ Pollut 223:560–566. https://doi.org/10.1016/j.envpol.2017.01.058
Yang S, Zhao J, Chang SX, Collins C, Xu J, Liu X (2019) Status assessment and probabilistic health risk modeling of metals accumulation in agriculture soils across China: a synthesis. Environ Int 128:165–174. https://doi.org/10.1016/j.envint.2019.04.044
Zeng F, Ali S, Zhang H, Ouyang Y, Qiu B, Wu F, Zhang G (2011) The influence of pH and organic matter content in paddy soil on heavy metal availability and their uptake by rice plants. Environ Pollut 159:84–91. https://doi.org/10.1016/j.envpol.2010.09.019
Zhang J, Wang L, Yang J, Liu H, Dai J (2015) Health risk to residents and stimulation to inherent bacteria of various heavy metals in soil. Sci Total Environ 508:29–36. https://doi.org/10.1016/j.scitotenv.2014.11.064
Zhang L, Zhu G, Ge X, Xu G, Guan Y (2018) Novel insights into heavy metal pollution of farmland based on reactive heavy metals (RHMs): pollution characteristics, predictive models, and quantitative source apportionment. J Hazard Mater 360:32–42. https://doi.org/10.1016/j.jhazmat.2018.07.075
Zhang W, Yan Y, Yu R, Hu G (2021) The sources-specific health risk assessment combined with APCS/MLR model for heavy metals in tea garden soils from south Fujian Province, China. Catena 203:105306. https://doi.org/10.1016/j.catena.2021.105306
Zhou J, Feng K, Li Y, Zhou Y (2016) Factorial Kriging analysis and sources of heavy metals in soils of different land-use types in the Yangtze River Delta of Eastern China. Environ Sci Pollut Res 23(15):14957–14967. https://doi.org/10.1007/s11356-016-6619-z
Funding
This work was funded by the Funds for Independent Innovation of Agricultural Science and Technology in Jiangsu Province (Grant No.: CX(20)3084), Jiangsu Social Development Project (Grant No.: BE2020781), National Natural Science Foundation of China (No. 42101079) and General Projects of Natural Science Research in Colleges and Universities of Jiangsu Province (Grant No.: 20KJB170014).
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All authors contributed to the study conception and design. The methodology was provided by Yan Li, Genmei Wang and Huanchao Zhang. Material preparation and sample collection were performed by Ning Li, Xiangling Zhang, Jiale Wen and Xinyu Cheng. Data collection was performed by Xiangling Zhang and Ning Li. Data analysis was performed by Ning Li. The first draft of the manuscript was written by Ning Li and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Li, N., Li, Y., Wang, G. et al. The sources risk assessment combined with APCS/MLR model for potentially toxic elements in farmland of a first-tier city, China. Environ Sci Pollut Res 29, 50717–50726 (2022). https://doi.org/10.1007/s11356-022-19325-5
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DOI: https://doi.org/10.1007/s11356-022-19325-5