Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review

Vinod Kumar; Shevita Pandita; Anket Sharma; Palak Bakshi; Pooja Sharma; Ioannis Karaouzas; Renu Bhardwaj; Ashwani Kumar Thukral; Artemi Cerda

doi:10.1080/24749508.2019.1701310

Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review

Kumar, Vinod; Pandita, Shevita; Sharma, Anket; Bakshi, Palak; Sharma, Pooja; Karaouzas, Ioannis; Bhardwaj, Renu; Thukral, Ashwani Kumar; Cerda, Artemi 2021-07-03 00:00:00 GEOLOGY, ECOLOGY, AND LANDSCAPES 2021, VOL. 5, NO. 3, 173–185 INWASCON https://doi.org/10.1080/24749508.2019.1701310 REVIEW ARTICLE Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review a,b c d e e f Vinod Kumar , Shevita Pandita , Anket Sharma , Palak Bakshi , Pooja Sharma , Ioannis Karaouzas , e e g Renu Bhardwaj , Ashwani Kumar Thukral and Artemi Cerda a b Department of Botany, DAV University, Jalandhar, India; Department of Botany, Govt College for women Gandhi Nagar, Jammu, India; c d Department of Botany, University of Jammu, Jammu and Kashmir, India; State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou, China; Department of Botanical and Environmental Sciences, Guru Nanak Dev University, Amritsar, India; f g Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, Anavyssos, Greece; Soil Erosion and Degradation Research Group, Department of Geography, University of Valencia, Valencia, Spain ABSTRACT ARTICLE HISTORY Received 4 October 2019 Agriculture is one of the major human activities that changed the landforms, water resources Accepted 27 November 2019 and the biogeochemical cycles. Pollution of agricultural soilsby metal(loid)s is a serious and global hazard but worldwide studies related to metal(loid)s pollution in agricultural soils are KEYWORDS very limited. To fulﬁl this gap, metal(loid)s content in agricultural soils from 2001 to 2019 all Metal(loid)s; agricultural over the world was reviewed. Multivariate statistical techniques, contamination indices and soils; pollution; human human health risk assessment were determined for the metal(loid)s. Among the analysed health assessment; cancer metal(loid)s, the average contents of Zn, Cu, Pb, Cr, Cd, As and Ni exceeded the Canadian, index and China soil guidelines limits. The results of contamination factor indicated that Cr, Pb, Cd, As and Zn are the key pollution contaminants. As and Cd had the highest enrichment among the analysed metal(loid)s according to the enrichment factor. The potential and modiﬁed ecologi- cal risk index showed that Cd is the foremost contaminant responsible for ecological threats. The non-carcinogenic risk for ingestion pathway indicated that As, Pb and Cr are the foremost contaminants responsible for aﬀecting human health, while dermal pathway results showed less risk of metal(loid)s in the agricultural soils. The carcinogenic risk revealed that As, Pb and Cr are the key contaminants that aﬀects human health. 1. Introduction pollutants accompanied by China’s Ministry of Environmental Protection and Ministry of Land and Agriculture is one of the major human activities that Resources, revealed that about 19.4% agricultural soils changed the landforms, water resources, and the bio- samples are contaminated by metal(loid)s, which sur- geochemical cycles (Rodrigo-Comino, Senciales, passed the standard limits (MEPPRC and MLRPRC, Cerdà, & Brevik, 2018; Sharma et al., 2017). It is also 2014). a key driver of the land degradation processes (and Food crops are the vital sources of human oral desertiﬁcation) and within the processes that are contact to metal(loid)s (Zheng et al., 2013), as responsible for the soil pollution (Cernansky, 2015). a consequence regular evaluation of metal(loid)s con- Agricultural activities are also responsible for enrich- tent in agricultural soils is of utmost signiﬁcance in ment of metal(loid)s in the soils is widely accepted by safeguarding its quality and certifying future sustain- the scientiﬁc community. Soil is the main reservoir of ability (Keesstra et al., 2016; Wong, Li, Zhang, Qi, & metal(loid)s in the biosphere and has an imperative Min, 2002). The natural content of metal(loid)s in impact in cycling of metal(loid)s in nature (Cao et al., soils was low due to natural processes (Shan et al., 2010). The signiﬁcant expansion of urbanization is 2013), while substantial geogenic enrichment has planting stress on the soil ecosystem (Guan et al., been conﬁrmed (Kumar, Sharma, Minakshi, & 2018). Particularly, in agricultural soils metal(loid)s Thukral, 2018a). Metal(loid)s accumulation in agricul- pollution has drawn increasing attention to scientists tural soils leads to nutrient loss and soil function and to the public throughout the globe owing to its deterioration that have great impact on the production harmful inﬂuence on the food safety (Toth et al., 2016; and quality of crops (Huamain, Chunrong, Cong, & Liu et al., 2017; Keshavarzi & Kumar, 2018; Kumar Yongguan, 1999; Kong, 2014). Metal(loid)s showed et al., 2019a, Dogra et al., 2019). Soil quality resources harmful eﬀects at low levels, while their excessive are greatly aﬀected by metal(loid)s content and have contents aﬀected the human health (Alloway, 2013; a signiﬁcant impact on the human health through the Burges, Epelde, & Garbisu, 2015; Khan, Cao, Zheng, food chain (Toth et al., 2016). The analysis of soil CONTACT Vinod Kumar vinodverma507@gmail.com Department of Botany, DAV University, Jalandhar, Punjab 144012, India The supplementary data for this article can be accessed here. © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 174 V. KUMAR ET AL. Huang, & Zhu, 2008). Zn, Ni, Pb, Cd, Hg, Cr, As, and anthropogenic activities and natural factors are the Cu have been enumerated as major control contami- main sources of metal(loid)s. Further, they also nants by USEPA (USEPA, 2014), and nine metal(loid) employed various contamination factors/indices like s (Pb, As, Cd, Cu, Be, Cr, Hg, Ni, and Ti) were among contamination factor, enrichment factor (EF), poten- the primary contaminants banned by China’s Ministry tial ecological risk and modiﬁed ecological risk, and of Environmental Protection. showed that sampling sites are moderately to highly Metal(loid)s sources in the agricultural soils polluted by the metal(loid)s. Kumar et al. (2019)in assisted as a foundation for the management that another on soils of India also applied multivariate ambition to attain good organisation of soil quality, analysis and contamination indices (CF), and con- which safeguards human health and soil environs cluded that metal(loid)s showed low to moderate con- (Kumar et al., 2019c; Heidari, Kumar, & Keshavarzi, tamination in the area. Krishna and Mohan (2016), in 2019). Thus, it is very imperative to apportion the another study on soils of Hyderabad, India, applied contamination of metal(loid)s in the agricultural contamination factor, EF and ecological risk index soils. The natural processes like geological parent (RI), and concluded that soils were moderately to materials and anthropogenic activities (e.g., release of highly polluted by the metal(loid)s. Further, they also untreated industrial wastes, agronomic practices, etc.) computed human health risk assessment and revealed are the foremost aspects responsible for contamina- that As, Cr, and Pb showed average to high risks. tion of agricultural soil by metal(loid)s (Huang et al., The key objective of this review paper is to appraisal 2015; Kumar et al., 2018b; Lu et al., 2012; Sun, Liu, the metal(loid)s (Fe, Cu, Cr, Co, Pb, Cd, As, Ni, Mn, Wang, Sun, & Yu, 2013). Cheng (2003) showed that and Zn) levels in agricultural soils throughout the the geological background content of metal(loid)s is globe from 2001 to 2019. Since the soil quality varies low in China, but with human activities, air, soil, and with the time, data for years before this time may not water are polluted by the metal(loid)s, which also reveal the scope of this work. Furthermore, evaluation aﬀects the human health directly or via the food strategies are being updated each year, and to make chain. Numerous limits on metal(loid)s were deﬁned the results equivalent, the selected period of work is to safeguard agricultural soils. Bioavailability is the regarded suitable. To evaluate the diﬀerent results, and crucial aspect responsible for metal(loid)s in associa- to incorporate them into a widespread dataset, multi- tion with environment and human beings (Lado, variate techniques were used to ﬁnd the possible Hengl, & Reuter, 2008). Various investigations on sources of metal(loid)s in the agricultural soils. agricultural soils have been reported throughout the Further CF, EF, potential ecological RI, and modiﬁed world by diﬀerent workers like Cai et al. (2012), Sun ecological risk index (MRI) were also applied to deter- et al. (2013), Niu, Yang, Xu, Yang, and Liu (2013), mine the pollution and ecological risk assessment of Huang et al. (2018), Guan et al. (2018), and Cai, Wang, metal(loid)s. Finally, the human risks associated with Wen, Luo, and Wang (2019) in China; Kumar et al. metal(loid)s of agricultural soils were determined by (2018a) and Dogra et al. (2019) in Keshavarzi and hazard quotient (HQ), hazard index (HI), and cancer Kumar (2018, 2019) in Iran; and Antibachi, index (CI). Our contribution will inform about the Kelepertzis, and Kelepertsis (2012), Skordas, State-of-the-Art of metal(loid)s contamination and Papastergios, and Filippidis (2013), and Kelepertzis with this information the necessary policies should (2014) in Greece. In the Mediterranean area, mainly be developed to achieve a sustainable management Spanish agricultural soils have been evaluated (Micó, that will help to accomplish the sustainable goals for Recatalá, Peris, & Sánchez, 2006; Peris, Recatalá, Micó, development launched by the United Nations and soil Sánchez, & Sánchez, 2008; Franco-Uría, López-Mateo, science is relevant to reach the wished Land Roca, & Fernández-Marcos, 2009; Martín, Ramos- Degradation Neutrality (Keesstra et al., 2018; Miras, Boluda, & Gil, 2013; Toth et al., 2016), while Keshavarzi, Kumar, Bottega, & Rodrigo-Comino, geochemical data are found for Italy (Abollino et al., 2019). 2002; Facchinelli, Sacchi, & Mallen, 2001) and Zagreb (Romic & Romic, 2003). Various multivariate statistical techniques were also 2. Material and methods applied to the metal(loid)s content in agricultural soils 2.1. Data collection to determine their sources of origin. Guan et al. (2018) while working on agricultural soils of Hexi Corridor, Metal(loid)s data on agricultural soils throughout the China used principal component analysis (PCA), and world were assembled by the available published lit- inferred that both natural as well as anthropogenic erature from 2001 to 2019 by searching the keywords activities were responsible for the contribution of “heavy metals in agricultural soils,”“heavy metal con- metal(loid)s in the agricultural soils. Keshavarzi and tent in agricultural soils,” and “assessment of heavy Kumar (2019) in their work on Northeastern Iran metals in agricultural soils” from the ISI of the Web of applied PCA and heatmap, and concluded that Science, Science Direct, Google Scholar, Research GEOLOGY, ECOLOGY, AND LANDSCAPES 175 Gate, and PubMed. Data from 81 indexed journals where C is the ith value of metal(loid)s in the agri- were collected for metal(loid)s in agricultural soils cultural soils and B is the background values of ith and converted into µg/g. Figure 1 illustrates the avail- metal(loid)s taken from Taylor and McLennan (1995). able data of metal(loid)s in diﬀerent regions of the The ratings applied for categorization of CF level are world. China recorded maximum number of sites given in Table S2. (94) followed by India (25) and Bangladesh (11) for collection of metal(loid)s in agricultural soils. All the 2.2.2. Enrichment factor (EF) metal(loid)s collected data are provided in the supple- EF was conducted to evaluate the enrichment level, mentary Table S1. and to assess the human inﬂuence of metal(loid)s on the agricultural soils (Loska, Wiechuła, & Korus, 2004). It was computed by following Buat-Menard 2.2. Quantiﬁcation of soil pollution and Chesselet (1979): A number of CF have been used to quantify the metal- (loid)s pollution in agricultural soils. The description EF ¼ n (2) ref sample ref of CF is as follows. background where C and B are the ith metal(loid)s in the agri- n n 2.2.1. Contamination factor (CF) cultural soil and background environment respec- CF is the ratio of metal(loid)s present in the agricul- tively. C and B is the content of reference ref ref tural soils divided by metal(loid)s in the background element used for normalization. Metals like Ti, Fe, environment. It was determined by following Al, Mn, and Sc were taken as reference elements Hakanson (1980): (Amil, Latif, Khan, & Mohamad, 2016; Hsu et al., 2016; Kara et al., 2014; Namaghi, Karami, & Saadat, CF ¼ (1) 2011; Szolnoki, Farsang, & Puskás, 2013). Fe was cho- sen as reference element due to its comparatively high United Kingdom Brazil England Algeria Italy Poland Iran Turkey Croatia South America Saudi Arabia Korea Greece Zimbabwe Spain Bangladesh India China 0 20406080 100 Number of collection sites for heavy metals in different countries Figure 1. Overview of collection of metal(loid)s in diﬀerent countries. 176 V. KUMAR ET AL. level and strength in the crust (Bhuiyan, Parvez, Islam, ADD dermal HQ ¼ (8) dermal Dampare, & Suzuki, 2010). The grades used to ﬁnd the RfD dermal enrichment level of metal(loid)s are presented in The sum of non-CR of each metal(loid)s was repre- Table S2. sented as HI for diﬀerent exposure pathways, and determined as: 2.3. Ecological risk assessment HI ¼ HQ þ HQ (9) ing dermal RI was suggested by Hakanson (1980) and conducted where RfD and RfD are the ingestion and oral/ ing dermal to determine the ecological risks posed by metal(loid)s dermal reference doses (µg/kg/d), respectively. HQ ing in the agricultural soils (Cui, Zang, Zhai, & Wu, 2014; and HQ are the HQ through ingestion and der- dermal Maanan et al., 2015). This index considers four mal pathways, respectively. aspects: content, pollutant type, toxicity degree, and The CR of metal(loid)s were determined to ﬁnd the the sensitivity of metal(loid)s contamination in the probabilities of human beings in developing the risk of agricultural soils. The RI was determined as: cancer by their exposure with carcinogens. The CI is the n n summation of CR for ingestion and dermal pathways. X X i i i RI ¼ E ¼ T CF (3) r r The slope factor (SF) represents the relationship i¼ 1 i¼1 between dose and response factor (USEPA, 2011). −6 −4 1×10 to 1 × 10 is the CR range prescribed by where E is the potential ecological RI of individual USEPA (2004), and calculated as: metal(loid)s and T is the toxicological response factor taken from Duodu, Goonetilleke, and Ayoko (2016). CR ¼ ADD SF (10) ing ing When RI is derived by employing EF, then it is called MRI and equation used to compute it are as follows: CR ¼ ADD SF (11) dermal dermal n n X X i i i MRI ¼ mE ¼ T EF (4) r r CI ¼ CR þ CR (12) ing dermal i¼ 1 i¼1 The toxicological response factor and grades used for classiﬁcation of ecological risk assessment are pro- 2.5. Statistical analysis vided in Table S3. The data was subjected to descriptive statistics by employing PAST v 3.21 software (Hammer & Harper, 2.4. Human health risk assessment 2001). The correlation among the diﬀerent metal(loid)s in agricultural soils was evaluated by using Pearson’s It links the concentration of metal(loid)s in the agri- correlation using R software v 3.5.1 (Statistical cultural soil with the possibility of harmful eﬀects on Computing, Vienna, Austria). Cluster analysis (CA) the human health. The HQ and cancer risk (CR) were was also conducted to ﬁnd the association between the conducted to evaluate the non-carcinogenic and carci- metal(loid)s. Finally, PCA was performed to evaluate the nogenic risk (CR) of each metal(loid)s in the agricul- source apportionment of metal(loid)s in the agricultural tural soils (USEPA, 2011). In agricultural soils, three soils (Kumar et al., 2017). exposure routes were measured: ingestion, dermal con- tact, and inhalation. For non-carcinogens, the average daily intake (ADD) of metal(loid)s through diﬀerent 3. Results and discussion routes was determined (USEPA, 2011)asfollows: 3.1. Descriptive statistics of metal(loid)s and C IR EF ED i s ADD ¼ (5) ing vis-a-vis the soil guidelines BW AT Metal(loid)s are frequently found in the soils. Among all C SA K ET EF ED CF i p ADD ¼ the metal(loid)s Pb, As, Cd, and Hg are included in the dermal BW AT top 20 hazardous substances of the ATSDR (ATSDR, (6) 2012) and the USEPA (USEPA, 2007). Metals may reside where ADD and ADD are the ADD from inges- in the soil for long duration based on type of metal and ing dermal tion and dermal pathways respectively (mg/kg/day). soil (Ghosh & Singh, 2005). The descriptive analysis of The other parameters used for determination of path- metal(loid)s is presented in Table 1. Among the analysed ways are given in Table S4. metal(loid)s, Fe content was the highest, while Cd con- The equation used to calculate HQ is as follows: tent was found minimum. The mean content of metal- (loid)s showed a trend, i.e., Fe > Zn > Mn > Cr > Pb > Ni ADD ing HQ ¼ (7) i >Cu>As >Co>Cd.The geometricmeanofmetal(loid) RfD ing sfollowedatrend,viz.,Fe>Mn >Zn>Ni >Pb>As >Cr GEOLOGY, ECOLOGY, AND LANDSCAPES 177 Table 1. Descriptive statistics of metal(loid)s in agricultural soils. µg/g Fe Cu Cr Co Pb Cd As Ni Mn Zn Min 0.1 0.004 0.026 0.003 0.02 0.03 2.35 0.27 1.1 0.25 Max 68,700 1149 7767.5 68.09 6153 96.9 276 1609.8 2492 36,756 Mean 1314 76.03 234.74 6.84 216.79 5.55 43.44 101.87 588.22 960.04 Std. error 667.71 11.24 78.82 0.51 61.23 1.25 4.02 15.99 22.14 360.41 Median 13,149 39.07 49.7 6.84 35.4 0.79 43.44 48.4 588.2 112.9 Geom. mean 8694.6 17.92 23.13 3.42 34.11 1.04 28.29 50.96 511.4 129.7 Coeﬀ. var 61.57 179.2 407.0 89.94 342.4 272.1 112.1 190.2 45.63 455.1 CCME (2007) - 63 64 40 70 1.4 12 50 - 200 CNEMC - 17 50.5 - 36 0.056 8.9 14.4 - 47.3 Canadian soil quality guidelines for the Protection of Environment and Human Health (2007). China National Environmental Monitoring Centre (1990). >Cu> Co >Cd. Metal(loid)s ranged from 0.1to As, Ni, and Zn were found greater than the values of 68,700 µg/g for Fe, 0.004 to 1149 µg/g for Cu, 0.003 to Canadian soil quality guidelines for Protection of 68.09 µg/gforCo,0.02to6153µg/gforPb,0.03to Environment and Human Health (2007) and China 96.9 µg/g for Cd, 2.35 to 276 µg/g for As, 0.27 to National Environmental Monitoring Centre (1990). 1609.8 µg/g for Ni, 1.1 to 2492 µg/g for Mn, and 0.25 to 36,756 µg/g for Zn, respectively (Table 1). The standard 3.2. Correlation analysis errorwas foundmaximumforFefollowedbyZnand Cr. The coeﬃcient of variation (CV) was found maximum Pearson’s correlation analysis was performed to forZnfollowedbyCrandPb,indicatinghigherdegreeof determine the dimensions of similarity and to alteration of these metals in the agricultural soils. The CV assess the associations among the metal(loid)s in reﬂects the variations in the data, representing the order the agricultural soils (Figure 2). From the results, it to which agricultural soils are aﬀected by the anthropo- was revealed that Fe was positively correlated with genic activities (Kumar et al., 2019aa). According to Cr, As, Co, and Mn, while showed negative corre- Zhou, Feng, Pei, Meng, and Sun (2016), the CV range lation with Cu. Co was positively correlated with from 10 to 100 represents modest alterations in the Cd, and negative relationship of Co was found with samples. The mean concentrations of Cu, Cr, Pb, Cd, As,Ni, andMn. Mn andAsalsoshowedpositive Figure 2. Pearson’s correlation analysis of diﬀerent metal(loid)s in agricultural soils. 178 V. KUMAR ET AL. correlation with each other. The high correlations divided into Cu and Zn, Pb and Ni, and Co and Cd. To among the metal(loid)s suggest that metal(loid)s determine the correlations among metal(loid)s, PCA was have thesameorigin(Micó et al., 2006). Inter- performed by decreasing the dataset to many inﬂuential element associations in the agricultural soil matrix aspects (Guan et al., 2016). For well elucidation of PCs, give statistics on origin and pathways of metal(loid) they were revolved using varimax rotation and chosen s in the geoenvironment (Dragovic, Mihailovic, & for consequent graphical presentations (Table 2). The Gajic, 2008). Eigen values of ﬁrst three components explained 43.9% of total variation. The loadings of PCA before varimax rotation indicated that PC1 explained 18.5% variation 3.3. Multivariate analysis and demonstrated positive loadings of Fe, Cr, As, and Mn. PC2 demonstrated positive loadings of Co and Cd, CA was done to determine the sources among the dif- while negative loading of Ni and 15% variation was ferent metal(loid)s by employing Ward’smethodand explained by this PC. Cu and Pb contribute to PC3 and Euclidean distance (Kumar, Sharma, Bakshi, Bhardwaj, demonstrated 11.1% of variance. PCA loadings after &Thukral, 2018c). CA demonstrated predominantly two varimax rotation showed that PC1 explained 17.5% fol- groups (Figure 3): group I (Fe, As, Mn, and Cr), and lowed by PC2 (15.3%) and PC3 (11%) of variance respec- groupII(Cu,Zn, Pb,Ni, Co,and Cd). Further, groupIis tively. The PCA loadings after varimax rotation followed divided into Fe and As, and Mn and Cr. Group II is also Figure 3. Cluster analysis of diﬀerent metal(loid)s in agricultural soils. Table 2. Principal component analysis of metal(loid)s in agricultural soils. Eigen values Extraction sums of squared loadings Rotation sums of squared loadings Components Total % Variance Cumulative % Total % Variance Cumulative % Total % Variance Cumulative % 1 1.8 18.5 18.5 1.8 18.5 18.5 1.7 17.5 17.5 2 1.5 15.0 33.5 1.5 15.0 33.5 1.5 15.3 32.8 3 1.1 11.1 44.6 1.1 11.1 44.6 1.1 11.0 43.9 4 1.0 10.5 55.1 1.0 10.5 55.1 1.0 10.6 54.5 5 1.0 10.0 65.1 1.0 10.0 65.1 1.0 10.6 65.1 Component matrix Rotated component matrix Variables PC1 PC2 PC3 PC1 PC2 PC3 Fe 0.69 0.49 −0.13 0.83 0.11 −0.12 Cu −0.16 0.03 0.79 −0.11 0.04 0.89 Cr 0.48 0.12 0.22 0.39 −0.17 −0.006 Co −0.45 0.70 −0.27 −0.06 0.84 −0.166 Pb 0.05 −0.13 −0.37 0.13 −0.08 −0.006 Cd −0.34 0.67 0.05 7.103E-5 0.79 0.16 As 0.67 0.25 −0.15 0.73 −0.02 −0.09 Ni 0.11 −0.43 −0.28 −0.08 −0.28 −0.25 Mn 0.55 0.10 0.30 0.55 −0.20 0.37 Zn −0.12 0.08 −0.003 −0.09 −0.09 −0.13 GEOLOGY, ECOLOGY, AND LANDSCAPES 179 the same trend as observed for before varimax rotation of Cd (Jiao, Chen, Chang, & Page, 2012). Escalated As PCA loadings. Pb and Zn showed high content in the content in agricultural soils has been attributed to the agricultural soils pose a great threat to human health, the usage of mineral fertilizers (Nicholson, Smith, Alloway, environment and its biota; consequently, it is vital to Carlton-Smith, & Chambers, 2003). determine the pollution origins of Pb and Zn (Dao, Morrison, Kiely, & Zhang, 2013). Pb is the foremost 3.4. Quantiﬁcation of pollution in agricultural indicator of traﬃc emissions (Arditsoglou & Samara, soils 2005; Hjortenkrans, Bergbäck, & Häggerud, 2006). The roads contribute Pb beside the farmland, where traﬃc The pollution level was determined by employing CF and activities and agricultural equipment’s release exhaust EF for metal(loid)s in the agricultural soils (Figure 4). CF with Pb, leading to pollution. While the manufacturing results showed that CF values for Co were found less than and practice of leaded petrol stopped since 2000, but still one, indicating minimum contamination in the agricul- Pb occurred in the soil (Chen, Chang, Liu, Clevers, & tural soils. CF values for Mn were found higher than the Kooistra, 2016). Thetire wearofcaris the primary cause range of 1–3,whileCFvaluesfor Cu and Ni were of Zn, as Zn-containing dust goes into the soil (Monaci, observed in the range of 3–6 grade for CF, representing Moni, Lanciotti, Grechi, & Bargagli, 2000). Due to water moderate and substantial contamination of these metal- scarcity and rising cost of fertilizers, farmers utilizing raw (loid)s in the agricultural soils, respectively. The CF of Cr, sewage to irrigate and fertilize the agricultural soil (Luo, Pb,Cd,As,and Znwere foundhigherthan6,indicating Ma, Zhang,Wei,&Zhu, 2009). High content of Cr in soil higher contamination of these metal(loid)s in the agricul- suggested that anthropogenic activities are probably tural soils. The EF of metal(loid)s in the agricultural soils linked with sewage irrigation (Li, He, Han, & Gu, 2009; have determined to distinguish metal(loid)s originating Liu et al., 2016). Cu and Zn content is primarily linked from human aspects those from natural attribution. The with livestock manures (Liang et al., 2017) since Cu and EF showed that Cu, Cr, Co, Ni, and Mn values of EF were Zn are existed in the livestock diets as a stabilizer, pro- found higher than >5–20, demonstrating moderate agri- viding great performance by giving antibacterial agents cultural soil contamination. Pb and Zn showed high to the guts and governing post-weaning scours (Holm, contamination with EF values being higher than 1990; Rosen & Roberts, 1996). Cu is generally regarded as >20–40. EF values greater than 40 were found for Cd an indicator metal of agricultural activities, which is and As, representing extreme agricultural soil associated with the usage of fertilizers (Acosta, Faz, contamination. Martínez-Martínez, & Arocena, 2011). Moreover, appli- cation of Cu-based fertilizers and fungicides on crops 3.5. Ecological risk evaluation of metal(loid)s in leads to enhanced level of Cu in the agricultural soils agricultural soils (Epstein & Bassein, 2001;Sun et al., 2013). The usage of P fertilizers is the vital source of Cd, and number of The RI of each metal(loid)s and MRI were determined to workers reported the enhancement of Cd content evaluate the ecological risks of metal(loid)s in the agri- under extreme usage of P fertilizers in agricultural soils cultural soils (Figure 5). Er values forCu, Cr,Co, Ni,Mn, (Cai et al., 2012). P rocks are the crucial material for and Zn were less than 40, demonstrating low ecological making the fertilizers, and contribute substantial level of risk in the agricultural soils. Pb and As demonstrated CF EF Cu Cr Co Pb Cd As Ni Mn Zn Figure 4. Contamination factor (CF) and enrichment factor (EF) of diﬀerent metal(loid)s in agricultural soils. Contamination and enrichment factor of metal(loid)s 180 V. KUMAR ET AL. Er mEr Cu Cr Co Pb Cd As Ni Mn Zn Figure 5. Potential ecological risk index (Er) and modiﬁed potential ecological risk (mEr) of each metal(loid)s in agricultural soils. modest ecological risks (Er 40–80). Er values higher than was found for Zn, Mn, Pb, and Cr, while maximum 320 were observed for Cd, representing very high ecolo- ADD values for adults were found for Zn, Mn, Pb, and gical risk of Cd in the agricultural soils. The RI values for Cr. The ADD values of metal(loid)s for both child and all metal(loid)s was 1883.3, indicating very high ecologi- adults for dermal pathway were found very less as cal risk in the agricultural soils. Moreover, the results of compared to ingestion pathway. The HQ was recorded MRI indicated that mEr value of Cd was found greater maximum for As, Pb, and Cr in case of ingestion path- than 320, showing high ecological risk in the agricultural way for both child as well as adults. Similarly, the HQ soils. Cu, Cr, Co, Zn, and Mn showed less ecological risk, values via dermal route were also found very less. The while mEr values of Pb and As showed substantial eco- HI of Pb, Cr, and As were recorded maximum for child logical risk in the agricultural soils. mEr values for Ni as compared to the adults. Children had more non- found higher than 40–80 representing adequate risk carcinogenic hazards as compared to the adults, repre- of Ni. senting they are vulnerable to environmental pollutants. The CR was determined for Ni, Cr, As, and Pb accord- ing to available SF of metal(loid)s. The results of CR are 3.6. Human health risk assessment presented in Table 4. The CR values via ingestion path- way was found higher both for child and adults, Cu, Cr, Co, Pb, Cd, Ni, Zn, Mn, and As were taken into whereas CR values via dermal pathway was recorded account for evaluation of human health risk as of their low for As, Pb, Ni, and Cr. comparatively high toxicity to the human beings Remediation of polluted soils by metal(loid)s aims in (USEPA, 2016). The results of non-CR showed by cleaning up the soils used for agriculture, diminish the metal(loid)s in the agricultural soils for child and adults related risks, improve soil nutrients, and increase food through ingestion and dermal pathways are represented production (Abdullahi, 2015). The removal processes in Table 3. The average daily dose values of metal(loid)s used for recovery of metal(loid)s contaminated soils via ingestion pathway for child was found higher as may be in-situ or ex-situ, and biological, physical and compared to the adults for ingestion pathway. The chemical (Ghosh & Singh, 2005;Khalidetal., 2017). maximum ADD values via ingestion pathway for child Table 3. Human health risk assessment of metal(loid)s in agricultural soils. Child Adult Child Adult Hazard index ADD ADD ADD ADD HQ HQ HI HI Heavy metals Ingestion dermal Ingestion dermal HQ Ingestion dermal HQ Ingestion Dermal Child Adult Cu 3.11 1.3609E-05 2.08 3.44322E-06 77.77 1.70113E-06 52.08 4.30403E-07 77.77 52.08 Cr 9.60 8.40348E-05 6.43 2.12617E-05 3201.32 0.001120464 2143.7 0.000283489 3201.3 2143.7 Co 0.28 4.89732E-07 0.19 1.23907E-07 932.82 8.16219E-06 624.6 2.06512E-06 932.8 624.6 Pb 8.87 3.88044E-05 5.94 9.81791E-06 2956.53 0.077 1979.8 0.019 2956.6 1979.8 Cd 0.23 9.93425E-07 0.15 2.51347E-07 454.14 3.9737E-05 304.1 1.00539E-05 454.1 304.1 As 1.78 7.77556E-06 1.19 1.9673E-06 5924.24 6.32159E-05 3967.1 1.59943E-05 5924.2 3967.1 Ni 4.17 3.64685E-06 2.79 9.22691E-07 208.39 4.55857E-06 139.5 1.15336E-06 208.3 139.5 Mn 24.07 0.00011 16.12 2.66391E-05 1002.75 0.0001 671.4 2.77491E-05 1002.7 671.4 Zn 39.28 1.71843E-05 26.3 4.3478E-06 130.93 2.86405E-07 87.6 7.24633E-08 130.9 87.6 ADD = average daily dose and HQ = Hazard quotient. Potential and modified potential ecological risk of individual metal(loid)s GEOLOGY, ECOLOGY, AND LANDSCAPES 181 Table 4. Carcinogenic risk assessment of metal(loid)s in agricultural soils. Child Adult Cancer Index SF CR CR CI CI Heavy metals (mg/kg)/day CR Ingestion dermal CR Ingestion dermal Child Adult Ni 1.7 7.08 6.19965E-06 4.74 1.56857E-06 7.09 4.74 Cd 15 3.45 1.49014E-05 2.25 3.7702E-06 3.45 2.25 Cr 0.5 4.8 4.20174E-05 3.21 1.06308E-05 4.80 3.22 As 1.5 2.67 1.16633E-05 1.78 2.95094E-06 2.67 1.79 Figure 6. Overview of strategies used for phytoremediation of metal(loid)s in the agricultural soils. These strategies are frequently applied in intermingling equivalent regulation levels for domestic situation after of reasonable and cost-eﬀective remediation of contami- rational treatment time from 30 min to 6 h. No unne- nated site. The overview of soil remediation techniques cessary nutrient loss in treated soil is found and no are presented in Figure 6. The utmost operative strategy secondary harmful product is generated. Long-durable on a lesser scale is soil exclusion and replacement. experiment and plant assay indicates great sustainability However, organizing of the soil and locating suitable of the approach and its possibility for agricultural pur- newsoilmay be cost ineﬃcient. Therefore, soil washing poses. Finally, we can conclude that more attention has been projected as a mode to eradicate metal(loid)s might be require to those zones or regions, where metal- from soil but it can be applied mainly to small scale sites (loid)s content was very high. Since from the last few as it is a time taking and costly method (Ahmad, Najeeb, years, various studies have noted that local and national &Zia, 2015). Phytoremediation is environmental inﬂuence on the agricultural soils are the main aspects to friendly and cheap method for soil clean up with low- understand ecological issues at worldwide level (Smith to-moderate levels of metal(loid)s (Sabir et al., 2015; et al., 2015;Steﬀan, Brevik, Burgess, & Cerdà, 2018). Sharma et al., 2018). It can be applied eﬀectively in Other researchers also studied that there is need to link association with other traditional remediation strategies the problems associated with soils to the public, although as a ﬁnal step of the remediation process. The eﬀective- till date, it is not divulgated properly to the public (Brevik ness of phytoremediation based on diverse aspects like et al., 2019). physico-chemical properties of the soil, metal(loid)s bioavailability, microbial and plant exudates, and the Conclusion capability of organisms to uptake, store and detoxify metal(loid)s (Khalid et al., 2017). Xu et al. (2019)in This review revealed that the average content of Zn, their work reported the design and demonstration of Cu, Pb, Cr, Cd, As, and Ni from the data collected a removal approach basedonideaofasymmetrical alter- was found higher than the Canadian and China soil nating current electrochemistry that accomplishes great- guidelines limit. The CF values indicated that As, Cd, est level of pollutant removal for Cu, Pb and Cd at Pb, Zn, and Cr showed high risk of contamination in diverse initial levels from 100 to 10,000 ppm, all attaining 182 V. KUMAR ET AL. the agricultural soils. As and Cd showed greatest Arditsoglou, A., & Samara, C. (2005). Levels of total sus- pended particulate matter and major trace elements in enrichment among the analysed metal(loid)s in the Kosovo: A source identiﬁcation and apportionment agricultural soils. The results of ecological risk assess- study. Chemosphere, 59(5), 669–678. ment indicated that Cd is the main contaminant ATSDR. (2012). 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Publisher: Taylor & Francis
Copyright: © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON).
ISSN: 2474-9508
DOI: 10.1080/24749508.2019.1701310
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Abstract

GEOLOGY, ECOLOGY, AND LANDSCAPES 2021, VOL. 5, NO. 3, 173–185 INWASCON https://doi.org/10.1080/24749508.2019.1701310 REVIEW ARTICLE Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review a,b c d e e f Vinod Kumar , Shevita Pandita , Anket Sharma , Palak Bakshi , Pooja Sharma , Ioannis Karaouzas , e e g Renu Bhardwaj , Ashwani Kumar Thukral and Artemi Cerda a b Department of Botany, DAV University, Jalandhar, India; Department of Botany, Govt College for women Gandhi Nagar, Jammu, India; c d Department of Botany, University of Jammu, Jammu and Kashmir, India; State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou, China; Department of Botanical and Environmental Sciences, Guru Nanak Dev University, Amritsar, India; f g Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, Anavyssos, Greece; Soil Erosion and Degradation Research Group, Department of Geography, University of Valencia, Valencia, Spain ABSTRACT ARTICLE HISTORY Received 4 October 2019 Agriculture is one of the major human activities that changed the landforms, water resources Accepted 27 November 2019 and the biogeochemical cycles. Pollution of agricultural soilsby metal(loid)s is a serious and global hazard but worldwide studies related to metal(loid)s pollution in agricultural soils are KEYWORDS very limited. To fulﬁl this gap, metal(loid)s content in agricultural soils from 2001 to 2019 all Metal(loid)s; agricultural over the world was reviewed. Multivariate statistical techniques, contamination indices and soils; pollution; human human health risk assessment were determined for the metal(loid)s. Among the analysed health assessment; cancer metal(loid)s, the average contents of Zn, Cu, Pb, Cr, Cd, As and Ni exceeded the Canadian, index and China soil guidelines limits. The results of contamination factor indicated that Cr, Pb, Cd, As and Zn are the key pollution contaminants. As and Cd had the highest enrichment among the analysed metal(loid)s according to the enrichment factor. The potential and modiﬁed ecologi- cal risk index showed that Cd is the foremost contaminant responsible for ecological threats. The non-carcinogenic risk for ingestion pathway indicated that As, Pb and Cr are the foremost contaminants responsible for aﬀecting human health, while dermal pathway results showed less risk of metal(loid)s in the agricultural soils. The carcinogenic risk revealed that As, Pb and Cr are the key contaminants that aﬀects human health. 1. Introduction pollutants accompanied by China’s Ministry of Environmental Protection and Ministry of Land and Agriculture is one of the major human activities that Resources, revealed that about 19.4% agricultural soils changed the landforms, water resources, and the bio- samples are contaminated by metal(loid)s, which sur- geochemical cycles (Rodrigo-Comino, Senciales, passed the standard limits (MEPPRC and MLRPRC, Cerdà, & Brevik, 2018; Sharma et al., 2017). It is also 2014). a key driver of the land degradation processes (and Food crops are the vital sources of human oral desertiﬁcation) and within the processes that are contact to metal(loid)s (Zheng et al., 2013), as responsible for the soil pollution (Cernansky, 2015). a consequence regular evaluation of metal(loid)s con- Agricultural activities are also responsible for enrich- tent in agricultural soils is of utmost signiﬁcance in ment of metal(loid)s in the soils is widely accepted by safeguarding its quality and certifying future sustain- the scientiﬁc community. Soil is the main reservoir of ability (Keesstra et al., 2016; Wong, Li, Zhang, Qi, & metal(loid)s in the biosphere and has an imperative Min, 2002). The natural content of metal(loid)s in impact in cycling of metal(loid)s in nature (Cao et al., soils was low due to natural processes (Shan et al., 2010). The signiﬁcant expansion of urbanization is 2013), while substantial geogenic enrichment has planting stress on the soil ecosystem (Guan et al., been conﬁrmed (Kumar, Sharma, Minakshi, & 2018). Particularly, in agricultural soils metal(loid)s Thukral, 2018a). Metal(loid)s accumulation in agricul- pollution has drawn increasing attention to scientists tural soils leads to nutrient loss and soil function and to the public throughout the globe owing to its deterioration that have great impact on the production harmful inﬂuence on the food safety (Toth et al., 2016; and quality of crops (Huamain, Chunrong, Cong, & Liu et al., 2017; Keshavarzi & Kumar, 2018; Kumar Yongguan, 1999; Kong, 2014). Metal(loid)s showed et al., 2019a, Dogra et al., 2019). Soil quality resources harmful eﬀects at low levels, while their excessive are greatly aﬀected by metal(loid)s content and have contents aﬀected the human health (Alloway, 2013; a signiﬁcant impact on the human health through the Burges, Epelde, & Garbisu, 2015; Khan, Cao, Zheng, food chain (Toth et al., 2016). The analysis of soil CONTACT Vinod Kumar vinodverma507@gmail.com Department of Botany, DAV University, Jalandhar, Punjab 144012, India The supplementary data for this article can be accessed here. © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 174 V. KUMAR ET AL. Huang, & Zhu, 2008). Zn, Ni, Pb, Cd, Hg, Cr, As, and anthropogenic activities and natural factors are the Cu have been enumerated as major control contami- main sources of metal(loid)s. Further, they also nants by USEPA (USEPA, 2014), and nine metal(loid) employed various contamination factors/indices like s (Pb, As, Cd, Cu, Be, Cr, Hg, Ni, and Ti) were among contamination factor, enrichment factor (EF), poten- the primary contaminants banned by China’s Ministry tial ecological risk and modiﬁed ecological risk, and of Environmental Protection. showed that sampling sites are moderately to highly Metal(loid)s sources in the agricultural soils polluted by the metal(loid)s. Kumar et al. (2019)in assisted as a foundation for the management that another on soils of India also applied multivariate ambition to attain good organisation of soil quality, analysis and contamination indices (CF), and con- which safeguards human health and soil environs cluded that metal(loid)s showed low to moderate con- (Kumar et al., 2019c; Heidari, Kumar, & Keshavarzi, tamination in the area. Krishna and Mohan (2016), in 2019). Thus, it is very imperative to apportion the another study on soils of Hyderabad, India, applied contamination of metal(loid)s in the agricultural contamination factor, EF and ecological risk index soils. The natural processes like geological parent (RI), and concluded that soils were moderately to materials and anthropogenic activities (e.g., release of highly polluted by the metal(loid)s. Further, they also untreated industrial wastes, agronomic practices, etc.) computed human health risk assessment and revealed are the foremost aspects responsible for contamina- that As, Cr, and Pb showed average to high risks. tion of agricultural soil by metal(loid)s (Huang et al., The key objective of this review paper is to appraisal 2015; Kumar et al., 2018b; Lu et al., 2012; Sun, Liu, the metal(loid)s (Fe, Cu, Cr, Co, Pb, Cd, As, Ni, Mn, Wang, Sun, & Yu, 2013). Cheng (2003) showed that and Zn) levels in agricultural soils throughout the the geological background content of metal(loid)s is globe from 2001 to 2019. Since the soil quality varies low in China, but with human activities, air, soil, and with the time, data for years before this time may not water are polluted by the metal(loid)s, which also reveal the scope of this work. Furthermore, evaluation aﬀects the human health directly or via the food strategies are being updated each year, and to make chain. Numerous limits on metal(loid)s were deﬁned the results equivalent, the selected period of work is to safeguard agricultural soils. Bioavailability is the regarded suitable. To evaluate the diﬀerent results, and crucial aspect responsible for metal(loid)s in associa- to incorporate them into a widespread dataset, multi- tion with environment and human beings (Lado, variate techniques were used to ﬁnd the possible Hengl, & Reuter, 2008). Various investigations on sources of metal(loid)s in the agricultural soils. agricultural soils have been reported throughout the Further CF, EF, potential ecological RI, and modiﬁed world by diﬀerent workers like Cai et al. (2012), Sun ecological risk index (MRI) were also applied to deter- et al. (2013), Niu, Yang, Xu, Yang, and Liu (2013), mine the pollution and ecological risk assessment of Huang et al. (2018), Guan et al. (2018), and Cai, Wang, metal(loid)s. Finally, the human risks associated with Wen, Luo, and Wang (2019) in China; Kumar et al. metal(loid)s of agricultural soils were determined by (2018a) and Dogra et al. (2019) in Keshavarzi and hazard quotient (HQ), hazard index (HI), and cancer Kumar (2018, 2019) in Iran; and Antibachi, index (CI). Our contribution will inform about the Kelepertzis, and Kelepertsis (2012), Skordas, State-of-the-Art of metal(loid)s contamination and Papastergios, and Filippidis (2013), and Kelepertzis with this information the necessary policies should (2014) in Greece. In the Mediterranean area, mainly be developed to achieve a sustainable management Spanish agricultural soils have been evaluated (Micó, that will help to accomplish the sustainable goals for Recatalá, Peris, & Sánchez, 2006; Peris, Recatalá, Micó, development launched by the United Nations and soil Sánchez, & Sánchez, 2008; Franco-Uría, López-Mateo, science is relevant to reach the wished Land Roca, & Fernández-Marcos, 2009; Martín, Ramos- Degradation Neutrality (Keesstra et al., 2018; Miras, Boluda, & Gil, 2013; Toth et al., 2016), while Keshavarzi, Kumar, Bottega, & Rodrigo-Comino, geochemical data are found for Italy (Abollino et al., 2019). 2002; Facchinelli, Sacchi, & Mallen, 2001) and Zagreb (Romic & Romic, 2003). Various multivariate statistical techniques were also 2. Material and methods applied to the metal(loid)s content in agricultural soils 2.1. Data collection to determine their sources of origin. Guan et al. (2018) while working on agricultural soils of Hexi Corridor, Metal(loid)s data on agricultural soils throughout the China used principal component analysis (PCA), and world were assembled by the available published lit- inferred that both natural as well as anthropogenic erature from 2001 to 2019 by searching the keywords activities were responsible for the contribution of “heavy metals in agricultural soils,”“heavy metal con- metal(loid)s in the agricultural soils. Keshavarzi and tent in agricultural soils,” and “assessment of heavy Kumar (2019) in their work on Northeastern Iran metals in agricultural soils” from the ISI of the Web of applied PCA and heatmap, and concluded that Science, Science Direct, Google Scholar, Research GEOLOGY, ECOLOGY, AND LANDSCAPES 175 Gate, and PubMed. Data from 81 indexed journals where C is the ith value of metal(loid)s in the agri- were collected for metal(loid)s in agricultural soils cultural soils and B is the background values of ith and converted into µg/g. Figure 1 illustrates the avail- metal(loid)s taken from Taylor and McLennan (1995). able data of metal(loid)s in diﬀerent regions of the The ratings applied for categorization of CF level are world. China recorded maximum number of sites given in Table S2. (94) followed by India (25) and Bangladesh (11) for collection of metal(loid)s in agricultural soils. All the 2.2.2. Enrichment factor (EF) metal(loid)s collected data are provided in the supple- EF was conducted to evaluate the enrichment level, mentary Table S1. and to assess the human inﬂuence of metal(loid)s on the agricultural soils (Loska, Wiechuła, & Korus, 2004). It was computed by following Buat-Menard 2.2. Quantiﬁcation of soil pollution and Chesselet (1979): A number of CF have been used to quantify the metal- (loid)s pollution in agricultural soils. The description EF ¼ n (2) ref sample ref of CF is as follows. background where C and B are the ith metal(loid)s in the agri- n n 2.2.1. Contamination factor (CF) cultural soil and background environment respec- CF is the ratio of metal(loid)s present in the agricul- tively. C and B is the content of reference ref ref tural soils divided by metal(loid)s in the background element used for normalization. Metals like Ti, Fe, environment. It was determined by following Al, Mn, and Sc were taken as reference elements Hakanson (1980): (Amil, Latif, Khan, & Mohamad, 2016; Hsu et al., 2016; Kara et al., 2014; Namaghi, Karami, & Saadat, CF ¼ (1) 2011; Szolnoki, Farsang, & Puskás, 2013). Fe was cho- sen as reference element due to its comparatively high United Kingdom Brazil England Algeria Italy Poland Iran Turkey Croatia South America Saudi Arabia Korea Greece Zimbabwe Spain Bangladesh India China 0 20406080 100 Number of collection sites for heavy metals in different countries Figure 1. Overview of collection of metal(loid)s in diﬀerent countries. 176 V. KUMAR ET AL. level and strength in the crust (Bhuiyan, Parvez, Islam, ADD dermal HQ ¼ (8) dermal Dampare, & Suzuki, 2010). The grades used to ﬁnd the RfD dermal enrichment level of metal(loid)s are presented in The sum of non-CR of each metal(loid)s was repre- Table S2. sented as HI for diﬀerent exposure pathways, and determined as: 2.3. Ecological risk assessment HI ¼ HQ þ HQ (9) ing dermal RI was suggested by Hakanson (1980) and conducted where RfD and RfD are the ingestion and oral/ ing dermal to determine the ecological risks posed by metal(loid)s dermal reference doses (µg/kg/d), respectively. HQ ing in the agricultural soils (Cui, Zang, Zhai, & Wu, 2014; and HQ are the HQ through ingestion and der- dermal Maanan et al., 2015). This index considers four mal pathways, respectively. aspects: content, pollutant type, toxicity degree, and The CR of metal(loid)s were determined to ﬁnd the the sensitivity of metal(loid)s contamination in the probabilities of human beings in developing the risk of agricultural soils. The RI was determined as: cancer by their exposure with carcinogens. The CI is the n n summation of CR for ingestion and dermal pathways. X X i i i RI ¼ E ¼ T CF (3) r r The slope factor (SF) represents the relationship i¼ 1 i¼1 between dose and response factor (USEPA, 2011). −6 −4 1×10 to 1 × 10 is the CR range prescribed by where E is the potential ecological RI of individual USEPA (2004), and calculated as: metal(loid)s and T is the toxicological response factor taken from Duodu, Goonetilleke, and Ayoko (2016). CR ¼ ADD SF (10) ing ing When RI is derived by employing EF, then it is called MRI and equation used to compute it are as follows: CR ¼ ADD SF (11) dermal dermal n n X X i i i MRI ¼ mE ¼ T EF (4) r r CI ¼ CR þ CR (12) ing dermal i¼ 1 i¼1 The toxicological response factor and grades used for classiﬁcation of ecological risk assessment are pro- 2.5. Statistical analysis vided in Table S3. The data was subjected to descriptive statistics by employing PAST v 3.21 software (Hammer & Harper, 2.4. Human health risk assessment 2001). The correlation among the diﬀerent metal(loid)s in agricultural soils was evaluated by using Pearson’s It links the concentration of metal(loid)s in the agri- correlation using R software v 3.5.1 (Statistical cultural soil with the possibility of harmful eﬀects on Computing, Vienna, Austria). Cluster analysis (CA) the human health. The HQ and cancer risk (CR) were was also conducted to ﬁnd the association between the conducted to evaluate the non-carcinogenic and carci- metal(loid)s. Finally, PCA was performed to evaluate the nogenic risk (CR) of each metal(loid)s in the agricul- source apportionment of metal(loid)s in the agricultural tural soils (USEPA, 2011). In agricultural soils, three soils (Kumar et al., 2017). exposure routes were measured: ingestion, dermal con- tact, and inhalation. For non-carcinogens, the average daily intake (ADD) of metal(loid)s through diﬀerent 3. Results and discussion routes was determined (USEPA, 2011)asfollows: 3.1. Descriptive statistics of metal(loid)s and C IR EF ED i s ADD ¼ (5) ing vis-a-vis the soil guidelines BW AT Metal(loid)s are frequently found in the soils. Among all C SA K ET EF ED CF i p ADD ¼ the metal(loid)s Pb, As, Cd, and Hg are included in the dermal BW AT top 20 hazardous substances of the ATSDR (ATSDR, (6) 2012) and the USEPA (USEPA, 2007). Metals may reside where ADD and ADD are the ADD from inges- in the soil for long duration based on type of metal and ing dermal tion and dermal pathways respectively (mg/kg/day). soil (Ghosh & Singh, 2005). The descriptive analysis of The other parameters used for determination of path- metal(loid)s is presented in Table 1. Among the analysed ways are given in Table S4. metal(loid)s, Fe content was the highest, while Cd con- The equation used to calculate HQ is as follows: tent was found minimum. The mean content of metal- (loid)s showed a trend, i.e., Fe > Zn > Mn > Cr > Pb > Ni ADD ing HQ ¼ (7) i >Cu>As >Co>Cd.The geometricmeanofmetal(loid) RfD ing sfollowedatrend,viz.,Fe>Mn >Zn>Ni >Pb>As >Cr GEOLOGY, ECOLOGY, AND LANDSCAPES 177 Table 1. Descriptive statistics of metal(loid)s in agricultural soils. µg/g Fe Cu Cr Co Pb Cd As Ni Mn Zn Min 0.1 0.004 0.026 0.003 0.02 0.03 2.35 0.27 1.1 0.25 Max 68,700 1149 7767.5 68.09 6153 96.9 276 1609.8 2492 36,756 Mean 1314 76.03 234.74 6.84 216.79 5.55 43.44 101.87 588.22 960.04 Std. error 667.71 11.24 78.82 0.51 61.23 1.25 4.02 15.99 22.14 360.41 Median 13,149 39.07 49.7 6.84 35.4 0.79 43.44 48.4 588.2 112.9 Geom. mean 8694.6 17.92 23.13 3.42 34.11 1.04 28.29 50.96 511.4 129.7 Coeﬀ. var 61.57 179.2 407.0 89.94 342.4 272.1 112.1 190.2 45.63 455.1 CCME (2007) - 63 64 40 70 1.4 12 50 - 200 CNEMC - 17 50.5 - 36 0.056 8.9 14.4 - 47.3 Canadian soil quality guidelines for the Protection of Environment and Human Health (2007). China National Environmental Monitoring Centre (1990). >Cu> Co >Cd. Metal(loid)s ranged from 0.1to As, Ni, and Zn were found greater than the values of 68,700 µg/g for Fe, 0.004 to 1149 µg/g for Cu, 0.003 to Canadian soil quality guidelines for Protection of 68.09 µg/gforCo,0.02to6153µg/gforPb,0.03to Environment and Human Health (2007) and China 96.9 µg/g for Cd, 2.35 to 276 µg/g for As, 0.27 to National Environmental Monitoring Centre (1990). 1609.8 µg/g for Ni, 1.1 to 2492 µg/g for Mn, and 0.25 to 36,756 µg/g for Zn, respectively (Table 1). The standard 3.2. Correlation analysis errorwas foundmaximumforFefollowedbyZnand Cr. The coeﬃcient of variation (CV) was found maximum Pearson’s correlation analysis was performed to forZnfollowedbyCrandPb,indicatinghigherdegreeof determine the dimensions of similarity and to alteration of these metals in the agricultural soils. The CV assess the associations among the metal(loid)s in reﬂects the variations in the data, representing the order the agricultural soils (Figure 2). From the results, it to which agricultural soils are aﬀected by the anthropo- was revealed that Fe was positively correlated with genic activities (Kumar et al., 2019aa). According to Cr, As, Co, and Mn, while showed negative corre- Zhou, Feng, Pei, Meng, and Sun (2016), the CV range lation with Cu. Co was positively correlated with from 10 to 100 represents modest alterations in the Cd, and negative relationship of Co was found with samples. The mean concentrations of Cu, Cr, Pb, Cd, As,Ni, andMn. Mn andAsalsoshowedpositive Figure 2. Pearson’s correlation analysis of diﬀerent metal(loid)s in agricultural soils. 178 V. KUMAR ET AL. correlation with each other. The high correlations divided into Cu and Zn, Pb and Ni, and Co and Cd. To among the metal(loid)s suggest that metal(loid)s determine the correlations among metal(loid)s, PCA was have thesameorigin(Micó et al., 2006). Inter- performed by decreasing the dataset to many inﬂuential element associations in the agricultural soil matrix aspects (Guan et al., 2016). For well elucidation of PCs, give statistics on origin and pathways of metal(loid) they were revolved using varimax rotation and chosen s in the geoenvironment (Dragovic, Mihailovic, & for consequent graphical presentations (Table 2). The Gajic, 2008). Eigen values of ﬁrst three components explained 43.9% of total variation. The loadings of PCA before varimax rotation indicated that PC1 explained 18.5% variation 3.3. Multivariate analysis and demonstrated positive loadings of Fe, Cr, As, and Mn. PC2 demonstrated positive loadings of Co and Cd, CA was done to determine the sources among the dif- while negative loading of Ni and 15% variation was ferent metal(loid)s by employing Ward’smethodand explained by this PC. Cu and Pb contribute to PC3 and Euclidean distance (Kumar, Sharma, Bakshi, Bhardwaj, demonstrated 11.1% of variance. PCA loadings after &Thukral, 2018c). CA demonstrated predominantly two varimax rotation showed that PC1 explained 17.5% fol- groups (Figure 3): group I (Fe, As, Mn, and Cr), and lowed by PC2 (15.3%) and PC3 (11%) of variance respec- groupII(Cu,Zn, Pb,Ni, Co,and Cd). Further, groupIis tively. The PCA loadings after varimax rotation followed divided into Fe and As, and Mn and Cr. Group II is also Figure 3. Cluster analysis of diﬀerent metal(loid)s in agricultural soils. Table 2. Principal component analysis of metal(loid)s in agricultural soils. Eigen values Extraction sums of squared loadings Rotation sums of squared loadings Components Total % Variance Cumulative % Total % Variance Cumulative % Total % Variance Cumulative % 1 1.8 18.5 18.5 1.8 18.5 18.5 1.7 17.5 17.5 2 1.5 15.0 33.5 1.5 15.0 33.5 1.5 15.3 32.8 3 1.1 11.1 44.6 1.1 11.1 44.6 1.1 11.0 43.9 4 1.0 10.5 55.1 1.0 10.5 55.1 1.0 10.6 54.5 5 1.0 10.0 65.1 1.0 10.0 65.1 1.0 10.6 65.1 Component matrix Rotated component matrix Variables PC1 PC2 PC3 PC1 PC2 PC3 Fe 0.69 0.49 −0.13 0.83 0.11 −0.12 Cu −0.16 0.03 0.79 −0.11 0.04 0.89 Cr 0.48 0.12 0.22 0.39 −0.17 −0.006 Co −0.45 0.70 −0.27 −0.06 0.84 −0.166 Pb 0.05 −0.13 −0.37 0.13 −0.08 −0.006 Cd −0.34 0.67 0.05 7.103E-5 0.79 0.16 As 0.67 0.25 −0.15 0.73 −0.02 −0.09 Ni 0.11 −0.43 −0.28 −0.08 −0.28 −0.25 Mn 0.55 0.10 0.30 0.55 −0.20 0.37 Zn −0.12 0.08 −0.003 −0.09 −0.09 −0.13 GEOLOGY, ECOLOGY, AND LANDSCAPES 179 the same trend as observed for before varimax rotation of Cd (Jiao, Chen, Chang, & Page, 2012). Escalated As PCA loadings. Pb and Zn showed high content in the content in agricultural soils has been attributed to the agricultural soils pose a great threat to human health, the usage of mineral fertilizers (Nicholson, Smith, Alloway, environment and its biota; consequently, it is vital to Carlton-Smith, & Chambers, 2003). determine the pollution origins of Pb and Zn (Dao, Morrison, Kiely, & Zhang, 2013). Pb is the foremost 3.4. Quantiﬁcation of pollution in agricultural indicator of traﬃc emissions (Arditsoglou & Samara, soils 2005; Hjortenkrans, Bergbäck, & Häggerud, 2006). The roads contribute Pb beside the farmland, where traﬃc The pollution level was determined by employing CF and activities and agricultural equipment’s release exhaust EF for metal(loid)s in the agricultural soils (Figure 4). CF with Pb, leading to pollution. While the manufacturing results showed that CF values for Co were found less than and practice of leaded petrol stopped since 2000, but still one, indicating minimum contamination in the agricul- Pb occurred in the soil (Chen, Chang, Liu, Clevers, & tural soils. CF values for Mn were found higher than the Kooistra, 2016). Thetire wearofcaris the primary cause range of 1–3,whileCFvaluesfor Cu and Ni were of Zn, as Zn-containing dust goes into the soil (Monaci, observed in the range of 3–6 grade for CF, representing Moni, Lanciotti, Grechi, & Bargagli, 2000). Due to water moderate and substantial contamination of these metal- scarcity and rising cost of fertilizers, farmers utilizing raw (loid)s in the agricultural soils, respectively. The CF of Cr, sewage to irrigate and fertilize the agricultural soil (Luo, Pb,Cd,As,and Znwere foundhigherthan6,indicating Ma, Zhang,Wei,&Zhu, 2009). High content of Cr in soil higher contamination of these metal(loid)s in the agricul- suggested that anthropogenic activities are probably tural soils. The EF of metal(loid)s in the agricultural soils linked with sewage irrigation (Li, He, Han, & Gu, 2009; have determined to distinguish metal(loid)s originating Liu et al., 2016). Cu and Zn content is primarily linked from human aspects those from natural attribution. The with livestock manures (Liang et al., 2017) since Cu and EF showed that Cu, Cr, Co, Ni, and Mn values of EF were Zn are existed in the livestock diets as a stabilizer, pro- found higher than >5–20, demonstrating moderate agri- viding great performance by giving antibacterial agents cultural soil contamination. Pb and Zn showed high to the guts and governing post-weaning scours (Holm, contamination with EF values being higher than 1990; Rosen & Roberts, 1996). Cu is generally regarded as >20–40. EF values greater than 40 were found for Cd an indicator metal of agricultural activities, which is and As, representing extreme agricultural soil associated with the usage of fertilizers (Acosta, Faz, contamination. Martínez-Martínez, & Arocena, 2011). Moreover, appli- cation of Cu-based fertilizers and fungicides on crops 3.5. Ecological risk evaluation of metal(loid)s in leads to enhanced level of Cu in the agricultural soils agricultural soils (Epstein & Bassein, 2001;Sun et al., 2013). The usage of P fertilizers is the vital source of Cd, and number of The RI of each metal(loid)s and MRI were determined to workers reported the enhancement of Cd content evaluate the ecological risks of metal(loid)s in the agri- under extreme usage of P fertilizers in agricultural soils cultural soils (Figure 5). Er values forCu, Cr,Co, Ni,Mn, (Cai et al., 2012). P rocks are the crucial material for and Zn were less than 40, demonstrating low ecological making the fertilizers, and contribute substantial level of risk in the agricultural soils. Pb and As demonstrated CF EF Cu Cr Co Pb Cd As Ni Mn Zn Figure 4. Contamination factor (CF) and enrichment factor (EF) of diﬀerent metal(loid)s in agricultural soils. Contamination and enrichment factor of metal(loid)s 180 V. KUMAR ET AL. Er mEr Cu Cr Co Pb Cd As Ni Mn Zn Figure 5. Potential ecological risk index (Er) and modiﬁed potential ecological risk (mEr) of each metal(loid)s in agricultural soils. modest ecological risks (Er 40–80). Er values higher than was found for Zn, Mn, Pb, and Cr, while maximum 320 were observed for Cd, representing very high ecolo- ADD values for adults were found for Zn, Mn, Pb, and gical risk of Cd in the agricultural soils. The RI values for Cr. The ADD values of metal(loid)s for both child and all metal(loid)s was 1883.3, indicating very high ecologi- adults for dermal pathway were found very less as cal risk in the agricultural soils. Moreover, the results of compared to ingestion pathway. The HQ was recorded MRI indicated that mEr value of Cd was found greater maximum for As, Pb, and Cr in case of ingestion path- than 320, showing high ecological risk in the agricultural way for both child as well as adults. Similarly, the HQ soils. Cu, Cr, Co, Zn, and Mn showed less ecological risk, values via dermal route were also found very less. The while mEr values of Pb and As showed substantial eco- HI of Pb, Cr, and As were recorded maximum for child logical risk in the agricultural soils. mEr values for Ni as compared to the adults. Children had more non- found higher than 40–80 representing adequate risk carcinogenic hazards as compared to the adults, repre- of Ni. senting they are vulnerable to environmental pollutants. The CR was determined for Ni, Cr, As, and Pb accord- ing to available SF of metal(loid)s. The results of CR are 3.6. Human health risk assessment presented in Table 4. The CR values via ingestion path- way was found higher both for child and adults, Cu, Cr, Co, Pb, Cd, Ni, Zn, Mn, and As were taken into whereas CR values via dermal pathway was recorded account for evaluation of human health risk as of their low for As, Pb, Ni, and Cr. comparatively high toxicity to the human beings Remediation of polluted soils by metal(loid)s aims in (USEPA, 2016). The results of non-CR showed by cleaning up the soils used for agriculture, diminish the metal(loid)s in the agricultural soils for child and adults related risks, improve soil nutrients, and increase food through ingestion and dermal pathways are represented production (Abdullahi, 2015). The removal processes in Table 3. The average daily dose values of metal(loid)s used for recovery of metal(loid)s contaminated soils via ingestion pathway for child was found higher as may be in-situ or ex-situ, and biological, physical and compared to the adults for ingestion pathway. The chemical (Ghosh & Singh, 2005;Khalidetal., 2017). maximum ADD values via ingestion pathway for child Table 3. Human health risk assessment of metal(loid)s in agricultural soils. Child Adult Child Adult Hazard index ADD ADD ADD ADD HQ HQ HI HI Heavy metals Ingestion dermal Ingestion dermal HQ Ingestion dermal HQ Ingestion Dermal Child Adult Cu 3.11 1.3609E-05 2.08 3.44322E-06 77.77 1.70113E-06 52.08 4.30403E-07 77.77 52.08 Cr 9.60 8.40348E-05 6.43 2.12617E-05 3201.32 0.001120464 2143.7 0.000283489 3201.3 2143.7 Co 0.28 4.89732E-07 0.19 1.23907E-07 932.82 8.16219E-06 624.6 2.06512E-06 932.8 624.6 Pb 8.87 3.88044E-05 5.94 9.81791E-06 2956.53 0.077 1979.8 0.019 2956.6 1979.8 Cd 0.23 9.93425E-07 0.15 2.51347E-07 454.14 3.9737E-05 304.1 1.00539E-05 454.1 304.1 As 1.78 7.77556E-06 1.19 1.9673E-06 5924.24 6.32159E-05 3967.1 1.59943E-05 5924.2 3967.1 Ni 4.17 3.64685E-06 2.79 9.22691E-07 208.39 4.55857E-06 139.5 1.15336E-06 208.3 139.5 Mn 24.07 0.00011 16.12 2.66391E-05 1002.75 0.0001 671.4 2.77491E-05 1002.7 671.4 Zn 39.28 1.71843E-05 26.3 4.3478E-06 130.93 2.86405E-07 87.6 7.24633E-08 130.9 87.6 ADD = average daily dose and HQ = Hazard quotient. Potential and modified potential ecological risk of individual metal(loid)s GEOLOGY, ECOLOGY, AND LANDSCAPES 181 Table 4. Carcinogenic risk assessment of metal(loid)s in agricultural soils. Child Adult Cancer Index SF CR CR CI CI Heavy metals (mg/kg)/day CR Ingestion dermal CR Ingestion dermal Child Adult Ni 1.7 7.08 6.19965E-06 4.74 1.56857E-06 7.09 4.74 Cd 15 3.45 1.49014E-05 2.25 3.7702E-06 3.45 2.25 Cr 0.5 4.8 4.20174E-05 3.21 1.06308E-05 4.80 3.22 As 1.5 2.67 1.16633E-05 1.78 2.95094E-06 2.67 1.79 Figure 6. Overview of strategies used for phytoremediation of metal(loid)s in the agricultural soils. These strategies are frequently applied in intermingling equivalent regulation levels for domestic situation after of reasonable and cost-eﬀective remediation of contami- rational treatment time from 30 min to 6 h. No unne- nated site. The overview of soil remediation techniques cessary nutrient loss in treated soil is found and no are presented in Figure 6. The utmost operative strategy secondary harmful product is generated. Long-durable on a lesser scale is soil exclusion and replacement. experiment and plant assay indicates great sustainability However, organizing of the soil and locating suitable of the approach and its possibility for agricultural pur- newsoilmay be cost ineﬃcient. Therefore, soil washing poses. Finally, we can conclude that more attention has been projected as a mode to eradicate metal(loid)s might be require to those zones or regions, where metal- from soil but it can be applied mainly to small scale sites (loid)s content was very high. Since from the last few as it is a time taking and costly method (Ahmad, Najeeb, years, various studies have noted that local and national &Zia, 2015). Phytoremediation is environmental inﬂuence on the agricultural soils are the main aspects to friendly and cheap method for soil clean up with low- understand ecological issues at worldwide level (Smith to-moderate levels of metal(loid)s (Sabir et al., 2015; et al., 2015;Steﬀan, Brevik, Burgess, & Cerdà, 2018). Sharma et al., 2018). It can be applied eﬀectively in Other researchers also studied that there is need to link association with other traditional remediation strategies the problems associated with soils to the public, although as a ﬁnal step of the remediation process. The eﬀective- till date, it is not divulgated properly to the public (Brevik ness of phytoremediation based on diverse aspects like et al., 2019). physico-chemical properties of the soil, metal(loid)s bioavailability, microbial and plant exudates, and the Conclusion capability of organisms to uptake, store and detoxify metal(loid)s (Khalid et al., 2017). Xu et al. (2019)in This review revealed that the average content of Zn, their work reported the design and demonstration of Cu, Pb, Cr, Cd, As, and Ni from the data collected a removal approach basedonideaofasymmetrical alter- was found higher than the Canadian and China soil nating current electrochemistry that accomplishes great- guidelines limit. The CF values indicated that As, Cd, est level of pollutant removal for Cu, Pb and Cd at Pb, Zn, and Cr showed high risk of contamination in diverse initial levels from 100 to 10,000 ppm, all attaining 182 V. KUMAR ET AL. the agricultural soils. As and Cd showed greatest Arditsoglou, A., & Samara, C. (2005). Levels of total sus- pended particulate matter and major trace elements in enrichment among the analysed metal(loid)s in the Kosovo: A source identiﬁcation and apportionment agricultural soils. The results of ecological risk assess- study. Chemosphere, 59(5), 669–678. ment indicated that Cd is the main contaminant ATSDR. (2012). 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Journal

Geology Ecology and Landscapes – Taylor & Francis

Published: Jul 3, 2021

Keywords: Metal(loid)s; agricultural soils; pollution; human health assessment; cancer index

References

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Metal contamination of farming soils affected by industry
Multivariate and geostatistical analyses of the spatial distribution and origin of heavy metals in the agricultural soils in Shunyi, Beijing, China
An inventory of trace element inputs to agricultural soils in China
Environmental and ecological risk assessment of heavy metals in sediments of Nador lagoon, Morocco
Spatial relations of heavy metals in arable and greenhouse soils of a Mediterranean environment region (Spain)
Bulletin on national survey of soil contamination (in Chinese)
Assessing heavy metal sources in agricultural soils of an European Mediterranean area by multivariate analysis
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A study on chemical properties of groundwater and soil in ophiolitic rocks in Firuzabad, east of Shahrood, Iran: With emphasis to heavy metal contamination
An inventory of heavy metal input to agricultural soil in England and Wales
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Increasing the knowledge of heavy metal contents and sources in agricultural soils of the European Mediterranean region
The multidisciplinary origin of soil geography: A review
Heavy metals distribution in agricultural topsoils in urban area
Phytoremediation: mechanisms and adaptations
Identification of sources of heavy metals in agricultural soils using multivariate analysis and GIS
Increasing farmer’s income and reducing soil erosion using intercropping in rainfed maize-wheat rotation of Himalaya, India
Major and trace element contents in apples from a cultivated area of central Greece
Biogeochemical cycles and biodiversity as key drivers of ecosystem services provided by soils
The effect of soil on human health: An overview
Multivariate and geostatistical analyses of the spatial distribution and sources of heavy metals in agricultural soil in Dehui, Northeast China
Cumulative impacts of human activities on urban garden soils: Origin and accumulation of metals
The geochemical evolution of the continental crust
Heavy metals in agricultural soils of the european union with implications for food safety
Treatment technologies for site cleanup: Annual status report, twelfth ed
Exposure factors handbook 2011 edition (Final)
Code of federal regulations: Priority pollutants list
Integrated risk information system (IRIS)
Heavy metals in agricultural soils of the Pearl River Delta, South China
Remediation of heavy metal contaminated soil by asymmetrical alternating current electrochemistry
Heavy metals in food, house dust, and water from an e-waste recycling area in South China and the potential risk to human health
Multivariate analysis combined with GIS to source identification of heavy metals in soils around an abandoned industrial area, Eastern China

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Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review

Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review

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Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review

Ecological and human health risks appraisal of metal(loid)s in agricultural soils: a review

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