Environmental, Ecological, and Health Risks Assessment of Olive Orchard Soils in Izmir Province of Turkey

doi:10.21203/rs.3.rs-1764874/v1

Download PDF

Research Article

Environmental, Ecological, and Health Risks Assessment of Olive Orchard Soils in Izmir Province of Turkey

https://doi.org/10.21203/rs.3.rs-1764874/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this older preprint version

Read the latest preprint version →

Soil contamination with TEs become a severe concern, however, the evaluation of ecological and human health problems in intensive agricultural areas remained limited. In this study, Pb, Cr, Ni, Al, Fe, Co, Mn, Cu, Cd, and Zn content of olive orchard soils in Izmir province of Turkey were investigated to the state of pollution, environmental, ecological, and health hazards. Soil samples were taken from 129 olive orchards at 0-30 cm depth. Air-dried samples were eliminated by a 0.5 mm sieve and digested in HNO₃ and HCl (3: 1) at a microwave digestion device. TheTEs concentrations are determined by ICP-OES. Cr and Ni levels were advanced at the limit level. In terms of EF, the soils are significantly contaminated by Cd (7.18), moderately contaminated by Ni (2.94), and Cu (2.56). In terms of Cf, soils were moderately contaminated by Cd (1.96), and in terms of Er moderate by Cd (58.83). Co, Fe, Al, and Mn are the lithogenic origin, and Pb, Zn, Al, Cd, Cu, and Ni are anthropogenic. The HQ, HI, and THI in terms of adults and children were below 1, all TEs via ingestion, skin contact, and inhalation pathways had no serious non-carcinogenic hazards. The harmful health consequences of TEs were accentuated in children. This study may serve as a method for managing the contamination-related risk of olive cultivation areas where agrochemicals are widely employed. Additional studies are recommended about TEs contamination risk and the potential health dangers in olive fruits.

Soil contamination

heavy metals

pollution indicates

olive orchards

Soil is among the mainly crucial ecosystems in terms of human living, and soil security is a critical component of national food protection and human, animal, and plant living (Wang et al., 2019). Pollution, soil erosion, salinization, and a loss of organic matter are the most serious threats to the soil (Aytop & Senol, 2022; European Commisssion, 2006). Soil contamination, particularly contamination and accumulation of soil trace elements (TEs) has a severe concern as a result of society's increasing urbanization and industrialization, drawing widespread common attention globally (Yang et al., 2018). Trace elements (TE) have been identified as serious environmental contaminants around the world due to their toxicity and persistence (Alloway, 1995). The most common is TEs that cause problems are chromium (Cr), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), and zinc (Zn) (USEPA 2015). By changing soil structure and function, high TEs levels in agricultural fields decrease product quality or yield (Varol et al., 2022). According to Liu et al. (2013), (2019a), when TEs present in agricultural soils, these metals can be absorbed from the soils by the roots of plants and then transferred to edible sections, posing a risk to human and animals health via transfer of food chain. Soil is a critical component of the food production chain. Excessive TEs accumulating in agricultural fields can cause further contamination in the continental and marine habitats, as well as have an influence on human health via a variety of exposure pathways, including skin touch, inhalant, direct intake, and eating via the chain of soil-food (Varol et al., 2022).

In the research, exposure of soils to TEs accumulation is shown as the cause of cardiovascular diseases, renal and nervous injury of the liver, problems of tendon system, hematological disorder, reproductive impacts, developmental malformations or cancer (Adimalla et al., 2020; Jia et al., 2018; Xiao et al., 2020; Varol et al,. 2020a; Varol et al., 2022). Because of this, heavy metal poisoning of agricultural soils has gotten a lot of attention from the community and governments all over the world. Agricultural soil contamination by TEs has been a global subject in recent years due to their non-biodegradable and carcinogenic character, as well as their bioaccumulation tendency (Fei et al., 2019; Francova et al., 2020; Hu et al., 2020; Varol et al., 2020; Varol et al., 2022). The TEs concentrations in the agricultural fields come from an elemental or anthropogenic origin (Varol et al., 2022). As part of the Earth's crust, TEs are found naturally in soils. As a result, parent material regulates their content in uncontaminated agricultural soils (Hu et al., 2020). Activities of humans are connected with high TEs concentrations in agricultural soils including metallurgy, industrial and residential affluence, exhaust gases, fertilizers, or pesticides (Islam et al., 2020; Kormoker et al., 2020a; Tusher et al., 2020). Removing TEs from soils of contaminated agricultural can be exceedingly hard, expensive, and time-consuming, because of this, the best method is contamination prevention (Hu et al., 2020; Wuana & Okieimen, 2011). It is critical to determine the sources of TEs in contaminated soils and quantify their contributions to conducting cost-effective pollution prevention strategies including management of soil pollution (Hu & Cheng 2013; 2016). It is very essential to determine the source of TEs in the soil and to reveal the relationship between them. Generally, these are determined by the factor, correlation, and cluster analyses (Ma et al., 2017; Varol et al., 2020a). Soil contamination indices are used to quantify soil contamination situations, like as agents of contamination or enrichment, the mark of pollution load, and accumulation (Shaheen et al., 2020). Ecological hazard indices are used to determine the ecological effects of TEs (Varol et al., 2020a). Like, hazard coefficient and carcinogenic hazard, health hazard assessment indices are used to determine the hazards caused by the TEs content of agricultural fields (Baltas et al., 2020; Deng et al., 2020; Jia et al., 2018; Rinklebe et al., 2019; Vural et al., 2021). In studies conducted, it is recommended to evaluate these indices together so that functionally improved the contamination levels and hazards of TEs in the soil of a particular region (Varol et al., 2021).

Turkey is among the important olive producers with its 188679 olive trees and 1738680 tons of olive production (555833 tons for table olive and 1182847 tons for olive oil). In terms of tree presence, the Aegean Region has the most important olive production areas in the country (75%) and Izmir province has 23% of the Aegean Region’s olive tree presence (Deliboran et al., 2022; TUIK, 2021). The presence of rich agricultural potential is located at the beginning of the factors that cause the industry of Izmir province. The other factors are easily providing the convenience of transportation opportunities, ports, laneways, iron roads, and ports. Izmir has got 13 organized industrial zones, 4 technology development zones and 2 free areas providing approximately 9.3% of industrial production in Turkey, The most important reason for the collection of industrial organizations here is the large hinterland of Izmir. Izmir province has a broad hinterland, and this feature has caused industrial institutions to collect in the region. In addition, the city itself is also a great market, and close to other great markets. Especially since the 1950s, the surroundings of the surroundings were successful with industrialization, the north of Izmir has been formed to the south and even the east of new industry. The most important industrial zones are the Izmir-Torbali zone in the south and the Izmir-Aliaga zone in the north. Petrochemical, chemical production, the machine, iron steel industry is intensified in the North direction of industrial generation, in the South direction, the industry based on agricultural products is in the foreground (Unal, 2007). Also, the Izmir province is an important olive and olive oil production center. While some olive orchards are irrigated by underground water, surface water from the water supply is used in some olive orchards. In this region, the Gediz River is very important as a source of water. It was born from the Murat Mountain at the Border of Usak-Kutahya, passing Usak, Manisa, and Izmir-Menemen districts. It is poured to the Aegean Sea through Karsıyaka and Foca districts. Throughout this flow route, it is primarily contaminated with domestic sewage waste. In addition, the surface water is polluted by Usak, Manisa, and Kemalpasa Organized Industries and Menemen Skin Organized Industrial wastes. Also, pollutants are involved in groundwater and surface water due to intensive agricultural activities (use of fertilizer, pesticides, etc.) in the basin (Senol et al., 2016). These waters are used in agricultural irrigation. The excess not taken by the plant is drained from the top or bottom of the surface. As a result, all living creatures are subject to pollutants due to the food chain (from soil to plant, plants to humans, and animals) between the living things. Because of using polluted irrigation water, pesticides, fertilizers, and soils of olive orchards, therefore table olives and olive oil have been facing TEs contamination. In terms of olive and olive oil, it is primarily important that soil pollution is extremely important. Consequently, it is indispensable to implement a wide study for determining the grade or human health hazards of TEs in the olives orchard soil. In many countries, more research is being done about TEs values, contamination, and origin identification, including an assessment of human health hazards of TEs in both agricultural and urban soils (Adimalla & Wang, 2018; Baltas et al., 2020; Dong et al., 2018; Jia et al., 2018; Pan et al., 2016; Rinklebe et al., 2019; Wu et al., 2018). Moreover, the ecological and health effects of TEs on the soils in Turkey were studied insufficient (Yaylali Abanuz, 2011; Baltas et al., 2020; Varol et al. 2020). However, to the first of our information, no research has been conducted on the determination of TEs levels in olive orchards in the Izmir province.

The aim of this study was to define probable sources of TEs with statistical methods of multiple variables, to state non-carcinogenic or carcinogenic human health hazards for territorial inhabitants subject to TEs of olive orchard soils, and to appreciate ecological and environmental hazards of TEs with various indices.

Research area

The research was conducted in the olive orchards of Izmir Province in Turkey (Figure 1). Izmir province has 23% of the Aegean Region olive tree existence (TUIK, 2014). Olive cultivation is carried out in many different topographies, soil groups, and microclimate areas in the Aegean Region, where olive production is most intense (75%). The majority of olive orchards soils are clayey loamy (CL), sandy loamy (SL), and slightly alkaline. Also, the organic matter coverage is low, and proportionally a great majority of soils fall into the less and less class (Aydogdu 2011). Izmir province has a Mediterranean climate. The summers are dry and hot, the winters are mild and rainy. July-August is the hottest, and January-February is the coldest. The number of days below zero does not pass 10 days. The medium yearly air temperature, precipitation and sunshine hours are 17.5 ⁰C, 713.8 mm, and 8.1 hours, respectively (MGM, 2022).

Sampling and analysis

Soil samples were taken in 2015 with Global Positioning System (GPS) from 129 olive orchards at 0-30 cm depth (Fig. 1). Air-dried samples were eliminated by 2 mm, and 0.5 mm sieve for analysis. Pb, Cr, aluminum (Al), iron (Fe), Ni, cobalt (Co), manganese (Mn), Cu, Zn, and cadmium (Cd) were analyzed as a Tes. Samples were digested in HNO₃ and HCl (3: 1) at a device of microwave digestion. Then, the liquids were diluted to the latest volume. ICP-OES (Varian, Vista) was used to determine theTEs concentrations.

Environmental risks assessment

Enrichment factor (EF) is a critical metric for determining the human activities effect of TEs concentrations in soils (Wu et al., 2018; Varol et al., 2020). EF is calculated according to Mazurek et al. (2017) with Eq. (1).

EF = sample [Ci ÷ Cref] / background [Ci ÷ Cref] (1)

Ci is a trace element concentration, and Cref is a reference element concentration in the formula. Al was selected as the reference component due to terms of abundant content and durability in soil (Jia et al. (2018). The continental upper crust levels were used as geochemical qualifications due to the unavailability of regional geochemical qualifications concentrations of TEs (Rudnick and Gao 2004).

Index of geoaccumulation (Igeo) is used to determine the values of TEs pollution of soils. Igeo is determined by comparing the TEs concentrations of soils to their geochemical trace concentrations (Mazurek et al., 2017). Igeo is calculated by Eq. (2) (Muller, 1969).

Igeo = log₂ [Ci ÷ 1.5 x Bi] (2)

Bi is the geochemical qualifications level of TEs (i) (Rudnick and Gao 2004), and Ci is a TEs concentration in the formula.

The factor of contamination (Cf) is a parameter for determining the level of TEs contamination in soils. The following equation is used to calculate Cf (Hakanson 1980) by Eq. (3).

C_fⁱ = Cⁱ÷ C_nⁱ (3)

Ci is a trace element concentration, and C_nⁱ is the background level of TEs (i) (Rudnick & Gao, 2004).

Factors of ecological risks

The risk factor of potential ecological (Er) is used to evaluate the possible ecological hazard of a particular component of soils (Hakanson 1980). It is represented as follows by Eq. (4).

Eⁱ_r= Tⁱ_rx Cⁱ_f (4)

Tⁱ_r is the toxic-response ingredient of TEs (i), and according to Hakanson (1980), it is 10, 5, 5, 5, 1 for Cr, Cu, Ni, Pb, or Zn, respectively. The contamination factor of TEs is known as Cⁱ_f.

Index of potential ecological risk (RI) is used to evaluate the ecological hazard of multi-element of soils. It is determined as the combination of the ecological effect variable (Hakanson, 1980). RI is generally determined as grades: low risk (RI ≤ 150), middle risk (150 < RI ≤ 300), major risk (300 <RI≤600), and upper risk (RI >600) (Pan et al., 2016). RI was determined by Eq (5).

ⁿƩ_{i =1}Eⁱ_r= ⁿƩ_{i =1}Tⁱ_{r x}Cⁱ_f (5)

Eⁱ_r is the possible ecological risk ingredient of TEs (i), and n i is the TEs number (it is 10 in our research).

Risk assessment of human health

In our research, the human health effects of TEs were determined in terms of adults and children. According to research, humans can be subjected to TEs of soils in some ways; (i) ingestion of soil particles, (ii) inhalation of soil particles, and (iii) dermal contact exposure pathways from the soils (USEPA, 2019a). Because of this, the health hazards of TEs were determined by carcinogenic and non-carcinogenic impacts via three pathways. Because of the lack of carcinogenic slope components for other TEs, carcinogenic health effects were determined for Cr, Cd, and Co. Non-carcinogenic health effects of TEs in soil were calculated by hazard quotients (HQs) (Jia et al., 2018; Wu et al., 2018). The following equations are used to compute the non-carcinogenic hazards (HQs) and carcinogenic hazards (CRs) of TEs in children and adults via three exposure pathways (USEPA, 2019b).

Risks of non-carcinogenic:

HQ_ingestion = (Cs x IRS x RBA x EF x ED)/(BW x AT x RfDo x 10⁶) (6)

HQ_dermal = (Cs x SA x AF x ABSd x EF x ED)/(BW x AT x RfDo x GIABS x 10⁶) (7)

HQ_inhalation = (Cs x EF x ED)/(AT x RfC x PEF) (8)

Carcinogenic risks:

CR_ingestion = (Cs x IFS x RBA x CSFo) / (AT x 10⁶) (9)

Where: IFS = (EF x EDa x IRSa / BWa )+ (EF x EDc x IRSc/ BWc)

CR_dermal= (Cs x DFS x ABSd x CSFo) / (AT x GIABS x 10⁶) (10)

Where: DFS = (EF x EDa x SAa x Afa / Bwa) + (EF x EDc x SAc x Afc / BWc)

CR_inhalation= (Cs x EF x ED x IUR x 1000) / (AT x PEF) (11)

The hazard index (HI) is the total of the HQs including three exposure pathways. HI was used to calculate non-carcinogenic risks for children and adults. Furthermore, total carcinogenic hazards (TCR) were calculated by the total CRs including three pathways. The following formula are used to determine the hazard index and overall carcinogenic risk:

HI = HQingestion + HQdermal + HQinhalation (12)

TCR = CRingestion + CRdermal + Crinhalation (13)

Non-carcinogenic health impacts are not assumed if HQ or HI levels are under one. Adverse noncarcinogenic health impacts may arise if the levels are greater than one (USEPA, 1989; 2004). The hazards of carcinogenic, which varies from 104 to 106, are deemed acceptable (USEPA, 1991a). Tables 1 and 2 give detailed information on the levels and units connected to these equations. The USEPA RSL calculator was used to evaluate all HQ, HI, and CR levels observed in our study (USEPA, 2019c).

Table 1 Parameters and their levels related to the evaluation of health risk in terms of TEs in soils

Parameters	Symbols	Units	Values	References
Metal concentration	Cs	mg/kg		Site-specific
Body weight-adult	BWa	kg	70	Site-specific
Body weight-child	BWc	kg	15	USEPA (1991b)
Exposure duration-child	Edc	years	6	USEPA (1991b)
Expose duration-adult	Eda	years	20	USEPA (2019d)
Exposure frequency	EF	days/year	350	USEPA (1991b)
Skin surface area-adult	SAa	cm²	6032	USEPA (2011)
Skin surface area-child	Sac	cm²	2373	USEPA (2011)
Soil intake ratio-adult	IRSa	mg/day	20	Jia et al. (2018)
Soil intake ratio-child	IRSc	mg/day	50	Jia et al. (2018)
Averaging time-child	ATc	Days	365 x EDc (non-carcinogenic)	USEPA (1989)
Averaging time-adult	ATa	Days	365 x EDa (non-carcinogenic)	USEPA (1989)
Skin adherence factor-adult	AFa	mg/cm²	0.07	USEPA (2002)
Skin adherence factor-child	AFc	mg/cm²	0.2	USEPA (2002)
Soil ingestion ratio	IFS	mg/kg	Age-adjusted	USEPA (2019d)
Soil dermal contact factor	DFS	mg/kg	Age-adjusted	USEPA (2019d)
Life time	LT	years	76	Site-specific
Averaging time	AT	days	365 x LT = 27.740 (carcinogenic)	Site-specific

Statistical analyses

Pearson correlation analysis was used to decide the relationships among TEs (p < 0.05). Analysis of principal components was conducted to analyze the potential origin of TEs (Varol et al., 2020; Wang et al., 2020). SPSS 20 was used to account for all statistical analyses.

Table 2 RBA, ABSd, RfDo, GIABS, RFC, IUR, the oral slope factor, and the particulate emission factor for TEs

Metal	Relative bioavailability factor (RBA) (unitless)	Dermal absorption fraction (ABSd) (unitless)	Oral reference dose (RfDo) (mg/kg-day)	Oral slope factor (CSFo) (mg/kg-day)^-1	Gastrointestinal Absorption (GIABS) (unitless)	Inhalation reference concentration (RFC) (mg/m³)	Particulate emission factor (PEF) (m³/kg)	Inhalation unit risk (IUR) (µg/m³)^-1
Al	1	0.001	-	-	1	0.005000	1.36 x 10⁹	-
Cd	1	0.001	0.001	-	0.025	0.00001	1.36 x 10⁹	0.0018
Co	1	0.001	0.0003	-	1	0.000006	1.36 x 10⁹	0.0090
Cr^b	1	0.001	0.0003	0.5	0.025	0.000100	1.36 x 10⁹	0.0840
Cu	1	0.001	0.003	-	1	-	1.36 x 10⁹	-
Fe	1	0.001	0.04	-	1	-	1.36 x 10⁹	-
Mn	1	0.001	0.7	-	0.04	0.000050	1.36 x 10⁹	-
Ni	1	0.001	0.024	-	0.04	0.000090	1.36 x 10⁹	0.0003
Pb	1	0.001	0.02	-	1	-	1.36 x 10⁹	-
Zn	1	0.001	0.3	-	1	-	1.36 x 10⁹	-
References	USEPA (2019d)	USEPA (2004)	USEPA (2019e)	USEPA (2019e)	USEPA (2019e) Jia et al. (2018)	USEPA (2019e)	USEPA (2019e)	USEPA (2019e)

The TEs concentration of olive orchard soils

The complementary statistical results of olive orchard soils are given in Table 3. The pH values were changed between 5.36-8.12 and 46% of them are in the mild alkaline class (7.4-7.9) (Table 3). The most abundant TEs were Al, followed by Fe and Mn. Another trace element was under their respective limits established by research and regulation According to the Regulation of Turkish Soil Pollution Control, Cu, Pb, and Zn concentrations of soils were below limit values, and Cr and Ni maximum concentrations were regarded as approximately 2.11 and 4.15 times higher than limit levels (SPCR, 2005). Concentrations of Cr and Ni pass over their limit levels in 8 (10.4%), and 15 (19.5%) samples, respectively. According to the soil world average levels (Kabata-Pendias, 2011), Cd, Cu, and Zn concentrations were lightly bigger, where about 1.2, 1.02, and 1.13 times bigger than their suitable average worldwide, respectively. While Co and Cr concentrations were bigger by about 3.5 times, Mn concentration by about 2 times, and Ni concentration was about 10 times bigger than the worldwide average. The Pb concentration was narrowly below its Worldwide and Europe average levels (Kabata-Pendias, 2011). Also, Ni, Co, Cu, Cr, Mn, Cd, and Zn concentrations were about 8.42, 3.8, 2.8, 2.2, 2.02, 1.5, and 1.16 times bigger than the European soils average (Kabata-Pendias, 2011) (Table 3). According to Rudnick & Gao (2004), Zn was about 1.19, Mn about 1.27, Cu about 1.71, Co and Cr about 2.3, Ni about 6.63 times bigger, and concentrations of Al, Fe, and Pb were below UCC values (Table 3).

Compared to mean TEs concentrations of agricultural soils in Harran Plain of Turkey, Fe and Al concentrations in our study were a little low than those in Harran Plain. Ni concentration was about 3.5, Co, Cr, and Pb about 2.5, Cu 1about.8, and Zn about 1.2 times higher than their respective in Harran plain (Varol et al., 2020) (Table 3). When compared with TEs concentration in Malatya province soils, while Ni concentration was about 4.4, Co about 3.2, Mn about 2.1, Cd and Pb about 1.8, Cu and Fe about 1.4, Zn about 1.2 were higher, Cr was slightly higher than their respective values (Varol et al., 2021) (Table 3). Also, according to Sungur and Isler (2021), Cd concentrations were below average in Canakkale agricultural soils (Table 3). These results related to various regions had distinct TEs concentrations in the soil the reason for the variability in both natural mineral corrosion and human activity.

Table 3 Summary statistics of TEs of olive orchard soils in Izmir province and comparison with other studies, regulation and average levels in the upper crust, Europe soils, and worldwide soils (mg/kg)

		Al	Cd	Co	Cr	Cu	Fe	Mn	Ni	Pb	Zn	References
Izmir Province	Mean	22520.9659	0.1762	7.5828	44.9147	19.1078	15821.2499	352.3812	37.8760	8.8498	34.8845	This study
	Median	22465.5000	0.1700	6.8300	33.8200	17.,4300	15874.6000	325.5400	24.8000	8.6100	32.7600	This study
	Standart deviation	5622.62491	0.08738	4.06986	36.49086	7.97687	5012.75707	148.31770	39.53544	4.44061	11.79008	This study
	Standart error	495.04452	0.00769	0.,35833	3.21284	0.70232	441.34865	13.05865	3.48090	0.39097	1.03806	This study
	Minimum	10955.80	0.02	2.06	9.28	6.59	5463.83	133.91	6.50	1.29	13.42	This study
	Maximum	37521.50	0.42	39.79	210.74	47.82	28834.00	984.11	311.49	25.41	79.60	This study
Soils of Worldwide		-	0.41	11.3	59.5	38.9	-	488	29	27	70	Kabata-Pendias (2011)
Soils of Europe		-	0.28	10.4	94.8	17,3	-	524	37	32	68.1	Kabata-Pendias (2011)
Maximum allowable concentration			5	50	200	150			60	300		Kabata-Pendias (2011)
Control regulation of Turkish roil		-	-	-	100	140	-	-	75	300	300	SPCR (2005)
Upper continental crust (UCC)		81500	0.09	17.3	92	28	39.200	774	47	17	67	Rudnick and Gao (2004)
Amik Plain of Turkey		-	-	20.4	-	-	-	-	274	5.6	-	Karanlik et al. (2011)
Bursa province ofTurkey		-	-	-	125	40	-	1667	158	81	477	Aydinalp and Marinova (2003)
Thrace region of Turkey		-	-	11	173	20	26900	600	50	33	45	Coskun et al. (2006)
Sinop province of Turkey		-	-	-	194.73	43,19	38849	-	85.02	17.01	65.1	Baltas et al. (2020)
Malatya province of Turkey		27524	0.244	12.6	59.9	36,4	21195	475	70.9	14.2	67	Varol et al. (2021)
Harran Plain of Turkey		42692		16	85	27	37505	679	89	10.6	68	Varol et al. (2020)
Canakkale province of Turkey		-	1.75	-	102.2	46,63	-	-	117.6	68.85	-	Sungur and Isler (2021)

Contamination indices of olive orchard soils

The calculated pollution indices (1.49 < EF < 7.18; -2.49 < Igeo < 0.16; 0.28 < Cf < 1.96) are given in Figure 2. The highest EF value was obtained by Cd (7.18). It was followed by Ni (2.94) >Cu (2.56) > Zn (1.93) > Pb (1.9) > Cr (1.79) > Mn (1.63) > Co (1.59) (Figure 2). According to Sutherland’s (2000) classification, Cd showed significantly (2-20), Ni, Cu, Zn showed moderate (2-5), and Pb, Cr, Mn, and Co showed minimal (<2) enrichment. The highest Igeo value was obtained from Cd (0.16). It was followed by Cu (-1.25) > Ni (-1.32) > Zn (-1.60) ≥ Pb (-1.72) > Mn (-1.83) > Cr (-1.92) = Co (-1.92) > Fe (-1.97) > Al (-2.49) (Figure 2). Soils were unpolluted to moderately polluted (0-1) by Cd, and unpolluted (<0) by other elements (Mazurek et al. 2017). The highest Cf values was obtained by Cd (1.96) that was followed by Ni (0.81) > Cu (0.68) > Zn (0.52) ≥ Pb (0.52) > Cr (0.49) > Mn (0.46) > Fe (0.40) > Al (0.28) (Figure 2). The soils were “moderately contaminated (1-3)” with Cd, and “low contamination (<1)” with Ni, Cu, Zn, Pb, Cr, Mn, Fe, Al. Oils, diesel oils, rotors, phosphate fertilizers, sludges, pesticides, colorings, batteries, production of semimetal, waste incineration, and manufacturing of iron and steel are all cited as possible anthropogenic sources of trace components of the environment (Lagerwerff & Specht, 1970; Sutherland 2000). In a research conducted in the olive orchards area, approximately 60% of the soils were sufficient class in terms of phosphorus (Deliboran et al., 2019). As it is known, phosphorus fertilizers have high Cd content (Assche & Clijsters, 1990). As a result of our study, it is thought that the high Cd content is due to phosphorus fertilization.

Indices of ecological risk

The highest E_r values was obtained by Cd (58.83), Cd was followed Ni (4.03) > Cu (3.41) > Pb (2.60) > Cr (0.98) > Zn (0.52) (Figure 2). According to Hakanson (1980), the olive orchard soils have “a moderate potential ecological risk (40-80)” caused by Cd. Similarly, Vural et al. (2021) suggested that Cd has the biggest E_r level in Malatya province of Turkey, and Hu et al. (2020) that in the agricultural fields of Handan (China). In the other study, Cd, Ni, and As were the highest Er level in India’s agricultural soils (Kumar et al., 2019). RI is generally found in four grades: low hazard (RI ≤ 150), middle hazard (150 < RI ≤ 300), major hazard (300 < RI ≤ 600), and upper hazard (RI > 600) (Mazurek et al., 2017; Pan et al., 2016). RI values ranged from 12.01 to 158.34, and RI levels of the vast majority of all samples were low risk (Figure 2). Only 1.5% of soils were at moderate risk with a few differences>150, because of this, soils had low ecological risk same (Figure 2) as the Harran Plain soils (Vural et al., 2020). High RI levels of soils are seldom recorded in the literature. For example, agricultural soils have a high ecological hazard in India (RI ¼ 544) because of the using agricultural practice like as chemical fertilizers or pesticides (Kumar et al., 2019), Similarly, agricultural soils have very high RI levels near a smelter in China (Wu et al., 2019).

Analysis of multivariate statistics

Pearson correlation matrix was used to determine relationships between TEs (Table 4). The highest correlation was determined between Ni and Cr (r=0.951) and between Ni and Co (r=0.813) (Table 4). Finding strong correlations between heavy metals may indicate that the elements are of the same origin or interdependent (Yi et al., 2011). The strong correlation between Cr and Ni shows that these two heavy metals originate from similar sources and were of a lithogenic origin (Taspinar et al., 2021). This highest correlation followed by Cr and Co (r=0.743), Zn and Cd (r=0.680), Mn and Al (r=0.668), Co and Fe (r=0.655), Zn and Fe (r=0.637), Cd and Fe (r=0.561), Fe and Al (r=0.543), Cu and Fe (r=0.506) (Table 4). In addition, positive correlation was found between Cd and Al (r=0.448), Co and Cd (r=0.419), Cr and Al (r=0.240), Cr and Fe (r=0.338), Cr and Cd (r=0.299), Cu and Al (r=0.266), Cu and Cd (r=0.283), Cu and Co (r=0.237) (Table 4).

Table 4 Pearson correlation analysis of TEs

	Al	Fe	Cd	Co	Cr	Cu	Mn	Ni	Pb	Zn
Al	1
Fe	0,543**	1
Cd	0,448**	0,561**	1
Co	0,468	0,655**	0,419**	1
Cr	0,240**	0,338**	0,299**	0.743**	1
Cu	0,266**	0,506**	0,283**	0.237**	0.119	1
Mn	0,668**	0,459**	0,405**	0.490**	0.256**	0.274**	1
Ni	0,222*	0,312**	0,282**	0.813**	0.951**	0.069	0.266**	1
Pb	0,405**	0,17	0,268**	-0.067	-0.207*	0.038	0.395**	-0.170	1
Zn	0,484**	0,637**	0,680**	0,312**	0.126	0.491**	0.445**	0.134	0.474**	1

Three significant components with eigenvalues >1 were identified according to the analysis of the principal component (PCA). The first component of PCA was representing 44% of the total variance. PC1 had big positive loading (≥0.7) in terms of Co, Fe, Al, Cd, Zn, and Mn (Table 5). The median concentration of these elements and Ni did not above the UCC levels (Table 3). Also, Co, Fe, Al, and Mn were connected (Table 5), and these TEs were influenced by sources of natural (lithogenic). These elements have low EF, Igeo, and Cf, and this supported this finding (Figure 2). It is accepted that the heavy metals present in PC1 consist of the decomposition of the bedrock material of lithogenic origin (Batlas et al., 2020; Chandrasekaran et al., 2015; Taspinar et al. 2021). The Cd median concentrations are above the UCC levels (Table 3), and the mean concentration of Ni is above the world soil average level (Table 3). Cd and Ni were greater than other TEs in terms of the EF, Igeo, and Cf levels (Fig. 2). Also, Cd has positively correlated with Al, Fe, Mn, and Zn which are the majority of abundant elements in the Earth’s crust (Table 4). These results related to Cd and Ni were natural origins and anthropogenic sources for example agricultural practices. It is known that phosphate fertilizers are an important source of Cd and Ni (Rutigliano et al., 2019). As a result, the first component was particularly related to lithogenic origin although agricultural practices contributed completely to Cd and Ni.

The second component represented 22% of the total variance, Pb and Zn had great positive loaded these components, while the third component represented 11% of the total variance and Pb had a high positive loaded. Pb has a positive correlation with Al, Cd, and Mn, and Zn with Fe, Cd, Cu, Al, and Pb. Also, the median concentration of these elements did not exceed the UCC and the world soil average levels (Table 3), and generally, their EF, Igeo, and Cf levels were low (Fig 2). Because of these results, Pb and Zn came from natural sources, and the second component was mostly associated with lithogenic sources. Also, it is known that the main reasons for the increase of Pb, Zn, Al, Cd, Mn, Cu, and Ni in the soils were the livestock manure and phosphorus fertilizers that are frequently used in agricultural production as anthropogenic (Baltas et al., 2020; Marrugo-Negrete et al., 2017). According to Cevik et al. (2009) and Kumar et al. (2019), the leading cause of cadmium in agriculturally produced soil is the use of fertilizers and pesticides in agriculture.

Table 5 Component matrix of TEs

Factor	PC1	PC2	PC3
Al	0.722	0.300	0.285
Fe	0.806	0.080	-0.368
Cd	0.715	0.226	-0.073
Co	0.818	-0.447	0.060
Cr	0.624	-0.703	0.114
Cu	0.485	0.237	-0.656
Mn	0.704	0.249	0.338
Ni	0.626	-0.713	0.174
Pb	0.245	0.691	0.510
Zn	0.710	0.490	-0.184
Eigenvalues	4.428	2.185	1.106
of variance	44.0	22.0	11.0
Cumulative	44.0	66.0	77.0

Indices of health risk assessment

The HQ, HI and THI leves for adults and children were below 1, considering that all TEs in soil via ingestion, skin contact, inhalation paths had no major non-carcinogenic risks (Table 6). Similar results were forwarded from the other researchs (Praveena et al., 2018; Varol et al., 2020; Varol et. al., 2021). For example, according to Taspinar et al. (2021), the THI values were below 1 for adults and children in peach orchards soils of Bilecik province. According to Jiang et al. (2017), in Jiangsu Province soils of China, for adults and children the THI values were 3.62 and 6.21, respectively. As a result of this study, for adult and children, the highest HQ values was obtained from Co, Cr and Mn via ingestion, dermal contact and inhalation, respectively (Table 6). For children, HQ_ingestionlevels declined in the order of Co (8.08E-02) > Fe (7.22E-02) > Al (7.20E-02) > Cr (4.78E-02) > Mn (4.69E-02) > Pb (2.02E-02) > Ni ( 6.05E-03) > Cu (1.53E-03) > Cd (5.75E-04) > Zn (3.72E-04), HQ_dermal levels followed the order of Cr (1.82E-02) > Mn (1.11E-02) > Ni (1.44E-03) > Co (7.67E-04) > Fe (6.86E-04) > Al (6.83E-04) > Cd (2.18E-04) > Pb (1.92E-04) > Cu (1.45E-05) > Zn (3.53E-06), and HQ_inhalation levels were found in the region of Mn (4.97E-03) > Al (3.18E-03) > Co (8.91E-04) > Cr (3.17E-04) > Ni (2.97E-04) > Cd (1.27E-05) (Table 6). For adult, HQ_ingestion values reduced in the region of Co (6.92E-03) > Fe (6.19E-039 > Al (6.17E-03) > Mn (4.02E-03) > Cr (4.10E-03) > Pb (1.73E-03) > Ni (5.19E-04) > Cu (1.31E-04) > Cd (4.93E-05) > Zn (3.19E-05), HQ_dermal values were followed the region of Cr (9.11E-04) > Mn (5.59E-04) > Ni (7.21E-05) > Co (3.85E-05) > Fe+Al (3.44E-05) > Cd (1.10E-05) > Pb (9.62E-06) > Cu (7.27E-07) > Zn (1.77E-07), and HQ_inhalation values were discovered in the region of Mn (4.97E-03) > Al (3.18E-03) > Co (8.91E-04) > Cr (3.17E-04) > Ni (2.97E-04) > Cd (1.27E-05) (Table 6).

Table 6 Non-carcinogenic and carcinogenic risks for residential receivers

Noncarcinogenic risks for adult

Noncarcinogenic risks for child

Carcinogenic risks

ingestion

dermal

HQ inhalation

ingestion

dermal

HQ inhalation

ingestion

dermal

inhalation

TCR

6,17E-03

3,43E-05

3,18E-03

9,38E-03

7,20E-02

6,83E-04

3,18E-03

7,58E-02

6,19E-03

3,44E-05

6,23E-03

7,22E-02

6,86E-04

7,29E-02

4,93E-05

1,10E-05

1,27E-05

7,30E-05

5,75E-04

2,18E-04

1,27E-05

8,06E-04

6,01E-11

6,92E-03

3,85E-05

8,91E-04

7,85E-03

8,08E-02

7,67E-04

8,91E-04

8,24E-02

1,27E-08

Cr^a

4,10E-03

9,11E-04

3,17E-04

5,33E-03

4,78E-02

1,82E-02

3,17E-04

6,63E-02

7,29E-06

3,52E-06

7,00E-07

1,15E-05

1,31E-04

7,27E-07

1,32E-04

1,53E-03

1,45E-05

1,54E-03

4,02E-03

5,59E-04

4,97E-03

9,55E-03

4,69E-02

1,11E-02

4,97E-03

6,30E-02

5,19E-04

7,21E-05

2,97E-04

8,88E-04

6,05E-03

1,44E-03

2,97E-04

7,79E-03

1,73E-03

9,62E-06

1,74E-03

2,02E-02

1,92E-04

2,04E-02

3,19E-05

1,77E-07

3,20E-05

3,72E-04

3,53E-06

3,75E-04

CHQ

THI

CHQ

THI

CCR

CTCR

2,99E-02

1,67E-03

9,66E-03

4,12E-02

3,49E-01

3,33E-02

9,66E-03

3,91E-01

7,29E-06

3,52E-06

7,13E-07

1,15E-05

HQ: hazard quotient; CHQ: cumulative HQ; HI: hazard index; THI: total HI; CR: carcinogenic risk; CCR: cumulative CR; TCR: total CR; CTCR: cumulative TCR. a b ^aCr(VI).

For adults, in terms of CHQ levels three exposure pathways have followed the region of CHQ_ingestion > CHQ_inhalation > CHQ_dermal, for children, CHQ levels have followed the region of CHQ_ingestion > CHQ_dermal> CHQ_inhalation (Table 6). For children THI level found was 8.6 times greater than adults (Table 6). This result is an indication of our study that children are further sensitive to the negative health impacts of TEs in the olive orchard soils. Many studies reported high THI values for children (Baltas et al. 2020; Jia et al., 2018; Pan et al., 2016; Rinklebe et al., 2019; Wu et al. 2018). For adults, HI values decreased in the region of Mn > Al > Co > Cr > Pb > Ni > Cu > Cd > Zn, for children followed Co > Al > Fe > Cr > Mn > Pb > Ni > Cu > Cd > Zn (Table 6). For adults and children, cumulative HQ levels of all TEs via ingestion accounted for 72,5% and 89% of THI, respectively.

The CR levels of Cd, Co, and Cr via three pathways, and TCR levels were within 1x10^-4 and 1x10^-6 as USEPA’s acceptable risk range (Table 6), thus suggesting that carcinogenic risks were not expected for residential receivers. In Turkey, similar results were found in other research areas, for example in Sinop province (Baltas et al. 2020), Harran Plain (Vural et al., 2020), and Malatya province (Vural et al., 2021). According to Wu et al. (2018), at the same time, great carcinogenic risks were fixed in the soils of the Qinghai-Tibet Plateau. In our research, TCR levels decreased in the region of Cr (1.15E-05) > Co (1.27E-08) > Cd (6.01E-11) (Table 6). The cumulative carcinogenic risk (CCR) levels in terms of all exposure pathways followed the region of CCR_ingestion > CCR_dermal> CCR_inhalation, and the CCR_ingestion level was 2.1 and 10.2 times bigger than CCR_dermal or CCR_inhalation levels, respectively (Table 6). The level of CCR_ingestion is estimated at 63.4% of the CTCR levels. Also, Cr was the major participant of the CTCR via ingestion, and dermal contact with the biggest contributions of 63.4% and 30.6%, respectively (Table 6).

Funding This work was supported by the National Boron Research Institute Directorate of Turkey (TENMAK_BOREN). “Project: 2015-30-06-20-003, Determination of Boron Nutrition of Olive (Olea europaea L.) Trees Grown in Izmir and Mugla Regions and The Effect of Boron Fertilization on The Yield and Some Quality Parameters of Olive”

Code availability Not applicable

Availability of data and materials Data may be accessed by contacting the authors.

Ethics approval Not applicable.

Consent to participate Not applicable.

Consent for publication Not applicable.

Disclosure statement I declared there is no financial/commercial conflict of interest.

Competing Interests The author declare no competing interests.

The mean level of Cr and Ni was advanced at their respective limit level designated by the Regulation of Turkish Soil Pollution Control, and maximum concentrations of Cr and Ni were about approximately 2.11 and 4.15 times higher than the limit values. The Cd, Cu, and Zn concentrations were 1.2, 1.02, and 1.13 times bigger than their similar worldwide average levels, respectively. Co and Cr concentrations were about 3.5 times, and Mn concentrations were about 2 times greater than worldwide average levels, Ni concentration was about 10 times. In terms of EF values, Cd showed high enrichment, it was followed by Ni, Cu, Zn, Pb, Cr, Mn, and Co, respectively. Based on mean Igeo values, the soils of olive orchards were contaminated with Cd as moderately polluted and followed by Ni, Cu, Zn, Pb, Cr, Mn, and Fe in terms of Cf levels. For the mean E_rvalues, the study areas have a moderate potential ecological risk caused by Cd. Soils of olive orchards in Izmir province had a low ecological risk for RI values of the vast majority due to all samples being low risk, and only 1.5% of soils were moderate risk with a few differences>150. As results of the Pearson correlation analysis, Ni and Cr have a strong correlation, and Ni and Co are due to the same origin or interdependence of these heavy metals. As a result of the principal component analysis, Co, Fe, Al, and Mn loaded the first component, and these TEs were controlled by natural sources (lithogenic). Cd and Ni were greater than other TEs in terms of the EF, Igeo, and Cf levels. Also, Cd has positively correlated with Al, Fe, Mn, and Zn which are the most abundant elements in the Earth’s crust. These results related to Cd and Ni came from both natural origins and anthropogenic sources, for example, agricultural practices like phosphate fertilizers. Also, Pb, Zn, Al, Cd, Mn, Cu, and Ni loaded the second and the third component, and the main reasons for these elements’ accumulation in orchards are agricultural activities, especially the use of chemical fertilizer and pesticides. HQ, HI, and THI levels were below 1 for adults and children, advanced that all TEs of soil had no significant non-carcinogenic risks via ingestion, dermal contact, or inhalation pathways. Among the TEs, the highest HQ levels for adults and children were obtained from Co, Cr, and mn for ingestion, dermal contact, and inhalation, respectively. THI level determined for children was 8.6 times higher than for adults. This result is an indication of our study, that children are further sensitive to the negative health effects of TEs in the soil. For adults and children, cumulative HQ levels of all TEs via ingestion accounted 72.5% and 89% of THI, respectively. The CR levels of Cd, Co, and Cr via three pathways and TCR levels were within USEPA’s tolerable risk scope of 1x10^-4 and 1x10^-6 considering that carcinogenic risks for residential receivers were not anticipated. TCR levels were reduced in the region of Cr > Co > Cd. Also, the CCRingestion level was 2.1 and 10.2 times bigger than CCRdermal and CCRinhalation levels, respectively. The level of CCRingestion was determined for 63.4% of the CTCR level. Also, Cr was the major source of the CTCR via ingestion, and dermal contact with the biggest contributions of 63.4% and 30.6%, respectively. These results suggest that this study may serve as a method for managing the contamination-related risk of olive cultivation areas where agrochemicals are widely employed. Also, additional studies are recommended about TEs contamination risk in olive crops and orchards, and the potential health dangers. Furthermore, regular monitoring procedures should be carried out in the olive orchards.

Adimalla, N., & Wang, H. (2018). Distribution, contamination, and health risk assessment of heavy metals in surface soils from Northern Telangana, India. Arabian. Journal Geosciences, 11, 684.
Adimalla, N., Chen, J., & Qian, H. (2020). Spatial characteristics of heavy metal contamination and potential human health risk assessment of Urban soils: A case study from an Urban region of South India. Ecotoxicology and Environ. Safety, 194, 110406.
Alloway, B. J. (1995). Cadmium. In: Heavy metals in soils. London. Blackie Academic and Professional. p. 122-151.
Assche, F. V., & Clijsters, H. (1990). Effects of metals on enzyme activity in plants. Plant and Cell Environment, 13, 195-206.
Aydinalp, C., & Marinova, S. (2003). Distribution and Forms of Heavy Metals in Some Agricultural Soils. Polish Journal of Environmental Studies, 12, 629-633.
Aydogdu, E. (2011). A study on the seasonal variation of plant nutrients in the leaves of Domat and Uslu olive varieties [master’s thesis]. Adana (Turkey): Cukurova University, Institute of Natural and Applied Sciences Department of Soil Science.
Aytop, H., & Senol, S. (2022). The effect of different land-use planning scenarios on the number of total soil losses in the Mikail Stream Micro Basin. Environmental Monitoring and Assessment, 194, 321.
Baltas, H., Sirin, M., Gokbayrak, E., & Ozcelik A.E. (2020). A case study on pollution and a human health risk assessment of heavy metals in agricultural soils around Sinop province, Turkey. Chemosphere, 241, 125015.
Cevik, F., Mzl, G., Derici, O.B., & Findik. O. (2009). An assessment of metal pollution in surface sediments of Seyhan dam by using enrichment factor, geo-accumulation index, and statistical analyses. Environ Monit Assess, 152(1-4), 309-317.
Chandrasekaran, A., Ravisankar, R., Harikrishnan, N., Satapathy, K. K., & Prasad, M. V. R. (2015). Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India-spectroscopical approach. Spectrochim Acta, Part A. 137, 589-600.
Coskun, M., Steinnes, E., Frontasyeva, M. V., Sjobakk, T. E., & Demkina, S. (2006). Heavy metal pollution of surface soil in the Thrace region, Turkey. Environ Monit Assess, 119, 545-556.
Deliboran, A., Savran, K., Dursun, O., Eralp, O., Pekcan, T., Turan, H. S., Aydogdu, E., Cilgin, I., Ata Olmez, H., Savran, S., Ozturk Gungor, F., Yildirim, A., & Nacar, A. S. 2019. Determination of nutritional status in terms of boron and the other elements of olives (Olea europaea L.) grown in Izmir province. Paper presented at: the 2019 International Symposium on Boron, Nevsehir, Turkey,
Deliboran, A., Cilgin, I., Aydogdu, E., Ata Olmez, H., Savran, K., Dursun, O., Eralp, O., Pekcan, T., Turan, H. S., Savran, S., Nacar, A. S., Ozturk Gungor, F., & Yildirim, A. 2022. Response of olive trees to different boron application types in Izmir and Mugla province of Turkey. Communications in Soil Science and Plant Analysis, 53(10), 1294-1307.
Deng, W., Liu, W, Li, X., & Yang, Y. (2020). Source apportionment of and potential health risks posed by trace elements in agricultural soils: a case study of the Guanzhong Plain, Northwest China. Chemosphere, 259, 127317.
Dong, R., Jia, Z., & Li, S. (2018). Risk assessment and sources identification of heavy metals in a typical country of Chongqing Municipality, Southwest China. Environmental Science Pollution Research, 22, 3498-3507.
EC, European Commission (2006). Proposal for a directive of the European Parliament and of the Council establishing a framework for the protection of soil and amending. Directive 2004/35/EC/*COM/2006/0232 final-COD 2006/0086 13. Retrieved December 5, 2021, from http://ec.europa.eu/environment/soil/index_en.htm.
Fei, X., Xia, R., Christakos, G., Langousis, A., Ren, Z., & Xiaonan, T. (2019). Comprehensive assessment and source apportionment of heavy metals in Shangai agricultural soils with different fertility levels. Ecological Indicators, 106, 105508.
Francova, A., Chrastny, V., Vitkova, M., Sillerova, H., & Komarek, M. (2020). Health risk assessment of metal(loid)s in soil and particulate matter from industrialized regions: a multidisciplinary approach. Environmental Pollution, 260, 114057.
Hakanson, L. (1980). An ecological risk ındex for aquatic pollution control a sedimentological approach. Water Research, 14(8), 975-1001. https://doi.org/10.1016/0043-1354(80)90143-8
Hu, Y., & Cheng, H. (2013). Application of stochastic models in identification and apportionment of heavy metal pollution sources in the surface soils of a large-scale region. Environmental Science Technology, 47(8), 3752-3760.
Hu, Y., & Cheng, H. (2016). The challenges and solutions for cadmium-contaminated rice in China: a critical review. Environment International, 92-93, 515-532.
Hu, Y., He, K., Sun, Z., Chen, G., & Cheng, H. (2020). Quantitative source apportionment of heavy metal(loid)s in the agricultural soils of an industrializing region and associated model uncertainty. Journal of Hazardous Material, 391, 122244.
Islam, M. S., Proshad, R., Haque, M. A., Hoque, M. F., Hossin, M. S., & Sarker, M. N. I. (2020). Assessment of heavy metals in foods around the industrial area: health hazard inference in Bangladesh. Geocarto International, 35, 280-295.
Jia, Z., Li, S., & Wang, L. (2018). Assessment of soil heavy metals for eco-environment and human health in a rapid urbanization area of the upper Yangtze Basin. Scientific Reports, 8, 3256.
Jiang, Y., Chao, S., Liu, J., Yang, Y., Chen, Y., Zhang, A., & Cao, H. (2017). Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province, China. Chemosphere, 168, 1658-1668.
Kabata-Pendias, A. (2010). Trace elements of soils and plants. 4th ed. Taylor Francis Group: CRC Press, p.548.
Karanlik, S., Agca, N., & Yalcin, M. (2011). Spatial distribution of heavy metals content in soils of Amik Plain (Hatay, Turkey). Environmental Monitoring and Assessment, 173, 181-191.
Kormoker, T., Proshad, R., Islam, M. S., Shamsuzzoha, M., Akter, A., & Tusher, T. R. (2020a). Concentrations, source apportionment, and potential health risk of toxic metals in foodstuffs of Bangladesh. Toxin Reviewers, https://doi.org/10.1080/15569543.2020.1731551.
Kumar, V., Sharma, A., Kaur, P., Sidhu, G. P. S., Bali, A. S., Bharwaj, R., Thukral, A. K., & Cerda, A. (2019). Pollution assessment of heavy metals in soils of India and ecological risk assessment: a state-of-the-art. Chemosphere, 216, 449-462.
Lagerwerff, J. V., & Specht, A. W. (1970). Contamination of roadside soil and vegetation with cadmium, nickel, lead, and zinc. Environmental Science & Technology, 4: 583-586. https://doi.org/10.1021/es60042a001
Liu, X., Song, Q., Tang, Y., Li, W., Xu, J., Wu, J., Wang, F., & Brookes, P. C. (2013). Human health risk assessment of heavy metals in the soil-vegetable system: a multi-medium analysis. The Science of the Total Environment, 463, 530-540.
Liu, J., Li, N., Zhang, W., Wei, X., Tsang, D. C. W., Sun, Y., Luo, X., Bao, Z., Zheng, W., Wang, J., Xu, G., Hou, .L, Chen, Y., & Feng, Y. (2019a). Thallium contamination in farmlands and common vegetables in a pyrite mining city and potential health risks. Environmental Pollution, 248, 906-915.
Ma, Y., Jia, Z., & Li, S. (2017). Risk assessment of heavy metals in the soil of Tongnan District (Southwest China): evidence from multiple indices with high-spatial-resolution sampling. Environmental Science and Pollution Research International, 24, 20282-20290.
Marrugo-Negrete, J., Pinedo-Hernández, J., & Díez, S. (2017). Assessment of heavy metal pollution, spatial distribution, and origin in agricultural soils along the Sinú River Basin, Colombia. Environmental Research, 154, 380-388.
Mazurek, R., Kowalska, J. B., Gasiorek, M., Zadrozny, P., Jozefowska, A., Zaleski, T., Kepka, W., Tymczuk, M., & Orlowska, K. (2017). Assesment of heavy metals contamination in surface layers of Roztocze national park forest soils (SE Poland) by indices of pollution. Chemosphere, 168, 839-850.
Muller, G. (1969). Index of geo-accumulation in sediments of the Rhine river. Geojournal, 2, 108-118.
MGM, Meteorological Service of Turkish State (2022). Retrieved March 28, 2022, from https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceler-istatistik.aspx?m=IZMIR.
Pan, L.B., Ma, J., Wang, X.L., Hou, H., 2016. Heavy metals in soils from a typical county in Shanxi Province, China: levels, sources, and spatial distribution. Chemosphere, 148, 248-254.
Praveena, S. M., Pradhan, B., & Aris, A. A. (2018). Assessment of bioavailability and human health exposure risk to heavy metals in surface soils (Klang district, Malaysia). Toxin Reviews, 37, 196-205.
Rinklebe, J., Antoniadis, V., Shaheen, S. M., Rosche, O., & Altermann, M. (2019). Health risk assessment of potentially toxic elements in soils along the central Elbe River, Germany. Environment International, 126, 76-88.
Rudnick, R.L., & Gao, S. (2004). Composition of the continental crust. In: Holland, HD, Turekian, KK, editors. Treatise on Geochemistry, Amsterdam (Holland): Elsevier. p. 1-51.
Rutigliano, F. A., Marzaioli, R., De Crescenzo, S., & Trifuoggi, M. (2019). Human health risks from consumption of two common crops grown in polluted soils. Science of the Total Environment, 691, 195-204.
Senol, M., Gul, T., Atis, E., & Salali, H. E.( 2016). The role of agriculture to prevent Water Pollution in the Gediz Basin. XII. Agriculture Economy Congress, 25-27 May 2016, Suleyman Demirel University, Agriculture Faculty, Department of Agricultural Economy, p. 2249-2256.
Shaheen, S. M., Antoniadis, V., Kwon, E., Song, H., Wang, S. L., Hseu, Z. Y., & Rinklebe, J. (2020). Pollution characteristics and health risk assessment of heavy metals in the vegetable bases of northwest China. Science of the Total Environment, 15(642), 864-878.
SPCR, Soil Pollution Control Regulation (2005). Republic of Turkey Ministry of Environment and Forestry. Official Gazette No, p. 25831.
Sungur, A., & Isler, M. (2021). Geochemical fractionation, source identification, and risk assessments for trace metals in agricultural soils adjacent to a city center (Canakkale, Turkey). Environmental Earth Sciences, 80, 299.
Sutherland, R. A. (2000). Bed Sediment-Associated Trace Metals in an Urban Stream, Oahu, Hawaii. Environmental Geology, 39(6), 611–627.
Taspinar, K., Atas, O., Yalcin, G., Kizilaslan, F., & Pinar, M. O. (2021). Soil contamination and health risk assessment of peach orchards soil of Bilecik Province Turkey. International Journal of Environmental Health Research, https://doi.org/10.1080/19603123.2021.1926439.
TUIK, Turkey Statistical Institute (2014). Retrieved March 29, 2021, from http://www.tuik.gov.tr/.
TUIK, Turkey Statistical Institute (2021). Retrieved March 29, 2021, from http://www.tuik.gov.tr/.
Tusher, T. R., Sarker, M. E., Nasrin, S., Kormoker, T., Proshad, R., Islam, M. S., AlMamun, S., & Tareq, A. R. M. (2020). Contamination of toxic metals and polycyclic aromatic hydrocarbons (PAHs) in rooftop vegetables and human health risks in Bangladesh. Toxin Reviews, https://doi.org/10.1080/15569543.2020.1767650.
USEPA, U.S. Environmental Production Agency (1989). Risk Assessment Guidance for Superfund. Human Health Evaluation Manual (Part A). Interim Final. Office of Emergency and Remedial Response. EPA/540/1–89/002.
USEPA, U.S. Environmental Production Agency (1991a). Risk Assessment Guidance for Superfund, Volume I: Human Health. Evaluation Manual, (Part B, Development of Risk-Based Preliminary Remediation Goals). Office of Emergency and Remedial Response. EPA/540/R-92/003.
USEPA, U.S. Environmental Production Agency (1991b). Human Health Evaluation Manual, Supplemental Guidance: "Standard Default Exposure Factors. OSWER Directive 9285.6-03.
USEPA, U.S. Environmental Production Agency (2002). Supplemental guidance for developing soil screening levels for superfund sites. OSWER 9355, 4-24.
USEPA, U.S. Environmental Production Agency (2004). Risk Assessment Guidance for Superfund Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment) Final. OSWER 9285.7-02EP.
USEPA, U.S. Environmental Production Agency (2011). Exposure Factors Handbook 2011 Edition. National Center for Environmental Assessment, Office of Research and Development, Washington (DC).
USEPA, U.S. Environmental Production Agency (2015). Code of Federal Regulations: Priority Pollutants List. Retrieved September 28, 2021, from https://www.epa.gov/sites/production/files/2015-09/documents/priority-pollutant-list-epa.pdf.
USEPA, U.S. Environmental Production Agency (2019a). Exposure assessment tools by media-soil and dust. Retrieved May 10, 2021, from https://www.epa.gov/expobox/exposure-assessment-toolsmedia-soil-and-dust.
USEPA, U.S. Environmental Production Agency (2019b). Regional screening levels (RSLs)- equations. Retrieved May 10, 2021, from https://www.epa.gov/risk/regional-screening-levels-rsls-equations.
USEPA, U.S. Environmental Production Agency (2019c). RSL calculator. Retrieved May 08, 2021, from https://epa-prgs.ornl. gov/cgi-bin/chemicals/csl_search.
USEPA, U.S. Environmental Production Agency (2019d). Regional screening levels (RSLs) - user’s guide. Retrieved May 10, 2021, from https://www.epa.gov/risk/regional-screening-levels-rsls-usersguide
USEPA, U.S. Environmental Production Agency (2019e). Regional removal management level (RML) resident soil table (TR-1E-04, HQ-3). Retrieved May 10, 2021, from https://semspub.epa.gov/work/HQ/199436.pdf
Unal, C. (2007). Spatial development and cluster analysis of the industry in Izmir. Journal of Ağrı İbrahim Çeçen University, Social Sciences Institute, AICUSBED 6, p.1-19, ISSN: 2149-3006, e-ISSN: 2149-4053.
Varol, M., Sunbul, M. R., Aytop, H., & Yılmaz, C. H. (2020). Environmental, ecological, and health risk of trace elements, and their sources in soils of Harran Plain, Turkey. Chemosphere, 245, 125592.
Varol, M., Sunbul, M. R., Aytop, H., & Yılmaz, C. H. (2020a). Environmental, ecological, and health risk of trace elements, and their sources in soils of Harran Plain, Turkey. Chemosphere, 245, 25592.
Vural, M., Gunduz, K., & Sunbul, M. R. (2021). Pollution status, potential sources and health risk assessment of arsenic and trace metals in agricultural soils: A case study in Malatya province, Turkey. Environmental Research, 202, 111806.
Varol, M., Gunduz, K., Sunbul, M. R., & Aytop, H. (2022). Arsenic and trace metal concentrations in different vegetable types and assessment of health risk from their consumption. Environmental Research, 206, 112252.
Varol, M., Gunduz, K., Sunbul, M. R. (2021). Pollution status, potential sources and health risk assessment of arsenic and trace metals in agricultural soils: A case study in Malatya province, Turkey. Environmental Research, 202, 111806.
Wang, S., Cai, L. M., Wen, H. H., Luo, J., Wang, Q. S., & Liu, X. (2019). Spatial distribution and source apportionment of heavy metals in soil from a typical county-level city of Guangdong Province, China. The Science of the Total Environment, 655, 92-101.
Wang, X., Dan, Z., Cui, X., Zhang, R., Zhou, S., Wenga, T., Yan, B., Chen, G., Zhang, Q., Zhong, L. (2020). Contamination, ecological and health risks of trace elements in soil of landfill and geothermal sites in Tibet. The Science of the Total Environment, 715, 136639.
Wu, J., Lu, J., Li, L., Min, X., & Luo, Y. (2018). Pollution, ecological-health risks, and sources of heavy metals in the soil of the northeastern Qinghai-Tibet Plateau. Chemosphere, 201, 234-242.
Wu, H., Yang, F., Li, H., Li, Q., Zhang, F., Ba, Y., Cui, L., Sun, L., Lv, T., Wang, N., Zhu, J. (2019). Heavy metal pollution and health risk assessment of agricultural soil near a smelter in an industrial city in China. International Journal of Environmental Health Research, 30, 174-186.
Wuana, R. A., & Okieimen, F. E. (2011). Heavy metals in contaminated soils: A review of sources, chemistry, risks and best available strategies for remediation. International Scholarly Research Notices, 2011, 402647.
Xiao, X., Zhang, J., Wang, H., Han, X., Ma, J., Ma, Y., & Luan, H. (2020). Distribution and health risk assessment of potentially toxic elements in soils around coal industrial areas, A global meta-analysis. The Science of the Total Environment, 713, 135292.
Yang, Q., Li, Z., Lu, X., Duan, Q., Huang, L., & Bi, J. (2018). A review of soil heavy metal pollution from industrial and agricultural regions in China: pollution and risk assessment.The Science of the Total Environment, 642, 690-700.
Yaylali-Abanuz, G. (2011). Heavy metal contamination of surface soil around Gebze industrial area, Turkey. Microchemical Journal, 99, 82-92.
Yi, Y., Yang, Z., & Zhang S. (2011). Ecological risk assessment of heavy metals in sediment and human health risk assessment of heavy metals in fishes in the middle and lower reaches of the Yangtze River basin. Environ. Pollut. 159, 2575-2585.

No competing interests reported.

Download PDF

Version 1

posted

You are reading this older preprint version

Read the latest preprint version →

Environmental, Ecological, and Health Risks Assessment of Olive Orchard Soils in Izmir Province of Turkey

Status:

Version 1

Abstract

Figures

Introduction

Methods And Materials

Results And Discussion

Statement And Declarations

Conclusion

References

Additional Declarations

Status:

Version 1