Soil–water–crop pathways of heavy metal contamination and human health risks in intensive smallholder farms of the Nahavand Plain, Iran

Abstract

Heavy metal (HM) contamination in intensively managed agroecosystems of arid regions poses persistent challenges for soil quality, groundwater integrity, and human health. This study presents an integrated assessment of HM concentrations, ecological pressure, and potential human health risks across 150 smallholder farms (< 1 ha) in the Nahavand Plain, Iran, encompassing wheat (45), barley (30), sugar beet (35), and coriander (40) cultivation systems. Seven metals (Cd, Pb, Hg, Cr, Ni, Cu, and Zn) were analyzed in soil and irrigation water samples using a suite of pollution indices (Cf, Igeo, PLI, Cdeg, and PERI) and health risk models (CDI, HQ, HI, and TCR). Across all cropping systems, Zn and Cu exhibited the highest concentrations, while Cd and Pb emerged as the most influential contributors to both ecological and health risk indices. Sugar beet systems consistently showed the highest contamination intensity and cumulative ecological risk, reflecting long-term intensive input management, whereas cereal-based systems displayed intermediate risk profiles. Groundwater metal concentrations were generally lower than those in soils; however, the recurrent presence of Cu, Zn, Cd, and Cr highlights the vulnerability of shallow aquifers to sustained agrochemical inputs and irrigation-related transport processes. Health risk assessment revealed pronounced age-dependent patterns, with children consistently exhibiting higher non-carcinogenic and carcinogenic risk estimates than adults across soil- and water-related exposure scenarios. Although total carcinogenic risk values generally remained within commonly accepted regulatory ranges, localized elevations—particularly in sugar beet- and wheat-dominated systems—underscore the importance of precautionary management. Elevated Pb levels observed in coriander systems indicate sensitivity to surface soil contamination rather than direct evidence of food safety non-compliance. Overall, the findings demonstrate that intensive fertilizer use and crop-specific management practices are key drivers of HM pressure in smallholder farming systems of arid regions. The results highlight the need for improved fertilizer governance, routine monitoring of soil and irrigation water quality, and the adoption of sustainable management practices to reduce long-term exposure risks and protect vulnerable populations. Future research should incorporate multi-season monitoring and refined assessment of soil–water–crop transfer pathways to better characterize cumulative exposure under diverse agricultural management scenarios.

Introduction

The rapid pace of global population growth, urbanization, and industrialization has substantially intensified agricultural production over recent decades, particularly in developing countries^1,2. While this intensification has contributed to improved food availability and economic output, it has simultaneously generated considerable environmental pressures, most notably land degradation. Among these pressures, soil contamination by heavy metals (HMs) has emerged as a critical challenge to agroecosystem sustainability, agricultural productivity, and long-term human health^3,4. Although HMs occur naturally in the Earth’s crust, anthropogenic activities—including fossil fuel combustion, industrial emissions, urban expansion, military training, and intensive agrochemical use—have markedly increased their concentrations in cultivated soils^5,6. These impacts are particularly severe in arid and semi-arid regions, where fragile soils exhibit limited buffering capacity and are highly vulnerable to degradation⁷.

Land degradation in agricultural landscapes is further intensified by deforestation, erosion, and unsustainable farming practices, including excessive fertilizer and pesticide application. As a consequence, HMs increasingly accumulate in both agricultural and peri-urban environments, leading to reduced soil fertility and progressive loss of arable land^8,9,10. Toxic metals such as cadmium (Cd), lead (Pb), mercury (Hg), and arsenic (As)—the latter classified as a metalloid—are of particular concern due to their persistence, toxicity, and capacity to exert long-term ecological and health effects¹². Numerous studies have documented elevated concentrations of Hg, Cr, Ni, Zn, Cu, and Cd in urban and peri-urban soils, primarily attributed to vehicular emissions, industrial activities, and atmospheric deposition^{11,12,13,14,15}.

Heavy metals enter agroecosystems through multiple pathways, including atmospheric deposition, irrigation with contaminated wastewater, application of phosphate fertilizers and pesticides, and surface runoff from polluted sites^16,17,18. Once introduced, metals may dissolve in soil water, bind to sediments, accumulate in biota, or remain associated with soil particles, from which they can be absorbed by plants or transported to groundwater¹⁹. Their mobility and potential bioavailability are strongly controlled by soil physicochemical properties such as pH, redox conditions, and organic matter content^20,21. Unlike many organic contaminants, HMs are not biodegradable and may persist in soils for decades, thereby posing chronic ecological and human-health risks^22,23. These characteristics underscore the necessity for integrated, pathway-oriented assessments and risk-based management strategies²⁴.

Recent studies conducted in arid and semi-arid agroecosystems have highlighted the magnitude of these challenges²⁵ demonstrated that long-term reliance on phosphate fertilizers and pesticide residues is a major driver of Cd and Pb enrichment in dryland soils, particularly under low organic-matter conditions that enhance metal mobility. Expanding on this work²⁶, reported pronounced spatial heterogeneity of toxic metals in smallholder farms (< 1 ha), emphasizing the need for spatially extensive sampling frameworks comparable to the approach adopted in the present study. Additional evidence from²⁷ indicates that soil physicochemical properties—including pH, electrical conductivity (EC), and organic matter—play a central role in regulating metal fractionation, soil–plant interactions, and potential health risks in arid environments. Collectively, these findings underscore the importance of integrated soil–water–crop assessments in regions where fertilizer dependence and irrigation variability intensify contamination pressures, such as the Nahavand Plain.

Land-use type further modifies HM geochemistry by altering soil physical and chemical conditions^28,29,30. In agricultural systems, crop–metal interactions influence metal distribution within the soil–plant continuum, with implications for environmental exposure pathways^31,32. Metal uptake by crops is governed by complex interactions among plant species, soil pH, organic matter, and root–metal dynamics^33,34,35,36. Previous studies have shown that barley and rice may accumulate higher levels of Cd and As, whereas wheat and maize generally exhibit lower uptake under comparable conditions^37,38,39,40. Once absorbed, metals can be translocated to above-ground tissues, contributing to potential soil-to-human exposure pathways⁴¹. For example, Pb has been shown to associate with grain outer layers and to utilize transport mechanisms shared with essential nutrients such as calcium and magnesium^42,43,44.

Phosphate fertilizers are widely recognized as a major agricultural source of Cd and other trace metals^45,46, while soil pH and redox potential exert strong control over HM precipitation and mobility^47,48. Symptoms of HM toxicity in plants include chlorosis, reduced biomass, and impaired physiological function, with toxicity rankings generally following the order Cd > As > Pb > Hg > Cr^49,50. Water resources are similarly susceptible, receiving HM inputs through industrial discharges, agricultural runoff, and infrastructure corrosion^51,52,53. Numerous epidemiological studies have linked HM exposure to adverse health outcomes, including renal and hepatic dysfunction, neurological impairment, carcinogenesis, and reproductive effects⁵⁴. Children are particularly vulnerable; for instance²⁴, reported significantly higher hazard indices for Pb and Cr in children even where overall concentrations remained within guideline limits. Additional studies have demonstrated both the potential for risk reduction through improved water treatment⁵⁵ and the severity of contamination in agricultural regions with prolonged fertilizer use⁶.

Despite the persistence and severity of HM contamination—particularly in regions with long histories of intensive agriculture—integrated studies that simultaneously address environmental contamination and human-health risks remain limited, especially for smallholder farming systems. In Iran, fertilizer use has increased approximately 330-fold over the past five decades, accompanied by a 10–30% annual rise in soil dependence on chemical inputs^56,57. However, most existing studies focus on large-scale farms, single crops, or isolated environmental compartments, leaving smallholder systems (< 1 ha) in arid regions underrepresented. To address this gap, the present study investigates the concentrations of key hazardous heavy metals (Hg, Cr, Ni, Pb, Zn, Cu, and Cd) in soils and irrigation water across 150 intensively managed smallholder farms in the Nahavand Plain, encompassing wheat (45 farms), barley (30), sugar beet (35), and coriander (40) cultivation systems. The study adopts an integrated, multi-compartment approach that links HM concentrations in soil and irrigation water with ecological indices and USEPA-based human health risk models for adults and children. Importantly, crop measurements are used to illustrate soil–plant transfer within the exposure pathway rather than to assess direct dietary compliance. The objectives of this study are to: (i) quantify and compare HM concentrations across cropping systems; (ii) evaluate contamination and ecological pressure using established indices; (iii) identify crop systems associated with elevated soil contamination; and (iv) assess non-carcinogenic and carcinogenic risks through ingestion, dermal contact, and inhalation pathways. By integrating environmental contamination metrics with health-risk assessment, this study provides evidence-based insights to support sustainable fertilizer management, irrigation-water monitoring, and public-health protection strategies in smallholder agricultural communities of arid regions.

Materials and methods

Study area

This research was conducted in the Nahavand Plain, one of the most important agricultural zones in Hamedan Province, western Iran, encompassing intensively managed wheat, barley, sugar beet, and coriander farms (Fig. 1). The plain is located at approximately 33°57′N latitude and 47°53′E longitude. Based on the De Martonne classification, the area is categorized as arid, while the Ambergris system defines it as arid–cold. The mean annual temperature is 14 °C, with July being the warmest month (37 °C on average) and January the coldest (− 2.5 °C). During the 2023–2024 agricultural year, annual precipitation averaged 330 mm, while reference evapotranspiration (ET_ref) reached 1952 mm, indicating a pronounced winter rainfall peak followed by a hot, dry summer⁵⁸.

Fig. 1

Location of sampled agroecosystems in the Nahavand Plain, Hamedan Province, Iran. The map was generated using QGIS (version 3.28; https://www.qgis.org) based on Sentinel-2 satellite imagery provided by the Copernicus Open Access Hub (European Space Agency). Sentinel data are freely available under the Copernicus Open Access Policy.

Agriculture is the backbone of Nahavand’s economy, supported by fertile soils and favorable climatic conditions, which make it one of the most productive farming regions in Hamedan Province. The landscape is a mosaic of high-intensity cultivation interspersed with remnant natural habitats, shaped by centuries of traditional agricultural practices. However, increasing urban expansion, unregulated industrial growth, and declining rainfall—sometimes dropping below 172 mm—are now threatening crop productivity and long-term resource sustainability. For the present study, farms located within urbanized zones, steep slopes, or industrial sites were excluded to minimize confounding effects. Selected sites represented dominant monoculture wheat systems and other high-input cropping practices prevalent in the region. Figure 1 represents a location map of the sampled farms and was included solely to document spatial coverage; no spatial interpolation or geostatistical modeling was performed.

Sampling of soil, water and crop

In November 2024, a comprehensive sampling campaign was conducted across 150 farms cultivating wheat, barley, sugar beet, and coriander (Fig. 1). At each site, surface soil samples were collected from the 0–30 cm layer using a composite strategy in which five subsamples (four corners and one center) were combined to obtain a representative sample for farms smaller than 1 ha. The 0–30 cm depth was selected because previous field observations in the same region showed no appreciable difference in HM concentrations between 0–30 cm and 30–60 cm profiles. This layer also represents the agronomically active plough zone, where fertilizers, pesticides, and root activity are concentrated, making it the most relevant depth for assessing metal accumulation and risk pathways in intensive farming systems. The resulting dataset of soil physicochemical properties (pH, EC, OM, and NC) across the four soil cropping systems^59,60 is illustrated in (Fig. 2). This study was conducted during a single agricultural season. Although seasonal moisture and redox changes can influence HM mobility⁶, indicated that total metal concentrations in the 0–30 cm plough layer remain relatively stable across seasons due to long-term agrochemical inputs and soil parent-material characteristics. Therefore, the single-season sampling is unlikely to affect the overall contamination or risk interpretation.

Fig. 2

Spatial variation of key soil physicochemical properties—(a) pH, (b) electrical conductivity (EC), (c) organic matter (OM), and (d) nitrogen content (NC)—across wheat, barley, sugar beet, and coriander farming systems in the Nahavand Plain, Hamedan Province, Iran.

During sampling, qualitative information on fertilizer type, pesticide use, and irrigation method was obtained through farmer interviews to document general management practices. However, precise quantitative records were not available for most smallholder farms, and therefore input data were used descriptively rather than in numerical form. Heavy metal source interpretation relied primarily on pollution indices and measured concentrations in soil, water, and crop tissues.

Crop sampling

Crop samples were harvested at physiological maturity. Whole above-ground biomass—including stems, leaves, and reproductive tissues—was collected for each crop as a single composite sample. Edible components such as wheat grain or sugar beet root were not separated, because the objective of plant sampling in this study was to quantify overall heavy-metal accumulation in aerial biomass rather than to evaluate dietary exposure. All plant samples were air-dried in shade to preserve tissue integrity, ground to a fine powder, and digested for metal analysis. Heavy-metal concentrations in plant tissues were therefore determined and reported on a dry-weight (DW) basis.

Soil sample processing and characterization

Soil samples were cleaned of visible debris, air-dried at laboratory temperature (~ 22 °C), and passed through a 2-mm sieve. Texture was determined by standard sieving, separating particles into sand (2.00–0.02 mm), silt (0.02–0.002 mm), and clay (< 0.002 mm). Soil pH was measured potentiometrically (Model PB-10, Sartorius, Germany) in a 1:2.5 soil-to-water mixture. Organic matter (OM) was quantified by the dichromate oxidation method⁶¹, and total nitrogen was measured using an elemental analyzer (vario EL III, Elementar, Germany). Across the four cropping systems, EC varied from 288 to 1,811 µS cm⁻¹, with sugar beet fields exhibiting the highest salinity levels (> 1,800 µS cm⁻¹), likely due to intensive irrigation. Soil pH ranged from 7.35 to 8.10, indicating neutral to slightly alkaline conditions suitable for crop growth. OM content was generally low (0.04–0.34%), with coriander soils showing relatively higher values. Nitrogen concentrations ranged from 0.002 to 0.017 mg l⁻¹, reflecting variability in nutrient availability across farms (Fig. 2).

Water sampling

A total of 150 irrigation-water samples were collected from adjacent surface waters, springs, and groundwater wells to ensure comprehensive hydrological representation across the study area. Samples were taken using acid-washed polyethylene bottles that were rinsed on-site with source water prior to final filling. Immediately after collection, all samples were acidified with 5% HNO₃ and stored in dark, cooled containers to prevent physicochemical alteration before analysis. Physicochemical parameters—including pH, electrical conductivity (EC), temperature, total dissolved solids (TDS), and nitrate (NO₃^-)—were measured following standardized analytical protocols⁶². Organoleptic properties (taste, odor, color, and turbidity) were assessed in the field and compared with⁶³ and⁶⁴ guidelines to evaluate suitability for drinking and irrigation. Irrigation sources were categorized into surface waters (rivers and canals), groundwater wells, and natural springs based on hydrological origin and farmer-reported usage. The purpose of water sampling in this study was to assess the overall irrigation-water quality of the region rather than to compare contamination differences among these source types.

Quality assurance and quality control (QA/QC) procedures were implemented throughout sampling and analysis. These included the use of pre-cleaned, acid-washed bottles, on-site rinsing prior to collection, immediate acidification, and laboratory-based controls such as reagent blanks, calibration blanks, and triplicate measurements. Although field blanks were not collected due to logistical constraints imposed by smallholder access conditions, the combined QA/QC measures ensured the reliability, accuracy, and integrity of the irrigation-water dataset.

Total phosphorus (TP) and total potassium (TK) concentrations in soil and plant tissues were measured using an automated continuous flow analyzer (Bran + Luebbe AutoAnalyzer, SPX, Charlotte, NC, USA), following established protocols. For heavy metal analysis, soil and crop samples were digested with a mixture of HNO₃, H₂SO₄, and HClO₄ to ensure complete mineralization. Digestion accuracy was ensured through the use of certified reference materials (CRM) and internal quality-control samples routinely applied by the analytical laboratory. Recovery percentages for all elements were within the acceptable range of 85–105%, consistent with USEPA 3050B and APHA (2017) standards⁶⁵. Concentrations of Zn, Cu, Cr, Ni, Pb, and Cd were then determined using inductively coupled plasma atomic emission spectrometry (ICP-AES 3410 ARL), which provides high sensitivity and precision. In parallel, separate samples were digested with aqua regia (HNO₃: HCl, 1:3) for the quantification of Hg and As using atomic fluorescence spectrometry (AFS), a technique widely recognized for its accuracy in trace metal detection. Quality assurance and validation were achieved by analyzing certified reference materials, ensuring reproducibility and reliability of the results (Table 1). To contextualize the measured HM levels, background concentrations, toxicity response factors, and maximum allowable concentrations (MAC) were compiled from both international guidelines and national environmental standards. For each metal and environmental compartment, differences among cropping systems were evaluated using one-way ANOVA with Tukey’s HSD post hoc test (α = 0.05), treating each farm as an independent observation.

Table 1 Reference background concentrations, toxicity response factors, and regulatory thresholds for selected heavy metals in soil (mg kg⁻¹).

Contamination factor (C_f) and pollution assessment indices

The contamination factor (C_f) is a widely used metric to evaluate HM enrichment in soils relative to natural background concentrations. Originally proposed by⁶⁹ for sediments, it remains a fundamental parameter in soil pollution studies. Cf was calculated as:

$$C_{f} = \frac{{C_{n} }}{{B_{v} }} \,$$

(1)

where C_n (mg kg⁻¹) is the measured concentration of the metal in the soil, and B_v (mg kg⁻¹) is the corresponding geochemical background value (Table 2).

Table 2 Contamination factor (C_f) classification for HMs in soil.

To further assess pollution severity, additional indices were applied: The degree of contamination (C_deg), the pollution load index (PLI), and the potential ecological risk index (PERI). These indices provide a multidimensional evaluation by integrating metal concentrations, toxicity response factors, and cumulative ecological risks (Table 3).

Table 3 Summary of pollution indices and their corresponding contamination intensity categories.

Regional baseline values for the Nahavand Plain are not available in published geochemical surveys, and deep undisturbed soil layers (> 60 cm) could not be sampled due to field-access limitations. Therefore, background concentrations were adopted from standard global geochemical datasets (Turekian & Wedepohl), which are widely used for pollution index calculations in arid-region heavy metal studies. This approach provides a consistent and scientifically valid baseline for calculating C_f, I_geo, PLI, and PERI. These indices are widely applied in heavy-metal assessments across arid and semi-arid regions, and their underlying assumptions are not affected by soil moisture regime or climatic conditions, making them appropriate for the environmental context of the Nahavand Plain.

C_deg assessment

The degree of contamination (C_deg) is a cumulative index designed to evaluate the overall intensity of HM pollution within a given site. It aggregates the contamination factors (C_f) of all metals analyzed, thereby providing a single measure of total contamination pressure. First proposed by⁶⁹, Cdeg is calculated as:

$$C_{\deg } \, = \sum\limits_{i = 1}^{n} {C_{{f_{i} }} }$$

(2)

where $C_{{f_{i} }}$ is the contamination factor of the i^th metal, and n is the total number of metals assessed (seven in this study). Pollution severity levels are classified according to the thresholds shown in (Table 3), facilitating interpretation of site contamination status.

PLI assessment

The pollution load index (PLI) offers an integrated evaluation of soil contamination by condensing the multiple C_f values of different metals into a single representative score. This metric, originally introduced by⁷⁰, is calculated as the geometric mean of contamination factors:

$$PLI \, = \, \left( {{\text{ C}}_{f1} \times \, C_{f2} \times C_{f3} \times ... \times C_{fn} } \right)^{1/n}$$

(3)

where n is the number of metals considered. PLI values provide a straightforward classification of soil quality, distinguishing between uncontaminated and heavily polluted sites. Thresholds are presented in (Table 3).

PERI assessment

The potential ecological risk index (PERI) is applied to assess the ecological implications of HM contamination in soils by integrating both contamination levels and the toxicological significance of metals. Developed by⁶⁹, PERI is expressed as:

$$PERI \, = \, \sum\limits_{i = 1}^{n} {E_{r}^{i} } = \sum\limits_{i = 1}^{n} {T_{r}^{i} } \, \times C_{{f_{i} }}$$

(4)

Here, $E_{r}^{i}$ is the ecological risk factor for the i^th metal, $T_{r}^{i}$ is the corresponding toxicity response factor (Table 4), and $C_{{f_{i} }}$ is the contamination factor. This index enables identification of sites with elevated ecological risk, with risk categories ranging from low to very high as summarized in (Table 3).

Table 4 Toxicity response factors ($T_{r}^{i}$) for selected HMs.

Assessment of HM pollution using the geoaccumulation index (I_geo)

The geoaccumulation index (I_geo), introduced by⁷¹, is a widely used tool for quantifying the degree of HM contamination in soils. This index compares present-day metal concentrations with corresponding geochemical background values, incorporating a correction factor to account for natural variations. The I_geo is calculated as:

$$I_{geo} \, = \, log \, \frac{{C_{n} }}{{1.5B_{v} }}$$

(5)

where C_n is the measured concentration of a given metal (mg kg^-1), Bv is the geochemical background concentration (mg kg⁻¹), and 1.5 is a correction factor to accommodate natural background variability. Interpretation of I_geo values follows the classification scheme shown in (Table 5).

Table 5 Classification of geoaccumulation index (Igeo) values and corresponding pollution levels.

Health risk assessment of HMs in soil

Health risk assessment is a fundamental step in determining the potential adverse impacts of HM exposure on human health⁷². This process involves four components: hazard identification, exposure assessment, dose–response evaluation, and risk characterization^{73, 74}. Humans may come into contact with soil-borne metals through three primary pathways: ingestion, inhalation, and dermal absorption. Soil ingestion was assessed as the primary exposure pathway because it is a standard USEPA- and WHO-recommended scenario, especially for children in rural agricultural settings. Dietary exposure was not modeled because edible plant tissues were not sampled separately, and using whole-plant concentrations for food-safety calculations would lead to overestimation and misinterpretation^75,76.

The chronic daily intake (CDI) for each pathway is estimated as follows:

- Ingestion pathway:

$$CDI_{ing} \, = \, \frac{{C_{soil} \times R_{Ing} \times {\text{EF}} \times ED}}{BW \times AT}$$

(6)

where CDI_ing (mg kg^-1 day^-1) is the daily intake via ingestion, Csoil is the concentration of HMs in soil (mg kg⁻¹), IngR is the ingestion rate (mg day^-1), EF is exposure frequency (days year^-1), ED is exposure duration (years), BW is body weight (kg), and AT is the averaging time (days).

- Inhalation pathway:

$$CDI_{inh} \, = \, \frac{{C_{soil} \times Inh \, R_{soil} \times EF \times ED}}{PEF \times BW \times AT} \,$$

(7)

where CDI_inh (mg kg^-1 day^-1) represents daily intake via inhalation, InhR is the inhalation rate (m³ day^-1), and PEF is the particulate emission factor (m³ kg^-1).

- Dermal pathway:

$$CDI_{derm} \, = \, \frac{{C_{soil} \times SA \times AF \times ABS \times EF \times ED}}{BW \times AT}$$

(8)

where CDIderm (mg kg^-1 day^-1) represents intake via dermal contact, SA is exposed skin surface area (cm²), AF is soil adherence factor (mg cm² day^-1), and ABS is the dermal absorption fraction (unitless). The parameter values adopted for adults and children are summarized in (Table 6), sourced from standard guidelines and previous studies^72,76,77.

Table 6 Parameters used for calculating chronic daily intake (CDI) of heavy metals for adults and children.

Based on CDI values, both non-carcinogenic and carcinogenic health risks can be quantified:

- Hazard quotient (HQ):

$$HQ = \sum \frac{CDI}{{RfD}}$$

(9)

where RfD is the reference dose. An HQ < 1 indicates negligible risk, while HQ ≥ 1 implies potential adverse effects.

- Hazard index (HI):

$$HI \, = \sum HQ \, = HQ_{ing} + HQ_{inh} + HQ_{derm}$$

(10)

Represents the cumulative non-carcinogenic risk across all metals and pathways.

- Carcinogenic risk (CR):

$$CR \, = \, CDI \, \times \, CSF$$

(11)

where CSF is the cancer slope factor.

- Total carcinogenic risk (TCR):

$$TCR \, = \sum \left( { \, CDI \, \times \, CSF_{ing} } \right) + \left( {CDI \, \times \, CSF_{inh} } \right) + \left( {CDI \, \times \, CSF_{derm} } \right)$$

(12)

Represents the aggregated carcinogenic risk across metals and exposure routes. RfD and cancer slope factors (CSF) for each HM and exposure pathway are provided in (Table 7). These toxicity parameters are sourced from authoritative databases and previous studies^{72,78,79,80,81,82}.

Table 7 Reference doses (RfD; mg kg^-1 day^-1) and carcinogenic slope factors (CSF; mg kg^-1 day^-1) for heavy metals via different exposure pathways.

According to⁷⁶, an HI < 1 suggests no significant non-carcinogenic health hazard, while HI ≥ 1 signals potential health concerns. For carcinogenic effects, a TCR between 1.0 × 10⁻⁶ and 1.0 × 10⁻⁴ is generally regarded as acceptable, values < 1.0 × 10^–6 imply negligible risk, and values > 1.0 × 10⁻⁴ indicate potential carcinogenic threats requiring attention⁸³.

Assessment of HM pollution in groundwater

Exposure assessment

The average daily dose (ADD) represents the amount of contaminant ingested per unit body weight per day during the exposure period. It was calculated as:

$$ADD = \, \frac{C \times IR \times EF \times ED}{{BW \times AT}} \,$$

(13)

where ADD (mg kg^-1 day^-1) is the daily intake, C (mg l^-1) is the HM concentration in groundwater, IR is the water ingestion rate (2 lit day^-1 for adults; 1 lit day⁻¹ for children), EF is exposure frequency (365 days year^-1), ED is exposure duration (70 years for adults; 10 years for children), BW is average body weight (72 kg adults; 32.7 kg children), and AT is the averaging time expressed as lifetime (25,550 days adults; 3,650 days children).

This equation quantifies the normalized daily intake of HMs through groundwater, accounting for exposure duration and frequency.

Human health risk assessment

Both non-carcinogenic and carcinogenic risks from groundwater ingestion were estimated.

- Non-carcinogenic risk:

The hazard quotient (HQ) was calculated as:

$$HQ \, = \, \frac{ADD}{{RfD}}$$

(14)

where RfD (mg kg⁻¹ day⁻¹) is the oral reference dose. An HQ > 1 indicates potential for adverse non-carcinogenic health effects. The parameters applied in this study are presented in (Table 8).

Table 8 Parameters used for health risk assessment via groundwater ingestion.

- Carcinogenic risk:

The excess lifetime cancer risk (ELCR) was estimated using:

$$ELCR{ = }ADD \times CSF$$

(15)

where CSF (mg kg^-1 day^-1) is the cancer slope factor, representing the lifetime probability of developing cancer from exposure to a carcinogen. The regulatory threshold for ELCR generally ranges from 1.0 × 10⁻⁶ to 1.0 × 10⁻⁴; values above this range suggest an elevated cancer risk. The RfD and CSF values applied in this study were compiled from USEPA guidelines and recent literature (Table 9).

Table 9 Reference doses (RfD; mg kg^-1 day^-1) and cancer slope factors (CSF; mg kg⁻¹ day⁻¹) for selected HMs.

It should be noted that pollution indices and health risk metrics applied in this study (including Cf, Igeo, PERI, CDI, HQ, HI, TCR, and ELCR) are deterministic outputs of established assessment models. These indices are calculated directly from measured concentrations and fixed exposure or toxicity parameters. Accordingly, inferential statistical tests (e.g., ANOVA, LSD, or DMRT) are not methodologically applicable to these metrics.

Results and discussion

Concentration and distribution of HMs in soil, groundwater, and crops

The measured concentrations of Cd, Cu, Zn, Pb, Ni, Cr, and Hg varied significantly among soils, groundwater, and crop biomass across the Nahavand Plain, reflecting differences in cropping systems, management intensity, and local agroecological conditions (Fig. 3). Based on one-way ANOVA followed by Tukey’s HSD test, statistically significant differences among cropping systems were observed separately for each metal within soil, groundwater, and crop compartments (p < 0.05).

Fig. 3

Concentration of heavy metals (HMs) in soil, groundwater, and crops in the Nahavand Plain. Differences among cropping systems were tested separately for each metal using one-way ANOVA followed by Tukey’s HSD test (p < 0.05). Different letters indicate significant differences within each panel. Different letters indicate statistically significant differences among cropping systems based on one-way ANOVA followed by Tukey’s HSD test (p < 0.05).

In soils, Zn and Cu consistently exhibited the highest measured concentrations across all cropping systems, with maximum values reaching 1719.9 and 595.5 mg kg^-1, respectively, particularly under wheat and sugar beet cultivation. In contrast, Cd and Hg occurred at substantially lower concentrations (< 1.6 mg kg^-1 and < 0.06 mg kg^-1, respectively). Mercury levels were uniformly low across farms, and the limited spatial variability observed does not indicate distinct contamination hotspots. As direct measurements of Hg inputs were not conducted, these concentrations are more plausibly attributed to background geogenic sources or atmospheric deposition rather than dominant anthropogenic inputs⁸⁹. The pronounced enrichment of Zn and Cu relative to background levels is consistent with long-term fertilizer and pesticide use, as many commercial formulations contain trace metal impurities^6,46. Soils under sugar beet cultivation exhibited significantly higher concentrations of Cd (up to 20.3 mg kg^-1) and Pb (> 24 mg kg^-1), suggesting localized contamination associated with intensive agrochemical application. Similar enrichment patterns have been widely reported in intensively managed agricultural systems, where Cd and Pb inputs are commonly linked to phosphate fertilizers and wastewater irrigation^18,24. Although the chemical composition of fertilizers and pesticides was not directly analyzed in this study, the observed soil concentrations align with well-established contamination pathways documented in regional studies.

Groundwater contained markedly lower HM concentrations than soils; however, Cu (up to 35.3 mg l^-1) and Zn (up to 285.9 mg l^-1) were detected across nearly all sampling locations, indicating high mobility of these elements in shallow aquifers (Fig. 3). While Pb and Ni concentrations generally remained below 3 mg l^-1, their frequent occurrence raises concerns regarding long-term groundwater quality, particularly given the reliance on groundwater for both irrigation and domestic use in the region. Mercury concentrations in groundwater were low overall, but localized values (~ 1.26 mg l^-1) warrant attention due to Hg’s high toxicity even at trace levels^84,90. These observations underscore the susceptibility of shallow aquifers in arid agricultural environments, where agrochemical leaching, soil erosion, and irrigation return flows serve as key contaminant transport pathways^16,19.

Measured HM concentrations in crop biomass further illustrate the transfer of metals along the soil–crop pathway (Fig. 3). In wheat biomass, Cu and Zn concentrations reached 309.7 and 163.9 mg kg^-1 (dry weight), respectively, while Cd ranged from 1.3 to 1.8 mg kg^-1. Barley showed a comparable pattern, with Zn concentrations exceeding 218.6 mg kg^-1. Sugar beet exhibited the highest measured concentrations among the studied crops, with Zn surpassing 3400 mg kg^-1 and Cd reaching up to 18.4 mg kg^-1 in some samples. In contrast, coriander generally showed lower concentrations for most metals (< 1 mg kg^-1), although moderate Cu and Zn levels were observed. It should be noted that all plant concentrations are reported on a dry-weight basis⁶³, which may yield higher numerical values than wet-weight measurements reported in some regulatory standards.

The observed inter-crop variability in measured metal concentrations reflects differences in root architecture, soil–plant interactions, and uptake-related physiological traits^33,36. Such variability emphasizes the influence of crop type and management practices on metal presence in above-ground biomass and, consequently, potential dietary exposure pathways. Notably, coriander exhibited relatively higher Pb concentrations despite lower corresponding soil Pb levels, likely due to its shallow, fibrous root system that enhances interaction with surface soil layers where Pb bioavailability is greater. Moreover, Pb mobility is strongly governed by soil pH, salinity, and irrigation regime rather than total soil concentration alone, which helps explain the observed patterns across crops.

From a sustainability perspective, these results reveal a dual challenge: agricultural soils act as long-term sinks for Zn, Cu, Pb, and Cd, while groundwater provides an efficient pathway for contaminant redistribution and chronic human exposure. Elevated metal concentrations in sugar beet systems are of particular concern because root crops are consumed directly, increasing the potential for dietary exposure^31,40. Likewise, the presence of Cd, Zn, and Cu in staple cereals such as wheat and barley highlights potential implications for food security in regions with high dependence on these crops. Persistent HM occurrence in groundwater further amplifies these risks. Addressing these challenges requires integrated management strategies, including stricter regulation of agrochemical inputs, routine monitoring of soil and irrigation water quality, and diversification toward cropping systems associated with lower measured metal concentrations, to safeguard long-term agroecosystem and food-system resilience^56,91,92.

Sources and controlling factors of HMs in soils

Correlation analysis revealed crop-specific yet internally consistent relationships between heavy metals (HMs) and soil physicochemical properties, enabling differentiation between lithogenic background contributions and anthropogenic inputs across the Nahavand Plain (Fig. 4). These relationships provide insight into dominant contamination pathways and controlling factors under contrasting cropping systems.

Fig. 4

Pearson’s correlation matrix between heavy metals and soil physicochemical properties under four major cropping systems in the Nahavand Plain: (a) wheat, (b) barley, (c) sugar beet, and (d) coriander.

In wheat fields, Cd showed strong positive correlations with Pb (R = 0.69) and Ni (R = 0.50), while Pb was also significantly correlated with Ni (R = 0.53) (Fig. 4a). Such associations point to a shared anthropogenic origin, most plausibly linked to prolonged application of phosphate fertilizers and wastewater irrigation, both of which are widely practiced in wheat cultivation. The significant correlation between Ni and electrical conductivity (EC; R = 0.52) further highlights the role of salinity in enhancing metal mobility. In contrast, Zn and Cu exhibited weak correlations with soil parameters (R < 0.20), suggesting greater dispersion or dilution under continuous cropping conditions. Collectively, these patterns indicate that while soil salinity and organic matter may limit the mobility of certain metals, they can simultaneously facilitate the presence of Cd and Pb, posing risks to soil quality and food safety.

In barley soils, Cr and Ni were strongly correlated (R = 0.59), with Ni also positively associated with Pb (R = 0.43) and Cd (R = 0.45) (Fig. 4b). The Cr–Ni relationship is characteristic of lithogenic sources, as clay-rich soils in the region tend to retain metals derived from parent material. However, the concurrent correlations of Cd with Pb and EC indicate superimposed anthropogenic influences, most likely arising from long-term fertilizer use. This combination of geogenic background and agricultural intensification raises concern regarding cumulative contamination and its potential transfer to groundwater and food systems.

Sugar beet fields displayed a distinct correlation structure (Fig. 4c). Cu and Zn showed strong positive relationships with soil organic matter (R = 0.45 and R = 0.43, respectively), consistent with enrichment through micronutrient fertilizers and pesticide inputs. Pb and Cd were also positively correlated (R = 0.50), reinforcing the role of fertilizer-related contamination. In addition, Ni exhibited a significant correlation with EC (R = 0.46), suggesting enhanced mobility under saline conditions—a critical issue given the high irrigation demand of sugar beet cultivation. Together, these relationships indicate that intensive irrigation and fertilizer inputs substantially increase heavy-metal loading in sugar beet production systems. In coriander soils, Hg was significantly correlated with soil organic matter (R = 0.39) and pH (R = 0.33), indicating enhanced retention under alkaline and organic-enriched conditions (Fig. 4d). Cr and Ni were strongly correlated (R = 0.73), confirming their predominantly lithogenic origin. In contrast, Cd showed positive correlations with Pb (R = 0.63) and Ni (R = 0.46), reflecting a notable anthropogenic contribution. Given that coriander is typically consumed fresh and without processing, the presence of Cd and Pb within its production systems represents a direct food-safety concern in addition to an environmental issue.

Soil physicochemical properties play a central role in regulating metal behavior across the study area. The slightly alkaline soil pH (7.3–8.1) limits the mobility of Pb, Cu, and Zn through adsorption and precipitation processes, whereas Cd and Ni remain comparatively mobile under similar conditions. Very low organic matter content (0.04–0.34%) restricts complexation with organic ligands, increasing the proportion of metals present in more bioavailable forms. Elevated EC values in some fields further enhance ionic activity, facilitating the mobility of specific metals, particularly Cd and Pb. Overall, the observed correlation patterns indicate that heavy-metal presence in the Nahavand Plain reflects the combined influence of natural soil-forming processes and intensified agricultural practices. The recurrent co-occurrence of Cd and Pb across all cropping systems strongly implicates phosphate fertilizers as a dominant anthropogenic source, while Cr and Ni relationships reflect the lithogenic signature of the region. The amplification of these background signals by unsustainable management practices—including fertilizer overuse, saline irrigation, and limited monitoring—highlights a critical policy gap. Addressing these challenges requires integrated soil and water quality monitoring alongside sustainable farming strategies, such as improving fertilizer-use efficiency, adopting biofertilizers, and enforcing irrigation-water quality standards^93,94. Such measures are essential not only for protecting ecosystem integrity but also for ensuring food safety in line with international standards^91,92.

Assessment of pollution indicators

The contamination factor (C_f) was used to characterize the intensity of soil heavy metal contamination relative to local background levels across the Nahavand Plain (Fig. 5). Overall, Cd, Cu, and Zn exhibited the highest C_f values and the widest variability among the investigated metals, particularly in soils under sugar beet cultivation. Wheat fields also showed elevated C_f values for these elements, whereas coriander soils consistently exhibited lower C_f levels across most metals. In contrast, Pb, Ni, Cr, and Hg generally displayed C_f values below unity across all cropping systems, indicating low contamination intensity within the Cf classification framework. As noted by the reviewer, C_f < 1 does not imply the absence of environmental concern but rather reflects lower contamination intensity according to index thresholds, highlighting the importance of complementary indices for comprehensive risk interpretation. Collectively, the C_f results identify Zn, Cu, and Cd as the primary contributors to soil contamination intensity in the study area, with higher values observed in intensively managed cropping systems.

Fig. 5

Log-transformed contamination factor (C_f), geoaccumulation index (I_geo), and pollution load index (PLI) for heavy metals in soils under four cropping systems of the Nahavand Plain. Values represent deterministic pollution indices calculated from measured concentrations; therefore, inferential statistical testing was not applicable.

The geoaccumulation index (I_geo) provided additional insight into metal enrichment patterns relative to pre-industrial background conditions (Fig. 5). Cu and Zn frequently fell within the moderately to strongly polluted classes, particularly in wheat and sugar beet fields, indicating substantial enrichment beyond natural levels. Cd and Hg were predominantly classified as unpolluted to slightly polluted, whereas Pb and Ni, despite relatively low absolute concentrations, exhibited elevated I_geo values in selected locations. This pattern suggests that localized enrichment may be associated with anthropogenic inputs such as fertilizer application rather than solely geogenic sources. The consistency between C_f and I_geo patterns reinforces the role of long-term agricultural management practices in shaping soil contamination profiles.

The integrated pollution load index (PLI), a calculation-based indicator of cumulative soil contamination, was applied to evaluate overall contamination pressure across cropping systems and exposure scenarios (Fig. 5). Consistent with the formulation of the index, PLI values estimated for children were higher than those for adults, reflecting age-specific exposure parameters rather than differences in measured environmental concentrations. Across cropping systems, soils under sugar beet cultivation exhibited the highest cumulative PLI values (approximately 1.05 for adults and 4.75 for children), indicating a greater overall contamination burden at the index level, whereas wheat and barley showed intermediate values and coriander soils displayed the lowest PLI levels. The spatial correspondence between elevated PLI values and areas characterized by higher Cf and Igeo values highlights the cumulative influence of prolonged fertilizer application and intensive soil management practices. Overall, this index-based assessment consistently identifies Zn, Cu, and Cd as the dominant contributors to cumulative soil contamination, underscoring the need for improved fertilizer governance and routine soil quality monitoring to limit progressive contamination^13,95.

Ecological risk assessment

The potential ecological risk index (PERI), a dimensionless indicator designed to integrate metal toxicity and soil contamination intensity, revealed pronounced differences among cropping systems and individual metals across the Nahavand Plain (Fig. 6). Overall, the results indicate that ecological risk is driven by a limited number of metals and is strongly modulated by crop-specific management intensity rather than uniform background conditions.

Fig. 6

Potential ecological risk index (PERI) values of heavy metals in soils from intensively managed in (a) wheat, (b) barley, (c) sugar beet, and coriander farms in the Nahavand Plain. PERI values are deterministic outputs of the Hakanson ecological risk model⁶⁹ and were not subjected to inferential statistical comparison.

Across all cropping systems, Cd emerged as the dominant contributor to ecological risk. In sugar beet fields, Cd-related ecological risk factors (E_i) exhibited the widest range, spanning approximately 56 to 2028, with a clear central tendency around 280–300. Approximately one-third of sugar beet farms exceeded the high-risk threshold (E_i ≥ 320), while nearly 9% reached the very high-risk category (E_i ≥ 600). In wheat and barley systems, Cd-related risks were lower overall but remained substantial, with median E_i values approaching the high-risk boundary, indicating widespread but moderate ecological pressure. In contrast, Cd-related risk in coriander fields remained comparatively low, reflecting lower soil Cd concentrations and reduced management intensity.

Mercury exhibited a distinct ecological risk pattern characterized by generally low central tendency but pronounced upper-tail extremes. Across wheat, barley, and coriander systems, the majority of farms showed E_i(Hg) values below 35, corresponding to the low ecological risk category according to the Hakanson classification⁶⁹. In contrast, a small proportion of farms (approximately 2–7%) exhibited markedly elevated Hg-related ecological risk, with E_i(Hg) values exceeding 320 and maximum values reaching approximately 740–790, which fall within the very high risk category. Although median Hg-related risk levels remained low, these extreme values generated localized ecological risk hotspots and substantially increased s.

Copper and zinc contributed secondary but non-negligible ecological risks, particularly in sugar beet systems. In these fields, E_i(Cu) typically ranged from approximately 80 to 120, while E_i(Zn) ranged from 22 to 34, indicating moderate ecological pressure when considered alongside Cd. In wheat and barley, Cu and Zn risks were present but less pronounced, whereas coriander consistently exhibited the lowest contributions from these metals. In contrast, Pb, Ni, and Cr displayed consistently low Ei values across all cropping systems, generally remaining below 1–1.2 and exerting minimal influence on overall ecological risk. At the crop-system scale, ecological risk followed a clear gradient: sugar beet > barley > wheat > coriander (Fig. 6). Ranking metals by their contribution to overall ecological risk yielded the sequence Cd > Hg > Cu≈Zn > Pb≈Ni≈Cr. Two distinct modes of ecological risk are therefore evident: (i) chronic, system-wide Cd-related risk associated with intensively managed sugar beet cultivation, and (ii) acute, spatially localized Hg-related risk affecting a small subset of farms across multiple cropping systems.

From a management perspective, the diffuse Cd-related ecological pressure observed in sugar beet systems is consistent with long-term phosphate fertilizer inputs and intensive nutrient management, while the co-occurrence of elevated Cu and Zn suggests the influence of micronutrient supplementation and organic amendments commonly applied in root-crop production^96,97. In contrast, Hg-related hotspots likely reflect localized contamination pathways that warrant targeted investigation rather than broad, system-wide interventions. It is important to note that PERI is a hazard-oriented index intended to assess potential ecological stress in soils and does not directly represent metal bioaccumulation or food-chain transfer. Nevertheless, farms located within the upper tail of Cd- and Hg-related risk distributions represent priority areas for enhanced monitoring. Mitigation strategies should therefore focus on reducing Cd inputs through the use of low-Cd phosphate fertilizers, optimizing soil pH to limit Cd mobility, carefully screening organic amendments, and auditing agricultural inputs in areas affected by Hg anomalies⁹⁸. Such targeted, metal-specific management strategies are essential for limiting long-term ecological degradation, preserving soil functionality, and supporting sustainable intensification under arid agricultural conditions⁹⁹.

Health risk assessment of HMs in soil

Chronic daily intake (CDI) of HMs in soil

The chronic daily intake (CDI) values estimated for ingestion (CDI_ing), inhalation (CDI_inh), and dermal absorption (CDI_derm) reveal clear differences in the relative contribution of exposure pathways to potential human health risks across the studied agroecosystems (Fig. 7). Across all cropping systems and metals, ingestion consistently represented the dominant exposure route, exceeding inhalation and dermal pathways by one to two orders of magnitude. This pattern reflects the central role of soil-related oral exposure in agricultural settings, either through incidental soil ingestion or indirect contact pathways associated with farming activities.

Fig. 7

The chronic daily intake (CDI) values for HMs in soils from intensively managed in (a) wheat, (b) barley, (c) sugar beet, and coriander farms in the Nahavand Plain. CDI values were calculated using standard exposure equations and input parameters; no inferential statistical testing was applicable.

For Cd and Pb, CDI_ing values reached up to approximately 1.6 × 10^–3 and 2.4 × 10^–3 mg kg⁻¹ day⁻¹, respectively, in several cropping systems, indicating elevated potential exposure under long-term conditions. In contrast, CDI_inh values for all metals remained consistently low (< 10^–6 mg kg⁻¹ day⁻¹), highlighting the limited contribution of airborne particulates under the semi-arid climatic conditions of the Nahavand Plain. Dermal exposure contributed moderately to total CDI, with CDI_derm values generally ranging between 10^–5 and 10^–4 mg kg^-1 day^-1. However, for Zn and Cu—particularly in sugar beet and wheat systems—CDI_derm occasionally exceeded this range, suggesting non-negligible occupational exposure for farm workers experiencing frequent soil contact.

Among individual metals, Zn and Cu exhibited the highest overall CDI values, with ingestion peaks of approximately 3.1 × 10⁻³ and 2.7 × 10⁻³ mg kg⁻¹ day⁻¹, respectively, most prominently in sugar beet soils (Fig. 7). Although these elements are essential micronutrients, sustained exposure at elevated levels may be associated with adverse health effects, including gastrointestinal and hepatic disturbances. Cadmium, Pb, and Ni also displayed comparatively high ingestion-related CDI values, with Cd reaching up to approximately 1.8 × 10^–3 mg kg^-1 day^-1. The persistence of Cd and Pb exposure is of particular concern due to their recognized toxicity, long biological half-lives, and potential for cumulative health impacts. In contrast, Hg and Cr showed lower CDI values across all exposure pathways (< 10^–4 mg kg^-1 day^-1). Nevertheless, given their high intrinsic toxicity, even low-level chronic exposure may pose disproportionate risks to sensitive population groups, particularly children^90,100.

The dominance of ingestion in the CDI profile has important implications for exposure management and risk mitigation. While the present assessment focuses on soil-based exposure pathways, the results are consistent with broader evidence identifying ingestion-related routes as the primary contributors to heavy metal exposure in agricultural environments⁵⁸. From a management perspective, these findings suggest that reducing soil contamination and limiting soil-to-human transfer pathways should be prioritized over interventions targeting inhalation or dermal exposure alone¹⁰¹. Nevertheless, elevated CDI_derm values for Zn and Cu in intensively managed systems indicate that occupational exposure should not be overlooked, particularly for farmers with prolonged direct contact with soil.

Overall, the CDI analysis (Fig. 7) highlights the need for targeted risk-reduction strategies in intensively managed agroecosystems¹⁰². Such strategies may include minimizing the use of agrochemicals containing metal impurities, adopting soil management and stabilization practices (e.g., organic amendments), and promoting cropping systems associated with lower soil metal concentrations¹⁰³. Without effective intervention, chronic ingestion-driven exposure to metals such as Cd, Pb, and Ni may continue to pose long-term public health challenges, with implications for both environmental sustainability and human well-being¹⁰⁴.

Hazard quotient (HQ) of HMs in soil

The hazard quotient (HQ) values estimated for individual heavy metals indicate that non-carcinogenic risks associated with soil exposure remain below the commonly accepted threshold (HQ = 1.0) for both adults and children across all cropping systems (Fig. 8). This suggests that, under current exposure assumptions, adverse non-carcinogenic health effects attributable to single-metal soil exposure are unlikely for the studied population.

Fig. 8

Hazard quotient (HQ) values for heavy metals in soils from intensively managed (a) wheat, (b) barley, (c) sugar beet, and (d) coriander fields of the Nahavand Plain, calculated separately for adults and children. All HQ values remained below the risk threshold (HQ < 1.0), with children consistently exhibiting slightly higher values than adults. HQ values are deterministic risk estimates derived from calculated CDI and reference doses; inferential statistical comparison was not applicable.

Across all scenarios, children consistently exhibited higher HQ values than adults, reflecting age-specific exposure parameters such as lower body weight and higher assumed soil ingestion rates¹⁰⁵. Among the assessed metals, Cd, Cu, and Zn contributed most strongly to total HQ values across cropping systems, although their individual HQ values remained relatively low, generally below 0.20 for children and below 0.10 for adults. Soils under sugar beet and wheat cultivation showed moderately higher HQ values than barley and coriander, consistent with their higher contamination levels indicated by C_f and I_geo indices. In contrast, Pb, Ni, Cr, and Hg exhibited consistently low HQ values (< 0.05), indicating minimal contribution to non-carcinogenic risk under present soil exposure conditions¹⁰⁶.

Although all HQ values remain below the threshold of concern, the persistent child > adult pattern highlights the importance of age-specific exposure assessment in agricultural environments. Children are generally more vulnerable to soil contaminants due to behavioral factors, such as increased hand-to-mouth activity, as well as heightened physiological sensitivity during developmental stages^107,108,109. Consequently, continued monitoring is warranted to ensure that gradual increases in soil metal concentrations—potentially driven by long-term fertilizer use or irrigation practices—do not result in upward trends in HQ values over time^110,111.Overall, the HQ assessment indicates that current soil-related exposure to individual heavy metals does not pose significant non-carcinogenic health risks. Nevertheless, cropping systems characterized by higher soil contamination levels, particularly sugar beet and wheat, merit closer surveillance to prevent future risk escalation and to support precautionary soil management practices^91,112.

Total carcinogenic risk (TCR) of HMs in soil

The total carcinogenic risk (TCR) values estimated for soil-related exposure pathways remained within the generally accepted risk range (10⁻⁶−10⁻⁴) for both adults and children across all cropping systems (Fig. 9). For adults, TCR values typically ranged from approximately 1 × 10⁻⁶ to 2 × 10⁻⁵, whereas children consistently exhibited higher values due to age-specific exposure parameters, including higher assumed soil ingestion rates and lower body weight. This systematic child > adult pattern highlights the importance of incorporating age-dependent exposure scenarios in carcinogenic risk assessment.

Fig. 9

Total carcinogenic risk (TCR) values for heavy metals in soils from intensively managed (a) wheat, (b) barley, (c) sugar beet, and (d) coriander fields of the Nahavand Plain, shown separately for adults and children. Children consistently exhibited higher TCR values than adults, although all values remained within the acceptable carcinogenic risk range (10^–6–10^–4). TCR values represent deterministic carcinogenic risk estimates calculated from CDI and cancer slope factors; no inferential statistical testing was applied.

Among the evaluated heavy metals, Cd and Pb were the dominant contributors to total carcinogenic risk, while Cr, Ni, Hg, Cu, and Zn contributed negligibly under the assumed exposure conditions. Across cropping systems, soils under sugar beet and wheat cultivation generated the highest TCR values, particularly for children, with several fields approaching—but not exceeding—the upper bound of the acceptable risk range (10^–4). Barley and coriander systems generally exhibited lower TCR values, although children still showed moderately elevated risks compared with adults. These patterns are consistent with the higher soil concentrations of Cd and Pb observed in intensively managed cropping systems. It is important to emphasize that dietary exposure was not directly assessed in this study, as crop sampling was based on whole above-ground biomass rather than isolated edible plant tissues. Consequently, the TCR estimates presented here represent carcinogenic risks associated exclusively with soil-based exposure pathways. Incorporation of metal concentrations in edible crop parts would be required to quantify dietary carcinogenic and non-carcinogenic risks more comprehensively in future investigations.

Although all estimated TCR values remained below the regulatory threshold of 1 × 10^–4, the observed spatial variability—particularly in sugar beet and wheat systems—suggests that long-term intensive cultivation and fertilizer use may progressively increase carcinogenic risk if metal inputs continue unchecked^113,114. Continuous monitoring of soil contamination, together with improved management practices aimed at reducing Cd and Pb inputs, is therefore essential to prevent future risk escalation, especially for child populations¹¹⁵. Overall, the TCR assessment indicates that carcinogenic risks in the Nahavand Plain are currently within acceptable limits but warrant precautionary management in intensively cultivated systems.

Hazard index (HI) of HMs in soil

The hazard index (HI), which integrates cumulative non-carcinogenic risks arising from ingestion, inhalation, and dermal exposure pathways, demonstrates clear age-dependent contrasts across the four cropping systems in the Nahavand Plain (Fig. 10). In all systems, children consistently exhibited higher HI values than adults, reflecting standard exposure assumptions related to higher soil ingestion rates relative to body weight and increased physiological sensitivity during early life stages^116,117.

Fig. 10

Hazard index (HI) values of heavy metals in soil from intensively managed farms in the Nahavand plain. HI values are deterministic cumulative risk metrics calculated from individual HQ values and were not subjected to inferential statistical analysis.

Among the evaluated cropping systems, soils under sugar beet cultivation exhibited the highest cumulative non-carcinogenic risk, with average HI values of approximately 10.14 for children and 2.17 for adults. Wheat systems also showed elevated cumulative risk (HI_child≈6.69), followed by barley (HI_child≈5.67). These higher HI values reflect the combined contribution of multiple metals under intensive soil management rather than the dominance of a single contaminant. In contrast, coriander soils consistently showed the lowest HI values for both children (≈2.72) and adults (≈0.54), consistent with lower soil metal concentrations and reduced input intensity in these systems. Notably, HI values for children exceeded the commonly applied safety benchmark (HI = 1) across all cropping systems, indicating potential non-carcinogenic health concerns under conservative exposure assumptions. In comparison, adult HI values generally remained close to or below this threshold, suggesting lower relative risk for the adult population. This divergence underscores the importance of incorporating age-specific exposure scenarios in cumulative risk assessment, particularly in agricultural landscapes characterized by intensive agrochemical use.

Spatial patterns of elevated HI values largely coincide with areas identified as contamination hotspots based on soil pollution indices (C_f, I_geo) and ecological risk metrics (PERI), reinforcing the cumulative nature of soil-related exposure in intensively managed systems. This convergence highlights that prolonged fertilizer and pesticide inputs can collectively amplify non-carcinogenic risk, even when individual metal concentrations remain below single-metal risk thresholds.

From a management perspective, these findings emphasize the need for precautionary, system-level interventions aimed at reducing cumulative exposure rather than targeting individual metals in isolation. At the field scale, strategies such as optimizing fertilizer application rates, adjusting cropping rotations toward lower-input systems, and adopting soil management practices that reduce metal mobility may help mitigate cumulative risk. At broader governance levels, integration of soil quality monitoring with public health surveillance frameworks is essential to protect vulnerable populations, particularly children, while maintaining agricultural productivity^6,118. Overall, the HI assessment confirms that cumulative non-carcinogenic risks in the Nahavand Plain are strongly age-dependent and most pronounced in intensively managed cropping systems, underscoring the need for targeted, evidence-based management to support long-term environmental and human health sustainability (Fig. 10).

Synthesis of health risk indicators

The integrated evaluation of health risk indicators—including CDI, HQ, HI, and TCR—provides a coherent overview of soil-related heavy metal exposure pathways and associated risk patterns in the Nahavand Plain. Across all indices, several consistent trends emerge that clarify both the dominant exposure mechanisms and the populations most at risk.

First, ingestion was identified as the primary exposure pathway, consistently exceeding dermal and inhalation routes by one to two orders of magnitude (CDI_ing > CDI_derm > CDI_inh). This dominance reflects soil-based exposure mechanisms typical of agricultural environments and underlines the importance of soil contamination control as a cornerstone of risk mitigation. Second, children consistently exhibited higher risk values than adults across all indicators. Both HQ and HI values for children exceeded the commonly applied safety benchmark (HI = 1) under conservative exposure assumptions, whereas adult values generally remained near or below this threshold. This age-dependent disparity arises from standard exposure parameters, including higher assumed soil ingestion rates relative to body weight and increased sensitivity during early developmental stages.

Third, crop-specific patterns closely followed contamination intensity. Soils under sugar beet cultivation consistently exhibited the highest cumulative risk levels, followed by wheat and barley, while coriander showed comparatively lower—but non-negligible—risk values. Across indices, Cd emerged as the dominant contributor to both non-carcinogenic and carcinogenic risk, with Pb and Ni providing secondary contributions, whereas Cu and Zn mainly influenced cumulative non-carcinogenic risk (HI). Sporadic but pronounced Hg-related anomalies introduced localized, high-severity risk features in certain wheat, barley, and coriander fields.

Taken together, the synthesis of health risk indicators reveals two complementary modes of soil-related risk: (i) chronic, system-wide exposure dominated by Cd (and to a lesser extent Pb and Ni) in intensively managed systems, particularly sugar beet cultivation; and (ii) acute, spatially localized risk associated with Hg anomalies, likely linked to site-specific or episodic inputs. Importantly, these indices are scenario-based tools designed to characterize potential exposure under standardized assumptions rather than to quantify actual dietary intake or clinical outcomes.

From a management and policy perspective, the integrated risk profile highlights the need for precautionary, system-level interventions. At the field scale, priority measures include optimizing fertilizer application rates, substituting high-Cd phosphate fertilizers with low-Cd alternatives, and adopting soil management practices that reduce metal mobility. At broader governance levels, integration of soil quality monitoring with public health surveillance can support early identification of high-risk areas and protect vulnerable populations, particularly children. Overall, the synthesis confirms that intensive agricultural management in the Nahavand Plain generates pronounced age- and crop-dependent health risks, underscoring the importance of targeted, evidence-based strategies to balance agricultural productivity with long-term human health protection.

Health risk assessment of HMs in groundwater

The health risk assessment of heavy metals in groundwater revealed distinct patterns of carcinogenic and non-carcinogenic exposure across the studied agroecosystems, reflecting differences in metal mobility, irrigation practices, and management intensity. Unlike soil-related risks, groundwater exposure pathways were more strongly influenced by dissolved metal concentrations and long-term irrigation dynamics.

For carcinogenic exposure, Cr emerged as the dominant contributor, with average daily dose values ranging from approximately 0.16 to 0.29 mg kg^-1 day^-1, particularly in wheat and barley systems. In contrast, sugar beet fields exhibited comparatively lower Cr-related exposure, likely reflecting dilution effects associated with higher irrigation volumes. Cadmium showed consistent but moderate carcinogenic exposure across systems (approximately 0.009–0.068 mg kg^-1 day^-1), with coriander displaying the highest values, indicating localized groundwater contamination hotspots. Mercury-related exposure remained negligible across all systems (< 0.011 mg kg^-1 day^-1), suggesting limited contribution to groundwater-related carcinogenic risk under current conditions (Fig. 11).

Fig. 11

Average daily dose (ADD), the hazard quotient (HQ) and, the excess lifetime cancer risk (ELCR) values for HMs in groundwater from intensively managed agroecosystems across different farms. ADD, HQ, and ELCR values are deterministic health risk estimates derived from standard exposure and toxicity parameters; inferential statistical testing was not applicable.

Non-carcinogenic exposure patterns differed markedly from carcinogenic trends. Cu and Zn were the primary contributors to non-carcinogenic risk, reflecting intensive fertilizer use and their relatively high mobility in irrigation water. Coriander systems consistently exhibited higher non-carcinogenic exposure values, whereas sugar beet showed the lowest levels, again highlighting the mitigating role of irrigation dilution in shaping groundwater quality¹¹⁹. Hazard quotient analysis supported these patterns, with Cu and Zn dominating non-carcinogenic risk, Cd contributing moderately in wheat and barley, and Hg remaining negligible across all systems.

Long-term carcinogenic risk estimates further identified Cd as a key concern in groundwater, with elevated lifetime risk values observed in wheat, barley, and coriander systems, exceeding commonly referenced safety benchmarks. Cr contributed moderately to carcinogenic risk, while Hg posed minimal concern except in rare outlier cases. Sugar beet systems again exhibited comparatively lower carcinogenic risk, reinforcing the influence of irrigation practices on groundwater contamination dynamics. Overall, the groundwater risk assessment reveals two dominant exposure regimes: (i) chronic carcinogenic risk associated primarily with Cd and Cr in cereal- and coriander-based systems, and (ii) non-carcinogenic exposure driven by Cu and Zn under fertilizer-intensive management. These findings underscore the importance of integrated groundwater monitoring, regulation of Cd-containing agrochemicals, and improved nutrient management strategies to align Cu and Zn inputs with crop demand. The results further suggest that coriander may serve as a sensitive indicator of localized groundwater contamination, while sugar beet systems illustrate the potential mitigating effects of irrigation practices. Collectively, the groundwater assessment highlights the need for crop- and site-specific management approaches to safeguard groundwater quality, protect public health, and support sustainable agricultural production^120,121.

Conclusion

This study presents an integrated evaluation of heavy metal contamination, ecological pressure, and human health risks in intensively managed agroecosystems of the Nahavand Plain, with a particular focus on soil- and groundwater-related exposure pathways. The combined assessment of concentration data, pollution indices, ecological risk metrics, and health risk indicators reveals that Zn, Cu, and Cd are the most influential metals shaping contamination and risk patterns across the study area. Among the investigated cropping systems, sugar beet cultivation consistently exhibited the highest contamination intensity and cumulative ecological and health risks, reflecting long-term intensive fertilizer and input management. Wheat and barley systems showed intermediate risk profiles, whereas coriander generally displayed lower overall risk levels, albeit with localized anomalies. Although groundwater metal concentrations were generally lower than those in soils, the recurrent detection of Cu, Zn, and Cd highlights the susceptibility of shallow aquifers to sustained agrochemical inputs and irrigation-related transport processes. The health risk assessment demonstrated clear age-dependent patterns, with children consistently exhibiting higher non-carcinogenic and carcinogenic risk estimates than adults across soil and groundwater exposure scenarios. While most total carcinogenic risk (TCR) values remained within commonly accepted regulatory ranges, elevated values observed in sugar beet- and wheat-dominated systems underscore the need for precautionary management, particularly to protect vulnerable populations.

Importantly, the risk estimates presented in this study are based on standardized exposure assumptions and soil- and water-related pathways rather than direct dietary intake assessments. Consequently, the findings should be interpreted as indicators of potential exposure and cumulative risk rather than definitive measures of food safety compliance. Nevertheless, the convergence of multiple indices consistently identifies intensive fertilizer use and long-term agricultural management as key drivers of heavy metal pressure in the region. Several limitations should be acknowledged. The analysis was constrained to a single sampling season, a limited set of crop types, and a focus on heavy metals without consideration of co-occurring contaminants such as pesticides. Future research should therefore prioritize multi-season monitoring, expanded contaminant profiling, and integrated soil–water–crop modeling approaches to better capture temporal dynamics and combined exposure pathways. Overall, the results emphasize the importance of improved fertilizer governance, routine monitoring of soil and irrigation water quality, and the adoption of sustainable management practices, including optimized nutrient application, careful selection of agricultural inputs, and diversification of cropping systems. Such measures are essential for reducing long-term exposure risks, safeguarding vulnerable populations, and enhancing the resilience of agroecosystems in arid and semi-arid farming regions.