Accumulation of arsenic and other metals in soil and human consumable foods of Meherpur district, southwestern Bangladesh and associated health risk assessment

doi:10.21203/rs.3.rs-1763781/v1

Groundwater contaminated with arsenic is a significant environmental health concern worldwide because of the potential health risk due to ingestion of agricultural products produced to irrigate arsenic-contaminated water. Besides arsenic, heavy metals like Cr, Cd, Pb, Co, and Ni pollution in agricultural soil and foods worldwide has increased in short order. Metals are indefatigable environmental pollutants that cause adverse effects on human health and the main entrance of those toxic metals in the human body through drinking or consuming contaminated foods and water. In this research, we have determined arsenic and other metals concentration in soil and food samples associated with health risk with possible multivariate statistical approaches like principal component and cluster analysis to identify the probable origin. The outcome of soil pollution measurement indices like contamination factor, geo-accumulation index, and enrichment factor revealed that the soil sample is strongly contaminated by arsenic, which is considered an anthropogenic activity. Two rice grains (R-1, R-3) and drumstick (Sajna) exceed the Indian standard of arsenic concentration (As- 1.1 mg/kg) in food. Compared with WHO, all the samples exceeded the WHO limit except Red amaranth in Cu and Pb, Guava in Cr, Cd, and Pb, and Drumsticks in Cu and Cd for food samples. Arsenic and Cd show the highest transfer factor in the soil to food sample. The high value of bioaccumulation index and translocation coefficient indicate that metals absorb in plant tissue both from soil and supplied contaminated water. In the case of daily ingestion of metals, all highly toxic metals like As, Ni, and Pb represent high concentrations and exceed the daily ingestion limit (As- 3µg kg-1day-1, Ni- 1.3µg kg-1day-1, and Pb- 3.57 µg kg-1day-1) developed by FAO/WHO and EFSA. From the potential hazard quotient, values of As and Pb indicate that residents are at high health risk. The results of carcinogenic risk for harmful metals indicate that for rice grain, the values of As, Pb, and Cd are greater than 10 − 6, which suggest that the inhabitant of the investigated area are at very high carcinogenic risk according to USEPA.

Arsenic

Soils and crops

Bio-accumulation Index

Potential Hazard Quotient

Carcinogenic Risk

Human Exposure

Arsenic is considered one of the most significant worldwide environmental viperous. Groundwater arsenic contamination has been indicated in several countries, including Bangladesh and West Bengal (Reza et al., 2010). In Bangladesh, arsenic can be described as the most common mass poisonous. Recently, 61 districts (out of 64) around the country have been affected by arsenic poisoning, and caused by 80 million people are at risk, and several thousands of them have shown arsenicosis symptoms (Chowdhury, 2001). The natural arsenic contamination in groundwater of Bangladesh causes extensive human exposure via drinking those contaminated water. Using arsenic-contaminated water for agricultural practices is a significant environmental and human health concern. The occurrence of arsenic in the GMB basin is natural in origin. Generally, most researchers agree that the arsenic contamination source is geological, but there is still controversy in identifying the source. To date, two significant theories reported mechanisms of arsenic contamination in underground water: oxidation of arsenic-bearing pyrite and reductive dissolution of FeOOH and MnOOH (Ahmed et al., 2004; McArthur et al., 2004; Zheng et al., 2004; Smedley and Kinniburgh, 2002). The second mechanism has been more acceptable in the last couple of years (Ravenscroft et al., 2001).

Around 80% of the soil in Bangladesh is alluvial in origin, carried by three mighty rivers like the Ganges, Brahmaputra, and Meghna, known as the GMB basin all over the globe. Among them the Ganges river flood plain covered 18.5% of total soils in Bangladesh and reported that hand tube wells and the Ganges flood basin were contaminated with high concentrations of arsenic (Chowdhury et. al., 1999). Massive extraction of groundwater contaminated with arsenic for irrigation has led to high concentrations of As in top soils (Meharg and Rahman, 2003). The maximum permissible limit of arsenic for agricultural soils is 20 mg/kg, and a high concentration of arsenic is toxic to plants, gradually reducing crop yields (Kabata and Pendis, 2001; Marin et. al., 1992). Elevated arsenic and other metals in soils have become a significant concern globally nowadays. Contaminated soil is the primary pathway to exposure to poisonous metals to human health. A human dietary product like crops, vegetables, and fruits grows in contaminated soils capable of translocating metals from soil to crops, resulting in a probable human health hazard. The uptake of arsenic in plants from irrigated water and soils is large enough to cause potential health hazards due to extensive contamination by arsenic—toxic metals As is omnipresent in soils as a trace amount. Globally, natural As concentration in soils is about 5 mg/kg but can be elevated in concentration depending on the soil's natural, anthropogenic, and origin (Mandal and Suzuki, 2002). Chronic ingestion of toxic metals can lead to a deleterious health hazard for a human being, even at a trace amount (Cadaret et. al., 2015). The current research work aimed (1) to assess the contamination level of arsenic and other metals in soils and crops in the study area, (2) to identify the possible sources and correlation together with the metals with multivariate approaches, and (3) to assess the contamination of soils from As-contaminated groundwater and transfer of arsenic via water-soil to crops, (4) to investigate contamination degree and accumulation of metals, (5) to measure human health risk due to ingestion of contaminants foods.

2.1 Site description

Meherpur, a district of Bangladesh located southwestern part of the country, and agricultural activities are the local inhabitants' primary livelihood source. It's a borderline district of Bangladesh play a significant role in 1971 during the liberation war. The study area is located in the Bholadanga village under the Sholataka union of Gangni upazila, Meherpur, Bangladesh. It covers the portion of the southwestern part of Bangladesh and is located in the graphical coordinates between 23º51'00" to 23º51'15''north latitudes and between 88º51'35" to 88º51'50" east longitudes. It is bounded by Doulatpur upazila on the north, Mirpur upazila on the east, Alomdanga upazila on the south, and Meherpur Sadar Upazila on the west. This area covers 1.5 sq. km. which covers the Bholadanga village area (Fig. 1).

2.2 Sampling

Soil samples (n = 8) and human consumable food samples (n = 9), along with paddy, fruits, and vegetables, were collected randomly from the nearby agricultural land and village area. Soil samples at 0–15 cm depth were collected (250 g each for different analyses) from adjacent fields of food samples. Triplicate soil samples were randomly collected to make a homogenous composite sample and kept in a polythene bag for each site. Afterward, the soil samples were dried in the air, grounded and passed through a 2 mm sieve, and finally stored in plastic pots. Four rice plants (RP) and five vegetables and fruits (FS) edible parts were collected randomly from each field. All the food samples were kept in clean air-protected polyethylene bags with an icebox for carrying to the laboratory and stored at 4°C until analysis. At the time of sampling, bio data information (age, body weight, sex) and food consumption rate and behaviors were collected from the local people to obtain individual arsenic exposure assessments. A list of collected food samples is shown in Table 1.

Table 1

List of collected food samples from Meherpur district, southwestern Bangladesh with descriptive identification
Vernacular Name	English Name	Scientific Name	Family	Sample ID	No. of Sample
Dhan	Paddy	Oryza sativa	Graminae	RP	4
Peyara	Guava	Psidium guajava	Myrtaceae	FS-1	2
Lal shak	Red amaranth	Amaranthus gangeticus	Amaranthaceae	FS-2	2
Dalim	Pomegranate	Punica granatum	Punicaceae	FS-3	2
Kochu	Arum	Colocasia esculenta	Araceae	FS-4	2
Sajina	Drumstick tree	Moringa oleifera	Moringaceae	FS-5	2

2.3 Sample analysis

Metal concentration in soil and food samples was analyzed at Analytical Research Division, BCSIR Laboratories, Dhaka, Bangladesh, an ISO/IEC 17025 recognized laboratory. Earlier in the analysis, all soil samples were oven-dried at 105°C, and collected triplicate samples were carefully mixed entirely to get a composite sample. They prepared soil samples kept in polyethylene bags for analysis. Then all food samples were rinsed with distilled water, and 0.05 M HCL for removing dust and soil particles from the root, straw, and grain (paddy) were separated, and all crops, vegetable, and fruits samples were dried for 48 h at 70 ºC in the oven to remove moisture.

2.4 Sample preparation

To extract total metal concentration, 10 g of dry soil material was weighed into a 150 ml beaker. 20 ml Aqua Regia was added to the samples, and the suspension was heated for approximately 2 hours at 120º C. Then 5 to 10 ml perchloric acid (HCLO4) was added and again digested at 100º C until had a clear solution. Then these solutions were filtered with WhatmanTM 41 (150 mm Ø) and stored in a 100 ml plastic bottle for analysis. To assess total metal content in food samples, 10 g wet crop samples of each weighed in 100 ml beaker and put in the oven for drying at 110° C. After oven-dry the sample was ashed up to 500° C. After completing ashing, the samples were digested at 100º C with 10 ml HNO3 and 5 ml HCLO4 and then filtered and stored for analysis at 4°C.

2.5 Instrumental analysis

The concentration of Cu, Zn, Fe, and Mn on the soil and food samples were measured using flame in an atomic absorption spectrometer (model: AA240FS, Varian, Australia), and Pb, Cd, Ni, and Cr were determined using Zeeman atomic absorption spectrometer (model: GTA 120-AA240Z, Varian, Australia) equipped with graphite furnace. Quality control method blank and standard check samples were measured sequentially.

3.1 Statistical analysis

Analytical calculations were statistically analyzed with IBM SPSS statistics software (Version 20), and Microsoft excel 2013 was used. Multivariate statistical analysis like principal component analysis and hierarchical cluster analysis was accomplished to identify the source of metals, and distribution was estimated using Ward's methods. The results were expressed with a dendrogram.

3.2 Assessment of soil contamination

The most acquainted methods of soil contamination degree are enrichment factor, geo-accumulation index, and contamination factor.

3.2.1 Enrichment Factor (EF)

Following Taylor (1964), the enrichment factor for every individual metal of the sample is usually computed by the following relationship;

EF =\(\frac{\left(\frac{\text{M}\text{e}\text{t}\text{a}\text{l}}{\text{F}\text{e}}\right)sample}{\left(\frac{\text{M}\text{e}\text{t}\text{a}\text{l}}{\text{F}\text{e}}\right)Background}\)

Iron (Fe) was considered the reference metal for geochemical normalization. The degree of soil contamination using enrichment factor can be classified into seven classes such as, 0–1 (No enrichment); 1–3 (Small enrichment); 3–5 (Medium enrichment); 5–10 (Medium to acute enrichment); 10–25 (Acute enrichment); 25–50 (Very acute enrichment) and greater than 50 (Extremely acute enrichment).

3.2.2 Geo-accumulation Index (I_geo)

The geo-accumulation index (Igeo) normally used to measure additional metal concentrations in soil was usually expressed by Muller (1979) using the equation:

Igeo =\(\frac{{\text{L}\text{o}\text{g}}_{2}\left({C}_{n}\right)}{1.5 \left({B}_{n}\right)}\)

Where Cn refers to metal concentration from analysis and Bn is the geochemical background value of that metal. In accordance with Muller (1981), the geo-accumulation index was classified into seven grades which are: ≤ 0 (Uncontaminated); 0–1 (Uncontaminated to moderately contaminate); 1–2 (Moderately contaminated); 2–3 (Moderately to Strong contaminated); 3–4 (Strong contaminated); 4–5 (Strong to extremely contaminate); ≥ 5 (Extremely contaminated)

3.2.3 Contamination Factors (CF)

Contamination factor (CF) may be expressed as the ratio of metal concentrations in the soil and their background value which are as follows (Bhuiyan et al., 2010).

CF =\(\frac{\text{H}\text{e}\text{a}\text{v}\text{y} \text{M}\text{e}\text{t}\text{a}\text{l} \text{C}\text{o}\text{n}\text{c}\text{e}\text{n}\text{t}\text{r}\text{a}\text{t}\text{i}\text{o}\text{n}\text{s}}{\text{M}\text{e}\text{t}\text{a}\text{l}\text{s} \text{B}\text{a}\text{c}\text{k}\text{g}\text{r}\text{o}\text{u}\text{n}\text{d} \text{V}\text{a}\text{l}\text{u}\text{e}}\)

Following Muller (1969), the levels of metal pollution are grouped in the range from 1 to 6 based on their intensities which are: 0 (Very minor or none); 1 (Minor to moderate); 2 (Moderately contaminated); 3 (Moderate to Strong); 4 (Strongly contaminated); 5 (Strong to severe strong); 6 (Severe strong). For the calculation of EF, Igeo, and CF values, by Krauskopf and Bird (1995), the crustal assemblage was used as the background values.

3.3 Degree of metal concentration in crops and human

3.3.1 Transfer Factors of Metal (TF)

The transfer factor (TF) was calculated for every single soil and plant sample to measure the bioaccumulation impact of plants with trace metals from the adjacent soils by the following equation:

TF =\(\frac{{\text{C}}_{\text{P}\text{l}\text{a}\text{n}\text{t}}}{{\text{C}}_{\text{s}\text{o}\text{i}\text{l}}}\)

Plant and Coil represent metal concentrations in green plant and soil, respectively, on a dry weight basis.

3.3.2 Net Translocation Coefficient (NTC)

The translocation coefficient (TC) conception has been utilized in literature to calculate the plants' ability to soak up and translocate elements from water and soil by their root to the consumable part (Mattinaet al., 2003).

TC root / soil = C root / C soil

TC straw / root = C straw / C root

TC grain / straw = C grain / C straw

Where Coil, Croot, Cstraw, and Cgrain are the total concentrations of metal in soil, root, straw, and grain, respectively.

3.3.3 Bio-accumulation Index (BI)

The bio-accumulation index (BI) is referred to the magnitude relationship of the number of elements in plants too that in the corresponding soil was determined for every single plant sample to measure the bio-accumulation effect of plants in the uptake of metals (arsenic) from the soils. The BI was computed as:

BI = Cp / Cs

Cp and Cs represent the total metal concentrations in the plants and soils on a dry weight basis. Now, Cp was calculated by the following equation.

C_p = (C_root × B_root + C_straw × B_straw + C_grain × B_grain) / B_total

Croot, Cstraw, and Cgrain are the concentrations of an element in the root, straw, and grain, Broot, Bstraw, and Bgrain are the biomass (dry weight basis) of the root, straw, and grain, respectively, and Btotal is the sum of Broot, Bstraw, and Brain.

3.3.4 Daily Ingestion of Metals (DIM)

The daily ingestion of metals (DIM) typically depends on the amount of a particular metal in the food sample and the ingestion rate of that respective food. The DIM for adults was calculated by the following relationship (Miclean et al., 2018):

DIM =\(\frac{{\text{C}}_{\text{M}\text{e}\text{t}\text{a}\text{l} \times {\text{W}}_{\text{F}\text{o}\text{o}\text{d}}}}{{\text{B}}_{\text{w}}}\)

Where Metal is the metal concentration in food samples, Wood is the average ingestion rate per day of the respective food, and Bw is the average body weight. The average daily ingestion of rice (grain), vegetable, and fruit for adults was considered to be 372 g, 274 g (Zhuanget al., 2009), and 200 g per person per day, respectively, while the average body weight for adults in the study was considered to be 65 kg.

3.3.5 Potential Hazard Quotient (PHQ)

The non-carcinogenic health hazard through food ingestion was calculated using hazard quotients for every single metal according to the equation USEPA Region Ⅲ (USEPA, 2000).

PHQ = \(\frac{\text{E}\text{F} \times \text{E}\text{D} \times \text{F}\text{I}\text{R} \times \text{M}\text{C}}{\text{R}\text{f}\text{D} \times \text{B}\text{W} \times \text{A}\text{T}}\) × 10^− 3

Where,

EF = Exposure frequency (365 days/year)

ED = Exposure duration (assumed 72 years for Bangladesh)

FIR = Ingestion rate of food (372, 274 and 200 g/day for rice, vegetables and fruits, respectively)

MC = Metal concentrations in food

RfD = Represents oral reference dose

BW = Body weight (avg. 65 kg in study area)

AT = Average life time (26280 days)

3.3.6 Carcinogenic Risk (CR) from Food (Rice) samples

The following formula computed the CR for As, Pb, and Cd. Carcinogenic hazard value greater than 10 − 6 indicates that the people in the respective area were at high carcinogenic risk according to USEPA 2005.

CR = \(\frac{\text{E}\text{F} \times \text{E}\text{D} \times \text{F}\text{I}\text{R} \times \text{M}\text{C} \times 10¯3}{\text{B}\text{W} \times \text{A}\text{T}}\)× CSF

Or, CR =\(\frac{\text{A}\text{D}\text{D} \times \text{C}\text{S}\text{F}}{1000}\)

CSF is the carcinogenic slope factor, which measures the upper-bound possibility of a single developing cancer due to lifetime exposure to a specific level of probable carcinogen through an ingestion route. The CSF value of As, Pb, and Cd is 1.5, 0.0085, and 15 mg kg-1 day-1, according to USEPA (USEPA, 2005).

4.1 Soil contamination

The laboratory results of metals concentration in soil samples of the research area are shown in Table 2. The concentration of arsenic, except for all other metals, was found higher value than the average concentration of As in soils of Bangladesh, 4 to 8 mg kg-1 (Williams et al., 2006; Alam and Sattar, 2000). The rest of the metal concentration shows average crustal values, which naturally present as an earth material. Table 3 shows the results of the degree of soil contamination. Results of enrichment factor (EF) Co, Cd, and Cu show no enrichment (EF < 1). Fe, Mn, Zn, and Pb show slight enrichment (1 ≤ EF < 3), and the results of arsenic show acute enrichment (10 ≤ EF < 25). EF value ranges from 0.05 to 1.5, revealing a natural process, i.e., the metal supply is entirely the crustal materials.

Table 2

Metal concentration (mg kg^− 1) in soil samples of Meherpur district, southwestern Bangladesh.
Sample ID	As	Fe	Mn	Co	Ni	Cu	Zn	Cr	Cd	Pb
SS-1	17.49	26255.43	577.26	11.42	28.34	23.92	73.04	19.07	0.12	10.01
SS-2	23.81	29137.77	655.98	12.16	30.28	26.55	78	25.41	0.16	11.02
SS-3	40.2	38356.36	825.18	17.87	46.8	42.88	87.15	35.24	0.13	16.3
SS-4	16.55	19114.27	411.63	8.23	20.33	16.45	54.48	13.01	0.06	9.01
SS-5	4.54	22304.03	415.16	8.78	22.29	22.24	118.32	13.15	0.11	10.91
SS-6	9.1	23315.67	510.45	11.04	27.46	22.89	82.42	18.14	0.08	9.29
SS-7	9.77	25042.19	494.41	12.04	28.55	24.28	66.2	18.6	0.07	9.57
SS-8	10.31	23119.45	515.74	10.57	26.17	26.37	74	17.43	0.06	10.01
Average	16.47	25830.65	550.73	11.51	28.78	25.70	79.20	20.01	0.10	10.77
Maximum	40.2	38356.36	825.18	17.87	46.8	42.88	118.32	35.24	0.16	16.3
Minimum	4.54	19114.27	411.63	8.23	20.33	16.45	54.48	13.01	0.06	9.01
Range	35.66	19242.09	413.55	9.64	26.47	26.43	63.84	22.23	0.1	7.29
SD	11.32	5853.633	136.72	2.94	8.01	7.62	18.71	7.27	0.04	2.35

Table 3

Results of Enrichment Factor (EF), Geo-accumulation Index (Igeo) and Contamination Factors (CF) of soil samples of Meherpur district, southwestern Bangladesh.
Sample ID	As			Fe			Mn			Co			Cu			Zn			Cd			Pb
Sample ID	EF	I_geo	CF	EF	I_geo	CF	EF	I_geo	CF	EF	I_geo	CF	EF	I_geo	CF	EF	I_geo	CF	EF	I_geo	CF	EF	I_geo	CF
SS-1	18.5	2.70	9.72	1	-1.51	0.53	1.16	-1.30	0.61	0.87	-1.72	0.46	0.83	-1.79	0.43	1.99	-0.52	1.04	1.14	-1.32	0.60	1.47	-0.96	0.77
SS-2	22.7	3.14	13.2	1	-1.36	0.58	1.18	-1.12	0.69	0.83	-1.62	0.49	0.83	-1.64	0.48	1.91	-0.43	1.11	1.37	-0.91	0.80	1.45	-0.82	0.85
SS-3	29.1	3.90	22.3	1	-0.97	0.77	1.13	-0.79	0.87	0.93	-1.07	0.71	1.02	-0.94	0.78	1.62	-0.27	1.25	0.85	-1.21	0.65	1.63	-0.26	1.25
SS-4	24.1	2.62	9.19	1	-1.97	0.38	1.14	-1.79	0.43	0.86	-2.19	0.33	0.78	-2.33	0.30	2.04	-0.95	0.78	0.78	-2.32	0.30	1.81	-1.11	0.69
SS-5	5.7	0.75	2.52	1	-1.75	0.45	0.97	-1.78	0.44	0.79	-2.09	0.35	0.91	-1.89	0.40	3.79	0.17	1.69	1.23	-1.44	0.55	1.88	-0.84	0.84
SS-6	10.8	1.75	5.05	1	-1.68	0.47	1.15	-1.48	0.54	0.95	-1.76	0.44	0.89	-1.59	0.42	2.52	-0.35	1.18	0.86	-1.91	0.40	1.53	-1.07	0.71
SS-7	10.8	1.85	5.43	1	-1.58	0.50	1.03	-1.53	0.52	0.96	-1.64	0.48	0.88	-1.76	0.44	1.88	-0.67	0.95	0.70	-2.10	0.35	1.46	-1.03	0.74
SS-8	12.4	1.93	5.73	1	-1.70	0.46	1.17	-1.47	0.54	0.91	-1.83	0.42	1.04	-1.65	0.48	2.29	-0.50	1.06	0.65	-2.32	0.30	1.67	-0.96	0.77
Mean	16.8	2.33	9.15	1	-1.57	0.52	1.12	-1.41	0.58	0.89	-1.74	0.46	0.90	-1.70	0.47	2.26	-0.44	1.13	0.95	-1.69	0.49	1.61	-0.88	0.83
[N.B.: Bold type faces indicate significant values]

In contrast, values greater than 1.5 indicate metals' most likely anthropogenic origin (Zhang and Liu, 2002). The higher value of arsenic suggests that the soils were contaminated by arsenic primarily due to an anthropogenic activity like pumping groundwater from the arsenic-bearing aquifer for irrigation purposes. The metals enrichment factor of less than 1.5 indicated that these metals did not noteworthily contaminate the soils in the investigated area and their little accumulation is thoroughly natural. The results of the geo-accumulation index (Igeo) for Fe, Mn, Co, Cu, Zn, Cd, and Pb show particularly uncontaminated (Igeo ≤ 0), and arsenic show moderately to strong contaminated (2 < Igeo < 3), which occurs due to use of high arsenic-contaminated groundwater. The contamination factor (CF) results showed that most soil samples are contaminated by arsenic very strongly, ranging from 2.52 to 22.33. The rest of all metals show minor to moderate contamination. The high arsenic contamination factor showed the highest degree of anthropogenic impact.

4.2 Metal concentration in foods

The laboratory results of the metal concentration of collected food samples represent in Table 4. A comparison of those metal accumulations with food standards established by WHO(1989) found that only rice grain (R-1to R-4) arsenic concentration is considered instead of rice plant. Two rice grains (R-1, R-3) and Sajna (Drumstick) exceed the Indian standard (As- 1.1 mg/kg) (Awasthi, 2000) limit for As in human consumable foods (Fig. 2a). For a nickel, all food samples exceed the Indian standard (Ni-1.5 mg/kg) value except Lalshak (Red amaranth) and Dalim (Pomegranate) (Fig. 2b). Except for Lalshak (Red amaranth) and Sajna (Drumstick), all the samples exceed the WHO limit (10 mg/kg) for Cu in food (Fig. 2c) (WHO, 1996). All the samples exceed the WHO standard (1 mg/kg) for Cr and Pb except Peyara (Guava) (Fig. 2d and 2f). For all paddy (grain) samples (R-1to R-4) and Dalim (Pomegranate), Cd concentration exceeds the WHO limit (0.2 mg/kg) for food samples (Fig. 2e).

Table 4

Metal concentration (mg kg^− 1) in food (rice grain and vegetables) samples of Meherpur district, southwestern Bangladesh.
Sample ID	As	Fe	Mn	Co	Ni	Cu	Zn	Cr	Cd	Pb
R-1	2	635.98	88.36	0.23	0.96	2.89	11.47	1.3	0.06	0.61
R-2	0.71	101.46	98.6	< 0.2	1.83	1.67	21.78	1.8	0.13	1.43
R-3	1.4	108.86	132.98	< 0.2	0.62	2.15	11.79	0.79	0.06	0.53
R-4	0.79	238.64	133.74	0.03	0.81	2.42	14.65	1	0.07	0.58
FS-1	0.12	188.45	1	0.18	1.64	10.81	12.79	0.89	0.06	0.75
FS-2	0.49	775.23	0.95	0.29	1.25	5.68	12.63	1.21	0.2	0.92
FS-3	0.079	49.57	0.28	< 0.2	1.22	12.77	29.58	1.64	0.24	1.8
FS-4	0.41	575.36	1.67	0.2	2.07	18.31	16.89	1.91	0.11	1.15
FS-5	1.59	139.06	0.55	< 0.2	2.43	6.9	21.26	2	0.14	1.55
Average	0.84	312.51	50.90	0.19	1.43	7.07	16.98	1.39	0.12	1.04
Maximum	2	775.23	133.74	0.29	2.43	18.31	29.58	1.91	0.24	1.55
Minimum	0.079	49.57	0.28	< 0.2	0.62	1.67	11.47	0.79	0.06	0.53
Range	1.92	725.66	133.46	0.27	1.81	16.64	18.11	1.12	0.18	1.02
SD	0.68	272.47	61.02	0.10	0.61	5.78	6.12	0.46	0.07	0.47
[N.B.: R-1 to R-4 = Rice grain concentration only]

4.3 Multivariate statistical analysis

4.3.1 Sources of metals concentration in soil samples

Principal component analysis (PCA) is essential for determining contaminant sources in multivariate statistical analyses. The results of PCA analysis of soil samples are presented in Table 5. Two principal components were noted for soil samples. Principal component analysis of soil samples elucidates the cumulative variance of 90.532% and 68.166%, respectively (Fig. 3a). PCA-1, As, Co, Ni, Cu, Fe, Mn, Cr, and Pb showed favorable loading, mainly natural or geogenic. Pb and Cu were predominantly contributed by lithogenic sources (Ahsan et al., 2019). Whereas PCA-2 showed the positive loadings of Zn, Cd, and Mg is provably anthropogenic in origin due to using different types of fertilizer (Khan et al., 2019). Total factor accumulation values greater than 0.75, 0.75 − 0.50, and 0.50 − 0.30 were graded as high, medium, and low, respectively (Ahsan et al., 2019). Moreover, cluster analysis was executed with Ward's methods to distribute the metals into different groups, representing the result with a dendrogram (Fig. 3b). Two clusters identified with the phenon line set to a rescaled distance of about 10 to show statistical similarity. Cluster-1 and cluster- 2 included Co, Ni, Cu, Fe, Mn, As, Pb, Cr, and Zn, Mg, Cd, which showed the positive loadings on PCA-1 and PCA-2, respectively. It also exhibits the similarity between principal component analysis (PCA) and cluster analysis (CA).

Table 5

Varimax rotated principal component analysis and communalities of the metals of the soil samples.
Parameters	PCA-1	PCA-2	Communalities
As	0.940	− 0.042	0.885
Co	0.964	0.135	0.947
Ni	0.967	0.175	0.965
Cu	0.915	0.295	0.924
Zn	− 0.087	0.963	0.934
Fe	0.956	0.277	0.991
Mn	0.974	0.138	0.968
Cr	0.978	0.165	0.984
Cd	0.517	0.545	0.564
Pb	0.853	0.413	0.898
Mg	0.303	0.897	0.897
Eigenvalue	8.142	1.816
Total variance %	68.166	22.366
Cumulative % of variance	68.166	90.532
[Bold type faces indicate significant values]

4.3.2 Sources of metals concentration in food (paddy) samples

Two principal components identified for paddy samples represent in Table 6.PCA analysis of the paddy sample explained the cumulative variance of 90.532% and 68.166%, respectively. PCA-1 showed the positive loading of As, Co, Ni, Cu, Fe, Mn, Cr, Pb, and PCA-2 showed the positive loading of Zn, Cd, and Mg. Metals from PCA-1 and PCA-2 are both natural and anthropogenic in origin. Because of the wide range of analytical testing of fertilizer products such as phosphate, micronutrient fertilizers, liming materials, insecticides, and pesticides contain an elevated level of As, Ni, Cd, and Pb compared to other fertilizer types. PCA showed (Fig. 4a) that the distribution of the same sorts of metals in soil samples and paddy samples were not analogous, which might be the result of distinct emission and accumulation characteristic of the considered metals by plants from the source to the environment (Chowdhury and Rasid, 2016). Afterward, cluster analysis (CA) was performed with Ward's methods to classify the metals content in the paddy into different groups, and the result showed with a dendrogram (Fig. 4b). Two main clusters were identified for paddy samples with the phenon line set to a rescaled distance of about 10 to show statistical similarity. Cluster-1 showed positive loading of Fe, Ni, Cr, Pb, Co, Mg, As, and Mn, whereas Zn, Cd, and Cu are the dominant metals of cluster-2. Only Cu and Mg showed dissimilarity between PCA and CA analyses in the paddy sample, which may happen due to the accumulation and resistance to accumulation of metals in plant cells from a different source (Chowdhury and Rasid, 2016).

Table 6

Varimax rotated principal component analysis and communalities of the metals of the crops (paddy) samples.
Parameters	PCA-1	PCA-2	Communalities
As	0.940	− 0.042	0.885
Co	0.964	0.135	0.947
Ni	0.967	0.175	0.965
Cu	0.915	0.295	0.924
Zn	− 0.087	0.963	0.934
Fe	0.956	0.277	0.991
Mn	0.974	0.138	0.968
Cr	0.978	0.165	0.984
Cd	0.517	0.545	0.564
Pb	0.853	0.413	0.898
Mg	0.303	0.897	0.897
Eigenvalue	8.142	1.816
Total variance %	68.166	22.366
Cumulative % of variance	68.166	90.532
[Bold type faces indicate significant values]

4.3.3 Pearson's correlation among the metals of soil and food samples

Mutual correlation among the studied metals concentration in the soil and food samples was identified to determine their internal relationships are represent in Table 7. In case of soil samples, As showed strong positive correlation with Co (r = 0.831),Ni (r = 0.854), Cu (r = 0.792), Fe (r = 0.871), Mn (r = 0.905), Cr (r = 0.903) and Pb (r = 0.829) and negative correlation with Zn (r = -0.135). Fe showed strong correlation with Mn (r = 0.973), Cr (r = 0.981) and Pb (r = 0.913). Homogeneous behavior among the metals groups revealed a similar source in origin (Bhuiyan et. al., 2010). In food samples, arsenic showed strong positive correlation with Co (r = 0.942), Ni (r = 0.972), Fe (r = 0.978), Mn (r = 0.983), Zn (r = 0.796), Cr (r = 0.963), Pb (r = 0.960) and insignificant correlation with Cu (r = 0.460). Fe showed strong correlation with Mn (r = 0.963), Cr (r = 0.969) and Pb (r = 0.970) which indicate similarity in soil and food samples as a common source.

Table 7

Pearson’s correlation matrix among metals concentration in soil and food samples
Parameters	As	Co	Ni	Cu	Zn	Fe	Mn	Cr	Cd	Pb
Soil samples As	1
Co	0.831	1
Ni	0.854	0.995	1
Cu	0.792	0.954	0.969	1
Zn	-0.135	0.055	0.106	0.246	1
Fe	0.871	0.969	0.977	0.954	0.179	1
Mn	0.905	0.946	0.953	0.916	0.045	0.973	1
Cr	0.903	0.967	0.971	0.932	0.053	0.981	0.987	1
Cd	0.564	0.479	0.500	0.477	0.406	0.662	0.658	0.617	1
Pb	0.829	0.861	0.901	0.940	0.365	0.913	0.848	0.871	0.551	1
Food samples

4.4 Accumulation of arsenic in soils and plants

Groundwater contaminated with arsenic, used for drinking purposes and the agricultural water supply, is considered the major ingestion route of arsenic to the human body and plants. Several hypotheses have been made to understand the origin (primary) and mobilization (secondary) causes of elevated high arsenic in groundwater. Arsenic in Bengal delta, especially in GMB (Ganges-Brahmaputra-Meghna) flood plains, came from the Himalayas and the highlands in the neighboring areas. In the Himalayan arsenic-bearing pyrite, sulfides washed out and accumulated in these GMB floodplain areas. Contaminants primarily affect the Holocene aquifer at a depth between 20 to 120 m, and it covers southwest and south-central areas of Bangladesh (Ravenscroft et al., 2005). Arsenic is present in Holocene sediments, which are later diluted with groundwater due to microbial activity and reductive dissolution of iron oxy-hydroxides (FeOOH). In the study area, a considerable quantity of arsenic-contaminated groundwater is used for irrigation from shallow aquifers (Holocene aquifers), which are mainly responsible for grain arsenic concentration. The flooded method of irrigation is used in this region. As a result, a considerable amount of arsenic is available to direct translocate to the rice plant. After a complete analysis of water, soil, and plant chemistry, it can be concluded that the majority of arsenic are enriched in the plant by the direct absorption from irrigation water, especially for rice plant, and the rest are accumulated arsenic from adjacent soil and water. A proposed model of arsenic circulation in an agronomical system modified by Sandberg and Allen, 1975 shown in Fig. 5.

4.5 Metals transformation from soils to crops

Transfer factor of metals results showed that the TF values for rice plants are higher than other vegetable samples in Table 8. For rice plants (RP), As, Cd and Mn showed greater concentration, Zn, Cu, Fe, Cr, and Pb showed moderate concentration, and Co and Ni showed low concentrations, which are moderately similar to their concentration in soil samples. The higher values of Arsenic for rice plants occurred due to the direct accumulation of arsenic from supplied groundwater for irrigation. Cadmium is the highest accumulated metal and showed outstanding TF values among all the analysis metals (Selinuset al., 2005). If the Cd enters the plant vessel, it interludes with the enzymes and takes the place of Zn, which results in an easy transfer of this metal from soil to the consumable part of the plant species compared to Zn (Miclean et al., 2019). Cd showed high accumulation in all the samples except Peyara without any visual effects. Cadmium transfer is highly impendence due to its significant toxicity. Although soil samples were found to be low to moderately contaminated with Cd with higher TF values for rice plants and vegetable samples. For vegetable samples, Cu and Zn showed higher concentrations than all other metals. Comparatively low to moderate TF values for Cr, Co, Fe and Ni are probably due to their low mobility and phytoavailability, expressing their strong sorption in soils which lower the free ion concentrations in the soil solution and make them minor available for plant accumulation (Selinuset al., 2005). The overall results strongly expressed that plant samples, especially rice plants, are mainly contaminated with As, Cd, Mn, and other vegetable samples are also contaminated with cadmium which showed a higher TF value for all the samples except Peyara (Guava).

Table 8

Transfer factors of metals from adjacent soil to crops in collected food samples from study area.
Soil Sample ID	Crop Sample ID	As	Fe	Mn	Co	Ni	Cu	Zn	Cr	Cd	Pb
SS-1	RP-1	8.36	0.29	1.55	0.11	0.19	0.61	0.68	0.37	2.92	0.42
SS-2	RP-2	3.28	0.22	1.00	0.14	0.17	0.60	0.61	0.30	2.94	0.41
SS-3	RP-3	5.27	0.42	1.34	0.18	0.21	0.34	0.45	0.30	1.85	0.42
SS-4	RP-4	9.00	0.65	2.35	0.32	0.38	0.98	0.81	0.69	5.33	0.60
SS-5	FS-1	0.03	0.008	0.002	0.02	0.07	0.49	0.11	0.07	0.50	0.07
SS-5	FS-5	0.35	0.006	0.001	nd	0.11	0.31	0.18	0.15	1.27	0.14
SS-6	FS-3	0.09	0.002	0.0005	nd	0.04	0.56	0.36	0.09	3.0	0.19
SS-7	FS-2	0.05	0.03	0.002	0.03	0.04	0.23	0.19	0.07	2.86	0.01
SS-8	FS-4	0.04	0.02	0.003	0.019	0.08	0.70	0.23	0.11	1.83	0.11
Mean		2.94	0.18	0.69	0.12	0.14	0.54	0.40	0.24	2.5	0.26
SD		3.74	0.23	0.89	0.11	0.11	0.23	0.25	0.20	1.38	0.20
[N.B.: Bold type faces indicate significant values]

The results of the net translocation coefficient (NTC) of arsenic for rice plants are almost similar to the transfer factor (TF) of arsenic in rice plants shown in Table 9. The translocation coefficient between soil and root showed a higher value than root-straw and straw-grain. Net translocation coefficient (NTC) between soil-root is very high compared to that soil contaminated with arsenic. A high value of TC root/soil indicates arsenic can directly accumulate through the plant root system via arsenic-contaminated irrigation water in the studied area. The high value of bio-accumulation indices showed that plants absorb arsenic from the soil, directly from supplied water, or both through their tissue.

Table 9

Net translocation coefficient and bio-accumulation index for arsenic in rice plants in studied area.
Samples ID	Net translocation coefficient			Bio-accumulation index
Samples ID	TC _{root / soil}	TC _{straw / root}	TC _{grain / straw}
RP-1	7.74	0.07	0.23	1.62
RP-2	3.12	0.04	0.22	1.12
RP-3	5.10	0.03	0.26	1.61
RP-4	8.73	0.02	0.23	2.70
Mean	6.17	0.04	0.24	1.76
SD	2.55	0.022	0.017	0.67

The overall analytical and statistical results strongly indicate that food samples of Bholadanga village of Meherpur district, southwestern Bangladesh badly contaminated with arsenic.

4.6 Human health hazards of local people

In the research area, a human was exposed to arsenic fatality through consumable food and drinking water. The schematic diagram of arsenic exposure to the human body is shown in Fig. 6. The daily ingestion of metals (Table 10) for rice and vegetables shows terrible value. Highly toxic metals like As, Ni, and Pb represent the maximum value. They all exceed the daily ingestion limit of arsenic 3 µg/kg/day, nickel 1.3 µg/kg/day, and lead 3.57 µg/kg/day for adults recommended by FAO/WHO (1989) and EFSA (2011).

Table 10

Daily ingestion of metals (µg/day) by food samples of Meherpur district, southwestern Bangladesh
Samples ID	As	Fe	Mn	Co	Ni	Cu	Zn	Cr	Cd	Pb
RP-1	11.45	3639.8	505.7	1.32	5.50	16.54	65.64	7.44	0.34	3.49
RP-2	4.06	580.7	564.3	nd	10.47	9.56	124.65	10.30	0.74	8.18
RP-3	8.01	623.0	761.1	nd	3.55	12.30	67.48	4.52	0.34	3.03
RP-4	4.52	1365.8	765.4	0.17	4.64	13.85	83.84	5.72	0.40	3.32
FS-1	0.37	579.8	3.08	0.55	5.05	33.26	39.35	2.74	0.18	2.31
FS-2	2.07	3267.9	4.00	1.22	5.27	23.94	53.24	5.10	0.84	3.88
FS-3	0.24	152.5	0.86	nd	3.75	39.29	91.02	5.05	0.74	5.54
FS-4	1.73	2425.4	7.04	0.84	8.73	77.18	71.20	8.05	0.46	6.53
FS-5	6.70	586.2	2.32	nd	10.24	29.08	89.62	8.43	0.59	6.53
Mean	4.4	1469.0	290.4	0.8	6.4	28.3	76.2	6.4	0.5	4.8
SD	3.78	1307.75	350.05	0.48	2.71	20.94	24.76	2.35	0.22	2.0
[N.B.: Bold type faces indicate significant values]

The potential hazard quotient (PHQ) has been considered a practical parameter for assessing risk related to the ingestion of metal through contaminated food crops. The non-carcinogenic health risk through food consumption was calculated using hazard quotients for each investigated metal according to the equation US-EPA Region Ⅲ (USEPA, 2000). If a hazard quotient value less than 1 suggests that the daily exposure to a selective metal through food consumption is unlikely to cause non-carcinogenic health effects. In contrast, a hazard quotient value greater than 1 shows that in the exposed population, long-standing health hazards may occur (Aviglianoet al., 2016). The results of the potential hazard quotient (Table 11) for contaminated metals revealed that the values of As in rice and drumstick (Sajna), Pb in rice, pomegranate (Dalim), arum (Kochu), drumstick (Sajna), and Cu in arum (Kochu) ingestion rate was higher than 1 (PHQ > 1; bold typed face), remarked that the local people in the research area seems to be exposed to the significant health hazard from arsenic and lead.

Table 11

Potential hazard quotients (PHQ) for individual metals caused by the consumption of foods in the study area.
Samples ID	As	Pb	Cd	Cr	Cu	Zn
RP-1	3.82	0.87	0.34	0.005	0.41	0.22
RP-2	1.35	2.05	0.74	0.007	0.24	0.42
RP-3	2.67	0.76	0.34	0.003	0.31	0.22
RP-4	1.51	0.83	0.40	0.004	0.35	0.28
FS-1	0.12	0.58	0.18	0.002	0.83	0.13
FS-2	0.69	0.97	0.84	0.003	0.60	0.18
FS-3	0.08	1.38	0.74	0.003	0.98	0.30
FS-4	0.58	1.2	0.46	0.005	1.93	0.24
FS-5	2.23	1.6	0.59	0.006	0.73	0.30
Mean	1.45	1.14	0.51	0.004	0.71	0.25
SD	1.26	0.47	0.23	0.002	0.52	0.084
[N.B.: Bold type faces indicate significant values]

The probability of an individual developing cancer over exposure to contaminated food consumption is calculated by using carcinogenic risk (CR). The CR was calculated for As, Pb, and Cd according to the equation developed by USEPA-2005, presented in Table 12. According to US-EPA, the carcinogenic risk value is greater than 10 − 6, which suggests that the people in the vicinity are at high carcinogenic risk. The results of carcinogenic risk for harmful metals indicate that for rice grain, the values of As, Pb, and Cd are greater than 10 − 6, which suggests that the people of the study area are at high carcinogenic risk according to USEPA.

Table 12

Carcinogenic risk of As, Pb and Cd due to direct consumption of contaminated food (rice) in the study area.
Sample ID	Carcinogenic risk
Sample ID	As	Pb	Cd
RP-1	0.0172	0.00003	0.0051
RP-2	0.0061	0.00007	0.0111
RP-3	0.0120	0.00003	0.0051
RP-4	0.0068	0.00003	0.006
Mean	0.0105	0.00004	0.0068
SD	0.00517	0.00002	0.00288

Analytical results from this research indicate that the availability of As in irrigation water led to significant enrichment of arsenic in the irrigation soil, mainly on the upper surface (0–10 cm), and through translocation processes or bioavailability of arsenic gets into the human consumable food chain. This study also suggests gradual arsenic poisoning in groundwater and irrigation soil has increased. Inhabitants of those areas were possibly affected through drinking and ingestion As contaminant food for a couple of years, and health hazards increased throughout the country. Arsenic concentration in soil ranges from 4.54 to 40.20 mg/kg, while irrigated and non-irrigated land contain 24.51 (avg.) and 8.43 (avg.) mg/kg of arsenic, respectively. Strong correlations between dissolved Fe, As, and Mn in soil (As vs. Fe, r = 0.871); (As vs. Mn, R² = 0.905) suggest that high elemental affinity present between Fe, Mn, and As and from which arsenic can strongly accumulate over the soil. According to principal component and cluster analysis, metals concentration in soil are natural (As, Co, Ni, Cu, Fe, Mn) and anthropogenic (Zn, Cd, and Mg). Soil contamination indices like enrichment factor, geo-accumulation index, and contamination factor indicate arsenic is the dominant metal (Enrichment factor = 16.76; Geo-accumulation index = 2.33 and Contamination factor = 9.15) contaminant in a soil sample collected from Bholadanga. Meherpur, Southwestern Bangladesh. These soil contamination indices suggest that the soil of the study area is highly contaminated with arsenic. Among the food samples, paddy contains the highest arsenic concentration compared to other vegetables or fruit samples. Arsenic concentration in paddy ranges from 78.2 to 211.7 mg/kg where roots shows maximum concentration 140.8 mg/kg (avg.) followed by straws 5.25 mg/kg (avg.) and grain 1.23 mg/kg (avg.). Eighty-five to Ninety-five percent of arsenic exist in the roots of paddy, and only 0.8 to 1% of arsenic translocates to the harvesting part of the rice in the study area. Significantly high value to net translocation coefficient from root to harvesting part of paddy and bioaccumulation index plants absorbs metals both from soil and supplied contaminated water. The transfer factors of metals arsenic (6.48 avg.) in paddy and cadmium (2.5 avg.) in paddy and other food samples show the maximum transfer rate from soil to plants, ensuring the circulation of metal from groundwater and soil to crops. The minimum (0.00047) cancer risk value exceeds the United States Environmental Protection Agency (USEPA) limit of 10 − 6, which strongly indicates that the people in the Bholadanga village were extremely carcinogenic. Daily intake of metals shows harmful metals like As, Ni, Cr, and Pb are the highest accumulated in the human body by consumable food in the affected areas. Arsenic and Pb show the maximum potential hazard quotient from the food sample. Carcinogenic risk assessment from food samples for As, Cd, and Pb exceeds the USEPA limit. The consequence of the risk assessment suggested that the inhabitants of the research area are at very high carcinogenic risk due to drinking or consume As contaminated food for a long time.

Data Availability: Data is available in the text of the manuscript.

Conflict of interest: The authors declare that they have no conflict of interest.

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Accumulation of arsenic and other metals in soil and human consumable foods of Meherpur district, southwestern Bangladesh and associated health risk assessment

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials And Methods

2.1 Site description

2.2 Sampling

2.3 Sample analysis

2.4 Sample preparation

2.5 Instrumental analysis

3. Data Analysis

3.1 Statistical analysis

3.2 Assessment of soil contamination

3.2.1 Enrichment Factor (EF)

3.2.2 Geo-accumulation Index (I_geo)

3.2.3 Contamination Factors (CF)

3.3 Degree of metal concentration in crops and human

3.3.1 Transfer Factors of Metal (TF)

3.3.2 Net Translocation Coefficient (NTC)

3.3.3 Bio-accumulation Index (BI)

3.3.4 Daily Ingestion of Metals (DIM)

3.3.5 Potential Hazard Quotient (PHQ)

3.3.6 Carcinogenic Risk (CR) from Food (Rice) samples

4. Results And Discussions

4.1 Soil contamination

4.2 Metal concentration in foods

4.3 Multivariate statistical analysis

4.3.1 Sources of metals concentration in soil samples

4.3.2 Sources of metals concentration in food (paddy) samples

4.3.3 Pearson's correlation among the metals of soil and food samples

4.4 Accumulation of arsenic in soils and plants

4.5 Metals transformation from soils to crops

4.6 Human health hazards of local people

5. Conclusions

Declarations

References

Status:

Version 1

Accumulation of arsenic and other metals in soil and human consumable foods of Meherpur district, southwestern Bangladesh and associated health risk assessment

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials And Methods

2.1 Site description

2.2 Sampling

2.3 Sample analysis

2.4 Sample preparation

2.5 Instrumental analysis

3. Data Analysis

3.1 Statistical analysis

3.2 Assessment of soil contamination

3.2.1 Enrichment Factor (EF)

3.2.2 Geo-accumulation Index (Igeo)

3.2.3 Contamination Factors (CF)

3.3 Degree of metal concentration in crops and human

3.3.1 Transfer Factors of Metal (TF)

3.3.2 Net Translocation Coefficient (NTC)

3.3.3 Bio-accumulation Index (BI)

3.3.4 Daily Ingestion of Metals (DIM)

3.3.5 Potential Hazard Quotient (PHQ)

3.3.6 Carcinogenic Risk (CR) from Food (Rice) samples

4. Results And Discussions

4.1 Soil contamination

4.2 Metal concentration in foods

4.3 Multivariate statistical analysis

4.3.1 Sources of metals concentration in soil samples

4.3.2 Sources of metals concentration in food (paddy) samples

4.3.3 Pearson's correlation among the metals of soil and food samples

4.4 Accumulation of arsenic in soils and plants

4.5 Metals transformation from soils to crops

4.6 Human health hazards of local people

5. Conclusions

Declarations

References

Status:

Version 1

3.2.2 Geo-accumulation Index (I_geo)