Heavy Metal Analysis in Agricultural Soils in Godavari River Basin of Rajahmundry Region, East Godavari District, Andhra Pradesh, India

Introduction

Soil is a resource in the environment that supports agricultural practices. Additionally, acted as a filter to eliminate contaminants in water that seeps into ground water aquifers that are crucial for agricultural activities, carbon storage, and water regulation¹, the crop productivity and soil fertility will be increased by using fertilizers, necessary for supplying sufficient nutrients and ensuring fruitful harvests.², the over utilization of fertilizers in agricultural fields, leads to the contamination^{3, 4 ,5},  this contamination increases the soil pollution and toxic levels^{6 ,7}, these are inorganic⁸, naturally, with high atomic weight, the density greater than 5g/cm^{3.  9}, these may occur naturally in soils and used to manufacture fertilizers, these fertilizers are made with heavy metals, agricultural activities are the source to depositing residues into soils^{10 ,11}. These metals are contaminated the soils & adversely affect the ecosystem, when migrated into groundwater and taken up by flora & fauna through bio accumulation and biomagnifications. It results a great threat to ecosystems, and risk to management of soils^{12, 13 ,14}, Heavy metals could be harmful to all living things when polluted soils are used for crop production^15,16,17,18, land formation is severely hampered by intense agriculture and other human activities, which also cause the biosphere’s pollution to rise¹⁹.

The organization for Toxic Substances and Disease Registry (TSDR) (2007) states that among the heavy metals like arsenic, cadmium (Cd), lead & mercury have negative consequences on health ^{3, 4,5,16,17}, accurate predictions of metal content in soil are crucial ^15,18,19. As per results of air deposition, roots may cling to crop surfaces and take up heavy metals from the soil^20,21, various studies were assessed on concentration & bioaccumulation of heavy metals caused by agricultural practices, excessive pesticide or fertilizer use²², these are leached and not degradable^23,24,25,26, because contaminated plants can cause cancer and chronic diseases²⁶, metals like copper, zinc, nickel, and manganese, all of which are harmful in large amounts, and some of few heavy metals even at very small doses, mercury, cadmium, lead, and arsenic are hazardous substances²⁷, these are affecting the air, water, soil, and living creatures ^28,29,30.

Methodology and Method.

Study area

The research area is in East Godavari district, there are eight villages in Rajahmundry region was chosen to collect the soil samples, which is exceptionally fertile and lush green fields. It is one of Andhra Pradesh’s 12 coastal districts and a part of the Godavari delta, it has a tremendous potential for surface water resources are more commonly seen in canal-irrigated portions of the delta region composed with red clayey, deltaic alluvial and deltaic alluvium soils, all of which are grey brown to black in color and have fine to medium textures. (Figure 1) The major crops are Coconut, Banana and Paddy, as well as more vegetable crops are also practices in the study area.

Sampling method

To assess the impact on soil quality by anthropogenic activities, sample were collected from agricultural land, eight soil samples are collected in 16 agricultural farms in the month of December 2020 to July 2021. They are located in Godavari river basin, that includes Kadiyapulanka- S1 (field 1 & 2), Pottilanka-S2 (field  3 & 4), Choppella-S3 (field 5 & 6), Jonnada –S4 (field 7 & 8), Aalamuru -S5 (field 9 & 10), Kapileswarapuram -S6 (field 11 & 12), Korumilli -S7 (field 13 & 14), and Kulla-S8 (field 15  & 16) (Table 1, Figure 1 & 2). Four composite soil samples were collected from 8 sampling station, 15 kg of soil from each of the four forming areas, making a “V” type cut with shovel at a depth about 15 cm to collect thick slices of soil and exposed dirt from top to bottom then placed in a bucket. There are approximately 15 samples were collected from each sampling unit. The sample has been mixed well and removed foreign materials like pebbles, gravel and roots. The quartering technique was applied by dividing the mixed samples into 4 parts, the 2 contrary quarters are detached and remaining two quarters remixed and process has repetitive upto the desired sample size is obtain, the sample was collected in polythene bag and labeled the place of collection, date and time.

Figure 1: Study area and sampling stations map Click here to view Figure

Figure 2: Soil sample collection point “V” Shaped cutting in the soil in the study area. Click here to view Figure

Table 1: Sampling stations in the study area

Name of the sampling station	Station No	Longitude	Latitude
Kadiyapulanka	S1	81.8131O	16.8925 O
Pottilanka	S2	81.8082O	16.9021 O
Choppella	S3	81.8483O	16.7383O
Jonnada	S4	81.8627 O	16.6969O
Aalamuru	S5	81.8996O	16.7793O
Kapileswarapuram	S6	80.8641O	16.3232O
Korumilli	S7	81.9108O	16.7541O
Kulla	S8	82.0068O	16.7541O

Methods

The calcium chloride solution (0.15%) used as extractant to analyse soil samples³¹. The heavy metals concentrations are determined by using an AAS (Lab-India AAS 8000. Make (model): Varian (AA240FS)), diethylene triamine penta acetic acid extractant used for assessed Fe, Zn and Cu in soil samples³². The instrument AAS was utilized for estimation of Fe, Zn and Cu, the glass ware are cleaned with 10 % HNO₃ solution & distil water^33,34, the standard and blank samples are made with analytical grade chemicals and reagents. The device was calibrated with a heavy metal blank of different concentrations and a reference standard. A blank and standard sample was run to ensure quality, the analysis were performed in three times.

Estimation of contamination and ecological risk.

An estimation of metal pollution in soil samples by calculating Contamination Factor, Coefficient Variation, PERI^35,36.

Contamination Factor (CF)

The CF was calculated using follow Equation … (1), it is a ratio of particular metal content -C_i, C_b-is a background value of such metal ^37,38.

CF= C_i/C_b       ……….(1)

Table 2: CF Classification.

Concentration levels	Un-contaminated	slight	moderate	considerable	strong	Very-strong
CF (Individual- metal)	Less than are equal to 0 (≤ 0)	0 less than are equal to 1 (0≤1)	1 less than are equal to 3 (1≤3)	3 less than are equal to 5 (3≤5)	5 less than are equal to 6 (5≤6)	greater than 6 (≥6)

Coefficient Variation (CV),

The level of human interference is clarified using the coefficient of variation. It is inversely correlated with human intervention, which is the more extensive category of human activity³⁹. It has been categorized into 3 categories, CV< 0.15 are low variation, 0.15 < CV < 0.36 are medium variation & CV > 0.36 are high variation are estimated as per Eq. (2). ^36,40.

CV= Standard Deviation/Mean  …….(2)

Soil Contamination Assessment.

Contamination of heavy metals status in collected soil sample was assessed with PERI. This is a process to recognize the impact of pollutants (heavy metals) in Agricultural soils using the formula showed that in Eqs. (3) & (4). PERI is the risk index in ecologically and elucidate as the sum of the PERI (Ei) of various metals, categorization of PERI was showed in Table 3.⁴¹.

PERI = Σ E_i   ……(3)

E_i= T_i(C_i/ C₀)  …….(4)

The following metals have different toxic response factors: Ni, Cu, Pb-5, Cd-30 Cr-2, Fe-1, & Zn- 1. Ci is a level of the trace metal in soils, and C₀ is background concentration of trace metals in collected samples of agricultural soils. Ei is PERI of a specific trace metal present in soil sample, RI is Risk Index.

Table. 3: PERI Classification.

Risk-R	low- level	moderate level	considerable level	high-level	very High
Ei	<40	40≤80	80≤160	160≤320	≥320
RI	≤150	150<RI≤300	300<RI≤600	–	>600

Results and discussion

Trace metals (heavy metals) are harmful to the environment & put nature in peril. This essay focuses on harmful impact of heavy metals on agricultural soils, including toxic effects of Cd, Pb, Cu, zinc (Zn), Cr, cobalt (Co), As, Ni, and Fe.²²

Pb can be found in rocks that are rich in phosphate and superphosphate a powerful affinity for organic material, the concentration of Pb in samples were observed as S4-88.29 ppm > S1-85.45 ppm > S8-83.27 ppm> S6-77.88 ppm > S3-72.16 ppm > S2-60.14ppm > S5, S7-57.92 ppm and the mean, standard deviation levels are 12.755 ± 72.878. The high content acceptable for lead in soil samples is 70 mg/kg^-1 as per WHO standards. The higher levels are pointing towards the anthropogenic activities and natural sources. It may be elated a large distance from the source to sink point by volatilizing at high temperatures^42&38. It will change the soil pH^{43 &44}, affected the soil absorption capacity & reduce fertility of the soil^45,46,47,48.

The Iron concentration at different sampling stations is below the standard level as per WHO. The minimum and maximum levels are observed in S1-10882.7mg/kg^-1, S4 – 22038.6 mg/kg^-1 in study area, higher levels are observed in S4>S5>S8>S7 samples, the mean and standard deviation levels are 4571.72±16889.1, similar studies results are by ^18,38&49. Higher levels were observed in all sampling stations, because the major sources is rock systems, high organic matter and continuous usage of inorganic fertilizers for good crop productivity in agricultural region ^50,51, the addition of fertilizers and compost is also increases Iron in soil samples ^49,52.

Zinc is an essential element to organisms, Zn levels were observed as higher to lower levels in the study area are S3>S1>S2 > S8 >S6>S4>S6>S7, the maximum levels are reported in S3-324.23 ppm, S1-257.34 ppm, S2-254.87 ppm , S7- 204.77 ppm indicated in Table 4 & Fig 5 . The mean and standard deviation is 224.583 ± 52.103 (Table 2 & fig 3). The Zn will increase by highly leached acidic soils. There are four samples have higher values remaining are in the below standard limit in the soil samples. Zn concentration in soils is raised by drain water, municipal waste water; industrial effluents utilized for irrigation, over usesage of Zn sulphate fertilizers might be cause for high level of Zn in agricultural soils leads to change the physic chemical parameters in soils. ⁵³largely contributed by anthropogenic activities like agricultural practices⁵⁴ human activities⁵³, excess Zn may alter the bicarbonate and organic matter contents, prevent organisms from producing certain enzymes, and change the pH of the soil^55&56. Similar studies were observed that higher concentrations in soils^57,58.

Typically, nickel is viewed as a geogenic element⁵⁹, mostly connected to the crystalline network of basic minerals⁶⁰. Nickel concentration in soil samples are as follow S1> S2> S5 > S7> S8 >S4 > S6> S3 sowed in figure 4, there are four samples have higher levels due to over usage of fertilizers and human activities⁵³, the mean and standard deviation is 12.492 ± 75.673 indicated in Table 2 and fig 3.

The major contribution of Cu is agricultural practices⁵³, and derived from anthropogenic activities⁵⁴, higher cupper levels are observed in S6 > S2 > S4 > S5 remaining all samples are below the standard limit as per the WHO standards indicated in fig 3 & 5, the mean and standard deviation values are 9.313 ± 27.511 (table 2 & fig 4). Cu might be attributed to the use of Cu containing and irrigation by sewage ^61,62, high concentration of Cu may be affected the soil micro organisms, change urease activity and oxidation potential^{63, 64,65}, damage the earthworms ^66,67 Northern Tanzania’s cultivated soils were found to have accumulated significant amounts of copper Northern Tanzania’s cultivated soils were found to have accumulated significant amounts of copper ⁶⁸.

The Cd concentration is very high in soils due to irrigation drains along with sewage^{17, 69,70}. The cadmium concentration levels in the present study soils samples have slightly concentration, the mean and standard deviation levels are 0.610  ± 1.15, the samples S1 & S8 have the minimum and maximum levels of the cadmium, due to over usage of chemical fertilizers its concentration had been increased. Cadmium is found in phosphate fertilizers^71,72. It (Cd⁺²) Effects in soils and kill microorganisms, increase the Earthworm mortality⁷³, absorb organic matter, as well as change the soil physicochemical characteristics^{74, 75, 76 , 77}. It enters the food chain by being absorbed by cereal-based crops such as rice and other crops such as vegetables.

The cobalt levels are slightly higher than the standard limit, the mean & standard deviation of cobalt was observed as 4.11173 ± 15.5663, and the maximum concentration observed in S5 > S2 > S1 sampling stations. Few samples are below the standard levels of WHO in soil samples^38,78.

Chromium levels in the present soil samples has been observed slightly higher levels in S3-127.82 ppm > S1 -118.85 ppm > S8- 112.72 ppm > S4-108.91 ppm,  reaming four samples have lower levels of the chromium, the minimum level of Cr was found in S6-73.94 ppm, the mean and standard deviation levels are  103.741 ± 17.0258. The high concentration of Cr was by using the waste water for irrigation in agricultural regions and dumping of waste from chemical industries in the drain.³⁸ similar studies stated that high concentration of Cr affected the soil microorganisms^79&80. Arsenic levels in the present study area observed as S4-15.21 ppm> S3-14.78 ppm> S8-13.27ppm are higher levels and the S6< S1< S7< S2 and S5 are have the minimum levels of the Arsenic, and the mean, standard deviation levels are 3.10689 ± 11.0325. Arsenic pollution is not a major concern⁸¹. The major source of Arsenic was the industrial activities and their products such fungicides, insecticides, pesticides, herbicides^{82, 83}. Over usage of these may cause the soil pollution,

Anthropogenic and geogenic sources are distinguished as the two main sources of the metal relationship ^{84, 85&86}. The overall higher levels were observed in S1- Kadiyapulanka, S4- Jonnada, and S8- Kula, the Mean levels in soil are obaserved in the order like Zn>Cr>Ni>Cu>Pb>Fe>Co>As> Cd.  An average & standard deviation in study area are Iron, Zinc, Chromium, Nickel, lead, Copper, Cobalt, Arsanic and Cadmium. were 16889.1 ± 4571.72mg kg^-1, 224.583 ± 52.103mg/kg^-1, 103.741 ± 17.0258 mg/kg^-1, 75.6738 ± 12.4923mg/kg^-1, 72.8788 ±12.7551mg/kg^-1, 27.5113 ± 9.31357 mg/kg^-1, 15.5663 ± 4.11173mg/kg^-1, 11.0325 ± 3.10689mg/kg^-1 and  1.15125 ± 0.61096mg kg^-1, respectively., It has assumed that long term exposure to high level of arsenic (As) damages the organs of organisms per trace metal levels in soil samples¹¹.The Copper (Cu) & lead (Pb) was impaired the immunity as well as fertility⁸⁷ .This may be due to the Pb added to gasoline in the past, as well as the low sensitivity of analytical methods used for measurement An increased efficiency of metal pollutants in crops are very different like rice, banana, Vegetables, and in commercial crops ^{88,89 &90}, but the contaminations are very easy in paddy than other crops⁹¹.Which suggest regular rice consumption is a significant risk to the health based on the concentration in soil samples⁹².

Lead in soils is found in various forms, such as the ionic form in soil solution, exchangeable in organic and inorganic matrixes, structural components of mineral lattices, and insoluble precipitates ^45,93, Mining and related activities discharge large amounts of wastewater and solid waste to the environment, which often contain Pb⁹⁴. Thus, Pb enters into soils through atmospheric diffusion, surface runoff flushing, and weathering⁹⁵.

Contamination Factor (CF)

Soil Pollution indices make it simple to gauge the degree of soil pollution¹⁸, the present study samples are observed as contamination by heavy metals, as per the classification (Table 2) Ni, Pb, Cr, Zn, As, Co and Cu metals were moderate contamination but the Cd is considerable contamination in S5, S7 and S8 soils samples (table 4) which indicated that agricultural soil are contaminating by the heavy metals. Hence, the fertilizers utilization should be decrease in agricultural sector.

Coefficient Variation (CV)

The categorization of coefficient Variation like (< 0.15) is low variation, (0.15 <0.36) is medium & (>0.36) was high variation found in order like Cd > Cu > As > Fe > Co > Zn > Pb>Ni> Cr with values 0.530691 > 0.338537 > 0.281612 > 0.27069 > 0.264144 > 0.231999 > 0.175019 > 0.165082 > 0.164118. Based on the categorization Cd is in the high variation remaining all metals are in medium variation in soil samples, indicates that the input of metals by anthropogenic activities in study area, and it shows heterogeneous occurrence⁴⁰.

Potential ecological risk index

The PERI was calculated for Pb, Zn, Co, Ni, Cd, Cr, Cu & As, results are indicated in table 6 and 7, as per the categorization of risk index (Table- 3), the values of PER index found to be highest for Cd in S2, S3, S5, S7 and S8 samples, The high level of Cd in fertilizers become a source for its enrichment in soil samples⁸². Which indicates the carcinogenic problems will rise in the organisms ⁹⁶, as well as low risk to moderate risk has been observed in all sampling stations in study area, toxic concentrations are gradually increasing & accumulate into to crops leads to ecological risk in study region.

The findings showed that the percentage of Cu, Pb and Cd are considerably enriched in soil. According to study of Mohammed⁹⁷ fertilizers and pesticide residuals are increases the toxicity in agricultural soils⁹⁸ , the distribution of heavy metals (Cr, Ni, Pb, Cd, & Zn), were found by colombian researchers in soil sample⁹⁹. The similar study have been observed in soils samples wide-ranged as follows Zn>Cr>Ni>Pb>Hg> Cd ^{99,100,101,102,103,104}, Heavy Metal content in study area soils are very high, due to over use of fertilizers, both natural & human activities contribute heavy metals into soil^{105,106, 107,108}.

Pearson’s correlation was widely used to know similarity to find interrelationship of parameters, the correlation analysis was showed in table 6. Cr – Co, Zn, Fe, Cd, Pb and As has positive correlation, Arsanic having positive correlation with Cr, Fe, Cd, Zn, Pb & Co. Cu has positive relation with Ni, Cd has positive correlation between Ni and Fe. A significant positive correlation was observed in agricultural soils is usage over usage of fertilizers, the Pb, and As are accumulated by using fertilizers¹⁰⁹. The correlation coefficient of Cr-Zn (0.559), Zn-Co (0.5609) As-Fe (0.5514) were greater than 0.5. The positively correlation was observed in between heavy metals (p < 0.01). A relatively negative correlations were noticed between (Pb – Ni), (Pb – Cu), (Pb – Co), (Cd – Zn), (Zn – Cu), (Ni – Zn), (Cr – Ni), (Cu – Cd), (Fe – Co), (Fe – Ni), (Fe – Cu) and so on in table 6. It indicates the less significant correlations between heavy metal, due to affect of different pollutant source ^80,110,111.

Table 4: Minimum, Maximum, Mean and SD

	Pb	Zn	Ni	Cu	Co	Fe	Cd	Cr	As
Min	57.92	159.83	55.81	13.82	10.28	10882.7	0.23	73.94	6.73
Max	88.29	324.23	91.37	38.63	19.81	22038.6	1.82	127.82	15.21
Mean	72.8788	224.583	75.6738	27.5113	15.5663	16889.1	1.15125	103.741	11.0325
SD	12.7551	52.103	12.4923	9.31357	4.11173	4571.72	0.61096	17.0258	3.10689

Table 5: Correlation of the heavy metals

	Pb	Zn	Ni	Cu	Co	Fe	Cd	Cr	As
Pb	1
Zn	0.1996	1
Ni	-0.36	-0.2909	1
Cu	-0.041	-0.3245	0.4181	1
Co	-0.356	0.5609	0.369	-0.1759	1
Fe	-0.133	-0.5975	-0.2017	-0.2579	-0.254	1
Cd	-0.393	-0.6996	0.1456	-0.1076	-0.202	0.778	1
Cr	0.3422	0.5592	-0.2253	-0.7095	0.4282	0.1086	-0.2699	1
As	0.2247	0.2717	-0.5994	-0.5742	0.0194	0.5514	0.23602	0.6295	1

** Correlation is significant at the 0.01 level.

Table 6: Contamination Factor values.

CF  value	Pb	Zn	Ni	Cu	Co	Cd	Cr	As
S1	***M	***M	***M	***M	***M	**S	***M	**S
S2	***M	***M	***M	***M	***M	***M	***M	***M
S3	***M	***M	**S	**S	***M	**S	***M	***M
S4	***M	***M	***M	***M	**S	***M	***M	***M
S5	***M	***M	***M	***M	***M	****C	***M	***M
S6	***M	***M	***M	***M	**S	***M	**S	**S
S7	**S	**S	***M	***M	**S	****C	***M	***M
S8	***	***M	***M	**S	***M	****C	***M	***M

** Slight contamination, ***Moderate contamination, ****Considerable contamination

Table 7: Coefficient Variation (CV)

	Pb	Zn	Ni	Cu	Co	Fe	Cd	Cr	As
CV	0.175019	0.231999	0.165082	0.338537	0.264144	0.27069	0.530691	0.164118	0.281612

Table 8: Classification of Potential Ecological Risk

Ei&Ri Values	S1	S2	S3	S4	S5	S6	S7	S8
Pb	low	low	low	low	low	low	low	low
Zn	low	low	low	low	low	low	low	low
Ni	low	low	low	low	low	low	low	low
Cu	low	low	low	low	low	low	low	low
Co	low	low	low	low	low	low	low	low
Cd	low	Considerable	low	Considerable	Considerable	Moderate	Considerable	Considerable
Cr	low	low	low	low	low	low	low	low
As	low	low	low	low	low	low	low	low
Ri = ∑Ei	low	low	low	low	Moderate	low	Moderate	Moderate

* L –Low level, **M-Moderate level, ***C- Considerable level

Table 9: Potential ecological risk index values.

Ei	S1	S2	S3	S4	S5	S6	S7	S8
Pb	7.283	5.126	6.150	7.525	4.936	6.638	4.936	7.097
Zn	1.425	1.411	1.795	1.099	1.0149	1.133	0.885	1.183
Ni	7.027	6.839	4.292	5.104	6.363	5.190	6.332	5.411
Cu	8.818	10.350	4.031	9.600	9.165	11.268	6.595	4.372
Co	15.578	16.289	15.745	8.968	16.573	8.600	9.972	12.457
Cd	15	87.391	28.043	86.739	105.652	46.956	112.173	118.695
Cr	2.629	2.012	2.8276	2.409	2.209	1.635	2.142	2.493
As	8.478	11.074	15.922	16.385	11.074	7.250	10.600	14.295
Ri	66.240	140.494	78.809	137.833	156.991	88.675	153.639	166.008

Figure 3: Min and Max values of Heavy metals                           Click here to view Figure

Figure 4: Min, Max, Mean and SD of Fe in soil sample Click here to view Figure

Figure 5: Concentration of trace metals in soil sample Click here to view Figure

Conclusion

Soil samples are collected for analyse the heavy metals concentrations and calculated the soil ecological risk index, results are showing enrichment of (heavy) trace metals like Fe>Zn> Cr>Ni>Pb>Cu>Co>As>Cd, most of the samples have high concentrations. The Pearson’s correlation matrix showed that significant strong correlation in between the heavy metals and influenced by each other metal. The contamination factor indicated soil samples were found to be contaminated, that is moderate contamination of heavy metal except Cd., it is in considerable contamination in S5, S7 and S8 soil samples. The coefficient variation was observed as high variation in metals concentration like Cd > Cu > As > Fe > Co > Zn > Pb > Ni > Cr, based on the categorization, here also Cd is in high variation remaining all metals are in medium variation and showing heterogeneous occurrence of metals. Potential ecological risk index was observed very high for Cd in S2, S5, S7 and S8 samples based on the PERI categorization. Based on the result analysis heavy metals concentrations are gradually increasing and may be accumulated into crops leads to ecological risk in study area due to over usage of chemical fertilizers, which indicated that agricultural soil are contaminating by the heavy metals. Hence, the fertilizers utilization should be decrease in agricultural sector. 

Acknowledgment

Authors are grateful to School of Life and Health Sciences at Adikavi Nannaya University in Rajamahendravaram provided the required resources to conduct research.

Conflict of interest

The authors declared no conflict of interest.

Funding Sources

There are no funding sources.

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Abbreviations

AAS– Atomic Absorption Spectroscopy

PERI – Potential Ecological Risk Index

CF – Contamination factor

CV – Coefficient variation

TSDR -Toxic Substances and Disease Registry