Groundwater quality assessment for drinking, irrigation, and human health hazards with special emphasis on Nitrate pollution in Uddanam area, Srikakulam district of Andhra Pradesh, India

doi:10.21203/rs.3.rs-2005119/v1

This study's goal is to evaluate the Uddanam region's groundwater quality for drinking, agricultural use, and potential health risks to people, with a focus on nitrates. From the research region, 50 groundwater samples were taken in both pre- and post-monsoons and analyzed for pH, EC, TDS, TH, TA, Ca²⁺, Mg²⁺, Na⁺, K⁺, CO₃, HCO₃⁻, Cl⁻, SO₄²⁻, NO₃⁻, F⁻, and Si, among other physic-chemical parameters, TDS, total hardness, nitrates and silica are the highest ions among all chemical parameters. May's findings indicate that kidney illness is a result of higher above said parameters. In addition, the chemical data intensity is represented using spatial interpolation techniques in Arc GIS 10.1 software, and intensity maps of the research region are prepared. The irrigation metrics salt absorption ratio (SAR), Kelley's ratio (KR), and percent sodium (%Na) are all within the research area's allowed limits.In the study area, pre and post-monsoon nitrate total hazard index (children, men, and women) affected percentages are 94%, 53%, 37% and 94%, 51%, 29% respectively, whereas the dermal there is no significant effect on the human body. The Gibbs diagram shows that the disintegration of rock formations is responsible for the groundwater chemistry and is further supported by scatter plots. Chemical elements are generated in the study due to geology such as Khondalite and alluvial soil disintegration. The excess silica percentage may lead to affect kidney-born disease in the study area and hence adequate water treatment is required prior to use.

Groundwater chemistry

USSL diagram

Wilcox

piper diagram Gibbs

and Human health hazard index

Water is a vital resource for both biotic and abiotic factions to survive (Bari &Yeasmin, 2014; Etikala et al. 2021). The phrase "water quality" refers to the physical, chemical, and biological qualities of water, whether it is fit for potable, irrigation, and other industrial uses (Golla et al, 2020; Akhtar, et al, 2021). Especially for drinking purposes, which may have an impact on human health (Li, P & Wu, 2019; Balaji et al, 2019). The primary source of drinking water is groundwater. In comparison to surface water, underground water is clean and pollution-free (Arveti, et al, 2019). The overuse of pesticides and fertilizers, rising human activity, and the fast development of industry have all contributed to the contamination of groundwater. Groundwater must first undergo quality testing before being used as portable water for home purposes because it has a high concentration of different ions, salts, etc. Otherwise, it can result in water-borne illnesses. Keeping groundwater in a fit state for human consumption is therefore crucial. (Golla, et al. 2021).

Kidney illness is currently the most serious issue confronting the entire planet. It was recorded in Nicaragua, El Salvador, Mexico, Sri Lanka, Croatia, Serbia, and Uddanam in India. Among all countries, Nicaragua, Sri Lanka, and the Uddanam region of Andhra Pradesh have the most patients. According to Indian government figures, about 50000 persons in the Uddanam region had chronic renal disease, with 5000 fatalities documented (Satyanarayanaet al, 2017).

Uddanam is one of the regions with a high population of persons suffering from chronic renal disease. The majority of both urban (90%) and rural (30 percent). The students rely solely on groundwater. The Mandal offices are conveniently accessible from many communities. The nearest railway stations are Sompeta and Palasa, from which trains to other regions of the nation may be boarded. The research region includes the Eastern Ghat Super Group, which is represented by the Khondalites Group, Charnockite Group, and Migmatites and dates back to more than 2500 million years ago. These are the area's earliest hard rocks, which are unconformable and are overlain by Holocene fluvio-marine Quaternary sediment layers. Chronic kidney disease (CKD), in which kidney function declines as the disease continues, eventually leading to kidney failure. The present study area Detroiter the groundwater quality due to the dissolution of the mineral and silica group of rocks. Hence, the proposed research is conducted to evaluate the groundwater quality in the Uddanam region for potable and agricultural uses as well as human health hazard evaluation.

Study area

Uddanam is a lush green region in the Srikakulam District of Andhra Pradesh state, India. (Fig.-1) located on the northeast coast of Andhra Pradesh with the rich coconut and cashew plantations. Geographically Uddanam is located at 18° 31' 2" to 19°7'54"N and 84°19'15" to 84°46"02'E. It elevates 41 metres above sea level on average. The study area is covered by parts of Survey of India (SOI) toposheet Nos.74 B/05, 74 B/06, 74 B/09 & 74 A/12. The study area is about 100 km northeast of the district headquarters at Srikakulam. The National Highway (NH-16) passes from the study area which connects Howrah in the east and Chennai in the south. It has rail and road connections to the nation's largest cities, including those in Andhra Pradesh, Telangana, and Odisha (Figure 1.0). Most of the villages whether near the coast or in the forest area are well interconnected by a network of metalloid roads.

To obtain more accurate analytical data, 50 groundwater samples were taken in the pre-and post-monsoon (Figure 2.0) and subsequently evaluated.After collecting the samples, the electrical conductance (EC), pH, and total dissolved solids (TDS) of the water are tested in the field using a portable waterproof EC/pH/TDS meter (Hanna-SKU: HI991301P)(Balaji et al. 2017, 2019;Reddy et al, 2022). A UV-visible spectrophotometer was used to analyze the water samples for nitrate (NO₃^2-) and sulfate (SO₄^2-).Volumetric methods were used to calculate the concentrations of carbonate (CO32-), bicarbonate (HCO3-), calcium (Ca2+), and magnesium (Mg2+). A flame photometer is used to determine the amounts of sodium (Na+) and potassium (K+). Utilizing the SPADNS approach, fluoride (f) was measured (Bhujangaiah, and Vasudeva Nayak, 2005). All concentrations are expressed in milligrams per liter (mg/l). The chemical analysis of pre- and post-monsoon is in Tables 1.0.

The groundwater in the Uddanam area has been examined in terms of physicochemical properties, and the drinking, irrigation, and human health hazard indexes have been derived as a result. These parameters are described more below:

Hydrogen–ion Concentration (pH):

The pre-monsoon pH of the study area's groundwater ranges from 5.90 to 7.90 with a mean value of 7.07, and the post-monsoon pH ranges from 5.9 to 7.9 with a mean value of 7.19, respectively. It is indicating that the groundwater is slightly acidic to alkaline in nature Due to the interaction of groundwater water with minerals and rock formation in the study area (Adimalla, & Wu, 2019). In the spatial distribution diagram, the higher pH range of the value s lies in the NW direction, whereas the lowest values fall in the SW direction (Figure 3a-o & Figure 4a-o)

EC and TDS

In this study, Pre-monsoon EC values varied from 282 to 2404 with a mean value of 1016.23 (mg/L). Post-monsoon EC values range from 245 to 2000 with a mean value of 945.15 (mg/L) respectively. Pre-monsoon TDS levels in the study region vary from 183.3 to 1562.60 with an average value of 660.55(mg/L), whereas post-monsoon TDS values range from 159.25 to 1300 with an average value of 617.24(mg/L).The groundwater in the area appears to be moderately mineralized, and the EC and TDS values indicate that the water has enough time to interact with the solidmedia in the specified area (Kumar, 2014). In the spatial distribution diagram, the higher pH range of the values lies NW direction, whereas the lowest values fall in the NE direction.

Total Alkalinity (TA) carbonate and Bi-carbonate

In this study, pre-monsoon total alkalinity of groundwater ranges from to 160 mg/L to335 mg/L with a mean value of 256.33 mg/L, and post-monsoon total alkalinity of groundwater ranges from 163 mg/L to 342 mg/L with a mean value of 277.17 mg/l, respectively. The mineral calcite found in rocks and dissolved CO₂ in groundwater may be the source of alkalinity. The concentration of CO₃^2- in groundwater was found in traces, while the concentration of HCO₃^- in the pre-monsoon varies from 80 to 533 mg/L, with an average value of 253.23 mg/L, and in the post-monsoon HCO₃^-ranges from 61.35 mg/l to 577 mg/l, with a mean value of 195.75 mg/L respectively. Anthropogenic activities contributing more bicarbonate to groundwater are likely possible in areas with moderate to high levels of total alkalinity. In the spatial distribution diagram, the higher pH range of the values lies in the SW direction, whereas the lowest values fall in the NE direction.

Total Hardness (TH)

In the pre-monsoon, the total hardness of the groundwater in this area ranged from 213.40 mg/L to 842.90 mg/L as CaCO3, with a mean value of 389.50 mg/L, whereas during post-monsoon TH varies between 118.5 mg/L and 675.10 mg/L as CaCO3, with a mean value of 337.96 mg/L.Due to high quantities of calcium and magnesium, the groundwater seems to be hard. The lower TH range of the values fall in the southern direction, whereas the higher TH range is in the central and northern direction.

Major ion chemistry

In the study area, the concentrations of Ca²⁺ in groundwater for pre-monsoon are found in the range of 38 mg/L to 265mg/L with a mean value of 87.38, Whereas, in the post-monsoon concentrations of Ca²⁺ in groundwater range between 25.65 mg/L to 170 mg/l with an average value of 78 mg/L, respectively, in which the majority of the wells (65%) fell permissible and the remaining (35%) exceeded the BIS standards. The main reason is due to the dissolution of the calcite, the Khondalite group of rocks. Mg²⁺ ion concentrations in pre-monsoon varies from 12 mg/L to 83.94 mg/L the average concentrations of Mg2+ recorded as 42.16 mg/l, whereas for post-monsoon in groundwater the Mg²⁺ concentrations varied from 3.4 mg/L to 78 mg/l, and the mean value of 35.0 mg/L, respectively. In the spatial distribution diagram, the higher Ca²⁺is found in the entire study area with excess values found in western areas, whereas the higher Mg²⁺ range of the values lies NE direction, while the lowest values fall in the SW direction.

Na⁺ and K⁺ in the ranges in the Pre-monsoon concentrations are as follows: Na⁺ ranges between 35 mg/l to 185 mg/l with an average of 95.62mg/L, whereas, for post-monsoon samples, the concentrations of Na⁺ range between 22.99 mg/L to 187.00 mg/L, with an average of 88.71 mg/L and in pre-monsoon, concentrations of K⁺ varies between 7 mg/l to 42 mg/l with an average of 13.79 mg/L, whereas in the post-monsoon, the ionic concentrations of K⁺ ranges between 3.92 mg/l to 27.0 mg/l with a mean of 13.2 mg/L, respectively. In the spatial distribution diagram, the higher Na⁺ range of the value s lies SE direction, and the lowest values fall in the NE direction, whereas the higher K⁺ values lies NE and SW direction.

The most prevalent cation in groundwater is Na⁺, which is followed by Ca²⁺and Mg²⁺. K⁺ has the lowest concentration in groundwater.In groundwater, Na⁺ concentrations are considerably higher than K⁺ concentrations. The Na⁺ may also be contributed to groundwater from rainwater rich in sodium content from a coastal area (Balaji et al, 2019). The seawater ingression may also cause to increase in sodium content in groundwater. Anthropogenic sources such as domestic and industrial waste and wastewater are also rich in Na⁺ and if percolated into groundwater can significantly contribute to raising the concentration of Na+ in groundwater. Groundwater can get enriched with K⁺ as a result of agricultural operations if potassium fertilizers are widely employed. When organic matter decomposes and leaches from the soil, the K⁺ absorbed by plants can also serve as a source of K⁺ in groundwater. (Golla et al. 2019).

Pre-monsoon chloride (Cl^-) concentrations in the groundwater in this study locality range from 48 mg/L to 343.97 mg/L with an average value of 157.95 mg/L, whereas post-monsoon samples have chloride concentrations that range from 2.3 mg/L to 326.0 mg/L with an average value of 132.67 mg/L.For pre-monsoon samples, the concentration of SO42- in the groundwater in the following research ranges from 10 mg/L to 87 mg/L, with a mean of 36.52 mg/L. The concentration of SO42 in post-monsoon samples, however, varies from 11 mg/L to 89 mg/L with an average value of 38.06 mg/L.Groundwater in the field of study may contain SO42- due to atmospheric precipitation, agricultural activity such as the use of fertilizer and pesticides, and other factors. In the spatial distribution diagram, the higher Cl^- values are seen in the central region and the lowest values are seen in NE and SW directions. Whereas the higher SO₄^2-range of the values lies in a central region, whereas the lowest values fall in the NE and SW direction.

The nitrate values for the Pre-monsoon area range from 16 mg/L to 74 mg/L with an average of 42.66 mg/L whereas for post-monsoon samples the nitrate values are ranges from 16 mg/L to 77 mg/L with a mean value of 42.20 mg/L in pre-monsoon (Marchand et al, 2002). The pre-monsoon values of fluoride in the groundwater of this study region ranging from 0.19 to 1.0 mg/L with a mean of 0.42 mg/L, while post-monsoon concentrations ranging from 0.24 to 1.0 mg/L with an average of 0.49 mg/L.

In the study area, the silica values for pre-monsoon range from 15 mg/L to 57 mg/L with an average of 32.67mg/L, respectively. Whereas in post-monsoon the silica values varied from 21 mg/l to 116 mg/l with a mean of 51.73 mg/l, respectively. It shows the study area may face problems with access silicon ion concentration. The weathering of the silicate group of minerals, which is mostly produced from the rock water of the research area, is the primary cause of the silica present in the area (Hem, 1959).

Irrigation water quality classification:

In irrigation water quality percent sodium and sodium absorption are very important factors in determining the appropriateness of water for irrigation.

Wilcox diagram

Calculating the Na⁺% is another way of evaluating the suitability of groundwater for agricultural use. (Wilcox, 1955), since soil's permeability is decreased when Na⁺ concentration reacts with it (Todd and Mays, 2005). Except for one sample that falls into the unfit group during both monsoons, the sodium percentage values of the remaining groundwater samples, both in the pre-and post-monsoon categories, are good to permissible for irrigation use (Figure 4.0)

USSL classification

All of the samples exhibit low to medium SAR levels both before and after the monsoon, according to the USSL diagram's plotting of SAR statistics. The 50 samples were divided into two fields: C2-S1 (53.33 percent) and the remaining C3-S1(40%) and C4-S1. The USSL diagram classifies the C3-S1 field as having a reasonably good water type for irrigation usage. This indicates that no expected alkali risk to crops exists (Figure 5.0).

Piper diagram

It is a description of the research area's groundwater facies. Using the piper diagram, the facies indicate the pre-date and post-monsoon periods. The piper diagram, which shows the major cations and anions, can be used to understand the hydrochemical dynamics of groundwater (Figure 6.0). The three main hydrochemical facies in pre- and post-monsoons are Ca-HCO3, Ca-Mg-HCO3, and Ca-Mg-Cl.

Nitrate (NO₃^2-) health risk assessment

Nitrate contamination of groundwater causes thyroid abnormalities, methemoglobinemia in newborns, and possibly some carcinogenic effects, which are health issues linked to ingesting nitrate (Bahadoran, et al. 2015). The nitrate health risk assessment was chosen to evaluate the potential health impacts on humans.

Risk calculations were performed with all samples with Eqs. 1 and 2 depends on the water consumption of children, teens, and adults. In this investigation, the chronic daily dose (CDD) and hazard quotient (HQ) for nitrate intake through oral water consumption were taken into account. The total health risk assessment was derived from the below equitation (Thomson B, 2007).

CDD _oral=CW × IR × EF × ED/ABW×AT ------------- (1)

HQ= CDD _oral× RfD --------------------- (2)

This equation's explanation is as follows:

CDD Oral CDD refers to the chronic daily dose (mg/kg-day); IR stands for the ingesting ratio; Nitrate concentration in drinking water is represented by Cw (mg/l), exposure frequency is given by EF (years/days), and exposure duration is represented by ED (years); BW stands for a person's body weight in kilograms; The standard dosage for nitrate (1.6 mg/kg-day) is specified by the abbreviations RfD and AT, which stand for average lifetime (years) which is advised in accordance with the USEPA's (United States Environmental Protection Agency) and IRIS's (Integrated Risk Information System's) respective recommendations (Aravinthasamy, et al. 2019;Molagamudi, 2022)

The total hazard quotient for nitrate was computed using Esq. (3)

HQ _oral=CDD/RFD ---------- (3)

Using the overall hazard index and non-carcinogenic risk (THI), the USEPA has set an upper permitted limit (EPA US) (2015). The total hazard health index value is unacceptable if it is more than 1.The percentages of children, men, and women impacted by the pre- and post-monsoon nitrate total hazard index in the study area are 94%, 53%, 37%, and 94%, 51%, 29%, respectively (Table 3&4).

HQ Dermal: By using following equation, the hazard quotient was employed to determine the nitrate health risk through dermal ingestion.

HQ Dermal=Cw × SA × Kp × F × ETs × EF × ED/BW × AT × 1000 -------- (4)

Dermal contact does not have a substantial impact on the targeted area for different groups of people, such as adults, women, and men (Table 3&4).

Sources of ions

Based on the analyzed results scatter and bi-variate plots were portrayed to distinguish the sources and controlling processes for groundwater chemistry. From the result, it is evident that Cl- and NO32- are of anthropogenic sources (Figure 7a&b). And the remaining ions may release into the water by carbonate dissolution and silicate weathering (Figure 7c-e).

Gibbs diagram:

The mechanisms responsible for controlling the groundwater chemistry are studied using Gibbs's diagram. The ratios (1) (Na⁺ + K⁺) / (Na⁺ + K⁺ + Ca²⁺) and (2) Cl^- / (HCO₃^- + Cl^-) were plotted against TDS (Figure 8.0). The area closest to the centre of Gibb's graph has the highest point density both pre and post-monsoons. The dominance of this cluster of points shows the lithological interactions with percolating precipitated water into the sub-surface which is further evaluated by scatter plots (Figure 7e). Hence, it could be concluded that the chief mechanism controlling the chemistry of groundwater in the study area is the rock-water interaction (Gibbs, 1970).

The research analysis explains that the study area groundwater chemistry sequence, cations, and anions, in both monsoons are as follows: Na⁺>Ca²⁺>Mg²⁺>K⁺ and Cl⁻>NO₃²⁻>SO₄²⁻>F⁻and the spatial distribution diagram explains most of the chemical elements are generated in the central and NW-SE direction. The irrigation parameters such as percent sodium and sodium absorption fell in the majorly permissible range in the study area. The piper diagram represents the study area water is Ca-HCO3, Ca-Mg-HCO3, and Ca-Mg-Cl kind of water, moreover, the study area, pre and post-monsoon nitrate total hazard index (children, men and women) affected percentages are 94%, 53%, 37%, and 94%, 51%, 29% respectively, whereas the dermal there is no significant effect on the human body. The ions such as Cl⁻ and NO₃²⁻ are of anthropogenic origin, whereas the remaining ions may be released into the aquifer by carbonate dissolution and silicate weathering and the Gibbs diagram explains the rock water of the study area. The prominent reasons for the study area groundwater contaminated due to the excess usage of fertilizers, and pesticides, dissolution of the mineral deposits (chondrites, and coastal alluvium) due to an increase in the excess of silica, TDS, and hardness may cause the kidney problem in the study. Hence, appropriate water treatment is needed to avoid possible health problems.

Funding information: No funding received

Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Adimalla, N., & Wu, J. (2019). Groundwater quality and associated health risks in a semi-arid region of south India: Implication to sustainable groundwater management. Human and ecological risk assessment: an international journal, 25(1-2), 191-216.
Akhtar, N., Ishak, M.I.S., Ahmad, M.I. et al. (2021). Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review. Water 2021, 13, 905. https://doi.org/ 10.3390/w13070905
Aravinthasamy, P., Karunanidhi, D., Subramani, T., et al. (2019) Fluoride contamination in groundwater of the Shanmuganadhi River Basin (south India) and its association with other chemical constituents using geographical information system and multivariate statistics. Geochemistry. https://doi.org/10.1016/j.chemer.2019.125555
Arveti, N., Golla, V., Yenamala, S. et al. (2017). Assessment of groundwater quality in Gudur area of Andhra Pradesh, South India. Fresenius Environmental Bulletin, 26(5), 3597-3606.
Bahadoran, Z., Mirmiran, P., Ghasemi, A. et al. (2015) Is dietary nitrate/nitrite exposure a risk factor for development of thyroid abnormality? A systematic review and meta-analysis. Nitric Oxide 47:65–76. doi:http://dx.doi.org/10.1016/j.niox.2015.04.002
Balaji, E.,Golla, V., Adimalla, N. et al. (2019). Factors controlling groundwater chemistry of Renigunta area, Chittoor District, Andhra Pradesh, South India: A multivariate statistical approach based on hydrogeochemistry.HydroResearch. doi:10.1016/j.hydres.2019.06.002
Balaji, E., Nagaraju, A.,Sreedhar, Y. et al. Hydrochemical characterization of groundwater in around Tirupati Area, Chittoor District, Andhra Pradesh, South India. Appl Water Sci 7, 1203–1212 (2017). https://doi.org/10.1007/s13201-016-0448-6
Bari, M. L., &Yeasmin, S. (2014). WATER QUALITY ASSESSMENT | Modern Microbiological Techniques. Encyclopedia of Food Microbiology, 755–765. doi:10.1016/b978-0-12-384730-0.00353-0
Bhujangaiah, N.S., & Vasudeva Nayak, (2005). Study of groundwater quality in and around Shimoga city, Karnataka.J.ind.coun.chem. 22(1); 42-47.
US EPA (2015). United States Environmental Protection Agency., Washington, USA National Primary Drinking Water Regulations. http://water.epa.gov/drink/contaminants/upload/mcl-2.pdf. (accessed 7/9/2015)
Etikala, B., Golla, V.,Adimalla, N. et al. (2021). Hydrogeochemical Characterization of Groundwater Using Conventional Graphical, Geospatial and Multivariate Statistical Techniques. In: Adhikary, P.P., Shit, P.K., Santra, P., Bhunia, G.S., Tiwari, A.K., Chaudhary, B.S. (eds) Geostatistics and Geospatial Technologies for Groundwater Resources in India. Springer Hydrogeology. Springer, Cham, 81-96. https://doi.org/10.1007/978-3-030-62397-5_5
Gibbs, R.J. (1970). Mechanisms controlling world water chemistry. Science, 170(3962), 1088-1090.
Golla V., Balaji, E., Arveti N. et al. (2020) Assessment of Groundwater Contamination with Emphasis on Sulfates, Barites Mining Area, Mangampeta, Andhra Pradesh, India. In: Babu K., Rao H., Amarnath Y. (eds) Emerging Trends in Civil Engineering. Lecture Notes in Civil Engineering, vol 61. Springer, Singapore. https://doi.org/10.1007/978-981-15-1404-3_26
Golla, V., Arveti, N., Etikala, B. et al. (2019). Data sets on spatial analysis of hydrogeochemistry of Gudur area, SPSR Nellore district by using inverse distance weighted method in Arc GIS 10.1. Data in brief, 22, 1003-1011.
Golla, V., Badapalli, P. K., &Telkar, S. K. (2021). Delineation of groundwater potential zones in semi-arid regions (Ananatapuram) using geospatial techniques. Materials Today: Proceedings.
Golla, V., Etikala, B., Arveti, N. et al. (2020). Assessment of Groundwater Contamination with Emphasis on Sulfates, Barites Mining Area, Mangampeta, Andhra Pradesh, India. In Emerging Trends in Civil Engineering (pp. 307-322). Springer, Singapore.
Hem, J.D. (1959) Study and interpretations of chemical characteristics of natural water. USGS 2254:263 Water Supply Paper.
Kumar, S.K., Bharani, R., Magesh, N.S. et al. (2014). Hydrogeochemistry and groundwater quality appraisal of part of south Chennai coastal aquifers, Tamil Nadu, India using WQI and fuzzy logic method. Applied Water Science, 4(4), 341-350.
Li, P., & Wu, J. (2019). Drinking Water Quality and Public Health. Expo Health 11, 73–79 (2019). https://doi.org/10.1007/s12403-019-00299-8
Marchand, D., Rayan, M.C., Bethune, D.N. et al. (2002). Groundwater–surface water interaction and nitrate origin in municipal water supply aquifers, Sanjose, Costa Rica
Molagamudi, S.R., Uravakonda, S., Badapalli, P.K. et al. (2022). Evaluation of groundwater chemistry and its impact on drinking, irrigation, and human health hazard risk assessment (HHRA) in Pincha river basin, semi-arid region of Andhra Pradesh, India. Int J Energ Water Res (2022). https://doi.org/10.1007/s42108-021-00170-0
Reddy, C.K.V.C., Golla, V., Badapalli, P.K. et al. (2022). Evaluation of groundwater contamination for fluoride and nitrate in Nellore Urban Province, Southern India: a special emphasis on human health risk assessment (HHRA). Appl Water Sci 12, 32. https://doi.org/10.1007/s13201-021-01537-8
Satyanarayana, G., Ramadasu, P., Padmavathi Devi, P. et al. (2017). Groundwater quality Assessment in Uddanamregion, Costal Srikakulam, Andhra Pradesh, India. IJPDA. 2017; 5(4):116-128.
Todd, D., & Mays, L. (2005) Groundwater Hydrology. 3rd Edition, John Wiley and Sons, Inc., Hoboken, 652 p.
USEPA. (2006). USEPA Region III Risk-based Concentration Table: Technical Background Information. Washington, DC: United States Environmental Protection Agency
WHO (World Health Organization ) (1984) Guidelines for Drinking Water Quality in Health Criteria and Other Supporting Informations. World Health Organization, Geneva. 2, 336.
Wilcox, L. (1955). Classification and use of irrigation waters (No. 969). US Department of Agriculture.

Table 1.0 Physico chemical analysis results of the samples

parameter	Pre- monsoon			Post - monsoon			WHO Limit	Samples exceeding WHO permissible limit
								Pre monsoon	Post monsoon
	MIN	MAX	AVG	MIN	MAX	AVG
pH	5.90	7.90	7.07	5.9	7.9	7.19	7-8	---	---
EC	282	2404	1016.2	245	2000	945.1	1400	11	5
TDS	183.3	1562.6	660.5	159.25	1300	617.2	500	29	31
TA	160	335	256.33	163	342	277.1	200	46	47
TH	213.4	842.90	389.50	118.5	675.10	337.9	200	50	46
Ca²⁺	38	265	87.38	25.65	170	78.0	75	34	36
Mg²⁺	12	83.94	42.16	3.4	78.0	34.8	30	39	29
Na⁺	35	185	95.62	22.99	137.93	59.70	20-200	---	---
K⁺	7	42	13.36	3.9	27.0	13.2	12	13	17
CO₃^_	BDL	BDL	BDL	BDL	BDL	BDL	150	---	---
HCO₃^-	80	533.74	253.23	61.35	577	195.7	150	33	21
Cl ^-	48	343.97	157.43	2.3	326.0	132.6	200	4	4
SO₄^2-	10	87	36.52	11	89	38.06	200	---	---
NO₃-	16	74	42.66	16	77	42.20	45	22	22
F^-	0.19	1.00	0.42	0.24	1.0	0.49	1	---	---
SiO₂	15	57	32.67	21	116	51.73	7.5- 10	50	50
% Na	20.58	50.45	35.69	14.58	58.00	31.86	---	----	---
RSC	-10.06	-0.79	-3.57	-8	0.32	-3.54	---	---	---
SAR	0.82	3.96	2.01	0.49	3.16	1.53	---	---	---
Kelly Ratio	0.22	0.98	0.53	0.12	1.26	0.45

Table 2.0 Pre-monsoon total hazard index of the study area

	NITRATE
	HQ ORAL			HQ DERMAL			THI
	CHILDREN	WOMEN	MEN	CHILDREN	WOMEN	MEN	CHILDREN	WOMEN	MEN
1)	3.26	1.51	1.13	1.16E-02	4.38E-03	3.70E-03	3.27	1.51	1.14
2)	1.86	0.86	0.64	6.60E-03	2.49E-03	2.11E-03	1.86	0.86	0.65
3)	1.35	0.63	0.47	4.80E-03	1.81E-03	1.53E-03	1.35	0.63	0.47
4)	2.42	1.12	0.84	8.60E-03	3.24E-03	2.75E-03	2.43	1.12	0.84
5)	1.58	0.73	0.55	5.60E-03	2.11E-03	1.79E-03	1.58	0.73	0.55
6)	2.42	1.12	0.84	8.60E-03	3.24E-03	2.75E-03	2.43	1.12	0.84
7)	1.58	0.73	0.55	5.60E-03	2.11E-03	1.79E-03	1.58	0.73	0.55
8)	2.91	1.35	1.01	1.04E-02	3.91E-03	3.31E-03	2.93	1.35	1.02
9)	0.96	0.44	0.33	3.40E-03	1.28E-03	1.09E-03	0.96	0.44	0.33
10)	1.86	0.86	0.64	6.60E-03	2.49E-03	2.11E-03	1.86	0.86	0.65
11)	0.90	0.42	0.31	3.20E-03	1.21E-03	1.02E-03	0.90	0.42	0.31
12)	2.99	1.39	1.04	6.55E-03	2.47E-03	2.06E-03	3.00	1.39	1.04
13)	1.41	0.65	0.49	2.22E-03	8.38E-04	6.88E-04	1.41	0.65	0.49
14)	1.46	0.68	0.51	1.81E-03	6.82E-04	5.52E-04	1.46	0.68	0.51
15)	2.93	1.35	1.02	2.97E-03	1.12E-03	8.94E-04	2.93	1.36	1.02
16)	2.76	1.28	0.96	2.38E-03	8.97E-04	7.05E-04	2.76	1.28	0.96
17)	3.15	1.46	1.09	2.36E-03	8.90E-04	6.89E-04	3.15	1.46	1.09
18)	3.43	1.59	1.19	2.27E-03	8.56E-04	6.54E-04	3.43	1.59	1.19
19)	1.86	0.86	0.64	1.10E-03	4.15E-04	3.13E-04	1.86	0.86	0.64
20)	1.91	0.89	0.66	1.03E-03	3.87E-04	2.88E-04	1.91	0.89	0.66
21)	1.65	0.77	0.57	8.11E-04	3.06E-04	2.24E-04	1.66	0.77	0.57
22)	1.86	0.86	0.64	8.38E-04	3.16E-04	2.29E-04	1.86	0.86	0.64
23)	1.52	0.70	0.53	6.35E-04	2.40E-04	1.71E-04	1.52	0.70	0.53
24)	1.41	0.65	0.49	5.48E-04	2.07E-04	1.46E-04	1.41	0.65	0.49
25)	1.97	0.91	0.68	7.18E-04	2.71E-04	1.89E-04	1.97	0.91	0.68
26)	2.68	1.24	0.93	9.18E-04	3.46E-04	2.38E-04	2.68	1.24	0.93
27)	3.09	1.43	1.07	1.00E-03	3.77E-04	2.56E-04	3.09	1.43	1.07
28)	2.99	1.39	1.04	9.16E-04	3.45E-04	2.32E-04	2.99	1.39	1.04
29)	1.35	0.63	0.47	3.92E-04	1.48E-04	9.80E-05	1.35	0.63	0.47
30)	3.04	1.41	1.05	8.39E-04	3.16E-04	2.07E-04	3.04	1.41	1.05
31)	3.66	1.69	1.27	9.63E-04	3.63E-04	2.35E-04	3.66	1.69	1.27
32)	1.24	0.57	0.43	3.12E-04	1.18E-04	7.52E-05	1.24	0.57	0.43
33)	2.70	1.25	0.94	6.51E-04	2.46E-04	1.55E-04	2.70	1.25	0.94
34)	2.53	1.17	0.88	5.85E-04	2.21E-04	1.38E-04	2.53	1.17	0.88
35)	2.14	0.99	0.74	4.75E-04	1.79E-04	1.11E-04	2.14	0.99	0.74
36)	3.32	1.54	1.15	7.10E-04	2.68E-04	1.64E-04	3.32	1.54	1.15
37)	2.14	0.99	0.74	4.41E-04	1.66E-04	1.00E-04	2.14	0.99	0.74
38)	1.18	0.55	0.41	2.35E-04	8.86E-05	5.30E-05	1.18	0.55	0.41
39)	3.09	1.43	1.07	5.95E-04	2.24E-04	1.33E-04	3.09	1.43	1.07
40)	1.86	0.86	0.64	3.45E-04	1.30E-04	7.62E-05	1.86	0.86	0.64
41)	1.97	0.91	0.68	3.54E-04	1.34E-04	7.74E-05	1.97	0.91	0.68
42)	3.66	1.69	1.27	6.38E-04	2.41E-04	1.38E-04	3.66	1.69	1.27
43)	3.31	1.53	1.15	5.60E-04	2.11E-04	1.20E-04	3.31	1.53	1.15
44)	3.55	1.64	1.23	5.83E-04	2.20E-04	1.23E-04	3.55	1.64	1.23
45)	4.16	1.93	1.45	6.65E-04	2.51E-04	1.39E-04	4.16	1.93	1.45
46)	3.09	1.43	1.07	4.81E-04	1.81E-04	9.98E-05	3.09	1.43	1.07
47)	3.26	1.51	1.13	4.94E-04	1.86E-04	1.01E-04	3.26	1.51	1.13
48)	3.38	1.56	1.17	4.97E-04	1.88E-04	1.01E-04	3.38	1.56	1.17
49)	2.48	1.15	0.86	3.56E-04	1.34E-04	7.16E-05	2.48	1.15	0.86
50)	2.48	1.15	0.86	3.47E-04	1.31E-04	6.92E-05	2.48	1.15	0.86
51)	0.90	0.42	0.31	3.20E-03	1.21E-03	1.02E-03	0.90	0.42	0.31
MIN	0.90	0.42	0.31	2.35E-04	8.86E-05	5.30E-05	0.90	0.42	0.31
MAX	4.16	1.93	1.45	1.16E-02	4.38E-03	3.70E-03	4.16	1.93	1.45
AVG	2.36	1.09	0.82	2.33E-03	8.78E-04	7.07E-04	2.37	1.10	0.82
AFFECTED%	94%	53%	37%	0%	0%	0%	94%	53%	37%

Table 3.0 Post monsoon total hazard index of the study area

	NITRATE
	HQ ORAL			HQ DERMAL			THI
	CHILDREN	WOMEN	MEN	CHILDREN	WOMEN	MEN	CHILDREN	WOMEN	MEN
	3.07	1.42	1.07	1.09E-02	4.12E-03	3.49E-03	3.08	1.43	1.07
	1.73	0.80	0.60	6.16E-03	2.32E-03	1.97E-03	1.74	0.80	0.60
	1.35	0.63	0.47	4.80E-03	1.81E-03	1.53E-03	1.35	0.63	0.47
	2.42	1.12	0.84	8.60E-03	3.24E-03	2.75E-03	2.43	1.12	0.84
	1.58	0.73	0.55	5.60E-03	2.11E-03	1.79E-03	1.58	0.73	0.55
	2.42	1.12	0.84	8.60E-03	3.24E-03	2.75E-03	2.43	1.12	0.84
	1.58	0.73	0.55	5.60E-03	2.11E-03	1.79E-03	1.58	0.73	0.55
	2.76	1.28	0.96	9.80E-03	3.70E-03	3.13E-03	2.77	1.28	0.96
	0.96	0.44	0.33	3.40E-03	1.28E-03	1.09E-03	0.96	0.44	0.33
	1.73	0.80	0.60	6.16E-03	2.32E-03	1.97E-03	1.74	0.80	0.60
	0.90	0.42	0.31	3.20E-03	1.21E-03	1.02E-03	0.90	0.42	0.31
	1.73	0.80	0.60	3.79E-03	1.43E-03	1.19E-03	1.74	0.80	0.60
	1.41	0.65	0.49	2.22E-03	8.38E-04	6.88E-04	1.41	0.65	0.49
	1.46	0.68	0.51	1.81E-03	6.82E-04	5.52E-04	1.46	0.68	0.51
	2.93	1.35	1.02	2.97E-03	1.12E-03	8.94E-04	2.93	1.36	1.02
	2.76	1.28	0.96	2.38E-03	8.97E-04	7.05E-04	2.76	1.28	0.96
	3.15	1.46	1.09	2.36E-03	8.90E-04	6.89E-04	3.15	1.46	1.09
	3.07	1.42	1.07	2.03E-03	7.67E-04	5.86E-04	3.07	1.42	1.07
	1.65	0.77	0.57	9.80E-04	3.70E-04	2.79E-04	1.66	0.77	0.57
	1.91	0.89	0.66	1.03E-03	3.87E-04	2.88E-04	1.91	0.89	0.66
	1.97	0.91	0.68	9.66E-04	3.64E-04	2.67E-04	1.97	0.91	0.68
	1.86	0.86	0.64	8.38E-04	3.16E-04	2.29E-04	1.86	0.86	0.64
	1.52	0.70	0.53	6.35E-04	2.40E-04	1.71E-04	1.52	0.70	0.53
	1.41	0.65	0.49	5.48E-04	2.07E-04	1.46E-04	1.41	0.65	0.49
	2.36	1.09	0.82	8.62E-04	3.25E-04	2.26E-04	2.36	1.09	0.82
	2.76	1.28	0.96	9.45E-04	3.57E-04	2.45E-04	2.76	1.28	0.96
	3.09	1.43	1.07	1.00E-03	3.77E-04	2.56E-04	3.09	1.43	1.07
	3.15	1.46	1.09	9.63E-04	3.63E-04	2.44E-04	3.15	1.46	1.09
	1.35	0.63	0.47	3.92E-04	1.48E-04	9.80E-05	1.35	0.63	0.47
	2.55	1.18	0.89	7.05E-04	2.66E-04	1.74E-04	2.55	1.18	0.89
	1.81	0.84	0.63	4.77E-04	1.80E-04	1.16E-04	1.81	0.84	0.63
	1.24	0.57	0.43	3.12E-04	1.18E-04	7.52E-05	1.24	0.57	0.43
	2.70	1.25	0.94	6.51E-04	2.46E-04	1.55E-04	2.70	1.25	0.94
	2.53	1.17	0.88	5.85E-04	2.21E-04	1.38E-04	2.53	1.17	0.88
	2.14	0.99	0.74	4.75E-04	1.79E-04	1.11E-04	2.14	0.99	0.74
	3.32	1.54	1.15	7.10E-04	2.68E-04	1.64E-04	3.32	1.54	1.15
	2.14	0.99	0.74	4.41E-04	1.66E-04	1.00E-04	2.14	0.99	0.74
	1.18	0.55	0.41	2.35E-04	8.86E-05	5.30E-05	1.18	0.55	0.41
	3.09	1.43	1.07	5.95E-04	2.24E-04	1.33E-04	3.09	1.43	1.07
	1.86	0.86	0.64	3.45E-04	1.30E-04	7.62E-05	1.86	0.86	0.64
	2.08	0.96	0.72	3.75E-04	1.41E-04	8.18E-05	2.08	0.96	0.72
	3.83	1.77	1.33	6.67E-04	2.52E-04	1.44E-04	3.83	1.77	1.33
	3.99	1.85	1.39	6.76E-04	2.55E-04	1.45E-04	3.99	1.85	1.39
	4.10	1.90	1.42	6.74E-04	2.54E-04	1.43E-04	4.10	1.90	1.42
	4.33	2.01	1.50	6.92E-04	2.61E-04	1.45E-04	4.33	2.01	1.50
	3.15	1.46	1.09	4.90E-04	1.85E-04	1.02E-04	3.15	1.46	1.09
	3.43	1.59	1.19	5.19E-04	1.96E-04	1.07E-04	3.43	1.59	1.19
	3.49	1.61	1.21	5.14E-04	1.94E-04	1.05E-04	3.49	1.61	1.21
	2.59	1.20	0.90	3.72E-04	1.40E-04	7.49E-05	2.59	1.20	0.90
	2.64	1.22	0.92	3.70E-04	1.40E-04	7.39E-05	2.64	1.22	0.92
	0.90	0.42	0.31	3.20E-03	1.21E-03	1.02E-03	0.90	0.42	0.31
MIN	0.90	0.42	0.31	2.35E-04	8.86E-05	5.30E-05	0.90	0.42	0.31
MAX	4.33	2.01	1.50	1.09E-02	4.12E-03	3.49E-03	4.33	2.01	1.50
AVG	2.34	1.08	0.81	2.23E-03	8.41E-04	6.75E-04	2.34	1.08	0.81
AFFECTED%	94%	51%	29%	0%	0%	0%	94%	51%	29%

No competing interests reported.

Groundwater quality assessment for drinking, irrigation, and human health hazards with special emphasis on Nitrate pollution in Uddanam area, Srikakulam district of Andhra Pradesh, India

Status:

Version 1

Abstract

Figures

Introduction

Materials And Methodology

Result And Discussion

Conclusions

Declarations

References

Tables

Additional Declarations

Status:

Version 1