Abstract
Nitrate is a common contaminant of drinking water. Due to its adverse health effects, this study aimed to determine nitrate levels in six southern districts of Tehran. A total of 148 samples were taken from tap waters. In 84.46% (n = 125) of the samples, the nitrate concentration was below national and WHO limits (50 mg/L); however, 15.54% (n = 23) were in violation of the criteria. The total mean concentration of nitrate was 36.15 mg/L (±14.74) ranging from 4.52 to 80.83 mg/L. The overall hazard quotient (HQ) for age groups were ordered as Children (1.71) > Infants (1.24) > Teenagers (1.2) > Adults (0.96). In all districts, the HQ values for infants and children groups were greater than 1, indicating potential adverse health risks. In teenagers age group, only the HQ estimations of districts 10 (HQ = 0.93) and 11 (HQ = 0.74) were lower than 1 and in adults age group, the estimated HQ values for districts were lower than 1 with the exception for district 19 (HQ = 1.19). The sensitivity analysis (SA) showed that nitrate content plays a major role in the value of the assessed risk.
HIGHLIGHTS
Levels and noncarcinogenic risk of nitrate were assessed in tap water.
The mean concentration of nitrate was 36.15 mg/L.
Analysis showed that nitrate concentration in 84.46% of the samples was below the standard level limit.
The highest noncarcinogenic risk was in the children group.
The 95th percentile of the simulated nitrate HQ in children was 2.14.
Graphical Abstract
INTRODUCTION
Water is an irreplaceable, essential need for the survival of the human civilization (Biglari et al. 2016). It is estimated that over one-third of the world's available freshwater is used for different purposes, such as agriculture, industry and domestic applications (Mahvi et al. 2005; Nouri et al. 2008; Atafar et al. 2010). With the rapid population growth and the impact of stressors such as increased drought periods and climate change, providing safe and accessible water has become a significant challenge in the twenty-first century (Radfard et al. 2018). Moreover, with regard to the estimation of the United Nations, one in four people may experience water shortage by 2050. The importance of clean water has also been reflected in the United Nations sixth goal of the 2030 Sustainable Development plan (Schwarzenbach et al. 2010; Patel et al. 2020; United Nations 2021). The quality of the consumed water is highly dependent on the characteristics of the source (Lowe et al. 2021). To provide high-quality drinking water and ensure its safety, regulations have been established setting maximum permissible levels for various water contaminants (Patel et al. 2020). Nitrate is one of the most prevalent contaminants found in the water (Khaniki et al. 2008). This is due to its high solubility, mobility and nonreactivity under oxidizing conditions (Ghalhari et al. 2021). Pollution of groundwater or surface waters to nitrate can majorly be traced back to human activities such as the application of organic and inorganic fertilizers and generation of organic wastes by humans, livestock and the food industry (Rezvani Ghalhari et al. 2021a). It might also have a natural origin (i.e. organic nitrogen mineralization in the soil) (Zendehbad et al. 2019). The removal of nitrate from a contaminated source such as an aquifer is carried out using technologies such as adsorption (Yousefi et al. 2016), ion exchange (Shahbazi et al. 2010), physical approaches (Hosseini & Mahvi 2018) and dilution by other water resources (Wollheim et al. 2017), which were difficult and costly. However, in a number of studies, it is suggested that the discharge of wastewater containing nitrate can degrade water quality and thus make it unsuitable to use as potable water via methods such as desalination and industrial applications (Panagopoulos 2020, 2021, 2022). Therefore, the emphasis should be more on preventive measures (Qasemi et al. 2018a). The chief concern with nitrate and nitrite is the inordinate amounts that enter the body via diet or drinking water. The amount of intake from drinking water is usually low compared to foodstuff; however, it may significantly increase via drinking in case of contamination (Sadler et al. 2016; Qasemi et al. 2018a).
Epidemiological studies associate nitrate with health concerns such as congenital disabilities, complications such as small for gestational age (SGA), thyroid disorder, increased risk of abortion and various types of cancer (Gholami et al. 2019; Temkin et al. 2019). A severe adverse outcome of nitrate consumption via drinking water is infant methemoglobinemia or blue baby syndrome, which decreases the oxygen carrying capacity of red blood cells by disrupting their binding reaction with oxygen molecules (Mortada & Shokeir 2018; Hosseini et al. 2021). According to the international organizations such as the International Agency for Cancer Research (IARC), nitrate and nitrite are probable carcinogens when their consumption prompts the formation of N-nitroso compounds, which induce cancer and thus subject to regulations (Mortada & Shokeir 2018; Qasemi et al. 2018b; Messier et al. 2019; Temkin et al. 2019). The World Health Organization (WHO) and Iranian national standard maximum limits for nitrate are 50 mg/L (Khaniki et al. 2008). Tehran is a megacity hosting over 8.5 million people and since the 1990s, it faced challenges such as rapid urbanization, increased population, increased agricultural and industrial activity and postponed wastewater collection network, which have served to compromise the quality of its water resources especially groundwater where one-third of the drinking water demand of the city is supplied (Khorasani et al. 2020; Sarmadi et al. 2021).
Studies report that despite constant regulation and monitoring in most countries, the nitrate levels in drinking water frequently exceed the permissible limits (Picetti et al. 2022). In fact, in a study by Sherris Allison et al. (2021), it was stated as a leading cause of water quality regulation violations in California, United States (Sherris Allison et al. 2021). On the other hand, establishing a historical record on nitrate concentration and human health risk assessment is essential for both the public and the authorities, as well as providing data and findings for developing research (Omonona & Okogbue 2021; Sherris Allison et al. 2021; Picetti et al. 2022). The health implication of nitrate becomes more pronounced as more research projects focus on the outcomes of dietary nitrate exposure (Taneja et al. 2019; Hosseini et al. 2021; Picetti et al. 2022). What's more, it was stated that between 2011 and 2016, 50% of the groundwater in Tehran aquifer was refilled via untreated wastewater discharge while at the same time, 47% of its water withdrawal was used for drinking (Khorasani et al. 2020). It was been indicated that nitrate concentration greater than 1 mg/L indicates contamination (Hamed et al. 2012). Therefore, with regard to the mentioned issues and the lack of research on nitrate levels in the drinking water network of Tehran in recent years, the aim of this study is to determine nitrate concentrations at the consumption point (i.e. tap water) in the southern region of Tehran megacity and assess the probable health risk using the USEPA risk assessment method.
METHODS
Study area
Coordinated in 35.7117 °N 51.4070 °E, Tehran province is located in the southern slope of the Alborz Mountain chain. It has a semi-arid climate and has an altitude varying from 1,050 and 1,200 m to 1,800 m in southern, central and northern regions, respectively. The annual temperature varies from 42 °C to −12 °C. Tehran province has an area of 730 km2 and 8,737,510 residents, of which 1,530,122 people live in the southern region where the sampling was conducted. This region includes districts 10, 11, 16, 17, 19 and Aftab district. The drinking water of Tehran is supplied from both ground water (40%) and surface water (60%) via Tehran-Karaj Aquifer and Karaj, Latian and Lar dams, respectively (Khorasani et al. 2020; Sarmadi et al. 2021).
Data collection
The municipal tap water was sampled in 148 spots in districts 10, 11, 16, 17, 19 and Aftab District (Figure 1). Next, the samples were transported to the laboratory for analysis, and nitrate concentration was analyzed using a UV-Vis spectrophotometer (DR-5000). All procedures were conducted according to Standard Methods for Water and Wastewater Analysis and were done in triplicates.
Health risk assessment
Parameters used in nitrate health risk assessment and their corresponding reference values
Parameters . | Symbols . | Units . | Infants . | Children . | Teenagers . | Adults . | Reference . |
---|---|---|---|---|---|---|---|
Age | – | Year | <2 | 2–6 | 6–16 | >16 | Gholami et al. (2019), Qasemi et al. (2018b), Rezvani Ghalhari et al. (2021b), Wang et al. (2021), Radfarda et al. (2019) |
Nitrate concentration | CN | mg/L | – | – | – | ||
Exposure duration | ED | Year | 0.5 | 6 | 13 | 40 | |
Exposure frequency | EF | day/year | 365 | 365 | 365 | 365 | |
Daily consumption | Cd | L/day | 0.3 | 0.85 | 2 | 2.5 | |
Body weight | BW | kg | 10 | 15 | 50 | 78 | |
Average time | AT | day | 182.5 | 2,190 | 4,745 | 14,600 | |
Oral reference dose | RFD | 1.6 | 1.6 | 1.6 | 1.6 | 1.6 |
Parameters . | Symbols . | Units . | Infants . | Children . | Teenagers . | Adults . | Reference . |
---|---|---|---|---|---|---|---|
Age | – | Year | <2 | 2–6 | 6–16 | >16 | Gholami et al. (2019), Qasemi et al. (2018b), Rezvani Ghalhari et al. (2021b), Wang et al. (2021), Radfarda et al. (2019) |
Nitrate concentration | CN | mg/L | – | – | – | ||
Exposure duration | ED | Year | 0.5 | 6 | 13 | 40 | |
Exposure frequency | EF | day/year | 365 | 365 | 365 | 365 | |
Daily consumption | Cd | L/day | 0.3 | 0.85 | 2 | 2.5 | |
Body weight | BW | kg | 10 | 15 | 50 | 78 | |
Average time | AT | day | 182.5 | 2,190 | 4,745 | 14,600 | |
Oral reference dose | RFD | 1.6 | 1.6 | 1.6 | 1.6 | 1.6 |
An HQ value less than 1 indicates that no adverse health effects may occur due to exposure to the reported pollutant, whereas an HQ value greater than 1 suggests potential adverse noncarcinogenic health effects may incur upon exposure (Raza et al. 2017; Kalteh et al. 2020).
Uncertainty analysis
According to USEPA guidelines, the obtained point estimate is not a suitable representative of the situation due to uncertainty issues (Bazeli et al. 2020). Therefore, a Monte–Carlo Simulation was carried out using Oracle Crystal Ball to address the uncertainty that might be caused by various factors and to provide an upper confidence limit (UCL). This was then followed by a sensitivity analysis (SA) to determine the contribution of each parameter involved in the analysis.
RESULTS
Nitrate concentration
In this study, the concentration of nitrate was determined in six districts located in the south of Tehran megacity. The samples were taken from tap waters connected to the municipal drinking water distribution networks at different spots (n = 148). Overall, the results of the spectrophotometer analysis showed that out of 148 samples, in 23 samples (% = 15.54) nitrate levels were in violation of national and WHO standards (50 mg/L) while in the rest of the samples, counting 125 samples (% = 84.46), the nitrate levels were below the limit. Moreover, the number of samples violating the national and WHO standard per district was in the following order: Aftab District (n = 11) > District 19 (n = 7) > District 16 (n = 4) > District 17 (n = 1). In districts 10 and 11, no exceeding nitrate levels were observed. Table 2 shows the overall and district-wise descriptive details of the study. According to Table 2, the concentration of nitrate across all the studied areas ranged from 4.52 (observed in district 19) to 80.83 mg/L (observed in Aftab district) with a total mean concentration of 36.15 (±14.74) mg/L. From highest to the lowest mean concentration of nitrate, the districts were ordered as District 19 (44.86 ± 13.67) > Aftab District (37.32 ± 16.33) > District 16 (37.26 ± 15.09) > District 17 (34.51 ± 10.61) > District 11 (27.95 ± 4.56) > District 10 (22.32 ± 2.44). Figure 2 shows the spatial distribution of nitrate across the studied area. The concentration gradient is colored from high (red) to low (green) concentrations.
Nitrate concentration in the studied districts
Districts . | Number of samples . | Exceeding the limita (%) . | Min (mg/L) . | Max (mg/L) . | Mean (mg/L) . | (±SD) . |
---|---|---|---|---|---|---|
10 | 13 | 0 (0) | 22.06 | 33.87 | 27.95 | 4.56 |
11 | 10 | 0 (0) | 18.96 | 25.96 | 22.32 | 2.44 |
16 | 26 | 4 (15) | 15.90 | 64.51 | 37.26 | 15.09 |
17 | 18 | 1 (6) | 20.37 | 64.00 | 34.51 | 10.61 |
19 | 20 | 7 (35) | 4.52 | 65.25 | 44.86 | 13.67 |
Aftaab | 61 | 11 (18) | 4.87 | 80.83 | 37.32 | 16.33 |
Total | 148 | 23 (15.54) | 4.52 | 80.83 | 36.15 | 14.74 |
Districts . | Number of samples . | Exceeding the limita (%) . | Min (mg/L) . | Max (mg/L) . | Mean (mg/L) . | (±SD) . |
---|---|---|---|---|---|---|
10 | 13 | 0 (0) | 22.06 | 33.87 | 27.95 | 4.56 |
11 | 10 | 0 (0) | 18.96 | 25.96 | 22.32 | 2.44 |
16 | 26 | 4 (15) | 15.90 | 64.51 | 37.26 | 15.09 |
17 | 18 | 1 (6) | 20.37 | 64.00 | 34.51 | 10.61 |
19 | 20 | 7 (35) | 4.52 | 65.25 | 44.86 | 13.67 |
Aftaab | 61 | 11 (18) | 4.87 | 80.83 | 37.32 | 16.33 |
Total | 148 | 23 (15.54) | 4.52 | 80.83 | 36.15 | 14.74 |
aWHO permissible limit :50 mg/L.
Spatial distribution of nitrate in southern districts of Tehran. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/wrd.2022.007.
Spatial distribution of nitrate in southern districts of Tehran. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/wrd.2022.007.
Health risk assessment
With regard to the health implications of nitrate in drinking water, a human health risk assessment was conducted for infants, children, teenagers and adult age groups according to the USEPA methodology detailed in the previous section. Using this method, the dietary health risk of nitrate was assessed and was presented in Figure 3. The overall point estimate HQ values for infants, children, teenagers and adults were 1.18, 1.28, 0.9 and 0.72, respectively. The HQ values for infant and children age groups were above 1 indicating high potential adverse dietary health risks due to nitrate. Additionally, obtaining the point estimates of HQ for each district shows that infants and children might be at potential health risk in districts 16, 17, 19 and Aftab as the point estimate HQ value in those districts were greater than 1. Moreover, the health risk is more pronounced in district 19 as the point estimated HQ value for teenagers was greater than 1 as well. Lastly, the HQ point estimates in districts 10 and 11 were lower than 1 indicating no risks (Figure 3).
Point estimate HQs and their corresponding upper confidence limit (P95) estimations for the studied districts.
Point estimate HQs and their corresponding upper confidence limit (P95) estimations for the studied districts.
After obtaining the point estimate, MCSs were run using Oracle Crystal Ball to obtain the UCLs for the estimate HQs. The results of MSCs are presented in Figure 3. According to the figure, it was found that the total obtained UCL for the infants, children, teenagers and adults were 1.24, 1.71, 1.20 and 0.96, respectively. This means that all groups except adults were at the potential noncarcinogenic health risk. Running the analysis for districts individually showed that infants and children were at the risk (HQ > 1) in all districts. Followed by that, the teenagers’ age group living in districts 16, 17, 19 and Aftab were also found to be at risk as well as the adults living in district 19. The overall MCS charts for the studied age groups are presented in Figure 4. In the health risk assessment, each parameter can have an independent and synergic effect on the evaluated health risk and determination of the role of each parameter can be conducive to risk mitigation efforts. Therefore, an SA was run to define the contribution of various parameters at play. As shown in Figure 5, it was found that nitrate concentration plays the main role on the imposed risk for all age groups, and more than 85% of the estimated risk was related to nitrate concentration. The tornado plots (Figure 5) shows that BW has a negative effect on the increasing assessed risk, and between the same age group with different weight, the probable risk in the persons with a higher weight are less than the persons with low weight. Additionally, it was found that IR can increase risk as it can increase the amount of nitrate entering the body.
Uncertainty analysis histograms of HQ in infants (a), children (b), teenagers (c) and adults (d) which exposed to nitrate.
Uncertainty analysis histograms of HQ in infants (a), children (b), teenagers (c) and adults (d) which exposed to nitrate.
Sensitivity analysis results for infants (a), children (b), teenagers (c) and adults (d) age groups.
Sensitivity analysis results for infants (a), children (b), teenagers (c) and adults (d) age groups.
DISCUSSION
Providing safe and high-quality drinking water for consumers is an imperative constant necessity as it might undermine population health. Therefore, monitoring contaminant levels such as nitrate in the water is subject to national and international regulations and health-related research (Królak & Raczuk 2018). In this study, the concentration of nitrate in 148 sampling spots within the municipal drinking water network of six districts located at the southern Tehran megacity was quantified according to Standard Methods for Water and Wastewater analysis in order to evaluate the water safety for consumers. Additionally, an HRA was conducted to assess the noncarcinogenic dietary health risks of nitrate. Comparison of nitrate levels of the samples with national and WHO permissible limits for nitrate showed that in the majority of the samples (n = 125, 84.46%), the nitrate concentration was below national and WHO limits; however, the levels in the rest of the samples (n = 23, 15.54%) were in violation of WHO and national criteria indicating the lack of safety for the consumers. Also, the total mean concentration of nitrate was 36.15 (±14.74) and sample concentrations ranged from 4.52 to 80.83 mg/L. Moreover, the highest mean concentrations of nitrate and the highest above-standard samples were found in Aftab and District 19. This might be due to the low depth of wells in District 19 and Aftab district compared to other districts which might increase the seepage of raw wastewater discharge into the groundwater resources (Khorasani et al. 2020). A study by Khorasani et al. (2020) found that between 2011 and 2016, 50% of the untreated wastewater has seeped into Tehran's groundwater resources while 47% of the withdrawn water was used for drinking. In that study, it was also stated that due to the hybrid use of surface and groundwater in the drinking water distribution network, the nitrate was diluted to levels lower than the standard (50 mg/L) (Khorasani et al. 2020). The nitrate levels of this work were also higher than the measurements by Shirazi et al. (2021). They investigated nitrate and nitrite levels in five random areas of Tehran city and found that the highest nitrate levels were observed in the western sampling sites of Tehran (4.6 ± 0.02 mg/L) which was lower than levels found in this study (Haji Seyed Mohammad Shirazi et al. 2021).
Comparing the observed mean concentration in this work with other recent similar studies conducted in Iran shows that despite being lower than WHO and national standards, the mean concentration of nitrate was higher than a number of studies carried out in other cities and provinces of Iran (Table 3). These include studies that were carried out in Ilam, Behbahan, Mashhad, Sanandaj and Semnan cities (Gholami et al. 2019; Heidariyeh et al. 2019; Oftadeh et al. 2019; Rezaei et al. 2019; Badeenezhad et al. 2021); a study in rural and urban areas of Isfahan province during spring and summer seasons (Aghapour et al. 2021); a study on drinking water nitrate in five southwest provinces of Iran (i.e. Ilam, Bushehr, Khuzestan, Fars and Lorestan provinces) (Jaafarzadeh et al. 2022). Additionally, the mean nitrate concentration in this work was higher than samples taken from wells in Hormozgan province, Kazerun city, Divandareh county, Gonabad and Bajestan (Bay et al. 2018; Qasemi et al. 2018a; Golaki et al. 2022; Mohammadpour et al. 2022); studies on the occurrence of nitrate in bottled water by Alimohammadi et al. (2018) and Rezvani Ghalhari et al. (2021b). However, the mean nitrate concentration of this study was lower than the mean levels quantified during the autumn and winter sampling periods in the study of Aghapour et al. (2021) in Isfahan province and the mean level in Shiraz city by Jaafarzadeh et al. (2022) (Aghapour et al. 2021; Jaafarzadeh et al. 2022). This suggests that the water quality of southern Tehran has lower quality compared to other cities and regions in Iran in terms of nitrate concentration.
Comparison of the nitrate levels determined in this work with other similar studies
No. . | Author . | Year . | Location . | No. of samples . | Sampling details . | Mean ± SD (mg/L) . | Reference . | |
---|---|---|---|---|---|---|---|---|
Studies in Iran | This study | 2022 | Tehran | 148 | Tap water | 36.15 ± 14.74 | – | |
Shirazi et al. | 2021 | West of Tehran | – | Tap water | 4.6 ± 0.02 | Haji Seyed Mohammad Shirazi et al. (2021) | ||
Panahi et al. | 2012 | Robat-Karim city | 40 (wells) | Well, Tap water | 2.1 | Panahi & Alavi Moghaddam (2012) | ||
32 (tap water | 2.05 | |||||||
Gholami et al. | 2019 | Ilam city | 77 | Tap water | 8.13 ± 5.4 | Gholami et al. (2019) | ||
Badeenezhad et al. | 2021 | Behbahan city | 90 | Tap water | 15.05 High rain season | Badeenezhad et al. (2021) | ||
13.35 Low rain season | ||||||||
Oftadeh et al. | 2019 | Mashhad city | 72 | Tap water | 16.63 ± 10.88 | Oftadeh et al. (2019) | ||
Rezvani et al. | 2021 | Kashan city | 20 | Bottled water | 8.37 ± 7.32 | Rezvani Ghalhari et al. (2021b) | ||
Mohammadpour et al. | 2022 | Hormozgan Province | 54 | Well | 7.37 ± 5.61 | Mohammadpour et al. (2022) | ||
Rezaei et al. | 2018 | Sanandaj city | 106 | Tap water | From 0.28 to 27.77 urban | Rezaei et al. (2019) | ||
From 1.28 to 80 rural | ||||||||
Golaki et al. | 2022 | Kazerun, Fars province | 25 | Well | 13.5 | Golaki et al. (2022) | ||
Bay et al. | 2018 | Divandareh county, Kurdistan province | 118 | Well | 31.37 ± 18.87 | Bay et al. (2018) | ||
Aghapour et al. | 2021 | Isfahan province | Spring = 287 rural, 113 urban | 1,178 Tap water samples 90 Spring samples 51 ghanat samples | Spring = 32.59 ± 24.96 rural, 30.15 ± 18.34 urban | Aghapour et al. (2021) | ||
Summer = 285 rural, 139 urban | Summer = 33 ± 22.34 rural, 37.2 ± 30.14 urban | |||||||
Autumn = 89 rural, 71 urban | Fall = 46.51 ± 25.68 rural, 47.98 ± 42.46 urban | |||||||
Winter = 230 rural, 105 urban | Winter = 33.45 ± 23.27 rural, 40.15 ± 34.29 urban | |||||||
Bazeli et al. | 2020 | Khaf county, | 28 | Well | 1.54 | Bazeli et al. (2020) | ||
Alimohammadi et al. | 2018 | Iran | 71 | Bottled water | 10.55 | Alimohammadi et al. (2018) | ||
Jaafarzadeh et al. | 2022 | Ilam, Bushehr, Khuzestan, Fars and Lorestan provinces | – | Drinking water | Ilam = 14.58 ± 2.62 Bushehr = 9.97 ± 3.14 Khuzestan = 52.77 ± 19.15 Fars = 64.63 ± 19.92 Lorestan = 22.85 ± 6.91 | Jaafarzadeh et al. (2022) | ||
Heidariyeh et al. | 2019 | Semnan city | 30 (tap water) 150 (bottled water) | Tap water | 7.27 ± 5.1 | Heidariyeh et al. (2019) | ||
Qasemi et al. | 2018 | Gonabad and Bajestan, | 18 (Gonabad) | Well | 29.33 ± 18.62 | Qasemi et al. (2018a) | ||
21 (Bajestan) | 37.95 ± 20.37 | |||||||
Studies worldwide | Mortada and Shokeir | 2018 | Dakahlia governorate, Egypt | 1291 | Tap water | 5.25 ± 1.61 | Mortada & Shokeir (2018) | |
Van den brand et al. | 2019 | Dutch regions, Netherland | 185 | Tap water | 4.7 | van den Brand et al. (2020) | ||
Wedyan et al. | 2021 | Northeast Jordan | – | Well | 44.4 | Wedyan et al. (2021) | ||
Adimalla | 2019 | Telangana province, India | 35 | Well | 58.74 | Adimalla et al. (2019) | ||
Adimalla | 2021 | Nirmal Province, India | 30 | Well | 43.30 ± 16.88 | Adimalla & Qian (2021) | ||
Taneja et al. | 2017 | Nagpur and Bhandara districts, India | 77 | Tap water | Rural = 45.69 ± 2.08 Urban = 22.53 ± 1.97 | Taneja et al. (2019) | ||
Ahada et al. | 2018 | Punjab, India | 76 | Well | 118.23 ± 33.45 | Ahada & Suthar (2018) | ||
Wang et al. | 2021 | Zhangjiakou, China | 489 | Well | 29.72 | Wang et al. (2021) | ||
Hu et al. | 2021 | Wanbei, China | 11 | Well | 24.01 | Hu et al. (2021) | ||
Barakat et al. | 2020 | Tadla, Morocco | 21 | Well | 24.73 ± 15.49 | Barakat et al. (2020) | ||
Rahman et al. | 2020 | Bangladesh | 99 | Well | 253.18 ± 168.8 | Rahman et al. (2020) | ||
Sadler et al. | 2016 | Semarang, Indonesia | 52 | Well | 20 | Sadler et al. (2016) | ||
Martínez et al. | 2014 | Mar del Plata, Argentina | Zone A = 11 Zone B = 20 Zone C = 10 | Well | Zone A = 72.9 | Martínez et al. (2014) | ||
Zone B = 38.2 | ||||||||
Zone C = 67.3 | ||||||||
Hameed et al. | 2020 | Vehari District, Pakistan | 48 | Tap water | 1.35 ± 4.02 | Hameed et al. (2021) | ||
Alam et al. | 2021 | Ahmadpur, Pakistan | 36 | Tap water | 0.4197 | Alam et al. (2021) | ||
Rehman et al. | 2020 | Harnai, Pakistan | 24 | Spring water | 0.389 | Rehman et al. (2020) | ||
Królak and Raczuk | 2018 | Poland | 196 | Bottled water = 9, | Bottled water, Supply water, Deep wells, Dug wells | Bottled water = 0.659 ± 0.422 | Królak & Raczuk (2018) | |
Supply water = 104 | Supply water = 2.714 ± 4.107 | |||||||
Deep wells = 25 | Deep wells = 9.509 ± 14.27 | |||||||
Dug wells = 58 | Dug wells = 43.52 ± 33.11 |
No. . | Author . | Year . | Location . | No. of samples . | Sampling details . | Mean ± SD (mg/L) . | Reference . | |
---|---|---|---|---|---|---|---|---|
Studies in Iran | This study | 2022 | Tehran | 148 | Tap water | 36.15 ± 14.74 | – | |
Shirazi et al. | 2021 | West of Tehran | – | Tap water | 4.6 ± 0.02 | Haji Seyed Mohammad Shirazi et al. (2021) | ||
Panahi et al. | 2012 | Robat-Karim city | 40 (wells) | Well, Tap water | 2.1 | Panahi & Alavi Moghaddam (2012) | ||
32 (tap water | 2.05 | |||||||
Gholami et al. | 2019 | Ilam city | 77 | Tap water | 8.13 ± 5.4 | Gholami et al. (2019) | ||
Badeenezhad et al. | 2021 | Behbahan city | 90 | Tap water | 15.05 High rain season | Badeenezhad et al. (2021) | ||
13.35 Low rain season | ||||||||
Oftadeh et al. | 2019 | Mashhad city | 72 | Tap water | 16.63 ± 10.88 | Oftadeh et al. (2019) | ||
Rezvani et al. | 2021 | Kashan city | 20 | Bottled water | 8.37 ± 7.32 | Rezvani Ghalhari et al. (2021b) | ||
Mohammadpour et al. | 2022 | Hormozgan Province | 54 | Well | 7.37 ± 5.61 | Mohammadpour et al. (2022) | ||
Rezaei et al. | 2018 | Sanandaj city | 106 | Tap water | From 0.28 to 27.77 urban | Rezaei et al. (2019) | ||
From 1.28 to 80 rural | ||||||||
Golaki et al. | 2022 | Kazerun, Fars province | 25 | Well | 13.5 | Golaki et al. (2022) | ||
Bay et al. | 2018 | Divandareh county, Kurdistan province | 118 | Well | 31.37 ± 18.87 | Bay et al. (2018) | ||
Aghapour et al. | 2021 | Isfahan province | Spring = 287 rural, 113 urban | 1,178 Tap water samples 90 Spring samples 51 ghanat samples | Spring = 32.59 ± 24.96 rural, 30.15 ± 18.34 urban | Aghapour et al. (2021) | ||
Summer = 285 rural, 139 urban | Summer = 33 ± 22.34 rural, 37.2 ± 30.14 urban | |||||||
Autumn = 89 rural, 71 urban | Fall = 46.51 ± 25.68 rural, 47.98 ± 42.46 urban | |||||||
Winter = 230 rural, 105 urban | Winter = 33.45 ± 23.27 rural, 40.15 ± 34.29 urban | |||||||
Bazeli et al. | 2020 | Khaf county, | 28 | Well | 1.54 | Bazeli et al. (2020) | ||
Alimohammadi et al. | 2018 | Iran | 71 | Bottled water | 10.55 | Alimohammadi et al. (2018) | ||
Jaafarzadeh et al. | 2022 | Ilam, Bushehr, Khuzestan, Fars and Lorestan provinces | – | Drinking water | Ilam = 14.58 ± 2.62 Bushehr = 9.97 ± 3.14 Khuzestan = 52.77 ± 19.15 Fars = 64.63 ± 19.92 Lorestan = 22.85 ± 6.91 | Jaafarzadeh et al. (2022) | ||
Heidariyeh et al. | 2019 | Semnan city | 30 (tap water) 150 (bottled water) | Tap water | 7.27 ± 5.1 | Heidariyeh et al. (2019) | ||
Qasemi et al. | 2018 | Gonabad and Bajestan, | 18 (Gonabad) | Well | 29.33 ± 18.62 | Qasemi et al. (2018a) | ||
21 (Bajestan) | 37.95 ± 20.37 | |||||||
Studies worldwide | Mortada and Shokeir | 2018 | Dakahlia governorate, Egypt | 1291 | Tap water | 5.25 ± 1.61 | Mortada & Shokeir (2018) | |
Van den brand et al. | 2019 | Dutch regions, Netherland | 185 | Tap water | 4.7 | van den Brand et al. (2020) | ||
Wedyan et al. | 2021 | Northeast Jordan | – | Well | 44.4 | Wedyan et al. (2021) | ||
Adimalla | 2019 | Telangana province, India | 35 | Well | 58.74 | Adimalla et al. (2019) | ||
Adimalla | 2021 | Nirmal Province, India | 30 | Well | 43.30 ± 16.88 | Adimalla & Qian (2021) | ||
Taneja et al. | 2017 | Nagpur and Bhandara districts, India | 77 | Tap water | Rural = 45.69 ± 2.08 Urban = 22.53 ± 1.97 | Taneja et al. (2019) | ||
Ahada et al. | 2018 | Punjab, India | 76 | Well | 118.23 ± 33.45 | Ahada & Suthar (2018) | ||
Wang et al. | 2021 | Zhangjiakou, China | 489 | Well | 29.72 | Wang et al. (2021) | ||
Hu et al. | 2021 | Wanbei, China | 11 | Well | 24.01 | Hu et al. (2021) | ||
Barakat et al. | 2020 | Tadla, Morocco | 21 | Well | 24.73 ± 15.49 | Barakat et al. (2020) | ||
Rahman et al. | 2020 | Bangladesh | 99 | Well | 253.18 ± 168.8 | Rahman et al. (2020) | ||
Sadler et al. | 2016 | Semarang, Indonesia | 52 | Well | 20 | Sadler et al. (2016) | ||
Martínez et al. | 2014 | Mar del Plata, Argentina | Zone A = 11 Zone B = 20 Zone C = 10 | Well | Zone A = 72.9 | Martínez et al. (2014) | ||
Zone B = 38.2 | ||||||||
Zone C = 67.3 | ||||||||
Hameed et al. | 2020 | Vehari District, Pakistan | 48 | Tap water | 1.35 ± 4.02 | Hameed et al. (2021) | ||
Alam et al. | 2021 | Ahmadpur, Pakistan | 36 | Tap water | 0.4197 | Alam et al. (2021) | ||
Rehman et al. | 2020 | Harnai, Pakistan | 24 | Spring water | 0.389 | Rehman et al. (2020) | ||
Królak and Raczuk | 2018 | Poland | 196 | Bottled water = 9, | Bottled water, Supply water, Deep wells, Dug wells | Bottled water = 0.659 ± 0.422 | Królak & Raczuk (2018) | |
Supply water = 104 | Supply water = 2.714 ± 4.107 | |||||||
Deep wells = 25 | Deep wells = 9.509 ± 14.27 | |||||||
Dug wells = 58 | Dug wells = 43.52 ± 33.11 |
Comparing the results of present study to other similar studies showed that the mean concentration of nitrate in the current study was higher than the studies conducted on tap water samples by Van de Brand et al. (2020), Taneja et al. (2019) and Alam et al. (2021) in Dakahlia governorate in Egypt, Dutch regions of Netherlands, Nagpur and Bhandara districts of India and Ahmadpur East in Pakistan, respectively (Mortada & Shokeir 2018; Taneja et al. 2019; van den Brand et al. 2020; Alam et al. 2021). It was also higher than levels reported by the studies of Hameed et al. (2021) and Rehman et al. (2020) on drinking water and on spring water, respectively, in Pakistan and Sadler et al. (2016) on drinking water wells in Semarang, Indonesia (Sadler et al. 2016; Rehman et al. 2020; Hameed et al. 2021). On the other hand, the mean concentration of nitrate in this work was lower than the levels reported by Wedyan et al. (2021), Adimalla & Qian (2021); Adimalla et al. (2019), Taneja et al. (2019), Rahman et al. (2020), Martínez et al. (2014) and Królak & Razcuk (2018) in Al Duliel Area in Jordan, South India, Nirmal province in India, Nagpur and Bhandara districts of India, Central Bangladesh, Mar del Plata in Argentina, southern districts of Punjab, and Poland, respectively (Martínez et al. 2014; Ahada & Suthar 2018; Królak & Raczuk 2018; Adimalla et al. 2019; Taneja et al. 2019; Rahman et al. 2020; Adimalla & Qian 2021; Wedyan et al. 2021). In general, the comparisons suggest that the quality of municipal drinking water in southern parts of Tehran megacity is lower than other cities and regions across the country as well as some cities and regions of the world in terms of nitrate levels. In all studies, the exceeding levels reported for sampling sites were majorly associated with excessive use of fertilizers in agriculture and human waste that can pollute the groundwater and surface water reservoirs (Martínez et al. 2014; Rahman et al. 2020; Adimalla & Qian 2021; Wedyan et al. 2021). For the southern districts of Tehran city, these issues are even more pronounced as factors such as late design and development of wastewater collection network, the prevalent use of cesspits and septic tanks and wastewater seepage into aquifers pose additional challenges for providing safe drinking water (Asadollahfardi 2009; Khorasani et al. 2020; Sarmadi et al. 2021).
Studies show that human waste and agricultural fertilizers are the main causes of nitrate pollution in cities and rural areas, respectively. Isotopic characterization of drinking water resources in Mashhad city, the second largest city in Iran, showed that human waste is the main contributing factor in the contamination of groundwater resources to nitrate, particularly when the sewer systems stand in poor condition, which might lead to direct sewer seepage (Zendehbad et al. 2019). A national-level study on the spatial distribution of nitrate in 2017 revealed that the nitrate levels have increased in populated regions over the past decade. In that study, the application of fertilizers was recognized as the primary source of this increasing trend (Alighardashi & Mehrani 2017).
Below-standard nitrate levels do not indicate low risks. For example, in Azhdarpoor et al. (2019)'s study in Saravan city in Iran, though more than 97% of the samples had concentrations lower than the standard limit, the estimated risk was greater than 1 for children, teenagers and adults (Azhdarpoor et al. 2019). According to Figure 3, the UCLs for the estimated HQ in the infants, children, teenagers and adults were 1.24, 1.71, 1.20 and 0.96, respectively. This means that all groups except adults were at potential noncarcinogenic health risk. The younger generations, especially infants and children, being at high risk was frequently reported in nitrate HRA studies that were discussed earlier and it was associated with factors such as lower BW and behavioral peculiarity compared to adults (Rojas Fabro et al. 2015; Sadler et al. 2016; Qasemi et al. 2018a; Gholami et al. 2019; Rezaei et al. 2019; Adimalla & Qian 2021; Aghapour et al. 2021; Alam et al. 2021; Wedyan et al. 2021).
Continuous intake of nitrate might increase the risk of methemoglobinemia in infants and other health complications for other age groups in the long term (Adimalla et al. 2019). It should not be forgotten that the nitrate exposure from drinking water only comprises a fraction of total dietary exposure and contribution from foodstuff, especially vegetables as a highly consumed food category, other beverages and even breastfeeding should also be taken into account (Mortada & Shokeir 2018; Gholami et al. 2019; van den Brand et al. 2020).
The SA (Figure 5) showed that nitrate concentration plays a major role in increased risk for all age groups. This was consistent with other HRA studies on nitrate such as the work of Mohammadpour et al. (2022) in Hormozgan province, Bazeli et al. (2020) in Khaf county, Iran (Bazeli et al. 2020; Mohammadpour et al. 2022). All in all, preventive measures such as nitrate dilution, hybrid use of bottled and tap water, development of an efficient wastewater collection system and constant monitoring of drinking water are suggested to reduce nitrate levels to protect public health.
CONCLUSION
The investigation of nitrate concentration at the end point of municipal drinking water distribution network (i.e. tap water) in southern districts of Tehran showed that the mean concentration of nitrate in all districts was below the WHO and national standards. In total, 148 samples were taken from tap water of six districts in the southern part of Tehran megacity. The total mean concentration was 36.15 mg/L. Our analysis showed that 84.46% of the samples were below the standard level limit, while 15.54% of samples exceeded the criteria. Districts 19 and Aftab contained the highest nitrate levels. Compared to other studies, the determined levels of nitrate were relatively higher except for some studies. It was considered particularly high since the nitrate content was mostly lower than the studies carried out in rural areas or on water resources. The results of the health risk assessment showed that infants, children and teenagers were the most vulnerable groups (HQ > 1) mostly due to their higher water intake and absorption rate per body and the age groups were ranked as infants > children > teenagers > adults in the HQ overall estimate. The SA revealed than nitrate concentration had the most contribution to the estimated noncarcinogenic health risk. The findings of this work can help future works in the attempt, for example, to profiling nitrate content in other food and beverages, authorities by providing a status of nitrate in the drinking water distribution network to devise risk mitigation strategies and the public by providing knowledge about the possible health outcomes of nitrate in order to better self-regulate their dietary nitrate intake.
CONFLICT OF INTEREST
The authors declare that there are no conflicting interests and they are not affiliated with or involved with any organization or entity with any financial interest or nonfinancial interest in the subject matter or materials discussed in this paper.
AUTHORS CONTRIBUTIONS
Safa Kalteh has made a substantial contribution to the conception and design of methods, validated, drafted the original work, wrote, reviewed and edited the article, and also contributed to project administration. Farshad Hamidi has made a substantial contribution to the conception and wrote, reviewed and edited the manuscript. Mahdi Ahmadi Nasab contributed to sample preparation and verified the methods. Narges Mohseni Gharibdoosti verified the methods and fabricated the samples. Mohammad Rezvani Ghalhari conceived the study, drafted the manuscript, and helped in writing, reviewing and editing. Mina Parvizishad verified the methods and fabricated the samples. Amir Hossein Mahvi: has made a substantial contribution to the conception and design of methods, reviewed and editing the manuscript, drafted the original work and helped supervise the project.
FUNDING
Research reported in this publication was supported by Elite Researcher Grant Committee under award number [996114] from the National Institutes for Medical Research Development (NIMAD), Tehran, Iran.
ACKNOWLEDGEMENTS
The authors would like to thank the staff of the water and wastewater chemistry laboratory, School of Public Health Tehran University of Medical Sciences, Tehran, Iran.
DATA AVAILABILITY STATEMENT
Data cannot be made publicly available; readers should contact the corresponding author for details.