Determination of leachate leakage around a valley type landfill and its pollution and risk on groundwater

doi:10.21203/rs.3.rs-3137503/v1

Download PDF

Article

Determination of leachate leakage around a valley type landfill and its pollution and risk on groundwater

https://doi.org/10.21203/rs.3.rs-3137503/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Landfill leachate has great pollution risk to groundwater, which is of practical significance to study the characteristics of leachate leakage and surrounding groundwater pollution and its harm to human health. Taking a typical valley-type landfill in South China as the research object, this paper ascertained the leakage area based on geophysical methods and groundwater sampling. A total of 21 parameters such as pH, total hardness (TH), total mineralization (TM), permanganate index (COD_Mn), ammonium (NH₃-N), nitrites (NO₃-N), nitrates (NO₂-N), sulphates (SO₄⁻), chloride (Cl⁻), fluorides (F⁻), volatile phenols, cyanide, and heavy metals (HMs) in groundwater and some indicators in leachate were tested, and the water quality and health risks were evaluated by using the Nemerow pollution index (NPI) method and BCRA (Rish-based Corrective Action) model. The results indicate that the leakage areas are existing in the middle of the landfill site, the middle and the south of the anti-seepage dam with a depth about 15-22m and main pollutants of COD_Mn and NH₃-N. The main pollutants of pH, NH₃-N, Fe and Mn were ranged from 5.80 to 6.70, 0.06 to 0.74 mg/L, 0.002–2.763 mg/L, and 0.003–1.181 mg/L, their rates exceed the class Ⅲ standard at 28.57%, 28.57%, 4.29% and 14.29%, respectively. The Nemerow pollution index showed that the groundwaters at ZK01 and ZK04 were seriously polluted. Groundwater quality was affected by leachate and natural geological background. The total non-carcinogenic risk of groundwater was ranked as LS102 < LS101 < ZK02 < ZK01 < ZK03 < ZK05 < ZK04, with Cl⁻ and Mn as the main non-carcinogenic pollutants in the landfill. This rank reveals the rule that the closer to the waste body, the higher the risk.

Earth and environmental sciences/Environmental sciences/Environmental impact

Earth and environmental sciences/Hydrology

leachate leakage

geophysical method

groundwater quality

Nemerow pollution index

BCRA model

landfill

With the rapid economic development and ever-increasing population, the number of waste landfills was expanding rapidly in China. Because of the high concentration of organic matter, inorganic matter, heavy metal and other components in landfill leachate, groundwater pollution caused by leaking has become one of the global ecological environment problems (Podlasek et al., 2023; Li et al., 2023; Asomaku SO, 2023; Liu et al, 2023; Du et al., 2022; Han et al., 2016). Most provinces in China have also reported pollution caused by the leakage?), such as Henan (Tong et al., 2012), Hebei (Gao et al., 2009), Guizhou (Yang et al., 2013), Shanghai (Tian et al., 2005) and Guangzhou (Liang and Zheng, 2009). Studies showed that the infiltration of leachate into underground aquifers was a complex and variable process (Mishra et al., 2019). Different types of landfills have different infiltration surfaces, and pollutants produced by local production activities also enter groundwater through different routes, which resulting in the diverse and complex sources for groundwater pollution. Valley-type landfills are the most typical landfills in South China, but few researches focus on them (Liu et al., 2022). Therefore, the study of groundwater pollution based on valley-type landfills is important for the groundwater pollution control and treatment practically.

In landfills without liner system, various organic and inorganic compounds may migrate to the unsaturated soil and reach to the saturated area and contaminate groundwater (Reyes-Lopez et al., 2008). Even with bottom liner, its performance degraded caused by factors like long-term corrosive action of the leachate and geomembrane aging in landfill environment (Liu et al., 2015; Liu et al., 2021; Liu et al., 2019), the neglect of this degradation would seriously underestimate the long-term impact of landfill leakage on the environment (Sun et al., 2019; Banu and Berrin, 2015). At present, most researches concentrated on the sampling method and geochemical technique to characterize conventional parameters in leachate pollutants and surrounding groundwater, such as chemical oxygen demand (COD), total organic carbon (TOC), total dissolved solids (TDS), pH and heavy metals (Danley-Thomson et al, 2020), the analyses on the pollution sources and the assessment of its harm to human based on multivariate statistical method and risk assessment model (Du et al., 2023; Liu et al., 2022; Xu et al., 2021). The increase in the number and area of liner system defects caused by chemical aging of geomembrane is the main reason for long-term leakage of landfill leachate and groundwater pollution during operation or after closure (Fady et al., 2014; Ewais and Rowe, 2014), but previous studies have paid little attention to this issue.

As a non-invasive technique, geophysical technology can preliminarily detect the geological environment characteristics of study area (Shangguan et al., 2016), and the pollution plumes produced by landfill leachate infiltration (Lu et al., 2023; Lu et al., 2023a; Abbaspour et al., 2000; Porsani et al, 2004; Santos et al., 2006). A valley-type landfill in Hunan Province was taken as an example in this study for the following purposes: (1) geophysical technology would be conducted to detect and determine the pollution range and depth produced by landfill leachate infiltration; (2) the parameters of leachate and groundwater would be determined to assess groundwater quality in studied area; (3) multivariate statistics would be applied to analyze the relationship of various parameters of groundwater and landfill leachate; (4) the risk of groundwater would be evaluated on the human health based on the RBCA model. The geophysical technology and the chemical parameter tests of the leachate and groundwater would be combined to provide theoretical support for the management and treatment of landfill, and this would effectively solve the problem of leachate pollution from the source.

2.1 Overview of the study area

The research object is a valley-type domestic waste landfill in South China, where is subtropical monsoon humid climate. The landfill was put into operation in 2014 and is still running. It is located in a small arcuate gully surrounded by low mountains on the north, west and south sides, and only open to the northeast. The barrier system for leakage prevention from the waste body is arranged at bottom and slope of the landfill with thickness ranging from several meters to more than ten meters. The surface water system is undeveloped.

The strata of the landfill mainly include quartz sandstone and siltstone of Middle Devonian Tiaomajian Formation (D₂t), artificial fill (Q₄^ml) and residual silt formed by weathered quartz sandstone (Q₄^eld) of Quaternary system. No magmatic rocks are found in this region. Fold structure and rock fracture are developed in the study area, which control the groundwater flow direction from southeast to northeast. And two descending springs outcrop at the upper and central landfill. The shallow metamorphic quartz sandstone with weathered fissure is the main aquifer. It is recharged by atmospheric precipitation along the rock structures or weathered cracks in process of hillside sheet flow (Zeng et al., 2019).

2.2 Geophysical research

Transient electromagnetic method (TEM) was used to detect the landfill impervious layer (Fig. 1). 25 measured lines were set, and data collection adopted the positioned measurement mode, with 5m interval of measuring points, 6.25HZ of transmitting frequency, 10A of transmitting current, 50µS of turn-off time, and 400 times of periodic superposition. The HPTEM system had its own processing software for data processing. In the field work, different operators were selected to detect the representative section repeatedly at the same position for self-inspection to ensure the quality of measurement results.

2.3 Samples collection and analysis

Sampling of groundwater and leachate were carried out in the summer of 2022. According to the geomorphic condition and flow direction of groundwater, 7 sample points were arranged to investigating the groundwater environment (Fig. 1), including five borehole samples (ZK01- ZK05), one of the existing monitoring well (LS01) adjacent to the landfill body, and one of background well (LS02) at the upstream of studying area. All the water samples were taken from the quartz sandstone reservoir, and covered the entire landfill site. Untreated leachate was taken from the entrance of the leachate equalization tank located at the northeast part of the landfill. All groundwater and leachate samples were stored and transported to laboratories for further analysis. Before the analysis, the samples were through a 0.45µm micro filtration membrane and sealed in the 500 mL polyethylene bottles which were washed with deionized water thoroughly. The samples for the heavy metal concentrations tests should be acidified to the pH value ≤ 2 by adding the nitric acid, then stored in a light-free refrigerator at 4 ℃.

Based on groundwater quality standard (GB/T 14848 − 2017) and environmental quality standard for surface water (GB 3838 − 2002), the parameters including pH, total hardness (TH), total mineralization (TM), permanganate index (COD_Mn), ammonium (NH₃-N), nitrites (NO₃-N), nitrates (NO₂-N), sulphates (SO₄⁻), chloride (Cl⁻), fluorides (F⁻), volatile phenols, cyanide, and heavy metals (HMs) were measured for all groundwater samples. While COD_Mn, NH₃-N, and HMs were tested for the leachate samples based on the standard for pollution control on the landfill site of municipal solid waste. The pH values were determined by glass electrode method, total hardness was tested by EDTA titrimetric volumetry, total mineralization was determined by dry gravimetry, and the COD_Mn was determined by dried gravimetric analysis. NH₃-N, NO₃-N, NO₂-N, SO₄⁻, Cl⁻, F⁻, volatile phenols, cyanide were all determined by spectrophotometric analysis introduced in groundwater quality standard (GB/T 14848 − 2017). HMs were determined by flame atomic absorption spectrophotometry (AAS-FL) and graphite furnace atomic absorption spectrometry (AAS-GF). Blank sample was set in each group of samples with the relative standard deviation less than 5%, and the measurement results were within the requirement of quality standard.

2.4 Health risk assessment

Since direct water intake exerts far more harmful effects on human health than that by skin contact and inhalation (Xie et al., 2022; Luo et al., 2021; Jiang et al., 2019), this paper would only assess the health risks for population health caused by drinking water. The RBCA health risk assessment model was developed by the American GSI Company based on the RBCA (Rish-based Corrective Action) proposed by the ASTM (American Society for Materials and Experiments) in order to evaluate the risks of contaminants in the environment. At present, it has been widely used in Europe, America and parts of China (Chang et al., 2004).

The exposure assessment model for direct intake of groundwater is:

$$EDI=\frac{{\rho }_{gw}\times IR\times EF\times ED}{BW\times AT}$$

Where, EDI is the average daily exposure dose by drinking contaminated groundwater, mg·kg^− 1·d^− 1.

Carcinogenic risks of single pollutants are calculated as:

$$CR=EDI\times {SF}_{0}$$

Where, CR is the carcinogenic risk of a single pollutant, without dimension.

Non-carcinogenic risks of single pollutants are calculated as:

$$HQ=\frac{EDI}{{RfD}_{0}}$$

Where, HQ is the non-carcinogenic risk of a single pollutant, without dimension.

The RBCA model divides chemicals into carcinogens and non-carcinogens according to the chemical classification by the US Environmental Protection Agency. And the carcinogenic risk level is limited to 10^− 6 − 10^− 4, while the maximum acceptable level for non-carcinogenic risk is 1 (Zhang et al., 2014). The model was used to gain the polluted risk level of groundwater in the landfill and to assess its impact on health of the locals. The various parameter values of the model are shown in Table 1 and Table 2.

Table 1

Exposure parameter in RBCA model
Parameter symbol	Parameter name	Unit	Recommend value
${\rho }_{gw}$	Concentrations of contaminants in groundwater	mg·L^− 1	/
IR	Daily groundwater consumption rate	L·d^− 1	2
EF	Exposure frequency	d·a^− 1	365
ED	Exposure duration	a	30
BW	Body mass	kg	53.1
AT	Average time for carcinogenic effect	A	72
AT_n	Average time for non-carcinogenic effect	a	30

Table 2

Toxicological parameters of pollutants
Exposure route	Category	Parameter	SF (mg·kg^− 1·d^− 1)	RfD (mg·kg^− 1·d^− 1)
Drinking pathway	non-carcinogenic	F-	-	0.06
		NH₃-N	-	0.97
		NO₃-N	-
		NO₂-N	-
		Cl⁻	-	0.1
		Fe	-	0.3
		Mn	-	0.046
		Zn	-	0.3
		Cu		0.04
	carcinogenic	Hg	-	0.0003
	carcinogenic	Ni	0.84	0.02
Note: “-“indicates no corresponding reference value.

3.1 Determination and characteristic of the leachate leakage

The resistivity inversion results of the landfill site are showed in Fig. 2 and Fig. 3. Previous studies reported that the appearance of low resistivity could be explained by high iron concentrations in leachate (Rosqvist et al., 2003; Kjeldsen et al., 2002). The landfill body is mostly composed of domestic garbage, which is easily corroded to produce leachate with strong conductivity and low resistance. While the resistivity of quartz sandstone, siltstone and other bedrock is higher. The overall decline in resistivity can be influenced by soils formed from altered or broken rocks and cracks and other geological structures (Lopes et al., 2012; Meju, 2000). Low resistance zone appeared under the landfill body in survey lines of S001-S004 and S010-S021 (Fig. 2). It was inferred that the anomalies were caused by tomographic relief based on the site topography and geomorphology characteristics. The uniform curves of apparent resistivity reflected the regular contact between the body and stratum, indicating that there is no leachate leakage under the impervious barrier.

Compared with the inversion sections of lines S005-S009 and S022-S025 (Fig. 3), the low-resistance areas were narrow and went down deeper (lines of S005-S009), and the contact areas between the waste body and the quartz sandstone were unclear (lines of S022-S025). Obviously, the leachate diffused vertically, and the landfill impervious layer was broken. Through analyzing of the multiple anomalies with low resistance occurred in different survey lines, it is inferred that leakage areas are existing in the middle of the landfill site with a depth of 15-20m (lines of S005 ~ 009), the middle area near the anti-seepage dam with a depth about 17-22m (lines of S022 ~ 025), and the south area of the dam with a depth about 15-22m (lines of S024 ~ 025).

For further information about the possible influence of leachate leakage on surrounding environment, untreated leachate from the regulating tank was analyzed specially (Table 3). Base on the standard for pollution control on the landfill site of municipal solid waste (GB16889-2008), all the measured values of parameters (except As.) exceeded the emission limits of water pollutants, and NH₃-N, COD_Mn which reflect the main pollution factors of household waste far exceeded the standard by dozens or hundreds of times. The Nemerow index method was used to evaluate the leachate pollution in the landfill site, with the calculated values of 83.6 (Table 3). This result indicates that the leachate in the landfill site had a great pollution potential to the surrounding environment as the main pollution source, this could be attributed to the leachate gathering caused by the horizontal and vertical block by impervious barrier (Ye et al., 2021). Therefore, it is necessary to regularly monitor the site anti-seepage system to avoid the failure of the system and long-term collection and infiltration of leachate, which would cause underground soil and water pollution.

Table 3

Composition and quality assessment of landfill leachate
Indicator	pH	COD_Mn	NH₃-N	As	Hg	Pb	Cd	Cr	Fe	Mn	NPI
Unit	-	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	/
Measured Value	5.5	6651	2648	0.099	0.0098	8.05	0.265	7.74	10.36	0.47	83.60
Referenced Value^#	/	100	25	0.1	0.001	0.1	0.01	0.1	/	/	83.60

“^#”: It was referred to the standard for pollution control on the landfill site of municipal solid waste (GB 16889 − 2008).

Table 4

Statistical analysis of pollutant concentration and water quality evaluation
Indicator	Depth	pH	TDS	Total hardness	COD_Mn	NH3-N	SO₄²⁻	Cl⁻	F⁻	Hg	Fe	Mn	Cu	Zn	NO₂-N	NO₃-N	Water Quality	NPI¹	NPI²
Unit	m	/	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	mg/L	Water Quality	NPI¹	NPI²
LS102	0	6.64	12.6	7.95	0.80	0.06	0.484	0.569	-	0.0002	0.002	0.003	-	0.004	-	0.295	Ⅲ	-	-
Grade		Ⅲ	Ⅰ	Ⅰ	Ⅰ	Ⅱ	Ⅰ	Ⅰ	Ⅰ	Ⅲ	Ⅰ	Ⅱ	Ⅰ	Ⅰ	Ⅱ	Ⅰ	Ⅲ	-	-
LS101	1.5	6.51	26.3	15.22	1.11	0.13	4.622	0.746	-	0.0001	0.102	0.037	-	0.002	-	3.629	Ⅲ	-	-
Grade		Ⅲ	Ⅰ	Ⅰ	Ⅱ	Ⅲ	Ⅰ	Ⅰ	Ⅰ	Ⅰ	Ⅱ	Ⅱ	Ⅰ	Ⅰ	Ⅱ	Ⅱ	Ⅲ	-	-
SK01	0.24	6.01	41.57	27.89	2.31	0.291	11.43	1.973	0.066	0.0003	2.763	0.626	-	0.016	-	0.542	Ⅴ	19.46	6.61
Grade		Ⅳ	Ⅰ	Ⅰ	Ⅲ	Ⅲ	Ⅰ	Ⅰ	Ⅰ	Ⅲ	Ⅴ	Ⅳ	Ⅰ	Ⅰ	Ⅱ	Ⅰ	Ⅴ	19.46	6.61
SK02	2.98	6.7	107.77	84.68	0.79	0.69	32.78	1.84	-	0.0006	0.007	0.235	0.002	-	-	1.278	Ⅳ	5.37	1.68
Grade		Ⅲ	Ⅰ	Ⅰ	Ⅰ	Ⅳ	Ⅰ	Ⅰ	Ⅰ	Ⅲ	Ⅰ	Ⅳ	Ⅰ	Ⅰ	Ⅱ	Ⅰ	Ⅳ	5.37	1.68
SK03	0.22	6.25	64.91	49.25	0.86	0.489	25.52	4.096	-	0.0001	0.031	0.236	0.007	0.024	-	1.182	Ⅳ	8.75	1.68
Grade		Ⅳ	Ⅰ	Ⅰ	Ⅰ	Ⅲ	Ⅰ	Ⅰ	Ⅰ	Ⅰ	Ⅰ	Ⅳ	Ⅰ	Ⅰ	Ⅱ	Ⅰ	Ⅳ	8.75	1.68
SK04	2.18	5.80	92.79	50.07	1.30	0.742	30.23	14.77	0.039	0.0001	0.072	1.181	0.002	0.034	0.121	9.787	Ⅳ	23.19	8.39
Grade		Ⅳ	Ⅰ	Ⅰ	Ⅱ	Ⅳ	Ⅰ	Ⅰ	Ⅰ	Ⅰ	Ⅰ	Ⅳ	Ⅰ	Ⅰ	Ⅱ	Ⅲ	Ⅳ	23.19	8.39
SK05	1.86	6.51	16.72	9.59	1.01	0.379	2.04	4.617	0.167	0.0002	0.057	0.06	0.012	0.024	0.037	2.058	Ⅲ	8.65	0.55
Grade		Ⅲ	Ⅰ	Ⅰ	Ⅱ	Ⅲ	Ⅰ	Ⅰ	Ⅰ	Ⅲ	Ⅰ	Ⅲ	Ⅱ	Ⅰ	Ⅱ	Ⅱ	Ⅲ	8.65	0.55
Maximum	2.98	5.80	12.60	7.95	0.79	0.060	0.484	0.569	-	0.0001	0.002	0.003	-	-	-	0.295
Minimum	0	6.70	107.77	84.68	2.31	0.742	32.780	14.77	0.167	0.001	2.763	1.181	0.012	0.034	0.121	9.789
Mean	-	6.35	51.81	34.95	1.17	0.397	15.301	4.087	-	0.000	0.433	0.340	0.006	0.017	-	2.682
Class Ⅲ standard value²			1000	450	3.0	0.5	250	250	1.0	0.001	0.3	0.1	1.0	1.0	1.0	20
Over standard rate (%)	-	28.6	-	-	-	28.57	-	-	-	-	14.29	14.29	-	-	-	-	57.14%

“¹”: It was referred to the background values of sample LS01 (GB 16889 − 2008);

“²”: It was referred to the class Ⅲ standard for groundwater quality (GB/T 14848 − 2017).

3.2 Characteristics of groundwater quality and pollution

Tested parameters of groundwater from the upstream to the downstream in the studied area are shown in Table 4. The concentrations of volatile phenols, cyanide, As, Cr, Pb and Cd in all samples, as well as fluoride, Cu and nitrite in some samples were below the detection limits. The pH values in groundwater ranged from 5.80 to 6.70, with the rate of 28.57% exceeding the class Ⅲ standard for groundwater quality (GB/T 14848 − 2017). And the concentrations of NH₃-N, Fe and Mn ranged from 0.06 to 0.74 mg/L, 0.002–2.763 mg/L, and 0.003–1.181 mg/L, with the rate of 28.57%, 4.29%, and 14.29% exceeding standard, respectively. The maximum concentrations were 1.48, 9.21, and 11.81 times of the values of class Ⅲ water quality standard, respectively. In addition, the groundwater quality at ZK02, ZK03 and ZK04 sampling points reached the Class Ⅳ standard, and the main pollutants were pH, NH₃-N and Mn. While SK01 reached Class Ⅴ water quality standard, its pH and Mn reached Class Ⅳ standard and Fe reached to Class Ⅴ standard, which showed the extremely poor groundwater quality.

Generally speaking, leachate generated from upstream site may infiltrate and pollute groundwater downstream, and furthermore lead to the concentrations of Fe, NH₃-N, NO₃-N and other compositions exceeding the standard values (Xu et al., 2021). As shown in Fig. 4, all parameters of borehole samples (ZK01 to ZK05) were higher than that of background wells (LS01 and ZK02), suggesting that the groundwater system in the landfill has been polluted. According to the locations of each sampling point, the linear distance to landfill site from far to near was ZK03 < ZK04 < ZK02 < ZK01 < ZK05, and the sampling depth from shallow to deep was ZK03 < ZK01 < ZK05 < ZK04 < Zk02. But the concentration of indicators did not change regularly with the distance and depth, indicating that there were other contributing factors in the pollution process (Varol et al., 2018). It was pointed out that the impact of landfill on groundwater quality depended on waste composition, soil accumulation, rainfall, hydraulic gradient and the geological environment of the landfill (Singh et al, 2008), which should be further investigated.

The highest concentration of Fe was found at ZK01, secondly at LS01 of background well. Contents of Fe and Mn in quartz sandstone in the study area were 4.47% and 0.21%, respectively. The excess of Fe in groundwater may be related to the underlying strata. The highest concentration of Mn was found at ZK04, followed by ZK01 to ZK03, but little at the background sites. ZK04 was sampled beneath the damaged anti-seepage dam and closest to the waste body, indicating that the Mn pollution in groundwater possibly mainly originated from landfill leakage rather than underlying bedrock. The concentrations of NH₃-N were higher in samples of ZK02 to ZK04, followed by ZK05 and ZK01, and a small amount was also detected in the background wells. NH₃-N was diffused taking landfill as the center and accumulated downstream controlled by rock fractures, hydraulic gradient and damaged dam.

To have a better comparison about the comprehensive groundwater pollution, the Nemerow pollution index method was used based on the parameter concentrations of background well at LS01 and the class Ⅲ standard for groundwater quality (GB/T 14848 − 2017). The results (Table 4) showed that, relative to the local background value, groundwater of all monitoring sites in the landfill were heavily polluted (NPI > 3), with a descending order of ZK04 (NPI = 23.19) > ZK01 (NPI = 19.46) > ZK03 (NPI = 8.75) > ZK05 (NPI = 8.65) > ZK02 (NPI = 5.31). While compared with the class Ⅲ standard (GB/T 14848 − 2017), only ZK01 and ZK04 belonged to severe polluted condition (NPI > 3), samples of ZK02 and ZK03 were in slight polluted risk (1.0 < NPI ≤ 2.0), and ZK05 was clean (NPI ≤ 0.7). The order of NPI for samples was ZK04 (NPI = 8.39) > ZK01 (NPI = 6.61) > ZK03 (NPI = 1.68) = ZK02 (NPI = 1.68) > ZK05(NPI = 0.55). The two calculated results displayed a great difference about the comprehensive pollution degree of groundwater. But groundwater at ZK01 and ZK04 was seriously polluted in either case. Nemerow pollution index method would highlight the impact of maximum value on pollution degree (Xie et al., 2023; Ye et al., 2021), Fe and Mn in the sites of ZK04 and ZK01 seriously exceeded the standard, which results in that the indexes of samples ZK04 and ZK01 were much higher than that of others.

3.3 Correlations between groundwater parameters

3.3.1 Correlation analysis (CA)

The correlation analysis result of each parameter in groundwater of landfill site was shown in Fig. 5. pH was negatively correlated with most of the parameters, especially with Mn (r=-0.897) and Zn (r=-0.778). Podlasek et al. (2023) also reported a similar relationship in the leachate parameters of different landfills. A large number of studies have confirmed that pH could affect the solidification of heavy metals in soils, and the solubility of heavy metals would increase with the decrease of pH value (Wijesekara et al., 2014; Lindamulla et al., 2022; Wdowczyk and Szymanska-Pulikowska., 2021). There were significant positive correlations between total mineralization, total hardness, NH₃-N and SO₄²⁻ in groundwater (r = 0.834 ~ 0.982). Similar results were also reported by Zhao et al (2016) and Zhou et al (2022), that the total dissolved solids in groundwater was significantly related with SO₄²⁻ and Ca²⁺. Moreover, some studies believed that EC was highly associated with NH₃-N (Mohammad-Pajooh et al., 2017), and sensitive to changes of TDS in leachate (Gupta and Paulraj, 2017). The high values of these parameters indicated high contents of dissolved inorganic and organic compounds (Gupta and Paulraj, 2017).

Remarkably, positive correlation appeared in COD_Mn and Fe (r = 0.949). COD_Mn reflects the pollution degree of water by reducing organic matter or inorganic matter, which can activate metals such as Fe and Mn in soil and enhance the migration ability of these metals into the groundwater by rainfall, resulting in serious Fe and Mn pollution (Xia et al., 2002). In addition, weak correlations between HMs should be noted, possibly due to their low concentration in leachate (Engelmann et al, 2017). However, Cl⁻ was positively related with Mn (r = 0.839) and Zn (r = 0.822), suggesting their similar source (Abunama et al, 2021).

3.3.2 Principal component analysis (PCA)

The relevance of parameters can be revealed by PCA to supplement the obstacles by CA, for minimizing the loss of data analysis (Mishra et al., 2016; Vahabian et al., 2019). Because the sample size was too small for source analysis in this study, PCA analysis aimed to reduce the variables that characterize groundwater quality (Wdowczyk and Szyma 'nska-Pulikowska, 2021).

PCA extracted five principal components from the parameters of groundwater, which accounted for 98.89% of the total variance (Table 5). Among them, PC1 accounts for 29.31% of the total variance loaded strongly by the total salinity, total hardness, NH₃-N and SO₄²⁻, followed by Hg and sampling depth. Researches have pointed out that inorganic parameters such as EC, TDS, COD and NH₄⁺ were dominant in PC1, resulting in great data differentiation (Podlasek et al., 2023; Ergene et al., 2022). PC2 accounts for 26.85% of the total variance, which exhibits strong loading of Cl⁻, Mn and NO₃-N. The COD_Mn and Fe have extremely strong loads on PC3, accounting for 17.23% of the total variance. PC4 is much concerned with Cu and F⁻, and accounts for 13.39% of the total variance. PC5 is related to strong negatively loadings of NO₂-N and account for 12.11%.

Table 5

The PCs distinguished from the chemical characteristics of groundwater
Variables	Factor 1		Factor 3	Factor 4	Factor 5
depth	0.58	0.22	-0.36	0.18	0.63
pH	-0.11	− .77^*	-0.55	-0.02	0.30
TDS	0.95^**	0.25	-0.04	-0.16	-0.02
Total hardness	0.99^**	-0.01	-0.06	-0.14	-0.05
COD_Mn	-0.10	0.20	0.96^**	-0.01	0.09
NH₃-N	0.88^**	0.41	-0.07	0.24	-0.02
Cl⁻	0.29	0.92^**	-0.05	0.19	-0.06
Hg	0.64	-0.56	0.14	-0.02	0.48
F⁻	-0.24	0.13	0.22	0.892^**	0.28
Fe	-0.07	-0.10	0.99^**	-0.03	0.03
Mn	0.39	0.81^*	0.42	-0.08	-0.02
Cu	0.01	-0.03	-0.29	0.928^**	-0.22
Zn	0.07	0.73	0.16	0.53	-0.39
NO₂-N	0.26	0.17	-0.17	0.07	-0.93^**
NO₃-N	0.16	0.95^**	-0.17	-0.08	0.15
SO₄²⁻	0.93^**	0.27	-0.04	-0.12	-0.20
Eigenvalues % of variance	29.31	26.85	17.23	13.39	12.11
Cumulative %	29.31	56.16	73.39	86.78	98.89

3.4 Health risk assessment

Carcinogens likes As, Cr and Cd in samples were all lower than the detection limit (Table 4), and the carcinogenic risk through drinking was ignored. Based on the RBCA model, the non-carcinogenic risks of Fe, Mn, Hg, Cu, Zn, NH₃-N, F⁻, Cl⁻, NO₂-N and NO₃-N in the landfill groundwater were evaluated (Table 6). It can be seen that the total non-carcinogenic risk levels of the drillhole samples all exceeded the maximum acceptable limit of 1, except for the background wells. The total hazard quotient through groundwater drinking in the study area was much higher in an order of LS102 < LS101 < ZK02 < ZK01 < ZK03 < ZK05 < ZK04. The closer sampling points to the waste body, the higher the risk to human by water drinking. The HQs of single parameter were in descending order of Cl⁻ > Mn > NO₃-N > Fe > Hg > F⁻ > NH₃-N > NO₂-N > Cu > Zn. Only the HQs of Cl⁻ in samples of ZK03 to ZK05 were greater than 1, while that of other parameters at different sampling points were lower than 1. It should be noted that the HQ of Mn at the ZK04 point was close to 1. To sum up, Cl⁻ and Mn are the main pollutants causing non-carcinogenic risk in the study area, and landfill leachate pollution would bring harm to the area below the dam, which decreases with the increased distance from the waste body.

Table 6

Health risk assessment results based on RBCA model
Sample sites	NH₃-N	Cl⁻	F⁻	Hg	Fe	Mn	Cu	Zn	NO₂-N	NO₃-N	Total hazard quotient
LS102	2.33E-03	2.14E-01	0.00E + 00	2.51E-02	2.51E-04	2.46E-03	0.00E + 00	5.02E-04	0.00E + 00	6.94E-03	2.52E-01
LS101	5.05E-03	2.81E-01	0.00E + 00	1.26E-02	1.28E-02	3.03E-02	0.00E + 00	2.51E-04	0.00E + 00	8.54E-02	4.27E-01
ZK01	1.13E-02	7.43E-01	4.14E-02	3.77E-02	3.47E-01	5.13E-01	0.00E + 00	2.01E-03	0.00E + 00	1.28E-02	1.71E + 00
ZK02	2.68E-02	6.93E-01	0.00E + 00	7.53E-02	8.79E-04	1.92E-01	1.88E-03	0.00E + 00	0.00E + 00	3.01E-02	1.02E + 00
ZK03	1.90E-02	1.54E + 00	0.00E + 00	1.26E-02	3.89E-03	1.93E-01	6.59E-03	3.01E-03	0.00E + 00	2.78E-02	1.81E + 00
ZK04	2.88E-02	5.56E + 00	2.45E-02	1.26E-02	9.04E-03	9.67E-01	1.88E-03	4.27E-03	4.56E-02	2.30E-01	6.89E + 00
ZK05	1.47E-02	1.74E + 00	1.05E-01	2.51E-02	7.16E-03	4.91E-02	1.13E-02	3.01E-03	1.39E-02	4.84E-02	2.02E + 00

This study showed that although multi-layer protection systems were used to prevent leachate leakage, the landfill impervious barrier and the retaining dam have been damaged and lost efficacy, causing the groundwater pollution. The physiochemical characteristics and Nemerow pollution indexes of groundwater indicate that partial monitoring sites exceeded the class Ⅲ standard for groundwater quality (GB/T 14848 − 2017), and reached the Class Ⅳ or Class Ⅴ with the excessive parameters of pH, NH₃-N and Mn. And groundwater at ZK01 and ZK04 was seriously polluted due to much higher concentrations of Fe and Mn, respectively. The results of health risk assessment suggests that the non-carcinogenic risk levels through drinking decreased with the increase of distance from the waste body, and Cl⁻ and Mn were the main non-carcinogenic pollutants in the study area.

It is worth noting that high background content possibly was one cause for Fe and Mn pollution in the landfill groundwater, except for leachate leakage. It is necessary to regularly monitor the landfill leachate and groundwater to further know their long-term interactions with the geological environment and pollution potential in order to improve the ability for effective treatment and appropriate management.

Ethics approval and consent to participate

Not application.

Consent for publication

Not application.

Availability of data and material

The data sets used and analyzed during this study are available from the corresponding author on reasonable request.

Competing interests

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.

Funding

This research was supported by the Natural Science Foundation of Hunan Province (2022JJ30244), the Research Project of Teaching Reform of Hunan Province (HNJG-2022-0790), the Key Team Project of Science and Technology Innovation in Xiangtan City (ZY-CXTD20221003)

Authors' contributions

Yulong Lu: Methodology, Writing - Original Draft, Investigation

Qing Xie and Chuanghua Cao: Conceptualization, Supervision

Chenyang Li: Data curation, visualization

Bozhi Ren and Yang Liu: Writing - Review & Editing, Validation

Acknowledgements

Not application.

Abbaspour, K., Matta, V., Huggenberg, P., et al., 2000. A contaminated site investigation: comparison of information gained from geophysical measure methods and hydrogeological modeling. J. Contam. Hydrol. 40, 365e380. https:// doi.org/10.1016/S0169-7722(99)00055-8.
Abunama, T., Othman, F., Nilam, T.I.T., 2021. Comparison of landfill leachate generation and pollution potentials in humid and semi-arid climates. Int. J. Environ. Waste Manag. 27 (1), 79–92. https:// doi.org/10.1504/IJEWM.2021.111906.
Asomaku, SO. 2023. Quality assessment of groundwater sourced from nearby abandoned landfills from Industrial City in Nigeria: Water pollution indices approach. Hydro Research. 6, 130-137. https:// doi.org/10.1016/J.HYDRES.2023.03.002.
Banu, S., Berrin, T., 2015. Parametric fate and transport profiling for selective groundwater monitoring at closed landfills: a case study. Waste Manag. 38, 263–270. https:// doi.org/10.1016/j.wasman.2014.12.020.
Chang, S.H., Kuo, C.Y., Wang, J.W, et al., 2004. Comparison of RBCA and Cal TOX for setting risk-based cleanup levels based on inhalation exposure. Chemosphere. 56(4), 359-367.
Danley-Thomson, A., Worley-Morse, T., Contreras, S.U.J., et al., 2020. Determining the effects of Class I landfill leachate on biological nutrient removal in wastewater treatment. Environ. Manag. 275, 111198. https:// doi.org/10.1016/j.jenvman.2020.111198.
Engelmann, P. D. M., Santos, V. H. J. M. D., Letícia Isabela Moser, Bruzza, E. D. C., et al., 2017. Environmental monitoring of water resources around a municipal landfill of the rio grande do sul state, brazil. Environ Sci Pollut Res Int. 24(26), 1-14. https://doi.org/10.1007/s11356- 017-9725-7.
Du, C., Li, Z., 2022. Contamination and health risks of heavy metals in the soil of a historical landfill in northern China. Chemosphere. 313:137349. https:// doi.org/10.1016/J.CHEMOSPHERE.2022.137349.
Ergene, D., Aksoy, A., Sanin, F.D., 2022. Comprehensive analysis and modeling of landfill leachate. Waste Manag. 145, 48–59. https://doi.org/10.1016/j. wasman.2022.04.030.
Ewais, A., Rowe, R., 2014. Effect of aging on the stress crack resistance of an HDPE geomembrane. Polym. Degrad. Stabil. 109, 194-208. https://doi.org/10.1016/j.polymdegradstab.2014.06.013.
Gao, H., Fan, Y., Ding, W.P., et al., 2009. Study on groundwater pollution in daily solid waste landfill. Water Resour. Prot. 25, 61–64. https://doi.org/1004-6933(2009)05-0061-04.
GB/T 14848-2017. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China. Standard for groundwater quality [S]. Beijing: Standards Press of China, 2017(in Chinese).
GB 3838-2002. State Environmental Protection Administration of the People's Republic of China, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. Environmental quality standards for surface water [S]. Beijing: China Environment Science Press, 2002(in Chinese).
GB 16889-2008. State Environmental Protection Administration of the People's Republic of China, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. Standard for pollution control on the landfill site of municipal solid waste [S]. Beijing: China Environment Science Press, 2002(in Chinese).
Gupta, A., Paulraj, R., 2017. Leachate composition and toxicity assessment: an integrated approach correlating physicochemical parameters and toxicity of leachates from MSW landfill in Delhi. Environ. Technol. 38 (13–14), 1599–1605. https://doi.org/ 10.1080/09593330.2016.1238515.
Han, Z., Ma, H., Shi, G., et al., 2016. A review of groundwater contamination near municipal solid waste landfill sites in China. Sci Total Environ. 569-570, 1255-1264. https://doi.org/10.1016/j.scitotenv.2016.06.201.
Jiang, F., Ren, B.Z., Hursthouse, A., 2019. Distribution, source identification, and ecological-health risks of potentially toxic elements (PTEs) in soil of thallium mine area (southwestern Guizhou, China). 26(16), 16556-16567. https://doi.org/10.1007/s11356-019-04997-3.
Kjeldsen, P., Barlaz, M.A., Rooker, A.P., et al., 2002. Present and Long-Term Composition of MSW landfill leachate: a Review. Crit. Rev. Env. Sci. Technol. 32 (4), 297e336. https://doi.org/10.1080/10643380290813462.
Li, S., Zhao, M., Xu, Y., et al., 2023. Pathway, flux and accumulation of pollutant emission from landfill receiving As- and Hg-containing hazardous waste. J. Clean. Production. 2023, 403. https://doi.org/10.1016/J.JCLEPRO.2023.136697.
Liang, J., Zheng, W.Q., 2009. Evaluation and control measures of the shallow layer groundwater pollution caused by Fengcun landfill in Zhanjiang, Guangdong. J. Geol. Hazards Environ. Preserv. 20, 63–67. https://doi.org/1006-4362（2009）03-0063-05.
Lindamulla, L., Nanayakkara, N., Othman, M., et al., 2022. Municipal solid waste landfill leachate characteristics and their treatment options in tropical countries. Curr. Pollut. Rep. 1–15. https://doi.org/10.1007/S40726-022-00222-X
Liu, Y., Wang, Y., Wang, J., et al., 2022. Pollution characteristics and health risk assessment of groundwater in a valley type landfill. Environ. Chemi. 41, 8,2540-2550. https://doi.org/10.7524/j.issn.0254-6108.2021121002.
Liu, Y., Bouazza, A., Gates, W.P., et al., 2015. Hydraulic performance of geosynthetic clay liners to sulfuric acid solutions. Geotext. Geomembranes. 43, 14-23. https://doi.org/10.1016/j.geotexmem.2014.11.004.
Liu, Y., He, B., Xie, J., et al., 2021. Compatibility of geosynthetic clay liners at different temperatures. J. Environ. Prot. Ecol. 22, 2295–2306.
Liu, Y., Gates, W.P., Bouazza, A., 2019. Impact of acid leachates on microtexture of bentonites used in geosynthetic clay liners. Geosynth. Int. 26, 136–145. https://doi.org/10.1680/jgein.18.00043.
Liu, Y., Li, X., Tu, Y., Lu, Y. 2023. Mining Leachates Effect on the Hydraulic Performance of Geosynthetic Clay Liners under Different Temperatures. Water. 15, 1132. https://doi.org/10.3390/ w15061132.
Lopes, D., Silva, S., Fernandes, F., et al., 2012. Geophysical technique and groundwater monitoring to detect leachate contamination in the surrounding area of a landfill--Londrina (PR--Brazil). J Environ Manage. 113, 481-487. https://doi.org/10.1016/j.jenvman.2012.05.028.
Lu, Y.L., Tao, J.L., Cao, C.H., et al., 2023. Detection of Landfill Leachate Leakage Based on ERT and OCTEM. Water. 15, 1778. https://doi.org/10.3390/w15091778.
Lu, Y.L., Yang T.C., Abdollah T.T., et al., 2023a. Fast Recognition on Shallow Groundwater and Anomaly Analysis Using Frequency Selection Sounding Method. Water. 15, 96. https://doi.org/10.3390/w15010096
Luo, X., Ren, B.Z., Hursthouse, A., 2021. Source identification and risk analysis of potentially toxic elements (PTEs) in rainwater runoff from a manganese mine (south central Hunan, China). Water Sci. Tech-W. Sup. (3). https://doi.org/10.2166/ws.2020.352.
Meju, M.A., 2000. Geoelectrical investigation of old/abandoned, covered landfifill sites in urban areas: model development with a genetic diagnosis approach. J. Appl. Geophys. 44, 115e150. https://doi.org/10.1016/S0926-9851(00)00011-2.
Menenti, M., Li, X., Jia, L., 2021. Multi-Source Hydrological Data Products to Monitor High Asian River Basins and Regional Water Security. Remote Sensing.
Mishra, S., Tiwary, D., Ohri, A, et al., 2019. Impact of municipal solid waste landfill leachate on groundwater quality in Varanasi, India. Groundwater for Sustainable Development. 9, 100230. https://doi.org/10.1016/j.gsd.2019.100230.
Mishra, H., Rathod, M., Karmakar, S., Kumar, R., 2016. A framework for assessment and characterisation of municipal solid waste landfill leachate: an application to the Turbhe landfill, Navi Mumbai, India. Environ. Monit. Assess. 188 (6), 1–23. https:// doi.org/10.1007/s10661-016-5356-6.
Mohammad-Pajooh, E., Weichgrebe, D., Cuff, G., 2017. Municipal landfill leachate characteristics and feasibility of retrofitting existing treatment systems with deammonification–A full scale survey. J. Environ. Manag. 187, 354–364. https:// doi.org/10.1016/j.jenvman.2016.10.061.
Porsani, J.L., Filho, W.M., Elis, V.R., et al., 2004. The use of GPR and VES in delineating a contamination plume in a landfifill site: a case study in SE Brazil. J. Appl. Geophys. 55, 199e209. http://dx.doi.org/10.1016/j.jappgeo.2003.11.001.
Podlasek, A., Vaverková, M.D., Koda, E., et al., 2023. Characteristics and pollution potential of leachate from municipal solid waste landfills: Practical examples from Poland and the Czech Republic and a comprehensive evaluation in a global context. ,117328-117328. http://dx.doi.org/10.1016/J.JENVMAN.2023.117328.
Reyes-López, J.A., Ramírez-Hernández, J., Lázaro-Mancilla, O., et al., 2008. Assessment of groundwater contamination by landfifill leachate: a case in México. Waste Manag.. http://dx.doi.org/10.1016/ j.wasman.2008.03.024.
Rosqvist, H., Dahlin, T., Fourie, A., et al., 2003. Proceedings Sardinia, Ninth International Waste Management and Landfifill Symposium. CISA Publisher, Italy, pp. 27e36.
Santos, F.A.M., Mateus, A., Figueiras, J., Gonçalves, M.A., 2006. Mapping ground water contamination around a landfifill facility using the VLF-EM method-a case study. J. Appl. Geophys. 60, 115e125. https://doi.org/10.1016/j.jappgeo.2006.01.002.
Shangguan, D., Liu, S., Ding, Y., et al., 2015. Characterizing the May 2015 Karayaylak Glacier surge in the eastern Pamir Plateau using remote sensing. J. Glaciol. 62(235), 944-953. https://doi.org/10.1017/jog.2016.81.
Singh, S. J. , Prakash, J. , Patnaik, S. , et al., 2008. Enhancement in superconducting transition temperature and upper critical field of lao0.8f0.2feas with antimony doping. Physics, 22(4), 32-32. https://doi.org/10.1088/0953-2048/22/4/045017
Sun, X.C., Xu, Y., Liu Y.Q., et al., 2019. Evolution of geomembrane degradation and defects in a landfill: Impacts on long-term leachate leakage and groundwater quality. J. Clean. Prod. 224:335-345. https://doi.org/10.1016/j.jclepro.2019.03.200.
Tian, Y.J., Hang, R.H., Yang, H., Zhou, H.Y., Li, D.T., 2005. Pollution on groundwater systems by the leachate from a seashore waste landfill site. Environ. Sanit. Eng. 13, 1–5. https://doi.org/1005-8206(2005)01-01-05.
Tong, X.X., Ning, L.B., Dong, S.G., 2012. GMS model for assessment and prediction of groundwater pollution of a garbage dumpling site in Luoyang. Environ. Sci. Technol.35, 197–201. https://doi.org/10.3969/j.issn.1003-6504.2012.07.042.
Vahabian, M., Hassanzadeh, Y., Marofi, S., 2019. Assessment of landfill leachate in semiarid climate and its impact on the groundwater quality case study: Hamedan, Iran. Environ. Monit. Assess. 191 [6], 1–19. https://doi.org/10.1007/s10661-019-7215-8.
Varol, S., Sekerci, M.E., 2018. Hyrogeochemistry, water quality and health rish assessment of water resources contaminated by agricultural activities in Korkuteli (Antalya, Turkey) district center. J. Water. Health. 16(4),1-26. https://doi.org/10.2166/wh.2018.003.
Wdowczyk, A., Szyma´nska-Pulikowska, A., 2021. Analysis of the possibility of conducting a comprehensive assessment of landfill leachate contamination using physicochemical indicators and toxicity test. Ecotoxicol. Environ. Saf. 221, 112434 https://doi.org/10.1016/j.ecoenv.2021.112434.
Wijesekara, S. S. R. M. D. H. R., Mayakaduwa, S.S., Siriwardana, A.R., et al., 2014. Fate and transport of pollutants through a municipal solid waste landfill leachate in Sri Lanka. Environ. Earth Sci. 72 (5), 1707–1719. https://doi.org/10.1007/s12665-014-3075-2.
Xia, L.J., Wen, X.L., 2002. Effects of waste leachate on availability of iron and manganese in landfill soil and on groundwater quality. Soil and Environmental Sciences, 11(1) 6-9. https://doi.org/10.16258/j.cnki.1674-5906.2002.01.002.
Xie, Q., Ren, B.Z., Deng X.P., 2023. Quantitative source identification, risk assessment and pollution of heavy metals in soils around a typical Sb smelter in central and southern China. Stoch Environ Res Risk Assess. https://doi.org/10.1007/s00477-023-02402-7.
Xie, Q., Ren, B.Z., 2020. Pollution and risk assessment of heavy metals in rivers in the antimony capital of Xikuangshan. Sci. Repot. 12,14393-14393. https://doi.org/10.1038/s41598-022-18584-z.
Xu, Y., Ma, Y.M., Zhang, Xi, et al., 2021. Health risk assessment of groundwater drinking pathway around a municipal solid waste landfill. Ecology and Environmental Sciences. 30[6]: 558-568. https://doi.org/10.16258/j.cnki.1674-5906.2021.03.014.
Yang, Y.L., Yang, T.Y., Yu, X.H., et al., 2013. Reach on groundwater pollution caused by landfills in Karst region in Guangzhou. Ground Water. 35, 77–80.
Ye, S.F., Guo, YS., Pan, X., et al., 2021. Investigation and evaluation of heavy metals in an informal landfill site. Environmental Engineering. 39(3): 214-219. https://doi.org/10.13205/j.hjgc.202103031.
Zeng, C.F., Zheng, G., Xue, X.L., 2019. Responses of deep soil layers to combined recharge in a leaky aquifer. Eng. Geol. 260, 105263-105263. https://doi.org/10.1016/j.enggeo.2019.105263.
Zhang, W.J., Wu, Y.Y., Wei, D.M., et al., 2014. Comparison of application in RBCA and CLEA model for health risk assessment in a contaminated site. Global Geology, 33(4): 952-958.
Zhao, J.T., Zhou, J.L., Gao, Y.X., et al., 2016. Spatial-temporal evolution of total dissolved solids of groundwater in plain area of Yanqi Basin, Xinjiang. Transactions of the Chinese Society of Agricultural Engineering. 32(5)V:120-125.
Zhou, R., Wu, L., Bao, S., et al., 2022. Pollutant identification of water and soil of uncontrolled landfills in Shenzhen. China Environmental Science. 42(3), 1287-1294. https://doi.org/10.19674/j.cnki.issn1000-6923.20210929.005.

There is NO Competing Interest.

Download PDF

Version 1

posted

You are reading this latest preprint version

Determination of leachate leakage around a valley type landfill and its pollution and risk on groundwater

Status:

Version 1

Abstract

Figures

1 Introduction

2 Materials and methods

2.1 Overview of the study area

2.2 Geophysical research

2.3 Samples collection and analysis

2.4 Health risk assessment

3 Results and discussion

3.1 Determination and characteristic of the leachate leakage

3.2 Characteristics of groundwater quality and pollution

3.3 Correlations between groundwater parameters

3.3.1 Correlation analysis (CA)

3.3.2 Principal component analysis (PCA)

3.4 Health risk assessment

4 Conclusion

Declarations

References

Additional Declarations

Status:

Version 1

Parameter symbol	Parameter name	Unit	Recommend value
\({\rho }_{gw}\)	Concentrations of contaminants in groundwater	mg·L^− 1	/
IR	Daily groundwater consumption rate	L·d^− 1	2
EF	Exposure frequency	d·a^− 1	365
ED	Exposure duration	a	30
BW	Body mass	kg	53.1
AT	Average time for carcinogenic effect	A	72
AT_n	Average time for non-carcinogenic effect	a	30