Buffering distance between hazardous waste landfill and water supply wells in a shallow aquifer

Accepted Manuscript Buffering distance between hazardous waste landfill and water supply wells in a shallow aquifer

Xu Ya, Dong Lu, Nai Changxing, Liu Yuqiang, Huang Qifei, Li Weishi, Liu Jingcai PII:

S0959-6526(18)33568-6

DOI:

10.1016/j.jclepro.2018.11.161

Reference:

JCLP 14920

To appear in:

Journal of Cleaner Production

Received Date:

27 February 2018

Accepted Date:

18 November 2018

Please cite this article as: Xu Ya, Dong Lu, Nai Changxing, Liu Yuqiang, Huang Qifei, Li Weishi, Liu Jingcai, Buffering distance between hazardous waste landfill and water supply wells in a shallow aquifer, Journal of Cleaner Production (2018), doi: 10.1016/j.jclepro.2018.11.161

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Buffering distance between hazardous waste landfill and water supply wells in a shallow aquifer Xu Yaa,b,c, Dong Lub, Nai Changxingb, Liu Yuqiangb , Huang Qifeib, Li Weishib,Liu Jingcaib aCollege

of water science, Beijing Normal university, Beijing 100085

bResearch

Institute of Soil and soliid Waste, Chinese Research Academy of Environment Sciences, Beijing 100012, China c ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Xu Ya e-mail:[email protected] Liu Yuqiang e-mail:[email protected]

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Buffering distance between hazardous waste landfill and water supply wells in a shallow aquifer Key words: Monte Carlo; health risk; leachate; safe drinking Abstract. The vulnerability of engineering barrier and the toxicity of leachate increase the need to maintain a certain buffering distance between landfill and drinking water sources. In order to provide decision-making support and technical guidance for the determination, and management of buffering distance, this paper coupled the dose-response model, leakage estimation model, exponential decay source model, and the advection-dispersion model for contaminants transportation and transformation in vadose and aquifer groundwater, and constructed an integral risk-based framework to help to calculate the buffering distance in shallow aquifers against the leachate contamination. Based on the framework and method, a case study is carried out. The results indicate that Zn and Ni have experience a similar dilution and attention process, but due to its smaller RDAF (required dilution and attenuation factor, equal to the ratio of initial concentration to limit concentration) value, Ni needs only a vertical separation distance (VSD) of 4 m (a 4 m vadose zone with saturated conductivity of 1×10-5 cm/s) without additional requirement on horizontal buffering distance. While, Zn requires an additional buffering distance of 380m in addition to the VSD to achieve to be diluted/attenuated to a risk-acceptable level. 2,4-D has larger RDAF than Zn, but due to its difference in degradation characteristics from Zn, it also needs a smaller buffering distance (135 m) than Zn; Further studies shown that the sensitivity of the dilution and attenuation of heavy metals to distance is relatively weak, especially when the distance is greater than 800m; organic pollutants are more sensitive to distance, even more than 800m; for the landfill site to dispose organic pollutants, the buffering distance of 400m is a conservative choice, while for sites to dispose heavy metal wastes, 400m may be a risky decision and needs further calculation and demonstration. 1. Introduction Groundwater pollution is currently a worldwide environmental problem, which poses well-known ecological (Mélida et al., 2018) and human-health risks (Bhowmick et al., 2018;). Landfill leachate is generally enriched in organic matter (Anne et al., 2018), ammonium(Juan et.al., 2017), and heavy metals(Ying, et al., 2017) and represents one of the major sources of groundwater contamination (Dan et al., 2017). The groundwater, once contaminated by leachate, not only causes a serious of ecological and environmental problems (e.g. water eutrophication and soil salinization), but may also cause many water-borne diseases. For example, water contaminated by heavy metals (e.g. manganese and arsenic) in leachate, when consumed by humans long term, can increase the risk of cancer (Bhowmick et al., 2018) and infant mortality (Rahman et al., 2010), and induce motor (Parvez et al., 2011) and cognitive dysfunction in children (Wasserman et al., 2004). Nitrate, commonly detected in municipal solid waste landfill, has been linked to “blue baby” disorder(Juan et.al., 2017), spontaneous abortion, and increased risk of non-Hodgkins lymphoma(Jason et al., 2012). Moreover, in recent years, emerging pollutants with geno-toxicity (Eirini, 2013), reproductive toxicity(Erik et al., 2005), and embryo-toxicity(Lourenço, 2017), such as pharmaceuticals, personal care products, and nanoparticles (Burcu, et al., 2000), were also identified in leachate and groundwater aquifers around landfills (Han, 2016). Though modern engineered landfills are designed and constructed to prevent leachate emission, leachate leakage still occurs because of the failure of the liner system. Statistics from the United States Environmental Protection Agency (USEPA) indicate that most landfills leak. Further study demonstrated that about three-quarters of the 55,000 landfills in Unite States have polluted the water bodies around them (Saeedreza and Amity, 2017). This has highlighted the importance of maintaining a reasonable separation distance between landfills and the private water wells for water security. This separation distance, if properly established and maintained, guarantees the continuous removal of hazardous compounds from leachate by natural attenuation process in the vadose zone and aquifers to help ensure that the well water satisfies water quality standards (Yang et al., 2017). Vadose and aquifer mediums serve as natural filters and absorbents that can alleviate groundwater contamination caused by leachate. Their ability to achieve this, however, varies with the pollutant type, soil characteristics, and hydrogeological conditions. For example, clear removal of methamphetamine was observed in fine-grained sediment, compared with minimal removal in a sand medium. Moreover, sediment exhibits an ability to remove pharmaceuticals and illicit drugs when they were treated alone, but produced little effect when they were mixed (Avishai and Siebner, 2017). Likewise, topsoil can effectively repair the groundwater with high perchlorate concentration(Greenhagen et al., 2014), while illitic soil can restore heavy-metal-contaminated groundwater, especially when the concentration of carbonate in soil is high(Elzahabi and Yong, 2001). Buffering distance, in this paper, is defined as the distance between the landfill and the closest drinking water well in the down-gradient direction of regional flow. Currently, a multitude of management strategies has been adopted for the choice of buffering distance between potential contamination sources and the wells. For example, the USEPA requires a 30.5 m clearance distance from wells to petroleum tanks, liquid tight manure storage, pesticide & fertilizer storage, and a 61.0 distance to manure stacks(Blaschke et al, 2016). Also, some countries and some states in the U.S. recommend a vertical isolation distance of 1.0 m between the liner bottom and groundwater table(US EPA., 1991). However, even though landfill remains the predominant disposal method of solid landfill, and represents one of the major source of groundwater contamination, studies focusing on the landfill buffering distance remain scarce. In many countries, no requirements for the buffering distance have been implemented at all (US EPA., 1991). Some countries, however, require the owners of the landfill to maintain a suitable separation distance between the landfill and the surrounding wells but specific values or methods to establish this are not provided(MEP.PRC,2008;MEP.PRC.2018). Only a minority of countries have adopted specific

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values for the buffering distance between the landfill and the down-gradient wells and the scientific background for the selection of this value is limited(The Management and Planning Organization, 2010;Deportment of Environment Offices, 2017). As is mentioned above, a buffering distance between a landfill site and a drinking water well should be reasonably determined and maintained to ensure the sustainable reduction in hazardous contaminants by natural attenuation processes in subsurface media so that the health risk of drinking water is acceptable. However, previous study of buffer distance mainly focused on oil tanks and septic tanks. Landfill-related research reports are not only rare in number, but also lacking in systematic frameworks, methodologies, and scientific backgrounds by only providing a specific buffering distance value. This may not only limit the extensively application of the buffering distance, but also to some extent lead to the neglect of its importance. Hence this paper is committed to overcome these deficiencies in knowledge by constructing the framework and method of buffer distance calculation, as well as the scientific background behind it. Based on the constructed framework and method, case studies were carried out to calculate the buffering distances of different pollutants under typical hydrogeological conditions. For the cases when the required buffering distance is neither practically nor economically feasible, additional solutions is recommended to lower requirement on buffering distance. The research results will not only provide theoretical and methodological support for the determination and management of buffering distance for landfill owners or operators, but also arouse people's attention to the setting of this distance. 2. Models and methods 2.1 Acceptable water quality for safe drinking Many countries and organizations have established standards for drinking water quality, in which concentration limits for different constitutes were recommended or required. For example, the USEPA set mandatory water quality standards for 97 contaminants and non-mandatory standards for 15 contaminants (USEPA, 2006.), while the EU Drinking Water Directive set criteria for only 48 contaminants but with stricter concentration limits(European U.C, 1998). Moreover, a total of 95 indices have been recommend for safe drinking according to the World Health Organization (WHO) drinking water guidelines (WHO, 2011). However, the number of indices and corresponding limits in these standards, as well as the scientific background behind them, are not consistent, which limits their applicability. The WHO recommended an acceptable-risk based method to determine the drinking water standard (WHO, 2011). This method determines the water quality indices and their limit values considering the habits (e.g. frequency and amount of drinking) and physical characteristics (e.g., weight, lifespan, and age) of exposed groups, as well as the toxicity of targeted pollutants, which increases its versatility. Furthermore, the database of contaminant toxicology parameters and population exposure parameters has been dynamically updated, which provides an opportunity for continuous improvement of the method. Therefore, this risk-based method was adopted in the current study. The risk associated with drinking groundwater contaminated by leachate was represented by the hazard quotient for non-carcinogenic hazards and the cancer risk for carcinogenic hazards. The hazard quotient (HQ) was calculated using the Eq.1 (USEPA, 1989; 2002): HQ = CDI/ RfD (1) where RfD is the toxicity reference dose of target chemicals (mg/kg/day), CDI is the average daily intake (mg/kg/day), and cam be calculated using Eq.2. CDI =

𝑐𝑔 × 𝐼𝑤 𝑊𝑏

(2)

where Cg (μg/L) is the concentration of targeted contaminants in groundwater, Iw (L/day) is the average water consumption, and Wb (kg) is the average body weight. The cancer risk (CR) was estimated using the formula as follows (USEPA, 1989; 2002): (3) (mg/kg/day−1)

where SF is the cancer slope factor for target chemicals Generally, when the value of HQ and/or Risk is <1, the health risk is acceptable. Therefore, the limit concentration CL in drinking water can be calculated by solving Eq. (1) and Eq. (2) or Eq. (1) and Eq. (3) . 2.2 Leachate concentration and leakage rate from hazardous waste landfill 2.2.1 Leachate leakage prediction model Though modern landfills are designed and constructed to prevent the emission of leachate, groundwater pollution caused by leachate leakage from standard landfills still occurs frequently. This commonly occurs because some defects are inevitably introduced into high-density polyethylene geomembrane (HDPE GM) during its installation and construction procedures, and which, consequently, forms the preferential and primary pathway of leachate leakage. Many empirical models have been developed for the prediction of leachate leakage for different liner structures. In China, the engineered barrier in hazardous waste landfill (HWL) is typically composed of two layers of HDPE GM and compacted clay liner (CCL). For this type of barrier system, the leakage rate can be estimated according to the empirical model developed by Giroud and Bonaparte (1989):

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[

ℎ𝑤 0.95

Q = 𝛽𝐶 1 + 0.1( 𝐿 ) 𝑠

]𝑎

0.1 0.9 0.74 ℎ𝑤𝑘 𝑠

(m3/s);

× 𝑆 × 𝑁

(4)

(m2);

where Q is the leakage rate a is the area of the defects in the HDPE Ks and Ls are the hydraulic conductivity (m/s) and thickness (m) of the CCL, respectively; hw is the leachate depth on the HDPE (m); N is the hole density in the HDPE (holes/ha); S is the bottom area of the landfill (ha); and βc is the coefficient with values of 0.21 and 1.15 for good contact and poor contact between the HDPE and the CCL, respectively. The leakage rate is strongly influenced by hw and N. Many previous studies have investigated the hole density in HDPE, and the frequency and severity of various defects in installed HDPE GM were calculated using the reported statistics(Laine, 1990;Kastman et al., 1984;McQuade et al., 1999). However, hw is often spatiotemporally heterogeneous and difficult to assess accurately because it is influenced by the precipitation, site management, and waste characteristics. Nevertheless, a maximum leachate table during the landfill management period (including operation period and aftercare period) is required by many countries. In China, a maximum depth of 0.3 m is required for HWL(MEP.PRC, 2018), and this value was therefore regarded as the worst situation, and used in Eq. (4) to calculate the leakage rate. 2.2 Leachate concentration prediction model Typically, the leachate composition and concentration will vary during the lifecycle of the landfill. One reason for the change in leachate concentration is a flushing-out of components as infiltrating precipitation passes through the waste materials. A declining source term model was adopted in this study to account for this process. This assumes that the concentration of a contaminant at any time is related to its initial concentration according to the following equation (Walker et al., 1993): 𝐶t = 𝐶0e

- 𝜆t

(5)

(6) where Ct is the concentration of hazardous constitutes in leachate at time t (mg/L); C0 is the initial concentration in leachate (mg/L); t is the time (years); i is the infiltration rate (mm/years); Wd is the depth of final waste (m); and Wfc is the field capacity of waste (-). 2.3 Simulating the attention and dilution process in subsurface mediums Contaminant migration through an impacted unsaturated–saturated groundwater system results from transport processes in connection with the dilution effect of groundwater flow (i.e. advection) and the attenuation effect of subsurface mediums (i.e. degradation, dispersion, and retardation). In a homogeneous and isotropic soil–water system, the transport processes, as well as the dilution and attention effect, can be modelled by applying a 1D advection–dispersion equation as follows (Bear, 1972;Freeze et al., 1979): (7) 𝐷𝐿 = 𝛼v + 𝐷m (8) where x is the distance along the pathway in the flow direction (m), c is the concentration at a distance x and a time t (mg/L), v is the groundwater velocity (m/s), n is the effective porosity (-), R is the retardation factor (-), γ is the first order decay rate (s−1), DL = the longitudinal coefficient of hydrodynamic dispersion (m2/s), α is the medium's dispersivity (m), and Dm is the coefficient of molecular diffusion (m2/s). Solutions to the above advection–dispersion equation have been developed for a number of boundary conditions. In these cases, the equation with the exponentially declining boundary condition [Eq. (5)], was solved using the Laplace transformation approach and an analytical solution was obtained as follows (Drury et al., 2003):

(9) μ = 1 +

4(𝛾 ‒ 𝜆)𝐷 2

v

(10)

Equations (9) and (10) are applicable to the contaminant transportation in both vadose and aquifer systems, and when applied to the simulation of aquifer flow, the transformed output from the previous vadose pathway forms the input for the next aquifer. For more details see Drury(2003). 2.4 Procedures for assessing the buffering distance Fig.1 describes the how the above-mentioned equations and models are combined to form an integral model and what the detailed procedure has been applied to use this model to simulate buffering distance. In the first step, the Dose-response equation was combined with the acceptable risk level to gain the limit concentration for safe drinking water quality levels for a specific contaminant. In the second step, the parameter i, together with wd wfc, were used to calculate the λ using Eq.(6); and then the calculated λ, along with C0 and Q calculated by Eq.(4), were inserted into analytical solution of advection-dispersion equation to gain the output

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concentration from vadose to groundwater In the third step, the transformed output (concentration and velocity) from the previous vadose pathway forms the input for the next aquifer and was used to calculate the concentration at a certain distance in the direction of groundwater flow. In the last step, the calculated concentration at a certain distance in the direction of groundwater flow were compared with the limit concentration gained in the first step to determine the buffering distance. it should be noted that due to the continuous injection of leachate, the groundwater concentration will gradually increase in the early stage, and reach to a peak concentration. Then the contaminants concentration in groundwater will gradually decreases with time as the leachate concentration decrease. A peak concentration will occur during the whole simulation process, and this concentration is used to determine the buffering distance. In addition, during the process of simulating buffering distance, several uncertainties occurred as a result of model simplification and the random nature of introduced model parameters. Thus, Monte Carlo framework, together with probability density functions describing the random nature of model variables, were employed here to quantify these uncertainties and their influence on buffering simulation results. The main variables considered includes rainfall, hole density, vadose zone thickness, and groundwater velocity in aquifers. The constructed integral model was solved by drawing random input variables from distribution functions, as specified in Table 3. The iterations were conducted 2002 times for each simulation following the Monte Carlo framework. This value was determined because further computations showed no significantly different results. The buffering distances under the less favorable condition were then determined from the 95th percentiles of the simulated distances in the direction of flow.

Fig.1 Framework and procedures for buffering distance 3. Case study 3.1 Site Characterization The landfill studied here is a hazardous waste landfill in southeastern China. The site is located just beside the Yangtze River (Fig.2), which is the largest river in Eurasia (Tong et al., 2016). The Yangtze River coincides with the lowest groundwater level contour and is recharged by the groundwater. The landfill occupies an area of 5.0 hm2 and consists of two 250 m × 100 m waste cells. As groundwater represents a major water resource for villages in remote undeveloped areas (Blaschke et al., 2016), it would pose a health risk to local villages scattered around the landfill if the drinking well were to become contaminated by leachate and its pollutants. It is therefore necessary to establish and maintain a proper separation distance, and determine whether there are any private wells that currently do not satisfy the buffering distance. 3.2 Model application and parameter set A total of 13 hazardous contaminants were detected from the leachate samples from this landfill. Among them, the

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contaminants whose concentration were significantly lower than the criteria, were excluded and not considered here. Finally, the heavy metals nickel (Ni) and zinc (Zn), and the semi-volatile organic compound (VOC) 2, 4-Dichlorophenol (2,4-DCP) were selected as the target contaminants for the calculation of buffering distance. The relevant parameters listed in table were inserted into the equations and yield the concentration limits of 5.92 × 10−2, 8.89 × 10−1, and 8.89 × 10−3 mg/L for Ni, Zn, and 2,4-DCP, respectively.

Fig. 2. Landfill site location Table 1 Reported HDPE GM defect rates Defect types

Size

Density (holes/ha)

1 mm

2.5

-

5.4

10 mm

2.5

9 mm

40

25.5 mm

25

25.5 mm

22

Tears

100 mm

10

Earth movement or landfill slips

Golder Associates

All types

1 mm to 3 m

27

-

McQuade and Needham (1999)

Pin holes

Holes

Cause

References Golder Associates

Manufacturing

Laine and Miklas (1990) Golder Associates Kastman (1984)

Mechanical damage

Golder Associates Kastman (1984)

Table 2 Input variables for simulating buffering distance Parameters Units A. Model variables for the calculation of water quality criteria Iw L/day Wb kg Ni RfD Zn mg/kg/day 2,4-DCP

Value 2 60 2 × 10−2 3 × 10−1 3 × 10−3

References

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B. Model variables for the calculation of leachate concentration and leakage Pin holes (0.1–5 mm) Holes (5–100 mm) N holes/ha Tears (100–10,000 mm) Ks m/s Ls m S ha i mm/years Wd m Wfc Ni C0 Zn mg/L 2,4-DCP C. Model variables for the simulation of contaminant transportation in the subsurface medium Vadose zone thickness m Aquifer thickness m Ni R in vadose Zn zone 2,4-DCP Ni γ in year−1 vadose Zn zone 2,4-DCP Ni R in Zn aquifer 2,4-DCP Ni γ in Zn year−1 aquifer 2,4-DCP v in aquifer m/s

4 23 10 1 × 10−7 0.6 3 78 20 0.5 2 120 20 4 20 0.042 0.042 5.23 0 0 0.07 0.17 0.17 20.9 0 0 0.07 1 × 10−7

Averaged from the reported detection rates in Table 1

Landfill-specific values

Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values Site-specific values

3.3 Results and discussions Fig.4 shows ratio of simulated concentration Cg to concentration limits CL at different distances. At the distance where the ratio is smaller than 1, the hazardous constitute has decreased to the acceptable concentration in drinking wells, and this distance can be thought as the buffering distance. As is shown in the Fig.4, the Cg/CL ratio of Zn drops to 1 at 380 m, which means the buffering distance for Zn is 380. Similarly, and the buffering distance for 2，4-D and Ni are 135 m and 0 m respectively. To guarantee all contaminants attenuate to a risk acceptable level, the buffering distance of 380m is required. Compared with location of the water supply wells in each direction around the landfill (Fig.3), the closest well in the southeast direction is 774 m away from the landfill boundary, and the wells in the northeast and west direction is 1044m and 800m, respectively. Obviously，the current distance between the landfill and the drinking wells is much longer than the predicted buffering distance of 380m. This simulated 380m distance is closer to the separation distance required by Alberta Environment and Sustainable Resource Development (AESRD) (400 m), but is merely half as likely as the distance required by Ministry of Environmental Protection of the People's Republic of China (MEPPRC) (800 m). The possible reason is that China's landfill management strategies is conservative, and a factor of safety of 2 may be incorporated.

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1044 m

800 m 774 m

Fig. 3. Simulated buffering distance and drinking wells around the landfill site

1.6 1.4

Cs/Cd

1.2

380m

1 0.8

135m

0.6 0.4 0.2 0 0

200

400

2,4 D

600

800

Ni

Zn

Distance,m

1000

1200

Fig. 4. Ratio of simulated concentration (Cg) to concentration limit (CL) for 2,4-DCP, Ni, and Zn at different buffering distances

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3.3.1 Dilution and attenuation required for different contaminants As mentioned in the previous section, different contaminants require different buffering distances. Obviously, different distances mean different requirement on dilution and attenuation, in other words, different pollutants require different DA. The required dilution and attenuation factor (RDAF) can be calculated using the Eq. (11). 𝐶0

(11)

RDAF = 𝑐

𝐿

200

10,000,000

160

1,000,000

120

100,000

80

10,000

40

1,000

Distance,m

0

0

200

Ni(DAF) Zn(RDAF)

400

600

800 Distance,m Zn(DAF) 2,4-D(DAF)

DAF(2,4-d)

DAF(Zn and Ni))

The initial concentration of Zn, Ni and 2,4-D in the leachate are 120, 2 and 20 mg/L respectively. Their limit concentration for safe drinking is 5.92×10-2, 8.89 x 10-1, and 8.89 x 10-3 mg/L respectively. Therefore, the RDAF that must be achieved by subsurface medium are accordingly 135,33.8 and 2,250 for Zn, Ni and 2,4-D. Of all three contaminates, Ni requires the smallest DAF of 33.8. This is reason why the Ni in this study, needs only a vertical separation distance of 4 m (a 4 m vadose zone with saturated conductivity of 1×10-5 cm/s) without additional requirement on horizontal separation distance. While, Zn requires an additional isolation distance of 380m in addition to the vertical separation distance. It seems a little strange, however, that 2,4-D requires a larger RDAF 16 times than Zn, but a smaller buffering distance 2 times than Zn. This is mainly due to the different degradation characteristics of them. VOCs tend to degrade into non-toxic or low-toxic components in subsurface mediums. This results are in agreement with Baun (2000) whose investigation indicates that the toxicity of organic matter has declined to a background level in the groundwater at the distance of 80-140 m away from the MSW landfill. Conversely, the buffering distance for Zn is 380 m, which is about 3 times larger than 2, 4-D. This is because heavy metals, like Zn, merely undergo adsorption-resolution reactions in subsurface mediums and are hard to decay. For example, in Violet’s study, Pb was detected at the point 4000 m away from landfill boundary in a porous medium aquifer.

100

1000

1200

1400

Ni(RDAF) 2,4-D(RDAF)

Fig.5 Dilution and attenuation of different contaminants at different distances 3.3.2 Dilution and attenuation under different distance Heavy metal pollutants (such as Zn and Ni) basically undergo the same or similar degradation processes. For example, when the distance equal to 800, 400, 200, and 100m, the DAF of Zn and Ni are 184.4 and 182.8, 137.1 and 136.9, 124.2 and 124, and 115 and 114.8. The DAF difference between these two contaminants is less than 0.2%. In contrast, there are obvious differences in degradation characteristics between heavy metals and organic pollutants. With Zn and 2,4-D as an example, when distances equal to 800, 400, 200 and 100m, their DAFs are, accordingly, 3637104.3 and 184.4, 43010.4 and 137.1, 4814.8 and 124.2, and 1593.5 and 115. The difference between their DAF value is significant, and are increasingly significant as the distance increases. It is shown that the dilution multiple of the underground medium increases with the increase of distance, but when the distance is greater than 800m, the trend becomes not obvious. This may be the main reason why some countries set the buffering distance to 800m. From the above analysis, it can be concluded that the dilution degradation of heavy metal pollutants is relatively insensitive to distance, especially when distance is larger than 800m. On the other hand, organic pollutants are more dependent on distance, and their dilution ability increases with the distance.

3.3.3 Additional measurement to lower requirement on distance Different distance will achieve different level of dilution and attenuation in contaminant concentration. In some cases, the predicted buffering distance may be neither practically nor economically feasible. For example, when the distance is 100 m and 200 m, the DAF of Zn in subsurface medium are 115.0 and 124.2 respectively, which are less than the RDAF of 135.

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Thus other measures should be taken to reduce the requirement on buffering distance. One possible method is waste pre-treatment before landfilling to weaken its leaching behavior, hence achieving the reduction of initial concentration of hazardous constitutes in leachate. The required reduction in leachate initial concentration was therefore simulated for different pollutants. Ni is not considered here as it need no additional horizontal buffering distance. The results show that a reduction of 1, 3, 12, 19, 22 ppm in Zn’s initial concentration by pre-treatment of waste is required to guarantee the safe drinking in the situation when separation distance is 350m, 300m, 200m, 100m, and 50m. To guarantee the concentration of 2,4-D reach the safe drinking criteria, an additional reduction of 0.5, 2.2, 6.0, 8.5 and 11.8 ppm in its initial concentration is required when separation distance is 120m, 100m, 80m, 50m. The simulated results indicate that even if the separation distance (350m, 300m, 200m,100m and 50m) is not fulfill the requirement of simulated buffering distance for Zn, the subsurface mediums can attenuate the Zn concentration to a risk-acceptable provided that the initial concentration of Zn in leachate is smaller than 119, 117, 108, 101 and 98 ppm. This means that an additional pre-treatment of waste before landfilling should be taken to achieve a reduction of 1, 3, 12, 19, 22 ppm in Zn’s initial concentration. Similarly, for 2, 4-D, a reduction of 0.5, 2.2, 6.0, 8.5 and 11.8 ppm in its initial concentration is required when separation distance is 120m, 100m, 80m, and 50m. The reduction in the initial concentration was shown to be effective in reducing the demand on buffering distance, especially for Zn. Simulated results indicate that in contrast to a reduction of 5.8 ppm (from 14.0 to 8.2 ppm), only a reduction a 3.0 ppm (from 101.0 to 98.0 ppm) is required to achieve a reduction of a half buffering distance (from 100m to 50 m).

(a)

1.2

Acceptable Zn concentration

117

101

Cocentration in wells, ppm

1

98

0.8

350 m distance 300 m distance 200 m distance

0.6

119 108

100 m distance 50 m distance

0.4 0.2 0 0

20

Initial of Zn, ppm 40 concentration 60 80 100

120

140

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0.025

130 m distance

120 m distance

100 m distance

80 m distance

(b)

50 m distance

Cocentration in wells, ppm

0.02

Acceptable 2,4-D concentration

0.015

8.2

11.5

14

17.8

0.01

0.005

19.5

0 0

2

ppm 4 Initial 6 concentration 8 10 of 2,4-D, 12 14

16

18

20

Fig. 6. Required initial concentration for Zn and 2,4-DCP at different distances

3.3.4 Uncertainty analysis The probabilistic distribution of these variables were determined in previous reports as shown in Table.3. The probability distribution of buffering distance with consideration of uncertainties is shown in Fig. 7a, Fig.7b and Fig.7c. The 95% confidence interval can be considered as the buffering distance required under less favorable conditions. It can be seen from Fig. 5 that in the unfavorable situation, the separation distance of Zn increased from 380 to 2600 m, and the buffering distance for 2,4-DCP protection distance increased from 135 m to 350 m. To guarantee the reduction of all contaminants to a risk-acceptable level under unfavorable conditions, a buffering distance of 2600 m is needed, which is much higher than the distance recommended by AESRD (400 m) and MEPPRC (800 m). Table 3 Uncertainty parameters and their values Parameters

Units

Mean

Standard deviation

Statistical distribution

References

i

mm

78

Normal distribution Normal distribution Normal distribution

Site-specific values

23

10 1 7

10

3

Normal distribution

Pin holes (0.1–5 mm) N

Holes (5–100 mm) Tears (100– 10,000mm)

4

holes/ha

Estimated from the reported values as shown in Table 1

Vadose zone thickness Aquifer thickness

m m

4 20

0.9 3

Normal distribution Normal distribution

Site-specific values Site-specific values

Groundwater velocity

m/s

1× 10−7

3 × 10−8

Normal distribution

Site-specific values

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8 5% percentile 50% percentile 95% percentile

7 Cs/Cd

6

10% percentile 90% percentile

5 4 3 2 Distance,m

1 0

(a)-2, 4-D

0

200

400

600

800

1000

1200

1400

1.6 5% percentile 50% percentile 95% percentile

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Fig. 7 Buffering distances with the consideration of uncertainties 3.4 Recommendation for determining buffering distance A reasonable separation distance is required between landfills and surrounding drinking water resources. However, examples

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in America, China, the EU and states of Canada show discrepancies in management strategies for buffering distance. For example, the USEPA did not explicitly provide the requirements of buffering distance, MEPPRC provides associated requirements but without specific values or methods to calculate the values, whereas some states of Canada specify the specific value of buffering distance. For landfills in which the hazardous components are the main organic pollutants or landfills with very low heavy metal components, setting a protective distance of 450 m should achieve the goal of protecting drinking water resources. However, if the landfill owner attempts to set a smaller distance, further simulation work should be conducted with the consideration of more drinking well locations, waste types and leaching behaviors, types and concentrations of hazardous contaminants in leachate, regional precipitation, and hydrogeological conditions. For hazardous waste landfill, the establishment of buffering distance is mainly associated with the concentration of the major contaminants in the leachate, the expected volume of leachate leakage, and the dilution capacity of underground media. When the simulated buffering distance is not economically or practically feasible, additional measures could be taken to reduce the requirements on dilution and attenuation of subsurface mediums. Many pollutants have the same or similar dilution and attenuation characteristics. One example is Zn and Ni. When the distance is certain, their DA is basically the same. At this point, if their RDAF difference is larger, the setting of the buffering distance needs to accommodate to the pollutants (Zn in this case) with larger RDAF, which is bound to cause excessive protection of the Ni. It is therefore suggested to lower admission requirements for nickel containing wastes, which will help to save the cost of pretreatment (solidification or stabilization). Of course, the owners can also have other options, for example, Increasing the demand for zinc containing waste, thus lowing the requirement on buffering distance. The relationship between the cost of curing stabilization and the relocation compensation cost involved in maintaining the buffer distance should be considered comprehensively. However, in any case, the setting of the buffer distance should take into consideration the degradation ability of the medium and the RDAF requirements of different pollutants. It is necessary to avoid the waste of resources / land caused by excessive protection, and to avoid the risk events caused by inadequate protection. The specific measures to be taken need to consider the balance between the pretreatment costs and the relocation compensation costs involved in maintaining the buffer distance. But in any case, the setting of the buffer distance should take into account the dilution and degradation of contaminants in subsurface medium, and the RDAF of different pollutants. It is necessary to avoid the waste of resources and land caused by excessive protection, and to avoid the risk events caused by inadequate protection. 4. Conclusion In this paper, the framework, method, and models to determine the buffering distance in shallow aquifers against the leachate contamination were constructed. This constructed framework and method applied in buffering distance simulation of a hazardous waste landfill located in a remote area in southwestern China that takes shallow aquifers as the major water resource. The results indicate that different pollutants require different buffering distances because of the variations in initial concentration in leachate, acceptable concentration in drinking wells, and attenuation and dilution behaviors in subsurface mediums. Nickel and 2,4-DCP, though more toxic, require a smaller distance than Zn because of their relatively small initial concentrations in leachate; Ni only requires a vertical separation distance of 4 m, while 2,4-DCP requires an additional 135 m horizontal distance, and 380 m for Zn. This simulated separation distance may be economically or practically infeasible. Therefore, other measures should be taken to avoid deterioration of water quality within the drinking well to an unacceptable level. The findings of this study suggest that a reduction of 1, 3, 12, 19, or 22 ppm in the initial concentration of Zn by waste pre-treatment can guarantee safe drinking water at separation distances of 350, 300, 200, 100, or 50 m, respectively. The framework and method to evaluate the buffering distance of landfill established in this paper will provide guidance for the buffering distance assessment of the existing landfill site and the buffering distance calculation of the new landfill site. For those landfills that their current separation distance is not great enough to guarantee the effective removal of hazardous constitutes in leachate, this paper also proposed the method to evaluate the effectiveness of additional measurement in reducing the requirement on buffering distance. Our findings also has great implications for environmental protection departments (e.g. USEPA, MEP.PRC) to draw up the standards related to the buffering distance of the landfill. First, for the MSW landfill, a specific value for buffering distance between the landfill site and the down-gradient wells with the consideration of precipitation, waste and leachate characteristics, and their national or regional variation. For HWL or other landfills that leachate is rich in heavy metals or other persistent pollutants, the required buffering distance varies and therefore it is not suitable to establish a specific value but reasonable method to calculate it. FUNDINGs This work was supported by the National Natural Science Foundation of China [grant numbers 51708529 and 61503219] and the Special Funds of the Ministry of Environmental Protection of the People’s Republic of China [grant number 2016YSKY14]. References Anne, T. S., Jes, J. R., Sebastian, H., 2018, Linking ecological health to co-occurring organic and inorganic chemical stressors in a groundwater-fed stream system, Science of The Total Environment, 642(15):1153-1162

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