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Groundwater quality management is challenging due to the fate and transport of multiple pollutants in the porous media, extensive polluters, and late aquifer responses to pollution reduction practices. Water quality trading (WQT) is an economically incentive-based policy for waste load allocation (WLA) in water resources. This study evaluates the effectiveness of 12 WLA scenarios on reducing groundwater nitrate and chloride, simultaneously using MODFLOW and MT3DMs. Here, the theoretical efficiencies of multi-pollutant WQT are also testified out of these scenarios by developing environmental, economic and practical conditions. For these purposes, Varamin plain, south-eastern Tehran, Iran, was chosen as the study area where both point and non-point pollution sources were considered in WQT. At first, an allowable quality limit (AQL) for the groundwater was set for pollutants regarding groundwater impairment and simulation outcomes. The AQL violations of WLAs were then calculated in addition to their marginal abatement costs and penalties. Here, nitrate abatement ranges between 3.3–18.3%, while chloride abatement ranges between 4.5–23.6%. Our findings show that, 5 WLA scenarios could pass the conditions of not violating any AQLs, and gaining remarkable benefits (> 25%) for all market attendants. Potential WQT strategies are finally prioritised regarding their viability and marginal costs. According to these conditions, trading discharge permits between wastewater treatment plants (WWTPs) with 50% nitrate removal (sellers) and farmers (buyers) are recommended as the optimal WQT alternative, which imposes no penalties or land-use changes. Here, the overall benefits of sellers and buyers exceed 47% and 81%, respectively, in comparison with not attending any WLA scenario. Highlights Varamin aquifer quality is analyzed in 12 WLA scenarios with point and non-point sources. Wastewater treatment and altering crop pattern can reduce pollutants in 10 years. Multi-pollutant WQT is theoretically feasible and has economic benefits. Four conditions are emphasized in order for the feasibility study of potential WQT. A practical WLA with low benefits has privilege over a highly beneficial WLA without practicability
Introduction
Groundwater is an essential water resource, particularly in arid and semi-arid areas, and its quality management is necessary prior to regional developments (Petersen-Perlman et al. 2018). Decreasing groundwater quality can adversely affect human health and disrupt the available water supply for domestic, agricultural, and even industrial purposes. Thus, quality enhancement is a main objective of different practices in aquifer management (Szymkiewicz et al. 2020). However, quality variations by point and non-point pollution sources impose some uncertainty for sustainable groundwater management (Jamshidi et al. 2018). Nitrogen fertilizer in agriculture remains a major contributor to water pollution, largely driven by the increasing global demand for food (Gonzalez Zapata et al. 2024). Excess nitrogen compounds can lead to significant water quality degradation, impacting ecosystems, human health, and economic activities (Kariman et al. 2018), as nitrate (NO3−) poses serious health risks (Rodriguez-Galiano et al. 2018). Nitrate and chloride (Cl−) are two classic groundwater pollutants which can be influenced by both water extraction and pollution discharges. Groundwater withdrawal and reducing its level can increase remained nitrate and chloride concentrations (Zhu et al. 2019). Fertilizer application in agriculture, manure wastes, and the wastewater of residential areas cause leaching nitrate to the aquifer (Alam et al. 2024; Najafi Alamdarlo et al. 2016). Land-use changes and hydrogeological factors also contribute to nitrate variation (Wang et al. 2024). Hydrogeological conditions coupling with nitrification or denitrification processes are also effective on nitrate variations (Torres-Martínez et al. 2020). Waste load allocation (WLA) strategies are policies recommended in large scale (e.g. basins) for controlling and managing these types of pollutants (Alfarrah and Walraevens 2018; Menció et al. 2016). They can include reducing agricultural fertilizer application for nitrogen management (Karlović et al. 2022), or reducing water softener application to control chloride sources (Overbo et al. 2021). The efficiency of WLAs deeply depends on aquifer conditions, polluters, and their practicability (Matiatos et al. 2019; Samadi-Darafshani et al. 2021).
Water quality trading (WQT) is a market-based WLA that uses trading to control pollution, offering flexibility and cost-effectiveness (Sadak et al. 2020). WQT introduces a cost-effective strategy to motivate polluters monitoring the quality of water resources themselves (Shortle et al. 2016). It presents polluters an alternative to couple their pollution abatement duties with economic incentives gained by trading credits (Corrales et al. 2017). WQT, as the cap-and-trade policy for water quality management, is applicable for major pollutants like nitrogen compounds. Recently, a study investigated the outcomes of land use and farming practices on the nitrogen pollutant trading in Lake Taupo (Spicer et al. 2021). Here, although several paths were theoretically identified by modelling, the efficiencies were reliant on farmers' values. It means that there is a gap between theorized WQT operations and what really occurs and the study expressed that the cap-and-trade policy should be aligned with the users’ social and economic conditions to achieve their goals. In another study, agricultural activities were the critical nutrient pollution source in the studied basin. Therefore, it has been explored how market-based strategies in WQT can address a win–win solution for pollution reduction in basins (Tabaichount et al. 2019). Sustainable WQT requires analyzing pollution from both point (PS) and non-point sources (NPS), setting total maximum daily loads (TMDL), defining allowable quality limits (AQL), and evaluating market participants' economic benefits. Groundwater modelling system (GMS) modules, as MODFLOW and MT3DMs, are simulation tools commonly used for groundwater modelling (Raetz 2022). By these means, nitrate with chloride transport and partial degradation can estimate the effectiveness of WQT programs and WLA scenarios in long-term operation (Cox et al. 2013). It also provides a framework to determine regionally allowable and practical water quality limits (AQL) and optimize pollutant load allocations in basin (Sadak et al. 2020).
This study develops an integrated method for sustainable groundwater WLA using a multi-pollutant WQT framework. It simulates aquifer conditions to evaluate WLA strategies like municipal WWTP operations and crop pattern changes for water quality improvement. These strategies are incorporated into an incentive-based discharge permit market. Using MODFLOW and MT3DMS, NO3- and Cl- concentrations are predicted over a decade. The framework tests WLA and WQT scenarios for pollution reduction and economic benefits. It also outlines a 4-step pre-evaluation for WQT feasibility, market impact, and profitability, offering a comprehensive approach to groundwater management.
Materials and Methods
Methodology
This study followed a three-step method. First, groundwater quality was simulated with a focus on the concentrations of NO3 and chloride. In the second step, different scenarios were testified based on the quality status of aquifers and standard limits to reach a cost-effective WLA policy among PS and NPS. These steps provided a framework for evaluating the economic benefits of implementing discharge permit market in the study area. Consequently, in the third step, the WLA strategy with practical treatment strategies and the highest profitable trading market was finally selected based on four innovative conditions (Fig. 1). Following these conditions is recommended in order to pre-evaluate the practicability and feasibility of defined any WQT program.
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Fig. 1
Methodology steps of this research
Study Area
The methodology is validated on the Varamin plain aquifer, located in the south-eastern of Tehran province, Iran between the latitude of 35.39° N and 35.07° N and longitude of 51.26° E and 51.55° E. The area of this plain is approximately 957 km2. The average annual temperature is about 14 °C. In the Varamin plain area, using the available data from 1967 to 2012, the monthly average precipitation changes from 51 mm (January) to 1.8 mm (September) while the monthly average evaporation is between 739 mm (July) and 114.2 mm (February) (Ministry of energy 2013).
In the recent decade, the droughts gradually decreased groundwater recharge in the study area as water extraction increased due to the rising demands. Since this water resource was rapidly depleting, its status has changed to “prohibited” by the state for additional water extraction. Consequently, its quality management has become more critical (Noghreyan et al. 2022).
Varamin plain supplies the agricultural and drinking water of two counties, Pakdasht and Varamin. However, it simultaneously receives the raw sewage of their urban residential areas in the north and the drainage of farmlands in the centre. The farmlands cover 86% of the entire plain. Approximately 70% of farmlands in this area are covered with wheat and barley crops, 15% with corn and the remaining 15% includes vegetables. In this area, the secondary treated wastewater of Eastern Tehran wastewater treatment plant (WWTP) is also available for artificial aquifer recharge (Ministry of energy 2013; Nouri et al. 2020). The primary PS in this area is the discharges of Varamin (WW1), Pakdasht (WW2), and Eastern Tehran WWTP (WW3), while the significant NPS is the leaching of farmlands. Table 1 outlines the specifications of these point sources. Here, the blueprint of WW3 is the approximate location for discharging this treated effluent to the plain.
Table 1. Point emission sources with their blue prints and specifications
WWTP | Blueprint | Population covered (Capita) | Average flow (m3/s) |
|---|---|---|---|
WW1 | 35° 24′ 0″ N, 51° 53′ 0″ E | 284,000 | 0.52 |
WW2 | 35° 28′ 0″ N, 51° 48′ 0″ E | 351,000 | 0.65 |
WW3 | 35° 31′ 0″ N, 51° 37′ 0″ E | 1,350,000 | 2.5 |
Accordingly, this study searches for a cost-effective and environmentally sound WLA that responds to the question that the construction of which facility, WW1 or WW2, should be prioritized regarding groundwater quality variations and total costs based on WQT program?
The geological structure of study area is illustrated in Fig. 2. Here, the approximate locations of point sources, groundwater level contours, flow directions, in association with the location of piezometer wells are marked. Since the area is relatively large, it is divided into six zones based on land-uses and observation wells with available water quality data. This zoning provides a more elaborate framework to show the sensitivity of groundwater to WLA scenarios in both T3: the short term (3 years), and T10: long term (10 years) periods. In the study area, 8 observation wells with available water quality data were highlighted to monitor the quality and groundwater level of the plains during the study period. Figure 3 shows the average precipitation and evapotranspiration (mm) in the plain during the modelling period.
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Fig. 2
a Geological structure of study area with its b information, and c zoning polluters
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Fig. 3
Precipitation and evapotranspiration during modelling time in Varamin plain
Simulation and Calibration
The conceptual model of the Varamin plain aquifer was developed using a combination of topographic data from DEM maps, initial groundwater levels obtained from the first simulation period (October 2009), and bedrock information from geophysical surveys. This conceptual model provided a foundation for understanding the aquifer's structure and behavior, enabling effective simulation of groundwater quality and levels (Ministry of energy 2013). To represent the study area accurately, the model domain was discretized into a grid with a 250-m resolution. Boundary conditions were defined using general head boundary (GHB) conditions based on groundwater level observations from 42 piezometer wells. Recharge sources included infiltration from agricultural and urban areas, while discharge involved groundwater extraction and natural outflows. These boundaries were refined with observed groundwater level data to ensure accurate representation of the aquifer's natural flow. For simulation purposes, the Varamin aquifer was modeled using the GMS software (Version 10.1). Groundwater levels were simulated using the MODFLOW, while water quality simulations for nitrate and chloride transport were performed using the MT3DMs module. Geological heterogeneities, such as variations in hydraulic conductivity, were incorporated using the geological map of the area, as shown in Fig. 2. The calibration process was carried out using data from 2009 to 2011, comparing observed groundwater levels and quality data from the piezometers with simulated values (Souri et al. 2023). Observed groundwater levels and quality data from 42 piezometer wells (Pz) were compared with the simulated values to assess the model's accuracy. Calibration metrics included the coefficient of determination (R2) and the root mean square error (RMSE), calculated using the equationsc1 and 2. The R2 values, which were above 0.9, and the RMSE indicated strong agreement between the observed and simulated data, confirming the model’s accuracy. The calibration ensured that both groundwater levels and pollutant concentrations were accurately represented.
1
2
where yi and are observed and calculated values at time i, respectively, and is the average of observed values. Moreover, n is the sample size equals the number of piezometer wells. To evaluate the impact of different WLA strategies, 12 scenarios were developed and tested by the calibrated model. These scenarios were designed to address point and non-point emission sources, targeting simultaneously nitrate and chloride concentrations reduction in the aquifer. WLA scenarios included various configurations of WWTPs and crop pattern changes. The model's validation involved simulating the groundwater quality and levels under these scenarios over T3 and T10. Outputs from the software provided insights into the effectiveness of each scenario in reducing multi-pollutant concentrations in the aquifer. The scenarios were qualitatively ordered based on their environmental impact, with the most environmentally friendly scenario being the one that achieved the lowest average pollution concentration across all observation wells for both nitrate and chloride over T10. This comprehensive modeling approach ensured that the simulation and calibration processes were robust and reliable, providing a solid basis for evaluating the proposed WLA strategies and their potential to improve groundwater quality in the Varamin plain aquifer.WLA Scenario
12 WLA scenarios were designed based on the calibrated model to examine and compare their impacts on groundwater quality. These scenarios are categorized in two main classes, as outlined in Table 2. Scenarios labelled S1.1–S1.9 target pollution control by WWTPs (PS), while scenarios labelled S2.1–S2.3 addresses agricultural pollution control (NPS). The first class (S1.1–S1.9) focuses on WLA strategies targeting PS through the construction and operation of WWTPs, with variable locations and nitrogen (N) removal efficiencies. Here, 25% and 50% TN removal in different WWTPs are based on the conventional efficiency of WWTPs (e.g. activated sludge or MLE) in nitrogen removal as similarly used in previous studies for WLA (Jamshidi and Niksokhan 2016). The second class (S2.1–S2.3) aims to control agricultural discharges (NPS) by altering the primary crop patterns in the study area. Here, the ratio of 15–70% crops area is compatible with the annual variations (± 25%) of crop production in the study area where wheat and barley usually includes 40–50% of production area (Souri et al. 2023). We should also add that all proposed WLA scenarios should be both technically feasible and aligned with legal and environmental standards for groundwater quality improvements. In Table 2, S0 represents the baseline status of the simulated aquifer without implementing any WLA. ‘A’ also denotes the affected zone of the study area, as showed in Fig. 2.
Table 2. The definition of different WLA scenarios in this study
Targeted emission sources | Scenario | Description |
|---|---|---|
S0 | Basic scenario | |
Point sources (PS) | S1.1 | WW2 with 25% N removal + aquifer recharge (A2) |
S1.2 | WW2 with 50% N removal + aquifer recharge (A2) | |
S1.3 | WW1 with 25% N removal + aquifer recharge (A4) | |
S1.4 | WW1 with 50% N removal + aquifer recharge (A4) | |
S1.5 | S1.1 + S1.3 | |
S1.6 | S1.2 + S1.4 | |
S1.7 | WW3 with 50% N removal + aquifer recharge (A1) | |
S1.8 | S1.1 + S1.3 + S1.7 | |
S1.9 | S1.2 + S1.4 + S1.7 | |
Non-point sources (NPS) | S2.1 | Wheat and barley: 15%; corn: 70%; vegetables: 15% |
S2.2 | Wheat and barley: 15%; corn: 15%; vegetables: 70% | |
S2.3 | Wheat and barley: 50%; corn: 25%; vegetables: 25% |
The WLA scenarios are defined in accordance with the regulatory limits required for regional applications, considering the feasibility and accessibility of these limits in relation to agricultural production, the capacity of WWTPs, and the consistency of associated financial costs. In scenarios S1.1–S1.9, the abated N was allocated to the target residential areas as reduced NO3 concentration (%). This approach is due to the fact that Pakdasht and Varamin cities lack wastewater collection and treatment systems, and consequently the domestic wastewater is conventionally discharged to the groundwater. N abatement in S1.1–S1.9 means that NO3 discharge and infiltration to groundwater would be reduced from the residential areas by constructing and operating WWTPs (WW1 or WW2) with different NO3 removal efficiencies. These scenarios' impacts were then analyzed and compared in the observation wells of the targeted zone (A2 and A4) and the whole study area.
For NPS in S2.1–S2.3, each crop's water footprint was referred to as well as the average yield and cultivation area. Therefore, the impacts of changing crop patterns on the study area in the form of water extraction and pollution reduction were estimated based on the average water footprints of targeted zones compared with S0. The modifications to the model were implemented by adjusting the outputs of the initially created model and subsequently calibrating it based on the provided inputs. Specifically, in scenarios S1.1 to S1.9, nitrogen removal was achieved by reducing the concentration of NO3 at the discharge points of the associated WWTPs, based on the mentioned WWTPs and their efficiency. This approach aimed to decrease the nitrogen load entering the groundwater system. Conversely, in scenarios S2.1–S2.3, the changes involved altering the water levels, either by increasing or decreasing, and modifying the pollution discharge reduction strategies in the relevant agricultural areas, based on the related crops and their specifications containing the crop yield, blue, green, and grey water footprint. These adjustments were intended to evaluate the impact of water level variations and enhanced pollution control measures on the overall quality of the groundwater. Here, according to recent literature, crop yields were estimated 0.52 kg/m2 for wheat and barley, 3.23 kg/m2 for corn, and 3.89 kg/m2 for vegetables (Vogel et al. 2019; Yousefi 2018). Accordingly, grey water footprint would be reduced by 30%, 23%, and 27% by applying S2.1, S2.2 and S2.3, respectively.
It should be noted that in the study area, chloride is mainly influenced by quantitative variation of groundwater due to annual recharges. It is assumed that wastewater treatment or changing crop patterns can barely reduce chloride concentration in domestic and agricultural discharges. In a nutshell, chloride is a pollutant mainly affected by water volume rather than treatment systems.
WLA scenarios were inputted to the calibrated model separately, and the outputs were obtained for NO3 and chloride concentrations in eight observation wells. Each scenario's impact on pollutants concentrations is estimated according to the average concentration of all observation wells for each timespan. Afterwards, WLA scenarios were qualitatively ordered according to their impacts on groundwater quality. Here, the most environmentally friendly WLA scenario is a scenario with the lowest pollution concentration in the whole plain on average concerning both NO3 and chloride concentrations in T10. Nevertheless, a sustainable WLA scenario requires further investigation from an economic perspective.
Economic Analysis
For the economic evaluation of WLAs based on discharge permit markets and their benefits, it is necessary to initially calculate related total costs (TC). For PS, TC is attributed to both the construction and operation of WWTPs during their lifetime. The TC can be defined per required biochemical oxidation demand (BOD) and N removal efficiencies in WWTPs regarding WLA scenarios. Equation 3 has been recently developed with this purpose (Jamshidi and Niksokhan 2016) and is similarly used in this study.
3
where CW is the annual capital and operation costs (M$/yr) in which M notes as a million in units, Q is the annually average wastewater inflow (m3/s), and T is the annual capital and operating cost of WWTPs per unit volume (M$/m3) which is calculated by Eq. 4.4
Here, TBOD and TNO3 are the costs of reducing BOD and NO3 pollutants, respectively (M$/m3). These values depend on the required efficiency as calculated by Eqs. 5 and 6, respectively.
5
X denotes the abatement of BOD concentration in the treatment plant ranges between 0 and 1. In this study, BOD concentration reduction for all treatment plants is considered as 0.9 which means that WWTPs should at least remove 90% of BOD concentration of wastewater in any cases and scenarios. However, it is noteworthy that BOD is only used for cost evaluations and is not included in environmental and water quality assessment in simulation and WLA.
6
where Z represents NO3 removal efficiency of WWTPs and it ranges between 0 and 1. For example, in S1.1 with 25% N removal, Z equals 0.25.Equations 5 and 6, developed by Jamshidi and Niksokhan (2016), can assess WWTP costs per pollutant removal. These equations account the accumulated capital and operating costs per pollution treatment (BOD and NO3 removal) and inflow (Q). As noted by developers, the background database of these equations rests on more than 50 operating WWTPs in Iran, mostly with mechanically aerated units like activated sludge. However, they are verified with global reports and their robustness is confirmed through rigorous data analysis (Jamshidi and Niksokhan 2016). Therefore, they can more or less estimate the overall treatment costs, particularly in regions where the tariffs of energy consumption are low. Yet, the coefficients can be modified to adapt different regions, economy, or with new technologies.
In addition to economic evaluation of different WLA scenarios, this study emphasizes on calculating the economic benefits of possible discharge permit markets in the study area. For this purpose, the average marginal costs (MC) of PS should be calculated for determining the costs of permits and penalties. This was calculated by Eq. 7. It is noteworthy that for PS, there is no need to subtract the total cost of PS-based WLA scenarios with S0 because the whole abatements in S1.1–S1.9 in these cases are additional to the basic scenario of S0.
7
where is the average marginal cost of each PS-based WLA scenario (M$.L/yr.mg), R is the reduction of pollutants concentration for each WLA scenario with S0 (mg/L). CW is defined earlier.For NPS, cost analysis was carried out differently. The crop MC was determined by the amount of production of each crop (Eq. 8), in association with all costs (Cf) and benefits (Bn) of producing each product (Eqs. 9 and 10). Based on the calculated benefits, the net benefit of each crop was calculated per m2.
8
P is the annual farm productions (kg/year), A is the cultivated area (m2), and Y is the average crop yield in the study area (kg/m2yr).
9
where Cf is the annual farming costs (M$/yr) and Ca is the average cost of cultivating a crop unit (M$/kg). Ca is the estimated costs according to annual payments required for cultivation including labour, seeds purchase, the costs of fertilizer, pesticide, installation and irrigation, agricultural machineries, and other services. In addition, Ct shows the transaction costs of switching crop pattern in each NPS-based WLA scenario. For example, changing from wheat to corn or vegetables in a farmland requires costs related to training workers and farmers, replacing equipments, preparing lands, education and official documents (M$/yr).10
Bn is the annual net benefit (M$/yr), SP is the product’s local selling price (M$/kg), and P and Cf were defined earlier. This equation calculates the net benefit for agricultural scenarios depending on the type of crops and land use. On the contrary to , the of farming WLAs () should contain the subtraction with S0. Otherwise, there would be duplications in calculating costs for lands without changing crop patterns. In other words, the reduction in overall benefits of farmers, or their total economic losses (CL) was calculated and equalized the total costs of these diffuse pollution sources. It should also be considered that in NPS-WLA scenarios (S2.1–S2.3), WWTPs are not required to be equipped with tertiary treatment units for nitrogen removal. Therefore, their related costs are limited to the BOD abatement of domestic wastewater (TNO3 = 0). It means that WWTPs should at least remove BOD to the required level regardless of PS or NPS WLA scenarios. These are shown in Eqs. 11 and 12.
11
12
where, is the marginal cost of NPS-based WLA scenarios (M$.L/yr mg), Bi is the net benefit of S0 (M$/yr) without implementing groundwater quality conservation programs and environmental punishments, CL is the annual economic loss of farmers for WLA scenarios without considering punishments (M$/yr), TBOD, Q, R (mg/L) and Bn (M$/yr) were defined earlier.WQT Assessment
Prior to the benefit assessment of WQT strategies, the possible seller and buyer of the tradable discharge permits should be determined according to their which can be calculated by or . Nevertheless, in order to induce some economic incentives for polluters for attending a water quality conservation program, it is required to define a price for monetary punishments. Therefore, according to the estimated MCs of discharge permits, the penalty price was calculated by Eq. 13.
13
where F is the total cost of environmental fines (M$/yr), and MCA is the average MC of all scenarios (M$.L/mg). E represents the violations (mg/L) remains in WLA scenario which is the negative difference of simulated and predicted pollutants from the AQL. The AQL is a water quality limit or standard for each that is regionally set for minimizing the ecological damages. 2 is a factor to enforce a stronger incentive for participants to comply with the regulations, encouraging their active involvement in the market. S0's total cost equal the calculated penalties, multiplied by the amount of violations.This punishment would be allocated per violations to polluters in scenarios which cannot satisfy the thresholds of the AQL. An environmental violation equals the difference between the average water quality of observation wells of each scenario with the AQL concentrations of NO3 and Cl−. scenarios with concentrations below AQL were marked as “none-violating” (NV), whereas others were classified as “violating” (V). It should be noted that AQL was estimated based on simulation tool with the purpose of improving water quality potential of aquifer by considering the practical reductions of PS and NPS. What makes AQL different to the conventional water quality standards is that: AQL is regionally oriented derived based on the receiving environment, and its limits for pollutants concentration in the water body should be matched with the accessible technologies of polluters for pollution reduction in short-term. Accordingly, the benefits of WQT are the economic savings (%) of scenarios determined as TCA in comparison with the total costs of S0's scenario (Eq. 14).
14
Here, TCA is the aggregate of CW and CL (M$/yr), in addition to probable penalties for scenarios with violations (V). However, F equals 0 in market-based WLA scenarios as they should be selected from strategies without violations (NV).
In WQT, since the directive of market-based environmental protection is founded on economic incentives, both permit sellers and buyers should find some economic motivation for this policy. Therefore, this study evaluates the total costs of sellers and buyers separately. Total costs for seller are calculated using Eq. 15.
15
Here, TCs is the total costs of sellers which is relatively compensated with money gained out of selling permits (M$/yr) and K is the total outcome of sold permits (M$/yr). Obviously, buyers are those market participants who do not pay for operating WWTPs or changing crop patterns but only for buying permits from sellers as Eq. 16.
16
where denotes the marginal costs of sellers and equals or depending on WLA scenario (M$.L/mg). D represents the differences of estimated groundwater quality with AQL (mg/L).Results
Model Evaluation
Quantitative and qualitative model calibration was carried out on the studied area to assess simulation accuracy. Due to the balance of groundwater resources, the model was calibrated in a steady-state, focusing on the hydraulic conductivity (HC) parameter. Based on drilling logs, pumping test results, and observation well data, the HC was evaluated, and its zoning is presented in Fig. 4a. During the unsteady period, the specific yield (SY) parameter was also calibrated based on the average SY coefficient. Figure 4b shows the zoning of the SY coefficient of the aquifer after recalibration. According to the qualitative data, the aquifer's longitudinal dispersion coefficient was also analyzed and recalibrated based on the three-dimensional parameters of the aquifer (Fig. 4c).
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Fig. 4
Zoning of the calibrated parameters in Varamin aquifer model
The results show that the northern part of the aquifer, due to the plain soil coarseness, has higher HC and SY of about 22 m/day and 0.13, respectively. By moving towards the outlet of the aquifer in the plain's southern borders, these coefficients decrease so that they reach about 4 m/day (HC) and 0.03 (SY). The variations of longitudinal dispersion coefficient of aquifer depend on the polluters and the unsaturated area thickness, which has higher values in the central and northern parts of the aquifer about 35 m2/day, while it is about 1 m2/day in the southern part and the outlet of the aquifer. Figure 5 illustrates the simulated groundwater level at T0 with the locations of observation wells.
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Fig. 5
Groundwater level with the locations of observation wells at T0
Water Quality
Figure 6 shows the simulated NO3 and Cl concentrations at T0. Here, it is apparent that the distribution of pollutants is not uniform over the plain, where NO3 and Cl concentrations are relatively high at the north and central-south parts of the plain. In the study area, the average NO3 and Cl concentrations are 28.4 AND 18.5 mg/L, respectively. These concentrations should be abated to less than AQL. Here, AQL for NO3 and Cl were determined as 23 and 15 mg/L, respectively. As previously defined in Section "WQT assessment", AQL is a water quality limit regionally set for minimizing ecological damages by providing a practical range for polluters to reduce their pollution. If the AQL of NO3 was set very strictly below 15 mg/L, the simulation verified that it would be not be achieved even by controlling all PS and NPS discharges in the long term (T10).
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Fig. 6
Simulated NO3 (left) and Cl (right) concentrations at T0
Figure 7 illustrate the variations of NO3 and Cl concentrations at T10 in WLA scenarios among all the observation wells, and their average in the study area, comparing with the AQL. Here, 8 scenarios can meet NO3 standard limit, while 7 scenarios can reduce Cl concentration below the AQL. It is noteworthy that only 3 PS-based WLA scenarios (S1.6, S1.8, and S1.9) can simultaneously satisfy both NO3 and chloride AQLS. It is interesting to note that higher nitrate removal (by WWTPS) does not linearly reduce nitrate concentrations in groundwater. Table 3 summarizes the abated pollutant concentrations in all WLA scenarios and determines their violation status regarding the AQL. Therefore, WLA scenarios like S1.1 and S1.7 are still environmentally violating (V), while others are non-violating (NV).
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Fig. 7
Minimum (min), maximum (max) and the average of CL (A) and NO3 (B) concentrations at T10 among all observation wells for all WLA scenarios
Table 3. Abated average pollutants’ concentrations in different WLAs in T10
Scenario | Abated pollution (%) | Abated pollution (mg/L) | Difference with AQL | Violation status | ||||
|---|---|---|---|---|---|---|---|---|
NO3 | Cl | NO3 | Cl | NO3 | Cl | NO3 | Cl | |
S0 | – | – | – | – | − 5.40 | − 3.49 | V | V |
S1.1 | 5.3 | 6.5 | 1.3 | 1.1 | − 0.17 | − 0.79 | V | V |
S1.2 | 6.8 | 7 | 1.7 | 1.2 | 0.19 | − 0.70 | NV | V |
S1.3 | 3.3 | 4.8 | 0.8 | 0.8 | − 0.65 | − 1.08 | V | V |
S1.4 | 3.9 | 5.6 | 0.9 | 0.9 | − 0.51 | − 0.94 | V | V |
S1.5 | 10.6 | 12.3 | 2.6 | 2.1 | 1.14 | 0.19 | NV | NV |
S1.6 | 11.7 | 16.9 | 2.9 | 2.9 | 1.40 | 0.97 | NV | NV |
S1.7 | 4.1 | 4.5 | 1.0 | 0.8 | − 0.45 | − 1.14 | V | V |
S1.8 | 12.7 | 15 | 3.1 | 2.5 | 1.65 | 0.64 | NV | NV |
S1.9 | 14.8 | 16.8 | 3.6 | 2.8 | 2.16 | 0.95 | NV | NV |
S2.1 | 18.3 | 23.6 | 4.5 | 4.0 | 3.03 | 2.09 | NV | NV |
S2.2 | 10 | 12.9 | 2.4 | 2.2 | 0.98 | 0.28 | NV | NV |
S2.3 | 15.3 | 19.6 | 3.7 | 3.3 | 2.29 | 1.41 | NV | NV |
Figures 8 and 9 illustrate the effectiveness of WLA scenarios on NO3 and Cl concentrations abatement (%) in the study area for T3 and T10. These figures indicate that among PS-based WLA, S1.6 and S1.9 have the highest NO3 abatement for T3 (4.3%) and T10 (12.7%), respectively. These two scenarios also have the highest Cl abatement in T3 (5.9%) and T10 (> 15%). It means that 50% N removal by WW1 and WW2 and reusing the treated effluent for artificial recharge (S1.6) during 3 years (T3) can reduce NO3 (4.3%) and Cl (5.9%) concentrations in the groundwater more than other PS-based WLA scenarios. The impact of this scenario in T10 is also identical to S1.9, with 50% N removal by all three WWTPs. Furthermore, among NPS-based WLA scenarios, S2.1 would have the highest NO3 abatement for both T3 (11.6%) and T10 (18.3%). S1.3 and S1.7 have the least NO3 (3.3%) and Cl (4.5%) abatement for T10, respectively. It implies that NPS-based WLA is relatively more effective on groundwater quality than PS-based WLA.
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Fig. 8
NO3 reduction of WLA (%) in aquifer in 3 (T3) and 10 years (T10)
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Fig. 9
Cl reduction of WLA (%) in aquifer in 3 (T3) and 10 years (T10)
Economic Evaluation
This study mainly emphasizes that appropriate WLAs are strategies that meet environmental demands, and simultaneously, contribute economic incentives. Figure 10a expresses the total cost (TC) required for switching from S0 to each WLA scenario. It shows that S1.3 and S1.9 require the least (38 M$/yr) and highest (311 M$/yr) costs, respectively. Comparative results show that PS-based scenarios are relatively more costly than NPS-based WLA scenarios, mainly because farmers can gain economic benefits from selling agricultural products. However, WWTPs are typically public services in the study area without economic benefits. The marginal cost is also calculated per the average impact of each WLA scenario on groundwater quality for T10. According to Fig. 10b, the marginal costs for NO3 removal range between 8.0 M$.L/mg yr (S1.3) and 42.4 M$.L/mg yr (S1.7). It means that 1mgNO3/L removal during 10 years in Varamin groundwater, on average, requires annually 14.6 M$ in S1.6. 1mgCl/L removal by S1.6 requires 22.1 M$, which implies that chloride abatement in groundwater is more costly than NO3 in the study area. Since MC accounts the costs of WLA per its effectiveness, it can be used as an appropriate tool for: (1) comparing the efficiency and finding a cost-effective discharge permit market, and (2) defining environmental penalties. Applying S1.3 would result in the least cost per unit pollution reduction for both NO3 and Cl pollutants. Accordingly, S2.1 has the most benefits for groundwater quality.
[See PDF for image]
Fig. 10
A Total cost (M$/yr) required for each multi-pollutant WLA scenario (left), and B the marginal cost for a unit reduction of NO3 and Cl pollutants (M$/yr/mg/L) (right)
WQT
Tables 4 and 5 show the results of trading discharge permits for the two pollutants, including the benefits for sellers and buyers. Here, 8 WLA scenarios can potentially trade NO3 and Cl credits in multi-pollutant WQT. S2.1 has the highest benefit for its sellers (35.7% for NO3 and 37.4% for Cl permits), in which corn farmers can sell their credits to other farmers. This trade is also economically beneficial for buyers as they benefit 71% and 71.4% in NO3 and Cl permit markets, respectively.
Table 4. WQT results for NO3 credits
Scenario | Seller | Buyer | Marginal costs (M$/yr)/(mg/L) | Buyers cost (M$/yr) | Penalty per violation (M$)/(mg/L) | Sellers total cost (M$/Yr) | Total WLA costs | Benefits for the seller (%) based on S0 | Benefits for the buyers (%) based on S0 |
|---|---|---|---|---|---|---|---|---|---|
S0 | – | – | – | – | 45.1 | – | 243.7 | – | – |
S1.1 | – | – | 9.0 | – | 45.1 | 55.5 | 55.4 | – | – |
S1.2 | WW2 | WW3, WW1 | 9.8 | 1.9 | 45.1 | 53.2 | 55.2 | 3.5 | 98.4 |
S1.3 | – | – | 8.0 | – | 45.1 | 67.8 | 67.8 | – | – |
S1.4 | – | – | 9.1 | – | 45.1 | 67.7 | 67.7 | – | – |
S1.5 | WW2, WW1 | Farmers | 12.6 | 14.4 | 45.1 | 71.5 | 85.9 | 16.8 | 88.2 |
S1.6 | WW2, WW1 | Farmers | 15.1 | 21.1 | 45.1 | 78.5 | 99.6 | 21.2 | 82.6 |
S1.7 | – | – | 42.4 | – | 45.1 | 231.8 | 231.8 | – | – |
S1.8 | WW1, WW2, WW3 | Farmers | 42.0 | 69.2 | 45.1 | 228.4 | 297.6 | 23.3 | 43.2 |
S1.9 | WW1, WW2, WW3 | Farmers | 41.0 | 88.3 | 45.1 | 222.9 | 311.2 | 28.4 | 27.5 |
S2.1 | Corn farmers | Vegetables, wheat and barley farmers | 11.7 | 35.4 | 45.1 | 63.6 | 99.0 | 35.7 | 71.0 |
S2.2 | Vegetable farmers | Corn, wheat and barley farmers | 30.6 | 30.2 | 45.1 | 166.8 | 196.9 | 15.3 | 75.2 |
S2.3 | Wheat and barley farmers | Corn, vegetables farmers | 22.5 | 51.4 | 45.1 | 122.4 | 173.8 | 29.6 | 57.8 |
Table 5. WQT results for Cl credits
Scenario | Seller | Buyer | Marginal costs (M$/yr)/(mg/L) | Buyers cost (M$/yr) | Penalty per violation (M$)/(mg/L) | Sellers total cost (M$/yr) | Total WLA costs | Benefits for the seller (%) based on S0 | Benefits for the buyers (%) based on S0 |
|---|---|---|---|---|---|---|---|---|---|
S0 | – | – | – | – | 74.2 | – | 258.8 | – | – |
S1.1 | – | – | 17.6 | – | 74.2 | 106.2 | 106.2 | – | – |
S1.2 | – | – | 19.7 | – | 74.20 | 107.1 | 107.1 | – | – |
S1.3 | – | – | 16.0 | – | 74.2 | 118.5 | 118.5 | – | – |
S1.4 | – | – | 17.8 | – | 74.2 | 114.4 | 114.4 | – | – |
S1.5 | WW2, WW1 | Farmers | 19.1 | 3.6 | 74.2 | 82.3 | 85.9 | 4.2 | 97.2 |
S1.6 | WW2, WW1 | Farmers | 26.9 | 26.1 | 74.2 | 73.5 | 99.6 | 26.2 | 79.8 |
S1.7 | – | – | 88.2 | – | 74.2 | 295.9 | 295.9 | 0.0 | 0.0 |
S1.8 | WW1, WW2, WW3 | Farmers | 72.6 | 46.4 | 74.2 | 251.2 | 297.6 | 15.6 | 64.2 |
S1.9 | WW1, WW2, WW3 | Farmers | 70.7 | 66.9 | 74.2 | 244.4 | 311.2 | 21.5 | 48.3 |
S2.1 | Corn farmers | Vegetables, wheat and barley farmers | 17.7 | 37.0 | 74.2 | 62.0 | 99.0 | 37.4 | 71.4 |
S2.2 | Vegetable farmers | Corn, wheat and barley farmers | 52.1 | 14.7 | 74.2 | 182.2 | 196.9 | 7.5 | 88.6 |
S2.3 | Wheat and barley farmers | Corn, vegetables farmers | 35.45 | 50.1 | 74.2 | 123.7 | 173.8 | 28.8 | 61.3 |
Regardless of theoretical results, this study emphasizes that 4 eco-practical conditions should be controlled in order, as pre-evaluations to introduce potentially efficient and robust WLA scenario for trading discharge permits. These conditions are as follows:
Multi-pollutant WLA should not preferably violate the AQLs (environmental condition).
Permit sellers and buyers should considerably benefit from WQT participation (economic condition).
WLA should be easy and practical, particularly for multi-pollutant permit sellers (practical condition).
Mostly recommended WQT scenario is the policy with the least marginal costs (optimal condition).
Note: market can theoretically assure WQT durability, particularly during unpredicted conditions.elasticity against pricing permits
Accordingly, S1.1, S1.3, S1.4 and S1.7 cannot satisfy the 1st condition, while S1.2 can only have a single-pollutant discharge permit market based on NO3 as Cl removal does not meet the AQL. Based on the 2nd condition for multi-pollutant WQT, accounting for the aggregated financial benefits of permit buyers and sellers is required for trading multiple credits. Figure 11 illustrates the total benefits of WLA scenarios for buyers and sellers by considering both pollutants. For example, WW1 and WW2, as the sellers of NO3 and Cl permits in S1.6, gain 47.4% higher benefits than S0, while it is 81.2% for the farmers (buyers). The initial costs of NO3 and Cl credits for trading are assumed equally as the annual marginal costs are rather identical about 12.6 M$ and 19.1 M$ per one unit pollution abatement (mg/L) in groundwater, respectively.
[See PDF for image]
Fig. 11
Market benefit for sellers and buyers in each WLA scenario
Based on the results, S1.6, S1.8, S1.9, S2.1 and S2.3 are scenarios that permit sellers may gain considerable benefits (e.g. > 25%). According to the 2nd condition, this specification is an advantage for these WLA scenarios. It is mainly because trading discharge permit is more likely a dynamic game with complete information in which the first player is the permit seller. Without gaining considerable benefits, the first player (sellers) may not participate in the market, and the required permits cannot be provided. On the contrary, permit buyers' benefits guarantee the permit market's durability. Permit sellers can freely sell permits at even higher prices than MC to increase their economic benefits. Since an enhancement in permit price will reduce buyers’ benefits, having a robust wide range for buyers’ benefits can be referred as an advantage for WQT due to its potential in permit price elasticity. For example, 85% benefit of buyer shows some space for safe benefit reduction of buyers without spoiling the 2nd condition. In a nutshell, the direct economic benefits of sellers may induce their participation in WQT. In contrast, buyers’ benefit is more like an assurance for sellers in future to gain higher benefits or, more importantly, compensate unpredicted treatment costs utilizing trading permits with higher prices. Accordingly, S1.9 is not recommended due to the risks of an inelastic market. The 3rd condition emphasizes that it is necessary to block impractical alternatives and choose easy-to-use WLA policies for WQT despite economic outcomes. Here, S1.5 and S1.6 are much easier to practice than S1.8, S2.1 and S2.3 as constructing WW1 and WW2 with limited NO3 removal are more practical and easier to use than crop changes among several farmers (S2.1–S2.3). Moreover, the MCS of NO3 abatement are 12.6, 15.1, 42, 11.7, and 22.5 M$.L/mg, respectively, while these are 19.1, 26.9, 72.6, 17.7, 35.4 M$.L/mg for Cl, respectively. Therefore, despite the least MCS of S2.1, S1.6 is chosen as an alternative for WQT with the highest priority as it passes the 1st, 2nd, and 3rd conditions in order and has the relatively lowest MC (4th condition). In longer terms (> 10 years), S2.1 can also be considered as a WQT alternative in decision-making.
In this study, there are three types of trading discharge permits. (1) In S1.2 (for NO3), WWTPs are both the sellers and buyers of credits in which farmers are not necessary to participate in trading. Thus, PS-PS market is theoretically applicable for trading NO3 permits in S1.2, but it was not recommended as there were limitations in NO3 and Cl abatement by WWTPs (1st condition). (2) In S1.5, S1.6, S1.8, and S1.9, trading permits can occur between PS-NPS, in which WWTPs sell their multiple credits (NO3 and Cl) to the farmers. Including both PS and NPS in trading is the advantage of these strategies that can improve market dynamics and pricing flexibility. (3) S2.1–S2.3 point to the NPS-NPS market between farmers, in which WWTPs only remove basic pollutants, like BOD, to the minimum safe level for wastewater reuse. Here, relatively lower marginal costs are mainly originated from the fact that farmers can enhance their income by changing crop patterns and selling new agricultural products. It implies that integrating WQT with other local markets can improve WQT motivations, even for WWTPs.
Discussion
WQT refers to simultaneously establishing a local market to achieve sustainable conditions through water quality enhancement and economic motivation (Cook and Shortle 2022; Saby et al. 2021). In this study, different WLA scenarios were designed to evaluate possible impacts on 10-year groundwater quality and related economic issues. These WLA scenarios were pivoted on NO3 and Cl parameters recently recommended by Lasagna et al. 2020. Their research expressed that NO3 and Cl are the most critical groundwater pollutants manageable through land-use changes and WWTPs the efficiencies of these practices are similarly verified in the current study for PS and NPS emission sources based on simulation in MODFLOW-MT3DMs.
MODFLOW and MT3DMs were emphasized as efficient tools for groundwater modelling (Raetz 2022). This simulation for Varamin plain revealed that pollution abatement by land-use changes was more efficient than PS-based WLA policies. This result contradicts Wada et al. (2021). They evaluated eight land-use and wastewater treatment scenarios concerning their impacts on nutrient loads in groundwater. In that study, groundwater quality was more sensitive to the construction of WWTP than in other scenarios (Wada et al. 2021). This contradiction is due to regional characteristics, as NPS pollution is almost expanded the entire Varamin plain. Olaoye et al. (2021) recently evaluated land-use changes' independent and synergistic impacts on groundwater quality variables in four periods Their results expressed that changing land use may lead to more significant flows but relatively more pollution removal regarding the variations of 8 water quality parameters.
It is recently revealed that the policy of limiting allowable pollution concentration needs to consider the combination of the regulator's pollution objectives and stakeholders' demands for easy-to-use applications. On this condition, water quality violations would be minimized for 20 years (Dinar and Quinn 2022). Likewise, it was previously emphasized the practicability of pollution removal in WWTPs (Jamshidi and Niksokhan 2016) and the economic motivations of markets for permit sellers (Imani et al. 2017) in WLA are as vital as pollution removal efficiencies. To the new outcomes of this research, the economic objectives with practical issues are determining durable groundwater quality management. The four conditions should be considered for a hypothetical WQT assessment. In other words, clinging to MC only for WQT assessment is not recommended as the environmental (e.g. AQL), economic (e.g. market benefits), and practical specifications of a WLA in a region are also critical. A recent study resulted in recommendations for preventing agricultural non-point source pollution, fostering cooperation between upstream and downstream regions, and expediting the sewage environmental tax system's implementation. The findings suggest that the proposed method can effectively manage sewage levels and inform decision-making for improving water quality (He et al. 2022).
According to recent estimations, the construction of WWTP may cost between 155 and 185 million USD, while maintaining an operating NO3 removal facility costs 72 million USD. However, for WQT assessment, it is required to consider the total costs annually, including the aggregate of construction and operating costs per flow rate and removal efficiency, as considered in Eqs. 4 and 5. This is because allowable permits for trading are typically determined annually concerning annual TMDL policies. In addition, Canning and Stillwell (2018) revealed that the riparian buffer zones could provide indirect, non-quantifiable advantages for maintaining or developing water treatment which is more practical for surface water quality management. However, other technologies and practices, such as denitrifying spring bioreactors (Stephenson et al. 2021), can apply to conventional agricultural and urban NPS removal technologies for groundwater quality management.
WQT strategies should simultaneously keep pollution concentration below AQL and provide economic incentives for the participants. Permit sellers are mainly responsible for pollution abatement in an area, while buyers economically support treatment costs through the market. Consequently, permit sellers would commence a game if they find considerable economic incentives, easy-to-use treatment systems, and cooperative administrative systems (Niksokhan et al. 2009a, b). However, this game may last if permit buyers have demands, freely participate in the market and buy the credits. Buyers have three options: (1) construct a treatment system, (2) buy credits from the sellers, and (3) pay for the penalties (Niksokhan et al. 2009a, b). Pricing credits and penalties are an economic tool in WQT that should be implemented realistically concerning the sellers’ abatement costs and buyers’ income. In the first step, sellers and buyers should theoretically gain benefits by participating in the market. Accordingly, this study separately compared the benefits of sellers and buyers for 8 WLA scenarios. Previously, an economic model has been developed to achieve a benefit-maximizing rule for farmers and define an optimal model using a survey and analyzing results for a WQT program (Fleming et al. 2018). They claimed that the program's success and environmental benefit depend on its ability to encourage farmers who previously did not participate in the past cost-sharing programs to adopt more crop acres in WQT. In another study, 147 different WQT programs and their details in 355 distinct markets were analyzed to evaluate markets concerning the demographic, political, environmental and economic aspects (BenDor et al. 2021). They reported that only one-half of markets have become operational, and new markets have also been declining. The prevalence and existence of water quality markets are nuanced by local political ideology, urban infrastructure, water body impairment, and environmental regulations.
Nonetheless, researchers are still working on discharge permit markets' theoretical and practical effectiveness. For example, the current study has considered urban infrastructure by including the construction and operation of new WWTPs, groundwater quality impairment and environmental regulations have been addressed by groundwater quality simulation and introducing regionally driven AQLs. Then four initial conditions were introduced in the final step for a hypothetical WQT assessment. In another recent study, a hypothetical water quality market was simulated in which one group of farmers were assigned as N permit sellers, and the others were permit buyers (Filippelli et al. 2022). They realized that in this single-pollutant water quality market, the trading between buyers and sellers reduces the total costs by 12%. Here, lower participation can result in lower trade benefits. Likewise, the current study has revealed that PS-PS discharge permit markets are mostly impractical due to the limitations on preventing environmental violations. On the contrary, NPS-NPS discharge permit markets are cost-effective but challenging to practice compared with PS-NPS discharge permit markets. Changing land use is not costly if the farmers’ income is included in economic evaluations. Compared with the construction and operation of WWTPs, changing land use requires convincing several farmers, making these strategies not easily applicable.
Conclusion
This study rigorously evaluated the effectiveness of 12 multi-pollutant WLA scenarios for the reduction of nitrate and chloride concentrations simultaneously in groundwater. It also re-evaluated the viability of these WLA scenarios as WQT programs regarding 4 Eco-practical conditions. The innovative and practical findings of this research are as follows:
Effective WLA strategies: Results showed that implementing WWTPs with 50% nitrate removal (scenario S1.6) and transitioning crop production from wheat/barley to corn were the most effective practices in the studied area. The immediate priority should be given to these WLA strategies that can significantly reduce NO3 and Cl− concentrations at the studied aquifer over a decade.
Multi-Pollutant WQT: The proposed multi-pollutant WQT proved economically beneficial for both permit sellers and buyers. It could offer greater market flexibility and pricing alternatives compared to a single-pollutant discharge permit market. This new approach can guide policy-makers in designing more complex cap-and-trade programs to motivate pollution reduction and provide financial benefits for all stakeholders.
Eco-practical conditions: The study proposed a step-by-step pre-evaluation method based on four conditions for assessing the viability of multi-pollutant WQT program prior to its implementation. The 1st condition confirms that WLA scenarios are environmentally non-violating. The 2nd condition approves the economical benefits of market participation for all polluters. The 3rd condition makes sure that the chosen WLA is practical in the region. Finally, the filtered alternatives are then allowed for optimization, like their least marginal costs.
Regarding the main findings above, this study emphasized on underscoring the balance of practicality and economic incentives that highlighted constructing and operating WWTPs. Taking strategies with higher economic revenues only causes impracticability and uncertainty for WQT. In addition, accurate cost assessments—including WWTP construction, operation, and permit trading expenses—are essential for predicting the success of WQT programs. These data can offer valuable insights for stakeholders in making informed decisions regarding investment and policy direction.
Acknowledgements
Iranian Water Resource Management Co. under contract No. S.07.1401 with University of Isfahan partially contributed to the funding of this research.
Author Contributions
M.A.Souri. led the investigation, prepared the methodology, did software analysis, validated, analyzed, did data curation, visualized, and wrote the original draft. S.Jamshidi. conceptualized the study, prepared the methodology, did analysis, supervised, did project administration, and wrote (reviewed and edited) the article. H.K.Moghaddam. collected resources, did software analysis, validated, and visualized the study.
Data availability
The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.
Declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Abbreviations and List of Symbols
Cultivated area (m2)
Allowable groundwater quality limit
Net benefit of S0 (M$/yr)
Annual net benefit (M$/yr)
Biochemical oxidation demand (5-day)
Average cost of cultivating a crop unit (M$/kg)
Annual farming costs (M$/yr)
Chloride
Annual economic loss of farmers for WLA scenarios without considering punishments (M$/yr)
Transaction costs of switching crop pattern in NPS-based WLA (M$/yr)
Annual capital and operation costs (M$/yr)
Differences of estimated groundwater quality with AQL (mg/L)
Violations (mg/L) remains in WLA scenario which is the negative difference of simulated and predicted pollutants from the AQL
Total cost of environmental penalties (M$/yr)
Hydraulic conductivity
Total outcome of sold permits (M$/yr)
Million
Marginal cost
Marginal costs of sellers and equals MCW or MCA depending on WLA scenario (M$.L/mg)
Average MC of all scenarios (M$.L/mg)
Marginal cost of NPS-based WLA scenarios (M$.L/yr.mg)
Average marginal cost of each PS-based WLA scenario (M$.L/yr.mg)
Nitrogen
Nitrate
Non-point source
Without AQL violation
Annual farm productions (kg/yr)
Point source
Piezometer well
Annually average wastewater inflow (m3/s)
Reduction of pollutants concentration for each WLA scenario with S0 (mg/L)
R-square
Root mean square error
Product’s local selling price (M$/kg)
Specific yield
Annual capital and operating cost of WWTPs per unit volume (M$/m3)
Costs of reducing BOD pollutant (M$/m3)
Total cost
The aggregate of CW and CL (M$/yr)
Total costs of sellers which is relatively compensated with money gained out of selling permits (M$/yr)
Trading discharge permit
Total maximum daily load
Costs of reducing NO3 pollutant (M$/m3)
United States Dollar
AQL violation
Waste load allocation
Water quality trading
Wastewater treatment plant
BOD abatement in WWTPs ranges between 0 and 1
Average crop yield in the study area (kg/m2yr)
NO3 abatement in WWTPs and it ranges between 0 and 1
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