Suitable cropland use is not only beneficial for satisfying human daily demand, but also for controlling non-point source pollution leaks into adjacent rivers. Optimal industrial production levels are economical, and they also avoid water deterioration. With the promise of being lower than the total allowed emission cap, water use participants have to balance trade-offs between optimal production levels and emission amounts. Effluent trading seems to be a cost-effective method to reduce effluent emission as it allows effluent reallocation among different sectors. Because of changing hydrological information and continuous development of treatment technology, the effluent production ratio is regarded as uncertain and is characterized as polygonal budget sets. This study tries to control the total emission quantity by optimizing cropland use and non-agricultural production levels using effluent trading under uncertain future environments. To illustrate the feasibility of the proposed model, an application is conducted in Indonisian Citarum River. The application finds that the proposed model is able to (1) identify an optimal effluent trading scheme that balances various production plans from multiple water users; (2) balance the trade-off between total emission reduction and total benefit maximization by changing budget levels; and (3) ease the decision makers burden, avoid information losses or distortions, and guide them in adjusting farmland planning, production levels, and effluent trading results under uncertainty. Based on the results, managerial implications are analyzed in terms of (1) the optimal crop area planning in the agricultural sector and the optimal production level in nonagricultural sectors; and (2) the optimal effluent trading pattern that expands economic development without deteriorating water environments. Finally, the comparison analysis with a traditional deterministic model, verify that with the incorporation of robust parameters, flexible solutions are offered to decision makers that have different attitudes toward constraints-violation risks.
to increasing amounts of high concentrations of untreated pollutants flowing into water bodies, water purification capacities become extremely limited. To help alleviated this problem, marketbased controls have been introduced (De Lange et al., 2016). Among which, effluent trading is regarded as an efficient economic tool for pollution reduction (Nguyen et al., 2013). In real-world policies, effluent trading has been successfully carried out in the European Union (Wurzel, 2006), USA (Steinman et al., 2012), and other countries (Tietenberg, 2010; Narassimhan et al., 2018). One of the recent examples is the nutrient trading program for point and nonpoint sources initiated in Pennsylvania and the Greater Miami River watershed in Ohio (Nguyen et al., 2013).This method is likely to be copied by others if a global waste water emission limiting regime is implemented.
Different from additional effluent taxes, effluent trading has long-term impacts on economic growth and environmental protection (Xiong and Li, 2019). Effluent trading enables effluent rights reallocation among water users, and improves the economic efficiency of effluent emissions within a watershed (Zhang et al., 2017). Similar to groundwater transfer (Skurray et al., 2013), effluent trading rights can be considered as a type of cap and trade policy, as governments allocate the initial effluent emission rights and participants’ interactive trading processes. In this way, under the cap given by the government, the emission participants make a tradeoff between production levels and effluent trading, as production levels affect total effluent amounts. To achieve water use sustainability, water quality and quantity are two factors should be considered (Marzullo and Morita, 2018). To be specific, the quantity of freshwater is largely influenced by the water quality, which is further related to effluent amounts (Weidner et al., 2019). If they are not solved appropriately, the earth could become unsustainable (Soltani and Kerachian, 2018). It is, therefore, pivotal to optimize the trade-off between production levels and pollutant control using effluent trading.