Optimizing the scale of markets for water quality trading

Abstract

Applying market approaches to environmental regulations requires establishing a spatial scale for trading. Spatially large markets usually increase opportunities for abatement cost savings but increase the potential for pollution damages (hot spots), vice versa for spatially small markets. We develop a coupled hydrologic-economic modeling approach for application to point source emissions trading by a large number of sources and apply this approach to the wastewater treatment plants (WWTPs) within the watershed of the second largest estuary in the U.S. We consider two different administrative structures that govern the trade of emission permits: one-for-one trading (the number of permits required for each unit of emission is the same for every WWTP) and trading ratios (the number of permits required for each unit of emissions varies across WWTP). Results show that water quality regulators should allow trading to occur at the river basin scale as an appropriate first-step policy, as is being done in a limited number of cases via compliance associations. Larger spatial scales may be needed under conditions of increased abatement costs. The optimal scale of the market is generally the same regardless of whether one-for-one trading or trading ratios are employed.

Sustainable Water‐Resources Allocation Through a Trading‐Oriented Mechanism Under Uncertainty in an Arid Region

“…In general, water trading is often deemed as a market approach completely . However, it is a quasi‐public goods, which cannot be allocated by market completely .…”

“…For instance, the strategies for the food safety and ecology protection would be emphasized in the future social‐economic development of this region, thus the initial water right obligations of agriculture and ecology would be improved. Constraint (3) presents that water demand can be satisfied by the sum of the initial water assignment and the amount of transaction (when flow levels are low, medium, and high) Among them, is trading ratio in district j , which equals to the practical amount of trading contrasting expected the amount of transaction in a water trading system . Constraint (4) means that the water treatment plans for municipal and industrial users cannot exceed the maximum capacities for retreatment.…”

“…Constraint (3) presents that water demand can be satisfied by the sum of the initial water assignment and the amount of transaction (when flow levels are low, medium, and high) Among them, y à js =y js is trading ratio in district j, which equals to the practical amount of trading contrasting expected the amount of transaction in a water trading system. [31] Constraint (4) means that the water treatment plans for municipal and industrial users cannot exceed the maximum capacities for retreatment. Constraint (5) is the non-negative constraint.…”

Enhancement of surface water quality using trading discharge permits and artificial aeration

“…In the second scenario, WLA based on discharge permit market is revised after assuming artificial aerations in the critical points of downstream as recommended by Doyle et al (2014). For this purpose, two techniques are considered for aeration.…”

“…The former strictly depends on the location and dispersion of emission sources in an ambient discharge framework (Wittmann 2014). Even Doyle et al (2014) emphasized on the necessity of optimizing the scale of market prior to the feasibility and economical studies. In Chesapeake Bay watershed, Nishizawa (2003) discussed the potential benefits of effluent trading.…”