Trading Systems for Nonpoint Source Pollution

Several types of permit trading systems for nonpoint-source discharges have been proposed: an ambient permit system, a zonal permit system, and a pollution offset system.

Morgan et al. (2000) proposed a marketable permit trading scheme to manage the nitrate pollution of groundwater supplies for rural communities with intensive agricultural activity with the level of nitrates monitored at the level of drinking water. The authors used a soil and

groundwater transportation model to predict the nitrate leaching rates from a particular crop area. According to their model, the contribution of each farm is weighted by a delivery coefficient determined exogenously. The permit trading system is defined as an ambient permit system, with the permits being denominated in terms of nitrate emissions measured at a receptor point (e.g., a well).

Their proposed ambient permit system integrates three models: a production model, a soil model, and a groundwater model. The production model defines the profits as a function of yield, with yields being defined as a function of fertilizer, agricultural practices, and crop rotations. Next, the abatement costs are defined as the difference in profits before any regulation is imposed and the profits after the regulations are adopted. The farm minimizes its abatement costs, where the costs are defined as the sum of the loss of profits and the expenditure on permits. The soil model estimates the water and the nitrogen emissions associated with each practice, and the groundwater model simulates the nitrate’s fate to the water through

groundwater.

In addition to estimating the delivery coefficients, the marginal abatement costs, and the initial permit allocation, the authors also underlined the importance of the baseline and the timing. The authors simulated the trading outcomes over the span of several years and assumed that the permit price is determined in a repeated auction. Farmers make the trading decision by comparing the equilibrium price with the marginal abatement cost. The abatement cost is higher for the farms whose emissions have the greatest impact on the water quality measured at a specific well. Their model is one of the first papers that showed how using different tools (i.e., a soil and a groundwater model) can be used to transform the nonpoint-source problem into point source, and how point source policies can be applied to the nonpoint.

Ermoliev et al. (2000) discussed the trading mechanisms in pollution permit markets. Their normative findings showed that, in the case of an ambient permit system with a single receptor, the market cost minimization solution is also the least-cost solution regardless of the transaction type: bilateral or sequential. In the case of multiple receptors, the convergence of the

solutions is assured if the transactions are sequential and multilateral, and hence a source supplying permits needs at least two trading partners.

Lock and Kerr (2007), in a background paper, analyzed the decisions that need to be made for setting up a nutrient trading system, such as identifying a target, allocating the

allowances, and setting up a monitoring system. According to them, the water quality goal needs to take into account both cost benefit analysis and political aspects. Next, a nutrient trading system should be made available only to the nonpoint sources. Furthermore, the trading cap needs to be expressed in units that can be easily allocated across the polluting sources. They also emphasize the importance of mapping the nutrient losses to the allowances needed.

In a follow-up paper, Kerr et al. (2007) introduced a permit trading system for nonpoint sources for a watershed that drains in a lake (a single receptor point). Zonal permits are created to account for the time it takes emissions leaving the field to reach the lake. Hence, zones are distinguished by years, rather than distance, and the permits depend on the year in which the emissions reach the lake. In their setting there is a market for each type of permit, where the permit type is given each year. The trading cap (the maximum acceptable emissions in a given year) associated with a market determines the total number of permits of a given type. Hence, permits across different markets can be traded at a ratio of one to one.

Prabodanie et al. (2009) proposed a nitrate-emissions-based pollution offset trading system applicable to a small-scale watershed. They used a leaching loss model to estimate the nitrate emissions from different land uses and the size of the permit required at field level, a transport model to estimate the a matrix of delivery coefficients, and a linear programing model that used the information based on the demand and supply of permits to determine the optimal trades. The size of a nitrate permit is equal to the estimated nitrate emissions from a land-use

option at field level, where the land-use options are defined as a combination of factors such as type of crop or stock, timing, method and rate of fertilizer applications, and other land

management practices. The authors used a nitrate transport model to estimate a matrix of delivery coefficients. They simulated the impact of field emissions at a given receptor at

different points in time. A linear relationship is assumed between the emissions leaving the field and the impact at the receptor. Finally, they used a linear program to determine the price and permit allocations that maximize the total surplus in the permit market subject to water quality standards and initial permit allocations. The authors simulated the outcomes of their proposed trading system using a hypothetical groundwater watershed draining into a lake, with six farms and five land options. An environmental authority decides environmental standards for two receptors and allocates the nitrate permits among the farms to satisfy the standards. Within the trading system, every farm estimates the profits from each land-use option and submits five bids/offers. The prices depend on the farm size and are equal to shadow prices of the individual environmental constraints. Their findings showed that the pollution offset trading, while

incurring small transactions costs, can achieve environmental constraints in a cost efficient way.