Sediment discharge from erosion, urban run-off, and construction can cause environmental degradation. Governments try to regulate sediment, but the regulatory approach is costly to land owners. In principle, a market-based system could reduce costs, but the associated transaction costs are far too high, as market participants must find trading partners, negotiate, and seek government approval. In this paper, we propose a smart market design with an associated market clearing model for sediment

more »

... ischarge. Market participants bid for and offer tradable discharge allowances to a central auctioneer. The allowances correspond to kilograms of sediment discharge per year, as estimated by an erosion model. The auctioneer then uses a linear program to price and allocate sediment allowances in a given catchment. Participants do not trade bilaterally, but rather through a central pool, reducing transaction costs. The market design can use all available relevant hydrological data, quantifies environmental effects explicitly, and gives price signals based on the environmental features. Additionally, the initial rights could be scaled back or up when catchment is over or under-allocated to keep a market operator with revenue neutrality. We simulate the smart market for two catchments in Auckland, New Zealand. A c c e p t e d M a n u s c r i p t N o t C o p y e d i t e d 3 of choosing the length of the planning horizon, complexity in clearing a market with multiple receptors, and the inter-temporal impact effects over a long planning horizon. Ribaudo et al. (1999) from a view of non-point sources pollution reviewed water quality policies and analyzed policy instruments from areas such as economic incentives, liability and future research. They pointed out that market based instruments should require government intervention when externalities are an issue. Garrick et al. (2009) presented a conceptual framework for policy reform in environmental water quality market. The authors focused the analysis on legal and regulatory aspects, and used two case studies: the Columbia (USA) and Murray-Darling (Australia) for comparing the design of the markets. Shortle and Horan (2001) described the economics of non-point pollution control. They noticed that policies in the USA are focused on emission proxies, pollution levels and ambient concentrations; to reach environmental targets cost-effectively, policy makers should address stochasticity, trading ratios and monitoring. Shortle and Horan (2008) extended their review about quality trading and focused on aspects such as the definition of the commodity, the market rules, especially the exchange ratios between point and non-point sources, and setting of environmental caps. In particular, the authors addressed stochasticity, observing that nonpoint source emissions are inherently riskier than point source emissions. The authors pointed out problems with a bilateral trading scheme and the associated transaction costs. Woodward and Kaiser (2002) reviewed water quality trading in the USA: exchanges, bilateral programs, clearing houses and sole-source offsets. The authors noticed that none is cost-efficient and environmentally effective because the commodities are non-uniform and transaction costs (monitoring, bargaining, searching, and information) are high. McCann et al. (2005) reviewed transaction cost concepts and typologies, and identified reasons that make market-based policies fail. The authors pointed out that transaction costs are high in most environmental market-based instruments. Netusil and Braden (2001) evaluated 45,171 kg (much more than Case 1), would use only one technology, and would pay $212,307. Participants 1 and 20 do not trade. However, if the regulator wanted keep revenue neutrality, up-scaling could be done by setting α = 1.19. Table 4 summarizes the market outcomes. In this case, participants would receive an allowance. Total trade quantities traded after up-scaling would be 101,077 kg to seller and 101,077 kg to buyers. For instance, participant 3 would now pay $254,386 compared to $257,391 without the scaling which is like receiving an allowance of approx. $3,000 from the up-scaling. Participant 15 would now pay $211,972 which is