Collaborative Research: The Proper Scale for Environmental Markets with Application to Nitrogen Trading in the Neuse River Basin

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。过去几十年来，公共政策最引人注目的发展之一是人们普遍接受利用市场来实现环境监管目标。环境市场现在涵盖了空气和水污染、捕捞配额、濒危物种栖息地、湿地和溪流。例如，在水污染市场中，监管机构规定了排放总量，但各种来源的个别排放量是通过市场交易决定的。每个环境市场都是由特定的空间尺度定义的，即允许交易发生的地理区域的大小。在实践中，在空间尺度上有很大的差异。二氧化硫市场覆盖美国大陆，但水污染市场往往局限于相对地方性的流域。尽管存在这种观察到的差异，但很少有研究考察给定市场的规模是否在环境和经济上是最优的。确定污染排放市场的最优规模需要同时分析企业遵守污染减排的经济成本；污染的空间格局及其对生态系统和人口的损害；以及人类在市场中的行为，尤其是操纵价格的能力。这个合作研究项目将整合所有这三个因素，并确定北卡罗来纳州纽泽河流域氮污染交易的最佳空间尺度。一个结合了合规成本和人类行为的理论经济模型将决定污水处理厂氮排放的空间格局。该模型将与水文和生物地球化学模型相结合，将排放映射到水质的空间分布中。将进行一系列的经济实验室实验来检验经济学模型的预测。实验还将分析关于合规成本和水质空间分布的反馈在多大程度上减轻了价格操纵。利用这些元素，研究人员将分析各种空间尺度，并选择对社会产生最大净效益的空间尺度。这项研究最直接的影响是对纽塞河流域的市场设计。这将为未来关于北卡罗来纳州水质监管的辩论提供信息。一般原则将直接适用于类似的地方水质法规，例如长岛海峡的氮交易市场。这项研究项目将对水质监管产生更广泛的影响。它将提供一个框架，将《清洁水法》规定的现行水质监管与基于最佳空间尺度的替代框架进行比较。该项目还将影响更一般的环境法规的设计，因为其方法为分析许多其他环境市场的最佳空间尺度提供了模板。本项目由美国国家科学基金会自然与人类系统耦合动力学（CNH）项目资助。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).One of the most striking developments in public policy over the last several decades is the widespread acceptance of the use of markets to achieve environmental regulation goals. Environmental markets now span air and water pollution, fishing quotas, endangered species habitat, wetlands, and streams. In a market for water pollution, for example, a regulator specifies the total amount of emissions, but the individual emissions by various sources are determined by trading in the market. Each environmental market is defined by a particular spatial scale, that is, the size of the geographic region over which trades are allowed to take place. In practice, there is substantial variation in spatial scale. The sulfur dioxide market encompasses the continental U.S., yet markets for water pollution are often constrained to relatively local watersheds. Despite this observed variation, little research has examined whether the scale of a given market is environmentally and economically optimal. Determining the optimal scale of a pollution emissions market necessitates the simultaneous analysis of economic costs of firms complying with pollution reduction; spatial pattern of pollution and corresponding damages to ecosystems and human populations; and the behavior of humans in the marketplace, particularly the ability to manipulate prices. This collaborative research project will integrate all three of these factors and determine the optimal spatial scale for nitrogen pollution trading in North Carolina's Neuse River basin. A theoretical economic model that combines compliance costs and human behavior will determine the spatial pattern of emissions of nitrogen from wastewater treatment plants. This model will be coupled with a hydrological and biogeochemical model that maps emissions into a spatial distribution of water quality. A series of economic laboratory experiments will be conducted to test the predictions of the economics model. The experiments also will analyze the degree to which feedback about compliance costs and the spatial distribution of water quality mitigates price manipulation. Using these elements, the investigators will analyze various spatial scales and select the one that yields the greatest net benefits to society.The most immediate impact of this study is the market design for the Neuse river basin. This will inform the future debate over North Carolina water quality regulation. The general principles will be directly applicable to similar local water quality regulations, such as the market for nitrogen trading in the Long Island Sound. The study project will impact water quality regulation more broadly. It will provide a framework to compare the current water quality regulation as specified by the Clean Water Act to an alternative framework based on the optimal spatial scale. The project also will influence the design of more general environmental regulation as its methodology provides a template for analyzing the optimal spatial scale of many other environmental markets. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.