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Please Note: If you are not a federal government employee and would like to attend a seminar, please contact Carl Pasurka (pasurka.carl@epa.gov) in advance so that you can gain access to the building unless someone else is listed in the seminar write-up.

Environmental Economics Seminar: Consequences of the U.S. Clean Water Act and the Demand for Water Quality
February 23, 2016, 1:30 - 3 pm
Room 4128, William Jefferson Clinton West Building, 1301 Constitution Ave., NW, Washington, DC
Joseph S. Shapiro (Department of Economics, Yale University)
David Keiser (Department of Economics, Iowa State University)
EPA Contact: Carl Pasurka, 202-566-2275
Abstract: Since the 1972 U.S. Clean Water Act, government and industry have invested over $1 trillion to abate water pollution, or $100 per person-year. But over half of US stream and river miles still have water quality so poor that they violate standards. This paper assembles the most comprehensive set of files ever compiled on water quality and its determinants to study changes in water pollution since the Clean Water Act, their causes, and their welfare consequences. The paper obtains three sets of findings. First, most types of water pollution have fallen dramatically since 1972, though were declining at nearly the same rate before then. Second, we study the contribution of the Clean Water Act to these declines. Third, we compare the willingness-to-pay for these declines in water pollution, as measured through the housing market, against their costs.

Climate Economics Seminar: Mitigation and Adaptation for Coastal Impacts from Sea Level Rise
February 25, 2016, 10 - 11:30 am
Room 4128, William Jefferson Clinton West Building, 1301 Constitution Ave., NW, Washington, DC
Delavane Diaz (Electric Power Research Institute)
EPA Contact: Carl Pasurka, 202-566-2275
Abstract: Coastal sector impacts from sea level rise (SLR) are a key component of the projected economic damages of climate change, a major input to decision-making and design of climate policy. Moreover, the ultimate costs to coastal resources will depend strongly on adaptation, society’s response to cope with the impacts. The first part of this talk presents a new optimization model to inform global estimates of coastal impacts, the Coastal Impact and Adaptation Model (CIAM). CIAM determines the optimal strategy for adaptation at the local level, evaluating over 12,000 coastal segments, as described in the DIVA database, based on socioeconomic characteristics and the potential impacts of relative sea level rise and uncertain sea level extremes. I will present a deterministic application of CIAM that demonstrates the model’s ability to assess local impacts and direct costs, choose the least-cost adaptation, and estimate global net damages for several climate scenarios that account for both global and local components of SLR (Kopp et al, 2014). CIAM finds large potential for coastal adaptation to reduce the expected impacts of SLR compared to the alternative of no adaptation, lowering global net present costs through 2100 by a factor of seven, although this does not include initial transition costs to overcome an under-adapted current state. In addition to producing aggregate estimates, CIAM results can also be interpreted at the local level, where retreat (e.g., relocate inland) is often a more cost-effective adaptation strategy than protect (e.g., construct physical defenses). The subsequent part of this talk presents related work exploring a specific climate threshold response, a potential disintegration of the West Antarctic Ice Sheet (WAIS). I will review the current scientific understanding of WAIS, identify methodological and conceptual issues related to incorporating threshold responses in integrated assessment models (IAMs), and demonstrate avenues to address some of them. Specifically, the threat of WAIS disintegration is represented in a stochastic hazard IAM framework (in an approximate way) that combines emulation of geophysical dynamics, expert knowledge, and learning. The DICE-WAIS model presented here is used to illustrate the relationships between scientific uncertainties, policy objectives, and economically-efficient strategies in the face of a specific climate threshold response.



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