26 research outputs found

    The U.S. Nuclear Waste Impasse: Transportation Implications

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    For several years there has been an impasse, in the political branches, over how to make progress on dealing with the intractable problem of nuclear waste disposal in the United States. Currently, over 120 sites, spread across 39 states, host commercial spent fuel—many of these sites are former reactors that have become de facto interim nuclear waste storage sites, pending a permanent solution. Transportation considerations are central in this discussion. With the potential for Congress to make progress on this issue following the 2018 midterm elections, this article reviews the potential paths forward and considers possible implications for the transportation sector

    Greenwashing No More: The Case for Stronger Regulation of Environmental Marketing

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    Fraudulent and deceptive environmental claims in marketing (sometimes called “greenwashing”) are a persistent problem in the United States, despite nearly thirty years of efforts by the Federal Trade Commission (FTC) to prevent it. This Essay focuses on a recent trend in greenwashing - fraudulent “organic” claims for nonagricultural products, such as home goods and personal care products. We offer three recommendations. First, we suggest ways that the FTC can strengthen its oversight of “organic” claims for nonagricultural products and improve coordination with the USDA. Second, we argue for inclusion of guidelines for “organic” claims in the next revision of the FTC’s Guidelines for the Use of Environmental Marketing Claims (often referred to as the “Green Guides”), which the FTC is scheduled to revise in 2022. Finally, we assert that the FTC should formalize the Green Guides as binding regulations, rather than their current form as nonbinding interpretive guidance, as the USDA has done for the National Organic Program (NOP) regulations. This Essay concludes that more robust regulatory oversight of “organic” claims, together with efforts by the FTC to prevent other forms of greenwashing, will ultimately bolster demand for sustainable products and incentivize manufacturers to innovate to meet this demand

    Realigning the Clean Water Act: Comprehensive Treatment of Nonpoint Source Pollution

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    Nonpoint source pollution is the biggest threat to water quality in the United States today. This Article argues for stronger federal controls over nonpoint source pollution. It begins by examining the history of water quality regulation in the United States, including the passage and amendment of the Clean Water Act and the evolving definition of “navigable waters” over time. The Article then discusses recent rulemaking and litigation developments, including the Clean Water Rule, the Navigable Waters Protection Rule, and the County of Maui, Hawaii v. Hawaii Wildlife Fund case. It offers three recommendations. First, the Article calls for a congressional amendment to the Clean Water Act to require binding controls on nonpoint source pollution. Second, recognizing that an amendment to the Clean Water Act may not be politically viable, it offers an approach for controlling nonpoint source pollution through an amendment to the Safe Drinking Water Act. Finally, it identifies tools that interested states, local governments, and citizens’ groups can utilize to take action on nonpoint source pollution under existing law. This Article concludes that reductions in nonpoint source pollution will lead to significant improvements in the water quality of our nation’s lakes, rivers, wetlands, and coastal areas, to the benefit of human and environmental health

    A statistical downscaling framework for environmental mapping

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    In recent years, knowledge extraction from data has become increasingly popular, with many numerical forecasting models, mainly falling into two major categories—chemical transport models (CTMs) and conventional statistical methods. However, due to data and model variability, data-driven knowledge extraction from high-dimensional, multifaceted data in such applications require generalisations of global to regional or local conditions. Typically, generalisation is achieved via mapping global conditions to local ecosystems and human habitats which amounts to tracking and monitoring environmental dynamics in various geographical areas and their regional and global implications on human livelihood. Statistical downscaling techniques have been widely used to extract high-resolution information from regional-scale variables produced by CTMs in climate model. Conventional applications of these methods are predominantly dimensional reduction in nature, designed to reduce spatial dimension of gridded model outputs without loss of essential spatial information. Their downside is twofold—complete dependence on unlabelled design matrix and reliance on underlying distributional assumptions. We propose a novel statistical downscaling framework for dealing with data and model variability. Its power derives from training and testing multiple models on multiple samples, narrowing down global environmental phenomena to regional discordance through dimensional reduction and visualisation. Hourly ground-level ozone observations were obtained from various environmental stations maintained by the US Environmental Protection Agency, covering the summer period (June–August 2005). Regional patterns of ozone are related to local observations via repeated runs and performance assessment of multiple versions of empirical orthogonal functions or principal components and principal fitted components via an algorithm with fully adaptable parameters. We demonstrate how the algorithm can be extended to weather-dependent and other applications with inherent data randomness and model variability via its built-in interdisciplinary computational power that connects data sources with end-users