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We assess whether current public support mechanisms for CO₂ transport infrastructure align with the economics and maturity of the emerging carbon capture and storage (CCS) industry, and identify more effective policy design principles. The investment risk associated with transport & storage (T&S) infrastructure is a main barrier to scaling CO₂ transport networks, yet dominant policy instruments (volumetric subsidies for capture) do not address this constraint. State-led approaches can enable final investment decisions but may create long-term subsidy dependence, while purely regulatory frameworks can provide long-term certainty without overcoming the initial chicken-and-egg problem. Drawing on the economics of CO₂ networks, evidence from CCS governance, and lessons from offshore wind and long-duration energy storage, we argue that effective CCS policy should prioritize de-risking T&S investment at earlystages, in particular through socialization of network costs, before transitioning toward performance-based instruments asthe market matures.

Scientific assessments are critical in informing households, communities, businesses, institutions, and governments as they respond to intensifying climate hazards. As climate change impacts accelerate, the pace of assessment and integration of science with decision-making and action must accelerate as well. A network of U.S. climate assessment efforts could rapidly synthesize actionable science and case studies to inform climate response strategies. To support future processes, this paper presents a selection of foundational topics needing assessment and near-term research across climate impacts, risks, and actions from the perspective of the U.S. and some of its key regions, environments, and economic sectors.

Federal Energy Regulatory Commisson Order No. 1920 requires PJM to incorporate state policies into its long-term transmission modeling. States have many policies that affect electricity supply and demand. But only policies described in a way that PJM can model will affect the amount of transmission need that PJM identifies. Policies that PJM can straightforwardly convert into model inputs include demand-side policies, resource retirements, resource-specific capacity targets, and renewable or clean energy standards. This issue brief describes each of the transmission-driving policy inputs states can provide and illustrates their importance using Policy Integrity’s own model.

Last year, the Trump Administration ended longstanding efforts to determine the extent to which pollution has disproportionate impacts on different communities, including overburdened and disadvantaged communities. But, at the same time, it reaffirmed its commitment to performing benefit-cost analysis to analyze the consequences of regulations, including environmental regulations. These approaches are mutually inconsistent. A proper benefit-cost analysis simply cannot be done without considering distribution of a policy’s impacts. Often, the populations affected by government policies vary from the median in significant ways. Heterogeneity by age, race, income, and other factors is relevant to the assessment of the benefits and costs of particular policies for three principal reasons. On the benefits side, certain groups face higher levels of exposure to environmental harms and higher harms from exposure to an additional unit of pollution than does an average member of the population. Also, certain groups have higher vulnerability to particular exposures. And, on the cost side, certain groups bear higher burdens because of differences in geography, spending patterns, and other behaviors. This article provides a robust review of the scientific, epidemiological, and economic literature for each of these mechanisms, surveys what agencies have already done, and sets forth an agenda for future research.

Across the federal government, agencies are beginning to integrate artificial intelligence (A.I.) tools into their operations. One area where A.I. may have particular benefits is in rulemaking, where lengthy processes and review procedures can slow down regulatory policymaking. Using A.I. tools may enable agencies to make the regulatory process significantly more efficient, enabling the government to govern more effectively and responsively. But the use of A.I. in rulemaking may sacrifice caution for the sake of increased efficiency, raising the risk that agencies finalize rules that are fundamentally flawed. This report discusses how the structure of A.I. models shapes their outputs and explores the opportunities and challenges of A.I. use for rulemaking.

How should one think about the Supreme Court's decision in Loper Bright Enterprises v. Raimondo? On its face, Loper Bright is a meaningful yet measured Supreme Court decision that requires agencies to act consistently with how courts read statutes. But for the Trump Administration, the opinion has served as an invitation to eliminate many federal regulations, including those aimed at protecting the environment and public health.

Many see the recent changes to New York’s Climate Leadership and Community Protection Act (CLCPA) as a retreat from New York’s climate ambition. But the recent CLCPA amendments could still allow for a cost-effective and robust program to reduce New York's greenhouse gas emissions—if the state acts promptly and seizes all available opportunities to enable effective emissions reductions.

Contrary to the suggestion that the 2023 update to the Office of Management and Budget’s Circular A-4 “ignored [a] consensus” favoring higher discount rates, the positions of the nine peer reviewers on the 2023 update were much more nuanced and diverse. Yet ironically, to the extent almost all reviews might have agreed on at least one point, it is this: virtually nobody favored the course of action now adopted by the Trump Administration, of simply retaining the twenty-year-old, outdated guidance on discounting without any updates.

This article highlights a range of opportunities to refine the federal rulemaking process. These measures, by streamlining and speeding rulemakings, can help support more durable policymaking by increasing the likelihood that final rules will complete judicial review in one term and avoid congressional repeal.

In this issue brief, we examine recent steps EPA has taken to warp its approach to risk evaluation under the Toxic Substances Control Act, the law that charges EPA with setting standards to address health and safety risks posed by toxic chemicals. In particular, we focus on two recent moves: (1) amendments to EPA’s final risk evaluation for formaldehyde, and (2) proposed changes to a foundational rule that governs how EPA conducts risk evaluations—known as the Framework Rule. In both, EPA makes a series of unsupported changes that will bias the agency’s analysis of the scope of risks from toxic chemicals and how best to address them. These moves will inevitably tee up flawed decisions and weak standards that fail to protect the public against dangerous chemicals.