Nonpoint source pollution is “the leading remaining cause of water quality problems” in the country. Approximately “half of all water pollution” choking our rivers comes from nonpoint sources, degrading at least “80,000 miles of rivers and streams” and “2.5 million acres of lakes and reservoirs.” Though states may disagree on the proper degree of regulation that pollution requires, water pollution does not stop at state borders; loosely regulated states still impair their neighbors’ water quality. The federal common law of nuisance can help address the nonpoint source pollution problem. By reviving this tort, the states would regain a powerful tool to defend their environments from out-of-state harm.

Beginning in the 2010s, corporations began making voluntary commitments to reduce carbon emissions, improve labor practices, and promote diversity and inclusion. These commitments shape consumer behavior, attract investors conscious of environmental, social, and governance factors, and enhance corporate reputations, yet remain largely unenforceable. This Article addresses this critical and timely gap in environmental governance. Drawing on consumer protection, securities regulation, fiduciary duty, treaty law, and due diligence frameworks, it demonstrates how current regimes reinforce legal voluntarism, and proposes a concrete legal pathway to ensure that corporate commitments produce measurable, enforceable outcomes.

The integration of artificial intelligence (AI) into implementation of the National Environmental Policy Act (NEPA) is unfolding against a backdrop of regulatory uncertainty and heightened judicial scrutiny. Along with significant Trump Administration changes to NEPA procedures, recent court decisions have cast doubt on the Council on Environmental Quality’s authority to issue binding NEPA regulations. Meanwhile, federal agencies have initiated pilot programs to apply AI in the preparation of environmental impact statements (EISs), which raises complex questions about transparency, algorithmic bias, public participation, and whether AI-generated EISs can withstand judicial review. This Article addresses two core questions: (1) what is the appropriate regulatory pathway for governing AI in NEPA compliance—rulemaking or legislation; and (2) how can agencies ensure that AI-generated EISs meet judicial standards under NEPA and the Administrative Procedure Act? It proposes a dual-path solution: enhancing technical infrastructure through explainable, auditable AI systems, and embedding human oversight mechanisms into critical stages of the process. These reforms aim to uphold procedural integrity while responsibly harnessing AI’s potential.