The Natural Resources Defense Council (NRDC) is a United States-based 501(c)(3) non-profit international environmental advocacy group, with its headquarters in New York City and offices in Washington D.C., San Francisco, Los Angeles, New Delhi, Chicago, Bozeman, and Beijing. Founded in 1970, as of 2019, the NRDC had over three million members, with online activities nationwide, and a staff of about 700 lawyers, scientists and other policy experts.
Strengthening the connection between physical climate science and adaptation communities is essential for producing actionable, integrated risk information. Here we present a climate impact taxonomy linking 35 climatic impact-drivers to 8 representative key risks, with metadata on climate impact characteristics, relevant subsystems and adaptation–mitigation linkages. This prototype taxonomy enables researchers, practitioners and policymakers to develop adaptation strategies and direct support towards the most urgent, evidence-based priorities across IPCC-aligned dimensions. Adaptation to climate risks requires integrating knowledge across IPCC working groups. This study presents a climate impact taxonomy that connects climatic impact-drivers from Working Group I to representative key risks from Working Group II and provides more direct guidance for risk assessment and adaptation strategies.
Abstract Growing global demand for natural gas has driven the expansion of liquefied natural gas (LNG) export terminals, which emit pollutants that can pose health risks to nearby communities. This study presents a novel modeling framework using the AMS/EPA Regulatory Model (AERMOD) to assess near‐source nitrogen dioxide (NO2) exposure, health impacts, and equity implications at the block‐group level. We apply this methodology to four LNG export terminals in the United States, simulating NO2 concentrations within a 50 km radius. Results show that LNG terminals substantially contribute to near‐source air pollution, with simulated 1‐hr maximum NO2 concentrations reaching up to 16% of the EPA's National Ambient Air Quality Standard (100 ppb). Site‐specific maximum concentrations were 15.7 ppb (Site A), 1.6 ppb (B), 10.7 ppb (C), and 0.3 ppb (D). Comparing NO2 concentrations with demographic patterns, Sites A and D showed higher concentrations, higher proportions of People of Color and low‐income populations, and greater health burdens in communities closer to the LNG facilities, indicating potential disproportionate impacts. The other sites showed weak or no spatial inequity patterns. Estimated annual NO2‐attributable all‐cause mortality rates per 100,000 people were 8.2 (A), 0.6 (B), 2.2 (C), and 0.1 (D); annual NO2‐attributable pediatric asthma rates per 100,000 children were 75.5 (A), 6.2 (B), 21.8 (C), and 1.1 (D). This study demonstrates how regulatory dispersion models like AERMOD can be adapted to evaluate near‐source health and equity impacts of industrial emissions and offers a transferable methodology for similar analyses across other high‐emitting facilities.
In this commentary, we focus on the association between exposure to per-and polyfluoroalkyl substances (PFAS) and effects on breastfeeding duration and mammary gland function. We argue that the ability to breastfeed is vulnerable to PFAS exposure and question whether recent regulatory and clinical decision-making contexts have adequately acknowledged these important public health impacts. Across geographically and sociodemographically distinct human populations, shorter duration of breastfeeding is apparent among those with the highest levels of circulating PFAS during pregnancy. Further, toxicological studies indicate that the mammary gland is one of the most sensitive tissues to disruption from PFAS exposure. However, recent analyses, such as the human health toxicity assessment supporting the national primary drinking water regulations and clinical monitoring recommendations fail to adequately incorporate these data into regulatory and clinical decisions that should also support new mothers and their infants. To be more protective of public health, we recommend that mammary gland functional effects, including breastfeeding duration, be incorporated in future risk assessment, regulatory, and clinical decision-making contexts. Future toxicological research, including routine toxicological testing, should use contemporary measures of mammary gland development and function to more fully evaluate the impacts on mammary gland function after exposure to a wider variety of PFAS beyond perfluorooctanoic acid (PFOA). In addition, clinical recommendations regarding breastfeeding should acknowledge and address the unique concerns expressed by PFAS-exposed individuals and communities.
Illegal, unreported, and unregulated fishing (IUU) traditionally refers to fishing activities that violate applicable laws or occur in areas that lack applicable laws. We propose the term IUU+ to capture a broader suite of fisheries sector environmental and associated supply chain trade-related crimes and behaviors. Although IUU+ activity is widely recognized as a serious threat to marine ecosystems, markets, and livelihoods, a quantitative understanding of these incidents, e.g., their frequency, geography, species, actors, and patterns in the type of illicit activity, remains difficult to obtain. We propose IUU+DB, a large language model driven system for building a global incident database of IUU+ activity. The system ingests heterogeneous documents, classifies whether they describe relevant incidents, extracts key data elements such as actors, locations, species, vessels, violations, and enforcement outcomes, and supports deduplication and trend analysis. Case studies and validation results show that IUU+DB can help organize fragmented evidence, surface geographic and behavioral hotspots, support fisheries-domain specific research in academia and non-government organizations, assist source and species risk assessments for industry, and provide support for policy implementation and targeted enforcement efforts to government agencies.
Across Africa, national and sub-national governments, community-based organisations, and research institutions are responding to the critical need for air quality data–a prerequisite for targeted, evidence-based clean air policy action–by setting up monitoring networks. However, the data generated by these monitoring networks isn’t magically ready for analysis and action. Projects need what’s called a Data Management System (DMS), the software that handles behind-the-scenes functions, such as data ingestion, aggregation, harmonisation, storage, quality control, validation, sharing, and more, to enable interpretation and application of the data for various use cases. The Clean Air COMPASS project was launched in December 2024 by the project leads, whose first task was to engage a Community of Practice for Air Quality Systems (COMPASS), a network of core partners representing different geographies and data expertise with established credibility to secure the stakeholder feedback needed to build an open-source DMS.
