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Managing the Traffic-Related Air Pollution (TRAP) Effects of Urban Warehousing Near Historically Marginalized Communities: A Scenario Analysis of Technology and Land Use Based Strategies

Ecommerce’s far-reaching impacts have prompted cities and companies to introduce strategies that advance urban freight transport’s environmental accountability. Many of these strategies have implications for equity. Warehousing and distribution centers (W&Ds) have concentrated in socially marginalized communities, in part, due to historical, racialized urban development practices. W&Ds generate high volumes of freight trips that are a prominent emitter of health-adverse, criteria air pollutants that burden nearby communities and workers. With the rapid proliferation of these facilities due to ecommerce-related demands, there is a need to evaluate and manage the traffic-related air pollution (TRAP) effect of these strategies on local communities. Most urban freight management strategies center on technological approaches (e.g., electrification), with limited implications for land use based strategies (e.g., zoning) that influence the spatial organization of W&Ds. Therefore, the proposed project endeavors to evaluate the distributional impacts of possible local policy interventions within ecommerce-related transport and land use systems with a focus on populations identified by federal Justice40 guidelines and steering committee input.

The methodology employs a novel, model-based approach to estimate the distribution of ecommerce’s TRAP-related health effects across population subgroups. Methodological procedures include household-level demand modeling using publicly available household travel surveys and population synthesis, traffic simulation (TransModeler), EPA MOVES4, and InMAP modeling with assumptions and parameters informed by interviews with experts from delivery companies, city planning agencies, and W&D operators. The model projects scenarios of future adoption of low- and zero-emission commercial vehicles and alternative W&D locations/characteristics, using sensitivity analyses to capture the effects of uncertainty in model parameters. The project identifies Seattle and New York City as case studies, due the states’ recent adoption of California’s Advanced Clean Truck Program, New York’s proposed Indirect Source Rule that targets W&D-derived pollution in historically marginalized communities, and both cities’ innovative efforts to analyze and mitigate the impacts of ecommerce. The findings and employed methods have long-term applicability for local and regional policymakers’ strategic equity goals concerning comprehensive urban mobility and land use planning.

The project’s objectives seek to capture the breadth of disparate impacts resulting from decisions made by consumers, delivery companies, state and local policymakers.

The UFL spearheads the project, with strategic leadership by Dr. Anne Goodchild (PI) and statistical leadership by Dr. Giacomo Dalla Chiara. Dr. Julian Marshall (co-PI) advises pollutant exposure and health effect estimation methods and interpretations. Travis Fried, Ph.D. student and RA, directs the methodological workflow and written production of results. Dr. Lianne Sheppard (UW Department of Environmental and Occupational Health Sciences and Biostatistics) serves as scientific advisor on the steering committee, providing additional support for interpretation of results and review of written materials.