Environmental health, racial/ethnic health-disparity, and climate impacts of freight transport in the United States

Atmospheric emissions from freight transportation contribute to human health and climate damage. Here, we quantify and compare three environmental impacts from inter-regional freight transportation in the contiguous United States: mortality attributable to PM2.5 air pollution, racial-ethnic disparities in mortality from PM2.5, and CO2 emissions. We compare all major transportation modes (truck, rail, barge, aircraft) and all major inter-regional routes (~30,000 routes). Our study is the first to comprehensively compare each route separately, and the first to explore racial-ethnic exposure disparities by route and mode, nationally. Impacts (health, health-disparity, climate) per tonne of freight are largest for aircraft. Among non-aircraft modes, per tonne, rail has the largest health and health-disparity impacts and the lowest climate impacts, whereas truck transport has the lowest health impacts and greatest climate impacts – an important reminder that health and climate impacts are often but not always aligned. For aircraft and truck, average monetized damages per tonne are larger for climate impacts than for PM2.5 air pollution; for rail and barge, the reverse holds. We find that average exposures for inter-regional truck and rail are the highest for White non-Hispanic people, from barge is highest for Black people, and from aircraft is highest for people who are mixed/other race. Level of exposure and disparity among racial-ethnic groups vary in urban and rural areas. This research can be used to inform, for a given inter-regional origin and destination, which freight mode offers the lowest environmental health, health-disparity, and climate impacts

Marginal Emissions Factors for Electricity Generation in the Midcontinent ISO

Environmental consequences of electricity generation are often determined using average emission factors. However, as different interventions are incrementally pursued in electricity systems, the resulting marginal change in emissions may differ from what one would predict based on system-average conditions. Here, we estimate average emission factors and marginal emission factors for CO₂, SO₂, and NO_<i>x</i> from fossil and nonfossil generators in the Midcontinent Independent System Operator (MISO) region during years 2007–2016. We analyze multiple spatial scales (all MISO; each of the 11 MISO states; each utility; each generator) and use MISO data to characterize differences between the two emission factors (average; marginal). We also explore temporal trends in emissions factors by hour, day, month, and year, as well as the differences that arise from including only fossil generators versus total generation. We find, for example, that marginal emission factors are generally higher during late-night and early morning compared to afternoons. Overall, in MISO, average emission factors are generally higher than marginal estimates (typical difference: ∼20%). This means that the true environmental benefit of an energy efficiency program may be ∼20% smaller than anticipated if one were to use average emissions factors. Our analysis can usefully be extended to other regions to support effective near-term technical, policy and investment decisions based on marginal rather than only average emission factors