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Assessing regional emissions of vehicle-based tire wear particle from macro-to micro/nano-scales with pandemic lockdowns and electromobility scenarios implications
Summary
Researchers developed a data-driven probabilistic model to estimate regional tire wear particle emissions across different land use scenarios, incorporating vehicle fleet data, driving patterns, and emission factors. Modeling suggested that tire wear particles represent a substantial and underappreciated pathway for microplastic entry into the atmosphere, with implications for both human health and environmental policy.
Despite increasing the public awareness of ubiquity of microplastics (MPs) in air, the issue on particular source of tire wear particles (TWPs) emission into atmosphere and their exposure-associated human health has not received the attention it deserves. Here we linked vehicle kilometers traveled (VKT) estimates covering demography, socio-environmental, and transportation features and emission factors to predict regional emission patterns of TWP-derived atmospheric MPs. A data-driven probabilistic approach was developed to consider variability across the datasets and uncertainty of model parameters in terms of country-level and vehicle-type emissions. We showed that country-specific VKT from billion to trillion vehicle-kilometer resulted in 10-10 metric tons of airborne TWP-derived atmospheric MPs annually in the period 2015-2019, with the highest emissions from passenger cars and heavy-duty vehicles. On average, we found that airborne TWP emissions from passenger cars by country had substantial decreased (up to ∼33%) during COVID-19 lockdowns in 2020 and pronounced increased (by a factor ∼1.9) from vehicle electrification by the next three decades. We conclude that the stunning mass of airborne TWP is a predominant source of atmospheric MP. We underscore the necessity of TWP emissions control among the United States, China, and India. Our findings can be of great use to environmental transportation planners for devising vehicle/tire-oriented decision support tools. Our data offer information to enhance TWP-exposure estimates, to examine long-term exposure trends, and subsequently to improve health risk assessment during pandemic outbreak and future electrification.
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