Tire wear particles (TWP), ubiquitously distributed, pose significant risks to ecosystems and human health. Conventional TWP emissions assessment relies on vehicle-type-specific mileage data, but insufficient data on robust vehicle activity statistics limit its applicability globally. Using 2012–2022 comprehensive provincial and national data from mainland China, including vehicle activity, population, and Gross Domestic Product (GDP), we developed an empirical model to estimate TWP emissions via accessible population and GDP indicators. Upon comparison with 2023 mileage-based TWP estimates across 32 Chinese regions and published data sets from 13 countries, our model demonstrated strong predictive performance, characterized by high coefficients of determination (R2 = 0.892 and 0.862), low mean absolute error (MAE = 0.107 and 0.196), and low root-mean-square error (RMSE = 0.143 and 0.271). Using this model, we estimated 2022 TWP emissions for 101 eligible countries (vehicle ownership of 35–885 vehicles per 1000 inhabitants), identifying mainland China, the USA, India, Japan, and Brazil as the top five emitters. Globally, TWP emissions are estimated to rise from 3764.6 Kt yr–1 (median) in 2010 to 4919.2 Kt yr–1 in 2024, and are projected at 7280.5 Kt yr–1 by 2050. This work provides a practical tool for large-scale TWP emission risk prediction.
Li et al. (2026) studied this question.