Vehicles' emissions produce a significant share of cities' air pollution, with a substantial impact on the environment and human health. Traditional emission estimation methods use remote sensing stations, missing vehicles' full driving cycle, or focus on a few vehicles. This study uses GPS traces and a microscopic model to analyse the emissions of four air pollutants from thousands of vehicles in three European cities. We discover the existence of gross polluters, vehicles responsible for the greatest quantity of emissions, and grossly polluted roads, which suffer the greatest amount of emissions. Our simulations show that emissions reduction policies targeting gross polluters are way more effective than those limiting circulation based on a non-informed choice of vehicles. Our study applies to any city and may contribute to shaping the discussion on how to measure emissions with digital data.

中文翻译：

---

通过针对严重污染者改善车辆减排政策

车辆排放在城市空气污染中占很大比例，对环境和人类健康产生重大影响。传统的排放估算方法使用遥感站、缺失车辆的完整行驶周期或集中在少数车辆上。本研究使用 GPS 轨迹和微观模型来分析欧洲三个城市数千辆汽车的四种空气污染物排放情况。我们发现存在严重污染者、排放量最大的车辆以及排放量最大的严重污染道路。我们的模拟表明，针对严重污染者的减排政策比基于不知情选择车辆的限制流通的政策更有效。