Mohajeri Nahid, Walch Alina, Gudmundsson Agust, Heaviside Clare, Askari Sadaf, Wilkinson Paul, Davies Michael
UCL Institute for Environmental Design and Engineering, Faculty of the Built Environment, University College London, London, UK.
Solar Energy and Building Physics Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Build Cities. 2021;2(1):759-778. doi: 10.5334/bc.124. Epub 2021 Sep 2.
In 2020, Covid-19-related mobility restrictions resulted in the most extensive human-made air-quality changes ever recorded. The changes in mobility are quantified in terms of outdoor air pollution (concentrations of PM and NO) and the associated health impacts in four UK cities (Greater London, Cardiff, Edinburgh and Belfast). After applying a weather-corrected machine learning (ML) technique, all four cities show NO and PM concentration anomalies in 2020 when compared with the ML-predicted values for that year. The NO anomalies are -21% for Greater London, -19% for Cardiff, -27% for Belfast and -41% for Edinburgh. The PM anomalies are 7% for Greater London, -1% for Cardiff, -15% for Edinburgh, -14% for Belfast. All the negative anomalies, which indicate air pollution at a lower level than expected from the weather conditions, are attributable to the mobility restrictions imposed by the Covid-19 lockdowns. Spearman rank-order correlations show a significant correlation between the lowering of NO levels and reduction in public transport ( < 0.05) and driving ( < 0.05), which is associated with a decline in NO-attributable mortality. These positive effects of the mobility restrictions on public health can be used to evaluate policies for improved outdoor air quality.
Finding the means to curb air pollution is very important for public health. Empirical evidence at a city scale reveals significant correlations between the reduction in vehicular transport and in ambient NO concentrations. The results provide justification for city-level initiatives to reduce vehicular traffic. Well-designed and effective policy interventions (. the promotion of walking and cycling, remote working, local availability of services) can substantially reduce long-term air pollution and have positive health impacts.
2020年,与新冠疫情相关的出行限制导致了有记录以来最广泛的人为空气质量变化。出行变化通过四个英国城市(大伦敦、加的夫、爱丁堡和贝尔法斯特)的室外空气污染(颗粒物和氮氧化物浓度)及其相关健康影响来量化。应用经天气校正的机器学习技术后,与该年机器学习预测值相比,所有四个城市在2020年都出现了氮氧化物和颗粒物浓度异常。大伦敦的氮氧化物异常为-21%,加的夫为-19%,贝尔法斯特为-27%,爱丁堡为-41%。大伦敦的颗粒物异常为7%,加的夫为-1%,爱丁堡为-15%,贝尔法斯特为-14%。所有负异常表明空气污染水平低于根据天气条件预期的水平,这都归因于新冠疫情封锁所实施的出行限制。斯皮尔曼等级相关显示,氮氧化物水平降低与公共交通减少(<0.05)和驾车减少(<0.05)之间存在显著相关性,这与氮氧化物所致死亡率下降相关。出行限制对公众健康的这些积极影响可用于评估改善室外空气质量的政策。
找到控制空气污染的方法对公众健康非常重要。城市层面的实证证据揭示了车辆交通减少与环境氮氧化物浓度降低之间的显著相关性。研究结果为城市层面减少车辆交通的举措提供了依据。精心设计且有效的政策干预措施(如推广步行和骑行、远程工作、当地服务可得性)可大幅减少长期空气污染并对健康产生积极影响。