Poor air quality disproportionally impacts cities in low- and middle-income countries. In Bogotá, Colombia, a metropolitan area with over 10 million inhabitants, fine particulate matter (PM_2.5) levels regularly exceed air quality guidelines, leading to detrimental effects on health. Although there is public interest to improve the city's air quality, the main sources of PM_2.5 pollution have not been clearly identified and the use of modeling for policy development in Bogotá has been limited. Here, we apply a modeling framework based on the Community Multiscale Air Quality Modeling System (CMAQ) to conduct seasonal simulations of air pollution in Bogotá and reveal the emissions sectors with the largest contributions to PM_2.5. Based on these results, we project and compare the air quality benefits of potential pollution mitigation strategies focused on these sources. The analysis finds that resuspended dust from unpaved roads is the largest local source of PM_2.5 and can contribute over 30% of seasonally-averaged concentration across the city. Vehicles, industrial activity, and unpaved road dust combined are responsible for over 60% of PM_2.5 pollution in Bogotá. A scenario analysis shows that paving roads can lead to PM_2.5 decreases of nearly 10 μg/m³ by 2030 in some areas of the city, but air quality will deteriorate significantly over others in the absence of additional emissions control measures. Mitigation strategies designed to target the sectors with the largest contributions to PM_2.5, including road cleaning systems, controls for industrial point sources, cleaner transportation fuels, and updated vehicle fleets, can largely avert projected increases in concentrations, although the impacts of different approaches vary throughout the city. This study is the first to use a comprehensive model to determine sector contributions to air pollution and inform potential emissions control policies in Bogotá, demonstrating an approach to guide pollution management in developing cities facing comparable challenges.

空气质量差对中低收入国家的城市造成了不成比例的影响。在哥伦比亚波哥大这个人口超过1000万的大都市地区，细颗粒物（PM _2.5）的水平经常超过空气质量准则，从而对健康产生不利影响。尽管有改善城市空气质量的公共利益，但尚未明确识别PM _2.5污染的主要来源，并且在波哥大政策制定中使用模型的方法受到限制。在这里，我们应用基于社区多尺度空气质量建模系统（CMAQ）的建模框架，对波哥大的空气污染进行季节性模拟，并揭示对PM _2.5贡献最大的排放部门。基于这些结果，我们计划并比较着眼于这些来源的潜在污染缓解策略对空气质量的好处。分析发现，未铺路面的重悬浮灰尘是PM _2.5的最大本地来源，可占全市季节性平均浓度的30％以上。在波哥大，车辆，工业活动和未铺砌的道路扬尘共同构成PM _2.5污染的60％以上。情景分析表明，铺路可能导致PM _2.5降低近10μg/ m ³到2030年在城市的某些地区，但是如果没有其他排放控制措施，空气质量将比其他地区明显恶化。旨在针对PM _2.5贡献最大的行业的缓解策略，包括道路清洁系统，工业点源控制，更清洁的运输燃料和更新的车队，可以在很大程度上避免预计的浓度增加，尽管不同方法的影响各不相同。整个城市。这项研究是首次使用综合模型来确定行业对空气污染的影响，并为波哥大的潜在排放控制政策提供信息，从而证明了一种方法，可指导面临类似挑战的发展中城市进行污染管理。