Air quality in Europe has been improving over the last decades. Notwithstanding, urban areas are still facing exceedances of the Air Quality Directive's limit and target values. In this study, we analyzed the effect of two mitigation measures on urban air quality: i) improvement of the biomass residential combustion appliances, and ii) electrification of passenger's cars fleet. Five European cities (Lisbon and Porto - Portugal, Athens - Greece, Kuopio - Finland, and Treviso - Italy) were used as case studies to evaluate the impact of the measures on the fine particle fraction (PM_2.5) concentrations. To facilitate decision making and the quick test of new measures, the LIFE Index-Air tool was developed. In this tool, the air pollutant concentrations are predicted by Artificial Neural Networks trained using a set of air quality modelling simulations. The results indicate that the replacement of old biomass heating systems by new improved fireplaces can be more effective in Treviso. On the other hand, the replacement of gasoline and diesel passenger vehicles by electric ones seems to be more effective in reducing PM_2.5 concentrations over Lisbon, Porto, and Athens. In Kuopio, both mitigation measures have an identical effect.

在过去的几十年里，欧洲的空气质量一直在改善。尽管如此，城市地区仍然面临超过空气质量指令的限制和目标值的问题。在这项研究中，我们分析了两种缓解措施对城市空气质量的影响：i）生物质住宅燃烧器具的改进，以及 ii）乘用车车队的电气化。五个欧洲城市（里斯本和波尔图 - 葡萄牙、雅典 - 希腊、库奥皮奥 - 芬兰和特雷维索 - 意大利）被用作案例研究，以评估这些措施对细颗粒物（PM _{2.5 ）的影响}) 浓度。为了促进决策和新措施的快速测试，开发了 LIFE Index-Air 工具。在该工具中，空气污染物浓度由使用一组空气质量建模模拟训练的人工神经网络预测。结果表明，在特雷维索，用改进的新壁炉替换旧的生物质供暖系统可能更有效。另一方面，用电动汽车替代汽油和柴油乘用车似乎更有效地降低了里斯本、波尔图和雅典的 PM _2.5浓度。在库奥皮奥，两种缓解措施具有相同的效果。