A current challenge in the environmental sciences field is to assess air quality at larger urban areas with high level of spatial resolution and, at the same time, with feasible computational resources time demand. This study provides a sensitivity analysis, focused on the implications of different grid resolutions on air quality results, followed by a performance assessment of the URBan AIR (URBAIR) model, a second-generation Gaussian model, as a tool for air quality management in urban areas. Estarreja area, a city located near an industrial complex, was used as case study, and the most critical air pollutants were investigated: particulate matter (PM10) and nitrogen dioxide (NO₂). Three different grid resolutions were tested: 0.1 km, 0.2 km and 0.3 km resolutions. Comparative results revealed that all grids provide similar results regarding the spatial distribution of PM10 and NO₂ concentrations, with evident differences in the magnitude of those concentrations and in the required computational time. The source apportionment analysis revealed the great contribution of industrial sources and road transport to NO₂ and PM10 concentrations, respectively. The URBAIR model is a useful tool to support decision-makers since it considers the specific characteristics of each city, which make it particularly helpful to assess different origins of air pollution, and so, to select the most effective sectorial measures that should be applied to improve local air quality.

环境科学领域当前的一个挑战是以高空间分辨率评估较大城市地区的空气质量，同时具有可行的计算资源时间需求。本研究提供敏感性分析，重点关注不同网格分辨率对空气质量结果的影响，然后对作为城市空气质量管理工具的第二代高斯模型 URBan AIR (URBAIR) 模型进行性能评估。领域。以工业园区附近的城市埃斯塔雷哈地区为例，调查了最关键的空气污染物：颗粒物 (PM10) 和二氧化氮 (NO ₂）。测试了三种不同的网格分辨率：0.1 公里、0.2 公里和 0.3 公里分辨率。比较结果表明，所有网格都提供了关于 PM10 和 NO ₂浓度空间分布的相似结果，但这些浓度的大小和所需的计算时间存在明显差异。源解析分析揭示了工业源和道路运输分别对 NO ₂和 PM10 浓度的巨大贡献。URBAIR 模型是支持决策者的有用工具，因为它考虑了每个城市的具体特征，这使得评估不同的空气污染源特别有帮助，因此，选择最有效的部门措施应该应用于改善当地空气质量。