Assessment of source contribution to air quality in an urban area close to a harbor: case-study in Porto, Portugal

• Autor(a) principal: Sorte, Sandra
• Data de Publicação: 2019
• Outros Autores: Arunachalam, Saravanan, Naess, Brian, Seppanen, Catherine, Rodrigues, Vera, Valencia, Alejandro, Borrego, Carlos, Monteiro, Alexandra
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/26629
• topic: Ship emissions; Source contribution; Air quality; Dispersion modelling; Port areas

Several harbors, like the Port of Leixões (Porto, Portugal), are located near urban and industrial areas, places where residential urban areas, highways and the refinery industry coexist. The need for assessing the contribution of the port to the air quality in its vicinity around the port is the motivation for the present study. This contribution was investigated using a numerical modelling approach based on the web-based research screening tool C-PORT. The impact of the meteorological conditions (namely atmospheric stability and wind direction) was first evaluated, and the most critical conditions for pollutants dispersion were identified. The dominant wind direction, from WSW, was responsible for the transport of pollutants over the surrounding urban area, which was potentiated by the diurnal sea breeze circulation. Multiple scenario runs were then performed to quantify the contribution of each emission sector/activity (namely maritime emissions; port activities; road traffic and refinery) to the ambient air quality. The multiple scenario runs indicated that land-based emission sources at the Port (including trucks, railways, cargo handling equipment and bulk material stored) were the major contributors (approximately 80%) for the levels of surface PM10 concentrations over the study area. Whereas, the main drivers of NOX concentrations were docked ships, responsible for 55-73% of the total NOX concentrations.