Influence of in-port ships emissions to gaseous atmospheric pollutants and to particulate matter of different sizes in a Mediterranean harbour in Italy

Ship emissions are a growing concern, especially in coastal areas, for potential impacts on human health and climate. International mitigation strategies to curb these emission, based on low-sulphur content fuels, have proven useful to improve local air quality. However, the effect on climate forcing is less obvious. Detailed information on the influence of shipping to particles of different sizes is needed to investigate air quality and climate interaction. In this work, the contributions of maritime emissions to atmospheric concentrations of gaseous pollutants (NO, NO2, SO2, and O-3) and of particles (sizes from 0.009 mu m to 30 mu m) were investigated considering manoeuvring (arrival and departure of ships) and hotelling phases (including loading/unloading activities). Results showed that the size distributions of shipping contributions were different for the two phases and could be efficiently described, using measured data, considering four size-ranges. The largest contribution to particles concentration was observed for D-p < 0.25 mu m, however, a secondary maximum was observed at D-p = 0.35 mu m. The minimum contribution was observed at D-p around 0.8-0.9 mu m with a negligible contribution from hotelling for size range 0.4-1 mu m. The comparison of 2012 and 2014 datasets showed no significant changes of gaseous and particulate pollutant emissions and of the contribution to particle mass concentration. However, an increase of the contribution to particle number concentration (PNC) was observed. Results suggested that harbour logistic has a relevant role in determining the total impact of shipping on air quality of the nearby coastal areas. Additionally, future policies should focus on PNC that represents an important fraction of emissions also for low-sulphur fuels. DOAS remote sensing proved a useful tool to directly measure NO2 and SO2 ship emissions giving estimates comparable with those of emission inventory approach. (C) 2016 Elsevier Ltd. All rights reserved.