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A characterisation of the dust transported from North Africa deserts to the Cape Verde Islands, including particle size distribution, concentrations and optical properties, for a complete annual cycle (the year 2011), is presented and discussed. The present analysis includes annual simulations of the BSC-DREAM8b and the NMMB/BSC-Dust models, 1-yr of surface aerosol measurements performed within the scope of the CV-DUST Project, AERONET direct-sun observations, and back-trajectories. A seasonal intrusion of dust from North West Africa affects Cape Verde at surface levels from October till March when atmospheric concentrations in Praia are very high (PM10 observed concentrations reach hourly values up to 710 mg/m 3 ). The air masses responsible for the highest aerosol concentrations in Cape Verde describe a path over the central Saharan desert area in Algeria, Mali and Mauritania before reaching the Atlantic Ocean. During summer, dust from North Africa is transported towards the region at higher altitudes, yielding to high aerosol optical depths. The BSC-DREAM8b and the NMMB/BSC-Dust models, which are for the first time evaluated for surface concentration and size distribution in Africa for an annual cycle, are able to reproduce the majority of the dust episodes. Results from NMMB/BSC-Dust are in better agreement with observed particulate matter concentrations and aerosol optical depth throughout the year. For this model, the comparison between observed and modelled PM10 daily averaged concentrations yielded a correlation coefficient of 0.77 and a 29.0 mg/m 3 'bias', while for BSC-DREAM8b the correlation coefficient was 0.63 and 'bias' 32.9 mg/m 3 . From this value, 12Á14 mg/m 3 is due to the sea salt contribution, which is not considered by the model. In addition, the model does not take into account biomass-burning particles, secondary pollutants and local sources (i.e., resuspension). These results roughly allow for the establishment of a yearly contribution of 42% of dust from North African deserts for PM10 levels observed in Cape Verde.

Tchepel, O., 2018. Temporal patterns and trends of particulate matter over Portugal: a long-term analysis of background concentrations. Air Quality, Atmosphere and Health 11,[397][398][399][400][401][402][403][404][405][406][407] The final publication is available on http://dx. AbstractAir quality management regarding PM concentrations in the atmosphere is a complex problem to tackle. In this paper, we aim to characterize the temporal patterns and trends of aerosol background levels over Portugal. Hourly data from the national air quality monitoring network, gathered from 2007 to 2016, is analysed using statistical methods. Data from 20 monitoring stations was processed to prepare datasets with different time scales, and results were grouped by their type of surrounding area (urban, suburban or rural). Urban and suburban background sites are characterized by strong seasonal patterns, with higher monthly mean concentrations in winter than in summer. In contrast, rural background PM10 concentrations are highest during August and September. This study suggests that urban background concentrations are significantly influenced by anthropogenic non-combustion sources, which contribute to the coarser aerosol fraction (PMc).PMc is about 3 µg m -3 higher during week-days than during Sundays, at urban sites. However, there is no clear relationship between the value of the PM2.5/PMc ratio and the type of monitoring station. During the 10-year period of study, a decrease of 1.83%/year, 3.58%/year and 4.89%/year was registered in PM10 concentrations at Portuguese rural, urban and suburban areas, respectively.Despite the higher decrease at suburban monitoring stations, those sites present the highest 10year mean PM10 concentrations. This work provides an import insight on temporal variations of PM10, PM2.5 and PMc concentrations over Portugal and summarizes trends through the last decade, contributing to the discussion on sources and processes influencing those concentrations.

Due to its dependence on fossil fuel combustion, emissions from the marine transport sector can significantly contribute to air pollution. This work aims to evaluate the impact of maritime transport emissions on air quality in Portugal using a numerical air quality modelling approach, with high-resolution emission data. Emissions from the European TNO inventory were compiled and pre-processed at hourly and high spatial (∼3 × 3 km) resolutions. Scenarios with and without these maritime emissions were then simulated with the WRF-CHIMERE modelling system, extensively tested and validated for Portugal domain, in order to evaluate their impact on air quality. A simulation was performed for one year (2016) and the resulting differences were analysed in terms of spatial distribution, time series and deltas. The main deltas for NO and PM10 are located over international shipping routes and major ports, while O concentrations are impacted in a larger area. The modelling results also indicate that shipping emissions are responsible for deltas in the concentration of NO higher than 20% over specific urban areas located in the west coast of Portugal, and less than 5% for PM10. For O the relative contribution is low (around 2%) but this contribution is also observed at locations more than 50 km from the coast.

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Several emission inventories exist for Europe, which include emissions originating from ship traffic in European sea areas. However, few comparisons of these inventories, in particular focusing on specific emission sectors like shipping, exist in literature. Therefore, the aim of this paper is to review and compare commonly used, and freely available, emission inventories available for the European domain, specifically for shipping and its main pollutants (NOx, SOx and PM10). Five different inventories were considered which include shipping activity: 1) EMEP; 2) TNO-MACC_III; 3) E-PRTR; 4) EDGAR and 5) STEAM. The inventories were initially compared in terms of total emission values and their spatial distribution. The total emission values are largely in agreement (with the exception of E-PRTR), however, the spatial representation shows significant differences in the emission distribution, in particular over the Mediterranean region. As for the contribution of shipping to overall emissions, this sector represent on average 16%, 11% and 5% of total NOx, SOx and PM10 emissions, respectively. Recommendations are given regarding the specific use of each available inventory.

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