Shipping emissions contribute significantly to air pollution at the local and global scales and will do so even more in the future because global maritime transport volumes are projected to increase. The Mediterranean Sea contains the major routes for short sea shipping within Europe and between Europe and East Asia. For this reason, concern about maritime emissions from Mediterranean harbours has been increasing on the EU and IMO (International Maritime Organization, London, UK) agenda, also supporting the implementation of a potential Mediterranean Emission Control Area (MedECA). Many studies are concerned with the impact of ship emissions in port cities. Studies of the contributions of ship emissions to air quality at the local scale include several monitoring and modelling techniques. This article presents a detailed review of the contributions of ship emissions of NO₂, SO₂, PM₁₀, and PM_2.5 on air quality in the main ports in the Mediterranean area. The review extracts and summarises information from published research. The results show a certain variability that suggests the necessity of harmonisation among methods and input data in order to compare results. The analysis illustrates the effects of this pollution source on air quality in urban areas, which could be useful for implementing effective mitigation strategies.

Agrivoltaics’ share of renewable generation is relevant for countries to achieve their energy transition targets. Agrivoltaics is the dual and synergistic use of the land by agricultural crop production and photovoltaic (PV) systems. For their development around a country, a fundamental step is to determine which areas are suitable. This research work has developed a methodological framework for a reliable agrivoltaic land eligibility analysis at regional scale based on a spatial multicriteria analysis (i.e., GIS/MCDM-AHP). The challenging step has been to select a set of relevant criteria, also based on experts’ knowledge, able to capture the factors that can affect both the solar PV potential and agriculture-oriented factors. On the basis of these criteria, properly weighted, a 30 m-resolution land eligibility map for agrivoltaic systems has been generated for the NUTS-2 regions of Italy. We have found that Italy has an eligible area of 10.7 million hectares and a capacity potential of 6435 GW, assuming an installed power density of 0.6 MW/ha. Thus, a land coverage of only 1.24% of this area would allow to reach the national 80 GW target of new renewable capacity to achieve the country’s decarbonisation and energy transition objectives by 2030. The potential of installed capacity results at GW scale for the main land categories of arable land and permanent crops if they are just covered by only 5% with agrivoltaic systems. Thus, the impact of agrivoltaic systems development on land occupation can be considered marginal especially in relation to benefits generated for both the energy and agricultural sectors. Such a method is essentially targeted to regional authorities for planning the sustainable development of agrivoltaic systems at the local level.

Urban air pollution continues to represent a primary concern for human health, despite significant efforts by public authorities for mitigating its effects. Regulatory monitoring networks are essential tools for air pollution monitoring. However, they are sparse networks, unable to capture the spatial variability of the air pollutants. For addressing this issue, networks of low cost stations are deployed, supplementing the regulatory stations. Regarding this application, an important question is where these stations are installed The objective of this study was to generate a site suitability map for the development of a network of low cost multi-sensor stations across a city for a spatially dense urban air quality monitoring. To do that, a site suitability analysis was developed based on two geographical variables properly selected for representing the impact of urban pollutant sources and urban form on the pollutant concentrations. By processing information about emissions patterns and street canyon effects, we were able to identify air quality hotspot areas supposed to show high spatial variability. Low cost monitoring stations, there located, are able to provide that informative content, which is lacking for both regulatory monitoring networks and predictive modelling for high resolution air quality mapping.

Data on air quality collected by the regional network of fixed stations in the most urbanized areas of the Campania region in the south of Italy are examined. Two periods are considered: before and during the adoption of the main directives limiting human activities to fight the spread of SARS-CoV-2 infection. The first period is from the 5th of February to the 5th of March, and the second is from the 13th of March to the 13th of April. Meteorological conditions in the two periods were compared and significant differences were not observed. Therefore, the comparison of air quality data is feasible. During the second period, an intercontinental transport of particulate matter occurred. Data collected during this event (4 p.m. on the 30th of March to 4 p.m. on the 31st of March) were excluded from the analysis. The main reduction of pollutant concentration is observed for NO₂ (−48% of the period average). PM₁₀ shows a lower reduction (−17%). The PM_2.5 average period concentration was quite constant, while the 98° percentile was reduced by −21%. Ozone shows, on the contrary, an increase in concentration due mainly to an increase in solar irradiation during the 2nd period, but also due to the decrease of NOx concentration. The reduction or the increase of pollutant concentration depends on the category of the station: background, industrial, residential, and traffic. In addition to air quality, the reduction of anthropogenic emissions is also studied. All the information available on the reduction of emissions from transport, industry, heating, and other main emissive sectors were collected. The results give useful insights for the development of air quality management policies that could be adopted when the sanitary emergency will end to guarantee the sustainable development of the Campania region.

Air pollution is still one of the biggest environmental threats to human health on a global scale. In urban environments, exposure to air pollution is largely influenced by the activity patterns of the population as well as by the high spatial and temporal variability in air pollutant concentrations. Over the last years, several studies have attempted to better characterize the spatial variations in air pollutant concentrations within a city by deploying dense, fixed as well as mobile, low-cost sensor networks and more recently opportunistic sampling and by improving the spatial resolution of air quality models up to a few meters. The purpose of this work has been to investigate the use of properly designed mobile monitoring campaigns along the streets of an urban neighborhood to assess the capability of an operational air dispersion model as SIRANE at the district scale to capture the local variability of pollutant concentrations. To this end, an IoT ecosystem—MONICA (an Italian acronym for Cooperative Air Quality Monitoring), developed by ENEA, has been used for mobile measurements of CO and NO₂ concentration in the urban area of the City of Portici (Naples, Southern Italy). By comparing the mean concentrations of CO and NO₂ pollutants measured by MONICA devices and those simulated by SIRANE along the urban streets, the former appeared to exceed the simulated ones by a factor of 3 and 2 for CO and NO₂, respectively. Furthermore, for each pollutant, this factor is higher within the street canyons than in open roads. However, the mobile and simulated mean concentration profiles largely adapt, although the simulated profiles appear smoother than the mobile ones. These results can be explained by the uncertainty in the estimation of vehicle emissions in SIRANE as well as the different temporal resolution of measurements of MONICA able to capture local high concentrations.