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Impacts of air pollution are not limited to human health and ecosystems, but are also important for building materials. The main objective of this study is the quantification and mapping of air pollution effects on the materials, namely the soiling effect of modern glass. An integrated modelling approach was implemented to quantify and analyze the spatial distribution of glass soiling due to exposure to air pollution. The methodology is based on an integrated modelling approach (transportation-emissions-dispersion modelling) applied with high spatial resolution for Coimbra (Portugal) urban area and compared with national scale modelling, showing the important contribution of local pollution sources affecting spatial variability in the soiling effect. Air quality data from CAMS (Copernicus Atmosphere Monitoring Service) were used to quantify the soiling effect at national scale. The results are presented and analyzed in terms of haze. The results obtained at national scale suggest that the average time to reach a 1% haze is 320 days, and this time is reduced to 180 days in the most affected areas. However, urban scale modelling applied with a detailed characterization of local pollution sources in Coimbra provides significantly different results and reveals that in the most affected areas, near road traffic, 1% haze could be reached in approximately 80 days. The methodology proposed and implemented in this study provides relevant information for the maintenance and preservation of building materials and highlights the importance of integrated modelling with high spatial resolution for the assessment of the soiling effect in the built environment. [ABSTRACT FROM AUTHOR]

The objective of this work is to develop a new modelling tool to quantify non-CO2 emissions from aircraft during the landing and take-off (LTO cycle) considering the following criteria: (i) utilising freely available activity data; (ii) using widely recommended emission factors; (iii) providing emissions with the spatial and temporal resolution required for local air quality assessment. Freely available flight tracking data obtained from Flightradar24 and emission factors from the European Environment Agency (EEA/EMEP) are considered for the algorithm implementation and tested for Lisbon airport. The analyses of aircraft emissions during various flight stages reveal that HC and CO are mostly emitted during taxiing (93%), while NOX and PM are mostly produced during climb-out (48% and 35%, respectively). Sensitivity analysis, by using simplified activity data from publicly available databases against detailed engine models and emission factors, showed variations in the daily emissions of less than 13% in the case of CO and NOX, but up to 34% for HC and PM. The modelling approach based on freely available activity data developed in this work may offer valuable insights for quantifying airport emissions, providing crucial inputs for air quality assessment, and supporting the definition of mitigation strategies aimed at enhancing sustainability in aviation practices. [ABSTRACT FROM AUTHOR]

Southern European countries such as Portugal still have a low bicycle share (up to 1%). Therefore, it is fundamental to research the potential benefits and drawbacks of modal shifts. This work analyses the implementation of a bike-sharing system (BSS) and its expected implications in emission reductions from road traffic for the case study of Coimbra city, Portugal. Although many different pollutants result from road traffic, we focused on small Particulate Matter (PM2.5) due to its harmful effects on human health. The methodology considers an integrated set of models for a) estimation of potential demand for the use of bike-sharing; b) mobility studies for the analysis of travel behavior; c) optimization modeling for the location of the bike-sharing stations and d) traffic emission modeling, to estimate the reduction of emissions due to bike-sharing modal shift. We considered two different potential scenarios for the location of bike stations. A modal share shift from car use toward bicycle in each is assumed, and the consequent traffic reduction and the associated emissions reduction are analyzed. The results show a non-homogeneous relation between traffic reduction and emission reduction across the urban space, achieving 12.5% of daily PM2.5 emissions in some urban roads. [ABSTRACT FROM AUTHOR]

Vegetation is a natural source of Volatile Organic Compounds (VOC) that plays an important role in atmospheric chemistry. The main objective of the current study is to implement a model to quantify process-based VOC emissions from plants that focuses on the relationship between the sensitivity of VOC emission estimates to spatial resolution data, based on scientific knowledge and vegetation dynamics derived from satellite observations. The Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) were elected to examine this issue using different resolutions of satellite-derived products: 22m from the DEIMOS-1 satellite, and 250m and 1000m provided by MODIS. The study is focused on an area of 80×80km in Portugal for 2011. Detailed land cover and meteorological data are also included in the emission quantification algorithm. The primary outcomes were determined using a multi-scale analysis showing spatial and temporal variations in the vegetation parameters and modeling results. The results confirm that the emissions model is highly sensitive to the spatial resolution of the satellite-derived data, resulting in about a 30% difference in total isoprene emissions for the study area. [ABSTRACT FROM AUTHOR]

This study is focused on the assessment of potential health benefits by meeting the air quality limit values (2008/50/CE) for short-term PM10 exposure. For this purpose, the methodology of the WHO for Health Impact Assessment and APHEIS guidelines for data collection were applied to Porto Metropolitan Area, Portugal. Additionally, an improved methodology using population mobility data is proposed in this work to analyse number of persons exposed. In order to obtain representative background concentrations, an innovative approach to process air quality time series was implemented. The results provide the number of attributable cases prevented annually by reducing PM10 concentration. An intercomparison of two approaches to process input data for the health risk analysis provides information on sensitivity of the applied methodology. The findings highlight the importance of taking into account spatial variability of the air pollution levels and population mobility in the health impact assessment. [ABSTRACT FROM AUTHOR]

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