Prioritising actions for improving classroom air quality based on the analytic hierarchy process: case studies in China and the UK

The air quality in classrooms significantly impacts school children’s health and learning performance. It has been reported worldwide that classroom air quality does not meet the required standard and actions are pledged for improvement. However, it poses a challenge for decision-making in terms of prioritising taking-up measures. The aim of this study is to propose a method of identifying the action measures for improving classroom air quality and prioritising them. Case studies in the UK and China were conducted, and the key measures were identified through literature studies, open-ended questionnaire surveys, and workshop discussions, which are classified into three categories: B1, policy; B2, technology; and B3, information sharing. The analytical hierarchy process (AHP) is applied in the prioritisation of the action measures. A total of 138 teachers and parents from China and the UK participated in this case study. The genetic algorithm-optimised Hadamard product (GAOHP) method is applied to justify the consistency ratio (CR) within the required threshold value in order to ensure the consistency of the subjective perception and the accuracy of comparative weights. The results show that item B2, technology, is the most desired measure by both Chinese and British parents and teachers, despite the deviation from the optimal choice in China and the UK. Among the proposed action measures, the UK respondents strongly expected air purifiers with natural ventilation as opposed to their Chinese counterparts preferring to share the real-time status of classroom air quality. Our work will provide strong support for the subsequent selection of indoor air quality improvement strategies for schools

THE IMPACT OF VEHICLES ON AIR QUALITY IN ZAGREB AND KOROMAČNO, CROATIA

This paper describes and analyses concentrations of main traffic related air pollutants and their impact on air quality, which affects the quality of human life. The data are obtained from the measuring stations in Zagreb and Koromačno (Croatia). These two places were chosen because of their diversity, related to traffic density – Zagreb is capital of Croatia, and Koromačno is a small town in Istria region. Due to a specific way of pollution assessment, the data are presented in diagrams using an application, designed for this purpose, which enables easy comparisons and interpretation of the data. The results of this research indicate specific patterns of changes in the pollutant concentrations in relation to emissions of road motor vehicles

Modelação multiescala de qualidade do ar urbana para cidades mais saudáveis

Ambient air pollution is nowadays a serious public health problem worldwide, especially in urban areas due to high population density and intense anthropogenic activity. Among the main urban air pollution sources, the road traffic sector is one of the major concerns and the largest contributor to nitrogen dioxide (NO2) concentrations, though regional background chemical conditions must also be considered. In this context, the use of modelling tools is crucial to understand atmospheric and social dynamics in multiple scales, as well as to support in defining the best air quality improvement strategies. The main objective of this thesis is to develop and apply a multiscale modelling system able to simulate air quality and health impacts in cities. For this purpose, the modair4health multiscale air quality and health risk modelling system was developed and operationalized. It includes the online model WRF-Chem, which provides air quality and meteorological fields from regional to urban scales, and the Computational Fluid Dynamics (CFD) model VADIS, which uses the urban WRF-Chem outputs to calculate flows and dispersion of traffic emissions-related air pollutants in urban built-up areas. A health module, based on linear and non-linear World Health Organization approaches, was also integrated in modair4health to assess the health impacts resulting from air quality changes, and the overall health damage costs are calculated based on economic studies. The application and assessment of the modair4health system allowed to identify the most appropriate configurations and input data, which were used to apply the system over the case study testing air quality improvement scenarios. One of the busiest road traffic areas of the city of Coimbra (Fernão de Magalhães Avenue) in Portugal was selected as case study. The application considered a 4 domains setup: three nested domains (25, 5 and 1 km2 resolutions) for the WRF-Chem, and the 4th domain (4 m2 resolution) over the target local study area and NO2 for the VADIS. WRF-Chem was applied along the year 2015 and VADIS was simulating two particular periods: one week in winter and another one in summer. Short-term health impacts were estimated and the non-linear approach led to lower health outcomes that seem better adjusted to the local reality. Finally, to assess the modair4health capabilities for decision-making support, two traffic management scenarios were tested over the case study: replacement of 50% of the vehicle fleet below EURO 4 by electric vehicles (ELEC), and introduction of a Low Emission Zone (LEZ). Air quality and health positive impacts were higher for the ELEC scenario. This study represents a scientific advance in multiscale air quality and health modelling. The modair4health system can be easily adapted and applied to other simulation domains, providing urban air pollution levels and subsequent health impacts for different case studies and supporting the assessment of air pollution control policies.A poluição atmosférica é atualmente um sério problema mundial de saúde pública, especialmente em áreas urbanas, devido à elevada densidade populacional e intensa atividade antropogénica. O setor dos transportes rodoviários é uma das principais preocupações e o que mais contribui para concentrações de dióxido de azoto (NO2) na atmosfera, embora as condições químicas de fundo regional devam também ser consideradas. Neste contexto, a utilização de ferramentas de modelação é crucial para compreender a dinâmica atmosférica e humana a diferentes escalas, e apoiar na definição das melhores estratégias para melhoria da qualidade do ar (EMQA). Esta tese tem como objetivo principal o desenvolvimento e aplicação de um sistema de modelação multiescala que permita simular qualidade do ar e impactos na saúde em cidades. Para isso, foi desenvolvido e operacionalizado o sistema modair4health - multiscale air quality and health risk modelling. Este sistema inclui o modelo online WRF-Chem, que fornece campos meteorológicos e de qualidade do ar da escala regional à urbana, e o modelo CFD VADIS, que utiliza os resultados do WRF-Chem para calcular o impacto das emissões do tráfego rodoviário no escoamento e dispersão de poluentes em áreas urbanas. Para avaliar os impactos na saúde humana, foi também integrado um módulo baseado nas abordagens linear e não-linear da Organização Mundial de Saúde (OMS), e os custos são calculados com base em estudos económicos. A aplicação e avaliação do sistema modair4health permitiram identificar as configurações e dados de entrada mais apropriados, que foram posteriormente utilizados para testar EMQA sobre o caso de estudo, que corresponde a uma das áreas de maior tráfego rodoviário da cidade de Coimbra (Avenida Fernão de Magalhães). O WRF-Chem foi configurado com 3 domínios aninhados (resoluções de 25, 5 e 1 km2), simulados para o ano 2015; enquanto que para o VADIS, foi definido um quarto domínio (resolução de 4 m2) sobre o caso de estudo para simular concentrações de NO2 em dois períodos específicos: uma semana no inverno e outra no verão. Para quantificar os impactos na saúde, as duas abordagens da OMS foram aplicadas ao caso de estudo para avaliar efeitos a curto-prazo. A abordagem não-linear apresentou resultados de saúde mais baixos que aparentemente estão melhor ajustados à realidade local. Por fim, foram avaliadas as potencialidades do sistema no apoio à tomada de decisão, testando dois cenários de gestão do tráfego rodoviário: substituição de 50% da frota de veículos abaixo de EURO 4 por veículos elétricos (ELEC), e introdução de uma Zona de Emissões Reduzidas (LEZ). O cenário ELEC potencia melhorias mais significativas na qualidade do ar e saúde. Este estudo representa um avanço científico na modelação multiescala da qualidade do ar e saúde. O sistema modair4health pode ser facilmente adaptado e aplicado a outros casos de estudo para avaliar a qualidade do ar urbana e impactos na saúde, bem como para testar medidas de controlo da poluição atmosférica.Programa Doutoral em Ciências e Engenharia do Ambient

An Internet of Things Platform for Air Station Remote Sensing and Smart Monitoring

Air pollution is currently receiving more attention by international governments and organizations. Nevertheless, current systems for air quality monitoring lack essential requirements which are key in order to be effective concerning users’ access to the information and efficient regarding real-time monitoring and notification. This paper presents an Internet of Things platform for air station remote sensing and smart monitoring that combines Big Data and Cloud Computing paradigms to process and correlate air pollutant concentrations coming from multiple remote stations, as well as to trigger automatic and personalized alerts when a health risk for their particular context is detected. This platform has been tested by analyzing the results of observing Andalusian, South of Spain, sensor network during a long period of time. The results show that this novel solution can help to reduce the impact of air pollution on human health since citizens are alerted in real time

Combined effect of high-resolution land cover and grid resolution on surface NO2 concentrations

High-resolution air quality simulations are often performed using different nested domains and resolutions. In this study, the variability of nitrogen dioxide (NO2) concentrations estimated from two nested domains focused on Portugal (D2 and D3), with 5 and 1 km horizontal grid resolutions, respectively, was investigated by applying the WRF-Chem model for the year 2015. The main goal and innovative aspect of this study is the simulation of a whole year with high resolutions to analyse the spatial variability under the simulation grids in conjunction with detailed land cover (LC) data specifically processed for these high-resolution domains. The model evaluation was focused on Portuguese air quality monitoring stations taking into consideration the station typology. As main results, it should be noted that (i) D3 urban LC categories enhanced pollution hotspots; (ii) generally, modelled NO2 was underestimated, except for rural stations; (iii) differences between D2 and D3 estimates were small; (iv) higher resolution did not impact model performance; and (v) hourly D2 estimates presented an acceptable quality level for policy support. These modelled values are based on a detailed LC classification (100 m horizontal resolution) and coarse spatial resolution (approximately 10 km) emission inventory, the latter suitable for portraying background air pollution problems. Thus, if the goal is to characterise urban/local-scale pollution patterns, the use of high grid resolution could be advantageous, as long as the input data are properly represented.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020), SusTEC (LA/P/0007/2020) and CESAM (UIDP/50017/2020 + UIDB/50017/2020 + LA/P/0094/2020), and for the contract granted to Joana Ferreira (2020.00622.CEECIND). Thanks are also due for financial support to OleaChain project “Skills for sustainability and innovation in the value chain of traditional olive groves in the Northern Interior of Portugal” (NORTE-06-3559-FSE-000188).info:eu-repo/semantics/publishedVersio

High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions

In this work, the first long-term (eight years) record of hourly concentrations of carbon monoxide (CO), nitrogen dioxide (NO2) and particulate matter with diameter less than 10 μm (PM10) from three sites in the city of Buenos Aires is analysed. Considering the short-term guidelines suggested by the WHO, the daily mean PM10 concentrations present a relatively large number of exceedances at the three sites. Different statistical techniques are combined to study the relationship between these relatively high PM10 concentrations and relevant surface meteorological variables. For all pollutants and sites, wind speed shows the largest differences between the lowest and highest concentration quartiles. To further explore its role on daily mean PM10 concentration, a k-means algorithm is applied, grouping days with similar surface 1h-wind sequences. Five wind sequence clusters are found, presenting distinctive air quality data features. Two clusters (1 and 2) show that PM10 exceedances occurring with winds entering the city from the river represent between 10 and 21% of total events at the three sites. The frequency of exceedance under these conditions decreases with the distance to the coast. For cluster 1, the hourly PM10 concentration profile and its associated daily wind sequence suggest an important contribution to exceedance events from the city's southernmost power plant. Two clusters (3 and 4), exhibiting continental winds, account for 49–59% of the exceedances and co-occur with relatively drier air conditions. The correlation between CO and PM10 for days belonging to cluster 3 supports the hypothesis of a potential remote or distributed source contribution with SW winds. For cluster 4, differences among sites in the number of events under NNW winds suggest an important contribution from the city's widest avenue to the PM10 levels at the most coastal site. A large contribution coming from urban sources is also indicated for these winds. Finally, cluster 5, exhibiting low wind speed sequences, accounts for 23–33% of the exceedances at the three sites. The average PM10 concentration increases with persistence of this cluster, which could be a driver for exceedances. These results contribute to show the importance of simple methods such as clustering analysis to obtain insights into air quality features such as exceedances and their potential drivers. They also suggest that further efforts in monitoring, modelling and emission estimates may help to better understand local, urban and regional source contributions to these events in the city of Buenos Aires.Fil: Pineda Rojas, Andrea Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Borge, Rafael. Universidad Politécnica de Madrid; EspañaFil: Mazzeo, Nicolás A.. Universidad Tecnológica Nacional. Facultad Regional Avellaneda; ArgentinaFil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Matarazzo, Bruno Nicolas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; ArgentinaFil: Cordero, Jose M.. Universidad Politécnica de Madrid; EspañaFil: Kropff, Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentin