Support tools for land use policies based on high resolution regional air quality modelling

Ajtai, Nicolae; Ştefănie, Horaţiu; Botezan, Camelia; Ozunu, Alexandru; Radovici, Andrei; Dumitrache, Rodica; Iriza-Burcă, Amalia; Diamandi, Andrei; Hirtl, Marcus

doi:10.1016/j.landusepol.2019.03.022

Cited by 9 publications

(8 citation statements)

References 38 publications

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“…These techniques can provide nearly continuous monitoring data, only interrupted by certain weather conditions. Satellite measurements are becoming more important for air quality management because their spatial resolution can reach down to 1 km, while their information content is suitable for the assessment of modelling results and combination with modelling tasks (Hirtl et al, 2020). All these techniques enable unattended detection at different altitudes and thus of the composition, clouds, structure, and radiation fluxes of the atmosphere as well as Earth surface characteristics, relevant for atmospheresurface feedback processes.…”

Section: Brief Overviewmentioning

confidence: 99%

“…At an even more operational level, LUR models (based on the spatial analysis of air quality data) have been coupled to high-resolution CTM runs to allow a precise identification of land use classes more exposed to PM 10 , SO 2 , and NO 2 . The results provided a methodological framework that could be used by authorities to assess the impact of specific plans on the exposed population and to include air quality in urban development policies (Ajtai et al, 2020).…”

Section: Contribution Of Modelling To Policy Making and Urban Managem...mentioning

confidence: 99%

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Advances in air quality research – current and emerging challenges

et al. 2022

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Abstract. This review provides a community's perspective on air quality research focusing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizing sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions, and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground-based and remote sensing instruments, including in particular those on satellites. The research should also capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposure to air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high-resolution distributions of these metrics over cities. The review also examines how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.

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Section: Brief Overviewmentioning

confidence: 99%

Section: Contribution Of Modelling To Policy Making and Urban Managem...mentioning

confidence: 99%

Advances in air quality research – current and emerging challenges

et al. 2022

View full text Add to dashboard Cite

show abstract

Section: Brief Overviewmentioning

confidence: 99%

“…have been coupled to high-resolution CTM runs to allow a precise identification of land use classes more exposed to PM10, SO2 and NO2. The results provided a methodological framework that could be used by authorities to assess the impact of specific plans on the exposed population, and to include air quality in urban development policies (Ajtai et al, 2020).…”

Section: Contribution Of Modelling To Policy Making and Urban Management Strategiesmentioning

confidence: 99%

“…Remote sensing measurements including satellite observations have a significant role in air quality management because of their spatial coverage, improving spatial resolution and their use in combination with modelling tasks (Hirtl et al, 2020), even for urban areas (Letheren, 2016). Machine learning algorithms are increasingly being used with remote sensing applications (e.g., Foken, 2021) and recent advances have highlighted the potential of statistical analysis tools (e.g., neural learning algorithms) for predicting air quality at the city scale based on data generated by stationary and mobile sensors (Mihaita et al, 2019).…”

Section: Observations To Support Air Quality Researchmentioning

confidence: 99%

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Advances in Air Quality Research – Current and Emerging Challenges

Sokhi

Moussiopoulos

Baklanov

et al. 2021

Preprint

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Abstract. This review provides a community’s perspective on air quality research focussing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterising sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research and (iii) and to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground based and remote sensing instruments, including especially those on satellites. The research should also capitalize on the growing area of lower cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry and meteorology. Assessment of exposure to air pollution should consider both the impacts of indoor and outdoor emissions, as well as apply more sophisticated, dynamic modelling approaches. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high resolution distributions of these metrics over cities. The review also examines, how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.

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