Airways and air pollution in childhood: State of the art

Lung ◽  
1990 ◽  
Vol 168 (S1) ◽  
pp. 335-346 ◽  
Author(s):  
Toke Hoppenbrouwers
Author(s):  
Alessandro Guido Cavalieri Manasse ◽  
Antonio De Bitonto

2021 ◽  
Author(s):  
Jeroen Kuenen ◽  
Stijn Dellaert ◽  
Antoon Visschedijk ◽  
Jukka-Pekka Jalkanen ◽  
Ingrid Super ◽  
...  

Abstract. This paper presents a state-of-the-art anthropogenic emission inventory developed for the European domain for a 18-year time series (2000–2017) at a 0.1° × 0.05° grid, specifically designed to support air quality modelling. The main air pollutants are included: NOx, SO2, NMVOC, NH3, CO, PM10 and PM2.5 and also CH4. To stay as close as possible to the emissions as officially reported and used in policy assessment, the inventory uses where possible the officially reported emission data by European countries to the UN Framework Convention on Climate Change and the Convention on Long-Range Transboundary Air Pollution as the basis. Where deemed necessary because of errors, incompleteness of inconsistencies, these are replaced with or complemented by other emission data, most notably the estimates included in the Greenhouse gas Air pollution Interaction and Synergies (GAINS) model. Emissions are collected at the high sectoral level, distinguishing around 250 different sector-fuel combinations, whereafter a consistent spatial distribution is applied for Europe. A specific proxy is selected for each of the sector-fuel combinations, pollutants and years. Point source emissions are largely based on reported facility level emissions, complemented by other sources of point source data for power plants. For specific sources, the resulting emission data were replaced with other datasets. Emissions from shipping (both inland and at sea) are based on the results from the a separate shipping emission model where emissions are based on actual ship movement data, and agricultural waste burning emissions are based on satellite observations. The resulting spatially distributed emissions are evaluated against earlier versions of the dataset as well as to alternative emission estimates, which reveals specific discrepancies in some cases. Along with the resulting annual emission maps, profiles for splitting PM and NMVOC into individual component are provided, as well as information on the height profile by sector and temporal disaggregation down to hourly level to support modelling activities. Annual grid maps are available in csv and NetCDF format (Kuenen et al., 2021).


2021 ◽  
pp. 337-349
Author(s):  
Francesco Bruzzone ◽  
Silvio Nocera

2021 ◽  
Author(s):  
Van-Duc Le

This paper applies a Spatiotemporal Graph Convolutional Recurrent Neural Network which is a tight combination of a Graph Neural Network (GNN) to a Recurrent Neural Network (RNN) architecture for air pollution forecasting in long-term for the entire city. Our model can effectively learn the spatial and temporal features of the air pollution data and its influential factors (e.g. weather, traffic, external areas) at the time. Our method achieves better performance than a state-of-the-art ConvLSTM model in air pollution forecasting and a hybrid GNN-based model that separates GNN and RNN in discrete layers.


Author(s):  
Annunziata Faustini ◽  
Marina Davoli

Despite the increased attention given to the health impact assessment of air pollution and to the strategies to control it in both scientific literature and concrete interventions, the results of the implementations, especially those involving traffic, have not always been satisfactory and there is still disagreement about the most appropriate interventions and the methods to assess their effectiveness. This state-of-the-art article reviews the recent interpretation of the concepts that concern the impact assessment, and compares old and new measurements of attributable risk and attributable fraction. It also summarizes the ongoing discussion about the designs and methods for assessing the air pollution impact with particular attention to improvements due to spatio-temporal analysis and other new approaches, such as studying short term effects in cohorts, and the still discussed methods of predicting the values of attributable risk (AR). Finally, the study presents the more recent analytic perspectives and the methods for directly assessing the effects of not yet implemented interventions on air quality and health, in accordance with the suggestion in the strategic plan 2020−2025 from the Health Effect Institute.


1996 ◽  
Vol 3 (1) ◽  
pp. 29-39 ◽  
Author(s):  
TEE L Guidotti

This second of two parts continues with the development of a framework for understanding air quality issues and their relationship to human health. Recognized health effects associated with air pollution are described and current controversies regarding ozone and PM10are briefly outlined. Epidemiological methods of investigating air quality effects are discussed, comparing recent landmark studies in Canada. Comparative prevalence studies do not reflect the state of the art in air pollution epidemiology but are frequently cited and conducted in Canada as if they were definitive. The implications of setting air quality standards and objectives on this basis or to meet arbitrary levels of risk of health effects are examined. The current state of the art does not support risk-based air quality standards. A policy of continuous improvement is most protective of both human health and the environment.


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