OLYMPUS-POPGEN: A synthetic population generation model to represent urban populations for assessing exposure to air quality.

SCIENTIFIC QUESTION: With the new individual- and activity-based approaches to simulating exposure to air pollutants, exposure models must now provide synthetic populations that realistically reflect the demographic profiles of individuals in an urban territory. Demographic profiles condition the behavior of individuals in urban space (activities, mobility) and determine the resulting risks of exposure and environmental inequalities. In this context, there is a strong need to determine the relevance of the population modeling methods to reproduce the combinations of socio-demographic parameters in a population from the existing databases. The difficulty of accessing complete, high-resolution databases indeed proves to be very limiting for the ambitions of the different approaches. OBJECTIVE: This work proposes to evaluate the potential of a statistical approach for the numerical modeling of synthetic populations, at the scale of dwellings and including the representation of coherent socio-demographic profiles. The approach is based on and validated against the existing open databases. The ambition is to be able to build upon such synthetic populations to produce a comprehensive assessment of the risk of environmental exposure that can be cross-referenced with lifestyles, indicators of social, professional or demographic category, and even health vulnerability data. METHOD: The approach implemented here is based on the use of conditional probabilities to model the socio-demographic properties of individuals, via the deployment of a Monte Carlo Markov Chain (MCMC) simulation. Households are assigned to housing according to income and house price classes. The resulting population generation model was tested in the Paris region (Ile de France) for the year 2010, and applied to a population of almost 12 million individuals. The approach is based on the use of census and survey databases. RESULTS: Validation, carried out by comparison with regional census data, shows that the model accurately reproduces the demographic attributes of individuals (age, gender, professional category, income) as well as their combination, at both regional and sub-municipal levels. Notably, population distribution at the scale of the model buildings remains consistent with observed data patterns. CONCLUSIONS AND RELEVANCE: The outcomes of this work demonstrate the ability of our approach to create, from public data, a coherent synthetic population with broad socio-demographic profiles. They give confidence for the use of this approach in an activity-based air quality exposure study, and thus for exploring the interrelations between social determinants and environmental risks. The non-specific nature of this work allows us to consider its extension to broader demographic profiles, including health indicators, and to different study regions.

Exploring the linkages between urban form, mobility and emissions with OLYMPUS: A comparative analysis in two French regions.

Nowadays, urban planners and decision-makers are confronted with an increasing number of major urban spaces whose functioning is accompanied by a high density of domestic, private and professional activities, all associated with the consumption of fossil fuels and the emission of atmospheric pollutants and greenhouse gases. As centers of activity and zones of economic and demographic resources, urban centers stand out as privileged areas for the implementation of local strategies aiming at reducing air pollutant emissions, whether through spatial planning, the evolution of services or the transformation of practices. In this work, we propose a diagnosis of the links between population, urban forms, mobility and air pollutant emissions, using the OLYMPUS activity-based emission model. The model is run over two distinct French regions, Pays de la Loire and Île-de-France, characterized by contrasting urban characteristics in terms of structure, density and accessibility. The results highlight the good transposability of the OLYMPUS model over different territories. Then, the interconnections between the specificities of urban systems on one side and the travel demand, modal share, mobility patterns and total road emissions on the other side, are explored. We notably show that the densification of urban centers exerts a pull on peri-urban areas, generating car trips from the suburbs and worsening air quality in the urban cores. The results underline the importance of targeted emission reduction strategies taking into account the unique characteristics and challenges of specific urban landscapes.

A natural experiment to assess how urban interventions in lower socioeconomic areas influence health behaviors: the UrbASanté study.

BACKGROUND: Mechanisms underlying the associations between changes in the urban environment and changes in health-related outcomes are complex and their study requires specific approaches. We describe the protocol of the interdisciplinary UrbASanté study, which aims to explore how urban interventions can modify environmental exposures (built, social, and food environments; air quality; noise), health-related behaviors, and self-reported health using a natural experiment approach. METHODS: The study is based on a natural experiment design using a before/after protocol with a control group to assess changes in environmental exposures, health-risk behaviors, and self-reported health outcomes of a resident adult population before and after the implementation of a time series of urban interventions in four contiguous neighborhoods in Paris (France). The changes in environmental exposures, health-related behaviors, and self-reported health outcomes of a resident adult population will be concurrently monitored in both intervention and control areas. We will develop a mixed-method framework combining substantial fieldwork with quantitative and qualitative analytical approaches. This study will make use of (i) data relating to exposures and health-related outcomes among all participants and in subsamples and (ii) interviews with residents regarding their perceptions of their neighborhoods and with key stakeholders regarding the urban change processing, and (iii) existing geodatabases and field observations to characterize the built, social, and food environments. The data collected will be analyzed with a focus on interrelationships between environmental exposures and health-related outcomes using appropriate approaches (e.g., interrupted time series, difference-in-differences method). DISCUSSION: Relying on a natural experiment approach, the research will provide new insights regarding issues such as close collaboration with urban/local stakeholders, recruitment and follow-up of participants, identification of control and intervention areas, timing of the planned urban interventions, and comparison of subjective and objective measurements. Through the collaborative work of a consortium ensuring complementarity between researchers from different disciplines and stakeholders, the UrbASanté study will provide evidence-based guidance for designing future urban planning and public health policies. TRIAL REGISTRATION: This research was registered at the ClinicalTrial.gov (NCT05743257).

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.