Association between COVID-19, mobility and environment in Brazilian capitals

<p>Brazilis is the country with highest number of COVID-19 cases and deaths in the sotuhern hsmisphere, third behind India and  U.S globally. Some studies have analized the relationship between mobility, meteorology and air pollution, finding that staying out-of-home increases cases about 5 days and deaths about two weeks after the exposure. (Ibarra-Espinosa, et al., 2021). In this work we will extend the analyses presented by Ibarra-Espinosa et al., (2021), by including more Brazilian cities. Specifically, the metropolitan region of Rio de Janeiro si cosndierer a MEgacity and monitors meteorology and air pollution, necessary to the analyses. The metropolitan regions of Porto Alegre, Belo horizonte and Curutiba as well. The method consists in applying a semiparametric model (Dominici et al, 2004), but in this case, controllying all the environmental factors and their interactions and the parameter consists in the mobility alone. We will compare local mobility index, as Google Residential Mobility Index (RMI), as done by Ibarra-Espinosa et al., (2021). Due to the high dispersion of the data, OVID-19 will be modeled by quasi-poisson and negative binomial distribution, with generalzied additive models (Wood., 2017; Zeileis et al., 2008; R Core Team, 2021).</p><p> </p><p>Ibarra-Espinosa, S., de Freitas, E.D., Ropkins, K., Dominici, F., Rehbein, A., 2021. Association between COVID-19, mobility and environment in São Paulo, Brazil. medRxiv. https://doi.org/10.1101/2021.02.08.21250113</p><p>Dominici F, McDermott A, Hastie TJ. 2004. Improved semiparametric time series models of air pollution and mortality. J Am Stat Assoc 99: 938–948.</p><p><span>R Core Team. 2021. R: A Language and Environment for Statistical Computing.</span></p><p>Wood S. 2017. <em>Generalized Additive Models: An Introduction with R</em>. Chapman and Hall/CRC.</p><p><span>Zeileis A, Kleiber C, Jackman S. 2008. </span>Regression Models for Count Data in R. J Stat Software, Artic 27:1–25; doi:10.18637/jss.v027.i08.</p>

Impact of meteorology and air pollution on Covid-19 pandemic transmission in Lombardy region, Northern Italy

Italy was the first, among all the European countries, to be strongly hit by the Covid-19 pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2). The virus, proven to be very contagious, infected more than 9 million people worldwide (in June 2020). Nevertheless, it is not clear the role of air pollution and meteorological conditions on virus transmission. In this study, we quantitatively assessed how the meteorological and air quality parameters are correlated to the Covid-19 transmission in Lombardy (Northern Italy), the region epicenter of the virus outbreak. Our main findings highlight that temperature and humidity related variables are negatively correlated to the virus transmission, whereas air pollution (PM2.5) shows a positive correlation. In other words, Covid-19 pandemic transmission prefers dry and cool environmental conditions, as well as polluted air. For these reasons, the virus might easier spread in unfiltered air-conditioned environments. Those results will be supporting decision makers to contain new possible outbreaks.

COMPARATIVE STUDY OF THE SIGNIFICANCE OF COMPETITION INDICES AND GENOTYPE OF SCOTS PINE TREE REACTIONS TO CHANGES IN METEOROLOGY AND AIR POLLUTION

Changing climatic conditions, increased length of growing season, competition, genotype and pollution are the most important factors for tree productivity and health. That is why only by knowing the impact of these factors on trees we can evaluate and change sylvicultural treatments that are important for the health and productivity of forest in Lithuania. The aim of the present study was to detect the significance of the competition index vs. genotype of Scots pine trees on their reactions to changes in meteorology and air pollution. Tree health, dendrometric parameters and stem basal area increment were chosen as response variables to meet the objectives of the presented study. The investigation was carried out at Scots pine genetic stand located in Aukstaitija national park, Vaisniunai district. Data on meteorology and air pollutants were obtained from ICP Integrated Monitoring Station located there. Genetically related individual groups in the stand were established by the neutral part of the genome of short repeated DNA sequence length polymorphism markers. Trees of distinctive short repeated sequences allele frequencies were grouped by Bayesian cluster analysis methods. Four genetically similar tree groups were separated in the monitored stand based on significance of ΔK value. Seven competition indices were used to determine the competition intensity effect on the tree increment and their dendrometric parameters including crown condition. The obtained results revealed that trees which demonstrated the most intensive BAI formation, best crown condition and the most significant reaction to changes in meteorology and air pollution comprised one tree genetic group while trees with adverse characteristics the second. Notwithstanding this competition intensity had the most significant effect on BAI formation.

ENVIRO-HIRLAM: on-line coupled modelling of urban meteorology and air pollution

The strategy of new generation integrated Meso-Meteorological (MetM) and Atmospheric Chemical Transport (ACT) models for predicting atmospheric composition, meteorology and climate change is discussed for the Enviro-HIRLAM (HIgh Resolution Limited Area Model) integrated system. Current progress in the Enviro-HIRLAM system development and its urban on-line coupled modelling applications is considered. Results of several sensitivity studies of the urban effects (urban albedo and roughness, anthropogenic heat flux, heat island, and urban aerosols) on meteorology and air pollution at different scales are presented. Several sensitivity tests of the off-line versus on-line coupling of MetM and ACT models in Enviro-HIRLAM as well as their verification versus the ETEX experiment are considered and results are discussed.

Towards improving the simulation of meteorological fields in urban areas through updated/advanced surface fluxes description

The increased resolution of numerical weather prediction models allows nowadays addressing more realistically urban meteorology and air pollution processes. This has triggered new interest in modelling and describing experimentally the specific features and processes of urban areas. Recent developments and results performed within the EU-funded project FUMAPEX on integrated systems for forecasting urban meteorology and air pollution are reported here. Sensitivity studies with respect to optimum resolution, parametrisation of urban roughness and surface exchange fluxes and the role of urban soil layers are carried out with advanced meso- or sub-meso meteorological models. They show that sensible improvements can be achieved by higher model resolution that is accompanied with better description of urban surface features. Recommendations, especially with respect to advanced urban air quality forecasting and information systems, are given together with an assessment of the needed further research and data.