Spatial-temporal modellization of the NO2 concentration data through geostatistical tools

The nitrogen dioxide is a primary pollutant, regarded for the estimation of the air quality index, whose excessive presence may cause significant environmental and health problems. In the current work, we suggest characterizing the evolution of NO2 levels, by using geostatisti- cal approaches that deal with both the space and time coordinates. To develop our proposal, a first exploratory analysis was carried out on daily values of the target variable, daily measured in Portugal from 2004 to 2012, which led to identify three influential covariates (type of site, environment and month of measurement). In a second step, appropriate geostatistical tools were applied to model the trend and the space-time variability, thus enabling us to use the kriging techniques for prediction, without requiring data from a dense monitoring network. This method- ology has valuable applications, as it can provide accurate assessment of the nitrogen dioxide concentrations at sites where either data have been lost or there is no monitoring station nearby

Modelling intra- and inter-day variability of NO2 concentrations in Portugal

Nitrogen dioxide (NO2), is a pollutant that is toxic by inhalation and there is evidence that long-term exposure to this, at high concentrations, has adverse health effects, namely in respiratory and cardiovascular systems. The goal of this study is to characterize the spatial and temporal evolution of NO2 concentration levels, taking into account that environmental data often incorporate distinct recurring patterns in time, imposed by social habits. We aim at capturing the cyclic nature of these environmental indicators, identifying the intra and inter-day variability. Simultaneously, we aim at modelling the temporal and spatial correlation inherent to this type of data. This study focus on NO2 hourly data collected in Portugal from October 1 to December 31, 2014. An initial exploratory study suggests that there are two main seasonal effects in the data and identifies variables such as the type of site, environment, and the day of the week as possible explanatory variables. Furthermore, the analysis of the correlation between meteorological parameters, as air temperature, wind speed and relative humidity and NO2 levels identifies significant negative associations among them. After describing the trend function, geostatistical approaches are applied to the resulting residuals with the aim of characterizing the space-time variability and deriving the predicted values through the kriging tools. This methodology can be used to complement the current design sampling, where there are districts without monitoring stations or with many missing values. Moreover, as meteorological data are available earlier than NO2 levels, we draw scenarios for NO2 levels for 2015.The authors acknowledge Foundation FCT (Fundação para a Ciência e Tecnologia) for funding through Individual Scholarship PhD PD/BD/ 105743/2014, Centre of Mathematics of Minho University and Center for Research & Development in Mathematics and Applications of Aveiro University within project UID/MAT/04106/2013.info:eu-repo/semantics/publishedVersio

Spatio‐temporal analysis of land use/land cover change dynamics in Paraguai/Jauquara Basin, Brazil

Data was collected from freely available images composites from the catalogs of the United States Geological Survey.Although global climate change is receiving considerable attention, the loss of biodiversity worldwide continues. In this study, dynamics of land use/land cover (LULC) change in the Paraguai/Jauquara Basin, Mato Grosso, Brazil, were investigated. Two analyses were performed using R software. The first was a comparative study of LULC among the LULC classes at the polygon scale, and the second was a spatio-temporal analysis of moving polygons restricted to the agricultural regions in terms of topology, size, distance, and direction of change. The data consisted of Landsat images captured in 1993, 1997, 2001, 2005, 2009, 2013, and 2016 and processed using ArcGIS software. The proposed analytical approach handled complex data structures and allowed for a deeper understanding of LULC change over time. The results showed that there was a statistically significant change from regions of natural vegetation to pastures, agricultural regions, and land for other uses, accompanied by a significant trend of expansion of agricultural regions, appearing to stabilize from 2005. Furthermore, different patterns of LULC change were found according to soil type and elevation. In particular, the purple latosol soil type presented the highest expansion indexes since 2001, and the elevated agricultural areas have been expanding and/or stabilizing since 1997.This work is part of the results of the research projects PTDC/MAT-STA/28243/2017 funded by the FCT (Fundação para a Ciência e Tecnologia) and Analise temporal do uso da terra para definição de cenários de mudança da paisagem natural por intervenções de natureza humana no Pantanal de Caceres/MT funded by Fundação de Amparo a Pesquisa do Estado de Mato Grosso-FAPEMAT. The first author also acknowledges Foundation FCT (Fundação para a Ciência e Tecnologia) for funding this research through Individual Scholarship Ph.D. PD/BD/150535/2019

Integrated human exposure to air pollution

The book “Integrated human exposure to air pollution” aimed to increase knowledge about human exposure in different micro-environments, or when citizens are performing specific tasks, to demonstrate methodologies for the understanding of pollution sources and their impact on indoor and ambient air quality, and, ultimately, to identify the most effective mitigation measures to decrease human exposure and protect public health. Taking advantage of the latest available tools, such as internet of things (IoT), low-cost sensors and a wide access to online platforms and apps by the citizens, new methodologies and approaches can be implemented to understand which factors can influence human exposure to air pollution. This knowledge, when made available to the citizens, along with the awareness of the impact of air pollution on human life and earth systems, can empower them to act, individually or collectively, to promote behavioral changes aiming to reduce pollutants’ emissions. Overall, this book gathers fourteen innovative studies that provide new insights regarding these important topics within the scope of human exposure to air pollution. A total of five main areas were discussed and explored within this book and, hopefully, can contribute to the advance of knowledge in this field