Excess Heat Factor climatology, trends, and exposure across European Functional Urban Areas

In Europe, regional climate change prospects indicate the urgency of adapting to extreme weather events. While increasing temperature trends have already been detected, in the last decades, the adoption of a European heatwave (HW) early-warning index is not yet consensual, partially due to the significant number of alternative algorithms, in some cases adjusted to the measurement of sector-specific impacts (as per the Expert Team on Climate Risk and Sector-specific Indices (ET-SCI)). In particular, the Excess Heat Factor (EHF) has been shown to accurately predict heat-related human health outcomes, in mid-latitude climates, provided that local summer exposure to excess heat is mostly driven by extreme air temperatures, with a lower contribution from relative humidity. Here, annual summaries of EHF-based HW detection were calculated for the European region, using daily maximum and minimum temperatures from the homogenised version of the E-OBS gridded dataset. Annual HW frequencies, duration, mean magnitude, maximum amplitude, and severity were subject to climatology and trend analysis across the European biogeographical regions, considering the 1961–1990 period as the baseline reference for anomaly detection in the more recent (1991–2018) decades. As HW-dependent morbidity/mortality affects mostly the elderly, an EHF-based HW Exposure Index was also calculated, by multiplying the recent probability of severe events per the number of people aged 65, or more, in the European Functional Urban Areas (FUAs). Results show that recent historical EHF-based patterns diverge across European Biogeographical regions, with a clear latitudinal gradient. Both the historical mean and recent trends point towards the greater exposure in the southern European Mediterranean region, driven by the significant increase of HW frequency, duration and maximum severity, especially in the last 3 decades; conversely, annual maximum EHF intensities (i.e., greatest deviations from the local 90th daily mean temperature) are mostly found in the northern and/or high altitude Boreal, Alpine and Continental regions, as a consequence of the latitudinal effect of local climatology on the HWM/HWA indices (this also translates into greater magnitudes of change, in this regions). Nonetheless, by simultaneously considering the probability of Severe HW occurrence in the last three decades, together with the log transformation of people aged 65 or more, results show that greater HW Exposure Indices affect FUAs across the whole Europe, irrespective of its regional climate, suggesting that more meaningful vulnerability assessments, early warning and adaptation measures should be prioritized accordingly.info:eu-repo/semantics/publishedVersio

An urban climate-based empirical model to predict present and future patterns of the Urban Thermal Signal

Air temperature is a key aspect of urban environmental health, especially considering population and climate change prospects. While the urban heat island (UHI) effect may aggravate thermal exposure, city-level UHI regression studies are generally restricted to temporal-aggregated intensities (e.g., seasonal), as a function of time-fixed factors (e.g., urban density). Hence, such approaches do not disclose daily urban-rural air temperature changes, such as during heatwaves (HW). Here, summer data from Lisbon's air temperature urban network (June to September 2005-2014), is used to develop a linear mixed-effects model (LMM) to predict the daily median and maximum Urban Thermal Signal (UTS) intensities, as a response to the interactions between the time-varying background weather variables (i.e., the regional/non-urban air temperature, 2-hours air temperature change, and wind speed), and time-fixed urban and geographic factors (local climate zones and directional topographic exposure). Results show that, in Lisbon, greatest temperatures and UTS intensities are found in 'Compact' areas of the city are proportional to the background air temperature change. In leeward locations, the UTS can be enhanced by the topographic shelter effect, depending on wind speed - i.e., as wind speed augments, the UTS intensity increases in leeward sites, even where sparsely built. The UTS response to a future urban densification scenario, considering climate change HW conditions (RCP8.5, 2081-2100 period), was also assessed, its results showing an UTS increase of circa 1.0 °C, in critical areas of the city, despite their upwind location. This LMM empirical approach provides a straightforward tool for local authorities to: (i) identify the short-term critical areas of the city, to prioritise public health measures, especially during HW events; and (ii) test the urban thermal performance, in response to climate change and urban planning scenarios. While the model coefficient estimates are case-specific, the approach can be efficiently replicated in other locations with similar biogeographic conditions.info:eu-repo/semantics/publishedVersio

Geostatistical simulations with heterotopic hard and soft data without modeling the linear model of coregionalization

Most mining decisions are based on models estimated/simulated given the information obtained from samples. During the exploration stage, samples are commonly taken using diamond drill holes which are accurate and precise. These samples are considered hard data. In the production stage, new samples are added. These last are cheaper and more abundant than the drill hole samples, but imprecise and are here named as soft data. Usually hard and soft data are not sampled at the same locations, they form a heterotopic dataset. This article proposes a framework for geostatistical simulation with completely heterotopic soft data. The simulation proceeds in two steps. First, the variable of interest at the locations where soft data are available is simulated. The local conditional distributions built at these locations consider both hard and soft data and are obtained using simple cokriging with the intrinsic coregionalization model. Second, the variable of interest in the entire simulation grid using the original and previously simulated values at soft data locations is simulated. The results show that the information from soft data improved both the accuracy and precision of the simulated models. The proposed framework is illustrated by a case study with data obtained from an underground copper mine

Multidimensional scaling for the evaluation of a geostatistical seismic elastic inversion methodology

Due to the nature of seismic inversion problems, there are multiple possible solutions that can equally fit the observed seismic data while diverging from the real subsurface model. Consequently, it is important to assess how inverse-impedance models are converging toward the real subsurface model. For this purpose, we evaluated a new methodology to combine the multidimensional scaling (MDS) technique with an iterative geostatistical elastic seismic inversion algorithm. The geostatistical inversion algorithm inverted partial angle stacks directly for acoustic and elastic impedance (AI and EI) models. It was based on a genetic algorithm in which the model perturbation at each iteration was performed recurring to stochastic sequential simulation. To assess the reliability and convergence of the inverted models at each step, the simulated models can be projected in a metric space computed by MDS. This projection allowed distinguishing similar from variable models and assessing the convergence of inverted models toward the real impedance ones. The geostatistical inversion results of a synthetic data set, in which the real AI and EI models are known, were plotted in this metric space along with the known impedance models. We applied the same principle to a real data set using a cross-validation technique. These examples revealed that the MDS is a valuable tool to evaluate the convergence of the inverse methodology and the impedance model variability among each iteration of the inversion process. Particularly for the geostatistical inversion algorithm we evaluated, it retrieves reliable impedance models while still producing a set of simulated models with considerable variability

Uma oficina de novidades : a implantação de núcleos urbanos na capitania de São Paulo, 1765-1775

Este trabalho apresenta parte dos resultados da tese de doutorado Método e Arte: criação urbana e organização territorial na capitania de São Paulo, 1765-1811, desenvolvida na Faculdade de Arquitetura e Urbanismo da Universidade de São Paulo, com apoio de bolsa da Fundação de Amparo à Pesquisa do Estado de São Paulo.Este artigo acompanha algumas dinâmicas de implantação de núcleos urbanos na capitania de São Paulo durante a administração do governador e capitão-general Morgado de Mateus (1765-1775). Destacam-se momentos significativos do processo de formação de paisagens urbanas, desde o recrutamento de povoadores e a busca de sítios até a definição dos traçados. A intenção é mostrar que a Coroa portuguesa foi tentando organizar determinados modos de conduzir a expansão urbana, ao passo que experiências e circunstâncias locais constantemente exigiram arranjos novos e específicos. A análise fundamenta-se numa seleção da documentação oficial já publicada e também em correspondência, em boa parte inédita, proveniente de agentes locais encarregados de tarefas ligadas ao povoamento. Procura-se tratar da política urbanizadora daquele período como um processo desenvolvido num contexto de conflitos mais do que como produto de um projeto pré-delineado por autoridades metropolitanas ou alheio a realidades do lugar. ______________________________________________________________________________________ ABSTRACTThis article investigates some of the dynamics associated with the establishment of urban nuclei in the captaincy of São Paulo during the administration of the Morgado de Mateus, governor and captain-general of the captaincy from 1765 to 1775. Several significant aspects about the formation process of urban landscapes stand out, from the recruitment of settlers and the search for suitable sites to the definition of urban layouts. The intention of this study is to show that the Portuguese crown made efforts to organize certain processes for conducting urban expansion, whilst local experience and circumstances continually demanded new and specific arrangements. The analysis is based on a selection of previously-published official documents, as well as mostly unpublished correspondence from local agents in charge of settlement-related tasks. The urbanization policy of the period is dealt with as a process that was executed in the context of conflicts, rather than as the product of a project pre-planned by metropolitan authorities or detached from the realities of the place at that time

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

<p>Abstract</p> <p>Background</p> <p>The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design.</p> <p>Methods/Design</p> <p>Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models.</p> <p>Discussion</p> <p>Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis.</p

Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning

In this paper we explore a unique, high-value spatio-temporal dataset that results from the fusion of three data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed), the corresponding fish catch reports (i.e., the quantity and type of fish caught), and relevant environmental data. The result of that fusion is a set of semantic trajectories describing the fishing activities in Northern Adriatic Sea over two years. We present early results from an exploratory analysis of these semantic trajectories, as well as from initial predictive modeling using Machine Learning. Our goal is to predict the Catch Per Unit Effort (CPUE), an indicator of the fishing resources exploitation useful for fisheries management. Our predictive results are preliminary in both the temporal data horizon that we are able to explore and in the limited set of learning techniques that are employed on this task. We discuss several approaches that we plan to apply in the near future to learn from such data, evidence, and knowledge that will be useful for fisheries management. It is likely that other centers of intense fishing activities are in possession of similar data and could use the methods similar to the ones proposed here in their local context

Validation of a Novel, Sensitive, and Specific Urine-Based Test for Recurrence Surveillance of Patients With Non-Muscle-Invasive Bladder Cancer in a Comprehensive Multicenter Study

Bladder cancer (BC), the most frequent malignancy of the urinary system, is ranked the sixth most prevalent cancer worldwide. Of all newly diagnosed patients with BC, 70-75% will present disease confined to the mucosa or submucosa, the non-muscle-invasive BC (NMIBC) subtype. Of those, approximately 70% will recur after transurethral resection (TUR). Due to high rate of recurrence, patients are submitted to an intensive follow-up program maintained throughout many years, or even throughout life, resulting in an expensive follow-up, with cystoscopy being the most cost-effective procedure for NMIBC screening. Currently, the gold standard procedure for detection and follow-up of NMIBC is based on the association of cystoscopy and urine cytology. As cystoscopy is a very invasive approach, over the years, many different noninvasive assays (both based in serum and urine samples) have been developed in order to search genetic and protein alterations related to the development, progression, and recurrence of BC. TERT promoter mutations and FGFR3 hotspot mutations are the most frequent somatic alterations in BC and constitute the most reliable biomarkers for BC. Based on these, we developed an ultra-sensitive, urine-based assay called Uromonitor®, capable of detecting trace amounts of TERT promoter (c.1-124C > T and c.1-146C > T) and FGFR3 (p.R248C and p.S249C) hotspot mutations, in tumor cells exfoliated to urine samples. Cells present in urine were concentrated by the filtration of urine through filters where tumor cells are trapped and stored until analysis, presenting long-term stability. Detection of the alterations was achieved through a custom-made, robust, and highly sensitive multiplex competitive allele-specific discrimination PCR allowing clear interpretation of results. In this study, we validate a test for NMIBC recurrence detection, using for technical validation a total of 331 urine samples and 41 formalin-fixed paraffin-embedded tissues of the primary tumor and recurrence lesions from a large cluster of urology centers. In the clinical validation, we used 185 samples to assess sensitivity/specificity in the detection of NMIBC recurrence vs. cystoscopy/cytology and in a smaller cohort its potential as a primary diagnostic tool for NMIBC. Our results show this test to be highly sensitive (73.5%) and specific (93.2%) in detecting recurrence of BC in patients under surveillance of NMIBC.info:eu-repo/semantics/publishedVersio