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The Italian territory is located at the heart of one of the global hot spots of climate change, where the implementation of climate‐smart land management practices is imperative to guarantee the present and future maintenance of ecosystem functions as well as the sustainability of human socioeconomic activities. The project HIGHLANDER (HIGH performance computing to support smart LAND sERvices) led by Cineca aims at building a comprehensive and multi‐sector framework for land‐management decision‐making in Italy. The project relies on high quality information on different components of the landscape, with a focus on climate‐driven processes, and state‐of‐the‐art computing infrastructures. The HIGHLANDER Data Portal maximizes the impact of HIGHLANDER results by providing access to data products and services. In this article, we describe the architectural features of the platform, as well as the available HIGHLANDER datasets and downstream applications. [ABSTRACT FROM AUTHOR]

The tourism sector is facing its most severe crisis under the COVID-19 pandemic. Social distancing measures, global travel restrictions, stay-at-home orders, and other lockdown measures brought tourism to a halt in 2020. We estimate the potential economic losses thereof in terms of added value and number of tourists by nationality. By using the city of Sorrento as prominent and representative case study, we implement time-series analysis with autoregressive-integrated moving average models on monthly data from January 2013 to December 2019. We thus forecast the loss of tourists and added value in 2020. The results reveal that the pandemic has significantly affected the tourism sector, the added value of tourism in Sorrento might decrease by over 70%, and tourist arrivals might similarly fall or even reach zero foreign arrivals. The local government should reassess the sustainability of tourism proposals by factoring in the lack of tourist arrivals and focusing on loyal tourists and proximity tourists, two fundamental target audiences. We analyse the potential economic effect of COVID-19 on tourism in 2020 A forecast analysis estimates the changes in added value and number of tourists An ARIMA model is employed on monthly data COVID-19 might negatively and severely affect the tourism economy Foreign tourism risks attracting zero travellers in the post-pandemic period [ABSTRACT FROM AUTHOR]

Economic data on construction market performance culled from recently published analysis and studies, have served to highlight and quantify the phenomena that have driven the negative global economic downturn, affecting the construction sector in particular, over the last two years, with obvious repercussions also for Italy. Although there were a few rallying signs that the downward trend was easing off slightly in early 2011 - both in Europe and, albeit rather more hesitantly, in Italy - those tenuous hopes for recovery were not backed up by actual statistical indicators, potentially providing some indication of promising development trends. Of the few emerging dynamics in the American market, which is recovering more swiftly than in Europe, there seems to have been a marked increase in the production of sustainable or "green" buildings, which are taking over increasingly larger slices of the market. [ABSTRACT FROM AUTHOR]

Simple Summary: Asbestos consumption figures could be used to construct epidemiological models to forecast the pleural mesothelioma mortality, although they are not frequently taken into consideration in this kind of analysis. Our purpose is to predict the future burden of pleural mesothelioma deaths in Italy until 2039 and to describe the exposure–response curve considering time lasted from the exposure start. Our results could be of interest to plan future needs of the Italian health system and to provide evidence on the consequences of asbestos exposures useful for countries in which this material is, at present, still used for productive activities. Statistical models used to forecast malignant pleural mesothelioma (MPM) trends often do not take into account historical asbestos consumption, possibly resulting in less accurate predictions of the future MPM death toll. We used the distributed lag non-linear model (DLNM) approach to predict future MPM cases in Italy until 2040, based on past asbestos consumption figures. Analyses were conducted using data on male MPM deaths (1970–2014) and annual asbestos consumption using data on domestic production, importation, and exportation. According to our model, the peak of MPM deaths is expected to occur in 2021 (1122 expected cases), with a subsequent decrease in mortality (344 MPM deaths in 2039). The exposure–response curve shows that relative risk (RR) of MPM increased almost linearly for lower levels of exposure but flattened at higher levels. The lag-specific RR grew until 30 years since exposure and decreased thereafter, suggesting that the most relevant contributions to the risk come from exposures which occurred 20–40 years before death. Our results show that the Italian MPM epidemic is approaching its peak and underline that the association between temporal trends of MPM and time since exposure to asbestos is not monotonic, suggesting a lesser role of remote exposures in the development of MPM than previously assumed. [ABSTRACT FROM AUTHOR]

Despite their differences, pleural and peritoneal mesothelioma are frequently lumped together to describe epidemic curves and to forecast future mesothelioma trends. This study aims to describe the malignant peritoneal mesothelioma (MPeM) epidemic in Italy (1996-2016) and to forecast future trends up to 2040 in order to contribute to the assessment of MPeM future burden. All MPeM deaths in Italy from 1996-2016 were collected (as provided by the Italian National Statistical Institute (ISTAT)) in order to estimate MPeM mortality rates for each 3-year period from 1996 to 2016. Poisson age-period-cohort (APC) models were then used to forecast MPeM future trends. Between 2017 and 2040, 1333 MPeM deaths are expected. The number of MPeM deaths, as well as mortality rates, are expected to constantly decrease throughout the considered period. Based on considering the information from this study, it can be concluded that the MPeM epidemic has probably already reached its peak in Italy.