Mean radiant temperature from global-scale numerical weather prediction models

In human biometeorology, the estimation of mean radiant temperature (MRT) is generally considered challenging. This work presents a general framework to compute the MRT at the global scale for a human subject placed in an outdoor environment and irradiated by solar and thermal radiation both directly and diffusely. The proposed framework requires as input radiation fluxes computed by numerical weather prediction (NWP) models and generates as output gridded globe-wide maps of MRT. It also considers changes in the Sun’s position affecting radiation components when these are stored by NWP models as an accumulated-over-time quantity. The applicability of the framework was demonstrated using NWP reanalysis radiation data from the European Centre for Medium-Range Weather Forecasts. Mapped distributions of MRT were correspondingly computed at the global scale. Comparison against measurements from radiation monitoring stations showed a good agreement with NWP-based MRT (coefficient of determination greater than 0.88; average bias equal to 0.42 °C) suggesting its potential as a proxy for observations in application studies

Heatwaves, droughts, and fires: exploring compound and cascading dry hazards at the pan-European scale

Compound and cascading natural hazards usually cause more severe impacts than any of the single hazard events alone. Despite the significant impacts of compound hazards, many studies have only focused on single hazards. The aim of this paper is to investigate spatio-temporal patterns of compound and cascading hazards using historical data for dry hazards, namely heatwaves, droughts, and fires across Europe. We streamlined a simple methodology to explore the occurrence of such events on a daily basis. Droughts in soil moisture were analyzed using time series of a threshold-based index, obtained from the LISFLOOD hydrological model forced with observations. Heatwave and fire events were analyzed using the ERA5-based temperature and Fire Weather Index datasets. The data used in this study relates to the summer seasons from 1990 to 2018. Our results show that joint dry hazard occurrences were identified in west, central, and east Europe, and with a lower frequency in southern Europe and eastern Scandinavia. Drought plays a substantial role in the occurrence of the compound and cascading events of dry hazards, especially in southern Europe as it drives duration of cascading events. Moreover, drought is the most frequent hazard-precursor in cascading events, followed by compound drought-fire events. Changing the definition of a cascading dry hazard by increasing the number of days without a hazard from 1 to 21 within the event (inter-event criterion), lowers as expected, the maximum number of cascading events from 94 to 42, and extends the maximum average duration of cascading events from 38 to 86 days. We had to use proxy observed data to determine the three selected dry hazards because long time series of reported dry hazards do not exist. A complete and specific database with reported hazards is a prerequisite to obtain a more comprehensive insight into compound and cascading dry hazards

Label-free multiphoton microscopy of intracellular lipids using Coherent anti-Stokes Raman Scattering (CARS)

Coherent Antistokes Raman Scattering (CARS) microscopy has emerged in the last decade as a powerful multiphoton microscopy technique to rapidly image lipid droplets (LDs) label-free with intrinsic three-dimensional spatial resolution in cells. In this thesis I investigate and compare the ability of hyperspectral CARS and dual-frequency/differential CARS (D-CARS) to enable the chemical specificity required to distinguish lipids of different chemical composition. In hyperspectral CARS a series of spatially-resolved images are acquired over a frequency range thus proving high chemical specificity. In D-CARS two vibrational frequencies are simultaneously excited and probed, and the resulting sum and difference CARS intensities are detected by a fast and efficient single photomultiplier. This results in a higher image speed than hyperspectral CARS and in an improved image contrast against the nonresonant CARS background with a straightforward data analysis. D-CARS and hyperspectral CARS techniques were applied to LDs in model and cellular systems. In model systems made by agarose gel, droplets of pure lipids with different degree of unsaturation (number of carbon-carbon double bonds in the fatty acyl chain) were used as test sample to compare Raman spectra with CARS spectra, and measure D-CARS images at specific chemically-selective wavenumbers. Building from this knowledge, cytosolic droplets induced by loading fatty acids to the culture media of human adipose-derived stem cells (ADSCs) were distinguished in composition both in fixed cells and in living cells during differentiation into adipocytes. Furthermore, the application of a in-house developed Hyperspectral Image Analysis (HIA) software on hyperspectral data provided spatial distributions and absolute concentrations for the chemical components of the investigated specimens. In particular quantitative information was extracted about the concentration of pure neutral lipid components within cytosolic LDs, and changes over time were inferred in living ADSCs according to the type of pure fatty acid added to the culture media

Soil rooting depth of Italy

Soils perform several functions in delivering ecosystem services and soil thematic maps are useful for environmental modelling, landscape planning, and management optimization. This study aimed at producing the first soil rooting depth map of Italy at 1:250,000 scale based on the legacy soil maps, soil data and benchmark profiles, combined with the auxiliary data. The map highlights that moderately deep (33%) and deep (25%) soils are predominant and mainly distributed in hilly areas, while very deep soils (18%) are prevalent in the fluvial and coastal plains. The validation procedure showed that 87% of the soil rooting depth map classes fall within the same and adjacent classes of the measured soil profiles database. The soil rooting depth map of Italy at 1:250,000 scale can be a useful tool to support land management and spatial planning in terms of agro-environmental measures, making reliable assessments for ecological sustainability studies, and for environmental territorial analyses

Mapping combined wildfire and heat stress hazards to improve evidence-based decision making

Heat stress and forest fires are often considered highly correlated hazards as extreme temperatures play a key role in both occurrences. This commonality can influence how civil protection and local responders deploy resources on the ground and could lead to an underestimation of potential impacts, as people could be less resilient when exposed to multiple hazards. In this work, we provide a simple methodology to identify areas prone to concurrent hazards, exemplified with, but not limited to, heat stress and fire danger. We use the combined heat and forest fire event that affected Europe in June 2017 to demonstrate that the methodology can be used for analysing past events as well as making predictions, by using reanalysis and medium-range weather forecasts, respectively. We present new spatial layers that map the combined danger and make suggestions on how these could be used in the context of a Multi-Hazard Early Warning System. These products could be particularly valuable in disaster risk reduction and emergency response management, particularly for civil protection, humanitarian agencies and other first responders whose role is to identify priorities during pre-interventions and emergencies

Quantitative spatiotemporal chemical profiling of individual lipid droplets by hyperspectral CARS microscopy in living human adipose-derived stem cells

There is increasing evidence showing that cytosolic lipid droplets, present in all eucaryotic cells, play a key role in many cellular functions. Yet their composition at the individual droplet level and how it evolves over time in living cells is essentially unknown due to the lack of suitable quantitative non-destructive measurement techniques. In this work we demonstrate the ability of label-free hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy, together with a quantitative image analysis algorithm developed by us, to quantify the lipid type and content in vol:vol concentration units of individual lipid droplets in living human adipose-derived stem cells during differentiation over 9 days in media supplemented with different fatty acids. Specifically, we investigated the addition of the poly-unsaturated linoleic and alpha-linolenic fatty acids into the normal differentiation medium (mostly containing mono-unsaturated fatty acids). We observe a heterogeneous uptake which is droplet-size dependent, time dependent, and lipid dependent. Cells grown in linoleic acid-supplemented medium show the largest distribution of lipid content across different droplets at all times during differentiation. When analyzing the average lipid content, we find that adding linoleic or alpha-linolenic fatty acids at day 0 results in uptake of the new lipid components with an exponential time constant of 22±2hr. Conversely, switching lipids at day 3 results in an exponential time constant of 60±5hr. These are unprecedented findings, exemplifying that the quantitative imaging method demonstrated here could open a radically new way of studying and understanding cytosolic lipid droplets in living cells

Tracking the impacts of climate change on human health via indicators: lessons from the Lancet Countdown

Background In the past decades, climate change has been impacting human lives and health via extreme weather and climate events and alterations in labour capacity, food security, and the prevalence and geographical distribution of infectious diseases across the globe. Climate change and health indicators (CCHIs) are workable tools designed to capture the complex set of interdependent interactions through which climate change is affecting human health. Since 2015, a novel sub-set of CCHIs, focusing on climate change impacts, exposures, and vulnerability indicators (CCIEVIs) has been developed, refined, and integrated by Working Group 1 of the “Lancet Countdown: Tracking Progress on Health and Climate Change”, an international collaboration across disciplines that include climate, geography, epidemiology, occupation health, and economics. Discussion This research in practice article is a reflective narrative documenting how we have developed CCIEVIs as a discrete set of quantifiable indicators that are updated annually to provide the most recent picture of climate change’s impacts on human health. In our experience, the main challenge was to define globally relevant indicators that also have local relevance and as such can support decision making across multiple spatial scales. We found a hazard, exposure, and vulnerability framework to be effective in this regard. We here describe how we used such a framework to define CCIEVIs based on both data availability and the indicators’ relevance to climate change and human health. We also report on how CCIEVIs have been improved and added to, detailing the underlying data and methods, and in doing so provide the defining quality criteria for Lancet Countdown CCIEVIs. Conclusions Our experience shows that CCIEVIs can effectively contribute to a world-wide monitoring system that aims to track, communicate, and harness evidence on climate-induced health impacts towards effective intervention strategies. An ongoing challenge is how to improve CCIEVIs so that the description of the linkages between climate change and human health can become more and more comprehensive.This work is supported by an unrestricted grant from the Wellcome Trust (209734/Z/17/Z).Peer Reviewed"Article signat per 26 autors/es: Claudia Di Napoli, Alice McGushin, Marina Romanello, Sonja Ayeb-Karlsson, Wenjia Cai, Jonathan Chambers, Shouro Dasgupta, Luis E. Escobar, Ilan Kelman, Tord Kjellstrom, Dominic Kniveton, Yang Liu, Zhao Liu, Rachel Lowe, Jaime Martinez-Urtaza, Celia McMichael, Maziar Moradi-Lakeh, Kris A. Murray, Mahnaz Rabbaniha, Jan C. Semenza, Liuhua Shi, Meisam Tabatabaei, Joaquin A. Trinanes, Bryan N. Vu, Chloe Brimicombe & Elizabeth J. Robinson "Postprint (published version

Identification of far-red light acclimation in an endolithic Chroococcidiopsis strain and associated genomic features: Implications for oxygenic photosynthesis on exoplanets

Deserts represent extreme habitats where photosynthetic life is restricted to the lithic niche. The ability of rock-inhabiting cyanobacteria to modify their photosynthetic apparatus and harvest far-red light (near-infrared) was investigated in 10 strains of the genus Chroococcidiopsis, previously isolated from diverse endolithic and hypolithic desert communities. The analysis of their growth capacity, photosynthetic pigments, and apcE2-gene presence revealed that only Chroococcidiopsis sp. CCMEE 010 was capable of far-red light photoacclimation (FaRLiP). A total of 15 FaRLiP genes were identified, encoding paralogous subunits of photosystem I, photosystem II, and the phycobilisome, along with three regulatory elements. CCMEE 010 is unique among known FaRLiP strains by undergoing this acclimation process with a significantly reduced cluster, which lacks major photosystem I paralogs psaA and psaB. The identification of an endolithic, extremotolerant cyanobacterium capable of FaRLiP not only contributes to our appreciation of this phenotype’s distribution in nature but also has implications for the possibility of oxygenic photosynthesis on exoplanets