The ECO System Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a new space mission developed by NASA-JPL which launched on July 2018. It includes a multispectral thermal ...infrared radiometer that measures the radiances in five spectral channels between 8 and 12 μm. The primary goal of the mission is to study how plants use water by measuring their temperature from the vantage point of the International Space Station. However, as ECOSTRESS retrieves the surface temperature, the data can be used to measure other heat-related phenomena, such as heat waves, volcanic eruptions, and fires. We have cross-compared the temperatures obtained by ECOSTRESS, the Advanced Spaceborne Thermal Emission and Reflectance radiometer (ASTER) and the Landsat 8 Thermal InfraRed Sensor (TIRS) in areas where thermal anomalies are present. The use of ECOSTRESS for temperature analysis as well as ASTER and Landsat 8 offers the possibility of expanding the availability of satellite thermal data with very high spatial and temporal resolutions. The Temperature and Emissivity Separation (TES) algorithm was used to retrieve surface temperatures from the ECOSTRESS and ASTER data, while the single-channel algorithm was used to retrieve surface temperatures from the Landsat 8 data. Atmospheric effects in the data were removed using the moderate resolution atmospheric transmission (MODTRAN) radiative transfer model driven with vertical atmospheric profiles collected by the University of Wyoming. The test sites used in this study are the active Italian volcanoes and the Parco delle Biancane geothermal area (Italy). In order to test and quantify the difference between the temperatures retrieved by the three spaceborne sensors, a set of coincident imagery was acquired and used for cross comparison. Preliminary statistical analyses show a very good agreement in terms of correlation and mean values among sensors over the test areas.
Urban surfaces play a crucial role in shaping the Urban Heat Island (UHI) effect by absorbing and retaining significant solar radiation. This paper explores the potential of high-resolution satellite ...imagery as an alternative method for characterizing urban surfaces to support UHI mitigation strategies in urban redevelopment plans. We utilized Landsat images spanning the past 40 years to analyze trends in Land Surface Temperature (LST). Additionally, WorldView-3 (WV3) imagery was acquired for surface characterization, and the results were compared with ground truth measurements using the ASD FieldSpec 4 spectroradiometer. Our findings revealed a strong correlation between satellite-derived surface reflectance and ground truth measurements across various urban surfaces, with Root Mean Square Error (RMSE) values ranging from 0.01 to 0.14. Optimal characterization was observed for surfaces such as bituminous membranes and parking with cobblestones (RMSE < 0.03), although higher RMSE values were noted for tiled roofs, likely due to aging effects. Regarding surface albedo, the differences between satellite-derived data and ground measurements consistently remained below 12% for all surfaces, with the lowest values observed in high heat-absorbing surfaces like bituminous membranes. Despite challenges on certain surfaces, our study highlights the reliability of satellite-derived data for urban surface characterization, thus providing valuable support for UHI mitigation efforts.
The purpose of this study is to analyze the surface temperature and the distribution of thermal signatures on Tuscany’s geothermal districts using data obtained through three separate surveys via ...satellite and an unmanned aerial vehicle (UAV). The analysis considers the highest available spatial resolution ranging from hundreds of meters per pixel of the satellite thermal images and the tenths/hundreds of centimeters per pixel of the thermal images acquired by the UAV. The surface temperature maps obtained by satellite data acquired at suitable spatial resolution and the thermal measurements obtained by the thermal camera installed on the UAV were orthorectified and geocoded. This allowed, for example, following the evolution of thermal anomalies, which may represent a modification of the current state of the geothermal field and a possible hazard for both the population and industrial assets. Here, we show the results obtained in three field campaigns during which the simultaneous acquisition of Landsat 8 satellite and UAV (FlyBit octocopter, IDS, Rome, Italy) thermal data were analyzed. By removing the atmosphere contribution from Landsat 8 data, we have produced three surface temperature maps that are compared with the ground field measurements and the surface temperature maps elaborated by FLIR VUE PRO-R on the UAV.
Epidemiological studies highlighted the possibility that exposure to cyanotoxins leads to the development of the neurodegenerative disease amyotrophic lateral sclerosis (ALS).
We devised a ...population-based case-control study in two Italian populations. We used residential proximity of the residence to water bodies as a measure of possible exposure to cyanotoxins.
Based on 703 newly-diagnosed ALS cases and 2737 controls, we calculated an ALS odds ratio (OR) of 1.41 (95% CI: 0.72–2.74) for current residence in the vicinity of water bodies, and a slightly lower estimate for historical residence (OR: 1.31; 95% CI: 0.57–2.99). Subjects <65 years and people living in the Northern Italy province of Modena had higher ORs, especially when historical residence was considered.
Overall, despite some risk of bias due to exposure misclassification and unmeasured confounding, our results appear to support the hypothesis that cyanotoxin exposure may increase ALS risk.
•People younger than 65 have an increased risk of ALS.•Living near water bodies increases the risk of ALS .•The risk for young people was confirmed also in subjects with historical residence.•People living in Emilia-Romagna, especially in the province of Modena have an increased risk of ALS.
Recently, the severe intensification of atmospheric carbon has highlighted the importance of urban tree contributions in atmospheric carbon mitigations in city areas considering sustainable urban ...green planning and management systems. Explicit and timely information on urban trees and their roles in the atmospheric Carbon Stock (CS) are essential for policymakers to take immediate actions to ameliorate the effects of deforestation and their worsening outcomes. In this study, a detailed methodology for urban tree CS calibration and mapping was developed for the small urban area of Sassuolo in Italy. For dominant tree species classification, a remote sensing approach was applied, utilizing a high-resolution WV3 image. Five dominant species were identified and classified by applying the Object-Based Image Analysis (OBIA) approach with an overall accuracy of 78%. The CS calibration was done by utilizing an allometric model based on the field data of tree dendrometry—i.e., Height (H) and Diameter at Breast Height (DBH). For geometric measurements, a terrestrial photogrammetric approach known as Structure-from-Motion (SfM) was utilized. Out of 22 randomly selected sample plots of 100 square meters (10 m × 10 m) each, seven plots were utilized to validate the results of the CS calibration and mapping. In this study, CS mapping was done in an efficient and convenient way, highlighting higher CS and lower CS zones while recognizing the dominant tree species contributions. This study will help city planners initiate CS mapping and predict the possible CS for larger urban regions to ensure a sustainable urban green management system.
The urban heat island (UHI) is an increasingly widespread phenomenon of concern to the wellbeing and the health of populations living in urban environments. The SUHI (Surface UHI) is directly related ...to UHI and influences its extension and intensity. Satellite images in the thermal infrared spectral region can be used to identify and study the SUHI. In this work, Landsat 8 TIR images were acquired to study the SUHI of a medium-sized municipality of the Po valley in the northern part of Italy. An additional Worldview 3 satellite image was used to classify the study area and retrieve the surface albedo of building roofs. Using the Local Climate Zone approach, existing roof materials were virtually replaced by solar reflective materials, and the mitigation potential of the SUHI and the UHI was quantified. This virtual scenario shows a decrease in the overheating of building roofs with respect to the ambient temperature of up to 33% compared to the current situation in the industrial areas. Focusing on UHI intensity, the air temperature decrease could be up to 0.5 °C.
Epidemiologic studies have raised the possibility that some pesticide compounds induce the neurodegenerative disease amyotrophic lateral sclerosis (ALS), though the available evidence is not entirely ...consistent.
We conducted a population-based case-control study in two Italian populations to assess the extent to which residence in the vicinity of agricultural crops associated with the application of neurotoxic pesticides is a risk factor for ALS, using crop acreage in proximity to the residence as an index of exposure.
Based on 703 cases and 2737 controls, we computed an ALS odds ratio of 0.92 (95% confidence interval 0.78-1.09) for those in proximity to agricultural land. Results were not substantially different when using alternative exposure categories or when analyzing specific crop types, with the exception of a higher risk related to exposure to citrus orchards and olive groves in Southern Italy, though based on few exposed subjects (N = 89 and 8, respectively). There was little evidence of any dose-response relation between crop proximity and ALS risk, and using long-term residence instead of current residence did not substantially change our estimates.
Though our index of exposure is indirect and subject to considerable misclassification, our results offer little support for the hypothesis that neurotoxic pesticide exposure increases ALS risk.
Background and goals: The estimate of the internal dose provided by physiologically based pharmacokinetic (PBPK) modelling is a big step forward in the frame of human health risk assessment (HRA) ...from contaminating sources. The PBPK model included in the MERLIN-Expo platform was here tested with data collected in a human biomonitoring (HBM) pilot study to check model efficacy in predicting concentrations in human blood and urine of people exposed to a modern solid waste incinerator (SWI). The aim of the study was to investigate if the use of a PBPK model integrated in a computational platform could replace more expensive and invasive pilot studies. Twenty eight subjects living and working within 4 km of the incinerator (exposed) and 21 subjects living and working outside this area (unexposed) were selected among the population recruited in the HBM study. The group of exposed (E) subjects and the group of non-exposed (NE) subjects were comparable for all relevant anthropometric characteristics and exposure parameters except for the exposure to SWI emissions. Three different scenarios were created: an “only diet-scenario” (DS), a “worst case scenario” (WCS) and a “most likely scenario” (MLS). The platform was tested for blood-lead (B-Pb), urinary-lead (U-Pb), urinary-anthracene (U-Ant) and urinary-fluoranthene (U-Flt). Average estimated U-Pb was statistically equal to the measured one (est. 0.411~0.278; meas. 0.398~0.455 µg/L) and estimated vs. measured U-Ant differ by one order of magnitude only (est. 0.018~0.010; meas. 0.537~0.444 ng/L) while for U-Flt and B-Pb, the error was respectively of two and four orders of magnitude. It is likely that the extremely high accuracy in the Pb concentration input values referring to diet led to the very accurate estimate for this chemical in urine, but the higher error in the B-Pb computed value suggests that PBPK model equations cannot entirely capture the dynamics for blood compartments. MERLIN-Expo seems a very promising tool in saving time, energy and money in the screening step of the HRA framework; however, many software validations are still required.
Dementia is a neurological syndrome characterized by severe cognitive impairment with functional impact on everyday life. It can be classified as young onset dementia (EOD) in case of symptom onset ...before 65, and late onset dementia (LOD). The purpose of this study is to assess the risk of dementia due to light pollution, and specifically outdoor artificial light at night (LAN).
Using a case-control design, we enrolled dementia patients newly-diagnosed in the province of Modena in the period 2017–2019 and a referent population from their caregivers. We geo-referenced the address of residence on the date of recruitment, provided it was stable for the previous five years. We assessed LAN exposure through 2015 nighttime luminance satellite images from the Visible Infrared Imaging Radiometer Suite (VIIRS). Using a logistic regression model adjusted for age, sex, and education, we calculated the risk of dementia associated with increasing LAN exposure, namely using <10 nW/cm2/sr as reference and considering ≥10-<40 nW/cm2/sr intermediate and ≥40 nW/cm2/sr high exposure, respectively We also implemented non-linear assessment using a spline regression model.
We recruited 58 EOD cases, 34 LOD cases and 54 controls. Average LAN exposure levels overlapped for EOD cases and controls, while LOD cases showed higher levels. Compared with the lowest exposure, the risk of EOD associated with LAN was higher in the intermediate exposure (OR = 1.36, 95% CI 0.54–3.39), but not in the high exposure category (OR = 1.04, 95% CI 0.32–3.34). In contrast, the risk of LOD was positively associated with LAN exposure, with ORs of 2.58 (95% CI 0.26–25.97) and 3.50 (95% CI 0.32–38.87) in the intermediate and high exposure categories, respectively. The spline regression analysis showed substantial lack of association between LAN and EOD, while almost linear although highly imprecise association emerged for LOD.
Although the precision of the estimates was affected by the limited sample size and the study design did not allow us to exclude the presence of residual confounding, these results suggest a possible role of LAN in the etiology of dementia, particularly of its late-onset form.
This work originates from an epidemiological study aimed to assess the correlation between population exposure to pesticides used in agriculture and adverse health effects. In support of the ...population exposure evaluation two models implemented by the authors were applied: a GIS-based proximity model and the CAREA atmospheric dispersion model. In this work, the results of the two models are presented and compared. Despite the proximity analysis is widely used for these kinds of studies, it was investigated how meteorology could affect the exposure assessment. Both models were applied to pesticides emitted by 1519 agricultural fields and considering 2584 receptors distributed over an area of 8430 km2. CAREA output shows a considerable enhancement in the percentage of exposed receptors, from the 4% of the proximity model to the 54% of the CAREA model. Moreover, the spatial analysis of the results on a specific test site showed that the effects of meteorology considered by CAREA led to an anisotropic exposure distribution that differs considerably from the symmetric distribution resulting by the proximity model. In addition, the results of a field campaign for the definition and planning of ground measurement of concentration for the validation of CAREA are presented. The preliminary results showed how, during treatments, pesticide concentrations distant from the fields are significantly higher than background values.
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