Assessing Satellite Data’s Role in Substituting Ground Measurements for Urban Surfaces Characterization: A Step towards UHI Mitigation

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

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study

(1) Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with still unknown etiology. Some occupational and environmental risk factors have been suggested, including long-term air pollutant exposure. We carried out a pilot case-control study in order to evaluate ALS risk due to particulate matter with a diameter of ≤10 µm (PM10) as a proxy of vehicular traffic exposure. (2) Methods: We recruited ALS patients and controls referred to the Modena Neurology ALS Care Center between 1994 and 2015. Using a geographical information system, we modeled PM10 concentrations due to traffic emissions at the geocoded residence address at the date of case diagnosis. We computed the odds ratio (OR) and 95% confidence interval (CI) of ALS according to increasing PM10 exposure, using an unconditional logistic regression model adjusted for age and sex. (3) Results: For the 132 study participants (52 cases and 80 controls), the average of annual median and maximum PM10 concentrations were 5.2 and 38.6 µg/m3, respectively. Using fixed cutpoints at 5, 10, and 20 of the annual median PM10 levels, and compared with exposure <5 µg/m3, we found no excess ALS risk at 5-10 µg/m3 (OR 0.87, 95% CI 0.39-1.96), 10-20 µg/m3 (0.94, 95% CI 0.24-3.70), and ≥20 µg/m3 (0.87, 95% CI 0.05-15.01). Based on maximum PM10 concentrations, we found a statistically unstable excess ALS risk for subjects exposed at 10-20 µg/m3 (OR 4.27, 95% CI 0.69-26.51) compared with those exposed <10 µg/m3. However, risk decreased at 20-50 µg/m3 (OR 1.49, 95% CI 0.39-5.75) and ≥50 µg/m3 (1.16, 95% CI 0.28-4.82). ALS risk in increasing tertiles of exposure showed a similar null association, while comparison between the highest and the three lowest quartiles lumped together showed little evidence for an excess risk at PM10 concentrations (OR 1.13, 95% CI 0.50-2.55). After restricting the analysis to subjects with stable residence, we found substantially similar results. (4) Conclusions: In this pilot study, we found limited evidence of an increased ALS risk due to long-term exposure at high PM10 concentration, though the high statistical imprecision of the risk estimates, due to the small sample size, particularly in some exposure categories, limited our capacity to detect small increases in risk, and further larger studies are needed to assess this relation

Residential proximity to petrol stations and risk of childhood leukemia

Petrol stations emit benzene and other contaminants that have been associated with an increased risk of childhood leukemia. We carried out a population-based case-control study in two provinces in Northern Italy. We enrolled 182 cases of childhood leukemia diagnosed during 1998-2019 and 726 age- and sex-matched population controls. We geocoded the addresses of child residences and 790 petrol stations located in the study area. We estimated leukemia risk according to distance from petrol stations within a 1000 m buffer and amount of supplied fuel within a buffer of 250 m from the child's residence. We used conditional logistic regression models to approximate risk ratios (RRs) and 95% confidence intervals (CIs) for associations of interest, adjusted for potential confounders. We also modeled non-linear associations using restricted cubic splines. In secondary analyses, we restricted to acute lymphoblastic leukemia (ALL) cases and stratifed by age (<5 and >= 5 years). Compared with children who lived >= 1000 m from a petrol station, the RR was 2.2 (95% CI 0.5-9.4) for children living<50 m from nearest petrol station. Associations were stronger for the ALL subtype (RR=2.9, 95% CI 0.6-13.4) and among older children (age >= 5 years: RR=4.4, 95% CI 0.6-34.1; age<5 years: RR=1.6, 95% CI 0.1-19.4). Risk of leukemia was also greater (RR=1.6, 95% CI 0.7-3.3) among the most exposed participants when assigning exposure categories based on petrol stations located within 250 m of the child's residence and total amount of gasoline delivered by the stations. Overall, residence within close proximity to a petrol station, especially one with more intense refueling activity, was associated with an increased risk of childhood leukemia, though associations were imprecise

Risk of ALS and passive long-term residential exposure to pesticides: a population based study.

Risk of ALS and passive long-term residential exposure to pesticides: a population based study

Risk of ALS and passive residential exposure to pesticides: a population based study.

. Risk of ALS and passive residential exposure to pesticides: a population based study

Remote sensing and GIS for the modeling of persistent organic pollutant in the marine environment

The characterization of the marine environment plays an important role in the understanding of the dynamics affecting the transport, fate and persistence (TFP) of Persistent Organic Pollutants (POPs). This work is part of a project funded by the Ministero dell’Istruzione, dell’Università e della Ricerca. The aim of the project is the assessment of the TFP of POPs in the Mediterranean sea. The analysis will be carried out at regionalmesoscale (central Mediterranean), and at local spatial scale considering different Italian test sites (the Delta of the Po River, the Venice Lagoon and the estuary of the Rio Nocella). The first step of this work involves the implementation of GIS geodatabases for the definition of the input dataset. The geodatabases were populated with MERIS and MODIS level 2 and level 3 products of Chlorophyll-a (CHL-a), Chromophoric Dissolved Organic Matter (CDOM), Aerosol Optical Thickness (AOT), Diffuse Attenuation Coefficient (DAC), Particulate Inorganic Carbon (PIC), Particulate Organic Carbon (POC) and Sea Surface Temperature (SST). The spatial scale (central Mediterranean sea) and the reference system (Plate Carrée projection) have been imposed as a constraint for the geodatabases. Four geodatabases have been implemented, two for MODIS and two for MERIS products with a monthly, seasonal and climatological temporal scale (2002 -2013). Here, we present a first application of a methodology aimed to identify vulnerable areas to POPs accumulation and persistence. The methodology allowed to assess the spatial distribution of the CHL-a in the central Mediterranean sea. The chlorophyll concentration is related to the amount of nutrients in the water and therefore provides an indicator of the potential presence of POPs. A pilot area of 300 x 200 km located in the North Adriatic sea has been initially considered. The seasonal and climatological MODIS and MERIS CHL-a variability were retrieved and compared with in-situ forcing parameters, i.e. Po River discharge rates and wind data. Study outlooks include a better accuracy of the distribution of the vulnerable areas achieved through the use of additional parameters (CDOM, SST, POC), and an assessment of the contribution of the contaminants by atmospheric dry deposition to the marine environment. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only