Methanesulphonic acid (MSA) stratigraphy from a Talos Dome ice core as a tool in depicting sea ice changes and southern atmospheric circulation over the previous 140 years

Firn core methanesulphonic acid (MSA) stratigraphy from Talos Dome (East Antarctica) was compared with anomalies of the satellite-measured sea ice extent (1973–1995) in the Ross Sea and Wilkes Land oceanic sector. In spite of the sparseness of sea ice data, the MSA maxima fit with many positive sea ice anomalies in the Ross Sea. This evidence suggests that marine biogenic activity enhanced by large sea ice cover is an important, but not exclusive, factor in controlling MSA concentration in snow precipitation at Talos Dome. Other than source intensity, differences in regional atmospheric transport mechanisms affect the arrival of MSA-rich aerosol at Talos Dome. To clarify the role of transport processes in bringing biogenic aerosol to Talos Dome, a spectral analysis was applied to the MSA, SOI (South Oscillation Index), and SAM (Southern Annular Mode) record. Synchronicity or phase shift between the chemical signature and atmospheric circulation modes were tested. The variations in the MSA profile have a periodicity of 6.9, 4.9, 3.5, and 2.9 years. The 6.9 and 2.9 year periodicities show a strong positive correlation and are synchronous with corresponding SOI periodicity. This variability could be related to an increase in MSA source intensity (by dimethylsulphide from phytoplanktonic activity) linked to the sea ice extent in the Ross Sea area, but also to an increased strength in transport processes. Both of these factors are correlated with La Niña events (SOI positive values). Furthermore, SAM positive values are related to an increased sea ice extent in the Ross Sea sector and show two main periodicities 3.3 and 3.8 years. These periodicities determine the MSA variability at 3.5 years. However, the effect of intensification of the polar vortex and the consequent reduction in transport process intensity, which reduce the delivery of air masses enriched in MSA from oceanic areas to Talos Dome, make the effect of the SAM on the MSA concentration at Talos Dome less active than the SOI. In this way, snow deposition at the Talos Dome records larger MSA concentration by the combined effects of increased source emissions and more efficient transport processes. The MSA record from Talos Dome can therefore be considered a reliable proxy of sea ice extent when the effect of changes in transport processes in this region of Antarctica is considered. Over the previous 140 years, these conditions occur with a periodicity of 6.9 years.     

Understanding the interacting factors that influence social vulnerability: a case study of the 2016 central Italy earthquake

This paper seeks to identify those areas that proved socially vulnerable to the earthquake that struck central Italy on 24 August 2016. The study involved four key steps. First, six relevant social vulnerability indicators were selected, based on previous conclusions in the literature. Second, the indicators were mapped using the inverse distance weighted interpolation method. Third, social vulnerability was assessed according to a spatial combination of the indicators. Fourth, in order to build a heterogeneity map, another approach was employed to represent the spatial variability of social vulnerability and to provide additional information on the synergistic contributions of the indicators. The results indicate that age and accessibility indicators affect the entire region under review, with highly vulnerable zones being close to small historical centres. These findings will be useful to governments, policymakers, and stakeholders with regard to implementing vulnerability mitigation strategies in Italian territories that are highly susceptible to earthquake hazards.     

Assessing indoor air quality of school environments: transplanted lichen <Emphasis Type="Italic">Pseudovernia furfuracea</Emphasis> as a new tool for biomonitoring and bioaccumulation

The aim of this research is to evaluate the ability of transplanted lichen Pseudovernia (P). furfuracea to biomonitor and bioaccumulate in urban indoor environments. The elements As, Cd, Cr, Cu, Hg, Ni and Pb and 12 selected polycyclic aromatic hydrocarbons (PAHs) were used to assess P. furfuracea as a biomonitoring tool for the indoor air quality of school environments. To achieve this purpose, lichen samples were exposed for 2 months in the outdoor and indoor environments of five school settings located in urban and rural areas. The results demonstrated that transplanted lichen P. furfuracea is a suitable biomonitoring tool for metals and PAHs in indoor settings and can discriminate between different levels of air pollution related to urbanisation and indoor conditions, such as those characterised by school environments. A transplanted lichen biomonitoring strategy is cost-effective, “green”, educational for attending children and less “invasive” than traditional air sampling methods. The feasibility of indoor monitoring by P. furfuracea is a relevant finding and could be a key tool to improve air quality monitoring programmes in school scenarios and thus focus on health prevention interventions for children, who are one of the most susceptible groups in the population.     

Handling of dioxin measurement data in the presence of non-detectable values: overview of available methods and their application in the Seveso chloracne study

Exposure measurements of concentrations that are non-detectable or near the detection limit (DL) are common in environmental research. Proper statistical treatment of non-detects is critical to avoid bias and unnecessary loss of information. In the present work, we present an overview of possible statistical strategies for handling non-detectable values, including deletion, simple substitution, distributional methods, and distribution-based imputation. Simple substitution methods (e.g., substituting 0, DL/2, DL/ radical2, or DL for the non-detects) are the most commonly applied, even though the EPA Guidance for Data Quality Assessment discouraged their use when the percentage of non-detects is >15%. Distribution-based multiple imputation methods, also known as robust or "fill-in" procedures, may produce dependable results even when 50-70% of the observations are non-detects and can be performed using commonly available statistical software. Any statistical analysis can be conducted on the imputed datasets. Results properly reflect the presence of non-detectable values and produce valid statistical inference. We describe the use of distribution-based multiple imputation in a recent investigation conducted on subjects from the Seveso population exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), in which 55.6% of plasma TCDD measurements were non-detects. We suggest that distribution-based multiple imputation be the preferred method to analyze environmental data when substantial proportions of observations are non-detects.     

Assessing coastal vulnerability to climate change: comparing segmentation at global and regional scales

Recent concerns about potential climate-change effects on coastal systems require the application of vulnerability assessment tools in order to define suitable adaptation strategies and improve coastal zone management effectiveness. In fact, while various research efforts were devoted to evaluate coastal vulnerability to climate change on a national to global level, fewer applications were carried out so far to develop more comprehensive and site-specific vulnerability assessments suitable to plan possible adaptation measures at the regional scale. In this respect, specific indicators are needed to address climate-change-related issues for coastal zones and to identify vulnerable areas at the regional level. Two sets of coastal vulnerability indicators were selected, one for regional and one for global studies, respectively, concerning the same features of coastal systems, including topography and slope, geomorphological characteristics, presence and distribution of wetlands and vegetation cover, density of coastal population and number of coastal inhabitants. The proposed set of indicators for the regional scale was chosen taking into account the availability of environmental and territorial data for the whole coastal area of the Veneto region and was based on site-specific datasets characterized by a spatial resolution appropriate for a regional analysis. Moreover, a GIS-based segmentation procedure was applied to divide the coastline into linear segments, homogeneous in terms of vulnerability to climate change and sea-level rise at the regional scale. This approach allowed to divide the Veneto shoreline into 140 segments with an average length of about 1 km, while the global scale approach identified four coastal segments with an average length of about 66 km. The performed comparison indicated how the more detailed approach adopted at the regional scale is essential to understand and manage the complexities of the specific study area. In fact, the 25-m DEM employed at the regional scale provided a more accurate differentiation of the coastal area's elevation and thus of coastal susceptibility to the inundation risks, compared to the 1-km DEM used at the global level. Moreover, at the regional level the use of a 1:20,000 geomorphological map allowed to differentiate the unique landform class detected at the global level (e.g., fluvial plain) in a variety of more detailed coastal typologies (e.g., open coast eroding sandy shores backed by bedrock) characterized by a different sensitivity to climate change and sea-level rise. Accordingly, the information provided by regional indicators can support decision-makers in improving the management of coastal resources by considering the potential impacts of climate change and in the definition of appropriate actions to reduce inundation risks, to avoid the potential loss of valuable wetlands and vegetation and to plan the nourishment of sandy beaches subject to erosion processes.     

Sources and trends of trace elements and polycyclic aromatic hydrocarbons in a shallow lake in the Mediterranean area from sediment archives of the Anthropocene

Environmental Science and Pollution Research - In this study, the anthropogenic contamination in Trasimeno lake (Central Italy) was investigated using three sediment cores spanning over the last...     

Modeling short-term variability of semivolatile organic chemicals in air at a local scale: an integrated modeling approach

Monitoring campaigns from different locations have recently shown how air concentrations of persistent semivolatile contaminants such as polychlorinated biphenyls (PCBs) often exhibit short-term (less than 24 h) variations. The observed patterns have been ascribed to different factors, such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and dynamics. Here, we present a new modeling approach developed in order to investigate the short-term variability in air concentrations of organic pollutants at a local scale. A new dynamic multimedia box model is supplied by a meteorological preprocessor (AERMET) with hourly values of air compartment height and wind speed. The resulting model is tested against an existing dataset of PCB air concentrations measured in Zurich, Switzerland. Results show the importance of such modeling approach in elucidating the short- and long-term behavior of semivolatile contaminants in the air/soil system.