Integrated Ambient and Microenvironment Model for Estimation of PM10 Exposures of Children in Annual and Episode Settings

Particulate matter air pollution is estimated to cause in the order of 350,000 excess deaths in the European Union calling for policy development and evaluation tools. In the current work, a model for PM₁₀ exposures of children is developed using microenvironment time activities and infiltration of ambient pollution indoors, both evaluated against observations earlier and integrated with city-wide air quality models in the current work. The model is demonstrated using data from two cities in Italy. High-end short-term exposures are characterized by an episode-day situation in Turin, and annual mean exposures in downtown Bologna. The air quality model was unable to capture the highest levels during the episode, and therefore, the exposure model was adjusted using observed–modeled ratio from a monitoring station. Air quality model performance for the annual levels was significantly better. Annual exposure variability within the target population was 1.5-fold in the downtown area Bologna and tenfold during the episode day in Turin.     

Exploring management strategies for community-based forests using multi-agent systems: A case study in Palawan, Philippines

This paper describes the experiences and lessons learned in applying a multi-agent systems (MAS) model to study the dynamics and complex interactions among stakeholders in the management of community-based forests. The MAS model is developed using the companion modelling (ComMod) approach, which allows for a collaborative development of the model between the stakeholders and researchers. This approach involves the development and application of role-playing games (RPGs) and computer simulation as learning tools and to validate the model. Inferences are drawn from the learning and negotiation processes that the stakeholders and researchers underwent in the collaborative development of the MAS model. These processes ultimately led to the development of a collaborative resource management plan. The approach and the MAS model were applied to a case study involving a community-based forest managed by three villages in the island of Palawan, Philippines.     

Predicting dioxin-like PCBs soil contamination levels using milk of grazing animal as indicator

Dioxin-like PCBs (dl-PCBs) are ubiquitous persistent organic pollutants of recognized negative effects on human health. Assessing highly polluted areas should be an important public health issue. This study proposes to use the milk of grazing animals as a bioindicator of dl-PCB contamination in the environment. The hypothesis is that milk concentration of dl-PCBs are related to soil concentrations of these compounds, and that soils are generally reflective of a larger environmental issue of dl-PCB contamination. In this study, we evaluate the possibility of predicting soil concentrations using milk of sheep, cows and buffalos in a spatial model. For this purpose, samples of soil and milk collected in Campania (Italy) were introduced in a GIS platform to perform geostatistical analysis for building a simple predictive model. The ordinary least squares regressions (OLS) showed a statistically significant correlation (p < 0.05) between soil and milk contamination. However, this relationship was spatially variable. Thus, a geographically weighted regression (GWR) was performed, obtaining R² values of 0.91, 0.77 and 0.66 for sheep’s, buffalo’s and cow’s milk respectively. Assessed the mathematical relationships between the variables, new data was introduced to evaluate the performance of the model. Predictions of soil contamination with dl-PCBs using sheep’s, cow’s and buffalo’s milk showed a mean error of 23%, 25% and 36% respectively. According to these results the sheep’s milk can be considered the best bioindicator of dl-PCBs contamination among the three species. The results of this project evidence the potentialities of the proposed approach to assess bioindicator performance in a spatial predictive model.     

Sun light degradation of 4-chloroaniline in waters and its effect on toxicity. A high performance liquid chromatography - Diode array - Tandem mass spectrometry study

This paper studies the degradation reactions that 4-chloroaniline can naturally undergo in waters for the action of sun light. 10.00 mg L⁻¹ 4-chloroaniline aqueous solution, without any addition of organic solvent, are undergone to photoirradiation under conditions that simulate sun light. The degradation pathway, followed by HPLC-DAD-MS/MS methods, is complex since the pollutant gives rise to many photoproducts: the predominant species are characterized by m/z values of 217 (P5) and 218 (P6) and are compatible with dimeric structures of 4-chloroaniline. Vibrio fischeri tests indicate that the photoproducts of 4-chloroaniline are characterized by a toxicity level significantly greater than the precursor.     

Aerospace wetland monitoring by hyperspectral imaging sensors: a case study in the coastal zone of San Rossore Natural Park

The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces.     

Spatial distribution and partitioning of polychlorinated biphenyl and organochlorine pesticide in water and sediment from Sarno River and Estuary,Southern Italy

The Sarno River is nicknamed “the most polluted river in Europe”. The main goal of this study is to enhance our knowledge on the Sarno River water and sediment quality and on its environmental impact on the gulf of Naples (Tyrrhenian Sea, Central Mediterranean Sea) in order to become a useful assessment tool for the regional administrations. For these reasons, 32 selected polychlorinated biphenyls (PCBs) and aldrin, α-BHC, β-BHC, δ-BHC, γ-BHC (lindane), 4,4′-DDD, 4,4′-DDE, 4,4′-DDT, dieldrin, endosulfan I, endosulfan II, endosulfan sulphate, endrin, endrin aldehyde, heptachlor, heptachlor epoxide (isomer B) and methoxychlor were determined in the water dissolved phase (DP), suspended particulate matter (SPM) and sediments. Total concentrations of PCBs ranged from 1.4 to 24.9 ng L^?1 in water (sum of DP and SPM) and from 1.01 to 42.54 ng g^?1 in sediment samples. The concentrations of total organochlorine pesticides (OCPs) obtained in water (sum of DP and SPM) ranged from 0.54 to 7.32 ng L^?1 and from 0.08 to 5.99 ng g^?1 in sediment samples. Contaminant discharges of PCBs and OCPs into the sea were calculated in about 1,247 g day^?1 (948 g day^?1 of PCBs and 326 g day^?1 of OCPs), showing that this river should account as one of the main contribution sources of PCBs and OCPs to the Tyrrhenian Sea.     

Energy and resource basis of an Italian coastal resort region integrated using emergy synthesis

Sustainable development of coastal zones must balance economic development that encourages human visitation from a larger population with desires that differ from the local residents with the need to maintain opportunities for the local resident society and conserve ecological capital, which may serve as the basis for residents.We present a case study in which the sustainability level of a coastal zone (Riviera del Beigua), located along the Ligurian coast of north-western Italy, was assessed through the lens of systems ecology using emergy synthesis to integrate across economic, social and environmental sub-systems.Our purposes were (1) to quantify the environmental sustainability level of this coastal zone, (2) to evaluate the role of tourism in affecting the economy, society and environment, and (3) to compare emergy synthesis to Butler's Tourism Area Life Cycle model (TALC). Results showed that 81% of the total emergy consumption in the coastal zone was derived from external sources, indicating that this tourist-heavy community was not sustainable. Tourism, as the dominant economic sub-system, consumed 42% of the total emergy budget, while local residents used the remaining 58%. The progressive stages of the TALC model were found to parallel the dynamic changes in the ratio of external emergy inputs to local emergy inputs, suggesting that emergy synthesis could be a useful tool for detecting a tourist region's TALC stage. Use of such a quantitative tool could expedite sustainability assessment to allow administrative managers to understand the complex relationship between a region's economy, environment and resident society so sound policies can be developed to improve overall sustainability.     

A multi-scale study of Orthoptera species richness and human population size controlling for sampling effort

Recent large-scale studies have shown that biodiversity-rich regions also tend to be densely populated areas. The most obvious explanation is that biodiversity and human beings tend to match the distribution of energy availability, environmental stability and/or habitat heterogeneity. However, the species–people correlation can also be an artefact, as more populated regions could show more species because of a more thorough sampling. Few studies have tested this sampling bias hypothesis. Using a newly collated dataset, we studied whether Orthoptera species richness is related to human population size in Italy’s regions (average area 15,000 km²) and provinces (2,900 km²). As expected, the observed number of species increases significantly with increasing human population size for both grain sizes, although the proportion of variance explained is minimal at the provincial level. However, variations in observed Orthoptera species richness are primarily associated with the available number of records, which is in turn well correlated with human population size (at least at the regional level). Estimated Orthoptera species richness (Chao2 and Jackknife) also increases with human population size both for regions and provinces. Both for regions and provinces, this increase is not significant when controlling for variation in area and number of records. Our study confirms the hypothesis that broad-scale human population–biodiversity correlations can in some cases be artefactual. More systematic sampling of less studied taxa such as invertebrates is necessary to ascertain whether biogeographical patterns persist when sampling effort is kept constant or included in models.