Monitoring Nitrogen Dioxide and its Effects on Asthmatic Patients: Two Different Strategies Compared

Objectives: To develop a `methodologyassessment' to evaluate the strengths and theweaknesses of two different epidemiological approachesand to identify the best suited monitoring strategy tomeasure the effects of `normal levels' of nitrogendioxide exposure on the health of an urban population.Methodology: all exposures to nitrogen dioxidewere determined with passive samplers, each samplerconsisting of 3 measuring Palmes tubes. In the firststudy the nitrogen dioxide exposure was assessed in 23school children (11 asthmatic and 12 non asthmatic).Children wore samplers for a week and parallelmeasurements were made in their kitchens, in bedroomsand outside their homes. The second study consisted ina case-control study where the relative risk ofhospital admission was calculated considering nitrogendioxide levels in a city of northern Italy. 110asthmatic patients were compared to a control group of 5322 people.Results: Personal sampler measurementshighlighted significant differences in exposure when nitrogen dioxide atmospheric levels were compared inasthmatic and healthy children (p<0.05). No otherparameters were significant in the two groups. Asignificant action of atmospheric nitrogen dioxide onhospital admission was demonstrated (p<0.01).Conclusions: Although a cause-effect relation assuch cannot be identified, the studies show a relationbetween the exposure to nitrogen dioxide and thepresence of adverse effects on people's health.However the `disadvantage' is for subjects withasthmatic pathologies, compared to the others. Tomanage this problem most effectively, a combinedapproach with the activation of specific personalmonitoring campaigns of the subjects with verifiedrisk seems necessary. This requires `reading' the dataresulting from most extensive and up to dateinformation systems, capable of a thorough controlboth of the living environment and of the clinicaloutcome of the whole population.     

Transition index maps for urban growth simulation: application of artificial neural networks,weight of evidence and fuzzy multi-criteria evaluation

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.     

Multi-metric evaluation of the models WARM,CropSyst, and WOFOST for rice

WARM (Water Accounting Rice Model) simulates paddy rice (Oryza sativa L.), based on temperature-driven development and radiation-driven crop growth. It also simulates: biomass partitioning, floodwater effect on temperature, spikelet sterility, floodwater and chemicals management, and soil hydrology. Biomass estimates from WARM were evaluated and compared with the ones from two generic crop models (CropSyst, WOFOST). The test-area was the Po Valley (Italy). Data collected at six sites from 1989 to 2004 from rice crops grown under flooded and non-limiting conditions were split into a calibration (to estimate some model parameters) and a validation set. For model evaluation, a fuzzy-logic based multiple-metrics indicator (MQI) was used: 0 (best) ≤ MQI ≤ 1 (worst). WARM estimates compared well with the actual data (mean MQI = 0.037 against 0.167 and 0.173 with CropSyst and WOFOST, respectively). On an average, the three models performed similarly for individual validation metrics such as modelling efficiency (EF > 0.90) and correlation coefficient (R > 0.98). WARM performed best in a weighed measure of the Akaike Information Criterion: (worst) 0<wk<1$0<w_k<1$ (best), considering estimation accuracy and number of parameters required to achieve it (mean wk=0.983$w_k=0.983$ against 0.007 and ∼0.000 with CropSyst and WOFOST, respectively). WARM results were sensitive to 30% of the model parameters (ratio being lower with both CropSyst, <10%, and WOFOST, <20%), but appeared the easiest model to use because of the lowest number of crop parameters required (10 against 15 and 34 with CropSyst and WOFOST, respectively). This study provides a concrete example of the possibilities offered using a range of assessment metrics to evaluate model estimates, predictive capabilities, and complexity.     

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 × 2 × 2 × 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5–13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection.     

The effects of the nitrofuran furaltadone on Ulva lactuca

The use of pharmaceuticals in the food production industry as prophylatic and therapeutic agents is necessary to promote animal health, but may entail significant consequences to natural ecosystems, especially in the cases of overdosing and use of banned pharmaceuticals. The vast effects that antibiotics released into the environment have on non-target organisms are already under the scope of researchers but little attention has been given to primary producers such as macroalgae. The present study assessed furaltadone’s, an antibacterial agent illegally used for veterinary purposes, uptake capacity by Ulva lactuca and its effect in the growth of this cosmopolitan macroalgae. Differences in macroalgal growth were shown when submitted to prophylactic and therapeutic concentrations of furaltadone in the water (16 and 32 μg mL⁻¹, respectively). The therapeutic concentration caused higher growth impairment than the prophylactic treatment did, with 87.5% and 58% reductions respectively. Furthermore, together with data collected from the accumulation assays, with values of internal concentrations as high as 18.84 μg g⁻¹ WW, suggest that the macroalgae U. lactuca should be included in field surveys as a biomonitor for the detection of nitrofurans.     

Seasonal and spatial variability of polychlorinated biphenyls (PCBs) in vegetation and cow milk from a high altitude pasture in the Italian Alps

The seasonal and spatial variability of polychlorinated biphenyls (PCBs) in vegetation and cow milk was studied in a high altitude pasture in the Alps (1900 m a.s.l.). PCB contamination in vegetation shows a concentration peak in June, which is mainly interpreted as the consequence of a temporary PCB enrichment of the air layer above the ground due to net emission fluxes from the soil. A three compartment dynamic model was developed to test this hypothesis. The North/South enrichment factor in the vegetation was 1.5-1.6 for penta- and hexa-substituted congeners and 1.7 for hepta- and octa-PCBs, according to the effect of temperature on compounds having higher K_oa values. Milk concentrations followed the vegetation seasonal trend. The congener abundance in milk is in agreement with the biotransformation susceptibility, absorption efficiency and residence time of the different congeners in dairy cows.     

Evaluating land cover change and its impact on hydrological regime in Upper Shire river catchment, Malawi

A study was conducted to investigate hydrological impacts of land cover changes in the degradation of the hydrological on flow regimes of the Upper Shire river, Malawi. Remote sensing techniques were used to inventory temporal changes of land cover changes in the catchment. Hydrological data were analyzed to reveal the alterations and trends for two periods; 1989 and 2002. The study revealed significant changes in magnitude and direction that have occurred in the catchment between 1989 and 2002, mainly in areas of human habitation. Trends in land cover change in the Upper Shire river catchment depict land cover transition from woodlands to mostly cultivated/grazing and built-up areas. The land cover mapping showed that 23% of the land was covered by agricultural land in 1989. Subsistence agricultural area has increased by 18%, occupying 41% of the study area in 2002. The effects of the derived land cover changes on river flow in the Upper Shire river were investigated using the semi distributed soil and water assessment tool (SWAT) model. River flows were found to be highly variable and sensitive to land cover changes. Simulation results show that 2002 land cover data produces higher flow peaks and faster travel times compared to the 1989 land cover data. The changes detected indicate the effects of land use pressure in the catchment. The study highlights the importance of considering effects of land use and land cover changes on ecosystems, and water resources for an informed decision on proper catchment planning and management.