Modelling local and synoptic scale influences on ozone concentrations in a topographically complex region of Southern Italy

A modelling study with the on-line coupled Eulerian chemical-weather model WRF/Chem for the Southern Italian region around Cosenza (Calabria) was conducted to identify the influences of synoptic scale meteorology, local scale wind systems and local emissions on ozone concentrations in this orographically complex region. Four periods of 5–7 days were chosen, one from each season, which had wind pattern characteristics representative of typical local climatological conditions, in order to study the local versus non-local impacts on ozone transport and formation. To account for the complex terrain, the horizontal resolution of the smallest modelling domain was 3 km. Model results were compared with measurements to demonstrate the capability of the model to reproduce ozone concentrations in the region. The comparison was favourable with a mean bias of ?1.1 ppb. The importance of local emissions on ozone formation and destruction was identified with the use of three different emission scenarios. Generally the influence of regional emissions on the average ozone concentration was small. However during periods when mountain-sea wind systems were well developed and synoptic scale winds were weak, the influence of local emissions from the urban area was at its greatest. The maximum influence of local emissions on ozone concentrations was 18 ppb.     

Wintertime size distribution of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in the urban environment: Street- vs rooftop-level measurements

The size distribution of ambient air particles and associated organic pollutants, such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs) including hexachlorocyclohexanes (HCHs), DDT and metabolites, etc., was investigated at a traffic-impacted site of Thessaloniki, Greece. Investigation took place during wintertime of 2006 at two heights above ground: at the street level (1.5 m) and at the rooftop level (15 m). Size-resolved samples (<0.95 μm, 0.95–1.5 μm, 1.5–3 μm, 3–7.5 μm and >7.5 μm) were concurrently collected from the two height levels using five-stage high volume cascade impactors. At both heights, particle mass exhibited bimodal distribution with peaks in the 0.95–1.5 μm and the 3–7.5 μm size fractions, whereas most organic pollutants exhibited one peak at 0.95–1.5 μm. Apart from the 0.95–1.5 μm fraction, particle concentrations of all size ranges were significantly higher at the street level than at the rooftop as a result of more intensive vehicular emissions and road dust resuspension. On the contrary, the concentrations of most organic pollutants did not differentiate significantly between the two elevations.     

Catchment-wide assessment of the cost-effectiveness of stormwater remediation measures in urban areas

The cost effectiveness of catchment-wide funding for the environmental remediation of urban waterways on the scale of a major metropolitan catchment is examined considering the typical land-use and pollutant-export characteristics of urban catchments. The evaluation is performed by comparing the effectiveness of the major stormwater treatment modes for the pollutants of concern with the proportion of pollutant export to which the measure applies. The heavy metals copper, lead, and zinc in the aqueous phase or bound to fine particulates are identified as representative of the pollutants of concern in drainage from urban catchments. The analysis suggests that these priority pollutants are predominantly (79–87%) derived from runoff from residential property and roads as disseminated urban surfaces. Analysis of a specific case of catchment-wide funding of stormwater remediation in the Sydney Harbour catchment, Australia reveals that the funding allocation cannot be expected to have achieved reductions in the loads of priority pollutants due to the types of treatment measures implemented and the sources addressed. The apportionment of funding in better accordance with the maximum potential effectiveness of stormwater treatment modes and the pollutant-export characteristics of urban catchments could thus be expected to achieve a more cost-effective result from such funding initiatives.     

Carbon accumulation through ecosystem recovery

A market has emerged for carbon sequestered through reforestation. The opportunity to restore ecosystems through this market rather than establish plantations is demonstrated by an Australian case study. In the state of Queensland there are vast areas that have been cleared relatively recently and could be restored to ecosystems with high resilience and important biodiversity values with appropriate management. In order to foster opportunities for carbon accumulation through ecosystem recovery spatially explicit information on sequestration rates, management recommendations, and clear definitions of ancillary biodiversity benefits need to be defined.     

Improving inverse model fitting in trees—Anisotropy,multiplicative effects,and Bayes estimation

Model fitting for individual-based effects in forests has some problems. Because samples measuring the separate influence of each individual are rarely available, the measured value in the sample represents the influence of all surrounding individual trees. Therefore, it is helpful to build inverse models that use the spatial pattern of the variable as well as that of the source trees. For example, since seed dispersal is influenced by wind effects, a model is discussed describing anisotropic effects to ensure an unbiased estimate of the total fruit number. Further, we present a model describing the absorption of radiation by trees. In this case a multiplicative combination of individual effects yields the total effect. Our approach uses logarithmic transformations of the original data to model multiplicative combinations as sum of transformed single effects. For fitting model parameters we propose an approach based on Bayesian statistics, to ensure ecologically interpretable parameters.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.