A source classification framework supporting pollutant source mapping,pollutant release prediction,transport and load forecasting,and source control planning for urban environments

Purpose

Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured pollutant source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose.

Methods

Existing source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority pollutants in Europe.

Results

The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority pollutant release data.

Conclusions

The SCF provides a well-structured approach for European pollutant source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.

     

Trends of brominated diphenyl ethers in fresh and archived Great Lakes fish (1979-2005)

While few environmental measurements of brominated diphenyl ethers (BDEs) were completed prior to the mid-1990s, analysis of appropriately archived samples might enable the determination of contaminant trends back to the introduction of these chemicals. In this paper, we first investigate the stability of BDEs in archived frozen and extracted fish samples, and then characterize trends of these chemicals in rainbow smelt (Osmerus mordax) and lake trout (Salvelinus namaycush) in each of the Great Lakes between 1979 and 2005. We focus on the four most common congeners (BDE-47, 100, 99 and 153) and use a change-point analysis to detect shifts in trends. Analyses of archived fish samples yielded precise BDE concentration measurements with only small losses (0.8% per year in frozen fish tissues, 2.2% per year in refrigerated extracts). Trends in fish from all Great Lakes showed large increases in BDE concentrations that started in the early to mid-1980s with fairly consistent doubling times (generally 2-4 years except in Lake Erie smelt where levels increased very slowly), though concentrations and trends show differences by congener, fish species and lake. The most recent data show that accumulation rates are slowing, and concentrations of penta- and hexa-congeners in trout from Lakes Ontario and Michigan and smelt from Lake Ontario started to decrease in the mid-1990s. Trends in smelt and trout are evolving somewhat differently, and trout concentrations in the five lakes are now ranked as Michigan>Superior=Ontario>Huron=Erie, and smelt concentrations as Michigan>Ontario>Huron>Superior>Erie. The analysis of properly archived samples permits the reconstruction of historical trends, congener distributions, biomagnification and other information that can aid the understanding and management of these contaminants.     

Regional coexistence and local dominance in Chaoborus: species sorting along a predation gradient

Variation in the intensity of predation across the well-known environmental gradient of freshwater habitats from small, ephemeral ponds to large, permanent lakes is a key factor in the development and maintenance of aquatic community structure. Here, we present data on the distribution and abundance of four species of Chaoborus (Diptera: Chaoboridae) across this environmental gradient. Chaoborus show a distinct pattern of species sorting when aquatic systems are divided into fish and fishless environments, and this pattern is consistent with species traits known to influence their vulnerability to fish predation (i.e., pigmentation, diel vertical migration [DVM] behavior, and body size). To test whether fish are the drivers of this pattern, we created a gradient in fish density by stocking bluegill sunfish (Lepomis macrochirus) into 15 experimental ponds in southwestern Michigan, USA, and then allowed Chaoborus species to colonize. There was clear evidence of species sorting along the predation gradient; Chaoborus americanus was most abundant in the fishless ponds, C. flavicans was neutral in response to fish, and C. punctipennis and C. albatus were most abundant at high fish biomass, a response consistent with their field pattern. Furthermore, prey preference experiments confirm that size selective predation and differences in Chaoborus species traits contribute to the pattern of Chaoborus abundance and distribution.     

Rareness and specialization in plant-pollinator networks

Most rare species appear to be specialists in plant-pollinator networks. This observation could result either from real ecological processes or from sampling artifacts. Several methods have been proposed to overcome these artifacts, but they have the limitation of being based on visitation data, causing interactions involving rare visitor species to remain undersampled. We propose the analysis of food composition in bee trap nests to assess the reliability of network specialization estimates. We compared data from a plant-pollinator network in the Monte Desert of Villavicencio Nature Reserve, Argentina, sampled by visit observation, and data from trap nests sampled at the same time and location. Our study shows that trap nest sampling was good for estimating rare species degree. The rare species in the networks appear to be more specialized than they really are, and the bias in the estimation of the species degree increases with the rareness. The low species degree of these rare species in the visitation networks results from insufficient sampling of the rare interactions, which could have important consequences for network structure.     

Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization

A combination of in-situ PM_2.5, sunphotometers, upward pointing lidar and satellite aerosol optical depth (AOD) instruments have been employed to better understand variability in the correlation between AOD and PM_2.5 at the surface. Previous studies have shown good correlation between these measures, especially in the US east, and encouraged the use of satellite data for spatially interpolating between ground sensors. This work shows that cases of weak correlation can be better understood with knowledge of whether the aerosol is confined to the surface planetary boundary layer (PBL) or aloft. Lidar apportionment of the fraction of aerosol optical depth that is within the PBL can be scaled to give better agreement with surface PM_2.5 than does the total column amount. The study has shown that lidar combined with surface and remotely sensed data might be strategically used to improve our understanding of long-range or regionally transported pollutants in multiple dimensions.     

A performance-based tabular approach for joint systematic improvement of risk control and resilience applied to telecommunication grid,gas network,and ultrasound localization system

Environment Systems and Decisions - Organizational and technical approaches have proven successful in increasing the performance and preventing risks at socio-technical systems at all scales....