Exposure to ultrafine and fine particles and noise during cycling and driving in 11 Dutch cities

Recent studies have suggested that exposures during traffic participation may be associated with adverse health effects. Traffic participation involves relatively short but high exposures. Potentially relevant exposures include ultrafine particles, fine particles (PM_2.5) and noise.Simultaneously, detailed real time exposure of particle number concentration (PNC), PM_2.5 and noise has been measured while driving and cycling 12 predefined routes of approximately 10–20 min duration. Sampling took place in eleven medium-sized Dutch cities on eleven weekdays in August till October 2006. To investigate variability in cyclists exposure, we systematically collected information on meteorology, GPS coordinates, type of road, traffic intensity, passing vehicles and mopeds while cycling.The overall mean PNC of car drivers was 5% higher than the mean PNC of cyclists. The overall mean concentration of PM_2.5 in the car was 11% higher than during cycling. Slightly higher 1-min peak concentrations were measured in the car (PNC 14%; PM_2.5 29% for 95-percentiles). Shorter duration peaks of PNC were higher during cycling (43% for 99-percentile of 1-s averages). Peaks in PNC typically last for less than 10 s. A large variability of exposure was found within and between routes. Factors that significantly predicted PNC variability during cycling were: passing vehicles (mopeds, cars), waiting for traffic lights, passing different types of (large) intersections and bicycle lanes and bike paths close to motorized traffic. No relation was found between PM_2.5 and those predictor variables. The correlation between PNC and noise was moderate (median 0.34). PM_2.5 had very low correlations with PNC and noise.PNC and PM_2.5 exposure of car drivers was slightly higher than that of cyclists. PNC was largely uncorrelated with PM_2.5 and reflected local traffic variables more than PM_2.5. Different factors were associated with high PNC and high noise exposures.     

Environmental bonds and the challenge of long-term carbon sequestration

The potential to capture carbon from industrial sources and dispose of it for the long-term, known as carbon capture and sequestration (CCS), is widely recognized as an important option to reduce atmospheric carbon dioxide emissions. Specifically, CCS has the potential to provide emissions cuts sufficient to stabilize greenhouse gas levels, while still allowing for the continued use of fossil fuels. In addition, CCS is both technologically-feasible and commercially viable compared with alternatives with the same emissions profile. Although the concept appears to be solid from a technical perspective, initial public perceptions of the technology are uncertain. Moreover, little attention has been paid to developing an understanding of the social and political institutional infrastructure necessary to implement CCS projects. In this paper we explore a particularly dicey issue--how to ensure adequate long-term monitoring and maintenance of the carbon sequestration sites. Bonding mechanisms have been suggested as a potential mechanism to reduce these problems (where bonding refers to financial instruments used to ensure regulatory or contractual commitments). Such mechanisms have been successfully applied in a number of settings (e.g., to ensure court appearances, completion of construction projects, and payment of taxes). The paper examines the use of bonding to address environmental problems and looks at its possible application to nascent CCS projects. We also present evidence on the use of bonding for other projects involving deep underground injection of materials for the purpose of long-term storage or disposal.     

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

Passive samplers versus surfactant extraction for the evaluation of PAH availability in sediments with variable levels of contamination

The purpose of this study was to test the efficiency of passive solid samplers, polyoxymethylene (POM) strips and polydimethylsiloxane (PDMS) silicon tubing, to predict the bioavailability of native PAHs in contaminated sediments. Results were compared with worm bioaccumulation data and solid/liquid extraction using the surfactant Brij((R)) 700 (B700). The two passive samplers were found to act differently. The PDMS sampler overestimated the availability of PAHs in all studied sediments. The POM method provided results in accordance with those obtained with the B700 extraction. However, POM and B700 methods underestimated PAH availability in low contaminated sediments where biological factors (digestible organic matter) become important. Bioavailability of total PAHs was correctly predicted by POM and B700 in highly contaminated aluminum smelter sediments. A closer examination of individual PAH results indicated that both techniques overestimated the availability of large molecules with logK(ow)>6 suggesting a biological mechanism limiting uptake of larger PAHs which seems to be related to the molecular size of compounds.     

QUANTIFYING URBAN INTENSITY IN DRAINAGE BASINS FOR ASSESSING STREAM ECOLOGICAL CONDITIONS1

ABSTRACT: Three investigations are underway, as part of the U.S. Geological Survey's National Water‐Quality Assessment (NAWQA) Program, to study the relation between varying levels of urban intensity in drainage basins and in‐stream water quality, measured by physical, chemical, and biological factors. These studies are being conducted in the vicinities of Boston (Massachusetts), Salt Lake City (Utah), and Birmingham (Alabama), areas where rapid urbanization is occurring. For each study, water quality will be sampled in approximately 30 drainage basins that represent a gradient of urban intensity. This paper focuses on the methods used to characterize and select the basins used in the studies. It presents a methodology for limiting the variability of natural landscape characteristics in the potential study drainage basins and for ranking the magnitude of human influence, or urbanization, based on land cover, infrastructure, and socioeconomic data in potential study basins. Basin characterization efforts associated with the Boston study are described for illustrative purposes.     

A comparison of taxon co-occurrence patterns for macro- and microorganisms

We examine co-occurrence patterns of microorganisms to evaluate community assembly "rules". We use methods previously applied to macroorganisms, both to evaluate their applicability to microorganisms and to allow comparison of co-occurrence patterns observed in microorganisms to those found in macroorganisms. We use a null model analysis of 124 incidence matrices from microbial communities, including bacteria, archaea, fungi, and algae, and we compare these results to previously published findings from a meta-analysis of almost 100 macroorganism data sets. We show that assemblages of microorganisms demonstrate nonrandom patterns of co-occurrence that are broadly similar to those found in assemblages of macroorganisms. These results suggest that some taxon co-occurrence patterns may be general characteristics of communities of organisms from all domains of life. We also find that co-occurrence in microbial communities does not vary among taxonomic groups or habitat types. However, we find that the degree of co-occurrence does vary among studies that use different methods to survey microbial communities. Finally, we discuss the potential effects of the undersampling of microbial communities on our results, as well as processes that may contribute to nonrandom patterns of co-occurrence in both macrobial and microbial communities such as competition, habitat filtering, historical effects, and neutral processes.     

Towards a framework for assessment and management of cumulative human impacts on marine food webs

Effective ecosystem‐based management requires understanding ecosystem responses to multiple human threats, rather than focusing on single threats. To understand ecosystem responses to anthropogenic threats holistically, it is necessary to know how threats affect different components within ecosystems and ultimately alter ecosystem functioning. We used a case study of a Mediterranean seagrass (Posidonia oceanica) food web and expert knowledge elicitation in an application of the initial steps of a framework for assessment of cumulative human impacts on food webs. We produced a conceptual seagrass food web model, determined the main trophic relationships, identified the main threats to the food web components, and assessed the components’ vulnerability to those threats. Some threats had high (e.g., coastal infrastructure) or low impacts (e.g., agricultural runoff) on all food web components, whereas others (e.g., introduced carnivores) had very different impacts on each component. Partitioning the ecosystem into its components enabled us to identify threats previously overlooked and to reevaluate the importance of threats commonly perceived as major. By incorporating this understanding of system vulnerability with data on changes in the state of each threat (e.g., decreasing domestic pollution and increasing fishing) into a food web model, managers may be better able to estimate and predict cumulative human impacts on ecosystems and to prioritize conservation actions.     

Spatial and Seasonal Variation of Dissolved Organic Carbon (DOC) Concentrations in Irish Streams: Importance of Soil and Topography Characteristics

Dissolved organic carbon (DOC) concentrations have increased in many sites in Europe and North America in recent decades. High DOC concentrations can damage the structure and functions of aquatic ecosystems by influencing water chemistry. This study investigated the spatial and seasonal variation of DOC concentrations in Irish streams across 55 sites at seven time occasions over 1 year (2006/2007). The DOC concentrations ranged from 0.9 to 25.9 mg/L with a mean value of 6.8 and a median value of 5.7 mg/L and varied significantly over the course of the year. The DOC concentrations from late winter (February: 5.2 ± 3.0 mg/L across 55 sites) and early spring (April: 4.5 ± 3.5 mg/L) had significantly lower DOC concentrations than autumn (October: mean 8.3 ± 5.6 mg/L) and early winter (December: 8.3 ± 5.1 mg/L). The DOC production sources (e.g., litterfall) or the accumulation of DOC over dry periods might be the driving factor of seasonal change in Irish stream DOC concentrations. Analysis of data using stepwise multiple linear regression techniques identified the topographic index (TI, an indication of saturation-excess runoff potential) and soil conditions (organic carbon content and soil drainage characteristics) as key factors in controlling DOC spatial variation in different seasons. The TI and soil carbon content (e.g., soil organic carbon; peat occurrence) are positively related to DOC concentrations, while well-drained soils are negatively related to DOC concentrations. The knowledge of spatial and seasonal variation of DOC concentrations in streams and their drivers are essential for optimum riverine water resources management.