Effects of broadleaf woodland cover on streamwater chemistry and risk assessments of streamwater acidification in acid-sensitive catchments in the UK

Streamwater was sampled at high flows from 14 catchments with different (0-78%) percentages of broadleaf woodland cover in acid-sensitive areas in the UK to investigate whether woodland cover affects streamwater acidification. Significant positive correlations were found between broadleaf woodland cover and streamwater NO3 and Al concentrations. Streamwater NO3 concentrations exceeded non-marine SO4 in three catchments with broadleaf woodland cover>or=50% indicating that NO3 was the principal excess acidifying ion in the catchments dominated by woodland. Comparison of calculated streamwater critical loads with acid deposition totals showed that 11 of the study catchments were not subject to acidification by acidic deposition. Critical loads were exceeded in three catchments, two of which were due to high NO3 concentrations in drainage from areas with large proportions of broadleaved woodland. The results suggest that the current risk assessment methodology should protect acid-sensitive catchments from potential acidification associated with broadleaf woodland expansion.     

The mobility of thiobencarb and fipronil in two flooded rice-growing soils

The mobility of the rice pesticides thiobencarb (S-[(4-chlorophenyl) methyl] diethylcarbamothioate) and fipronil ([5-amino-3-cyano-1-[2,6-dichloro-4-(trifluoromethyl)phenyl]-4-[(trifluoromethyl)sulfinyl]pyrazole) were investigated in the glasshouse under flooded conditions using two Australian rice-growing soils. When using leakage rates of 10 mm day(-1), less than 20% of applied thiobencarb and fipronil remained in the water column after 10 days due to rapid transfer to the soil phase. Up to 70% and 65% of the applied thiobencarb and fipronil, respectively, were recovered from the 0-1 cm layer of soils. Only 5-7% of each pesticide was recovered from the 1-2 cm layer, and less than 2% was recovered from each 1 cm layer in the 2-10 cm region of the soils. Analysis of the water leaking from the base of the soil cores showed between 5-10% of the applied thiobencarb and between 10-20% of the applied fipronil leaching from the soil cores. The high levels of pesticide in the effluent was attributed to preferential flow of pesticide-laden water via soil macropores resulting from the wetting and drying process, worm holes and root channels.     

Effect of overlying water pH, dissolved oxygen, salinity and sediment disturbances on metal release and sequestration from metal contaminated marine sediments

Experiments were undertaken to examine the key variables affecting metal release and sequestration processes in marine sediments with metal concentrations in sediments reaching up to 86, 240, 700, and 3000 mg kg(-1) (dry weight) for Cd, Cu, Pb and Zn, respectively. The metal release and sequestration rates were affected to a much greater extent by changes in overlying water pH (5.5-8.0) and sediment disturbance (by physical mixing) than by changes in dissolved oxygen concentration (3-8 mg l(-1)) or salinity (15-45 practical salinity units). The physical disturbance of sediments was also found to release metals more rapidly than biological disturbance (bioturbation). The rate of oxidative precipitation of released iron and manganese increased as pH decreased and appeared to greatly influence the sequestration rate of released lead and zinc. Released metals were sequestered less rapidly in waters with lower dissolved oxygen concentrations. Sediments bioturbated by the benthic bivalve Tellina deltoidalis caused metal release from the pore waters and higher concentrations of iron and manganese in overlying waters than non-bioturbated sediments. During 21-day sediment exposures, T. deltoidalis accumulated significantly higher tissue concentrations of cadmium, lead and zinc from the metal contaminated sediments compared to controls. This study suggests that despite the fact that lead and zinc were most likely bound as sulfide phases in deeper sediments, the metals maintain their bioavailability because of the continued cycling between pore waters and surface sediments due to physical mixing and bioturbation.     

Improving estimation of indoor exposure to inhalable particles for children in the first year of life

There is growing scientific evidence linking early childhood exposure to environmental agents with asthma and other illnesses that may not appear until later in life. Unfortunately the direct measurement of personal exposures of children in the first year of life is not possible by existing methodologies. This study developed and evaluated a new methodology to better assess exposure of children to inhalable particles in the first year of life while involved in floor play in the home. We constructed the Pre-Toddler Inhalable Particulate Environmental Robotic (PIPER) sampler. Two series of measurements of inhalable particles were carried out. One collected filter samples of airborne inhalable particles and a second used a real-time total particle mass concentration monitor. Samples were collected for seven residential locations. Duplicate samples were collected with PIPER 20 cm above the floor and from an identical stationary monitor positioned at a height of 110 cm. The mean observed airborne inhalable particle concentrations measured by PIPER was 98.6 microg/ m3, whereas simultaneously collected stationary samples mean concentration was 49.8 microg/m3. The average observed ratio of PIPER samples to stationary samples was 2.4. A paired t test comparison of the two sampling methods indicated a statistically significant higher level of inhalable particle concentration measured by PIPER in comparison with the fixed sampler (P < 0.0001). Peak concentrations as measured by a real-time monitor were in excess of 3600 microg/m3. The results suggest that children playing on the floor are exposed to a higher concentration of total inhalable particles than previous methodologies estimate.     

Reproducibility and imputation of air toxics data

Ambient air quality datasets include missing data, values below method detection limits and outliers, and the precision and accuracy of the measurements themselves are often unknown. At the same time, many analyses require continuous data sequences and assume that measurements are error-free. While a variety of data imputation and cleaning techniques are available, the evaluation of such techniques remains limited. This study evaluates the performance of these techniques for ambient air toxics measurements, a particularly challenging application, and includes the analysis of intra- and inter-laboratory precision. The analysis uses an unusually complete-dataset, consisting of daily measurements of over 70 species of carbonyls and volatile organic compounds (VOCs) collected over a one year period in Dearborn, Michigan, including 122 pairs of replicates. Analysis was restricted to compounds found above detection limits in > or =20% of the samples. Outliers were detected using the Gumbell extreme value distribution. Error models for inter- and intra-laboratory reproducibility were derived from replicate samples. Imputation variables were selected using a generalized additive model, and the performance of two techniques, multiple imputation and optimal linear estimation, was evaluated for three missingness patterns. Many species were rarely detected or had very poor reproducibility. Error models developed for seven carbonyls showed median intra- and inter-laboratory errors of 22% and 25%, respectively. Better reproducibility was seen for the 16 VOCs meeting detection and reproducibility criteria. Imputation performance depended on the compound and missingness pattern. Data missing at random could be adequately imputed, but imputations for row-wise deletions, the most common type of missingness pattern encountered, were not informative. The analysis shows that air toxics data require significant efforts to identify and mitigate errors, outliers and missing observations, and that these steps are essential and should be performed prior to using these data in receptor, exposure, health and other applications.     

Earth stewardship: Shaping a sustainable future through interacting policy and norm shifts

Transformation toward a sustainable future requires an earth stewardship approach to shift society from its current goal of increasing material wealth to a vision of sustaining built, natural, human, and social capital—equitably distributed across society, within and among nations. Widespread concern about earth’s current trajectory and support for actions that would foster more sustainable pathways suggests potential social tipping points in public demand for an earth stewardship vision. Here, we draw on empirical studies and theory to show that movement toward a stewardship vision can be facilitated by changes in either policy incentives or social norms. Our novel contribution is to point out that both norms and incentives must change and can do so interactively. This can be facilitated through leverage points and complementarities across policy areas, based on values, system design, and agency. Potential catalysts include novel democratic institutions and engagement of non-governmental actors, such as businesses, civic leaders, and social movements as agents for redistribution of power. Because no single intervention will transform the world, a key challenge is to align actions to be synergistic, persistent, and scalable.     

Concentrations, distributions and critical level exceedance assessment of SO2, NO2 and O3 in South Africa

South Africa has been identified as a source of industrial pollution that is significant at a global scale. This study was designed to provide quantitative information, by direct measurement, across northeastern South Africa, which includes the highly industrialised Mpumalanga Highveld. The specific aim of the study was to evaluate whether or not acidic atmospheric pollution poses a threat to soils, plants and water bodies of South Africa. To address this aim, a network of 37 passive sampling sites was established to measure monthly mean concentrations of near-surface SO₂, NO₂ and ozone. The area covered extended over the northern and eastern interior of South Africa while avoiding sources of local emissions such as towns, mines and highways. The field campaign was conducted between August 2005 and September 2007. Spatial distributions and temporal trends for these pollutant gases were assessed. Critical levels analysis comparisons were made against applicable air quality standards, guidelines and limits to evaluate the potential for adverse atmospheric pollution impacts on regional environments. The assessment indicates that only in the central source area of the South African industrial Highveld are some levels exceeded. In remote areas, including the sensitive forested regions of the Drakensberg escarpment, pollutant concentrations are below the critical thresholds for environmental damage.     

Challenges in understanding the sources of bioaccumulated metals in biota inhabiting turbid river systems

Bioaccumulation of As, Cd, Cu, Pb and Zn by Macrobrachium prawns was observed to occur in the Strickland River downstream of a gold mine at Porgera, Papua New Guinea. This was despite the total metal concentrations of waters and sediments indicating no difference from reference sites within tributaries. To provide information on potential sources and bioavailability of metals to prawns, an extensive range of analyses were made on waters, suspended solids, deposited sediments and plant materials within the river system. Dissolved metal concentrations were mostly sub-micrograms per liter and no major differences existed in concentrations or speciation between sites within the Strickland River or its tributaries. Similarly, no differences were detected between sites for total or dilute acid-extractable metal concentrations in bed sediments and plant materials, which may be ingested by the prawns. However, the rivers in this region are highly turbid and the dilute acid-extractable cadmium and zinc concentrations in suspended solids were greater at sites in the Strickland River than at sites in tributaries. The results indicated that mine-derived inputs increased the proportion of these forms of metals or metalloids in the Strickland River. These less strongly bound metals and metalloids would be more bioavailable to the prawns via the dietary pathway. The results highlighted many of the difficulties in using routine monitoring data without information on metal speciation to describe metal uptake and predict potential effects when concentrations are low and similar to background. The study indicated that the monitoring of contaminant concentrations in organisms that integrate the exposure from multiple exposure routes and durations may often be more effective for detecting impacts than intermittent monitoring of contaminants in waters and sediments.     

Using Expert and Non-expert Models of Climate Change to Enhance Communication

Climate change is a significant global risk that is predicted to be particularly devastating to coastal communities. Climate change adaptation and mitigation have been hindered by many factors, including psychological barriers, ineffective outreach and communication, and knowledge gaps. This qualitative study compares an expert model of climate change risks to county administrators' “mental” models of climate change and related coastal environmental hazards in Crystal River, Florida, USA. There were 24 common nodes in the expert and the combined non-expert models, mainly related to hurricanes, property damage, and economic concerns. Seven nodes mentioned by non-experts fit within, but were not a part of, the expert model, primarily related to ecological concerns about water quality. The findings suggest that effective climate outreach and communication could focus on compatible parts of the models and incorporate local concerns to find less controversial ways to discuss climate-related hazards.     

Air Quality Screening Model with Long-Term Averaging

A simple screening model is presented for estimating maximum ground level concentrations of air pollutants from single elevated buoyant sources of emissions. The model, which incorporates plausible error margins, is based on the Gaussian dispersion formula. Maximum longer-term (3, 8, 24 h) concentrations are estimated using a joint probability analysis of the persistence of meteorological worst case events.