Understanding the fate and transport of petroleum hydrocarbons from coal tar within gasholders

Coal tars have been identified as posing a threat to human health due to their toxic, mutagenic and carcinogenic characteristics. Workers involved in former gasholders decommissioning are potentially exposed to relevant concentrations of volatile and semi-volatile hydrocarbons upon opening up derelict tanks and during tar excavation/removal. While information on contaminated sites air-quality and its implications on medium-long term exposure is available, acute exposure issues associated with the execution of critical tasks are less understood. Calculations indicated that the concentration of a given contaminant in the gasholder vapour phase only depends on the coal tar composition, being only barely affected by the presence of water in the gasholder and the tar volume/void space ratio. Fugacity modelling suggested that risk-critical compounds such as benzene, naphthalene and other monocyclic and polycyclic aromatic hydrocarbons may gather in the gasholder air phase at significant concentrations. Gasholder emissions were measured on-site and compared with the workplace exposure limits (WELs) currently in use in UK. While levels for most of the toxic compounds were far lower than WELs, benzene air-concentrations where found to be above the accepted threshold. In addition due to the long exposure periods involved in gasholder decommissioning and the significant contribution given by naphthalene to the total coal tar vapour concentration, the adoption of a WEL for naphthalene may need to be considered to support operators in preventing human health risk at the workplace. The Level I fugacity approach used in this study demonstrated its suitability for applications to sealed environments such as gasholders and its further refining could provide a useful tool for land remediation risk assessors.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

Assessment of the effects of nickel on benthic macroinvertebrates in the field

A field-based evaluation of the biological effects of potential nickel (Ni) exposures was conducted using monitoring data for benthic macroinvertebrates and water chemistry parameters for streams in England and Wales. Observed benthic community metrics were compared to expected community metrics under reference conditions using RIVPACS III+?software. In order to evaluate relationships between Ni concentrations and benthic community metrics, bioavailable Ni concentrations were also calculated for each site. A limiting effect from Ni on the 90th percentile of the maximum achievable ecological quality was derived at “bioavailable Ni” exposures of 10.3 μg l^?1. As snails have been identified as particularly sensitive to nickel exposure, snail abundance in the field in response to nickel exposure, relative to reference conditions, was also analysed. A “low effects” threshold for snail abundance based on an average of spring and autumn data was derived as 3.9 μg l^?1 bioavailable Ni. There was no apparent effect of Ni exposure on the abundance of Ephemeroptera (mayflies), Plecoptera (stoneflies) or Tricoptera (caddisflies) when expressed relative to a reference condition within the range of “bioavailable Ni” exposures observed within the dataset. Nickel exposure concentrations co-vary with the concentrations of other stressors in the dataset, and high concentrations of Ni are also associated with elevated concentrations of other contaminants.     

An Approach for Evaluating the Repeatability of Rapid Wetland Assessment Methods: The Effects of Training and Experience

We sampled 92 wetlands from four different basins in the United States to quantify observer repeatability in rapid wetland condition assessment using the Delaware Rapid Assessment Protocol (DERAP). In the Inland Bays basin of Delaware, 58 wetland sites were sampled by multiple observers with varying levels of experience (novice to expert) following a thorough training workshop. In the Nanticoke (Delaware/Maryland), Cuyahoga (Ohio), and John Day (Oregon) basins, 34 wetlands were sampled by two expert teams of observers with minimal protocol training. The variance in observer to observer scoring at each site was used to calculate pooled standard deviations (SD_pool), coefficients of variation, and signal-to-noise ratios for each survey. The results showed that the experience level of the observer had little impact on the repeatability of the final rapid assessment score. Training, however, had a large impact on observer to observer repeatability. The SD_pool in the Inland Bay survey with training (2.2 points out of a 0–30 score) was about half that observed in the other three basins where observers had minimal training (SD_pool = 4.2 points). Using the results from the survey with training, we would expect that two sites assessed by different, trained observers who obtain DERAP scores differing by more than 4 points are highly likely to differ in ecological condition, and that sites with scores that differ by 2 or fewer points are within variability that can be attributed to observer differences.     

The influence of sampling protocol on nonmethane hydrocarbon mixing ratios

The effect of sampling protocol on ambient air hydrocarbon mixing ratios was examined on eight sampling days in Los Angeles during 2007 and 2008. Four protocols, which were based on previously published multi-city urban hydrocarbon studies in the United States, were compared and differences were quantified. Whole air canister samples were collected and analyzed for nonmethane hydrocarbons (NMHCs). Differing sampling protocols resulted in large differences in mixing ratios, up to an order of magnitude, for certain NMHCs on the same sampling day. However, the magnitude of the variability between NMHC levels obtained by the four protocols was not consistent throughout the eight sampling days. It was found that sampling time, followed by sampling location, had the greatest influence on the magnitude of the mixing ratio. Ratios between hydrocarbons, often used in urban studies to gain information on emission sources, also varied depending on the protocol used. Comparison of absolute NMHC mixing ratios collected in urban environments using differing sampling protocols should be made with care.