Euro Chlor Risk Assessment for the Marine Environment Osparcom Region: North Sea - Trichloroethylene

This risk assessment on trichloroethylene (TRI) was carried out specifically for the marine environment, according to the methodology laid down in the EU risk assessment Regulation (1488/94) and the Guidance Document of the EU New and Existing Substances Regulation (TGD, 1997). The study consists of the collection and evaluation of data on effects and environmental concentrations from analytical monitoring programs in large rivers and estuaries in the North Sea area. The risk is indicated by the ratio of the "predicted environmental concentrations" (PEC) and the "predicted no effect concentrations" (PNEC) for the marine aquatic environment. In total, 19 studies for fish, 30 studies for invertebrates and 14 studies for algae have been evaluated. Both acute and chronic toxicity studies have been taken into account and the appropriate assessment factors have been used to define a PNEC value of 150 µg/l. Most of the available monitoring data apply to rivers and estuaries and were used to calculate PECs. The most recent data (1991-1995) support a typical PEC of 0.1 µg TRI/l water and a worst case PEC of 3.5 µg TRI/l water. The calculated PEC/PNEC ratios give a safety margin of 40 to 1,500 between the predicted no effect concentration and the exposure concentration. Additional evaluation of environmental fate and bioaccumulation characteristics showed that no concern for food chain accumulation is expected.     

Human influence on California fire regimes.

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.     

Estimating preferences for outdoor recreation:: a comparison of continuous and count data demand system frameworks

Continuous and count data demand system models have emerged as attractive alternatives to the discrete choice random utility maximization models (RUMs) that currently dominate the seasonal, multi-site recreation demand literature. This paper compares the frameworks conceptually and investigates their empirical performance with a common data set. Although the two modeling approaches employ substantially different behavioral and econometric assumptions, results from a recreation application based on the 1997 Iowa Wetlands Survey suggest that qualitatively similar policy inferences arise from the competing structures.     

Development and application of protocols for the determination of response of real-time particle monitors to common indoor aerosols

Protocols have been developed and applied for the generation of aerosols that are likely to be comparable to those encountered in field settings for the calibration of easily transportable/portable real-time particle monitors. Aerosols generated were simulated environmental tobacco smoke, cedar wood smoke, cooking oil fumes, and propane stove particles. The time-integrated responses of three nephelometers and a monitor for particle-bound polynuclear aromatic hydrocarbons (PAH) were compared with gravimetric respirable suspended particulate matter (RSP) in a controlled-atmosphere chamber. In general, the monitor responses increased linearly with increasing mass concentration. However, the two monitors that reported mass per volume concentrations tended to overreport the actual RSP concentrations by factors up to 4.4. The real-time PAH monitor did not respond to cooking oil fumes, indicative of little PAH being present in the aerosol. One of the monitors that has been used in a variety of studies reported in the literature (DustTrak) was collocated with gravimetric RSP samplers in several hospitality venues in the Louisville, KY, area. Field studies indicated that the units overreported actual RSP concentrations by factors of 2.6-3.1, depending on whether the sampling was conducted in the nonsmoking or smoking sections of the facilities.     

PREDICTING CHANGE IN NON-LINEAR SYSTEMS

Complex systems are characterizedby surprising switches to new behaviours. Evaluating and predicting these changes demands anunderstanding of the behaviour of the whole system. The combined ecosystem-climate system shows chaoticor pseudorandom behaviour, stochastic or trulyrandom behaviour, as well as simple bifurcation andsemi-stability. Semistability involves the suddenchange from a destabilized attractor to a newstable attractor which may occur after an apparentlyunpredictable time delay. We present some recentresults for analyzing time series data and for usingsimulations of non-linear models to predict these changes.     

Modeling of NO x Emissions from Oil Refinery Furnaces

The current paper investigates the possibility of establishing an empirically based model for predicting the emission rate of nitrogen oxides (NO _x ) from oil refinery furnaces, in order to continually track emissions with respect to environmental licence limits. Model input data were collected by direct stack monitoring using an electrochemical cell NO _x analyser, as well as a range of telemetry sensors to obtain refinery process parameters. Principal Component Analysis (PCA), in conjunction with Partial Least Squares (PLS) regression was then used to build a series of models able to predict NO _x emissions from the furnaces. The models produced were proven to be robust, with a relatively high accuracy, and are able to predict NO _x levels over the range of operating conditions which were sampled. It was found that due to structural/operational variations a separate model is usually required for each furnace. The models can be integrated with the refinery operating system to predict NO _x emission rates on a continuous basis. Two models representing structurally different furnaces are considered in this paper. This revised version was published online in July 2006 with corrections to the Cover Date.