Fungicidal values of bio-oils and their lignin-rich fractions obtained from wood/bark fast pyrolysis

Pine wood, pine bark, oak wood and oak bark were pyrolyzed in an auger reactor. A total of 16 bio-oils or pyrolytic oils were generated at different temperatures and residence times. Two additional pine bio-oils were produced at the National Renewable Energy Laboratory in a fluidized-bed reactor at different temperatures. All these bio-oils were fractionated to obtain lignin-rich fractions which consist mainly of phenols and neutrals. The pyrolytic lignin-rich fractions were obtained by liquid-liquid extraction. Whole bio-oils and their lignin-rich fractions were studied as potential environmentally benign wood preservatives to replace metal-based CCA and copper systems that have raised environmental concerns. Each bio-oil and several lignin-rich fractions were tested for antifungal properties. Soil block tests were conducted using one brown-rot fungus (Gloeophyllum trabeum) and one white-rot fungus (Trametes versicolor). The lignin-rich fractions showed greater fungal inhibition than whole bio-oils for a impregnation solution 10% concentration level. Water repellence tests were also performed to study wood wafer swelling behavior before and after bio-oil and lignin-rich fraction treatments. In this case, bio-oil fractions did not exhibit higher water repellency than whole bio-oils. Comparison of raw bio-oils in soil block tests, with unleached wafers, at 10% and 25% bio-oil impregnation solution concentration levels showed excellent wood preservation properties at the 25% level. The good performance of raw bio-oils at higher loading levels suggests that fractionation to generate lignin-rich fractions is unnecessary. At this more effective 25% loading level in general, the raw bio-oils performed similarly. Prevention of leaching is critically important for both raw bio-oils and their fractions to provide decay resistance. Initial tests of a polymerization chemical to prevent leaching showed some success.     

Contaminant exposure in terrestrial vertebrates

Here we review mechanisms and factors influencing contaminant exposure among terrestrial vertebrate wildlife. There exists a complex mixture of biotic and abiotic factors that dictate potential for contaminant exposure among terrestrial and semi-terrestrial vertebrates. Chemical fate and transport in the environment determine contaminant bioaccessibility. Species-specific natural history characteristics and behavioral traits then play significant roles in the likelihood that exposure pathways, from source to receptor, are complete. Detailed knowledge of natural history traits of receptors considered in conjunction with the knowledge of contaminant behavior and distribution on a site are critical when assessing and quantifying exposure. We review limitations in our understanding of elements of exposure and the unique aspects of exposure associated with terrestrial and semi-terrestrial taxa. We provide insight on taxa-specific traits that contribute, or limit exposure to, transport phenomenon that influence exposure throughout terrestrial systems, novel contaminants, bioavailability, exposure data analysis, and uncertainty associated with exposure in wildlife risk assessments. Lastly, we identify areas related to exposure among terrestrial and semi-terrestrial organisms that warrant additional research.     

Towards a planning support system for environmental management and agri-environmental measures--the Colorfields study

The authors present the beginnings of a planning support system (PSS) for agri-environmental measures exemplified by a virtual implementation of Colorfields and blooming strips on model farms, based on real-world data. This paper starts with an introduction to the Colorfields, a concept for transdisciplinary and sustainable landscape design of set-aside land. Colorfields comprise of blooming strips of flowering annual or biennial plants, which are designed and drilled in pattern on fallow land creating Land Art. The temporary scenic arrangements of the Colorfields combine the advantages of ecological strips, e.g. providing habitats for insects (especially bees), improving soil fertility through the cultivation of intercrops, with improvements of the social recognition of farmers as producers of pleasant landscapes instead of monoculture fields.The prototype of the PSS uses two software tools of different scientific origin, the bio-economic modeling system MODAM and the landscape visualization system Lenné3D, which are linked based on geo-data. The resulting system helps to assess the economic effects and visualizes the effects of the specific landuse patterns under different scenarios.The economic assessment of blooming strips on arable land and of one Colorfield on fallow land shows that these measures prove to be profitable from an economic viewpoint assuming the current area payments for the obligatory European Union set-aside program. Furthermore, the visualizations enable the design to be tested virtually by exploring the resultant scenery. They provide artists, planners and stakeholders including farmers with a tool to virtually wander through landscape scenarios supporting a collaborative design and a shared vision for the community.The results of the two model farms and previous case studies for Colorfields demonstrate how current policy conditions could be used for the improvement of environmental and scenic qualities. Furthermore, the ability of the tools, MODAM and Lenné3D, suggests to support and promote these activities.     

Mapping Turbidity in the Charles River, Boston Using a High-resolution Satellite

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

Benchmarking for best practice environmental management

Benchmarking of environmental performance to demonstrate theachievement of best practice environmental management is acomponent of a new form of licensing of industrialdischarges in Western Australia. The paper describes theapproaches to benchmarking for the critical environmentalissues for an alumina refinery and wastewater treatmentplant. It also describes the lessons learnt from thebenchmarking process on appropriate methods, the benefitsand difficulties in the benchmarking process, and changesthat would assist benchmarking for best practiceenvironmental management.