Molecular receptive ranges of olfactory receptor neurones responding selectively to terpenoids, aliphatic green leaf volatiles and aromatic compounds, in the strawberry blossom weevil Anthonomus rubi

Summary. An important question in insect-plant interactions is which of the numerous plant compounds contribute to the perception of odour qualities in herbivorous insects and are likely to be used as cues in host-searching behaviour. In order to identify which plant-produced volatiles the strawberry blossom weevil Anthonomus rubi detects, we have used electrophysiological recordings from single olfactory neurones linked to gas chromatography and mass spectrometry. We here present 15 receptor neurone types specialised for naturally produced compounds present in the host and nonhost plants and two types for two aggregation pheromone components. The active compounds were terpenoids, aromatic and aliphatic esters, alcohols and aldehydes, some of which are induced by feeding activity of the weevils. The neurones were characterised by a strong response to one or two primary odorants and weaker responses to a few others having similar chemical structure. With one exception, the molecular receptive range of each neurone type was within one chemical group. Enantiomers of linalool separated on a chiral column activated two neurone types with different enantioselectivity. Inhibition by linalool of another neurone type, excited by α-pinene, indicated an additional mechanism for coding the information about this compound. Altogether, detection of 54 compounds by olfactory receptor neurones is shown, of which 40 have been chemically identified in this study. Thus A. rubi has the ability to detect a large number of odorants that may be used in host selection behaviour.     

Evaluation of commercial landscaping mulch for possible contamination from CCA

Wood treated with chromated copper arsenate (CCA) is found in construction and demolition (C&D) debris, and a common use for wood recycled from C&D debris is the production of mulch. Given the high metals concentrations in CCA-treated wood, a small fraction of CCA-treated wood can increase the metal concentrations in the mulch above regulatory thresholds. The objective of this study was to determine the extent of contamination of CCA-treated wood in consumer landscaping mulch and to determine whether visual methods or rapid X-ray fluorescence (XRF) technology can be used to identify suspect mulch. Samples were collected throughout the State of Florida (USA) and evaluated both visually and chemically. Visual analysis focused on documenting wood-chip size distribution, whether the samples were artificially colored, and whether they contained plywood chips which is an indication that the sample was, in part, made from recycled C&D wood. Chemical analysis included measurements of total recoverable metals, leachable metals as per the standardized synthetic precipitation leaching procedure (SPLP), and XRF analysis. Visual identification methods, such as colorant addition or presence of plywood, were found effective to preliminarily screen suspect mulch. XRF analysis was found to be effective for identifying mulch containing higher than 75 mg/kg arsenic. For mulch samples that were not colored and did not contain evidence of C&D wood, none exceeded leachable metal concentrations of 50 microg/L and only 3% exceeded 10 mg/kg for recoverable metals. The majority of the colored mulch made from recycled C&D wood contained from 1% to 5% CCA-treated wood (15% maximum fraction) resulting in leachable metals in excess of 50 microg/L and total recoverable metals in excess of 10 mg/kg. The maximum arsenic concentration measured in the mulch samples evaluated was 230 mg/kg, which was above the Florida residential direct exposure regulatory guideline of 2.1 mg/kg.     

Online sorting of recovered wood waste by automated XRF-technology: part II. Sorting efficiencies

Sorting of waste wood is an important process practiced at recycling facilities in order to detect and divert contaminants from recycled wood products. Contaminants of concern include arsenic, chromium and copper found in chemically preserved wood. The objective of this research was to evaluate the sorting efficiencies of both treated and untreated parts of the wood waste stream, and metal (As, Cr and Cu) mass recoveries by the use of automated X-ray fluorescence (XRF) systems. A full-scale system was used for experimentation. This unit consisted of an XRF-detection chamber mounted on the top of a conveyor and a pneumatic slide-way diverter which sorted wood into presumed treated and presumed untreated piles. A randomized block design was used to evaluate the operational conveyance parameters of the system, including wood feed rate and conveyor belt speed. Results indicated that online sorting efficiencies of waste wood by XRF technology were high based on number and weight of pieces (70-87% and 75-92% for treated wood and 66-97% and 68-96% for untreated wood, respectively). These sorting efficiencies achieved mass recovery for metals of 81-99% for As, 75-95% for Cu and 82-99% of Cr. The incorrect sorting of wood was attributed almost equally to deficiencies in the detection and conveyance/diversion systems. Even with its deficiencies, the system was capable of producing a recyclable portion that met residential soil quality levels established for Florida, for an infeed that contained 5% of treated wood.     

ATRAZINE IN SPRING RUNOFF AS RELATED TO ENVIRONMENTAL SETTING EBRASKA, 19921

ABSTRACT: A synoptic sampling of five surface-water sites in central Nebraska was conducted by the U.S. Geological Survey as part of its National Water-Quality Assessment Program during storm runoff in May 1992 to relate transport, yields, and concentrations of atrazine to environmental setting. Atrazine was the most extensively applied pesticide in the study unit. Atrazine transport was related to the size of contributing drainage area, quantity of atrazine applied, amount of precipitation, and volume of stream-flow. Estimated yields and mean concentrations of atrazine were related to the percentage of cropland in a drainage area. The largest estimated yields and mean concentrations of atrazine in surface water were associated from drainage areas with the highest percentage of cropland, and the smallest was associated with the smallest amount of cropland. Atrazine concentrations increased as streamflow increased but decreased at or near the time of peak streamflows, perhaps due to dilution. Atrazine concentrations then increased and remained elevated far into the stream recession. Atrazine is a regulated contaminant in finished public-water supplies. Large concentrations of atrazine could affect the management of public-water supplies because atrazine remains in solution in contrast to many other pesticides that are more easily removed.     

Trace metal emissions from co-combustion of refuse derived and packaging derived fuels in a circulating fluidized bed boiler

Energy recovery from refuse derived fuels (RDF) and packaging derived fuels (PDF) is one option in integrated waste management. Nine RDF and PDF co-combustion tests with peat and coal in a circulating fluidized bed boiler were carried out in this work. Heavy metal emissions in flue gas and fly ash were measured. Multivariate data analyses were used to find out the most important parameters affecting metal emissions in the flue gas.

The results showed that total heavy metal emissions were low. Although RDF and PDF had more heavy metals than peat and coal, the multivariate data analysis showed that an increase of the RDF or PDF share in the fuel mixture up to 20% did not correlate directly with the metal emissions in the flue gas. Distribution of Cd, Cu, Zn and Sn between flue gas and fly ash correlated with each other. Injection of limestone to bind sulphur and chlorine did not have a significant effect on heavy metal emissions in the flue gas. Heavy metals concentrated on the fly ash, but all fly ashes passed the EPA-TCLP tests.     

Social sustainability and collaborative learning

The social dimension is central to sustainable development of agri-food systems. If farmers are not satisfied with their situation or motivated to continue farming, many of today's environmental goals will be impossible to achieve. Between 1997 and 2003, several case studies were carried out on social sustainability, the importance of recognition in the farming system, and the potential role of increased collaboration between actors. The main hypothesis was that improved recognition is a basis for sustainable social conditions. Our findings show that many farmers today perceive an impoverished social situation. They believe they lack control over decisions, which hinders their ability to continue farming. Public images and political decisions show a lack of respect for farmers' skills and knowledge. However, increased collaboration among actors is believed to be one important way forward, creating stronger relationships and networks, as well as a stronger identity for farmers. Our findings emphasize the need for authorities and other organizations to support farmers and to facilitate collaborative learning and decision-making processes for socioecological sustainability.     

Experimental investigation of hydrogen–air deflagrations and detonations in semi-confined flat layers

This paper presents results of an experimental investigation on the deflagration and deflagration-to-detonation transition (DDT) in an obstructed (blockage ratio BR = 50%), semi-confined flat layer filled with uniform hydrogen–air mixtures. The effect of mixture reactivity depending on flat layer thickness and its width is studied to evaluate the critical conditions for sonic flame propagation and the possibility for detonation onset. The experiments were performed in a transparent, rectangular channel with a length of 2.5 m. The flat layer thickness was varied from 0.06 to 0.24 m and the experiments were performed for different channel widths of 0.3, 0.6 and 0.9 m. The experimental results show flame velocity vs. hydrogen concentration for different thicknesses and widths of the semi-confined flat layer. Three different flame propagation regimes were observed: slow subsonic flame (M << 1), sonic deflagration (M ～ 1) and detonation (M >> 1). It is shown that flame acceleration (FA) to sonic speed is independent of the width of the flat layer. The critical expansion ratio for effective flame acceleration to sonic speed was found to be linearly dependent on the reciprocal layer thickness.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.