Degradation of the herbicide dichlobenil and its metabolite BAM in soils and subsurface sediments

The worldwide used herbicide dichlobenil (2,6-dichlorobenzonitrile) has resulted in widespread presence of its metabolite 2,6-dichlorobenzamide (BAM) in surface water and groundwater. To evaluate the potential for natural attenuation of this BAM pollution in groundwater, we studied the degradation of BAM and dichlobenil in 16 samples of clayey till, unconsolidated sand and limestone, including sediments from both oxidized and reduced conditions. The degradation of dichlobenil occurred primarily in the upper few meters below surface, although dichlobenil was strongly sorbed to these sediments. However, the degradation of dichlobenil to BAM could not be correlated to either sorption, water chemistry, composition of soils or sediments. Degradation of dichlobenil to BAM was limited (<2% degraded) in the deeper unsaturated zones, and no degradation was observed in aquifer sediments. This illustrates, that dichlobenil transported to aquifers does not contribute to the BAM-contamination in aquifers. A small, but significant degradation of BAM was observed in the upper part of the unsaturated zones in sandy sediments, but no degradation was observed in the clayey till sediment or in the deeper unsaturated zones. The insignificant degradation of BAM in aquifer systems shows that BAM pollution detected in aquifers will appear for a long time; and consequently the potential for natural attenuation of BAM in aquifer systems is limited.     

Flavonoid wing pigments increase attractiveness of female common blue (Polyommatus icarus) butterflies to mate-searching males

 Common blue butterflies (Polyommatus icarus) sequester flavonoids from their larval host plants and allocate these UV-absorbing pigments to the wings. In field experiments using dummies constructed from female butterflies, mate-searching males inspected flavonoid-rich dummies more intensively than those with little or no flavonoids. Flavonoid content as signalled by UV-wing pattern may indicate ontogenetically determined female quality or enhance detectability to males. Received: 21 March 2000 / Accepted in revised form: 17 May 2000     

Enhanced twin pregnancy detection within an open neural tube defect and down syndrome screening protocol using free-beta hCG and AFP

We have applied our multimarker approach of maternal serum alpha-fetoprotein (AFP) and free-beta human chorionic gonadotropin (hCG) for Down syndrome screening to multiple gestations to assess its efficacy for improved detection of twin and triplet pregnancies. This study matched 225 cases of twin pregnancy and 39 cases of triplet pregnancy each with ten singleton pregnancies based on gestational week, race, time to receive sample, time of year of sample, and geographical area. The ratios of the MOM for each group at the tenth, 50th, and 90th percentiles were compared by the Wilcoxon test. Risks for twins were calculated using Bayes' rule, the age-related incidence of twins, and the levels of AFP and free-beta hCG. The tenth, 50th, and 90th percentiles of free-beta hCG MOMs in twin and triplet cases were 0.85, 1.99, and 4.51, and 1.38, 2.78, and 4.07, respectively. For AFP, the MOMs at these percentiles were 1.26, 1.91, and 2.99, and 2.02, 2.68, and 5.30, respectively. The twin and triplet distributions for each marker were statistically significantly different from the singleton distributions (P<0.0001) and from each other (P=0.0012). At a twin risk cut-off of 1 in 50, 77.4 per cent of all twin gestations can be detected in a second-trimester AFP and free-beta hCG screening protocol with 5.1 per cent of singleton pregnancies falsely identified as at risk for twins. Our dual marker protocol for mid-trimester pregnancy screening combining AFP and free-beta hCG can identify over 77 per cent of twin pregnancies in women less than 35 years of age. This benefit may contribute to an improved outcome of pregnancy by early detection of multiple gestation.     

Natural biodegradation of wood preservatives

Natural biodegradation can contain groundwaters impacted by creosote and pentachlorophenol. Using natural biodegradation for such sites is attractive because groundwater restoration is often impracticable, but the dissolved plumes are biodegradable and exert relatively low oxygen demands. Three case studies of its successful use are presented, with emphasis on the types of evidence needed, the rates and extents of removal, and the strategies for incorporating natural biodegradation into a remediation approach. Natural biodegradation was proven at all three sites, using a combination of field geochemical measurements, laboratory simulations, and computer modeling. Contaminant plumes at these three sites were contained within 100 to 700 feet downgradient of the apparent sources, although the rates of biodegradation varied widely. Natural biodegradation should be considered as part of an overall remedial strategy for most sites contaminated by creosote and/or pentachlorophenol.     

A context-intensive approach to imputation of missing values in data sets from networks of environmental monitors

Although networks of environmental monitors are constantly improving through advances in technology and management, instances of missing data still occur. Many methods of imputing values for missing data are available, but they are often difficult to use or produce unsatisfactory results. I-Bot (short for “Imputation Robot”) is a context-intensive approach to the imputation of missing data in data sets from networks of environmental monitors. I-Bot is easy to use and routinely produces imputed values that are highly reliable. I-Bot is described and demonstrated using more than 10 years of California data for daily maximum 8-hr ozone, 24-hr PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), mid-day average surface temperature, and mid-day average wind speed. I-Bot performance is evaluated by imputing values for observed data as if they were missing, and then comparing the imputed values with the observed values. In many cases, I-Bot is able to impute values for long periods with missing data, such as a week, a month, a year, or even longer. Qualitative visual methods and standard quantitative metrics demonstrate the effectiveness of the I-Bot methodology.Implications: Many resources are expended every year to analyze and interpret data sets from networks of environmental monitors. A large fraction of those resources is used to cope with difficulties due to the presence of missing data. The I-Bot method of imputing values for such missing data may help convert incomplete data sets into virtually complete data sets that facilitate the analysis and reliable interpretation of vital environmental data.     

Towards quantifying the glacial runoff signal in the freshwater input to Tyrolerfjord–Young Sound,NE Greenland

Terrestrial freshwater runoff strongly influences physical and biogeochemical processes at the fjord scale and can have global impacts when considered at the Greenland scale. We investigate the performance of the HIRHAM5 regional climate model over the catchments delivering freshwater to Tyrolerfjord and Young Sound by comparing to the unique Greenland Ecological Monitoring database of in situ observations from this region. Based on these findings, we estimate and discuss the fraction of runoff originating from glacierized and non-glacierized land delivered at the daily scale between 1996 and 2008. We find that glaciers contributed on average 50–80% of annual terrestrial runoff when considering different sections of Tyrolerfjord–Young Sound, but snowpack depletion on land and consequently runoff happens about one month earlier in the model than observed in the field. The temporal shift in the model is a likely explanation why summer surface salinity in the inner fjord did not correlate to modelled runoff.     

Supporting Diverse Data Providers in the Open Water Data Initiative: Communicating Water Data Quality and Fitness of Use

Shared, trusted, timely data are essential elements for the cooperation needed to optimize economic, ecologic, and public safety concerns related to water. The Open Water Data Initiative (OWDI) will provide a fully scalable platform that can support a wide variety of data from many diverse providers. Many of these will be larger, well‐established, and trusted agencies with a history of providing well‐documented, standardized, and archive‐ready products. However, some potential partners may be smaller, distributed, and relatively unknown or untested as data providers. The data these partners will provide are valuable and can be used to fill in many data gaps, but can also be variable in quality or supplied in nonstandardized formats. They may also reflect the smaller partners' variable budgets and missions, be intermittent, or of unknown provenance. A challenge for the OWDI will be to convey the quality and the contextual “fitness” of data from providers other than the most trusted brands. This article reviews past and current methods for documenting data quality. Three case studies are provided that describe processes and pathways for effective data‐sharing and publication initiatives. They also illustrate how partners may work together to find a metadata reporting threshold that encourages participation while maintaining high data integrity. And lastly, potential governance is proposed that may assist smaller partners with short‐ and long‐term participation in the OWDI.     

Hydrocarbon emission fingerprints from contemporary vehicle/engine technologies with conventional and new fuels

The present paper presents results from the analysis of 29 individual C₂–C₉ hydrocarbons (HCs) specified in the European Commission Ozone Directive. The 29 HCs are measured in exhaust from common, contemporary vehicle/engine/fuel technologies for which very little or no data is available in the literature. The obtained HC emission fingerprints are compared with fingerprints deriving from technologies that are being phased out in Europe. Based on the total of 138 emission tests, thirteen type-specific fingerprints are extracted (Mean ± SD percentage contributions from individual HCs to the total mass of the 29 HCs), essential for receptor modelling source apportionment. The different types represent exhaust from Euro3 and Euro4 light-duty (LD) diesel and petrol-vehicles, Euro3 heavy-duty (HD) diesel exhaust, and exhaust from 2-stroke preEuro, Euro1 and Euro2 mopeds. The fuels comprise liquefied petroleum gas, petrol/ethanol blends (0–85% ethanol), and mineral diesel in various blends (0–100%) with fatty acid methyl esters, rapeseed methyl esters palm oil methyl esters, soybean oil methyl or sunflower oil methyl esters. Type-specific tracer compounds (markers) are identified for the various vehicle/engine/fuel technologies.An important finding is an insignificant effect on the HC fingerprints of varying the test driving cycle, indicating that combining HC fingerprints from different emission studies for receptor modelling purposes would be a robust approach.The obtained results are discussed in the context of atmospheric ozone formation and health implications from emissions (mg km^?1 for LD and mopeds and mg kW h^?1 for HD, all normalised to fuel consumption: mg dm^?3 fuel) of the harmful HCs, benzene and 1,3-butadiene.Another important finding is a strong linear correlation of the regulated “total” hydrocarbon emissions (tot-HC) with the ozone formation potential of the 29 HCs (ΣPO₃ = (1.66 ± 0.04) × tot-RH; r² = 0.93). Tot-HC is routinely monitored in emission control laboratories, whereas C₂–C₉ are not. The revealed strong correlations broadens the usability of data from vehicle emission control laboratories and facilitates the comparison of the ozone formation potential of HCs in exhaust from of old and new vehicle/engine/fuel technologies.