Integral assessment of estrogenic potentials in sediment-associated samples

Background, aim, and scope  The enzyme-linked receptor assay (ELRA) detects estrogenic and anti-estrogenic effects at the molecular level of receptor binding and is a useful tool for the integrative assessment of ecotoxicological potentials caused by hormonally active agents (HAA) and endocrine disrupting compounds (EDC). The main advantage of the ELRA is its high sample throughput and its robustness against cytotoxicity and microbial contamination. After a methodological adaptation to salinity of the ELRA, according to the first part of this study, which increased its salinity tolerance and sensitivity for 17-β-estradiol, the optimised ELRA was used to investigate 13 native sediments characterised by different levels of salinity and chemical contamination. The applicability of the ELRA for routine analysis in environmental assessment was evaluated. Salinity is often a critical factor for bioassays in ecotoxicological sediment assessment. Therefore, salinity of the samples was additionally adjusted to different levels to characterise its influence on elution and binding processes of receptor-binding substances. Materials and methods  The ELRA was carried out with the human estrogen receptor α (ER) in a 96-well microplate format using the experimental setup known from the competitive immunoassay based on ligand–protein interaction. It is an important improvement that a physiologically relevant receptor was used as a linking protein instead of an antibody. The microplates were coated with a 17-β-estradiol-BSA conjugate, and dilution series of estradiol and of native sediment samples were added and incubated with the ER. After a washing step, a biotinylated mouse anti-ER antibody was added to each well. Receptor binding to estradiol, agonistic and antagonistic receptor binding, were determined by a streptavidin-POD-biotin complex with subsequent measurement of the peroxidase activity at the wavelength of 450 nm using a commercial ELISA multiplate reader. The sediment elutriates and pore water samples of sediments were tested in a dilution series to evaluate at which dilution step the receptor-binding potential ends. In the elution process (see Section 2.1 to 2.2), a method was developed to adjust the salinity to the levels of the reference testings, which offers an appropriate option to adjust the salinity in both directions. Statistical evaluation was made with a combination of the Mann–Whitney U test and the pT-method. Results  This part of the study characterised the environmental factor ‘salinity’ for prospective applications of the ELRA. Using reference substances such as 17-β-estradiol, the ELRA showed sigmoid concentration-effect relations over a broad range from 0.05 μg/l to 100 μg/l under physiological conditions. After methodological optimisation, both sensitivity and tolerance of the assay against salinity could be significantly raised, and the ELRA became applicable under salinity conditions up to concentrations of 20.5‰. The mean relative inter-test error (n = 3) was around 11% with reference substances and below 5% for single sediments elutriates in three replicates each. For sediment testings, the pore water and different salinity-adjusted elutriates of 13 sediments were used. A clear differentiation of the receptor-binding potential could be reached by application of the pT-method. Thereby, pT-values from one to six could be assigned to the sediments, and the deviation caused by the different salinity conditions was one pT-value. The mean standard deviation in the salinity adaptation procedure of the elutriates was below 5%. Discussion  Although the ELRA has already been used for assessments of wastewater, sludge and soil, its applicability for samples to different salinity levels has not been investigated so far. Even if the ELRA is not as sensitive as the E-screen or the YES-assay, with regard to reference substances like 17-β-estradiol, it is a very useful tool for pre-screening, because it is able to integrate both estrogenic as well as anti-estrogenic receptor-binding effects. According to the results of sediment testing, and given the integrative power to detect different directions of effects, the ELRA shows sufficient sensitivity and salinity tolerance to discriminate receptor-binding potentials in environmental samples. Conclusions  The optimised ELRA assay is a fast, cost-effective, reliable and highly reproducible tool that can be used for high-throughput screening in a microplate format in detecting both estrogenic and anti-estrogenic effects. Additionally, the ELRA is robust against microbial contaminations, and is not susceptible towards cytotoxic interferences like the common cell-culture methods. The general applicability and sufficient sensitivity of the ELRA was shown in freshwater environments. Marine and brackish samples can be measured up to salinity levels of 20.5‰. Recommendations and perspectives  In view of the proven sensitivity, functionality and the fastness of the ELRA, it is recommendable to standardise the test method. At the moment, no adequate in vitro test procedure exists which is standardised to DIN or ISO levels. The E-screen and the yeast estrogen/androgen screens (YES/YAS) sometimes underlie strong cytotoxic effects, as reported in the first part of this study. Further development of an ELRA assay using human androgen receptors appears to be very promising to gain information about androgenic and anti-androgenic effects, too. This would offer a possibility to use the ELRA as a fast and reliable pre-screening tool for the detection of endocrine potentials, thus minimising time and cost-expensive animal experiments.     

A study of the total atmospheric sulfur dioxide load using ground-based measurements and the satellite derived Sulfur Dioxide Index

We present characteristics of the sulfur dioxide (SO₂) loading over Thessaloniki, Greece, and seven other selected sites around the world using SO₂ total column measurements from Brewer spectrophotometers together with satellite estimates of the Version 8 TOMS Sulfur Dioxide Index (SOI) over the same locations, retrieved from Nimbus 7 TOMS (1979–1993), Earth Probe TOMS (1996–2003) and OMI/Aura (2004–2006). Traditionally, the SOI has been used to quantify the SO₂ quantities emitted during great volcanic eruptions. Here, we investigate whether the SOI can give an indication of the total SO₂ load for areas and periods away from eruptive volcanic activity by studying its relative changes as a correlative measure to the SO₂ total column. We examined time series from Thessaloniki and another seven urban and non-urban stations, five in the European Union (Arosa, De Bilt, Hohenpeissenberg, Madrid, Rome) and two in India (Kodaikanal, New Delhi). Based on the Brewer data, Thessaloniki shows high SO₂ total columns for a European Union city but values are still low if compared to highly affected regions like those in India. For the time period 1983–2006 the SO₂ levels above Thessaloniki have generally decreased with a rate of 0.028 Dobson Units (DU) per annum, presumably due to the European Union's strict sulfur control policies. The seasonal variability of the SO₂ total column exhibits a double peak structure with two maxima, one during winter and the second during summer. The winter peak can be attributed to central heating while the summer peak is due to synoptic transport from sources west of the city and sources in the north of Greece. A moderate correlation was found between the seasonal levels of Brewer total SO₂ and SOI for Thessaloniki, Greece (R = 0.710–0.763) and Madrid, Spain (R = 0.691) which shows that under specific conditions the SOI might act as an indicator of the SO₂ total load.     

A validated 2-D diffusion–advection model for prediction of drift from ground boom sprayers

Correct field drift prediction is a key element in environmental risk assessment of spraying applications. A reduced order drift prediction model based on the diffusion–advection equation is presented. It allows fast assessment of the drift potential of specific ground boom applications under specific environmental wind conditions that obey the logarithmic wind profile. The model was calibrated based on simulations with a validated Computational Fluid Dynamics (CFD) model. Validation of both models against 38 carefully conducted field experiments is successfully performed for distances up to 20 m from the field edge, for spraying on flat pasture land. The reduced order model succeeded in correct drift predictions for different nozzle types, wind velocities, boom heights and spray pressures. It used 4 parameters representing the physical aspects of the drift cloud; the height of the cloud at the field edge, the mass flux crossing the field edge, the settling velocity of the droplets and the turbulence. For the parameter set and range considered, it is demonstrated for the first time that the effect of the droplet diameter distribution of the different nozzle types on the amount of deposition spray drift can be evaluated by a single parameter, i.e., the volume fraction of droplets with a diameter smaller than 191 μm. The reduced order model can be solved more than 4 orders of magnitude faster than the comprehensive CFD model.     

Predicting bioremediation of hydrocarbons: Laboratory to field scale

There are strong drivers to increasingly adopt bioremediation as an effective technique for risk reduction of hydrocarbon impacted soils. Researchers often rely solely on chemical data to assess bioremediation efficiently, without making use of the numerous biological techniques for assessing microbial performance. Where used, laboratory experiments must be effectively extrapolated to the field scale. The aim of this research was to test laboratory derived data and move to the field scale. In this research, the remediation of over thirty hydrocarbon sites was studied in the laboratory using a range of analytical techniques. At elevated concentrations, the rate of degradation was best described by respiration and the total hydrocarbon concentration in soil. The number of bacterial degraders and heterotrophs as well as quantification of the bioavailable fraction allowed an estimation of how bioremediation would progress. The response of microbial biosensors proved a useful predictor of bioremediation in the absence of other microbial data. Field-scale trials on average took three times as long to reach the same endpoint as the laboratory trial. It is essential that practitioners justify the nature and frequency of sampling when managing remediation projects and estimations can be made using laboratory derived data. The value of bioremediation will be realised when those that practice the technology can offer transparent lines of evidence to explain their decisions.     

Satellite derived trends in NO2 over the major global hotspot regions during the past decade and their inter-comparison

We assessed satellite derived tropospheric NO₂ distribution on a global scale and identified the major NO₂ hotspot regions. Combined GOME and SCIAMACHY measurements for the period 1996-2006 have been used to compute the trends over these regions. Our analysis shows that tropospheric NO₂ column amounts have increased over the newly and rapidly developing regions like China (11 ± 2.6%/year), south Asia (1.76 ± 1.1%/year), Middle East (2.3 ± 1%/year) and South Africa (2.4 ± 2.2%/year). Tropospheric NO₂ column amounts show some decrease over the eastern US (−2 ± 1.5%/year) and Europe (0.9 ± 2.1%/year). We found that although tropospheric NO₂ column amounts decreased over the major developed regions in the past decade, the present tropospheric NO₂ column amounts over these regions are still significantly higher than those observed over newly and rapidly developing regions (except China). Tropospheric NO₂ column amounts show some decrease over South America and Central Africa, which are major biomass burning regions in the Southern Hemisphere.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Ultrafine particles near a major roadway in Raleigh,North Carolina: Downwind attenuation and correlation with traffic-related pollutants

Ultrafine particles (UFPs, diameter < 100 nm) and co-emitted pollutants from traffic are a potential health threat to nearby populations. During summertime in Raleigh, North Carolina, UFPs were simultaneously measured upwind and downwind of a major roadway using a spatial matrix of five portable industrial hygiene samplers (measuring total counts of 20–1000 nm particles). While the upper sampling range of the portable samplers extends past the defined “ultrafine” upper limit (100 nm), the 20–1000 nm number counts had high correlation (Pearson R = 0.7–0.9) with UFPs (10–70 nm) measured by a co-located research-grade analyzer and thus appear to be driven by the ultrafine range. Highest UFP concentrations were observed during weekday morning work commutes, with levels at 20 m downwind from the road nearly fivefold higher than at an upwind station. A strong downwind spatial gradient was observed, linearly approximated over the first 100 m as an 8% drop in UFP counts per 10 m distance. This result agreed well with UFP spatial gradients estimated from past studies (ranging 5–12% drop per 10 m). Linear regression of other vehicle-related air pollutants measured in near real-time (10-min averages) against UFPs yielded moderate to high correlation with benzene (R² = 0.76), toluene (R² = 0.49), carbon monoxide (R² = 0.74), nitric oxide (R² = 0.80), and black carbon (R² = 0.65). Overall, these results support the notion that near-road levels of UFPs are heavily influenced by traffic emissions and correlate with other vehicle-produced pollutants, including certain air toxics.     

Ultrafine particle fluxes above four major European cities

Little information is known about the behaviour of ultrafine particles (UFP) on a citywide scale. Total particle number flux, dominated by UFP, and other meteorological parameters were collected from tower sites in Manchester, London, Edinburgh and Gothenburg between 1999 and 2006 using the eddy covariance technique. Averaged diurnal cycles were produced for particle number flux, concentration, sensible heat flux, emission velocity, friction velocity, wind speed and temperature. UFP flux cycles showed clear diurnal trends which were linked to traffic activity and local sources. Wind sector analysis showed contributions to flux from local heavily urbanised areas. A simple parameterised model linking UFP flux to traffic activity, sensible heat and friction velocity above the city was produced.     

Influence of air mass source region on nanoparticle events and hygroscopicity in central Virginia,U.S.

During autumn, 2006, variation in the frequency of aerosol nucleation events, as inferred from nanoparticle growth events, and associated hygroscopicity were investigated as a function of air mass transport history at a mixed deciduous forest in central Virginia, U.S. Above-canopy size distributions of aerosols between 0.012 and 0.700 μm diameter, size-resolved particle hygroscopicity at eight dry diameters between 0.012 and 0.400 μm, and cloud condensation nuclei (CCN) activity were characterized. Air mass back trajectories were clustered to identify source regions. Growth events were most frequent in fast-moving air masses (mean = 9 m s^?1) that originated over the north central U.S. Under these flow regimes, mean values for preexisting sub-μm aerosol number concentrations (4700 cm^?3), corresponding surface area (142 μm² cm^?3), air temperature (6.2 °C), and relative humidity (RH, 49.4%) were relatively low compared to other regimes. Under stagnant flow conditions (mean = 3 m s^?1), mean number concentrations were higher (>6000 cm^?3) and size fractions <0.1 μm diameter exhibited enhanced hygroscopicity compared to other source regions. These results indicate that precursors emitted into relatively clean, cold, and dry air transported over the southeastern U.S. reacted to form condensable intermediates that subsequently produced new aerosols via nucleation and growth. This pathway was an important source for CCN. During events in October, nanoparticles were produced in greater numbers and grew more rapidly compared to November and December.