Sorption of 3,4-dichloroaniline on four contrasting Greek agricultural soils and the effect of liming

Sorption of 3,4-dichloroaniline (3,4-DCA) on four typical Greek agricultural soils, with distinct texture, organic matter content and cation exchange capacities, was compared by using sorption isotherms and the parameters calculated from the fitted Freundlich equations. The sorption process of 3,4-DCA to the soil was completed within 48–72 h. The 3,4-DCA sorption on all soils was well described by the Freundlich equation and all sorption isotherms were of the L-type. The sandy clay loam soil with the highest organic matter content and a slightly acidic pH was the most sorptive, whereas the two other soil types, a high organic matter and neutral pH clay and a low organic matter and acidic loam, had an intermediate sorption capacity. A typical calcareous soil with low organic matter had the lowest sorption capacity which was only slightly higher than that of river sand. The 3,4-DCA sorption correlated best to soil organic matter content and not to clay content or cation exchange capacity, indicating the primary role of organic matter. The distribution coefficient (K _d) decreased with increasing initial 3,4-DCA concentration and the reduction was most pronounced with the highly sorptive sandy clay loam soil, suggesting that the available sorption sites of the soils are not unlimited. Liming of the two acidic soils (the sandy clay loam and the loam) raised their pH (from 6.2 and 5.3, respectively) to 7.8 and reduced their sorption capacity by about 50 %, indicating that soil pH may be the second in importance factor (after organic matter) determining 3,4-DCA sorption.     

Quantitative microbial risk assessment (QMRA) for setting health-based performance targets during soil aquifer treatment

Environmental Science and Pollution Research - A quantitative microbial risk assessment was conducted to assess the health risks associated with the exposure of agricultural workers to tertiary...     

Concentration and size distribution of ultrafine particles near a major highway

Motor vehicle emissions usually constitute the most significant source of ultrafine particles (diameter <0.1 microm) in an urban environment, yet little is known about the concentration and size distribution of ultrafine particles in the vicinity of major highways. In the present study, particle number concentration and size distribution in the size range from 6 to 220 nm were measured by a condensation particle counter (CPC) and a scanning mobility particle sizer (SMPS), respectively. Measurements were taken 30, 60, 90, 150, and 300 m downwind, and 300 m upwind, from Interstate 405 at the Los Angeles National Cemetery. At each sampling location, concentrations of CO, black carbon (BC), and particle mass were also measured by a Dasibi CO monitor, an aethalometer, and a DataRam, respectively. The range of average concentration of CO, BC, total particle number, and mass concentration at 30 m was 1.7-2.2 ppm, 3.4-10.0 microg/m3, 1.3-2.0 x 10(5)/cm3, and 30.2-64.6 microg/m3, respectively. For the conditions of these measurements, relative concentrations of CO, BC, and particle number tracked each other well as distance from the freeway increased. Particle number concentration (6-220 nm) decreased exponentially with downwind distance from the freeway. Data showed that both atmospheric dispersion and coagulation contributed to the rapid decrease in particle number concentration and change in particle size distribution with increasing distance from the freeway. Average traffic flow during the sampling periods was 13,900 vehicles/hr. Ninety-three percent of vehicles were gasoline-powered cars or light trucks. The measured number concentration tracked traffic flow well. Thirty meters downwind from the freeway, three distinct ultrafine modes were observed with geometric mean diameters of 13, 27, and 65 nm. The smallest mode, with a peak concentration of 1.6 x 10(5)/cm3, disappeared at distances greater than 90 m from the freeway. Ultrafine particle number concentration measured 300 m downwind from the freeway was indistinguishable from upwind background concentration. These data may be used to estimate exposure to ultrafine particles in the vicinity of major highways.     

Size distribution and diurnal and seasonal trends of ultrafine particles in source and receptor sites of the Los Angeles basin

This paper presents results from a study conducted in two urban areas of southern California, Downey and Riverside, to examine the effect of different sources and formation mechanisms on the size distribution and temporal trends of ultrafine particles. Near-continuous data were collected for 5 months at each location. Our data clearly identified Downey as a source site, primarily affected by vehicular emissions from nearby freeways, and Riverside as a receptor site, where photochemical secondary reactions form a substantial fraction of particles, along with local vehicular emissions. In Downey, the diurnal trends of total particle number concentration and elemental carbon (EC) appear to be almost identical throughout the day and irrespective of season, thereby corroborating the role of primary emissions in the formation of these particles. This agreement between EC and particle number was not observed in Riverside during the warmer months of the year, while very similar trends to Downey were observed during the winter months in that area. Similarly, the size distribution of ultrafine particles in Downey was generally unimodal with a mode diameter of 30-40 nm and without significant monthly variations. The number-based particle size distributions obtained in Riverside were bimodal, with a significant increase in accumulation mode as the season progressed from winter to summer. During the warmer months, there was also an increase in sub-100-nm particles in the afternoon hours, between 2:00 p.m. and 4:00 p.m., that also increased with the temperature. The differences observed in the ultrafine particle distribution and temporal trends clearly demonstrated that mechanisms other than direct emissions play an important role in the formation of ultrafine particles in receptor sites of the Los Angeles Basin.     

A comparative chemometric study for water quality expertise of the Athenian water reservoirs

The aim of the present study is to compare the application of unsupervised and supervised pattern recognition techniques for the quality assessment and classification of the reservoirs used as the source for the domestic and industrial water supply of the city of Athens, Greece. A new optimization strategy for sampling, monitoring, and water management is proposed. During the period of October 2006 to April 2007, 89 samples were collected from the three water reservoirs (Iliki, Mornos, and Marathon), and 13 parameters (metals and metalloids) were analytically determined. Generally, all the elements were found to fluctuate at very low levels, especially for Mornos that comprises the main water reservoir of Athens. Iliki and Marathon showed relatively elevated values, compared to Mornos, but below the legislative limits. Multivariate unsupervised statistical techniques, such as factor analysis/principal components analysis, and cluster analysis and supervised ones, like discriminant analysis and classification trees, were applied to the data set, and their classification abilities were compared. All the chemometric techniques successfully revealed the critical variables and described the similarities and dissimilarities among the sampling points, emphasizing the individual characteristics in every sample and revealing the sources of elements in the region. New data from posterior samplings (November and December 2007) were used for the validation of the supervised techniques. Finally, water management strategies were proposed concerning the sampling points and representative parameters.     

Contribution of transition metals in the reactive oxygen species activity of PM emissions from retrofitted heavy-duty vehicles

We assessed the contribution of water-soluble transition metals to the reactive oxygen species (ROS) activity of diesel exhaust particles (DEPs) from four heavy-duty vehicles in five retrofitted configurations (V-SCRT, Z-SCRT, DPX, hybrid, and school bus). A heavy-duty truck without any control device served as the baseline vehicle. Particles were collected from all vehicle-configurations on a chassis dynamometer under three driving conditions: cruise (80 km h^?1), transient UDDS, and idle. A sensitive macrophage-based in vitro assay was used to determine the ROS activity of collected particles. The contribution of water-soluble transition metals in the measured activity was quantified by their removal using a Chelex^® complexation method. The study demonstrates that despite an increase in the intrinsic ROS activity (per mass basis) of exhaust PM with use of most control technologies, the overall ROS activity (expressed per km or per h) was substantially reduced for retrofitted configurations compared to the baseline vehicle. Chelex treatment of DEPs water extracts removed a substantial (≥70%) and fairly consistent fraction of the ROS activity, which ascertains the dominant role of water-soluble metals in PM-induced cellular oxidative stress. However, relatively lower removal of the activity in few vehicle-configurations (V-SCRT, DPX and school bus idle), despite a large aggregate metals removal, indicated that not all species were associated with the measured activity. A univariate regression analysis identified several transition metals (Fe, Cr, Co and Mn) as significantly correlated (R > 0.60; p < 0.05) with the ROS activity. Multivariate linear regression model incorporating Fe, Cr and Co explained 90% of variability in ROS levels, with Fe accounting for the highest (84%) fraction of the variance.     

Impact of roadside noise barriers on particle size distributions and pollutants concentrations near freeways

Increasing epidemiological evidence has established an association between a host of adverse health effects and exposure to ambient particulate matter (PM) and co-pollutants, especially those emitted from motor vehicles. Although PM and their co-pollutants dispersion profiles near the open freeway have been extensively characterized by means of both experimental measurements and numerical simulations in recent years, such investigations near freeways with roadside barriers have not been well documented in the literature. A few previous studies suggested that the presence of roadside structures, such as noise barriers and vegetation, may impact the decay of pollutant concentrations downwind of the freeway by limiting the initial dispersion of traffic emissions and increasing their vertical mixing due to the upward deflection of airflow. Since the noise barriers are now common roadside features of the freeways, particularly those running through populated urban areas, it is pertinent to investigate the impact of their presence on the particles and co-pollutants concentrations in areas adjacent to busy roadways. This study investigated two highly trafficked freeways (I-710 and I-5) in Southern California, with two sampling sites for each freeway, one with and the other without the roadside noise barriers. Particle size distributions and co-pollutants concentrations were measured in the immediate proximity of freeways and at different distances downwind of the freeways. The results showed the formation of a “concentration deficit” zone in the immediate vicinity of the freeway with the presence of roadside noise barrier, followed by a surge of pollutant concentrations further downwind at 80–100 m away from freeway. The particle and co-pollutants concentrations reach background levels at farther distances of 250–400 m compared to 150–200 m at the sites without roadside noise barriers.     

Siting MSW landfills with a spatial multiple criteria analysis methodology

The present work describes a spatial methodology which comprises several methods from different scientific fields such as multiple criteria analysis, geographic information systems, spatial analysis and spatial statistics. The final goal of the methodology is to evaluate the suitability of the study region in order to optimally site a landfill. The initial step is the formation of the multiple criteria problem's hierarchical structure. Then the methodology utilizes spatial analysis processes to create the evaluation criteria, which are mainly based on Greek and EU legislation, but are also based on international practice and practical guidelines. The relative importance weights of the evaluation criteria are estimated using the analytic hierarchy process. With the aid of the simple additive weighting method, the suitability for landfill siting of the study region is finally evaluated. The resulting land suitability is reported on a grading scale of 0-10, which is, respectively, from least to most suitable areas. The last step is a spatial clustering process, which is being performed in order to reveal the most suitable areas, allowing an initial ranking and selection of candidate landfill sites. The application of the presented methodology in the island of Lemnos in the North Aegean Sea (Greece) indicated that 9.3% of the study region is suitable for landfill siting with grading values greater than 9.     

An intelligent way for discerning plastics at the shorelines and the seas

Irrespective of how plastics litter the coastline or enter the sea, they pose a major threat to birds and marine life alike. In this study, an artificial intelligence tool was used to create an image classifier based on a convolutional neural network architecture that utilises the bottleneck method. The trained bottleneck method classifier was able to categorise plastics encountered either at the shoreline or floating at the sea surface into eight distinct classes, namely, plastic bags, bottles, buckets, food wrappings, straws, derelict nets, fish, and other objects. Discerning objects with a success rate of 90%, the proposed deep learning approach constitutes a leap towards the smart identification of plastics at the coastline and the sea. Training and testing loss and accuracy results for a range of epochs and batch sizes have lent credibility to the proposed method. Results originating from a resolution sensitivity analysis demonstrated that the prediction technique retains its ability to correctly identify plastics even when image resolution was downsized by 75%. Intelligent tools, such as the one suggested here, can replace manual sorting of macroplastics from human operators revealing, for the first time, the true scale of the amount of plastic polluting our beaches and the seas.

     

Effectiveness of tertiary treatment processes in removing different classes of emerging contaminants from domestic wastewater

● Different advanced treatment processes were tested for ECs removal from wastewater. ● UV radiation showed low to moderate removal for 5 of the 38 micropollutants. ● Among tested membrane processes, nanofiltration showed the better performance. ● The use of PAC achieved high or partially removal for 31 out of the 38 compounds. ● The environmental and economical evaluation of a pilot-scale PAC unit is suggested. In this work, 38 different organic emerging contaminants (ECs), belonging to various chemical classes such as pharmaceuticals (PhCs), endocrine-disrupting chemicals (EDCs), benzotriazoles (BTRs), benzothiazoles (BTHs), and perfluorinated compounds (PFCs), were initially identified and quantified in the biologically treated wastewater collected from Athens’ (Greece) Sewage Treatment Plant (STP). Processes already used in existing STPs such as microfiltration (MF), nanofiltration (NF), ultrafiltration (UF), UV radiation, and powdered activated carbon (PAC) were assessed for ECs’ removal, under the conditions that represent their actual application for disinfection or advanced wastewater treatment. The results indicated that MF removed only one out of the 38 ECs and hence it was selected as pretreatment step for the other processes. UV radiation in the studied conditions showed low to moderate removal for 5 out of the 38 ECs. NF showed better results than UF due to the smaller pore sizes of the filtration system. However, this enhancement was observed mainly for 8 compounds originating from the classes of PhCs and PFCs, while the removal of EDCs was not statistically significant. Among the various studied technologies, PAC stands out due to its capability to sufficiently remove most ECs. In particular, removal rates higher than 70% were observed for 9 compounds, 22 were partially removed, while 7 demonstrated low removal rates. Based on our screening experiments, future research should focus on scaling-up PAC in actual conditions, combining PAC with other processes, and conduct a complete economic and environmental assessment of the treatment.