Assessment of total concentrations of heavy metals in industrial sludges from the North of Vietnam and their potential impact on the ecosystem

Environmental Science and Pollution Research - Industrial sludges from wastewater treatment plants of industrial parks and a drinking water treatment plant in northern Vietnam were investigated in...     

Ecological and physiological controls of species composition in green macroalgal blooms

Green macroalgal blooms have substantially altered marine community structure and function, specifically by smothering seagrasses and other primary producers that are critical to commercial fisheries and by creating anoxic conditions in enclosed embayments. Bottom-up factors are viewed as the primary drivers of these blooms, but increasing attention has been paid to biotic controls of species composition. In Washington State, USA, blooms are often dominated by Ulva spp. intertidally and Ulvaria obscura subtidally. Factors that could cause this spatial difference were examined, including competition, grazer preferences, salinity, photoacclimation, nutrient requirements, and responses to nutrient enrichment. Ulva specimens grew faster than Ulvaria in intertidal chambers but not significantly faster in subtidal chambers. Ulva was better able to acclimate to a high-light environment and was more tolerant of low salinity than Ulvaria. Ulvaria had higher tissue N content, chlorophyll, chlorophyll b: chlorophyll a, and protein content than Ulva. These differences suggest that nitrogen availability could affect species composition. A suite of five grazers preferred Ulva to Ulvaria in choice experiments. Thus, bottom-up factors allow Ulva to dominate the intertidal zone while resistance to grazers appears to allow Ulvaria to dominate the subtidal zone. While ulvoid algae are in the same functional-form group, they are not functionally redundant.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

Controlling mechanisms of aluminium in soil solution--an evaluation of 180 podzolic forest soils.

To monitor the level of soil acidification in the county of V?rmland in the middle west of Sweden 180 podzolic forest soils were investigated. Soil solutions from four horizons were obtained by centrifugation and the soil was sampled for a determination of the exchangeable pool by extraction. The concentrations of inorganic Al and its fraction of the total Al in solution were greater in the south of the county (up to 50%). The factors influencing the total Al and free inorganic Al3+ in the soil solutions were evaluated. Saturation indices (SI) for five different mineral phases were calculated but none implied equilibrium conditions. The relationships between pAl3+ and pH (in the pH range 4-6.2) gave slopes of about 1, which indicated that ion exchange/complexation reactions may be important for determining the Al3+ concentration in the B and C horizons. In the E horizon solutions complexation with soluble organic acids seemed to be the major factor which influenced the Al3+ activity. The influence of organic matter on Al solubility was supported by partial least square (PLS) regressions.     

Modelling of stable isotope fractionation by methane oxidation and diffusion in landfill cover soils

A technique to measure biological methane oxidation in landfill cover soils that is gaining increased interest is the measurement of stable isotope fractionation in the methane. Usually to quantify methane oxidation, only fractionation by oxidation is taken into account. Recently it was shown that neglecting the isotope fractionation by diffusion results in underestimation of the methane oxidation. In this study a simulation model was developed that describes gas transport and methane oxidation in landfill cover soils. The model distinguishes between (12)CH(4), (13)CH(4), and (12)CH(3)D explicitly, and includes isotope fractionation by diffusion and oxidation. To evaluate the model, the simulations were compared with column experiments from previous studies. The predicted concentration profiles and isotopic profiles match the measured ones very well, with a root mean square deviation (RMSD) of 1.7vol% in the concentration and a RMSD of 0.8 per thousand in the delta(13)C value, with delta(13)C the relative (13)C abundance as compared to an international standard. Overall, the comparison shows that a model-based isotope approach for the determination of methane oxidation efficiencies is feasible and superior to existing isotope methods.     

An enzyme-linked immunosorbent assay for the determination of dioxins in contaminated sediment and soil samples

A 96-microwell enzyme-linked immunosorbent assay (ELISA) method was evaluated to determine PCDDs/PCDFs in sediment and soil samples from an EPA Superfund site. Samples were prepared and analyzed by both the ELISA and a gas chromatography/high resolution mass spectrometry (GC/HRMS) method. Comparable method precision, accuracy, and detection level (8 ng kg(-1)) were achieved by the ELISA method with respect to GC/HRMS. However, the extraction and cleanup method developed for the ELISA requires refinement for the soil type that yielded a waxy residue after sample processing. Four types of statistical analyses (Pearson correlation coefficient, paired t-test, nonparametric tests, and McNemar's test of association) were performed to determine whether the two methods produced statistically different results. The log-transformed ELISA-derived 2,3,7,8-tetrachlorodibenzo-p-dioxin values and log-transformed GC/HRMS-derived TEQ values were significantly correlated (r=0.79) at the 0.05 level. The median difference in values between ELISA and GC/HRMS was not significant at the 0.05 level. Low false negative and false positive rates (<10%) were observed for the ELISA when compared to the GC/HRMS at 1,000 ng TEQ kg(-1). The findings suggest that immunochemical technology could be a complementary monitoring tool for determining concentrations at the 1,000 ng TEQ kg(-1) action level for contaminated sediment and soil. The ELISA could also be used in an analytical triage approach to screen and rank samples prior to instrumental analysis.     

Refinery evaluation of optical imaging to locate fugitive emissions

Fugitive emissions account for approximately 50% of total hydrocarbon emissions from process plants. Federal and state regulations aiming at controlling these emissions require refineries and petrochemical plants in the United States to implement a Leak Detection and Repair Program (LDAR). The current regulatory work practice, U.S. Environment Protection Agency Method 21, requires designated components to be monitored individually at regular intervals. The annual costs of these LDAR programs in a typical refinery can exceed US$1,000,000. Previous studies have shown that a majority of controllable fugitive emissions come from a very small fraction of components. The Smart LDAR program aims to find cost-effective methods to monitor and reduce emissions from these large leakers. Optical gas imaging has been identified as one such technology that can help achieve this objective. This paper discusses a refinery evaluation of an instrument based on backscatter absorption gas imaging technology. This portable camera allows an operator to scan components more quickly and image gas leaks in real time. During the evaluation, the instrument was able to identify leaking components that were the source of 97% of the total mass emissions from leaks detected. More than 27,000 components were monitored. This was achieved in far less time than it would have taken using Method 21. In addition, the instrument was able to find leaks from components that are not required to be monitored by the current LDAR regulations. The technology principles and the parameters that affect instrument performance are also discussed in the paper.     

Effect of vegetation type on throughfall deposition and seepage flux

This paper compares different vegetation types (coniferous and deciduous forest, grassed and pure heathland) in terms of input (throughfall deposition) and output (seepage flux) in a region with intermediate nitrogen load (+/-20kg Nha(-1)y(-1) via bulk precipitation) in comparable conditions in north Belgium. Coniferous forest (two plots Pinus sylvestris and two plots Pinus nigra) received significantly higher nitrogen and sulphur throughfall deposition than deciduous forest and heathland. Grassed and pure heathland had significantly highest throughfall quantities of Ca(2+) and Mg(2+), respectively. The observed differences in throughfall deposition between the different vegetation types were not univocally reflected in the ion seepage flux. Considerable seepage fluxes of NO(3)(-), SO(4)(2-), Ca(2+) and Al(III) were only found under the P. nigra plots. We discuss our hypothesis that the P. nigra forests already evolved to a situation of N saturation, while the other vegetation types did not.     

The relationship between diversity profiles,evenness and species richness based on partial ordering

Problems with the notion of evenness, such as ambiguity, proliferation of indices, choice of indices, etc. can be overcome by a more fundamental, mathematical approach. We show that the Lorenz curve is an adequate representation of evenness. The corresponding Lorenz order induces a partial order in the set of equivalent abundance vectors. Also diversity can adequately be studied through a partial order and represented by a curve derived from the classical Lorenz curve. This curve is known as the intrinsic diversity profile (or k-dominance curve) and was introduced by Patil and Taillie (1979) and Lambshead et al. (1981).