Field evaluation of in situ remediation of a heavy metal contaminated soil using lime and red-mud

We evaluated the effectiveness of lime and red mud (by-product of aluminium manufacturing) to reduce metal availability to Festuca rubra and to allow re-vegetation on a highly contaminated brown-field site. Application of both lime and red mud (at 3 or 5%) increased soil pH and decreased metal availability. Festuca rubra failed to establish in the control plots, but grew to a near complete vegetative cover on the amended plots. The most effective treatment in decreasing grass metal concentrations in the first year was 5% red mud, but by year two all amendments were equally effective. In an additional pot experiment, P application in combination with red mud or lime decreased the Pb concentration, but not total uptake of Pb in Festuca rubra compared to red mud alone. The results show that both red mud and lime can be used to remediate a heavily contaminated acid soil to allow re-vegetation.     

Ecosystem responses to climate change at a Low Arctic and a High Arctic long-term research site

Long-term measurements of ecological effects of warming are often not statistically significant because of annual variability or signal noise. These are reduced in indicators that filter or reduce the noise around the signal and allow effects of climate warming to emerge. In this way, certain indicators act as medium pass filters integrating the signal over years-to-decades. In the Alaskan Arctic, the 25-year record of warming of air temperature revealed no significant trend, yet environmental and ecological changes prove that warming is affecting the ecosystem. The useful indicators are deep permafrost temperatures, vegetation and shrub biomass, satellite measures of canopy reflectance (NDVI), and chemical measures of soil weathering. In contrast, the 18-year record in the Greenland Arctic revealed an extremely high summer air-warming of 1.3 °C/decade; the cover of some plant species increased while the cover of others decreased. Useful indicators of change are NDVI and the active layer thickness.     

Synthesis and analytical follow-up of the mineralization of a new fluorosurfactant prototype

Fluorinated surfactants have become essential in numerous technical applications due to their unparalleled effectiveness and efficiency. The environmental persistence of the non-biodegradable perfluorinated alkyl moiety has become a matter of concern. Therefore, it was searched for new molecules with chemically stable fluorinated end groups which can be microbially transformed into labile fluorinated substances. One prototype substance, 10-(trifluoromethoxy)decane-1-sulfonate, has shown biomineralization. Monitoring the formation of metabolites over time elucidated the mechanism of biotransformation. Analysis was performed utilizing liquid chromatography-single quadrupole mass spectrometry (LC-MS) and quadrupole-time of flight tandem mass spectrometry (QqTOF-MS). It was possible to distinguish between two major degradation pathways of the fluorinated alkylsulfonate derivative: (i) a desulfonation and subsequent oxidation and degradation of the alkyl chain being predominant and (ii) an insertion of oxygen with a subsequent cleavage and degradation of the molecule. The utilized trifluoromethoxy-endgroup resulted in instable trifluoromethanol after degradation of the alkyl chain, which led to a high degree of mineralization of the molecule.     

Effects of pig manure compost and nonionic-surfactant Tween 80 on phenanthrene and pyrene removal from soil vegetated with Agropyron elongatum

This paper evaluates the effects of pig manure compost (PMC) and Tween 80 on the removal of phenanthrene (PHE) and pyrene (PYR) from soil cultivated with Agropyron elongatum. Soils spiked with about 300mgkg(-1) of PHE and PYR were individually amended with 0%, 2.5%, 5% and 7.5% (dry wt) of PMC or 0, 20 and 100mgkg(-1) of Tween 80. Unplanted and sterile microcosms were prepared as the controls. PAH concentration, total organic matter (TOM), dissolved organic carbon (DOC), total heterotrophic and PAH degrading microbial populations in soil were quantified before and after 60d period. The results indicated that A. elongatum could significantly enhance PYR removal (from 46% to 61%) but had less impact on PHE removal (from 96% to 97%). Plant uptake of the PAHs was insignificant. Biodegradation was the key mechanism of PAH removals (<3% losses in the sterile control). Increase in PMC or Tween 80 levels increased the removal of PYR but not of PHE. Maximal PYR removal of 79% and 92% were observed in vegetated soil receiving 100mgkg(-1) Tween 80 and 7.5% PMC, respectively. Enhanced PYR removal in soil receiving PMC could be explained by the elevated levels of DOC, TOM and microbial populations as suggested by Pearson correlation test. While the positive effect of Tween 80 on PYR removal could probably due to its capacities to enhance PYR bioavailability in soil. This paper suggests that the addition of either PMC or nonionic-surfactant Tween 80 could facilitate phytoremediation of PAH contaminated soil.     

An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

Persistent “upwelling shadows” and their influence on zooplankton distributions

Physical (temperature and salinity) and biological (zooplankton) properties were sampled over a 15 mo period in 1988 and 1989 to monitor nearshore environmental variability in northern Monterey Bay, California, USA. During the upwelling seasons of 1988 and 1989, there were two distinct bodies of water along the sampling transect. The offshore water body was characterized by recently upwelled water (typically <12°C) while the nearshore body was significantly warmer (approaching 16°C). A sharp thermal gradient (=front) separated the two water bodies. This front persisted 6.5 km from shore throughout the upwelling season of 1988 and was present again in 1989. Zooplankton-assemblage analysis confirmed the presence of two distinct regions in northern Monterey Bay. We refer to this phenomenon as an upwelling shadow, which is the result of the advection of recently upwelled water bearing nutrients and larvae past coastal recesses which are equatorward of upwelling centers.     

Monitoring of diazinon concentrations and loadings,and identification of geographic origins consequent to stormwater runoff from orchards in the Sacramento River watershed,U.S.A

Diazinon contamination of California's rivers has resulted in placing several rivers on the federal Clean Water Act § 303d list of impaired waterways. Impaired water body listing requiresthe development of Total Maximum Daily Loads (TMDL). Previous studies identified stormwater related diazinon pulses in California rivers. This study was conducted to monitor diazinonconcentrations in the Sacramento River watershed after rainfallevents, to ascertain whether pulses could be identified and, ifconcentrations of concern were observed, to estimate loadings anddetermine geographic origins of the insecticide. TMDL developmentrequires knowledge of contaminant sources, loadings, and geographic origins. Flow and diazinon concentrations peaked in the Sacramento River at Sacramento after the three largest stormsduring January and February 1994. Diazinon concentrations peakedconsequent to each of three storms. Diazinon concentrationsmeasured in the Sacramento River at Sacramento exceeded theCalifornia Department of Fish and Game acute and chroniccriteria for protection of aquatic life during January andFebruary for nine and nineteen days, respectively. Multipleexceedances were observed throughout the watershed. Diazinon loading and geographic origin differed with each of the three storms. The design of this study provides a useful template for others attempting to identify loadings and sources of contaminants in surface waters and to rectify aquatic ecosystemcontamination from various land use practices.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.