Classification of local- and landscape-scale ecological types in the southern Appalachian Mountains

Five local ecological types based on vegetative communities and two landscape types based on groups of communities, were identified by integrating landform, soil, and vegetation components using multivariate techniques. Elevation and several topographic and soil variables were highly correlated with types of both scales. Landscape ecological types based only on landform and soil variables without vegetation did not correspond with types developed using vegetation. Models developed from these relationships could allow classification and mapping of extensive areas using geographic information systems.     

Reduction of SO2 emissions by ammonia gas during unstaged combustion

The reduction of SO₂ by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH₃:SO₂ molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO₂ emissions was found at 40% excess air, at an NH₃:SO₂ molar ratio of 5.4. The onset of SO₂ reduction occurred at an NH₃:SO₂ ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO₂ reduction.It is difficult to determine how the SO₂ reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide.     

A simple,cost-effective multispecies toxicity test using organisms with a cosmopolitan distribution

Difficulties in making accurate, ecosystem-level predictions of environmental effects of chemicals, mixtures, and effluents based solely on the results of tests on single species have necessitated the development of more environmentally realistic, predictive testing methods. This paper describes a multispecies, community-level toxicity test based on the colonization of artificial substrates by microbial species. Tests examined the colonization of initially barren polyurethane foam artificial substrates by Protozoa from a species source colonized in a natural system. Differences in colonization were examined in microecosystems amended with low levels of cadmium, a very toxic heavy metal, and TFM, an organic biocide used against larval sea lamprey. Tests examined differences in colonization over 28 days. For cadmium, effect levels were estimated to be near 1 g 1^–1, in the low range of effect levels determined from chronic single species tests. For TFM, effect levels were estimated to be between 1 and 10 ppm, overlapping the concentrations used in environmental applications. The colonization response, which depends on naked microbial cells reproducing and migrating through toxicant amended water to new substrates, is very sensitive. Tests based on colonization can be adapted to use species from a target receiving system or can use species from a designated natural source. Field validation of these tests can employ nearly identical methods to those used in laboratory studies to assess the accuracy of predictions based on test system data.     

Environmental and biological monitoring of methyl ethyl ketone (MEK)

This study was conducted to evaluate the usefulness of various biological parameters for monitoring of workers exposed to methyl ethyl ketone (MEK). Fifty male workers from a large magnetic videotape factory participated in this study. Personal air samples were collected using 3M organic vapor monitors and analysed for MEK by gas chromatography with flame ionisation detector (FID). 10 mL of urine; blood (1 mL) and exhaled air were also collected at the end of an 8-hour workshift. The headspace GC method was applied for measurement of urinary and blood MEK. MEK in expired air was analysed directly by using a GC/FID.The correlation coefficients (r) between environmental MEK and all other biological parameters measured show significant positive relationships. The r for environmental MEK and urine MEK was 0.84; for blood 0.73 and for breath 0.64. The correlation coefficients between blood and urine was 0.72; blood and breath was 0.88 and urine and breath 0.60. These findings suggest that measurements of unmetabolised MEK in blood, exhaled air and urine can be used for biological monitoring of MEK exposure. Nevertheless, laboratory methodological assessment is in favour of measuring urinary MEK as it is non-invasive and does not have to be analysed immediately after collection.     

The influence of geometry and draught shields on the performance of passive samplers

Passive samplers provide an excellent opportunity to perform indicative measurements or establish a dense network of measuring sites. A drawback compared with conventional active measuring methods is the larger spread of results. This variation can, to a large extent, be attributed to the influence of temperature, sampler geometry and wind on sampling results. A proper design of sampler geometry and optimum choice of draught shield can reduce the influence of wind velocity on a badge type sampler to less than 10%. Wire mesh screens prove to be inadequate in damping turbulence. Filters give good results. Attention should be paid to the size and isolation value of the walls of the sampler to prevent thermal updrafts occurring within the sampler. Tube type samplers are less influenced by wind, provided that turbulence is prevented from influencing diffusion within the sampler.     

Development of an ombrotrophic peat bog (low ash) reference material for the determination of elemental concentrations

Given the increasing interest in using peat bogs as archives of atmospheric metal deposition, the lack of validated sample preparation methods and suitable certified reference materials has hindered not only the quality assurance of the generated analytical data but also the interpretation and comparison of peat core metal profiles from different laboratories in the international community. Reference materials play an important role in the evaluation of the accuracy of analytical results and are essential parts of good laboratory practice. An ombrotrophic peat bog reference material has been developed by 14 laboratories from nine countries in an inter-laboratory comparison between February and October 2002. The material has been characterised for both acid-extractable and total concentrations of a range of elements, including Al, As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Mn, Na, Ni, P, Pb, Ti, V and Zn. The steps involved in the production of the reference material (i.e. collection and preparation, homogeneity and stability studies, and certification) are described in detail.     

Organochlorine Pesticide Residues in Wheat and Drinking Water Samples from Jaipur, Rajasthan, India

The organochlorine pesticide contamination in dietary sources has caused serious threat to the human progeny. The present study was therefore conducted to evaluate the pesticide contamination in wheat flour and drinking water from Jaipur City, Rajasthan, India using Gas Chromatograph. All the wheat and water samples were found to be contaminated with various organochlorine pesticide residues of DDT and its metabolites, HCH and its isomers, heptachlor and its expoxide and aldrin. The amount of pesticide detected in wheat flour was higher than the permissible limits prescribed by WHO/FAO. In drinking water only a few pesticides exceeded the permissible limits. Seasonal variations of pesticides residues were also observed during the study period.     

The fate of fipronil in modular estuarine mesocosms

The degradation and corresponding product manifold for the pesticide fipronil was determined in three replicate estuarine mesocosms. Aqueous fipronil concentrations rapidly decreased over the 672 h timescale of the experiment (95% removal). Loss was apparently first-order in fipronil, although there appeared to be a change in the removal mechanism after 96 h that corresponded to a dramatic slowdown in its disappearance. The reduction product of fipronil, fipronil sulfide, was not detected in the water column; however, it formed rapidly in sediments and was identified as the major product of fipronil degradation in the system (20% yield at 672 h, with respect to initial fipronil concentration). Fipronil sulfone is thought to form primarily via biological oxidation; and, although it was generated rapidly in the water column (10% yield), only trace amounts were detected in the sediment (1% yield). The direct photolysis product of fipronil, fipronil desulfinyl, was present in all samples; it formed rapidly in the water column (4% yield) and partitioned into the sediment phase (7% yield) over the course of the experiment. The mass balance on fipronil and associated products was 42% at 672 h.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results. The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

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.