State estimation in wastewater engineering: Application to an anaerobic process

The use of an extended Kalman filter for state estimation in biological wastewater treatment processes is discussed. The application of the technique requires an adequate mechanistic dynamic model and the identification and modelling of the major sources of stochastic disturbances in the process. The filter allows the on-line tracking of process variables which are not directly measurable. The use of an extended Kalman filter is illustrated through a simulated application to a high rate anaerobic wastewater treatment process.     

Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Laboratory-polluted soils: a methodological approach to establish equilibrium conditions for different metal chemical forms in soils

An approach based on the number of extractions performed over time was applied to study the time necessary to attain equilibrium conditions between the different chemical forms present in two natural soils laboratory-loaded with heavy metals (Cu(II), Pb(II), Zn(II)). The influence of some soil parameters, such as pH value, cation exchange capacity and organic matter content, on the equilibrium time was evidenced both by the different nature of the soils and by the treatment of soils with paper mill sludge. Equilibrium conditions were determined by studying the metal partitioning in the soil on a case by case basis. The behaviour of the three metals was not the same, and the conditions of equilibrium among the different chemical forms were the result of the amount of heavy metals added as well as of the nature of the soil.     

Impact of automobile emissions on the levels of platinum and lead in Accra,Ghana

Examination of car fleet records in Accra demonstrates an increasing proportion of catalytic converter-equipped cars in the relatively old car fleet (average age 13 years) due to their import from developed countries. However, only leaded petrol is sold in Ghana. Lead anti-knocking additives, which are known to affect catalyst activity and promote thermal sintering and mechanical abrasion, may increase Pt emissions. This possible synergism prompted the concomitant determination of Pb and Pt levels in road dust and roadside soils in Ghana. Both metals followed traffic density with higher concentrations in urban areas compared to remote sites. In urban areas, the range for Pb (365 +/- 93 microg g(-1) for dust and 291 +/- 76 microg g(-1) for soil) reflects precatalyst levels in Europe and the US, while the range for Pt (39 +/- 24 ng g(-1) for dust and 15 +/- 5.3 ng g(-1) for soil) is typical for the same countries. The elevated Pt concentrations were unexpected due to recent introduction of catalysts to Ghana compared to the prolonged use of catalysts in Europe and the US.     

Suspended particulates and bioaerosols emitted from an agricultural non-point source

Suspended particulate and bioaerosol levels were measured at three sites downwind of an agricultural non-point source during the wheat harvesting season. Suspended particulates were detected at mean values ranging from 10000 to 2420 micrograms m-3 at distances of from 20 to 60 m downwind of the source, respectively. Airborne viable bacterial counts were recorded at mean values ranging between 10(4) and 10(6) colony forming units (cfu) m-3, whereas, Gram negative (Gram -ve) bacteria varied between 10(3) and 10(5) cfu m-3. Fungi levels were detected at mean values varying between 10(5) and 10(6) cfu m-3. However, streptomycetes were found at lower counts than those recorded for viable bacteria and fungi. Total viable bacteria, Gram -ve bacteria, fungi and streptomycetes associated hay fragments were determined at mean values of 1.5 x 10(6), 1.6 x 10(3), 2.2 x 10(4) and 6 x 10(3) cfu g-1 of hay, respectively. Cladosporium, white and red yeasts as well as Alternaria were the predominant airborne fungi, whereas, Alternaria was the dominant species associated with hay fragments. Pseudomonas, Acinetobacter and Enterobacteriaceae were the dominant Gram -ve bacteria. The most common fungal genera, such as Cladosporium and Fusarium (minor short axis), as well as Streptomyces species have an aerodynamic diameter (dae) of less than 5 microns, which can penetrate and deposit in the alveoli. Farmers and nearby residents are exposed to high levels of organic dust and bioaerosols during the wheat harvesting season. This may cause health problems in exposed persons based on toxic or allergic reactions.     

Arsenic speciation in human hair: a new perspective for epidemiological assessment in chronic arsenicism

The analysis for arsenic in hair is commonly used in epidemiological studies to assess exposure to this toxic element. However, poor correlation between total arsenic concentration in hair and water sources have been found in previous studies. Exclusive determination of endogenous arsenic in the hair, excluding external contamination has become an analytical challenge. Arsenic speciation in hair appears as a new possibility for analytical assessing in As-exposure studies. This study applied a relative simple method for arsenic speciation in human hair based on water extraction and HPLC-HG-ICP-MS. The concentration of arsenic species in human hair was assessed in chronically As(V)-exposed populations from two villages (Esqui?a and Illapata) of the Atacama Desert, Chile. The arsenic concentrations in drinking water are 0.075 and 1.25 mg L(-1), respectively, where As(V) represented between 92 and 99.5% of the total arsenic of the consumed waters. On average, the total arsenic concentrations in hair from individuals of Esqui?a and Illapata were 0.7 and 6.1 microg g(-1), respectively. Four arsenic species, As(III), DMA(V), MMA(V) and As(V), were detected and quantified in the hair extracts. Assuming the found species in extracts represent the species in hair, more than 98% of the total arsenic in hair corresponded to inorganic As. On average, As(III) concentrations in hair were 0.25 and 3.75 microg g(-1) in Esqui?a and Illapata, respectively; while, the As(V) average concentrations were 0.15 and 0.45 microg g(-1) in Esqui?a and Illapata, respectively. Methylated species represent less than 2% of the extracted As (DMA(V)+ MMA(V)) in both populations. As(III) in hair shows the best correlation with chronic exposure to As(V) in comparison to other species and total arsenic. In fact, concentrations of As(total), As(III) and As(V) in hair samples are correlated with the age of the exposed individuals from Illapata (R= 0.65, 0.69, 0.57, respectively) and with the time of residence in this village (R= 0.54, 0.71 and 0.58, respectively).     

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.