Energy management in hybrid electric vehicles using optimized radial basis function neural network

This paper deals with energy management in hybrid electric vehicles. Use of radial basis function neural network (RBFNN) for the problem of energy management gains importance in the present decade. Use of genetic algorithm (GA) and particle swarm optimization (PSO) as optimization algorithms for parameter estimation is also well known. However, none of the researchers in the area tried to use GA and PSO as training algorithms for the problem. Hence in this paper, we propose two novel methods, based on RBFNN. The difference between RBFNN-based approaches in the literature and those used in this paper is the use of GA and PSO (i.e. optimising algorithms) as training algorithm to train RBFNNs. Interestingly, it is seen that the proposed approaches of this paper outperform RBFNN-based approaches in the literature with traditional training.     

Impacts of climatic change and low frequency variability in reference series on daily maximum and minimum temperature in southern South America

Understanding the climate and its variability, in particular with regard to their socioeconomic impact, requires specific measurements of precipitation and temperature and their circulations. This becomes more important in applications to diverse systems. In order to improve knowledge about temporal changes and trends in temperature, we analyzed series of maximum and minimum daily surface temperatures at eight reference stations in southeastern South America during variable periods, with the longest periods of around 100 years. To study the evolution of the temperature series and to reduce the number of parameters, a nonhierarchical cluster analysis was performed. The algorithm assigns each day to one of four groups: warm, wet, cold and dry. Low frequency variations were found in these groups and their association with circulation structure, circulation patterns and precipitation. We concluded that the set of wet days is one of the main factors driving secular variations of maximum and minimum temperature and variations in precipitation. We also inferred that after 1920 till 1930, a low frequency oscillation is observed in the form of linear trends (increase of warm days and decrease of cold days).     

Prediction of SVOC vegetation and atmospheric concentrations using calculated deposition velocities

A simple modeling concept was previously applied to study air-foliage exchange of both polybrominated diphenyl ethers (PBDEs) and polycyclic aromatic hydrocarbons (PAHs) using field measurements. In this paper, the predictive capabilities of this framework were tested using an independent set of data collected at the same sampling location for a different time period. Firstly, atmospheric (particle-bound and gaseous phase) PBDE and PAH concentrations were used to predict their accumulation in spruce needles. Conversely, we used PBDE and PAH concentrations in vegetation to predict their atmospheric concentrations. In both cases, calculated and measured values showed good agreement, providing evidence that the developed framework and our derived deposition velocities can be used as a predictive tool for these two different classes of semi-volatile organic compounds.     

Determination of the sources of toxic elements in environmental particles using microscopic and statistical analysis techniques

Samples of urban dust were physically fractionated into subsamples having unique size, density, ferromagnetism, and elemental compositional characteristics. The high density fractions containing the majority of each of the potentially toxic metals (Pb, Cd, Zn, Cr, Co, Mn) were subjected to X-ray microanalysis and to bulk analysis using instrumental neutron activation. Microanalysis was used to classify individual particles with respect to primary sources. The bulk analytical results were subjected to factor analysis to delineate the underlying factors (particle sources) responsible for the compositional variation in the subsamples. The advantages of the combined use of microanalytical and statistical techniques for source definition are described. X-ray microanalysis is used to substantiate the attribution of a given factor to a suspected particle source, to aid in the determination of the number of factors (sources) present, and to assess the extent to which a given factor represents a unique source of particles. Bulk analysis/factor analysis promotes the most effective use of X-ray microanalysis to characterize major particle types, and provides data on some toxic trace metals (e.g., Cd) that are not detectable using X-ray microanalysis. Target transformation factor analysis also is more useful in the quantitative determination of the relative mass contributions of major sources to the total dust sample.     

An efficient neural network model for aiding the coagulation process of water treatment plants

Environment, Development and Sustainability - In a water treatment plant, the decision to carry out a jar test, for determining the required coagulant dosage, is made based on notable changes in...     

Assessing groundwater quality and its sustainability in Joypurhat district of Bangladesh using GIS and multivariate statistical approaches

Sustainable groundwater quality is a key global concern and has become a major issue of disquiets in most parts of the world including Bangladesh. Hence, the assessment of groundwater quality is an important study to ensure its sustainability for various uses. In this study, a combination of multivariate statistics, geographical information system (GIS) and geochemical approaches was employed to evaluate the groundwater quality and its sustainability in Joypurhat district of Bangladesh. The results showed that the groundwater samples are mainly Ca–Mg–HCO₃ type. Principal component analysis (PCA) results revealed that geogenic sources (rock weathering and cation exchange) followed by anthropogenic activities (domestic sewage and agro-chemicals) were the major factors governing the groundwater quality of the study area. Furthermore, the results of PCA are validated using the cluster analysis and correlation matrix analysis. Based on the groundwater quality index (GWQI), it is found that all the groundwater samples belong to excellent to good water quality domains for human consumption, although iron, fluoride and iodide contaminated to the groundwater, which do not pose any significant health hazard according to World Health Organization’s and Bangladesh’s guideline values. The results of irrigation water quality index including sodium adsorption ratio (SAR), permeability index and sodium percentage (Na %) suggested that most of the groundwater samples are good quality water for agricultural uses. The spatial distribution of the measured values of GWQI, SAR, Fe (iron), EC (electrical conductivity) and TH (total hardness) were spatially mapped using the GIS tool in the study area.     

The forecasting of municipal waste generation using artificial neural networks and sustainability indicators

The feasibility of modeling municipal waste generation (MWG) for countries at different levels of development using artificial neural networks (ANN) and selected generic indicators of sustainability was investigated. The main goals of this research were to develop ANN-based models for predicting MWG, to overcome the problem of incomplete MWG data, which is notable in developing countries, and to provide a new method for the planning of municipal solid waste management systems as well as for the simulation of various other scenarios. Data from 26 European countries was used in this study as training, test and validation datasets for the developing of ANN models. Since this kind of modeling is particularly important for developing countries where MWG data is missing or incomplete, emphasis was placed on modeling of MWG for Bulgaria and Serbia. Based on a comparison of actual MWG data with predictions given by the model, we show that ANNs can be applied successfully to modeling and forecasting MWG on a national scale. Moreover, the scope for possible application of the model is broad, since it uses generic indicators of sustainability such as gross domestic product, domestic material consumption and resource productivity, and performs well for countries with highly diversified levels of economic development, industrial structure, productivity and output.     

Evaluation of sustainability using an integrated approach at process and product level: a case study

The present world is facing problems like rapid depletion of natural resources and undesired environmental changes on a global scale. Manufacturing organisations are realising the importance of mitigating the present crisis and are adopting sustainable manufacturing principles. Since it is important to achieve sustainable manufacturing, sustainability assessment models were developed. Sustainability assessment models have their own drawbacks and may not provide clear scope for complete sustainable development. A system approach has been developed to overcome this shortcoming by integrating various sustainability assessment models that are already in practice. This article reports the advantages of collecting the advantages of individual sustainability assessment models and how the implementation of the integrated approach has helped to identify the current sustainability level and the scope for future developments in an automotive industry.     

Low level radioactivity measurements with phoswich detectors using coincident techniques and digital pulse processing analysis

A new system has been developed for the detection of low radioactivity levels of fission products and actinides using coincidence techniques. The device combines a phoswich detector for alpha/beta/gamma-ray recognition with a fast digital card for electronic pulse analysis. The phoswich can be used in a coincident mode by identifying the composed signal produced by the simultaneous detection of alpha/beta particles and X-rays/gamma particles. The technique of coincidences with phoswich detectors was proposed recently to verify the Nuclear Test Ban Treaty (NTBT) which established the necessity of monitoring low levels of gaseous fission products produced by underground nuclear explosions. With the device proposed here it is possible to identify the coincidence events and determine the energy and type of coincident particles. The sensitivity of the system has been improved by employing liquid scintillators and a high resolution low energy germanium detector. In this case it is possible to identify simultaneously by alpha/gamma coincidence transuranic nuclides present in environmental samples without necessity of performing radiochemical separation. The minimum detectable activity was estimated to be 0.01 Bq kg(-1) for 0.1 kg of soil and 1000 min counting.     

Disinfection of filtered and unfiltered secondary effluent in two ozone contactors

the objective of this study was to evaluate the effect of filtration of secondary effluent on the mass transfer and disinfection efficiencies of two ozone contactors. The two contactors used in the comparison were a multicolumn bubble diffuser and a stirred tank reactor. The approach chosen was based on a type of statistical experimental design used in a previous contactor comparison. The design made it possible to compare the ozone transfer and coliform reduction efficiencies of the two contactors with respect to applied dose, while at the same time comparing filtered and unfiltered effluent. Results indicated that better mass transfer efficiency and, consequently, better coliform reduction efficiency occurred in the bubble diffuser, and the differences between contactors increased with dose. Mass transfer in both contactors was higher in unfiltered effluent than in filtered effluent. The most significant factors affecting the fecal coliform numbers in the treated secondary effluent were total chemical oxygen demand (COD) and absorbed ozone dose. Regression equations were developed to predict final coliform numbers as a function of COD and absorbed ozone dose.     

High-resolution spatial analysis of stomatal ozone uptake in arable crops and pastures

Ozone effects on plants depend on atmospheric transport and stomatal uptake. Thus, ozone-risk assessments should use measured ozone concentrations and account for the influence of atmospheric conditions and soil moisture on stomatal and nonstomatal ozone deposition. This requires disaggregated data for the physical input parameters and species-specific data for specific stomatal conductance (g(s)). In this study, an approach was developed based on a resistance analogue transport model. This model requires interpolated routine-measuring data for ozone concentration at 3-5 m height, wind speed, precipitation, and soil moisture content as inputs to estimate the amount of ozone taken up by wheat (Triticum aestivum) and grass/clover pastures with a 1x1-km resolution. The model was applied to the area under agricultural production in Switzerland. Using data for June 1994, the calculations revealed that the median of the distribution of stomatal ozone uptake was 88% higher in wheat compared to grassland. This was mainly due to the higher maximum stomatal conductance in wheat. Because ozone flux to soil and to external plant surfaces was comparable in both vegetation types, the difference in the stomatal fluxes was mainly responsible for distinct differences in flux partitioning. In both cases, only about 11% of the total cumulative flux was absorbed by external plant surfaces, whereas the soil was a strong sink responsible for as much as 50% of the total flux into grasslands. The higher-ozone flux to wheat resulted in clearly lower-ozone concentrations at canopy height, but no significant correlation between cumulative canopy-level ozone exposure, expressed as accumulated exposure above 40 ppb (AOT40), and stomatal uptake was found. Thus, to estimate the ozone risk for crops using a flux-based approach may lead to results that differ substantially from those obtained with a concentration-based approach.     

The relationships of sprawl and ozone air quality in United States' metropolitan areas

This article reports the results of an examination of the relationships between degree of sprawl and improvements in ozone air quality for 52 metropolitan areas in the US. It also examines state political alignment and environmental resources with regard to these two primary objects of investigation. Evidence of a relationship between sprawl and air quality improvement was identified, but the evidence is ambiguous. More research appears warranted to explore the sprawl–air quality improvement relationship. Electronic Publication     

Exploring the linkages between river water chemistry and watershed characteristics using GIS-based catchment and locality analyses

A typology of land characteristics for the Humber catchment in central/eastern England is identified in relation to land use, hydrology and demographic, topographic and geological characteristics, using GIS and statistical analyses. Empirical relationships between land characteristics and water quality were examined in relation to the spatial variability in water quality across the Humber catchment. Analyses of relationships between land characteristics and water quality were undertaken at two hierarchical scales: (1) individual catchments and (2) localities of 10 km radius draining to each sampling site. The importance of urban and agricultural sources was identified, together with a hydrological component linked to dilution of point source inputs and mobilisation of specific sediment-associated contaminants in higher-energy (higher-flow) environments. High-solubility (dissolved) chemical determinands (such as B, Cl and SO₄), which undergo conservative transport through the river network, show the strongest linkages with land characteristics at the catchment scale. Cr, Zn and Ca show stronger correlations with land characteristics at the locality rather than the catchment scale, indicating that the concentrations of these determinands are more closely linked to the availability of localised sources. This work provides a starting point for investigating how changes in land use and management of drainage basins might impact river water quality at the regional scale and fluxes to the coastal zone, by providing a mechanism for examining linkages between regional-scale land characteristics and river water quality. The next step requires development of the approach within a more rigorous statistical framework and the extension of the regional analysis within a wider national and international context. Electronic Publication     

Predicting the transfer of radiocaesium from organic soils to plants using soil characteristics

A model predicting plant uptake of radiocaesium based on soil characteristics is described. Three soil parameters required to determine radiocaesium bioavailability in soils are estimated in the model: the labile caesium distribution coefficient (kd1), K+ concentration in the soil solution [mK] and the soil solution-->plant radiocaesium concentration factor (CF, Bq kg-1 plant/Bq dm-3). These were determined as functions of soil clay content, exchangeable K+ status, pH, NH4+ concentration and organic matter content. The effect of time on radiocaesium fixation was described using a previously published double exponential equation, modified for the effect of soil organic matter as a non-fixing adsorbent. The model was parameterised using radiocaesium uptake data from two pot trials conducted separately using ryegrass (Lolium perenne) on mineral soils and bent grass (Agrostis capillaris) on organic soils. This resulted in a significant fit to the observed transfer factor (TF, Bq kg-1 plant/Bq kg-1 whole soil) (P < 0.001, n = 58) and soil solution K+ concentration (mK, mol dm-3) (P < 0.001, n = 58). Without further parameterisation the model was tested against independent radiocaesium uptake data for barley (n = 71) using a database of published and unpublished information covering contamination time periods of 1.2-10 years (transfer factors ranged from 0.001 to 0.1). The model accounted for 52% (n = 71, P < 0.001) of the observed variation in log transfer factor.     

Prediction of the fate of radioactive material in the South Pacific Ocean using a global high-resolution ocean model

We investigate the release of radioactive contaminants from Moruroa Atoll in a global high-resolution off-line model. The spread of tracer is studied in a series of simulations with varying release depths and time-scales, and into ocean velocity fields corresponding to long-term annual mean, seasonal, and interannually varying scenarios. In the instantaneous surface release scenarios we find that the incorporation of a seasonal cycle greatly influences tracer advection, with maximum concentrations still found within the French Polynesia region after 10 years. In contrast, the maximum trace is located in the southeast Pacific when long-term annual mean fields are used. This emphasizes the importance of the seasonal cycle in models of pollution dispersion on large scales. We further find that during an El Ni?o/Southern Oscillation (ENSO) event reduced currents in the region of Moruroa Atoll result in increased concentrations of radioactive material in French Polynesia, as direct flushing from the source is reduced. In terms of the sensitivity to tracer release time-rates, we find that a gradual input results in maximum concentrations in the near vicinity of French Polynesia. This contrasts the instantaneous-release scenarios, which see maximum concentrations and tracer spread across much of the South Pacific Ocean. For example, in as little as seven years radioactive contamination can reach the east coast of Australia diluted by only a factor of 1,000 of the initial concentration. A comparison of results is made with previous studies. Overall, we find much higher concentrations of radionuclides in the South Pacific than has previously been predicted using coarser-resolution models.     

Perfluoroalkyl substances in soft tissues and tail feathers of Belgian barn owls (Tyto alba) using statistical methods for left-censored data to handle non-detects

Perfluoroalkyl substances (PFASs) were investigated in tail feathers and soft tissues (liver, muscle, preen gland and adipose tissue) of barn owl (Tyto alba) road-kill victims (n = 15) collected in the province of Antwerp (Belgium). A major PFAS producing facility is located in the Antwerp area and levels of PFASs in biota from that region have been found to be very high in previous studies. We aimed to investigate for the first time the main sources of PFASs in feathers of a terrestrial bird species. Throughout this study, we have used statistical methods for left-censored data to cope with levels below the limit of detection (LOD), instead of traditional, potentially biased, substitution methods.Perfluorooctane sulfonate (PFOS) was detected in all tissues (range: 11 ng/g ww in muscle–1208 ng/g ww in preen oil) and in tail feathers (< 2.2–56.6 ng/g ww). Perfluorooctanoate (PFOA) was measured at high levels in feathers (< 14–670 ng/g ww), but not in tissues (more than 50% < LOD). Perfluorohexane sulfonate (PFHxS) could only be quantified in liver and preen oil, while other PFASs were sporadically detected in liver. PFOS levels in feathers and liver were highly correlated (r = 0.78, p < 0.01), in contrast to PFOA (r = − 0.11, p = 0.78). Combined with high PFOA levels in feathers this suggests that PFOA may be present on the external surface of feathers, due to external contamination originating from the air in the vicinity of point sources. Therefore the possibility of using feathers as a passive air sampler for high PFOA levels should be investigated in the future.     

A preliminary study of ozone trend and its impact on environment in Hong Kong

As far as the impact of air pollutants on human health being is concerned, ozone (O3) is one of the most pollutant sources, and, in particular, the ground level ozone is responsible for a variety of adverse effects on both human being and plant life. To protect the population from such adverse health effects, early information and precautions about the high ozone level need to be ascertained. In this study, statistical characteristics of ground level ozone is analyzed according to field monitoring data in mixed residential, commercial and industrial areas, e.g., Tsuen Wan area in Hong Kong. The study deals with the characteristics of hourly and daily mean ozone levels under different climatic conditions such as temperature, solar radiation (SR), wind speed (WS), and other pollutant concentration levels. The study aims to investigate the importance of meteorological factors and their impact on relevant pollutant concentration levels from a chemical aspect. Further, reasons for the spatial and temporal variation of ozone levels are discussed. All these results will provide a physical basis for accurately predicting ozone concentration in similar research.     

A study of daily and seasonal variations of radon concentrations in underground buildings

A study of daily and seasonal variations of radon concentrations in underground buildings in major cities of China was carried out. According to the data from the Model 1027 continuous monitor, radon concentrations in the underground buildings changed through two cycles each day. The first cycle was from 12:00 to 0:00 and the highest or lowest value, depending on location, was at about 19:00. The second cycle had a little change. Based on the data from solid state nuclear detectors (SSNTDs), it was concluded that the radon concentrations in underground buildings in winter were lower than in summer, which was opposite to that above the ground level. Similar to that above the ground level, the radon concentrations in spring were close to the year-round average radon concentrations.     

An overview of cross-sectional studies of mortality and air pollution and related statistical issues

A heuristic framework is developed for assessing statistical studies of air pollution and mortality which use the General Linear Model as a principal tool for analysis. Arrays that systematically compare the information of each study are introduced. In addition, a number of studies are contrasted against several statistical criteria to assess the reliability of the study results. Reliability is considered in terms of statistical estimation theory and practice. Finally, there is a discussion of several points of statistical contention which can affect the results of these studies. The conclusion is that statistical studies that use the General Linear Model have made limited use of available methods and tests. Several issues are raised which will require additional research.     

Assessment of urban sprawl characteristics in Indian cities using remote sensing: case studies of Patna,Ranchi, and Srinagar

Environment, Development and Sustainability - The rapid urban growth in mid-sized cities of developing nations has induced conflict between development and the environment, often leading to urban...