Fecundity of the freshwater fish Channa punctatus (Bloch) from three aquatic bodies

The fecundity studies on Channa punctatus revealed that there is a relationship between length of the fish with fecundity, weight of the fish and ovary with fecundity. The length and fecundity exhibit curvilinear relationship and a straight line relationship is observed between fecundity and body weight. Fecundity and ovary weight also exhibited linear relationship. The comparative degree of fecundity of the fish is Jagat tank > Kadaganchi tank > Kagina river. Although fish collected from Jagat tank exhibits higher fecundity, all the other three aquatic bodies provide proper environmental conditions for the growth and reproductive activity of the fish.     

Arsenic and other toxic elemental contamination of groundwater, surface water and soil in Bangladesh and its possible effects on human health

The problems of contamination caused by arsenic (As) and other toxic metals in groundwater, surface water and soils in the Bengal basin of Bangladesh have been studied. Altogether 10 groundwater, seven surface water and 31 soil samples were collected from arsenic-affected areas and analysed chemically. The geologic and anthropogenic sources of As and other toxic metals are discussed in this paper. The chemical results show that the mean As concentrations in groundwater in the Char Ruppur (0.253mg As L^–1), Rajarampur (1.955mg As L^–1) and Shamta areas (0.996mg As L^–1) greatly exceed the WHO recommended value, which is 0.01mg As L^–1. The concentrations of As in groundwater are very high compared to those in surface water and in surface soil in the three (As-affected) areas studied. This indicates that the source of As in groundwater could be bedrock. The relatively high concentrations of Cr, Cu, Ni, Pb and Zn in surface water, compared to world typical value, are due to the solubility of metal ions, organometalic complexes, coprecipitation or co-existance with the colloidal clay fraction. In the soil, the elevated concentrations of As, Cr, Cu, Ni, Pb and Zn are due to their strong affinity to organic matter, hydrous oxides of Fe and Mn, and clay minerals.     

Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.     

Rapid estimation of compost enzymatic activity by spectral analysis method combined with machine learning

The aim of this study was to investigate the feasibility of using visible near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) as an easy, inexpensive, and rapid method to predict compost enzymatic activity, which traditionally measured by fluorescein diacetate hydrolysis (FDA-HR) assay. Compost samples representative of five different compost facilities were scanned by DRS, and the raw reflectance spectra were preprocessed using seven spectral transformations for predicting compost FDA-HR with six multivariate algorithms. Although principal component analysis for all spectral pretreatments satisfactorily identified the clusters by compost types, it could not separate different FDA contents. Furthermore, the artificial neural network multilayer perceptron (residual prediction deviation = 3.2, validation r² = 0.91 and RMSE = 13.38 μg g^?1 h^?1) outperformed other multivariate models to capture the highly non-linear relationships between compost enzymatic activity and VisNIR reflectance spectra after Savitzky–Golay first derivative pretreatment. This work demonstrates the efficiency of VisNIR DRS for predicting compost enzymatic as well as microbial activity.     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

Prediction of total bed material load for rivers in Malaysia: A case study of Langat,Muda and Kurau Rivers

A soft computational technique is applied to predict sediment loads in three Malaysian rivers. The feed forward-back propagated (schemes) artificial neural network (ANNs) architecture is employed without any restriction to an extensive database compiled from measurements in Langat, Muda, Kurau different rivers. The ANN method demonstrated a superior performance compared to other traditional sediment-load methods. The coefficient of determination, 0.958 and the mean square error 0.0698 of the ANN method are higher than those of the traditional method. The performance of the ANN method demonstrates its predictive capability and the possibility of generalization of the modeling to nonlinear problems for river engineering applications.     

Indicator-Based Approach for Assessing the Vulnerability of Freshwater Resources in the Bagmati River Basin,Nepal

To assess the vulnerability of water resources in the Bagmati River Basin in Nepal, this paper adopts an indicator-based approach wherein vulnerability is expressed as a function of water stress and adaptive capacity. Water stress encompasses indicators of water resources variation, scarcity, and exploitation and water pollution, whereas adaptive capacity covers indicators of natural, physical, human resource, and economic capacities. Based on the evaluation of eleven indicators, which were aggregated into eight vulnerability parameters, an increasingly stressful situation and lack of adaptive capacity became evident. Considerable spatial variation in indicator values suggests differential policy options. While the northern parts need attention to reduce pollution loading and conserve vegetation cover, the southern parts need improvements in physical capacity, i.e. water infrastructures. The comprehensive and easily interpretable findings of the study are expected to help decision makers reach sound solutions to reduce freshwater resources vulnerability in the Bagmati River Basin, Nepal. With its inherent flexibility, the approach has demonstrated its potential for application in different times and areas for monitoring and comparison purposes.     

Environmental Kuznets Curve: the case of Bangladesh for waste emission and suspended particulate matter

Economists have shown the empirical relationships between the economic growth of a nation and its environmental quality using the hypothesis of the Environmental Kuznets Curve (EKC). To understand the EKC phenomena, a study of the literature was undertaken. As waste, waste emission, and suspended particulate matter (SPM) are the active agents of environmental degradation, the study focused on those agents for EKC consideration. Through understanding the different EKC trajectories, an attempt was made to relate the economic development of Bangladesh to the EKC. It is shown that the EKCs for waste, emissions from waste, and SPM follow the conventional EKC trajectory with a turning point related to higher income per capita in most cases. The type of economic policy that Bangladesh should follow to deal with the pollutants and their sources is also shown. The study recommends creating a tunnel in the EKC to lower the turning point in Bangladesh. The study is likely to help stimulate policy development in Bangladesh.     

Investigation of arsenic removal in batch wise water treatments by means of sequential hydride generation flow injection analysis

Arsenic water pollution is a big issue worldwide. Determination of inorganic arsenic in each oxidation state is important because As(III) is much more toxic than As(V). An automated arsenic measurement system was developed based on complete vaporization of As by a sequential procedure and collection/preconcentration of the vaporized AsH(3), which was subsequently measured by a flow analysis. The automated sensitive method was applied to monitoring As(III) and As(V) concentrations in contaminated water standing overnight. Behaviors of arsenics were investigated in different conditions, and unique time dependence profiles were obtained. For example, in the standing of anaerobic water samples, the As(III) concentration immediately began decreasing whereas dead time was observed in the removal of As(V). In normal groundwater conditions, most arsenic was removed from the water simply by standing overnight. To obtain more effective removal, the addition of oxidants and use of steel wools were investigated. Simple batch wise treatments of arsenic contaminated water were demonstrated, and detail of the transitional changes in As(III) and As(V) were investigated.     

Assessment of the sources of suspended particulate matter aerosol using US EPA PMF 3.0

The main purpose of this paper was to carry out a source apportionment of suspended particulate matter (SPM) samples using positive matrix factorization procedure. The central and local Government of Japan introduced strict emission regulations in 2002/10 and 2003/10, respectively, in curbing SPM pollution from major metropolitans. This paper also highlighted the impact of the measures taken by the central and local Government of Japan on the reduction of SPM and the contributions of sources. SPM samples were collected for 6 years starting from 1999 to 2005 at two sites, i.e., site A (urban) and site B (suburban) of Yokohama, Japan. Microwave digestion and inductively coupled plasma-mass spectroscopy (ICP-MS) were employed to measure Mg, Al, Ca, V, Cr, Mn, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Ag, Cd, Cs, Ba, Pb and Bi, while water soluble ions (Na⁺, NH₄  ⁺_{4}^{\ \,+}, K⁺, Ca^2 +, Mg^2 +, Cl⁻, NO₃  ^-_{3}^{\ \,-} and SO₄  ^2-)_{4}^{\ \,2-}) as well as carbonaceous mass (EC and OC) were analyzed using ion chromatograph and CHN analyzer, respectively. The sources identified at two sites were automobile, soil dust, marine aerosol, mixed sources, and secondarily formed aerosol. Also, source quantification was performed. Automobile and soil dust were striking contributors at site A. Automobile and soil dust of SPM aerosol might be produced from local origin at current study areas. Besides, Asian dust had an impact on high concentrations of SPM aerosol in some certain period of the year due to the outflows of East Asian emission. In contrast, secondary aerosol in the form of sulfate and ammonium as well as mixed sources (coal, long-transported Cs, and other unknown sources) were remarkable at site B. Stationary/industrial combustion has apparently more impact on the release of SPM components at site B than A. Automobile regulations in 2002 and 2003, respectively, resulted in reduction of SPM by 28% for site A and 16% for site B. There was also net reduction of automobile contribution at both sites due to the above measures being implemented.