Physicochemical properties associated with the presence of <Emphasis Type="Italic">Burkholderia pseudomallei</Emphasis> in small ruminant farm water supplies in Peninsular Malaysia

Burkholderia pseudomallei causes melioidosis, a life-threatening infection in both humans and animals. Water is an important reservoir of the bacteria and may serve as a source of environmental contamination leading to infection. B. pseudomallei has an unusual ability to survive in water for a long period. This paper investigates physicochemical properties of water associated with the presence of B. pseudomallei in water supply in small ruminant farms in Peninsular Malaysia. Physicochemical properties of water samples taken from small ruminant farms that included temperature, pH, dissolved oxygen (DO₂), optical density (OD), and chemical oxygen demand (COD) were measured after which the samples were cultured for B. pseudomallei. Multivariable logistic regression model revealed that slightly acidic water pH and higher COD level were significantly associated with the likelihood of the B. pseudomallei presence in the water.     

Effect of different biochars amendment on soil biological indicators in a calcareous soil

Environmental Science and Pollution Research - Previous studies suggest that biochar has potential to benefit soil when used as an amendment, but only few studies have investigated how the...     

Empirical gas emission and oxidation measurement at cover soil of dumping site: example from Malaysia

Methane (CH₄) is one of the most relevant greenhouse gases and it has a global warming potential 25 times greater than that of carbon dioxide (CO₂), risking human health and the environment. Microbial CH₄ oxidation in landfill cover soils may constitute a means of controlling CH₄ emissions. The study was intended to quantify CH₄ and CO₂ emissions rates at the Sungai Sedu open dumping landfill during the dry season, characterize their spatial and temporal variations, and measure the CH₄ oxidation associated with the landfill cover soil using a homemade static flux chamber. Concentrations of the gases were analyzed by a Micro-GC CP-4900. Two methods, kriging values and inverse distance weighting (IDW), were found almost identical. The findings of the proposed method show that the ratio of CH₄ to CO₂ emissions was 25.4 %, indicating higher CO₂ emissions than CH₄ emissions. Also, the average CH₄ oxidation in the landfill cover soil was 52.5 %. The CH₄ and CO₂ emissions did not show fixed-pattern temporal variation based on daytime measurements. Statistically, a negative relationship was found between CH₄ emissions and oxidation (R ²?=?0.46). It can be concluded that the variation in the CH₄ oxidation was mainly attributed to the properties of the landfill cover soil.     

The effectiveness of digital soil mapping to predict soil properties over low-relief areas

This study investigates the ability of different digital soil mapping (DSM) approaches to predict some of physical and chemical topsoil properties in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province, Iran. According to a semi-detailed soil survey, 120 soil samples were collected from 0 to 30 cm depth with approximate distance of 750 m. Particle size distribution, coarse fragments (CFs), electrical conductivity (EC), pH, organic carbon (OC), and calcium carbonate equivalent (CCE) were determined. Four machine learning techniques, namely, artificial neural networks (ANNs), boosted regression tree (BRT), generalized linear model (GLM), and multiple linear regression (MLR), were used to identify the relationship between soil properties and auxiliary information (terrain attributes, remote sensing indices, geology map, existing soil map, and geomorphology map). Root-mean-square error (RMSE) and mean error (ME) were considered to determine the performance of the models. Among the studied models, GLM showed the highest performance to predict pH, EC, clay, silt, sand, and CCE, whereas the best model is not necessarily able to make accurate estimation. According to RMSE%, DSM has a good efficiency to predict soil properties with low and moderate variabilities. Terrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas.     

Study of MoO3-γAl2O3 catalysts behavior in selective catalytic reduction of SO2 toxic gas to sulfur with CH4

Environmental Science and Pollution Research - In the present study, a detailed investigation was carried out on MoO3 alumina-supported catalysts behavior in selective catalytic reduction of SO2 to...     

Wheat productivity responses in the rice-based system under different no-till techniques and nitrogen sources

Environmental Science and Pollution Research - No-till wheat is gaining popularity in rice-based cropping system as it provides a better chance for timely planting of wheat, management of crop...     

Wind Tunnel Simulation of Neutral Atmospheric Surface Layers by the Counter-Jet Technique

A new technique to generate thick turbulent boundary layers In relatively short distances, which is capable of modifying and controlling rapidly the mean and unsteady profiles of the simulated layers, is presented. The increased thickness is achieved in the "I.IT. Environmental Wind Tunnel" by providing large momentum defects at the wall through upstream oriented, spanwise discrete wall jets, with changeable jet velocities and controllable jet angles. Various mean velocity profiles of the boundary layer (which can be represented by a wide range of power law exponents) are obtained at the same streamwise position using different settings of the counter-jet parameters and different types of artificial surface roughness. The transverse uniformity of these layers is also documented. Selected measurements of the flow field in the vicinity of a "building" model tested in three surface layers are compared in order to examine the sensitivity of measured effects to changes in the surface layer characteristics. Viewing the flow field with the aid of the modular flow concept, changes in the wake of the "building," in the flow above its roof and in the shear layer spreading downstream from its top are recorded through profiles of mean velocity and turbulence intensity. The effect of the wind direction with respect to the model is also investigated.     

Forecasting Daily Maximum Surface Ozone Concentrations in Brunei Darussalam—An ARIMA Modeling Approach

Abstract

A time series approach using autoregressive integrated moving average (ARIMA) modeling has been used in this study to obtain maximum daily surface ozone (O₃) concentration forecasts. The order of the fitted ARIMA model is found to be (1,0,1) for the surface O₃ data collected at the airport in Brunei Darussalam during the period July 1998-March 1999. The model forecasts of one-day-ahead maximum O₃ concentrations have been found to be reasonably close to the observed concentrations. The model performance has been evaluated on the basis of certain commonly used statistical measures. The overall model performance is found to be quite satisfactory as indicated by the values of Fractional Bias, Normalized Mean Square Error, and Mean Absolute Percentage Error as 0.025, 0.02, and 13.14% respectively.