Search results

Purpose – This paper aims to detect or identify the presence of hydrocarbon infiltration on sampling point in the Rambe River area according to the obtained VOCs and the adsorbed SVOCs.

Design/Methodology/Approach – The Gore-sorber method has been used to capture volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) as indicators of subsurface hydrocarbon generation and entrapment. This method is usually used in environmental surveys for the oil investigations in certain areas for surface survey screening, designed to collect a broad range of VOCs and (SVOCs) at lower concentrations, quickly and inexpensively. The results also indicated a general correlation between the GORE-SORBER and reference method data. The research was conducted in Rambe River Village, Tebing Tinggi sub-district of Tanjung Jabung Barat district, Jambi Province Indonesia. The collection of the Gore-Sorber modules were analyzed using a gas chromatography-mass spectrometer thermal desorption (GC/MS).

Findings – The results showed that from all sampling points in Tebing Tinggi areas, the dominant components detected are carbonyl sulphide, dimethyl sulfide, ethane, propane, butane, 2-methyl butane, pentane, and carbon sulfide with carbon chain in the range C2-C5. These hydrocarbon gases (C1-C4) which may be from thermogenic or microbial processes. The highest concentrations of carbonyl sulfide were 392.67 ng and dimethyl disulfide 261.90 ng.

Originality/Value – In addition to estimate and predict the petroleum formation, this article provides information about the presence of oil fields in the area of the Sungai Rambe Village

Improved nuclear reactor configurations that address major concerns of environmentalists and safety analysts are discussed. In addition to social acceptance, these new modes of power generation have economic potential to become the dominant producers of energy in the twenty‐first century. The class of power generation with this promise is the high temperature gas reactor (HTGR); the variant we focus on is the pebble‐bed modular reactor (PBMR). We also focus on using nuclear power as an energy source for desalinating seawater. Finally, the case is made that HTGR reactors are ideal for supplying the high‐temperature heat needed for manufacturing molecular hydrogen, a leading candidate for clean fuel consumption. These three themes are developed in a broad context with the objective of recommending policy actions dealing with global warming, public health, and economic opportunity.

The purpose of this study is to investigate forecast models using data provided by the Texas Commission on Environmental Quality (TCEQ) to monitor and develop forecast models for air quality management.

The models used in this research are the LDF (Fisher Linear Discriminant Function), QDF (Quadratic Discriminant Function), REGF (Regression Function), BPNN (Backprop Neural Network), and the RBFN (Radial Basis Function Network). The data used for model evaluations span a 12‐year period from 1990 to 2002. A control chart of the data is also examined for possible shifts in the distribution of ozone present in the Houston atmosphere during this time period.

Results of this research reveal variables that are significantly related to the ozone problem in the Houston area.

Models developed in this paper may assist air quality managers in modeling and forecasting ozone formations using meteorological variables.

This is the first study that has extensively compared the efficiency of LDF, QDF, REGF, BPNN and RBFN forecast models used for tracking air quality. Prior studies have evaluated Neural Networks, ARIMA and regression models.

Describes the three main methods of used oil recycling. Details the laundering process carried out by Smallman Lubricants and the subsequent quality tests. Refers to environmental and health aspects. Mentions three other reprocessing technologies.

This study attempts to formulate a conceptual and operational model that encapsulates the highlights of scientific sustainability research and that identifies the critical success factors of sustainable development from the perspective of different stakeholder groups. It seeks to identify viable consensus pathways in sustainable development strategies that are marked by conflicts among different stakeholders. To do so, this study focuses on three case studies that are part of the EU project SMILE, its way of sustainability thinking, and its stakeholders to encapsulate different sustainability approaches and different needs for sustainable development. To identify critical success/failure factors in the search for sustainable development at the interface of economic, environmental, and social factors, we use interview results, first, to compose case study–specific pentagon models. These models offer a systematic framework for sustainability and, in general, distinguish between five key forces, that is, software (e.g., knowledge), hardware (e.g., research facilities), finware (e.g., financial support), ecoware (e.g., environmental amenities), and orgware (e.g., institutional support systems). In a second step, we use both the questionnaire results and a multi-criteria spider approach to quantify the relative importance of the pentagon factors for each stakeholder group. This way we are able to develop stakeholder-specific pentagon models. Although there are many applications of the basic pentagon model in the sustainability literature, our attempt can be seen as the first one that combines cases at different time and spatial scales to generalize the interfaces between scientific research and policy arenas.