Measuring the association of environmental,corporate, financial,and social CSR: evidence from fuzzy TOPSIS nexus in emerging economies

Environmental Science and Pollution Research - The purpose of this research is to measure the combing impact of corporate social responsibility on company performance and to conduct a comparative...     

A robust method for collecting and processing the on-road instantaneous data of fuel consumption and speed for motorcycles

ABSTRACT

Using the laboratory-based fuel consumption models for predicting real-world fuel consumption requires the measurement of data under certain conditions to obtain high accuracy of predicted result. Therefore, it is necessary to develop a logging device for measuring the real-time fuel consumption and speed of vehicle on the road. This article presents a study on developing the on-board data logging device to collect real-world data of fuel consumption and speed for motorcycles with the update rate of 1 Hz. The instantaneous speed of the motorcycle was determined based on the rotational speed of the wheel and the wheel radius. Another module was used to determine the instantaneous fuel consumption rate (FR) though measuring the duration injection pulse. The relationship between the duration injection pulse and the injected amount of fuel was established with high correlation coefficient of 0.997. In addition, a filter was designed to remove noise in the dataset collected using the data logging device. The random errors in the speed and the FR profiles were detected and replaced, the percentage of these errors is 1.8% and 2.4%, respectively. The developed method is a precise one for transient fuel consumption and speed measurement. In chassis dynamometer test, the average deviation between steady speed measured by the chassis and the data logging device is only approximately 0.35%. At transient state, the biggest deviation between these two datasets is less than 3.5%. The average FR at steady speed measured by the developed method is slightly different from the one measured by the carbon balance method. The difference is 0.9%, 2.5%, and 0.25% at the speeds of 30 km/h, 50 km/h, and 70 km/h, respectively. Following the transient test cycle, the fuel consumption measured by the developed method is 4.35% lower than that determined by the carbon balance method.

Implications: A robust method for collecting and processing the on-road instantaneous data of fuel consumption and speed was developed for motorcycles. The proposed method can record well the real-world driving data for motorcycles, including the fuel consumption and speed, with the update rate of 1 Hz. The filter was designed to minimize noise while maintaining data integrity of the collected dataset, the percentage of errors in the the speed and the FR profiles is 1.8% and 2.4%, respectively. The proposed method, therefore, can be used as effective tools for future studies relating to the fuel consumption and emission of motorcycles on the road.     

Application of soft computing to predict water quality in wetland

Prediction of water quality is a critical issue because of its significant impact on human and ecosystem health. This research aims to predict water quality index (WQI) for the free surface wetland using three soft computing techniques namely, adaptive neuro-fuzzy system (ANFIS), artificial neural networks (ANNs), and group method of data handling (GMDH). Seventeen wetland points for a period of 14 months were considered for monitoring water quality parameters including conductivity, suspended solid (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO), temperature, pH, phosphate nitrite, and nitrate. The sensitivity analysis performed by ANFIS indicates that the significant parameters to predict WQI are pH, COD, AN, and SS. The results indicated that ANFIS with Nash-Sutcliffe Efficiency (NSE = 0.9634) and mean absolute error (MAE = 0.0219) has better performance to predict the WQI comparing with ANNs (NSE = 0.9617 and MAE = 0.0222) and GMDH (NSE = 0.9594 and MAE = 0.0245) models. However, ANNs provided a comparable prediction and the GMDH can be considered as a technique with an acceptable prediction for practical purposes. The findings of this study could be used as an effective reference for policy makers in the field of water resource management. Decreasing variables, reduction of running time, and high speed of these approaches are the most important reasons to employ them in any aquatic environment worldwide.

     

Assessing and selecting interventions for river water quality improvement within the context of population growth and urbanization: a case study of the Cau River basin in Vietnam

In this study, a multi-criteria methodology is proposed to identify and prioritize interventions for water quality improvement with the aid of computer simulation models. The methodology can be used to elaborate and compare future socio-economic development scenarios to select the best interventions based on three criteria: (1) ideas of experts and stakeholders about the importance of scenarios, (2) impacts of each scenario on surface water quality in watershed, and (3) benefit–cost analysis for each scenario. A score is computed for each scenario based on a weighted sum technique which enables to take into consideration different level of importance for the three criteria. The methodology is applied to Cau River basin in Vietnam, with the aid of a computer tool, to assess interventions for river water quality improvement within the context of population growth and urbanization. The results show that fast future population growth in upstream has significant impacts. In 2020, an increase of 116 % of the population in Bac Kan town can lead to an increase of 120 and 135 % in BOD₅ and NH₄ ⁺ median concentrations, respectively, with the implementation of a treatment plant for 10,000 people in Bac Kan town. Therefore, the increase of the domestic wastewater treatment plant’s capacity in Bac Kan town, at least twice as the projection of local government, is necessary. These results will help decision makers to select the best interventions for Cau River basin management.     

Impact of simulated acid rain on the growth of three species Brassica integrifolia,Brassica rapa,Brassica juncea in Hanoi,Vietnam

Environmental Science and Pollution Research - Over the past decade, the extent and magnitude of acid rain in Vietnam and other Asian countries have become more apparent. In this study, the effect...     

Main and added effects of heatwaves on hospitalizations for mental and behavioral disorders in a tropical megacity of Vietnam

Environmental Science and Pollution Research - Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves...     

Effects of introducing energy recovery processes to the municipal solid waste management system in Ulaanbaatar, Mongolia

Currently, most developing countries have not set up municipal solid waste management systemswith a viewof recovering energy fromwaste or reducing greenhouse gasemissions. In this article, we have studied the possible effects of introducing three energy recovery processes either as a single or combination approach, refuse derived fuel production, incineration and waste power generation, and methane gas recovery from landfill and power generation in Ulaanbaatar, Mongolia, as a case study. We concluded that incineration process is the most suitable as first introduction of energy recovery. To operate it efficiently, 3Rs strategies need to be promoted. And then, RDF production which is made of waste papers and plastics in high level of sortingmay be considered as the second step of energy recovery. However, safety control and marketability of RDF will be required at that moment.