Application of WRF-Chem to simulate air quality over Northern Vietnam

Environmental Science and Pollution Research - The WRF-Chem (Weather Research and Forecasting with Chemistry) model is implemented and validated against ground-based observations for meteorological...     

A state-of-the-art review on emission characteristics of SI and CI engines fueled with 2,5-dimethylfuran biofuel

Environmental Science and Pollution Research - Currently, the considerable decline in fossil fuel resources and the high rise in vehicle emissions have prompted researchers and governments to...     

Toward environmental sustainability: how do urbanization,economic growth,and industrialization affect biocapacity in Brazil?

The South American country Brazil is one of the richest countries in terms of natural resources, representing 14 percent of the world’s total biocapacity. However, the biocapacity (biosphere’s ability to generate resources and sequester waste) per capita in Brazil has shown a massive decline over the last five decades, while economic growth and urbanization have rapidly increased for the same period. Brazil is one of the largest creditors of biocapacity to the world, and biocapacity loss in Brazil can lead to devastating environmental consequences. Therefore, this work empirically investigates the influence of urbanization, economic growth, and industrialization on biocapacity controlling human capital from 1961 to 2016 in Brazil. The Bayer and Hack cointegration test, the Autoregressive Distributed Lag (ARDL) technique, and Hacker and Hatemi-J (J Econ Stud 39:144–160, 2012) causality tests are employed. The findings unfolded a U-shaped relationship between economic growth and biocapacity, evidencing that economic growth reduces biocapacity, but after achieving a threshold level, it promotes biocapacity. Urbanization has a negative relationship with biocapacity per capita, indicating that urbanization is a significant driver of the biocapacity loss in Brazil. Further, urbanization and economic growth Granger cause biocapacity. Lastly, relevant policy implications are proposed to overcome the reduction in biocapacity.

     

Accuracy improvement of various short-term load forecasting models by a novel and unified statistical data-filtering method

ABSTRACT

Time-series and machine-learning methods are being strongly exploited to improve the accuracy of short-term load forecasting (STLF) results. In developing countries, power consumption behaviors could be suddenly changed by different customers, e.g. industrial customers, residential customers, so the load-demand dataset is often unstable. Therefore, reliability assessment of the load-demand dataset is obviously necessary for STLF models. Hence, this paper proposes a novel and unified statistical data-filtering method with the best confidence interval to eliminate unexpected noises/outliers of the input dataset before performing various short-term load forecasting models. This proposed novel data-filtering method, so-called the data pre-processing method, is also compared to other existing data-filtering methods (e.g. Kalman filter, Density-Based Spatial Clustering of Applications with Noise, Wavelet transform, and Singular Spectrum Analysis). By using an SCADA system?-based database of a typical 22kV distribution network in Vietnam, NYISO database, and PJM-RTO database, case studies of short-term load forecasting have been conducted with a conventional ARIMA model, an ANN forecasting model, an LSTM-RNN model, an LSTM-CNN combined model, a deep auto-encoder (DAE) network, a Wavenet-based model, a Wavenet and LSTM hybrid model, and a Wavelet Neural Network (WNN) model, which are to validate the novel and unified statistical data-filtering method proposed. The achieved numerical results demonstrate which the accuracy of the aforementioned STLF models can be significantly improved due to the proposed statistical data-filtering method with the best confidence interval of the input load dataset. The proposed statistical data-filtering method can considerably outperform the existing data-filtering methods.     

Extraction,chemical compositions,and cytotoxic activities of essential oils of Thevetia peruviana

Abstract

In this study, The essential oil of flowers, fruits, and leaves of Thevetia peruviana, which were collected in Vietnam, were being reported for the first time. The essential oil of flowers was extracted by different methods: n-hexane extraction, distillation water, and supercritical CO₂ extraction. The compositions of essential oil of different parts of Thevetia peruviana were analyzed by GC-FID and GC/MS systems. Major chemical compositions of essential oil were identified as monoterpenes, sesquiterpenes, terpenoids, and sterol. The activities of total essential oil extracts of the Thevetia peruviana exhibit inhibitory activities against five cancer cell lines.     

Influencing factors on sustainable development: a case study in Quang Tri province,Vietnam

Background Sustainable development (SD) is a common concept. Knowledge and attitudes are essential in the SD process. This study assesses the knowledge, attitudes, and practices (KAP) of local people about SD. Aim To study the factors that influence the understanding of the concept, contents, and indicators of different aspects affecting the health and environmental issues. Methods A cross-sectional study was carried out from June to July 2007 among 546 households in the Quang Tri province. Data were gathered on basis of socio-demographic variables, namely age, gender, education, occupation, income, and region. Chi square tests and multivariate analysis were performed on the obtained data. The data were cleaned and analysed using SPSS 15.0 for windows. Results Occupation is related to knowledge, attitude, or practice. Income is related to knowledge or practice. Gender related to only attitude. Lastly, region is related to attitude or practice. The proportion of wrong understanding about SD is 2.0 times (95% CI: 1.3; 3.1, p < 0.001) higher than that of the people who have good understanding about it. The rate of willingness to do any related SD programmes of the people who understanding is 2.1 times (95% CI: 1.4; 3.2, p < 0.001) higher than that of the people who have bad one. Conclusions This study shows that knowledge on sustainability of the local communities is low. Occupation and income influence understanding of SD more than region, age, gender, and education. Most of the local people who do not understand SD in general, do not want to participate or act in SD programmes.     

Complex hydrochemical characteristics of the Middle–Upper Pleistocene aquifer in Soc Trang Province,Southern Vietnam

Environmental Geochemistry and Health - Environmental isotope techniques were applied to study the hydrochemical characteristics of groundwater in Soc Trang Province, Southern Vietnam, in frame of...     

Modeling of partial nitrification and denitrification in an SBR for leachate treatment without carbon addition

A process of partial nitrification and denitrification in a sequencing batch reactor (SBR) treating leachate was simulated by applying a modified version of activated sludge model no. 3 (ASM3), named ASM3_2step. This model modifies the ASM3 model by separating nitrification and denitrification into two steps with nitrite as an intermediate substrate. Three periods, including long term period, steady state and cycle evolution, were used for calibration. Three main processes were observed, including biomass production, nitrification (focusing on nitrite accumulation) and denitrification. The kinetic and stoichiometric parameters ( m_{\textA_NH} \mu_{{{\text{A\_NH}}}} , Y_{\textA_NH} Y_{{{\text{A\_NH}}}} , Y_{\textA_\textNO2} Y_{{{\text{A}}\_{\text{NO}}_{2} }} , Y_{\textH_\textO2} Y_{{{\text{H}}\_{\text{O}}_{2} }} , b _A, K_{\textA_NH} K_{{{\text{A\_NH}}}} ), were determined from biokinetic and respirometry tests. Some of the default values of kinetic and stoichiometric parameters available in the ASM3 model and in the literature were kept constant, while some others were adjusted step by step until observed state variables fit with experimental data. The maximum specific growth rate of nitrite oxidizing bacteria (0.108 day⁻¹) (simulated by the model) and that of ammonium oxidizing bacteria (0.61 day⁻¹) (from biokinetic tests) are the parameters which have the highest influence on the nitrite accumulation, even more than oxygen supply intensity or Kla value. Other important parameters were K_{\textAO_NH} K_{{{\text{AO\_NH}}}} and K_{\textAO_\textNO2} K_{{{\text{AO}}\_{\text{NO}}_{2} }} , calibrated at the values of 1.37 and 1.59 mg O₂/L, respectively. The modified model and values of the kinetic and stoichiometric parameters obtained from the modeling process will be used for optimization of the partial nitrification in the next study.     

Industrial transformation and shrimp aquaculture in Thailand and Vietnam: pathways to ecological,social, and economic sustainability?

Shrimp aquaculture in Vietnam is in the process of being transformed into a major industry around the intensification of the production system. The experiences of other countries in the region, especially in Thailand where high input production systems dominate, suggests that now is a critical time for intervention to redirect industry into pathways that are more sustainable ecologically, socially, and economically. In Thailand, years of experience with intensified systems and a complex industrial organization has not led to sustainable solutions. The challenge here is for society to regain control and then to redirect the transformation along more efficient and benign pathways. Our analyses suggest that current pathways in both countries are unlikely to lead to a sustainable industry. A complete transformation of the way shrimp are grown, fed, processed, distributed, and regulated is needed.