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Polychlorinated biphenyl (PCBs) are persistent organic compounds used between 1930 and 1970 as thermal insulators in electrical equipment such as transformers, electrical condensers, heat exchangers, and hydraulic systems. Currently, this xenobiotic is a potential source of pollution to soil and water resources. This research aimed to isolate and characterize bacteria strains possessing a high potential to degrade PCBs contained in used dielectric oils. The bacteria strains were isolated from a soil sample taken from “Alao” Hydroelectric Power Center. Four culture media were used for the soil sample culturing: Agar for Standard Methods Medium (STD), Phosphorus, Ammonium, and Salts Medium (PAS), Minimum Medium (Mm), and Minimum Medium (Mm) supplemented with 25 µL of oil contaminated with 43,6 ppm of PCBs. The isolation, screening, and stabilization process were carried out using three culture media: STD, PAS, and Mm, each supplemented with 25 µL of oil contaminated with 43,6 ppm of PCBs. Nineteen bacterial colonies were isolated and exposed to a higher concentration of PCBs. Eighteen colonies could tolerate 250 µL of oil contaminated with 500 ppm of PCBs. Once stabilized and purified these bacteria strains, were characterized according to their microscopic and macroscopic characteristics and tolerance to heavy metals. Through biochemical tests, 18 strains were identified belonging to Providencia alcalifaciens, Proteus mirabillis, Providencia rettgeri, Providencia stuartii, Pseudomona alcaligenes, Morganella morganii, and Shigella disenteriae

The Global Positioning System (GPS) is satellite-based, with receiving equipment worldwide utilizing geographic positioning satellites in Earth orbit. The system is unaffected by the radio positioning system, so it provides highly accurate three-dimensional positioning, velocity, and time data to users. In this paper, Alishan Township, Chiayi County, central Taiwan, is selected to test an automatic real-time monitoring system comprising of one machine with multiple GPS antennas. To this end, the Alishan Public Works Section installed advanced measuring instruments and a landslide-monitoring system composed of a high-efficiency transmission system. A pre- and post-rainfall data survey was conducted on this slope section. Together with the rainfall records, real-time ground-slip monitoring data was collected, and subsequently analyzed to understand the disaster situation and ground slip characteristics of the Alishan Highway following an earthquake (1998). In the future, more effective management values will be set to reduce the loss of slope disasters to conserve land and public safety. For the first time in Taiwan, this paper presents displacement data indicating that after the typhoon rains, a maximum surface movement velocity of 2.5 cm every six days is attained, while the total displacement per month is as high as 10 cm. These data can be used as for the remediation of this section of the Alishan Highway.

The photocatalytic activity of the ZnO NRs/CuO composite film was investigated by using both experimental and numerical methods. The ZnO NRs/CuO composite film exhibits significantly enlarge absorption range to visible-light and suppress the recombination rate of the photogenerated electron-hole pairs, which can be well utilized as a photocatalyst. The ZnO NRs/CuO composite film also presents good stability, and reusability, and durability for photo-decomposition purpose. The optimal ZnO NRs/CuO composite film contains 1μ-thick of CuO film and 10 nm-thick of ZnO NRs film. The donor concentration in ZnO NRs film should be lower than 1016 cm−3. The short circuit current density of the optimal composite film is 25.8 mA/cm2 resulting in the calculated pseudo-order rate constant of 1.85 s−1. The enhancement in degradation efficiency of this composite film is attributed to the inner electric field and large effective surface area of ZnO NRs film.

This study evaluates droughts in the Mekong River Basin (MKB) based on a multidisciplinary method, mainly using the Standardized Precipitation Index (SPI) and Mann–Kendall (MK) test. Precipitation data corresponding to the seasonality of the regional climate were retrieved from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement from 2001 to 2020, at a monthly temporal scale and 0.1 degree spatial resolution. Drought events and their average interval, duration, and severity were determined based on Run theory. Our results revealed the most extreme drought period was in January 2014, at the time the lowest precipitation occurred. Spatial extreme drought results indicated that Zone 2 in the upstream MKB has the highest frequency of drought, with 44 events observed during 19 years, and experiences the most severe droughts, whereas Zone 24 in the downstream MKB has the most prolonged drought duration of seven months. The periods and locations of extreme drought were identified using the SPI, corresponding to historic droughts of the MKB. Furthermore, the MK test shows an increasing trend of droughts in the lower MKB and the cluster analysis identified six clusters of times series. Overall, our study provides essential findings for international and national water resource stakeholders in identifying trends of extreme drought in the MKB.

Ban Khoang is a mountainous commune in Sa Pa district located in the central part of Lao Cai province, Vietnam. Landslides occur frequently in this area and seriously affect the local living conditions. To help the local authority in developing a landslide disaster action plan, the statistical index method for landslide susceptibility mapping is applied. As the result, the landslide susceptibility zonation (LSZ) map was created. The LSZ map indicates that areas of low, moderate, high and very high landslide susceptibility zones are, respectively, 20.3 km2, 12.4 km2, 15.4 km2, and 5.2 km2; most of the observed landslide areas that are well predicted belong to high or very high landslide susceptibility classes. In detail, 80% observed landslide areas and 78.57% number of observed landslides were well predicted, and the area (AUC) under the receiver operating characteristic (ROC) curve obtained 80.3%. Hence, the high and very high landslide susceptibility classes in the LSZ map can be considered highly believable, and the LSZ map will be reliable to use in the practice.

This paper investigates a novel hybrid model that employs Henry’s gas solubility optimization algorithm to search for adaptive weights of a deep neural network for a landslide susceptibility application. The model is trained using 13 features from a case study site in Viet Nam, including topographically derived data, satellite-derived indexes, physical and climatic information. The training and validating process terminated with the Root mean square error = 0.3898, Mean absolute error = 0.3115, Area under Receiving characteristic curves = 0.862, and Overall accuracy = 0.7831. The results show that the proposed model outperforms other methods, and it was used to map the susceptible level of the entire study area. Therefore, this model can be used as an alternative method for similar landslide studies and other natural hazard analyses, given input data availability.

The Linbeiken area is located in the village of Pingding, Taiwan. Since the Mindulle and Aere Typhoons in 2004, and as a result of the landslide triggered by the continuous heavy rainfall on 9 June 2006, there has been a persistent collapse of side slopes in the area. This paper describes the equipment that was installed to collect on-site topographic and hydrological information in the Linbeiken area upstream of the Pingding River and to monitor changes in the landslide area, as well as the measurements that were collected during the 2008 Typhoon Sinlaku. A case study of a landslide in Pingding, Taiwan was used to monitor the accurate coordinate changes in the potential landslide areas during typhoons. The goal of this study was to establish warning indexes, and to strengthen the software and hardware at the local disaster response center in the hope of gaining a full idea of the surface movement in landslide areas in future flood seasons. This is important for boosting the preparedness to adapt to landslide hazards, for improving disaster warnings, and for reporting efficiently to better protect the lives and property of local residents. The results show that the landslide disaster monitoring and warning system in Taiwan, as applied during Typhoon Sinlaku in 2008, is both effective and comprehensive.

Forest fires constitute a major environmental problem in tropical countries, especially in the context of climate change and increasing human populations. This paper aims to identify the causes of frequent forest fires in Son La Province, a fire-prone and forested mountainous region in northwest Vietnam, with a view to constructing a forest fire-related database with multiple layers of natural, social and economic information, extracted largely on the basis of Landsat 7 images. The assessment followed an expert systems approach, applying multi-criteria analysis (MCA) with an analytical hierarchy process (AHP) to determine the weights of the individual parameters related to forest fires. A multi-indicator function with nine parameters was constructed to establish a forest fire risk map at a scale of 1:100,000 for use at the provincial level. The results were verified through regression analysis, yielding R2 = 0.86. A real-time early warning system for forest fire areas has been developed for practical use by the relevant government authorities to provide more effective forest fire prevention planning for Son La Province.

Traffic speed forecasting in the short term is one of the most critical parts of any intelligent transportation system (ITS). Accurate speed forecasting can support travelers’ route choices, traffic guidance, and traffic control. This study proposes a deep learning approach using long short-term memory (LSTM) network with tuning hyper-parameters to forecast short-term traffic speed on an arterial parallel multi-lane road in a developing country such as Vietnam. The challenge of mishandling the location data of vehicles on small and adjacent multi-lane roads will be addressed in this study. To test the accuracy of the proposed forecasting model, its application is illustrated using historical voyage GPS-monitored data on the Le Hong Phong urban arterial road in Haiphong city of Vietnam. The results indicate that in comparison with other models (e.g., traditional models and convolutional neural network), the best performance in terms of root mean square error (RMSE), mean absolute error (MAE), and median absolute error (MDAE) is obtained by using the proposed model.

Climate change has been impacting strongly on economic sectors, facilities, people and wealth. Developing sustainable disaster prevention and mitigation technologies in the context of climate change is a long-term and urgent task of all levels, sectors and localities. Based on the analysis of scientific findings on the evolution of some major climatic factors (temperature and rainfall), sea level rise and the impact of these factors on the sectors of the sector Quang Ninh Tourism. At the same time, assessing the impact of climate change on all sectors, form the basis for new proposals for high-tech applications. Keywords Climate change; Disaster; Disaster prevention; Disaster mitigation; Quang Ninh; Quang Ninh flooding DOI: https://doi.org/10.23953/cloud.ijarsg.373

TiO2 nanocrystal doped with Cu has been fabricated by wet chemical processing. The obtained results of x-ray diffraction, optical absorption in the UV–Vis bands and luminescence spectra have shown that Cu has substituted Ti in the structure of TiO2 anatase phase when the Cu concentration is about 8 at%. In the case of larger Cu concentrations the copper oxide appeared and increased with increasing Cu concentration. The samples doped with Cu strongly absorb the visible light (400–900 nm) and their absorption edge shifts to the longer wavelength in dependence on the Cu concentration. The absorption in the visible light band is attributed to transitions between the impurities levels of Cu created in the energy band gap of TiO2. In addition, an absorption shoulder above 800 nm is observed and supposed to be related with the absorption of CuO. The experimental results prove that the TiO2 anatase doped with Cu is suitable for hydrogen generation by photocatalytic water splitting under sunlight.