Characterization and prediction of meandering channel migration in the GIS environment: A case study of the Sabine River in the USA

This study focused on the prediction of a 22 km meandering channel migration of the Sabine River between the states of Texas and Louisiana. The meander characteristics of 12 bends, identified from seven orthophotos taken between 1974 and 2004, were acquired in a GIS environment. Based on that earlier years' data acquisition, channel prediction was performed for the two years 1996 and 2004 using least squares estimation and linear extrapolations, yielding a satisfactory agreement with the observations (the median predicted and observed migration rates were 3.1 and 3.6 [m/year], respectively). The best-predicted migration rate was found to be associated with the longest orthophoto-recorded interval. The study confirmed that channel migration is strongly correlated with bend curvature and that the maximum migration rate of the bend corresponded to a radius of curvature [bend radius (R(C))/channel width (W(C))] of 2.5. In tight bends of a smaller radius of curvature than 1.6, secondary flow scouring near the bend apex increases bend curvature. The stability index of the dimensionless bend radius was determined to be 2.45. Overall, this study proves the effectiveness of least squares estimation with historical orthophotography for characterization of meandering channel migration.     

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.     

Assessing Health Benefits of Controlling Air Pollution from Power Generation: The Case of a Lignite-Fired Power Plant in Thailand

The impact pathway approach (IPA) is used to estimate quantitatively the level of health effects caused by particulate matter (PM₁₀) and sulfur dioxide (SO₂) emission from a lignite-fired power plant located in the Mae Moh area in northern region of Thailand. Health benefits are then assessed by comparing the levels of estimated health impacts without and with the installation of the flue gas desulfurization (FGD) equipment. The US EPA industrial source complex model is used to model air pollution dispersion at the local scale, and the sector average limited mixing meso-scale model is used to model air pollution transport at the regional scale. The quantification of the health end points in physical terms is carried out using the dose–response functions established recently for the population in Bangkok, Thailand. Monetarization of these effects is based on the benefit transfer method with appropriate adjustment. Finally, it has been found that the installation of the FGD to control SO₂ emission at Mae Moh significantly reduces adverse health effects not only on the population living near the power plant but also all over the country. A FGD unit installed at the 300-MW power unit can result, on average, in 16 fewer cases of acute mortality, 12 fewer cases of respiratory and cardiac hospital admissions, and almost 354,000 fewer days with acute respiratory symptoms annually. In monetary terms this benefit is equivalent to US $18.2 million (1995 prices) per annum. This benefit is much higher than the annualized investment and operation costs of FGD (US $7.4 million/yr).     

Gaseous nitrous acid (HONO) and nitrogen oxides (NOx) emission from gasoline and diesel vehicles under real-world driving test cycles

Reactive nitrogen species emission from the exhausts of gasoline and diesel vehicles, including nitrogen oxides (NO_x) and nitrous acid (HONO), contributes as a significant source of photochemical oxidant precursors in the ambient air. Multiple laboratory and on-road exhaust measurements have been performed to estimate the NO_x emission factors from various vehicles and their contribution to atmospheric pollution. Meanwhile, HONO emission from vehicle exhaust has been under-measured despite the fact that HONO can contribute up to 60% of the total hydroxyl budget during daytime and its formation pathway is not fully understood. A profound traffic-induced HONO to NO_x ratio of 0.8%, established by Kurtenbach et al. since 2001, has been widely applied in various simulation studies and possibly linked to under-estimation of HONO mixing ratios and OH radical budget in the morning. The HONO/NO_x ratios from direct traffic emission have become debatable when it lacks measurements for direct HONO emission from vehicles upon the fast-changing emission reduction technology. Several recent studies have reported updated values for this ratio. This study has reported the measurement of HONO and NO_x emission as well as the estimation of exhaust-induced HONO/NO_x ratios from gasoline and diesel vehicles using different chassis dynamometer tests under various real-world driving cycles. For the tested gasoline vehicle, which was equipped with three-way catalyst after-treatment device, HONO/NO_x ratios ranged from 0 to 0.95 % with very low average HONO concentrations. For the tested diesel vehicle equipped with diesel particulate active reduction device, HONO/NO_x ratios varied from 0.16 to 1.00 %. The HONO/NO_x ratios in diesel exhaust were inversely proportional to the average speeds of the tested vehicles.

Implications: Photolysis of HONO is a dominant source of morning OH radicals. Conventional traffic-induced HONO/NO_x ratio of 0.8% has possibly linked to underestimation of the total HONO budget and consequently underestimation of OH radical budget. The recently reported HONO/NO_x ratio of ~1.6% was used to stimulate HONO emission, which resulted in increased HONO concentrations during morning peak hours and its impact of 14% OH increment in the morning. However, the results were still lower than the measured concentrations. More studies should be conducted to establish an updated traffic-induced HONO/NO_x ratio.     

Partition of heavy metals in a tropical river system impacted by municipal waste

A research program was established to identify the governing factors for the partition coefficient (K _D ) of heavy metals between suspended particulate and dissolved phases in the Day River system a tropical, highly alluvial aquatic system, in Vietnam. The targeted river system, draining an urbanized–industrialized catchment where discharged wastewater is mostly untreated, could be separated into the least impacted, pristine area, and the most impacted, polluted area. Organic matter degradation was shown to govern the variation of parameters like total organic carbon, biochemical oxygen demand, chemical oxygen demand, nutrients, conductivity, or redox potential. Heavy metals in both dissolved and particulate phases were enriched in severely polluted area because of wastewater inflow that contains concentrated metals and intensification of metal influx from sediment. Results show log K _D in the order Mn?<?As?<?Zn?<?Hg?<?Ni?<?Cu?<?Cd?<?Co?<?Pb?<?Cr?<?Fe and As?<?Zn?<?Ni?<?Mn?<?Cr?<?Cu?<?Co?<?Fe in the polluted zone and the pristine zone, respectively. A decreasing tendency of partition coefficients of 11 heavy metals considered from the pristine to the impacted zones was observed. Three explanations for the difference are: (1) increase of solubility of most heavy metals in low redox potential, (2) competition for the binding sites with major and minor cations, and (3) complexation with dissolved organic matter concentrated in municipal waste impacted water. Apart from domestic waste impact, statistical analysis has contributed to identify the influence of climate condition and hydrological regime to the partition of heavy metals in the area.     

Effect of HPLC binary mobile phase composition on the analysis of carbonyls

The relative performance of the binary mobile phase in the high-performance liquid chromatography analysis of carbonyl compounds (CCs) was tested using the liquid-phase standards containing 15 aldehyde/ketone-DNPH mixture. The Hichrome column was employed for the analysis of CCs at a flow rate of 1.5 mL min(?-?1). The binary mobile phases prepared using both acetonitrile/water (AW) and a possible alternative of methanol:water (MW) mixture were examined by their calibration results. The data derived from these two binary phases were then evaluated in terms of three key variables (i.e., resolution, relative sensitivity, and retention time). The relative water content (or the water to organic solvent ratio (W/A) or (W/M)) of the binary phase was found as the key variable for the performance. The results indicate that the optimal resolution of AW combination was attained consistently for most composition, while MW generally suffered from overpressure problem. The changes of water content in the AW mixture led to the changes of all three variables in the quantitative analysis of CCs. The obtained results confirm that the AW mixture should be the optimal elutant for the CC analysis, as other simple binary compositions like MW are limited in many respects.     

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.     

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.     

Investigation of As, Mn and Fe fixation inside the aquifer during groundwater exploitation in the experimental system imitated natural conditions

Water-dissolved oxygen was supplied into anaerobic aquifer , which oxidized Fe(II), Mn(II) and trivalent arsenic and changed them into undissolved solid matter through hydrolysis, precipitation, co-precipitation and adsorption processes. The experiment was carried out on the column imitated a bore core of anaerobic aquifer with water phase containing Fe(II), Mn(II), As(III) concentration of 45.12 mg/L, 14.52 mg/L, 219.4 μg/L, respectively and other ions similarly composition in groundwater. After 6 days of air supply, concentration of iron reduced to 0.38 mg/L, manganese to 0.4 mg/L, arsenic to 9.8 μg/L (equivalent 99.16% of iron, 97.25% of manganese and 95.53% of arsenic fixed), and for other ions, the concentration changed almost according to general principles. Ion phosphate and silicate strongly influenced on arsenic removal but supported iron and manganese precipitation from water phase. Based on the experimental results, new model of groundwater exploitation was proposed.     

Soil particle-size composition and coastal erosion and accretion study in Soc Trang mangrove forests

Coastal erosion results in loss of land, which impacts the economy, coastal residents and settlement plans, especially in the context of rising sea levels caused by climate change. Studying soil particle-size fractions in mangrove forests will help provide a better understanding of the relationship between soil proportions and coastal processes as well as the role of mangrove forests to support coastal planning and management. Soil samples were collected at 26 sampling plots at depths of 10 cm and 40 cm in the Cu Lao Dung (CLD), Long Phu (LP) and Vinh Chau (VC) mangrove forests in Viet Nam’s Soc Trang Province. The soil proportions based on six different particle-sizes (<0.074 mm, 0.074–0.1 mm, 0.1–0.25 mm, 0.25–0.5 mm, 0.5–1.0 mm, and >1.0 mm) were measured using a dry sieving method. Analysis showed that soil particle-sizes ranging between 0.074 and 0.5 mm made up 75–95 % of the soil sample weight at both depths. The high standard deviation values of soil proportions of each given particle-size among sampling plots indicated the soil proportions by particle-size varied widely across the sampling plots. Cluster analysis found similar pattern of soil particle-size proportions for samples collected in CLD and VC, and different pattern of soil particle-size proportions in samples collected at LP, which is more impacted by the Mekong River flow and has a thin mangrove forest belt.?Non-metric dimension scaling (NMDS) analysis showed that sampling plots across the landward sites of the three mangrove forest areas were distributed in the nearby locations (Stress?=?0.11). This indicated that soil proportions of particle-sizes of samples collected from areas of the natural forest composed of different species were more similar. Such similarities were not found, however, in samples collected from middle and seaward plots dominated by single-species plantations.