长江口潮滩芦苇根表铁膜磁性特征及其环境意义

湿地植物根表铁膜对包括重金属在内的物质迁移转化具有重要作用,其氧化铁组成研究备受重视,但利用环境磁学方法进行表征的研究还未见报道.本文对长江口潮滩植物芦苇根系及周边沉积物进行了磁学分析,并结合沉积物粒度、漫反射光谱等测试,对芦苇根表铁膜的磁性矿物组成进行了系统研究.结果表明,芦苇根表铁膜磁性矿物主要包括磁铁矿和赤铁矿.由于沉积物不同深度氧化还原环境的不同,铁膜磁性矿物组成存在垂向差异.研究柱样24 cm深度以上,由于相对氧化的环境,铁膜磁性矿物除磁铁矿外,还有较多的赤铁矿贡献;24 cm深度以下,因根系处于相对还原的环境,磁性矿物以磁铁矿为主.与沉积物相比,24 cm以上深度铁膜中亚铁磁性矿物含量较低,24 cm深度以下则相反,反映铁膜和沉积物磁性矿物来源不同.本项研究表明,磁性测量方法有助于认识湿地植物根表铁膜的矿物组成,对湿地生物地球化学过程研究具有重要价值.     

How application of agricultural waste can enhance soil health in soils acidified by tea cultivation: a review

Environmental Chemistry Letters - Tea is one of the world’s most consumed beverages and an important crop of many developing countries. Intensive tea cultivation has negative impacts on soil...     

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.     

Potential health risks of toxic heavy metals and nitrate via commonly consumed bivalve and vegetable species in Ho Chi Minh City,Vietnam

Environmental Science and Pollution Research - This study aimed to evaluate the health risks of cadmium (Cd), lead (Pb), inorganic arsenic (As), and nitrate exposure through the consumption of...     

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.     

Nutrient ratios and the complex structure of phytoplankton communities in a highly turbid estuary of Southeast Asia

Phytoplankton diversity and abundance in estuarine systems are controlled by many factors. Salinity, turbidity, and inorganic nutrient concentrations and their respective ratios have all been proposed as principal factors that structure phytoplankton diversity and influence the emergence of potentially toxic species. Although much work has been conducted on temperate estuaries, less is known about how phytoplankton diversity is controlled in tropical, monsoonal systems that are subject to large, seasonal shifts in hydrology and to rapidly changing land use. Here, we present the results of an investigation into the factors controlling phytoplankton species composition and distribution in a tropical, monsoonal estuary (Bach Dang estuary, North Vietnam). A total of 245 taxa, 89 genera from six algal divisions were observed. Bacillariophyceae were the most diverse group contributing to 51.4 % of the microalgal assemblage, followed by Dinophyceae (29.8 %), Chlorophyceae (10.2 %), Cyanophyceae (3.7 %), Euglenophyceae (3.7 %) and Dictyochophyceae (1.2 %). The phytoplankton community was structured by inorganic nutrient ratios (DSi:DIP and DIN:DIP) as well as by salinity and turbidity. Evidence of a decrease in phytoplankton diversity concomitant with an increase in abundance and dominance of certain species (e.g., Skeletonema costatum) and the appearance of some potentially toxic species over the last two decades was also found. These changes in phytoplankton diversity are probably due to a combination of land use change resulting in changes in nutrient ratios and concentrations and global change as both rainfall and temperature have increased over the last two decades. It is therefore probable in the future that phytoplankton diversity will continue to change, potentially favoring the emergence of toxic species in this system.     

Indoor pesticide application practices and levels in homes of Bangkok Metropolitan Region

This study investigated the indoor application practices of pesticides in different homes located in urban, suburban, and rural areas of the Bangkok Metropolitan Region (BMR). A multi-stage stratified-judgmental sampling was applied to select 280 representative households in BMR for an in-depth questionnaire survey. We found about 71% of these households having mosquitoes as their main indoor nuisance. An inventory on the types and active ingredients was obtained through a shop-shelf survey. Among 22 available commercial products, 12 different active ingredients were observed with the pyrethroid containing pesticides are the most common. The stepwise regression analysis was conducted to reveal the statistical association between indoor levels of total pyrethriods (in the air and on the floor surface of homes) and the household application practices such as the overlap time period since the last application, application and storage locations, and frequency of applications, for instances.     

Study of the Climate Change Impacts on Water Quality in the Upstream Portion of the Cau River Basin,Vietnam

This paper presents simulations of climate change impacts on water quality in the upstream portion of the Cau River Basin in the North of Vietnam. The integrated modeling system GIBSI was used to simulate hydrological processes, pollutant and sediment wash-off in the river basin, and pollutant transport and transformation in the river network. Three projections for climate change based on emission scenarios B1, B2, and A2 of IPCC Special Report on Emission Scenarios (SRES) were considered. By assuming that the input pollution sources and watershed configuration were constant, based on 2008 data, water quality in the river network was simulated up to the terminal year 2050. For each climate change scenario, patterns of precipitation in wet and dry year were considered. The change in annual and monthly trends for dissolved oxygen (DO), biochemical oxygen demand (BOD), and ammonium ions (NH4+) load and concentration for different portions of the watershed have been analyzed. The results of these simulations show that climate change has more impact on changing the seasonal water quality parameters than on altering the average annual load of the pollutants. The percent change and change pattern in water quality parameters are different for wet and dry year, and the changes in wet year are smaller than those in dry year.     

Calculating of river water quality sampling frequency by the analytic hierarchy process (AHP)

River water quality sampling frequency is an important aspect of the river water quality monitoring network. A suitable sampling frequency for each station as well as for the whole network will provide a measure of the real water quality status for the water quality managers as well as the decision makers. The analytic hierarchy process (AHP) is an effective method for decision analysis and calculation of weighting factors based on multiple criteria to solve complicated problems. This study introduces a new procedure to design river water quality sampling frequency by applying the AHP. We introduce and combine weighting factors of variables with the relative weights of stations to select the sampling frequency for each station, monthly and yearly. The new procedure was applied for Jingmei and Xindian rivers, Taipei, Taiwan. The results showed that sampling frequency should be increased at high weighted stations while decreased at low weighted stations. In addition, a detailed monitoring plan for each station and each month could be scheduled from the output results. Finally, the study showed that the AHP is a suitable method to design a system for sampling frequency as it could combine multiple weights and multiple levels for stations and variables to calculate a final weight for stations, variables, and months.