Community concerns about landfills: A case study of Hanoi,Vietnam

This paper examines the nature of community concerns about a landfill in Hanoi, Vietnam and compares these concerns to those found in studies of North American landfills. Based on a survey of 174 households living near Hanoi's landfill, it was found that concerns were uniformly high within the study area. Although the community initially believed the proponent's claims that the landfill would not pollute the environment, their faith in those claims disappeared once the landfill opened and began to produce numerous negative impacts on the community. Residents called for a variety of technical, management and economic measures to mitigate these impacts.     

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.     

Sustainable solutions for solid waste management in Southeast Asian countries

Human activities generate waste and the amounts tend to increase as the demand for quality of life increases. Today’s rate in the Southeast Asian Nations (ASEANs) is alarming, posing a challenge to governments regarding environmental pollution in the recent years. The expectation is that eventually waste treatment and waste prevention approaches will develop towards sustainable waste management solutions. This expectation is for instance reflected in the term ‘zero emission systems’. The concept of zero emissions can be applied successfully with today’s technical possibilities in the agro-based processing industry. First, the state-of-the-art of waste management in Southeast Asian countries will be outlined in this paper, followed by waste generation rates, sources, and composition, as well as future trends of waste. Further on, solutions for solid waste management will be reviewed in the discussions of sustainable waste management. The paper emphasizes the concept of waste prevention through utilization of all wastes as process inputs, leading to the possibility of creating an ecosystem in a loop of materials. Also, a case study, focusing on the citrus processing industry, is displayed to illustrate the application of the aggregated material input–output model in a widespread processing industry in ASEAN. The model can be shown as a closed cluster, which permits an identification of opportunities for reducing environmental impacts at the process level in the food processing industry. Throughout the discussion in this paper, the utilization of renewable energy and economic aspects are considered to adapt to environmental and economic issues and the aim of eco-efficiency. Additionally, the opportunities and constraints of waste management will be discussed.     

Multiple categorization in resume screening: Examining effects on hiring discrimination against Arab applicants in field and lab settings

Debate exists as to what the more appropriate prediction is regarding the effects of multiple stigmatized group memberships on employment discrimination. The ethnic prominence (EP), multiple minority status (MMS), and subordinate male target hypotheses were assessed for the combined effects of ethnic group membership (Arabic), sex, social status, and job type on hiring evaluations. Two correspondence tests in the field (Study 1) and two experimental studies in the lab (Study 2) and in the field (Study 3) were conducted. Studies 1 and 2 showed evidence for the EP hypothesis when low‐status jobs were tested. The odds for rejection were four times higher for Arab than for Dutch applicants. Applicants' sex, socio‐economic status, and external client contact did not moderate findings (Study 1). The effect of applicants' ethnic group membership was further moderated by raters' motivation to control prejudice (Study 2). Study 3 showed evidence for the MMS hypothesis. We found double jeopardy against Arab women who applied for high‐status jobs when recruiters' prejudice was controlled. Study findings show that discrimination in resume screening may depend upon the particular intersection of applicant, job, and recruiter characteristics. We discussed implications for anonymous resume screening and research on evaluation of applicants possessing multiple stigmatizing characteristics. Copyright © 2011 John Wiley & Sons, Ltd.     

Regression model under skew-normal error with applications in predicting groundwater arsenic level in the Mekong Delta Region

Environmental and Ecological Statistics - Recently there has been some renewed interest in skew-normal distribution (SND) because it provides a nice and natural generalization (in terms of...     

Association between heavy metals and antibiotic-resistant human pathogens in environmental reservoirs: A review

Heavy metals can act as co-selecting agents and promote antibiotic resistance. Most frequent resistances to heavy metals are observed for zinc and cadmium. P. aeruginosa and E. coli are commonly resistant to heavy metals and antibiotics. Heavy metals proliferate antibiotic resistance through co- and cross-resistance. Heavy metal and antibiotic resistances are common near anthropogenic activities. Antibiotic resistance in human pathogens can proliferate under selective pressures. Heavy metals in environmental reservoirs may contribute to selecting antibiotic-resistant strains. To determine the associations between heavy metals and antibiotic resistance, a literature review was conducted to systematically collect and categorize evidence for co-occurrence of resistance to heavy metals and antibiotics within human pathogenic bacteria in water, wastewater, and soil. In total, 42 publications adhered to inclusion criteria. Across the reservoirs, zinc and cadmium were the most commonly observed heavy metals associated with resistance to antibiotics. Pseudomonas aeruginosa and Escherichia coli were the most commonly studied bacteria with reported co-occurrence of resistance to several heavy metals and antibiotic classes. As co-selecting agents, prevalence of heavy metals in the environment can proliferate resistance to heavy metals and antibiotics through co-resistance and cross-resistance mechanisms. In comparing different reservoirs, soils and sediments harbor higher heavy metal and antibiotic resistances compared to water environments. Additionally, abiotic factors such as pH can affect the solubility and hence, the availability of heavy metals to bacterial pathogens. Overall, our review demonstrates heavy metals act as co-selecting agents in the proliferation of antibiotic resistance in human pathogens in multiple environmental reservoirs. More studies that include statistical data are needed to further describe the exposure-response relationships between heavy metals and antibiotic resistance in different environmental media. Moreover, integration of culture-based and molecular-based methods in future studies are recommended to better inform our understanding of bacterial co- and cross-resistance mechanisms to heavy metals and antibiotics.     

Socioeconomic and indigeneity determinants of the consumption of non-timber forest products in Vietnam’s Bu Gia Map National Park

ABSTRACT

Conservation of protected areas requires understanding of the consumption of forest products by rural people who live near protected forests. Socioeconomic factors such as a better education, income, land holding size, have been used to understand the patterns of consumption of non-timber forest products (NTFPs). Ethnicity, and especially whether or not people are indigenous to the forested areas, may also change consumption patterns. In this study we analysed the socioeconomic factors, indigeneity and geographical locations of people living in the buffer zones of Vietnam’s Bu Gia Map National Park to better understand the key determinants of the consumption of NTFPs. We conducted 121 interviews with local households and found that indigeneity, education, family size, and the area of land used were statistically significant in explaining the amount of NTFPs consumed, while indigeneity and area of land used by local people had positive relationships with the diversity (measured in number of categories) of NTFPs consumed by local people. Interestingly, there were statistically significant effects of interactions between the area of land used and indigeneity on the consumption of NTFPs. The amount of these products is important for indigenous people who belong to the groups using small and medium areas of land. The medium land use group consumed significantly fewer categories of NTFPs than the small and large land use groups. This data may help local managers to develop interventions that support biodiversity conservation, promote sustainability of these important resources and improve the social welfare of marginal groups.     

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.