Fractal geometry and applicability to biological simulation shapes for sustainable architecture design in Vietnam

Environmental Science and Pollution Research - Sustainability is the biggest goal that all areas including building architecture aim at. Sustainability is created by the harmony of buildings to the...     

Green synthesis of ZrO2 nanoparticles and nanocomposites for biomedical and environmental applications: a review

Environmental Chemistry Letters - Pollution and diseases such as the coronavirus pandemic (COVID-19) are major issues that may be solved partly by nanotechnology. Here we review the synthesis of...     

An integrated and quantitative vulnerability assessment for proactive hazard response and sustainability: a case study on the Chan May-Lang Co Gulf area,Central Vietnam

A natural factors-based approach was developed to examine proactive responses to hazards and improving sustainability on the Chan May-Lang Co Gulf area, Central Vietnam. The approach was based on a weight-of-evidence method within an integrated and quantitative vulnerability assessment in which the spatial relationship between a set of evidential factors (lithology, distance to the coastline, altitude, slope, aspect, drainage, wind speed during storms, and land use and cover) and a set of hazard locations was combined with the prior probability (total vulnerability) to obtain the posterior probability of hazard occurrence. The result showed that 44.3 % of the study area had high to very high total vulnerability, due to the high density of vulnerable objects and frequency of severe damage from typhoons, floods, landslides, and erosion. The result also demonstrated that the contribution of natural factors was directly proportional to total vulnerability in approximately 75 % of the study area, indicating a high dependence of vulnerability on natural factors. In the remaining areas, low contributions were found in the high and very high vulnerability areas dominated by high anthropogenic activities. In contrast, natural factors were important contributors to total vulnerability in areas characterized by dense vegetation, consolidated rocks, and altitude greater than 300 m, reflecting high natural resilience. The present study demonstrated that a proactive approach may provide appropriate measures to mitigate hazards and to increase the sustainability of the study area.     

Controlling various contaminants in wastewater effluent through membranes and engineered wetland

For effective wastewater reclamation and water recovery, the treatment of natural and effluent organic matters (NOM and EfOM), toxic anions, and micropollutants was considered in this work. Two different NOM (humic acid of the Suwannee River, and NOM of US and Youngsan River, Korea), and one EfOM from the Damyang wastewater treatment plant, Korea, were selected for investigating the removal efficiencies of tight nanofiltration (NF) and ultrafiltration (UF) membranes with different properties. Nitrate, bromate, and perchlorate were selected as target toxic anions due to their well known high toxicities. Tri-(2-chloroethyl)-phosphate (TCEP), oxybenzone, and caffeine, due to their different K _ow and pK _a values, were selected as target micropollutants. As expected, the NF membranes provided high removal efficiencies in terms of all the tested contaminants, and the UF membrane provided fairly high removal efficiencies for anions (except for nitrate) and the relatively hydrophobic micropollutant, oxybenzon. Through the wetlands, nitrate was successfully removed. Therefore, a fair process of combining membranes with an engineered wetland could be proposed for sustainable wastewater reclamation and optimum control of contaminats.     

Analysis of polychlorinated dibenzo-p-dioxins and furans in various aqueous samples in Taiwan

Twenty-one fresh water samples were taken from reservoirs, wells and drinking water treatment plants in Taiwan for measurement of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) concentrations. Due to low concentration of PCDD/Fs, water samples (400-1000 L) were collected by using the on-site large volume pre-concentration system and analyzed by high resolution gas chromatography (HRGC)/high resolution mass spectrometer (HRMS). Different characteristics of dioxin profiles in surface water and groundwater are observed. The PCDD/F concentrations in fresh water samples varied from 0.001 to 0.265 pg WHO₉₈-TEQ/L which are lower than the standard (12 pg WHO₉₈-TEQ/L) set by the Taiwan Environmental Protection Administration (TEPA) for drinking water. Only a small fraction (<5%) of the total PCDD/F concentration in fresh water samples was water-soluble. As a result of their hydrophobicity, PCDD/Fs are effectively removed along with suspended solid via the water treatment process (average 98% removal efficiency).     

Development of Spatial and Temporal Emission Inventory for Crop Residue Field Burning

Accurate emission inventory (EI) is the foremost requirement for air quality management. Specifically, air quality modeling requires EI with adequate spatial and temporal distributions. The development of such EI is always challenging, especially for sporadic emission sources such as biomass open burning. The country of Thailand produces a large amount of various crops annually, of which rough (unmilled) rice alone accounted for over 30 million tonnes in 2007. The crop residues are normally burned in the field that generates large emissions of air pollutants and climate forcers. We present here an attempt at a multipollutant EI for crop residue field burning in Thailand. Available country-specific and regional primary data were thoroughly scrutinized to select the most realistic values for the best, low and high emission estimates. In the base year of 2007, the best emission estimates in Gigagrams were as follows: particulate matter as PM_2.5, 128; particulate matter as PM₁₀, 143; sulfur dioxide (SO₂), 4; carbon dioxide (CO₂), 21,400; carbon monoxide (CO), 1,453; oxides of nitrogen (NO_x), 42; ammonia (NH₃), 59; methane (CH₄), 132; non-methane volatile organic compounds (NMVOC), 108; elemental carbon (EC), 10; and organic carbon (OC), 54. Rice straw burning was by far the largest contributor to the total emissions, especially during the dry season and in the central part of the country. Only a limited number of EIs for crop residue open burning were reported for Thailand but with significant discrepancies. Our best estimates were comparable but generally higher than other studies. Analysis for emission uncertainty, taking into account possible variations in activity data and emission factors, shows considerable gaps between low and high estimates. The difference between the low and high EI estimates for particulate matter and for particulate EC and OC varied between −80% and +80% while those for CO₂ and CO varied between −60% and +230%. Further, the crop production data of Thailand were used as a proxy to disaggregate the emissions to obtain spatial (76 provinces) and temporal (monthly) distribution. The provincial emissions were also disaggregated on a 0.1° × 0.1° grid net and to hourly profiles that can be directly used for dispersion modeling.     

Toward successful implementation of conservation research: A case study from Vietnam

A number of different approaches have been used to explain the successes and failures of biodiversity conservation strategies in developing countries. However, to date, little attention has been paid toward assessing the influence of knowledge transfer between science, policy, and conservation practices in the implementation of these strategies. Vietnam’s Pu Luong Cuc Phuong Conservation Area is a globally important ecosystem, situated within a limestone landscape and inhabited by hundreds of local communities. Biodiversity conservation has become an important part of sustainable development in this area. This study analyzes three conservation strategies employed in the Pu Luong Cuc Phuong Conservation Area by applying the Research–Integration–Utilization (RIU) model of scientific knowledge transfer. Our analyses reveal weaknesses in scientific knowledge transfer arising from low-quality research and poor integration strategies. Based on our results, we developed recommendations to improve research and integration in an effort to enhance science-based policy support.     

Application of soft computing to predict water quality in wetland

Prediction of water quality is a critical issue because of its significant impact on human and ecosystem health. This research aims to predict water quality index (WQI) for the free surface wetland using three soft computing techniques namely, adaptive neuro-fuzzy system (ANFIS), artificial neural networks (ANNs), and group method of data handling (GMDH). Seventeen wetland points for a period of 14 months were considered for monitoring water quality parameters including conductivity, suspended solid (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO), temperature, pH, phosphate nitrite, and nitrate. The sensitivity analysis performed by ANFIS indicates that the significant parameters to predict WQI are pH, COD, AN, and SS. The results indicated that ANFIS with Nash-Sutcliffe Efficiency (NSE = 0.9634) and mean absolute error (MAE = 0.0219) has better performance to predict the WQI comparing with ANNs (NSE = 0.9617 and MAE = 0.0222) and GMDH (NSE = 0.9594 and MAE = 0.0245) models. However, ANNs provided a comparable prediction and the GMDH can be considered as a technique with an acceptable prediction for practical purposes. The findings of this study could be used as an effective reference for policy makers in the field of water resource management. Decreasing variables, reduction of running time, and high speed of these approaches are the most important reasons to employ them in any aquatic environment worldwide.

     

Visualization and quantification of transparent exopolymer particles (TEP) in freshwater using an auto-imaging approach

Most water sources are full of microscopic transparent exopolymer particles (TEP), which are currently regarded as a major initiator of biofilm formation. This study developed and applied an auto-imaging FlowCAM-based method for online observation and quantification of TEP in freshwater. Samples from reservoirs in Taiwan with a wide range of water quality were directly used to develop this methodology. Factors that potentially affect the measurement were tested. The results showed that characteristics of the particles measured instantaneously after staining samples with Alcian blue differed significantly from those measured at steady states, as a result of particle aggregation. Compared to traditional microscopic methods, this proposed method provides a simple, rapid, and less labor-intensive analysis with particle morphological conservation and a large number of particle attributes. By overcoming the limitations from the former, this technique would offer routine monitoring of these transparent particles from various freshwater sources and feed water in membrane filtration, hence facilitating the use of TEP as a critical parameter for biofouling investigation in water treatment. Application of the method for Taiwan reservoirs showed a wide variety of morphological forms of TEP and its abundance, up to 25,000 ppm.