Using a social learning configuration to increase Vietnamese smallholder farmers’ adaptive capacity to respond to climate change

Social learning is crucial for local smallholder farmers in developing countries to improve their adaptive capacity and to adapt to the current and projected impacts of climate change. While it is widely acknowledged that social learning is a necessary condition for adaptation, few studies have systematically investigated under which conditions particular forms of social learning are most successful in improving adaptive capacity of the most vulnerable groups. This study aims to design, implement and evaluate a social learning configuration in a coastal community in Vietnam. We make use of various methods during four workshop-based interventions with local smallholder farmers: interviews with key farmers and commune leaders, farmer-to-farmer learning, participatory observations and focus group discussions. The methods for evaluation of social learning configuration include in-depth interviews, focus group discussions and structured survey interviews. Our findings show that the social learning configuration used in this study leads to an increased problem ownership, an enhanced knowledge-base with regard to climate change impacts and production adaptation options, improved ability to see connections and interdependencies and finally, strengthened relationships and social cohesion. The results suggest that increased social learning in the community leads to increase in adaptive capacity of smallholder farmers and improves both their economic and environmental sustainability. We discuss the key lessons for designing learning configurations that can successfully enhance adaptive capacity and smallholder farmers’ agency and responsiveness to the challenges posed by climate change impacts.     

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...     

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.     

Assessing and selecting interventions for river water quality improvement within the context of population growth and urbanization: a case study of the Cau River basin in Vietnam

In this study, a multi-criteria methodology is proposed to identify and prioritize interventions for water quality improvement with the aid of computer simulation models. The methodology can be used to elaborate and compare future socio-economic development scenarios to select the best interventions based on three criteria: (1) ideas of experts and stakeholders about the importance of scenarios, (2) impacts of each scenario on surface water quality in watershed, and (3) benefit–cost analysis for each scenario. A score is computed for each scenario based on a weighted sum technique which enables to take into consideration different level of importance for the three criteria. The methodology is applied to Cau River basin in Vietnam, with the aid of a computer tool, to assess interventions for river water quality improvement within the context of population growth and urbanization. The results show that fast future population growth in upstream has significant impacts. In 2020, an increase of 116 % of the population in Bac Kan town can lead to an increase of 120 and 135 % in BOD₅ and NH₄ ⁺ median concentrations, respectively, with the implementation of a treatment plant for 10,000 people in Bac Kan town. Therefore, the increase of the domestic wastewater treatment plant’s capacity in Bac Kan town, at least twice as the projection of local government, is necessary. These results will help decision makers to select the best interventions for Cau River basin management.     

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.     

Utilization of high-volume mine tailing and by-products in composite binder production: hardened properties and sustainable development

Journal of Material Cycles and Waste Management - This study was designed to investigate the hardened performance of the paste specimens produced using a composite binder with high volumes of mine...