Life Cycle Assessment of Ethiopian Cement Manufacturing: A Potential Improvement on the Use of Fossil Fuel in Mugher Cement Factory

The use of imported fuel in the Ethiopian cement industry increased the cost of production and the environmental burden, necessitating intervention. The greenhouse gas (GHG) emission, energy usage intensity, and resource exploitation of Ethiopian cement production were evaluated using the life cycle impact assessment (LCA) tool, aiming to recommend improvements. The LCA study used cumulative energy demand (CED) and Intergovernmental Panel on Climate Change (IPCC) 2006 life cycle impact assessment (LCIA) methods. For the case study of Mugher cement factory (MCF), the results on energy use intensities showed 3.74, 3.67, and 2.64 GJ/ton of clinker, Ordinary Portland cement (OPC), Pozzolana Portland cement (PPC), respectively. The result revealed MCF's energy use intensity was within the global range of 3.32 to 5.11 GJ/ton of cement production using similar kiln technology. The results on the GHG emissions were 0.87, 0.84, and 0.59 tons of CO2-equivalent/ton of clinker, OPC, and PPC, respectively. Process emissions accounted for 60% of overall CO2 emissions, with energy-related emissions accounting for the remaining 40%. CO2 emissions of MCF are below the global limit of 0.9 tons/ton of clinker, where all energy sources are fossil fuels. However, it is higher than the 0.65 ton/ton of clinker from a moderate rotary kiln in China. MCF used 70% of its total energy sources from imported fossil fuels, and transportation of the imported fuel added 1.2% CO2 to total emissions. A suggested fossil fuel use improvement scenario for MCF, where coffee husk replaces 50% of the imported coal improved the energy intensity, GHG emissions, and total cost of coal in clinker production by 1.2%, 14%, 36%, respectively.

Environmental Degradation-Education Nexus in Malaysia

This study aims to examine the role of education on CO2 emissions in Malaysia from 1974 to 2014. The unit root tests indicated that the variables were integrated in the same order. As such, the Johansen Co-integration Approach can be employed in this empirical analysis to analyze the impacts of the selected variables. The long-run estimation revealed that economic growth (GDP) and energy consumption (ENERGY) has a negative effect on CO2 emissions. Meanwhile, secondary school education (EDU) demonstrated a significant positive relationship with environmental degradation in the long-run. This can be inferred that secondary school education has a negative effect on environmental quality. However, a negative relationship was found between CO2 emissions and economic growth in the long-run. Besides that, this study had highlighted a positive association between gross fixed capital (GFC) and CO2 emissions. The findings from this study shed light on the vital importance of education in affecting environmental degradation. Empirical evidence suggested that the current education system will need to be redesigned for the reduction of CO2 emissions in the future. This is supported by the result that indicated the secondary level education promotes higher consumption of technologies that emit pollutants rather than promoting environmental awareness.

Critical Factors and their Correlation Affecting Green Industry Performance: Evidences from Small and Medium Enterprises

Large companies have achieved excellent progress toward green production while small and medium enterprises (SMEs) showed limited progress. This research aims to investigate key factors affect different stages of enhancing green industry implementation particularly in SMEs. This study conducted a systematic analysis to offer recommendations to unlock the inhibitors of the green industry. The electronic products and electrical equipment manufacturing industry in Thailand was chosen as a case study. Questionnaires is the main approaches to collect primary data from SMEs. The structural equation model is developed to examine correlation and the degree of influencing factors. The model indicated that the latent factors’ influence on the decision-making of SMEs in applying the green industry reflected by the influence of eighteen observable variables and it suggests that the external contexts from stakeholder have a greater influence on the decision-making than the internal context as organizational resources and capabilities. Whereas the level of certification conform with green industry criteria has minor correlation with the decision-making of SMEs. Innovative policy strategy is recommended to create synergy between incentive-based instruments in term of product charges or product tax, subsidies and voluntary measure as product certification are recommended tools to enhance green industry adoption by SMEs.

Fire Drivers Affecting Forest Fire Occurrences in the Tropical Mixed Broad-leaved Forests of Nepal

Forest fires triggered by various natural and anthropogenic drivers are increasing and threatening forest ecosystems across the globe. In Nepal, the high value Tropical Mixed Broad-leaved Forests are prone to fire caused by both natural and anthropogenic drivers. Thus, understanding fire drivers and their effect is important for the sustainable forest fire management. However, the preceding studies on forest specific fire drivers and their effect are limited. This research has identified the fire drivers and assessed their effect to fire occurrences in the Tropical Mixed Broad-leaved Forests of Nawalparasi District, Nepal. Fire drivers were identified and prioritized by participatory approaches. The fire incidences and burnt areas were obtained from the MODIS fire data (2001–2017). The results revealed altogether 20 drivers including eight natural and 12 anthropogenic. Based on the public perception and magnitude of forest fire, among the natural drivers, temperature, precipitation, forest fuel, aspect, elevation and slope were the major drivers. Likewise, among the anthropogenic drivers, forest distance from roads and settlements showed significant effect. The natural drivers, ambient temperature >30ºC and annual precipitation <2400 mm, revealed signi-ficant impacts on forest fire. Likewise, forests situated at lower elevation (<500 m), and southern and eastern aspects were highly vulnerable to fire. Considering anthropogenic drivers, forest lying within 500 m from the roads and settlements were highly vulnerable to fire. Among the forest types, the Hill Sal Forest was more affected. Future strategies should address the major fire drivers, construction of adequate fire lines and conservation ponds for the sustainable forest management.

Why Should Different City Characteristics Customize the Rate of Pollution Charge? Evidence of Factors Affecting Willingness-to-pay for Wastewater Management in Thailand

A challenge for wastewater management is enhancing the efficiency of resource allocation. Polluter Pays Principle is a wastewater charge collection approach that could help support the financial burden faced by many countries. Tailor-made policy implementation based on city characteristics is critical to the success of implementing a national policy to fit well in different local contexts. This study examined gaps for improving municipal wastewater management systems in Thailand through in-depth interviews and a questionnaire survey to identify the factors influencing households’ perception and willingness to pay in three different cities. A contingent variation method technique was used to evaluate the preferences of residents. The study revealed that different cities have different factors that influence willingness-to-pay decisions as well as pay-out levels. A single common factor positively affecting willingness-to-pay preference in all three cities is perception and engagement of wastewater treatment service. Citizens with a positive perception of receiving wastewater service are not only more likely to pay the wastewater charge, but also at a higher amount.

Quantifying Avoidable Food Waste and Identifying Its Underlying Causes: A Case Study of a University Dormitory in Thailand

To develop well-planned and effective policies and programs for reducing avoidable food waste, it is important to quantify the actual food waste level in particular settings and assess relationships among consumers’ awareness, attitudes, and behaviors. Recognizing these considerations, this paper measured avoidable food waste generated by university students living in dormitory buildings and identified its underlying causes in the case of Kanchanaburi campus, Mahidol University, Thailand. The study applied a food waste composition survey 18 times between January and May 2019 while administering questionnaires in October 2019 to the dormitory students. Based on these measures, the study identified 1,417 instances of avoidable food waste. Approximately half of the avoidable food waste had not even been eaten. Most of this waste was generated by female students. Some factors in terms of motivation, opportunity, and ability using a Motivation, Opportunity, Ability framework were found to have induced more food waste among female students. Due attention to the effect of avoidable food waste reduction includes educating dormitory students about food waste as well as more space and increased visibility of stored food in shared refrigerators. Targeting university students for reducing avoidable food waste in the setting of everyday life in dormitories is needed rather than simply focusing on the food service sector on campus.

Source Contribution of 1,3 Butadiene in the Vicinity of Petrochemical Industrial Area

Emissions and ambient concentrations of 1,3 butadiene released from the synthetic rubber industries in the largest petroleum and petrochemical complex in Thailand were evaluated in this study. The industrial emissions in this analysis were those emitted from process fugitive, combustion stack, flare, and wastewater treatment facility. It was found that wastewater treatment units were the largest emission source among other potential sources. The contribution of emission from wastewater treatment plants were about 92% of total 1,3 butadiene emission. The extent and magnitude of 1,3 butadiene in ambient air were further evaluated through the simulation of AERMOD dispersion model using these emission data together with local meteorological and topographical characteristics. Predicted annual 1,3 butadiene concentrations at every receptor were lower than its ambient air quality standard (< 0.33 μg m-3). Source apportionment analysis was performed with the objective to reveal the contribution of each emission source to the ambient concentrations at each receptor. Analytical results indicated that wastewater treatment units were the major emission source affected to the environmental concentrations of 1,3 butadiene in the study area. Evaluation of the potential adverse health impact of this chemical revealed that there may be a potential carcinogenic risk from inhalation exposure of 1,3 butadiene. Therefore, an effort in controlling emission of 1,3 butadiene should be given the priority to effectively manage the level of this compound in the environment.

Land Cover Classification Based on UAV Photogrammetry and Deep Learning for Supporting Mine Reclamation: A Case Study of Mae Moh Mine in Lampang Province, Thailand

Detailed, accurate, and frequent mapping of land cover are the prerequisite regarding areas of reclaimed mines and the development of sustainable project-level for goals. Mine reclamation is essential as the extractive organizations are bounded by-laws that have been established by stakeholders to ensure that the mined areas are properly restored. As databases at the mines area become outdated, an automated process of upgrading is needed. Currently, there are only few studies regarding mine reclamation which has less potential of land cover classification using Unmanned Aerial Vehicle (UAV) photogrammetry with Deep learning (DL). This paper aims to employ the classification of land cover for monitoring mine reclamation using DL from the UAV photogrammetric results. The land cover was classified into five classes, comprising: 1) trees, 2) shadow, 3) grassland, 4) barren land, and 5) others (as undefined). To perform the classification using DL, the UAV photogrammetric results, orthophoto and Digital Surface Model (DSM) were used. The effectiveness of both results was examined to verify the potential of land cover classification. The experimental findings showed that effective results for land cover classification over test area were obtained by DL through the combination of orthophoto and DSM with an Overall Accuracy of 0.904, Average Accuracy of 0.681, and Kappa index of 0.937. Our experiments showed that land cover classification from combination orthophoto with DSM was more precise than using orthophoto only. This research provides framework for conducting an analytical process, a UAV approach with DL based evaluation of mine reclamation with safety, also providing a time series information for future efforts to evaluate reclamation. The procedure resulting from this research constitutes approach that is intended to be adopted by government organizations and private corporations so that it will provide accurate evaluation of reclamation in timely manner with reasonable budget.

Centuries of Heat Waves over India during 20th and 21st Century

An assessment of temperature extremes is made for the Indian subcontinent to identify the changes since 1951 to 2015, and for the future climate periods till 2100 for all the 21 CMIP5 (Coupled Model intercomparision Project phase 5) models and the representative concentration pathways RCP4.5 and RCP8.5 were examined for the period from 1 March to 31 May to characterize the heat waves in future climates and mean maximum and mean minimum bias were evaluated for the Indian subcontinent. Later two highest recorded temperature regions were chosen Northwest & Central India (NW&CIN) and only central India (CIN) box and the features of heat waves such as intensity and frequency were evaluated up to 2100. Corresponding temperature predictions from historical runs for the period 1951–2005 of 21 global CMIP model outputs and statistics were performed with the India Meteorological Department (IMD) gridded maximum temperature data for validation. Statistical metrics of BIAS, RMSE and MAE have indicated low BIAS, high correlation and high IOA (Index of Agreement) validating CMIP climate simulations. By analyzing the statistics of all the 21 models with respect to the observational gridded data from IMD came to conclusion that among all the 21 models 5 models were performing well for Indian region and having good index of agreement with IMD. The frequencies of the days having thresholds of 40 ºC, 42 ºC and 45 ºC for the maximum temperature over India during the pre-monsoon are evaluated up to 21st century. All models are showing that the intensity and frequency of heat waves were increasing significantly for both RCP4.5 and RCP8.5. Specifically, the characteristics of heat waves in terms of intensity, duration and area extent are calculated and compared to heat waves of the current climate.

Ozone Formation Potential of Ambient Volatile Organic Compounds at Roadside in Bangkok, Thailand

Volatile organic compounds (VOCs) play an important role in atmospheric chemistry due to their high reactivity—reacting photochemically with oxides of nitrogen (NOx) in the presence of solar radiation forming tropospheric ozone (O3). Each VOC species have different effects on ozone formation according to the rates and pathways of their reactions. The objective of this study aims to examine ozone formation from the estimation of ozone formation potential (OFP). The observation of 29 VOCs species was carried out in the urban area near the roads of Bangkok, Thailand. Measurements were carried out during the dry season, from 16th February to 15th March, 2018. The air samples were analyzed using gas chromatography flame ionization detector (GC-FID). The results showed that toluene had the highest VOCs concentration followed by propane, and carbon tetrachloride (CCl4). The average ratio of benzene to toluene (B/T) and toluene to benzene (T/B) indicate that both toluene and benzene emitted from industrial area and vehicular emission. Ratio of m/p-xylene to benzene (m/p-X/B) indicate that BTEX emitted far from the source. The ozone formation potential indicated that toluene was the main VOC contributing to the total ozone formation. High VOCs concentration in monitoring site was influenced by vehicular sources and the sea breeze brought the pollutants back to the land.