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Second-generation bioethanol can be produced from various lignocellulosic biomasses such as wood, agricultural or forest residues. Lignocellulosic biomass is inexpensive, renewable and abundant source for bioethanol production. The conversion of lignocellulosic biomass to bioethanol could be a promising technology though the process has several challenges and limitations such as biomass transport and handling, and efficient pretreatment methods for total delignification of lignocellulosics. Proper pretreatment methods can increase concentrations of fermentable sugars after enzymatic saccharification, thereby improving the efficiency of the whole process. Conversion of glucose as well as xylose to bioethanol needs some new fermentation technologies to make the whole process inexpensive. The main goal of pretreatment is to increase the digestibility of maximum available sugars. Each pretreatment process has a specific effect on the cellulose, hemicellulose and lignin fraction; thus, different pretreatment methods and conditions should be chosen according to the process configuration selected for the subsequent hydrolysis and fermentation steps. The cost of ethanol production from lignocellulosic biomass in current technologies is relatively high. Additionally, low yield still remains as one of the main challenges. This paper reviews the various technologies for maximum conversion of cellulose and hemicelluloses fraction to ethanol, and it point outs several key properties that should be targeted for low cost and maximum yield.

The current status and challenges associated with the production and utilization of cellulosic ethanol in Korea are reviewed in this paper. Cellulosic ethanol has emerged as a promising option for mitigating Korea's CO(2) emissions and enhancing its energy security. Korea's limited biomass resources is the most critical barrier to achieving its implementation targets for cellulosic ethanol. Efforts to identify new suitable biomass resources for cellulosic ethanol production are ongoing and intensive. Aquatic biomasses including macroalgae and plantation wastes collected in the Southeast Asia region have been found to have great potential as feedstocks for the production of cellulosic ethanol. R&D explorations into the development of technologies that can convert biomass materials to ethanol more efficiently also are underway. It is expected that cellulosic ethanol will be in supply from 2020 and that, by 2030, its use will have effectively reduced Korea's total gasoline consumption by 10%.

Understanding the system of connections between societal contexts and policy outcomes in municipal governments provides important insights into how community sustainability happens, and why it happens differently in various communities. A growing body of research in recent years has focused on understanding the socio-economic characteristics of communities and cities that are recognized as policy leaders in sustainability. In this paper, we expand the focus beyond the leaders in sustainability as we apply a selection of socio-demographic influences of community sustainability to a large sample of U.S. communities using community classification analytics to identity a range of community types and levels of engagement with sustainability. Our typology presents an integrated and comprehensive perspective on the structure of community sustainability in the United States, highlighting key points of comparison between human capital factors such as population size and density, affluence, home ownership, and adoption of sustainability policy. The analysis provides new insights not only about community leaders in sustainability, but also communities with the civic and social capacity to do more, and the challenges that may inhibit sustainability efforts in others.

Abstract Transportation de-carbonization is a complex problem involving the economy, population, technology and environment. Implementing the pathway simulation based on systematic methods will help to optimize the transportation sustainability plan. This study’s key motivation is that earlier research ignored the relationship between driving factors and the transmission process. To quantitatively identify the path and process of emission reduction, a hybrid system dynamics STIRPAT-SD model is proposed to explore the transportation optimization’s de-carbonization ability. This study fully considers the composition of elements and subsystems based on the STIRPAT theoretical model and visually shows the system’s feedback relationship. Transportation structural and technical optimization scenarios are set to identify the threshold reduction paths. It is found these optimization strategies have significant de-carbonization effects. And transportation structure policy has the highest de-carbonization efficiency, the emission intensity decreased by 9.1% under the TSS2 scenario (Transportation structure scenario). This study proposes a novelty model combining dynamic simulating processes with a significantly theoretical model to improve simulation and factor composition accuracy. And the joint scenario setting identifies the most effective de-carbonization pathway and clarifies the threshold of all possible pathways. Research findings can effectively track, test, predict the achievement of policy goals, and provide policy optimization references for the sustainable development related to the transportation system in practice.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

This study aims to explore the application of fractional order chaotic system (FOCS), based on the T-S fuzzy model, in the design of secure communication (SC) and this SC system’s role in the construction of efficiency evaluation system for dispatching operation of energy saving and power generation under a low carbon economy (LCE). First, the definition of fractional order differential equations and the stability theory of FOCS are discussed. T-S fuzzy control is introduced to analyse the stability of FOCS. Then, based on the adaptive synchronisation theory, the combined FOCS is designed for SC, and the performance of the system constructed here is analysed in a MATLAB environment. Next, an evaluation index system of the dispatching operation effect of energy saving and power generation under LCE is constructed. The confidential communication system constructed here is used to transmit the index data. The particle swarm optimisation (PSO) algorithm is then used to optimise the back propagation neural network (BPNN) model. The BPNN algorithm based on PSO (PSO-BPNN) is obtained, and the evaluation model is constructed. After training this model, it is applied to the evaluation of the dispatching operation effect for energy saving and power generation in 10 provinces in China. The simulation results show that the FOCS based on the T-S fuzzy model can acquire the criterion of system stability. Furthermore, the constructed SC system can effectively undertake the secure transmission of square and sine waves. The performance of the PSO-BPNN model seems to be better than other algorithms. After analysing the data on energy saving and power generation from 10 provinces in China using this model, the comprehensive evaluation value of province 5 is found to be the highest and good (0.802), while that of province 4 is the lowest and general (0.600). Summarising, the FOCS based on T-S fuzzy model constructed here is applied to the design of SC. This can improve the confidentiality of data transmission and reduce the transmission error. Moreover, the BPNN evaluation model based on PSO can effectively achieve the evaluation of the dispatching operation effect of energy saving and power generation under LCE.

Energy is consumed at every stage of the cycle of water production, distribution, end use, and recycled water treatment. Understanding the nexus of energy and water may help to minimize energy and water consumption and reduce environmental emissions. However, the interlinkages between water and energy have not received adequate attention. To address this gap, this paper disaggregates and quantifies the energy consumption of the entire water cycle process in Beijing. The results of this study show that total energy consumption by water production, treatment and distribution, end use, and recycled water reuse amounts to 55.6 billion kWh of electricity in 2015, or about 33% of the total urban energy usage. While water supply amount increased by only 10% from 2005 to 2015, the related energy consumption increased by 215% due to water supply structural change. The Beijing municipal government plans to implement many water saving measures in the area from 2016 to 2020, however, these policies will increase energy consumption by 74 million kWh in Beijing. This study responds to the urgent need for research on the synergies between energy and water. In order to achieve the goal of low-energy water utilization in the future, water and energy should be integrated in planning and management.

Paper mill sludge (PMS) is a residual biomass that is generated at paper mills in large quantities. Currently, PMS is commonly disposed in landfills, which causes environmental issues through chemical leaching and greenhouse gas production. In this research, we are exploring the potential of fast pyrolysis process for converting PMS into useful bio-oil and biochar products. We demonstrate that by subjecting PMS to a combination of acid hydrolysis and torrefaction pre-treatment processes it is possible to alter the physicochemical properties and composition of the feedstock material. Fast pyrolysis of pretreated PMS produced bio-oil with significantly higher selectivity to levoglucosenone and significantly reduced the amount of ketone, aldehyde, and organic acid components. Pretreatment of PMS with combined 4% mass fraction phosphoric acid hydrolysis and 220 °C torrefaction processed prior to fast pyrolysis resulted in a 17 times increase of relative selectivity towards levoglucosenone in bio-oil product along with a reduction of acids, ketones, and aldehydes combined from 21 % to 11 %. Biochar, produced in higher yield, has characteristics that potentially make the solid byproduct ideal for soil amendment agent or sorbent material. This work reveals a promising process system to convert PMS waste into useful bio-based products. More in-depth research is required to gather more data information for assessing the economic and sustainability aspects of the process.