Combat Climate Change Research Articles

Green University Model – World Trend and Policy Implications for Vietnam

Green university model is now developing dramastically, spreading and becoming a mainstream trend in world higher education. Main features of this trend are universities integrating sustainable development goals into their operations, implementing their mission in building a prosperous and safe society. With key solutions using modern technology and techniques, universities strive to develop smart educational ecosystems, explore natural resources to improve quality of life, and participate in combating climate change, solving ecological problems of resources and human health. A number of green university rankings have been created, becoming a place to encourage the trend of developing green university model as a breakthrough solution for smart universities. Based on the approach of content and trend of green university development, the article presents some recommendations for green development in Vietnamese universities.

Navigating the green shipping: Stochastic hydrogen hub deployment in inland waterways

The maritime industry is shifting toward sustainability to help combat climate change, given the sector’s significant contribution to global greenhouse gas emissions. This study focuses on the strategic integration of hydrogen fuel—a zero-emission alternative—into inland waterway transport systems. We recognize the operational characteristics of inland shipping networks and the complexities of two-stage financial planning. Consequently, we propose a two-stage stochastic framework for the deployment of hydrogen refueling hubs, taking into account financial uncertainties in the future. This approach contrasts with a myopic strategy and a two-stage deterministic framework, addressing both immediate financial constraints and future uncertainties. We focus on the Yangtze River’s shipping network as a case study, and our analysis validates the superior performance of our proposed two-stage stochastic strategy. This suggests its potential to accommodate volatile future financial uncertainties while ensuring the economic and operational viability of hydrogen integration.

WTO 수산보조금협정에 관한 소고

Negotiations on the norms regulating fisheries subsidies were launched within the WTO framework as part of the Doha Development Agenda in 2001, and have been ongoing for over 20 years. The Agreement on Fisheries Subsidies was finalized at the 12th Ministerial Conference in June 2022.
 The Agreement is a significant outcome of more than two decades of negotiations on fisheries subsidies. It is the first multilateral agreement to recognize that certain trade policies, such as subsidies, can have harmful impacts on the world’s marine environment, and to address the environmental issue of marine sustainability in the WTO framework by building a harmonized and interrelated relationship among trade, environment, and development. This is significant because multilateral norms on subsidies are not limited to marine resource sustainability. The WTO Members are currently exploring the appropriate role and function of subsidies in the design of policies to effectively reduce greenhouse gas emissions from domestic industries, especially as they face the challenge of combating climate change. This is because climate change response policies using subsidies may fall within the scope of the WTO Subsidies Agreement and be subject to countervailing measures, whereas fuel subsidies that are harmful to the environment may not be regulated as they do not meet the specificity requirement. Under these circumstances, the Agreement shows that it is possible for the Members to agree on trade norms for sustainable development in response to the negative spillover effects of subsidies.
 However, the Agreement is limited by its incomplete form, which had to leave out norms relating to subsidies that contribute to overcapacity and overfishing, and special treatment for developing countries. In addition, the Agreement will be ineffective unless comprehensive norms on fisheries subsidies are agreed upon within four years of its entry into force, unless otherwise agreed upon by the Members. However, given that the current Agreement covers significant portion of dangerous situations in which subsidies can harm the marine environment, and that negotiations are currently underway to seek a comprehensive norm, it is possible that a comprehensive agreement could emerge that would encompass the outcomes of more than two decades of fisheries subsidy negotiations.

Renewable energy adoption in multinational energy companies: A review of strategies and impact

This review provides a succinct overview of the research on renewable energy adoption within multinational energy companies, focusing on the review of strategies and their impact. As the global community intensifies its efforts to combat climate change, the renewable energy sector has become a focal point for multinational energy companies seeking sustainable and environmentally friendly solutions. This study critically examines the strategies employed by these companies to incorporate renewable energy sources into their operations and assesses the impact of such initiatives. The review begins by exploring the various strategies adopted by multinational energy corporations in their pursuit of renewable energy integration. These strategies encompass technological advancements, regulatory compliance, investment frameworks, and partnerships with key stakeholders. By analyzing a diverse range of multinational energy companies, the study aims to identify patterns and best practices that contribute to successful renewable energy adoption. Furthermore, the research delves into the broader impact of these strategies on both the companies themselves and the global energy landscape. The analysis considers economic implications, environmental benefits, and social responsibility, providing a comprehensive evaluation of the multifaceted effects of renewable energy adoption. Insights from this review can inform future decision-making processes for energy corporations, policymakers, and other stakeholders involved in the transition to a sustainable energy future. This review contributes valuable insights into the evolving landscape of renewable energy adoption among multinational energy companies. By examining strategies and their impact, the study seeks to enhance our understanding of the challenges and opportunities in fostering a more sustainable and resilient energy sector on a global scale.

Empowering sustainable power generation: The vital role of power electronics in California's renewable energy transformation

This paper elucidates the pivotal role played by power electronics in catalyzing the ongoing transformation of California's energy landscape towards sustainability through renewable sources. As California intensifies its efforts to combat climate change and foster energy resilience, the integration of renewable energy technologies becomes paramount. Through a comprehensive analysis, this study unveils the indispensable functions of power electronics in enabling the efficient generation, transmission, and utilization of renewable energy resources. By exploring key renewable energy systems such as solar, wind, and hydro power, and their intricate interactions with power electronics, this research underscores their collective impact on the state's energy transition. Insights garnered from this examination not only shed light on the technical intricacies of renewable energy integration but also inform strategic decision-making for policymakers, utilities, and stakeholders vested in California's sustainable energy future.

Geospatial mapping of carbon estimates for forested areas using the InVEST model and Sentinel-2: A case study in Galicia (NW Spain)

CO2 emissions have increased exponentially in recent years, so measuring and quantifying carbon sequestration is a step towards sustainable forest management and combating climate change. The overall goal of this study is to develop an accurate model for estimating carbon storage and sequestration for forest areas of the Atlantic Biogeographic Region. Specifically, the modelling and field sampling are carried out in the municipality of Baiona (Galicia, NW Spain), which was selected as a representative biome of this region. The methodology consists of carrying out two object-based image analysis (OBIA) classifications in spring and autumn to observe possible stocks of seasonal differences. Two carbon storage and sequestration models are built up (model 1 and model 2): model 1 for forest areas only and model 2 including all other land cover in the study area. Sentinel-2 geospatial data for 2021, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) tools and geographic information systems (GIS) are used. A Kappa index of 0.92 is obtained for both classifications, thus ruling out any notable seasonal differences in the images used. The results from both models indicate that it is land covers associated with forest uses which store the most carbon in the study area, accounting for >50 % more than the other land covers. It is concluded that the methodology and data used are very useful for quantifying ecosystem services, which will help the governance of the region by implementing measures to mitigate some of the effects of climate change and help to create silvicultural models for the sustainable management of the Atlantic Biogeographic Region.

Assessing the Effectiveness of Regional Storm Surge Reduction Strategies and Tank Level Structural Mitigation Measures for Aboveground Storage Tanks

The effectiveness of regional storm surge reduction strategies and tank-level structural mitigation measures in reducing the failure probability of aboveground storage tanks (ASTs) were studied. Given past failures during flood and hurricane events, several studies have developed fragility models for ASTs. However, the suitability of these fragility models for different hurricane hazard scenarios is unknown. Furthermore, to combat climate change and sea level rise, several regional storm surge reduction strategies are being proposed. However, the effectiveness of these strategies in improving the safety of ASTs is also unknown. So, herein, a framework was proposed that facilitates assessing the suitability of fragility models and the quantification of AST failures and their consequences while propagating uncertainties using Monte Carlo simulations. The application of the proposed framework to Cameron, Louisiana, provided several key insights: (1) fragility models that do not model wave loads and dislocation failure are not suitable for the region; (2) a regional risk mitigation strategy was insufficient for lowering future spill volume, repair, and cleanup costs; and (3) considering bottom-plate failure of anchored tanks—a structural risk mitigation measure—would lead to a 47–72% reduction in the consequences of tank failure.

Youth response to climate change: Learning from Indigenous land-based camp at the Northern Saskatchewan Indigenous Communities, Canada

This paper represents Youth's involvement in land-based learning in Indigenous culture camps (LLICP) in a powerful and innovative approach to addressing the pressing global issue of climate change. Following Indigenist and relational approaches, we (Indigenous and non-Indigenous youth and educators) explore the critical aspects of this initiative, highlighting its significance and potential impact. Indigenous communities have long held a deep connection with the land and possess traditional knowledge that is invaluable in combating climate change. The LLICP initiative involves organizing cultural camps designed for youth from diverse backgrounds to learn from Indigenous elders and community leaders about the vital relationship between the environment and Indigenous cultures. The LLICP provides a unique opportunity for young people to engage with Indigenous wisdom, traditional practices, and land-based teachings. Through Indigenous elders and knowledge-keepers guidelines, we learned a holistic understanding of sustainable living, biodiversity conservation, and the importance of preserving ecosystems. Our learning helped us, particularly our youths, to become proactive stewards of the environment and advocates for climate action. The LLICP fosters cross-cultural understanding and collaboration, encouraging a sense of unity among youths. The LLICP inspires innovative solutions to climate-related challenges and empowers youth to take leadership roles in their communities, advocating for sustainable policies and practices. The LLICP offers a powerful means of engaging young people in the fight against climate change while respecting and honoring Indigenous knowledge and heritage. It is a promising step towards a more sustainable and resilient future for all.

Discounting the Distant Future: What Do Historical Bond Prices Imply about the Long-Term Discount Rate?

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. From the viewpoint of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long-term discount rate to estimate the rate when taking historical US and UK data, and to further contribute to the discussion about the urgency of climate action in the context of environmental economics and stochastic methods. Century-long historical records of 3-month bonds, 10-year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond-pricing models, which are designed for nominal rates that are assumed to be positive. We, therefore, use the Ornstein–Uhlenbeck model, which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long-term discount rate is 1.7% for the UK and 2.2% for the US. The value of 1.4% used by Stern is less than a standard deviation from our estimated long-run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the need for immediate and substantial spending to combat climate change.

Production of Chestnut Coppice Biomass in a Framework of Low Mechanization and High Expectations to Combat Climate Change and Other Social Expectations

Climate change has become one of the most critical problems facing modern society. Sustainable forest management can be an important solution to counter the increasing concentration of carbon dioxide in the atmosphere. In particular, management of the chestnut forest could prove to be an effective strategy to absorb carbon dioxide as this species is characterized by sustained growth, so it has a high capacity to store carbon, and through the use of wood products, it is possible to sequester it for a considerable period. Chestnut (Castanea sativa Mill.) forests cover an area of about 800,000 ha in Italy, most of which is managed as coppice. It plays a central role in the Latium Region where its productive function is very important, as it provides timber of excellent quality. The purpose of this paper is to verify whether the current management of chestnut is efficient, as well as whether retractable wood products can contribute to the fight against climate change. The chestnut coppice located in the municipality of Tolfa (Lazio region, Italy) produces timber for 352 m3/ha and stores about 390,000 kg of CO2. Wood residues and losses during woodworking, together with emissions for the use of machineries, generate emissions of 368,000 kg of CO2. The chestnut semi-finished products, with long-term use prospects, retain a net volume of 22,000 kg of CO2. Although this is good for combating climate change, the amount of CO2 stored is very low, less than 6% of the CO2 stored by functional unit. Chestnut wood has a high versatility of use, so it could replace several products generated by fossil raw materials. Moreover, the implementation of precision forestry, the adoption of forest management more oriented to favor larger plants, the development of local economies and the reduction in the carbon footprint of the wood supply chain through the use of sustainable technologies would increase the capacity for climate change mitigation and increase the added value of its products.

Delivering double wins: How can Africa's finance deliver economic growth and renewable energy transition?

As economies grow, they tend to prioritize industrializing with fossil fuels over protecting the environment, impeding efforts to combat climate change. Therefore, there is an urgent need to address the critical policy concern of financing a clean energy transition to ensure sustainable economic growth for current and future generations. We examine the effect of financial development on clean energy transition in 20 low-income and middle-income countries in sub-Saharan Africa. The study employs fixed-effects and instrumental variable two-stage Least squares (IV-2SLS) models to examine the effect of financial development on the transition to renewable energy. Overall, the results show a positive effect of financial development on renewable energy transition. However, the financial development effect is only significant for financial institutions instead of financial markets – a signal of weak financial markets in the region. More importantly, the results show that this financial development effect on renewable energy transition is significant only in low-income countries, contrary to middle-income economies. We recommend that governments in the region further develop and promote innovative financial market products such as green bonds and digital finance that support private sector investments in renewable energy. Regarding trade, it is critical to subsidize environmentally friendly green energy imports while taxing non-renewable products that promote the use of fossil fuels.

UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs

AbstractWe are in a race against time to combat climate change and increase food production by 70% to feed the ever‐growing world population, which is expected to double by 2050. Agricultural research plays a vital role in improving crops and livestock through breeding programs and good agricultural practices, enabling sustainable agriculture and food systems. While advanced molecular breeding technologies have been widely adopted, phenotyping as an essential aspect of agricultural research and breeding programs has seen little development in most African institutions and remains a traditional method. However, the concept of high‐throughput phenotyping (HTP) has been gaining momentum, particularly in the context of unmanned aerial vehicle (UAV)‐based phenotyping. Although research into UAV‐based phenotyping is still limited, this paper aimed to provide a comprehensive overview and understanding of the use of UAV platforms and image analytics for HTP in agricultural research and to identify the key challenges and opportunities in this area. The paper discusses field phenotyping concepts, UAV classification and specifications, use cases of UAV‐based phenotyping, UAV imaging systems for phenotyping, and image processing and analytics methods. However, more research is required to optimize UAVs’ performance for image data acquisition, as limited studies have focused on the effect of UAVs’ operational parameters on data acquisition.

A global perspective on the nexus between energy and stock markets in light of the rise of renewable energy

The rise in renewable energy and the associated divestment initiatives from fossil fuel around the world have become prominent in combating climate change. This paper revisits the relationship between energy and stock markets by accounting for renewable energy through the use of the Divisia index method. The paper contributes to the literature by using three renewable energy tariffs rather than relying on clean energy stocks as a proxy for renewable energy. We retrieve data for both the price and consumption of fossil energy (oil, coal and gas) and renewable energy (solar, wind and hydro). We estimate a Vector Autoregressive (VAR) model over the period 2000–2019 across 25 countries globally. Our study identifies a significant time-dependent dynamics between renewable energy and both the energy stock and carbon markets, while fossil energy has no significant influence on those markets. The increasing influence of renewable energy in this nexus signals to policymakers that investors have started to shift their focus of attention from fossil to renewable energy.

Application of Neuro-Fuzzy to the elephant grass production process: A systematic bibliographic review

The transition to renewable energy sources can help combat climate change, as they emit fewer greenhouse gas emissions. Biomass is an important source of energy production, being composed of organic materials, such as residues from agricultural and forestry crops, among others, with emphasis on elephant grass. The application of Neuro-Fuzzy in production processes, especially laboratory ones, is of utmost importance, as it allows the creation of more accurate and efficient prediction and control models in the bioenergetic context. Given this context, the objective of this article is to identify how the state of knowledge is configured regarding the application of the use of Neuro-Fuzzy for the chemical quantification process of elephant grass cellulose. A Systematic Bibliographic Review was carried out to search and map published scientific data to identify numerous applications for the use of Neuro-Fuzzy, mainly in renewable energy. By carrying out the research using the Systemic Bibliographic Review, it was possible to identify several opportunities for the application of Neuro-Fuzzy in the chemical quantification of elephant grass. However, it was observed that this article presents a novelty on the application of the use of Neuro-Fuzzy for the process of chemical quantification of cellulose, in addition to the production of bioethanol from this biomass. Of the 22 documents analyzed in this research, 100% were articles in the form of applied research and literature review, demonstrating great relevance in this line of research, which is the application of Artificial Intelligence in field and laboratory production processes using elephant grass. as biomass to produce bioethanol.

Value chain extension services for climate-smart agriculture adoption: evidence from Burkina Faso's cotton farming

PurposeThis study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.Design/methodology/approachTo address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.FindingsThe study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.Research limitations/implicationsThe use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.Originality/valueThe study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

Future Assessment of Low Cost EV Automobile Market in Bangladesh

The global automotive landscape is undergoing a profound transformation, driven by the imperative to reduce greenhouse gas emissions and combat climate change. Bangladesh, a densely populated country grappling with environmental challenges and urban traffic, stands poised at the brink of embracing electric mobility as a solution. This abstract delves into the future trajectory of the low-cost electric vehicle (EV) market in Bangladesh, examining key factors influencing its growth, challenges hindering its adoption, and potential strategies for overcoming these barriers. The low-cost EV market in Bangladesh presents a promising avenue for sustainable transportation, offering the dual benefits of reducing carbon emissions and mitigating dependence on imported fossil fuels. This includes fostering collaboration between the government and private sector to develop comprehensive EV policies, investing in research and development to enhance battery technology and drive down costs, and implementing targeted financial incentives to make EVs more accessible to a wider demographic. Furthermore, public awareness campaigns and educational initiatives can play a crucial role in dispelling misconceptions and fostering acceptance of EVs among consumers. In conclusion, while challenges persist, the future of the low-cost EV market in Bangladesh is undeniably bright. With the right mix of policy support, infrastructure development, and industry innovation, Bangladesh has the potential to emerge as a regional leader in sustainable transportation, paving the way for a cleaner, greener, and more prosperous future.

Impact of knowledge and trust on households' solar energy consumption behavior: Do social influence and gender matter?

Clean and renewable energy resources like solar energy are essential for a sustainable and eco-friendly future, as they decrease reliance on fossil fuels and combat climate change. This study explores trust and knowledge as drivers of solar energy consumption behavior (SECB). Particularly, this study finds the role of social influence and gender as moderators in the associations between trust and SECB, as well as knowledge and SECB. The World Bank energy access data based on the 8500 Pakistani households survey was examined for empirical analysis. Findings reveal that trust and knowledge positively impact SECB. Knowledge also influences trust in solar energy. Meanwhile, higher social influence weakens the association of knowledge and trust with SECB. Furthermore, it was found that the association of knowledge and trust with SECB is stronger for females than males. The findings-based implications are provided for practitioners and researchers.

A prediction-based model to optimize construction programs: Considering time, cost, energy consumption, and CO2 emissions trade-off

Efforts to combat climate change demand global action to promote a sustainable development worldwide. Given the construction industry's significant energy consumption, it is crucial to curtail energy consumption and CO2 emissions in this sector. This study aims to predict and trade-off four essential objectives: time, cost, energy consumption, and CO2 emissions. Initially, various factors affecting time and cost was identified using the CoCoSo method. Subsequently, 11 machine learning algorithms were employed to predict all four targets. Results revealed that support vector regression achieved an accuracy of 95.77% in project duration prediction, while the neural network algorithm demonstrated accuracy of 93.64%, 97.63%, and 97.99% in predicting cost, energy consumption, and CO2 emissions, respectively. Additionally, the research findings from six scenarios highlighted the non-linear relationship among project objectives. Deviating from the optimal point resulted in increases on both sides, with more significant impacts observed at values less than optimal duration. This research equips engineers with a valuable tool for accurately predicting project outcomes by adjusting input values, ensuring successful project execution and efficient resource allocation. Additionally, the framework's predictive abilities are beneficial for companies with energy and CO2 policies, influencing various sectors, regions, and policies tied to energy, emissions, costs, climate change, ESG, and UN SDGs. Its application extends to shaping regulations, strategies, and targets.

Potential impact of future climate change on grassland cover in Burkina Faso.

The objective of this study was to analyse the potential impact of future climate change on grassland cover in Burkina Faso. MODIS NDVI 250m time series were used to monitor changes in grassland over 2000-2022. The random forest regression (RFR) model was fit by regressing reference data of grassland cover against current climatic and other environmental predictors to predict the current grassland cover map (2022). Projected climate model data of CMIP6 used under SSP 126 and SSP 585 scenarios were integrated into the fit RFR model to predict future change. The results revealed that grassland areas were largely dominated by non-significant productivity change (55%) during 2000-2022. In this period, grassland area knew more increased productivity (35%) than decrease (10%). Burkina Faso is predicted to face more decreased areas of grassland cover than increase by 2061-2080 under SSP 126 and SSP 585 scenarios. The findings of this study can help to set up appropriate adaptation measures to combat climate change in Burkina Faso.

Renewable energy consumption - financial globalization-tourism nexus with nonlinearity and cross-sectional dependence during Asia's carbon-free transition.

Adopting renewable energy consumption is one of the most important aspects of international efforts to combat climate change, improve energy security, and encourage the shift to a more robust and sustainable energy system. Therefore, the empirics and policymakers worldwide are searching for factors that can promote renewable energy consumption. This analysis intends to investigate the role of financial globalization and tourism on renewable energy consumption in Asia and sub-regions such as Central Asia, East Asia, South Asia, Southeast Asia, and West Asia. The analysis utilized the linear and nonlinear CS-ARDL methods. Long-run outcomes of the linear and nonlinear models confirm that a rise in financial globalization and tourism promotes renewable energy consumption in Asia and all sub-regions. However, the nonlinear model highlights that a fall in financial globalization hurts renewable energy consumption in Central and South Asian regions, and tourism only hurts renewable energy consumption in Asia. In addition, ICT, GDP, and GHG emissions help promote renewable energy consumption. These results suggest that Asian policymakers must increase collaboration in the financial sectors and promote sustainable tourism in the regions to promote renewable energy consumption.