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The traditional carbon accounting method, with a lag of over 2 years due to the release time of statistical yearbooks, impedes timely policy adjustments in urban planning and management. Hence, there is an urgent need to establish a real-time carbon emissions characterization model. Xi'an which has a complex land-use structure was chosen as the study site and its carbon emissions were calculated using the Emission Factor Method. The GIS-Kernel Density (KD) model was constructed, and land use was subdivided based on Point of Interest (POI) and road network data. Based on the results of carbon emissions accounting and land-use subdivision, a Multilayer perceptron (MLP) model was established. The remote sensing (RS) images of Xi'an underwent supervised classification, and the carbon emissions of Xi'an were characterized based on the subdivision results and MLP model. The results show that: (1) The accuracy of the characterization model is more than 90%, and with the improvement of RS technology, the accuracy will be further improved; (2) Compared with the existing model, this model can real time reflect the spatial distribution of carbon emissions; (3) Atmospheric emission of Xi'an will be 41.92 million tons at the end of 2022, a decrease of 2.80 million tons compared with that of 2020, but an increase of 0.33 million tons from 2021. The north of Xi'an and periphery of the central urban area are the main carbon sink loss areas, while the east of Xi'an and north foot of the Qinling Mountains are carbon sink growth areas.

Smart energy networks provide an effective means to accommodate high penetrations of variable renewable energy sources like solar and wind, which are key for the deep decarbonisation of energy production. However, given the variability of the renewables as well as the energy demand, it is imperative to develop effective control and energy storage schemes to manage the variable energy generation and achieve desired system economics and environmental goals. In this paper, we introduce a hybrid energy storage system composed of battery and hydrogen energy storage to handle the uncertainties related to electricity prices, renewable energy production, and consumption. We aim to improve renewable energy utilisation and minimise energy costs and carbon emissions while ensuring energy reliability and stability within the network. To achieve this, we propose a multi-agent deep deterministic policy gradient approach, which is a deep reinforcement learning-based control strategy to optimise the scheduling of the hybrid energy storage system and energy demand in real time. The proposed approach is model-free and does not require explicit knowledge and rigorous mathematical models of the smart energy network environment. Simulation results based on real-world data show that (i) integration and optimised operation of the hybrid energy storage system and energy demand reduce carbon emissions by 78.69%, improve cost savings by 23.5%, and improve renewable energy utilisation by over 13.2% compared to other baseline models; and (ii) the proposed algorithm outperforms the state-of-the-art self-learning algorithms like the deep-Q network., This work was supported by the Smart Energy Network Demonstrator project (grant ref. 32R16P00706) funded by ERDF and BEIS. This work is also supported by the EPSRC EnergyREV project (EP/S031863/1) and the Horizon Europe project i-STENTORE (101096787) and FNR CORE project LEAP (17042283). This research received no external funding., Peer Reviewed, Postprint (published version)

Renewable energies and low-carbon energy technologies have currently limited use in greenhouses. The use of sustainable energy technologies in many sectors, including agricultural greenhouses, is desirable and attractive for reducing the climate impacts of agriculture. Their maturity, reliability and cost-effectiveness has been proved and their use in many applications has been accelerated. Reports regarding net-zero energy and net-zero carbon emission greenhouses are limited so far. However, the global policies for climate change mitigation and creation of a net-zero carbon economy in the coming decades favors the use of benign energy sources replacing the polluting fossil fuels. The use of heat pumps and solar-PV systems for energy generation covering the needs for heat, cooling and electricity in an existing greenhouse located in Crete, Greece has been investigated. The combined use of these green energy technologies can eliminate the use of fossil fuels resulting in a net-zero carbon-emissions greenhouse. The size of the greenhouse studied was 3,300 m2, the nominal power of the solar-PV system generating all the required electricity was estimated at 254.23 KWel  and its installation cost at 233,052 €. A heat pump with COP equal to 3 and power at 254.23 KWel  can cover all the peak heat and cooling demand of the greenhouse while its installation cost is at 1,144,035 €. The total installation cost of the abovementioned benign energy systems is at 417.30 €/m2. Our research indicates that sustainable energy technologies can generate all the required energy in agricultural greenhouses zeroing their net-carbon emissions and promoting the carbon neutral agriculture.

The existing studies that examined the green aid effectiveness in reducing carbon dioxide (CO2) emissions found mixed results; however, neither of these studies considered the role of aid fragmentation in the effectiveness of green aid flows. By using the dynamic panel generalized method of moments (GMM) methodology to panel data of 92 countries covering the period between 2002 and 2018, this study examines the impact of green aid fragmentation on the effectiveness of green aid flows in reducing CO2 emissions. Using different fragmentation measures, this paper finds that green aid fragmentation is detrimental to the effectiveness of green aid flows in reducing CO2 emissions per capita. The findings also highlight that the damaging impact of green aid fragmentation is lower in countries with stronger institutions. This paper highlights the need for better coordination of the green aid flows by having less fragmented green aid flows.

Global climate change imposes significant challenges on the ecological environment and human sustainability. Industrial parks, in line with the national climate change mitigation strategy, are key targets for low-carbon revolution within the industrial sector. To predict the carbon emission of industrial parks and formulate the strategic path of emission reduction, this paper amalgamates the benefits of the “top-down” and “bottom-up” prediction methodologies, incorporating the logarithmic mean divisia index (LMDI) decomposition method and long-range energy alternatives planning (LEAP) model, and integrates the Tapio decoupling theory to predict the carbon emissions of an industrial park cluster of an economic development zone in Yancheng from 2020 to 2035 under baseline (BAS) and low-carbon scenarios (LC1, LC2, and LC3). The findings suggest that, in comparison to the BAS scenario, the carbon emissions in the LC1, LC2, and LC3 scenarios decreased by 30.4%, 38.4%, and 46.2%, respectively, with LC3 being the most suitable pathway for the park’s development. Finally, the paper explores carbon emission sources, and analyzes emission reduction potential and optimization measures of the energy structure, thus providing a reference for the formulation of emission reduction strategies for industrial parks.

The existing studies that examined the green aid effectiveness in reducing carbon dioxide (CO2) emissions found mixed results; however, neither of these studies considered the role of aid fragmentation in the effectiveness of green aid flows. By using the dynamic panel generalized method of moments (GMM) methodology to panel data of 92 countries covering the period between 2002 and 2018, this study examines the impact of green aid fragmentation on the effectiveness of green aid flows in reducing CO2 emissions. Using different fragmentation measures, this paper finds that green aid fragmentation is detrimental to the effectiveness of green aid flows in reducing CO2 emissions per capita. The findings also highlight that the damaging impact of green aid fragmentation is lower in countries with stronger institutions. This paper highlights the need for better coordination of the green aid flows by having less fragmented green aid flows.

Understanding and predicting urban traffic carbon emissions constitute an urgent agenda in research and policy decision-making. Since the exhausted emissions vary in time and different urban settings, assessing the spatiotemporal distribution of carbon emissions is fundamentally important for land use planning. This paper attempts to identify the spatial and temporal heterogeneity of the impacts of land use and built environment on urban traffic carbon emissions. A spatial standard deviational ellipse (SDE) model and a geographically and temporally weighted regression (GTWR) model were developed to explore the spatiotemporal dependency of traffic carbon emissions on land use and built environment factors and applied to the core urban zones of Dalian, China. Results show the center of gravity of traffic carbon emissions have a footprint characterized by a shift to the southeast first and then to the northwest, with weekday and weekend performance being consistent. Compared to other periods, emissions are spatially agglomerated during internal hours (9:00–15:59), especially during weekdays. Land use and built environment factors affect carbon emissions differently across space and time whereas the effects of residential population density, employment density, medical, road network density on weekdays are larger than that on weekends. Furthermore, we found that increasing land use mix leads to a greater negative impact on weekday emissions. This supplements the important role of mixed land use planning in decarbonization. Based on the findings, we propose various policy interventions to support the development of carbon neutral cities.

Based on the Environmental Kuznets Curve (EKC) theory, this research seeks to probe the impact of nuclear and renewable energy on carbon emissions in Pakistan. In order to analyze Pakistan's cointegration from 1990 to 2022, this study uses the ARDL technique. The findings provided empirical support for the Environmental Kuznets Curve (EKC) theory and demonstrated that the use of nuclear and renewable energy resources is linked to lower carbon dioxide (CO2) over the long term. Carbon dioxide emissions from burning fossil fuels, which are used for most of the world's energy needs, have been steadily rising in recent years. Policymakers recognize this and are working to reduce reliance on nonrenewable energy sources while increasing nuclear and renewable energy use.

To achieve sustainable growth, energy is incumbent because all modern production is based on it. Unfortunately, about 80% of the global population uses polluted energy, adversely damaging the environment. The present study asses the asymmetric role of renewable energy in the mitigation of CO2 emissions in Pakistan. The Non-linear ARDL econometric approach is used to estimate the empirical results of the time series data from 1980 to 2020. The study found that positive change in renewable energy adversely declines CO2 emissions while negative change increases CO2 emissions. Additionally, the HDI and trade openness lessens CO2 emissions, while urbanization increases CO2 emissions. The study recommends that Pakistan should promote eco-friendly consumption patterns. Pakistan should focus on promoting renewable energy resources, which will help combat the upsurge in industrial and housing carbon dioxide emissions.

El Grupo Intergubernamental de Expertos sobre el Cambio Climático (IPCC) estima que se debe alcanzar el objetivo de cero emisiones netas a escala global para el año 2050. A fin de conseguirlo, muchas empresas privadas se han comprometido a lograr las cero emisiones netas para 2050. El Comité Directivo de Datos Climáticos (CDSC) está trabajando en una iniciativa para crear un repositorio digital central global de divulgaciones climáticas que intente abordar los desafíos de datos actuales. Este documento evalúa el progreso de las instituciones financieras europeas en sus esfuerzos por superar los desafíos de datos descritos por el CDSC. Utilizando un enfoque de minería de textos, junto con la aplicación de modelos de lenguaje de gran tamaño (LLM) para la verificación de contexto, calculamos un Índice de Divulgación de Gases de Efecto Invernadero (GHGDI), analizando 23 divulgaciones muy específicas presentes en los informes ESG comprendidos entre 2019 y 2021 y pertenecientes a la mayoría de los bancos significativos bajo supervisión directa del BCE. Posteriormente se compara este índice con la puntuación otorgada por el Carbon Disclosure Project (CDP). Los resultados indican una correlación moderada entre aquellas instituciones que no informan al CDP cuando se les solicita y un bajo GHGDI. Las instituciones con una puntuación alta, por su parte, no guardan necesariamente correlación con un GHGDI alto., The Intergovernmental Panel on Climate Change (IPCC) estimates that global net-zero should be achieved by 2050. To this end, many private firms are pledging to reach net-zero emissions by 2050. The Climate Data Steering Committee (CDSC) is working on an initiative to create a global central digital repository of climate disclosures, which aims to address the current data challenges. This paper assesses the progress within European financial institutions towards overcoming the data challenges outlined by the CDSC. Using a text-mining approach, coupled with the application of commercial Large Language Models (LLM) for context verification, we calculate a Greenhouse Gas Disclosure Index (GHGDI), by analysing 23 highly granular disclosures in the ESG reports between 2019 and 2021 of most of the significant banks under the ECB’s direct supervision. This index is then compared with the CDP score. The results indicate a moderate correlation between institutions not reporting to CDP upon request and a low GHGDI. Institutions with a high CDP score do not necessarily correlate with a high GHGDI.

Environmental deterioration led by global warming is accelerating, and low-carbon development has become a global consensus. China, as the world's largest developing country, has also responded to low-carbon development and proposed a "30.60" dual-carbon target aimed at reducing carbon emissions. At the same time, the third industrial revolution oriented by information and communication technology (ICT) is taking place. Driven by new technologies such as the Internet and big data, the digital economy has become an important engine for high-quality economic development in China. However, while the digital economy promotes high-quality economic development, can it also promote China's low-carbon development? Based on the panel data of 31 key cities in China from 2011 to 2019, this paper explores the impact of digital economy development on carbon emissions through corresponding econometric models, and analyzes its potential mechanism based on the results. The results show that: First, there is a linear relationship between the digital economy development and carbon emissions of these 31 key cities in China, and digital economy development can restrain carbon emissions. Second, the results of this study are inconsistent with the existing research results, the reason may be the differences in model measurement scale and sample characteristics, and indirectly shows that there are differences in the level of digital economy development among Chinese cities. Third, the potential mechanism behind this relationship may be that digital economy development suppresses carbon emissions by improving innovation efficiency, promoting high-quality economic development, influencing government interventions, and applying ICT to improve energy efficiency or reduce energy consumption. Based on the above conclusions, this study draws the following practical implications: first, improve the speed and quality of digital economy development; second, improve the cultivation of digital talent

Purpose: This paper aims to review and analyze the prior research on the relationship between financial development and carbon emissions. As the financial sector develops and the economies grow, carbon emissions are expected to increase. Therefore, it is necessary to identify and understand the factors that contribute to this relationship. Theoretical framework: Recent studies indicate that financial development facilitates and expands businesses, which may cause an increase in carbon emissions; on the other hand, sustainable development of the financial sector may lead to lower carbon emissions through eco-friendly investments. Design/Methodology/Approach: This study will employ a systematic literature review to investigate the relationship between financial development and carbon emissions and analyze how developing and developed countries differ concerning these two factors. Findings: The result showed that empirical studies have produced various, frequently contradicting findings and conclusions. Some studies show a strong positive correlation between financial development, environmental performance indices, and economic growth, while others find a more nuanced correlation. Research, practical & social implications: This study might stimulate additional investigation into green financial development and emission reductions through green investments. Findings could aid in adjusting policies to account for disparities between developed and developing countries' financial-emission relationships. Green financial instruments might encourage eco-investments and reduce emissions. The social advantages include helping to reduce gaps by providing resources and expertise to poorer nations, promoting sustainability, and contributing to climate solutions. Originality/Value: This research thoroughly assesses and analyzes prior research on the relationship between financial development and carbon emissions. Particularly in the context of developed and emerging count

Reducing the carbon footprint of global supply chains is a challenge for many companies. Governmental emission regulations are increasingly stringent, and consumers are increasingly environmentally conscious. Companies should therefore integrate carbon emissions in their supply chain decision making. In this paper, we study the inbound supply mode and inventory management decision making for a company that sells an assortment of products. Stochastic demand for each product arrives periodically and unmet demand is backlogged. Each product has two distinct supply modes that differ in terms of their carbon emissions, speed, and costs. The company needs to decide when to ship how much using which supply mode such that total holding, backlog, and procurement costs are minimized while the emissions associated with different supply modes across the assortment remains below a target level. We assume that shipment decisions for each product are governed by a dual-index policy for which we optimize the parameters. We formulate this decision problem as a mixed integer linear program that we solve through Dantzig–Wolfe decomposition. We benchmark our decision model against two state-of-the-art approaches in a large test-bed based on real-life carbon emissions data. Relative to our decision model, the first benchmark lacks the flexibility to dynamically ship products with two supply modes while the second benchmark makes supply mode decisions for each product individually. Our computational experiment shows that our decision model can outperform the first and second benchmark by up to 15 and 40 percent, respectively, for moderate carbon emission reduction targets.

Many developed countries have committed to targets to reduce their carbon emissions under international agreements. However, a recent 2021 study found that only one country, The Gambia, is on track to meeting its Paris targets. A key mechanism for achieving these national targets is the government. Therefore, the failure of most countries to meet their targets highlights the importance of evaluating the major policy alternatives. Australia instituted a carbon pricing scheme in 2012 that was repealed in 2014 and subsequently replaced with an emissions reduction fund in 2015. This provides a unique opportunity to study the effects of these two major alternative government policies on government salience. This study applies stakeholder theory and finds that the power and urgency of both policies was weakened by uncertainty, an often-neglected factor affecting stakeholder salience. Furthermore, we note that an evaluation of government salience must also consider firm and industry differences and the effect of positively versus negatively framed interventions.

Renewable energies and low-carbon energy technologies have currently limited use in greenhouses. The use of sustainable energy technologies in many sectors, including agricultural greenhouses, is desirable and attractive for reducing the climate impacts of agriculture. Their maturity, reliability and cost-effectiveness has been proved and their use in many applications has been accelerated. Reports regarding net-zero energy and net-zero carbon emission greenhouses are limited so far. However, the global policies for climate change mitigation and creation of a net-zero carbon economy in the coming decades favors the use of benign energy sources replacing the polluting fossil fuels. The use of heat pumps and solar-PV systems for energy generation covering the needs for heat, cooling and electricity in an existing greenhouse located in Crete, Greece has been investigated. The combined use of these green energy technologies can eliminate the use of fossil fuels resulting in a net-zero carbon-emissions greenhouse. The size of the greenhouse studied was 3,300 m2, the nominal power of the solar-PV system generating all the required electricity was estimated at 254.23 KWel  and its installation cost at 233,052 €. A heat pump with COP equal to 3 and power at 254.23 KWel  can cover all the peak heat and cooling demand of the greenhouse while its installation cost is at 1,144,035 €. The total installation cost of the abovementioned benign energy systems is at 417.30 €/m2. Our research indicates that sustainable energy technologies can generate all the required energy in agricultural greenhouses zeroing their net-carbon emissions and promoting the carbon neutral agriculture.

Renewable energies and low-carbon energy technologies have currently limited use in greenhouses. The use of sustainable energy technologies in many sectors, including agricultural greenhouses, is desirable and attractive for reducing the climate impacts of agriculture. Their maturity, reliability and cost-effectiveness has been proved and their use in many applications has been accelerated. Reports regarding net-zero energy and net-zero carbon emission greenhouses are limited so far. However, the global policies for climate change mitigation and creation of a net-zero carbon economy in the coming decades favors the use of benign energy sources replacing the polluting fossil fuels. The use of heat pumps and solar-PV systems for energy generation covering the needs for heat, cooling and electricity in an existing greenhouse located in Crete, Greece has been investigated. The combined use of these green energy technologies can eliminate the use of fossil fuels resulting in a net-zero carbon-emissions greenhouse. The size of the greenhouse studied was 3,300 m2, the nominal power of the solar-PV system generating all the required electricity was estimated at 254.23 KWel  and its installation cost at 233,052 €. A heat pump with COP equal to 3 and power at 254.23 KWel  can cover all the peak heat and cooling demand of the greenhouse while its installation cost is at 1,144,035 €. The total installation cost of the abovementioned benign energy systems is at 417.30 €/m2. Our research indicates that sustainable energy technologies can generate all the required energy in agricultural greenhouses zeroing their net-carbon emissions and promoting the carbon neutral agriculture.

Background Compared to traditional breathing circuits, low-volume anesthesia machines utilize a lower-volume breathing circuit paired with needle injection vaporizers that supply volatile agents into the circuit mainly during inspiration. We aimed to assess whether or not low-volume anesthesia machines, such as the Maquet Flow-i C20 anesthesia workstation (MQ), deliver volatile anesthetics more efficiently than traditional anesthesia machines, such as the GE Aisys CS2 anesthesia machine (GE), and, secondarily, whether this was in a meaningful economic or environmentally conscious way. Methodology Participants enrolled in the study (Institutional Review Board Identifier: 2014-1248) met the following inclusion criteria: 18-65 years old, scheduled for surgery requiring general anesthesia at the University of California Irvine Health, and expected to receive sevoflurane for the duration of the procedure. Exclusion criteria included age <18 years old, a history of chronic obstructive pulmonary disorder, cardiovascular disease, sevoflurane sensitivity, body mass index >30 kg/m2, American Society of Anesthesiologists >2, pregnancy, or surgery scheduled <120 minutes. We calculated the total amount of sevoflurane delivered and consumption rates during induction and maintenance periods and compared the groups using one-sided parametric testing (Student's t-test). There was no suspicion that the low-volume circuit could use more sevoflurane and that the outcome did not answer our research question. One-sided testing allowed for more power to be more certain of smaller differences in our results. Results In total, 103 subjects (MQ: n = 52, GE: n = 51) were analyzed. Seven subjects were lost to attrition of different types. Overall, the MQ group consumed significantly less sevoflurane (95.5 ± 49.3 g) compared to the GE group (118.3 ± 62.4 g) (p = 0.043), corresponding to an approximately 20% efficiency improvement in overall agent delivery. When accounting for the fr

Understanding the imbalance of carbon emissions in the urban residential building (URB) sector is beneficial for equitable and effective emission reduction policies. However, carbon imbalance in URB and its major driving factors remain unclear. Therefore, according to the Kaya identity and Zenga index, this study aims to analyze the imbalance in carbon emissions and carbon emission unit area of URB from 2005 to 2019. The results represent the following: 1) Although the overall carbon emission unit area reached its peak value (36.17 kgCO2/m2) in 2011, the overall carbon emission of URB did not reach the peak value, arriving at 0.86 BtCO2 in 2019; 2) the obvious imbalance of carbon emission and carbon emission unit area was led by the population and energy consumption unit area, respectively; 3) Compared to the difference in economy, the difference in climate had a larger impact on inter-group imbalance of carbon emission unit area without heating. In summary, these results and provided policies facilitate future formulation of fair and effective provincial decarbonization responsibility and emission mitigation implementation policies., Design & Construction Management

Land-use land-cover (LULC) changes are occurring rapidly in Southeast Asia (SEA), generally associated with population growth, economic development and competing demands for land. Land cover change is one of the vital factors affecting carbon dynamics and emissions. SEA is an important region to study urban-caused LULC emissions and the potential for nature-based solutions (NBS) and nature climate solutions (NCS), as it is home to nearly 15% of the world’s tropical forests and has some of the world’s fastest rates of urban growth. We present a fine-scale urban cluster level assessment for SEA of current (2015) and future (2050) scenarios for carbon sequestration service and climate mitigation potential. We identified 956 urban clusters distributed across 11 countries of SEA. Considering the urban expansion projected and decline in forests, this region could see a carbon loss of up to 0.11 Gigatonnes (Scenario SSP4 RCP 3.4). Comparing carbon change values to urban emissions, we found that the average offset value ranging from −2% (Scenario SSP1 RCP 2.6) to −21%. We also found that a few medium and large urban clusters could add to more than double the existing carbon emissions in 2050 in the SSP3 and SSP4 RCP 3.4 scenarios, while a minority of clusters could offset their emissions under SSP1. Our study confirms that NCS, and particularly reforestation, are in many cases able to offset the direct emissions from land cover conversion from SEA urban clusters. Hence, documenting the plausible LULC transitions and the associated impacts gains significance in the SEA region as the results can be useful for informing policy and sustainable land management., Peer Reviewed

Many developed countries have committed to targets to reduce their carbon emissions under international agreements. However, a recent 2021 study found that only one country, The Gambia, is on track to meeting its Paris targets. A key mechanism for achieving these national targets is the government. Therefore, the failure of most countries to meet their targets highlights the importance of evaluating the major policy alternatives. Australia instituted a carbon pricing scheme in 2012 that was repealed in 2014 and subsequently replaced with an emissions reduction fund in 2015. This provides a unique opportunity to study the effects of these two major alternative government policies on government salience. This study applies stakeholder theory and finds that the power and urgency of both policies was weakened by uncertainty, an often-neglected factor affecting stakeholder salience. Furthermore, we note that an evaluation of government salience must also consider firm and industry differences and the effect of positively versus negatively framed interventions.

Climate change has become a global concern, and the prediction of carbon emissions is key to achieving carbon-reduction goals. The existing framework cannot accurately reflect the spatial distribution of carbon emissions, making it difficult to guide urban planning and management. Therefore, in this study, a carbon emission spatial simulation and prediction model was established. The model includes the GIS-Kernel Density sub-model for subdividing built-up area, the Land Use-Carbon Emission sub-model for establishing the correlation between land use and carbon emissions, the Multi Objective Programming-Principal Component Analysis-BP neural network sub-model for presetting development scenarios, and the Patch-generating Land-use Simulation sub-model for predicting. Xi'an was chosen as the study site, and two extreme scenarios were determined. A total of 373,318 development paths were segmented from the interval, and the optimal path was selected. All scenarios were simulated, and the carbon emissions and their spatial distribution were calculated. The results showed that the overall accuracy of the simulation exceeded 90%. Under the optimal path, Xi'an's carbon emissions reach 60.6 million tons at peak time, which will be reduced to 47.38 million tons by 2060. In addition, the model analyzed the temporal and spatial changes of carbon sources and sinks and drew up the path of carbon reduction by technology and urban planning. This model can provide a reference for regional carbon-reduction planning and carbon reduction technology implantation. It can propose strategies from the perspective of planning and management.

Background. Using JavaScript frameworks has become a popular approach for developing web applications. However, the large bundle sizes associated with framework usage may not always be necessary from a sustainability standpoint. Utilizing a framework or not could potentially impact a web application’s performance and carbon emissions. Objectives. This study aims to identify sustainable approaches to frontend web development and investigate whether a comparable difference in performance, energy consumption, and carbon emissions exists between applications built using a framework like React.js versus those developed using vanilla JavaScript. Methods. A literature review was conducted to identify important factors for creating sustainable web applications from previously published materials. An empirical study was performed where two test applications were created; one developed in vanilla JavaScript and one using the React.js framework. Experiments on these prototypes compared performance and estimated carbon emissions on the applied technologies. Results. When researching literature published on sustainability within web development, the factor most frequently mentioned was web performance optimization. The results of the empirical study found that the application written in vanilla JavaScript achieved higher performance metrics and lower estimated carbon emissions than the prototype developed with React.js. Conclusions. This thesis has found that web performance optimization is an important, powerful, and easy-to-use approach for achieving more sustainable web applications. This study has found several important factors for creating sustainable web applications, which can significantly impact an application’s carbon emissions. The study found that the best-performing test application achieved the lowest estimated carbon footprint. This thesis recommends that developers make informed decisions and consider sustainability when choosing a development strategy, like

This thesis aims to explore the potential of virtual reality (VR) to promote sustainable behaviours. The literature review draws from various fields that discuss the advantages and limitations of VR in design experiences (Scurati, et al., 2021)and how VR can provide an overview on training and transfer, education, and procedural, cognitive and maintenance training (Psotka, 1995) In virtual reality and education and training paper Joseph Psotka provides a brief overview of existing VR research on. Contributing to this literature in VR and education for designing behaviour change with a sustainability focus, by utilizing VR technology, this research focuses on transforming a carbon calculator into an immersive VR environment with the goal of increasing users’ awareness of carbon emissions. Hence, this research allows individuals with little to no experience to create and be part of immersive experiences that effectively convey information and increase users’ awareness of carbon emissions. Adopting semi-structured interviews and digital material exploration as its research methodology, this study involves participants from different backgrounds and levels of knowledge about carbon emissions aiming to create an immersive experience that could effectively educate and engage users in understanding and addressing sustainability issues. Through the development of a hi-fi prototype, participants who tested the VR experience expressed an increased interest in learning about carbon emissions, indicating the potential of immersive VR in raising awareness and fostering behaviour change. The study was conducted in collaboration with Nordic Waves Group, a Denmark-based organization that focuses on UN’s 17 New World Goals, demonstrates the practical application of the research in a real-world context, aligning with their commitment to the Sustainable Development Goals. The findings of this study emphasize the potential of VR in promoting sustainable behaviours and highlight the imp, Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

The contemporary imperative of sustainable development has established an unprecedented degree of urgency, in view of the intransigent challenges posed by the persistent and ever-increasing energy and climate crises. In 2019, the Swedish building industry accounted for 21% of the nation’s total greenhouse gas emissions, with the structural framework of a building contributing to 34% of its overall emissions. In response to climate change and the housing demand caused by a growing population, sustainable construction solutions are needed. By substituting steel beams with timber beams, the carbon emissions caused by the building industry can be reduced significantly. This study investigates whether timber based, or steel-reinforced timber beams can provide comparable load-bearing capacity to steel beams while reducing carbon. How this impacts the cross-sectional height of the beams is also taken into consideration. Different load-bearing properties were calculated according to Eurocode using Excel for all the surveyed beams. The carbon emissions were calculated based on the weight of each beam combined with climate data obtained from the Swedish National Board of Housing, Building and Planning. Findings suggest that timber-based beams made from glulam or laminated veneer lumber exhibit moment capacity and bending stiffness on par with those of steel beams while reducing the carbon emissions drastically, but at the cost of increased cross-section height. Steel beams were identified as the main source of carbon emissions. Consequently, also making steelreinforced timber beams only marginally successful in reducing carbon emissions if at all.

The building sector contributes significantly to carbon dioxide (CO2) due to the high energy use in building material production. One of the most critical concerns the World Summit on Sustainable Development must address is saving energy. In order to reduce CO2 emissions and their impact on the climate, strategies such as reducing energy demand, increasing efficiency, and using renewable resources instead of fossil fuels need to be implemented. This study was conducted through a mix of qualitative and quantitative methods to examine the possibility of lowering energy use and emissions in columns. The main purpose is to examine the potential environmental impact and energy use using a lifecycle assessment (LCA) approach. Steel production contributes significantly to climate change because it uses a lot of energy and produces many greenhouse gases. In Sweden, the steel industry uses coal as the main fuel, as shown from the data collected. Various studies explore the potential for reducing greenhouse gas (GHG) emissions and improving carbon sinks, such as taking measures in the building, energy supply, and forestry industries. This study concludes that buildings can be designed to be more energy-efficient, with better materials that are energy-efficient and lower carbon emissions. Material substitution can reduce energy use and carbon emissions. The replacement of steel with wood in construction can significantly reduce carbon emissions. The research findings indicate that an effective strategy to enhance the sustainability of buildings during the production phase is to reduce energy consumption and carbon emissions by incorporating wood as a primary building material.

Pollution is one of humanity's most pressing problems. Although there are many types of pollution, air pollution is one of the main causes of global warming. Therefore, simultaneously improving environmental quality and economic growth, and studying the variables that affect this relationship, has been one of the key issues for researchers and policymakers in recent years, especially in the wake of the United Nations 2030 Agenda for Sustainable Development.This paper aims to estimate the relationship between carbon emissions, GDP per capita, renewable energy and non-renewable energy sources as well environmental taxes in G10 industrialized countries over the period 1972-2020. Regression analysis and panel data were used to answer the questions. Previous studies of the Ecological Kuznets Curve (EKC) for CO2 emissions, with most samples based on G10 member countries, have had mixed results. The environmental Kuznets curve shows that economic development initially leads to environmental degradation, but once economic growth reaches a certain level, the relationship between society and the environment begins to improve and the degree of environmental degradation decreases. From a very simple perspective, this might suggest that economic growth is good for the environment. Critics, however, argue that economic growth is not guaranteed to lead to environmental improvements, which can often backfire. At the very least, it requires very targeted policies and attitudes to ensure that economic growth goes hand in hand with environmental improvement., Tre helt olika miljö-/BNP-kurvorStudien undersöker etablerade teorier för att beskriva sambandet mellan miljöskador och ekonomisk aktivitet, inklusive Environmental Kuznets Curve (EKC), Brundtland Curve Hypothesis (BCH) och Environmental Daly Curve (EDC).

Nature-based solutions (NbS) are recognized as widely available and cost-effective mechanisms for sequestering carbon and offsetting carbon emissions. Realistic NbS implementations for carbon neutrality need to be effective at the global level and also appropriate for the socio-economic and physical conditions prevailing at the local level. This paper presents a framework that can help stakeholders identify demands, locations, and types of NbS interventions that could maximize NbS benefits at the local scale. Key processes in the framework include (1) interpolating carbon emissions data at larger spatial scales to high-resolution cells, using land use and socio-economic data; (2) assessing NbS effects on carbon reduction and their location-related suitability, through qualitative literature review, and (3) spatially allocating and coupling multiple NbS interventions to land use cells. The system was tested in Stockholm, Sweden. The findings show that the urban center should be allocated with combinations of improving access to green spaces and streetscapes, while the rural and suburban areas should prioritize preserving and utilizing natural areas. Our proposed method framework can help planners better select target locations for intended risk/hazard-mitigating interventions.

Based on the Environmental Kuznets Curve (EKC) theory, this research seeks to probe the impact of nuclear and renewable energy on carbon emissions in Pakistan. In order to analyze Pakistan's cointegration from 1990 to 2022, this study uses the ARDL technique. The findings provided empirical support for the Environmental Kuznets Curve (EKC) theory and demonstrated that the use of nuclear and renewable energy resources is linked to lower carbon dioxide (CO2) over the long term. Carbon dioxide emissions from burning fossil fuels, which are used for most of the world's energy needs, have been steadily rising in recent years. Policymakers recognize this and are working to reduce reliance on nonrenewable energy sources while increasing nuclear and renewable energy use.

Based on the Environmental Kuznets Curve (EKC) theory, this research seeks to probe the impact of nuclear and renewable energy on carbon emissions in Pakistan. In order to analyze Pakistan's cointegration from 1990 to 2022, this study uses the ARDL technique. The findings provided empirical support for the Environmental Kuznets Curve (EKC) theory and demonstrated that the use of nuclear and renewable energy resources is linked to lower carbon dioxide (CO2) over the long term. Carbon dioxide emissions from burning fossil fuels, which are used for most of the world's energy needs, have been steadily rising in recent years. Policymakers recognize this and are working to reduce reliance on nonrenewable energy sources while increasing nuclear and renewable energy use.

Renewable energies and low-carbon energy technologies have currently limited use in greenhouses. The use of sustainable energy technologies in many sectors, including agricultural greenhouses, is desirable and attractive for reducing the climate impacts of agriculture. Their maturity, reliability and cost-effectiveness has been proved and their use in many applications has been accelerated. Reports regarding net-zero energy and net-zero carbon emission greenhouses are limited so far. However, the global policies for climate change mitigation and creation of a net-zero carbon economy in the coming decades favors the use of benign energy sources replacing the polluting fossil fuels. The use of heat pumps and solar-PV systems for energy generation covering the needs for heat, cooling and electricity in an existing greenhouse located in Crete, Greece has been investigated. The combined use of these green energy technologies can eliminate the use of fossil fuels resulting in a net-zero carbon-emissions greenhouse. The size of the greenhouse studied was 3,300 m2, the nominal power of the solar-PV system generating all the required electricity was estimated at 254.23 KWel  and its installation cost at 233,052 €. A heat pump with COP equal to 3 and power at 254.23 KWel  can cover all the peak heat and cooling demand of the greenhouse while its installation cost is at 1,144,035 €. The total installation cost of the abovementioned benign energy systems is at 417.30 €/m2. Our research indicates that sustainable energy technologies can generate all the required energy in agricultural greenhouses zeroing their net-carbon emissions and promoting the carbon neutral agriculture.

This research project aims to investigate fuel tankering practices in the aviation industry, exploring their relation to carbon emissions and evaluating the Brazilian fuel tankering scenario in comparison to global and national policies and regulations. The study recommends sustainable national measures and compares global practices for minimizing the higher emissions due to fuel tankering. The results of the study show that the Brazilian aviation industry can sustainably neutralize the carbon emissions from the fuel tankering practice. The study recommends that airlines allocate part of the savings generated to purchasing carbon credits to offset the carbon emitted. Future research should focus on all members of the aviation ecosystem and external factors, including the fuel tankering post-pandemic scenario, the development of biofuels, and the global, cross-country analysis of fuel tankering strategies and their managerial processes.

Reducing carbon emissions from the construction industry has been vital to addressing the growing global environmental change challenge. Building energy consumption data is crucial to many applications, such as carbon emission auditing, energy efficiency improvement, etc. This study aims to mine the energy consumption patterns of commercial buildings and explore the applicability of a data-driven model in building carbon emissions prediction. This research selected Dalian's large-scale green commercial building as a case study. The electrical load data for the past four years were collected, and the indoor and outdoor environmental data were monitored under different seasons. Machine learning was used to develop building carbon emissions forecasting models. The average annual increase rate of building electricity consumption before the pandemic was 5.9%. Miscellaneous electric loads (MELs) is the largest electricity consumer in the target building. On typical days, indoor illuminance and CO2 are highly correlated under different seasons. A forecasting model based on ensemble learning is found to have certain advantages in building carbon emissions prediction. © 2023 Elsevier Ltd

This paper presents a mathematical model for a multi-period hydrogen supply chain design problem consider-ing several design features not addressed in other studies. The model is formulated as a mixed-integer program allowing the production and storage facilities to be extended over time. Pipeline and tube trailer transport modes are considered for carrying hydrogen. The model also allows finding the optimal pipeline routes and the number of transport units. The objective is to obtain an efficient supply chain design within a given time frame in a way that the demand and carbon dioxide emissions constraints are satisfied and the total cost is minimized. A computer program is developed to ease the problem-solving process. The computer program extracts the geographical information from Google Maps and solves the problem using an optimization solver. Finally, the applicability of the proposed model is demonstrated in a case study from Oman.

Background. Using JavaScript frameworks has become a popular approach for developing web applications. However, the large bundle sizes associated with framework usage may not always be necessary from a sustainability standpoint. Utilizing a framework or not could potentially impact a web application’s performance and carbon emissions. Objectives. This study aims to identify sustainable approaches to frontend web development and investigate whether a comparable difference in performance, energy consumption, and carbon emissions exists between applications built using a framework like React.js versus those developed using vanilla JavaScript. Methods. A literature review was conducted to identify important factors for creating sustainable web applications from previously published materials. An empirical study was performed where two test applications were created; one developed in vanilla JavaScript and one using the React.js framework. Experiments on these prototypes compared performance and estimated carbon emissions on the applied technologies. Results. When researching literature published on sustainability within web development, the factor most frequently mentioned was web performance optimization. The results of the empirical study found that the application written in vanilla JavaScript achieved higher performance metrics and lower estimated carbon emissions than the prototype developed with React.js. Conclusions. This thesis has found that web performance optimization is an important, powerful, and easy-to-use approach for achieving more sustainable web applications. This study has found several important factors for creating sustainable web applications, which can significantly impact an application’s carbon emissions. The study found that the best-performing test application achieved the lowest estimated carbon footprint. This thesis recommends that developers make informed decisions and consider sustainability when choosing a development strategy, like

The building sector contributes significantly to carbon dioxide (CO2) due to the high energy use in building material production. One of the most critical concerns the World Summit on Sustainable Development must address is saving energy. In order to reduce CO2 emissions and their impact on the climate, strategies such as reducing energy demand, increasing efficiency, and using renewable resources instead of fossil fuels need to be implemented. This study was conducted through a mix of qualitative and quantitative methods to examine the possibility of lowering energy use and emissions in columns. The main purpose is to examine the potential environmental impact and energy use using a lifecycle assessment (LCA) approach. Steel production contributes significantly to climate change because it uses a lot of energy and produces many greenhouse gases. In Sweden, the steel industry uses coal as the main fuel, as shown from the data collected. Various studies explore the potential for reducing greenhouse gas (GHG) emissions and improving carbon sinks, such as taking measures in the building, energy supply, and forestry industries. This study concludes that buildings can be designed to be more energy-efficient, with better materials that are energy-efficient and lower carbon emissions. Material substitution can reduce energy use and carbon emissions. The replacement of steel with wood in construction can significantly reduce carbon emissions. The research findings indicate that an effective strategy to enhance the sustainability of buildings during the production phase is to reduce energy consumption and carbon emissions by incorporating wood as a primary building material.

Background. Using JavaScript frameworks has become a popular approach for developing web applications. However, the large bundle sizes associated with framework usage may not always be necessary from a sustainability standpoint. Utilizing a framework or not could potentially impact a web application’s performance and carbon emissions. Objectives. This study aims to identify sustainable approaches to frontend web development and investigate whether a comparable difference in performance, energy consumption, and carbon emissions exists between applications built using a framework like React.js versus those developed using vanilla JavaScript. Methods. A literature review was conducted to identify important factors for creating sustainable web applications from previously published materials. An empirical study was performed where two test applications were created; one developed in vanilla JavaScript and one using the React.js framework. Experiments on these prototypes compared performance and estimated carbon emissions on the applied technologies. Results. When researching literature published on sustainability within web development, the factor most frequently mentioned was web performance optimization. The results of the empirical study found that the application written in vanilla JavaScript achieved higher performance metrics and lower estimated carbon emissions than the prototype developed with React.js. Conclusions. This thesis has found that web performance optimization is an important, powerful, and easy-to-use approach for achieving more sustainable web applications. This study has found several important factors for creating sustainable web applications, which can significantly impact an application’s carbon emissions. The study found that the best-performing test application achieved the lowest estimated carbon footprint. This thesis recommends that developers make informed decisions and consider sustainability when choosing a development strategy, like

Background. Using JavaScript frameworks has become a popular approach for developing web applications. However, the large bundle sizes associated with framework usage may not always be necessary from a sustainability standpoint. Utilizing a framework or not could potentially impact a web application’s performance and carbon emissions. Objectives. This study aims to identify sustainable approaches to frontend web development and investigate whether a comparable difference in performance, energy consumption, and carbon emissions exists between applications built using a framework like React.js versus those developed using vanilla JavaScript. Methods. A literature review was conducted to identify important factors for creating sustainable web applications from previously published materials. An empirical study was performed where two test applications were created; one developed in vanilla JavaScript and one using the React.js framework. Experiments on these prototypes compared performance and estimated carbon emissions on the applied technologies. Results. When researching literature published on sustainability within web development, the factor most frequently mentioned was web performance optimization. The results of the empirical study found that the application written in vanilla JavaScript achieved higher performance metrics and lower estimated carbon emissions than the prototype developed with React.js. Conclusions. This thesis has found that web performance optimization is an important, powerful, and easy-to-use approach for achieving more sustainable web applications. This study has found several important factors for creating sustainable web applications, which can significantly impact an application’s carbon emissions. The study found that the best-performing test application achieved the lowest estimated carbon footprint. This thesis recommends that developers make informed decisions and consider sustainability when choosing a development strategy, like