Carbon Footprint Management Research Articles

Eco-Friendly Office Platform: Leveraging Machine Learning and GIS for Carbon Footprint Management and Green Space Analysis

This research focuses on developing an innovative platform to manage carbon footprint data related to office activities and monitor green spaces, integrating geoinformatics and machine learning technologies. The platform addresses the lack of automated systems for tracking carbon emissions, particularly in high paper consumption environments, such as those involving printing and photocopying. Additionally, it monitors green spaces within corporate settings, an aspect often overlooked in existing systems. The study demonstrates the platform’s capability to automate carbon footprint calculations and provide accurate assessments of green areas, achieving a high accuracy rate of 96.22% and a Kappa coefficient of 0.92. The results confirm the platform’s ability to deliver both comprehensive and granular environmental insights, supporting decision making for more sustainable office environments. The key novelty of this study lies in the integration of real-time data capture with geoinformatics and machine learning to efficiently track both carbon footprints and green spaces. This approach offers a practical solution to a gap in environmental data management in office settings, enabling organizations to align their practices with sustainability goals. The platform’s precise, automated system contributes significantly to the development of eco-friendly workplaces, highlighting its academic and practical value in the field of environmental sustainability.

Impacts on Regional Growth and “Resource Curse” of China’s Energy Consumption “Dual Control” Policy

Accurately evaluating the effectiveness of the energy consumption “dual control” policy can effectively solve serious the current environmental pollution and promote ecological civilization. However, researchers have rarely considered the impacts on the regional “resource curse” of the energy consumption “dual control” policy. A dynamic computable general equilibrium model (CGE) was built to evaluate the impacts on the regional “resource curse” of the energy intensity control and total energy control policy. The results showed the following. (1) The energy consumption “dual control” policy changes the supply-and-demand relationship of factors and reduces the crowding-out effect of humans and capital. (2) The energy consumption “dual control” policy has restrained GDP growth, and the total output and total investment have declined. However, the impact in regions without the “resource curse” is remarkable. (3) The energy consumption “dual control” policy has a significant inhibitory effect on major pollutants and carbon emissions. (4) The energy consumption “dual control” policy has played a positive role in breaking the regional “resource curse”. The areas with a high and low “resource curse” have become smaller, and the areas without the “resource curse” have increased significantly. The following suggestions are made: (1) increase the flexibility of the “dual control” policy of energy consumption, (2) establish an energy consumption budget management system, and (3) accelerate the establishment of a carbon footprint management system.

Carbon Footprint Assessment Based on Agricultural Traceability System Records: A Case Study of Onion Production in Southern Taiwan

This study proposes an improved methodology based on life cycle assessment (LCA), which is used to calculate the carbon footprint of agriculture, provides a simple and feasible calculation path, and constructs a streamlined framework for calculating the carbon footprint based on the agricultural traceability system records. Using important economic crop (Onion) as research subject, and choose the largest planting area in R.O.C. (southern Taiwan) as a case study. A total of 64 farm production history records have been collected, includes all of farms certified with a traceable agricultural products (TAP) label. Through a detailed analysis of the traditional carbon footprint calculation method, found that agricultural traceability system records could replace the data source in carbon footprint verification (CFV) process, and system records could be used as activity data after being organized. With our method, no need to go through a complicated CFV process, just download the existing data on agricultural traceability system, can start calculating carbon footprint as soon as possible. To compared to traditional assessment method, results show a margin of error is less than 6% compared to traditional assessment methods. Advantages of improved method were be found, such as easy data acquisition, simplified calculation steps, and improved data transparency and accuracy. From statistical data, show that at least seven categories of carbon emission sources for carbon footprints, the most significant of carbon emission impact are fertilizers. The result of improved methodology based on life cycle assessment (LCA), show that using the improved methods can help promote the carbon footprint management efficiency of agricultural organizations such as Farmers’ Association or Agricultural Production Marketing Group, promptly monitor the carbon footprint status of their fields and adjust strategies to reduce carbon footprints in real-time, advancing towards the goal of net-zero carbon emissions.

Raising data availability and quality for improved disruption and carbon footprint management through a novel approach to primary data sharing: Virtual Watch Tower / VWT

Abstract The global supply chain and logistics industry is a self-organizing ecosystem consisting of numerous actors that work together to move goods from end to end. The different stakeholders involved are usually interdependent organizations, like freight forwarders, carriers, terminals, and homeland security agencies and information exchange between them is required to coordinate the activities along the individual transport chains. However, the exchange of information has often been analog, flawed, late, and incomplete. New circumstances, like unprecedented supply chain disruptions, new regulatory requirements around greenhouse gas (GHG) emissions, and generally growing shipper expectations create an urgent need for improved data sharing between actors. New technologies, like digital platforms, networks, and architectures as well as social media, mobile, analytics, cloud, and internet of things (SMACT) have brought some improvements, but not the required holistic digital perspective required or expected. Averages and approximations are usually insufficient to close data gaps, e.g., only primary data allows for accurate GHG emission calculations. Primary data sharing is widely seen as the missing piece of the puzzle. Primary data is data from the source providing an accurate state and picture of a situation. Primary data sharing at scale requires a new form of digital collaboration. We propose a rethink of digital collaboration as a means for broader primary private data sharing for complete end-to-end datasets and data quality, particularly focusing on the sharing of data associated with both transport plans and progress made in the respective movements of goods for more better disruption and carbon footprint management through more accurate calculations of estimated times of arrival (ETA) and GHG emissions. We introduce an example for digital collaboration in end-to-end supply chains that is focusing specifically on primary data sharing. The new thinking around digital collaboration manifests itself in the Virtual Watch Tower / VWT initiative (www.virtualwatchtower.org). In 2022, RISE and Singapore Maritime Institute signed a collaboration agreement focused on innovation in shipping. The VWT initiative is the first collaborative project under the umbrella of this partnership. The VWT is led by RISE, A*STAR, and VTT. VWT is a community-driven, digitally empowered initiative, a cargo owner-driven, and terminal-centric approach for improved supply chain management. It is the users themselves who co-create and co-evolve the solution that they need. The initiative aims to create a community that shapes the digital tool (VWTnet) they need to reach the required higher levels of visibility. This, through primary data sharing across the supply chain ecosystem and between actors (VWT Users) participating in individual end-to-end transports (VWT Shipments). The VWT serves as an object of research to hone the new thinking and understand the implications of its implementation.

Water and Carbon Neutral Buildings: systemic approaches and hybrid strategies

Abstract In order to achieve a real green transition in the design, construction and use of the built environment, especially in contemporary urban contexts, it is necessary to assess the water saving benefits combined with binding energy efficiency and climate neutrality targets in a holistic manner. This approach cannot focus on stand-alone requirements. Special emphasis is placed on technological solutions that transform energy and water consumption from negative to positive at all stages of the life cycle, including construction and operation. The aim is not just to reduce expenditure, but to increase the effectiveness of the savings through an effective and cyclical approach over the long term. This paper presents the results of a research project that develops a set of integrated indicators in accordance with the Itaca Protocol standard, UNI/PdR Practice 13.0:2019, with the introduction of elements from the Level(s). The environmental indicator system is designed to simultaneously assess the requirements of water-neutral and carbon-neutral construction, in line with EU recommendations C/2021/2279 and C/2021/9332. The hybrid water-energy strategies used in the application of this system are evaluated in terms of their potential to achieve the aforementioned goals. This approach, illustrated by best practice examples, aims to provide a holistic assessment of the environmental performance of integrated buildings in contemporary urban contexts, taking into account both water efficiency and carbon reduction. The objective is to guide the technological design and construction of sustainable buildings, promoting a synergetic approach to water and carbon footprint management, starting from the case study of a building in Palermo.

Analysis and Reflection on the Strategy Benchmarking of Power Battery Management in China and Europe

In 2023, the European Union (EU) enacted the Regulation on Batteries and Waste Batteries (hereinafter referred to as the New Law on Batteries), which strengthens the regulatory framework for the entire lifecycle of power batteries. This development presents both challenges and opportunities for global power battery manufacturers and operators. As a significant player in the global power battery industry chain and the world’s largest producer of electric vehicles and power batteries, China must systematically assess the impact of global battery management strategies, including the EU’s New Law on Batteries, from a lifecycle perspective. This understanding is crucial for maintaining China’s competitive edge in the global power battery market and achieving mutually beneficial outcomes in international trade negotiations. This paper constructs a strategy analysis framework based on the lifecycle approach. By summarizing the power battery management strategies of both the EU and China, it provides a comprehensive overview of strategies across different countries, highlights the key regulatory focus areas, and offers relevant strategy recommendations. The main conclusions and insights are as follows: (1) The New Law on Batteries achieves lifecycle regulation from “cradle” to “grave” and back to “cradle”. (2) China emphasizes the management of waste power batteries, with an increasingly robust strategy system at the recycling stage, yet lacks comprehensive measures for other lifecycle stages. (3) The EU has established a comprehensive lifecycle strategy management system centered on the New Law on Batteries, characterized by strong coordination and a synergistic combination of strategies across different sectors. Finally, this paper identifies three major compliance challenges posed by the New Law on Batteries, necessitating enhanced strategy development and implementation in the areas of carbon footprint management, circular economy, and digital battery passports.

Real-world implementation of a cloud-based MPC for HVAC control in educational buildings

In their quest to enhance energy efficiency and carbon footprint management, many enterprises are turning their attention towards optimizing their facilities through amplified data monitoring and innovative control methods. In this context, this research highlights a practical solution in a commercial building located in the United States. It explains the creation, implementation, and costs of a universally applicable model predictive control (MPC) framework for the building’s heating, ventilation, and air conditioning (HVAC) system. The paper elaborates on both the hardware and software used to accumulate pertinent data and the formulation of the MPC system. This approach leverages cloud-based microservices and can be seamlessly integrated into current building management systems. In this regard, this paper presents three innovative strategies: Proportional–integral (PI)+Preheating, MPC, and occupancy-based control. These scenarios were designed to improve energy efficiency and thermal comfort significantly by reducing temperature fluctuations and adhering more closely to the setpoint temperature. The implementation of these strategies resulted in substantial energy savings, with reductions in energy consumption of 12.83%, 19.21%, and 14.98%, respectively.

Data-Driven Carbon Footprint Management of Electric Vehicles and Emission Abatement in Electricity Networks

Electric vehicles (EVs) are believed to play an important role in mitigating carbon emissions in the transportation sector. However, EVs may still cause carbon emissions in the power sector if they are charged by electricity generated from burning fossil fuels like coal. Researchers have focused on managing emissions on the power generation side. However, the underlying driver of carbon emissions is the demand of consumers. To this end, a probabilistic carbon footprint management strategy is proposed for EVs in this paper. First, the conventional deterministic carbon emission flow model is extended to a probabilistic one (PCEF) to track the carbon footprint of EVs considering various uncertainties based on non-intrusive load monitoring (NILM) and the two-point estimation method (2PEM). Second, a stochastic chance-constrained carbon footprint management model for EV charging is proposed to address the carbon obligation allocation of EVs from the perspective of consumption and provide a technical basis for demand-driven stimulation to reduce carbon emissions. Third, a solution methodology is proposed to solve the formulated chance-constrained problem based on nonparametric Bayesian modeling and inference. The proposed model and methodologies are verified on the IEEE 39-bus system. The feasibility of the proposed PCEF model is validated. According to the simulation result, the computation speed of the proposed PCEF model is improved from 3456.8 seconds to 1341.3 seconds compared with the Monte Carlo simulation by sacrificing the accuracy within 2%. Besides, the proposed emission control strategy can realize a better emission control performance compared with the other state-of-art works. Compared with the base case, the total emission is reduced by 82 tons annually, and the emission reduction rate is increased by nearly twice.

Incorporation of artificial intelligence toward carbon footprint management in hotels to create sustainable, green hotel: Mini review

Incorporation of artificial intelligence toward carbon footprint management in hotels to create sustainable, green hotel: Mini review

A novel lightweight CF decision-making approach for highway reconstruction and operation

Road infrastructure is a major emitter of greenhouse gases (GHGs), contributing significantly to the overall carbon emissions of many countries. Due to their importance in the life-cycle carbon footprint (CF) assessment of highway projects, highway reconstruction, rehabilitation, and operation have garnered increased attention. Existing highway CF studies have relied heavily on on-site data. They were often limited by a handful of operation or reconstruction scenarios. Most existing highway CF studies focused solely on mitigating the infrastructure CF and ignored the potential savings of highway traffic CF resulting from different traffic behaviour and technology options. A comprehensive CF saving potential comparison between the highway infrastructure and traffic for the city- or nation-wide policy decision-making is needed. Moreover, the loss of design and operation information for many existing highway projects with long operational periods necessitates a new approach to assess and manage the CF of highway reconstruction, rehabilitation, and operation. As a result, this study has proposed a new lightweight CF decision-making approach to help highway reconstruction, rehabilitation, and traffic operation management with informative stage-based highway decision-making supporting framework and digital platform that enable the comparison between highway infrastructure and traffic CF's potential savings. With the help of the developed framework and platform, the project decision-maker and government policymaker can leverage better information support and dynamically compare CF decision-making scenarios regarding different highway infrastructure and traffic options. This study contributes to knowledge in three ways: (1) evaluating and validating an informative highway CF decision-making framework for highway infrastructure and traffic assessment and management, (2) proving the applicability of using a lightweight data collection and model building method for highway infrastructure CF assessment and management practice, and (3) providing an applicable way of building a highway CF digital twins (DT) platform for visualisation, decision-making, and management of the highway infrastructure and traffic.

Carbon reduction performance and economic analysis in building construction - a pilot trial of low-carbon construction in the O•PARK2 construction phase

With the wide application of green building standards to reduce the carbon emissions from the operation phase, the carbon emissions during the construction phase are becoming more and more significant. Carbon footprint management is necessary and low-carbon measures, including low-carbon construction materials, construction site electrification, on-site renewable energy systems, and low-carbon alternative fuels should be considered. Taking a real case of a Design-Build-Operate project, O•PARK2, as a pilot trial, this study investigates the carbon reduction efficiency and cost increment of various low-carbon measures, and introduces the Green Premium Index to explore the tradeoff between carbon reduction and carbon offsetting by credit purchasing. Low-carbon measures adopted in O•PARK2 were proved to be carbon reduction efficient, achieving 4,612 tonnes of CO2e emission reduction. Early development of decarbonisation strategy enables further emission reduction and lower cost increments during the construction phase, in which low-carbon construction material should be prioritised, followed by construction site electrification, and the use of solar panels and B5 biodiesel. With low-carbon construction materials locally manufactured, construction decarbonisation progress in Hong Kong will be significantly enhanced. Lowcarbon construction should see carbon reduction as the main direction, and carbon offsetting as supplemental.

An insight into seasonal variations in food waste characteristics and associated carbon footprint management

The abundant stockpiling of food waste (FW) which leads to climate change has been a growing concern over its carbon footprint (CF) in recent years. In India, student enrollment in higher education has been increasing in recent years, reaching close to 4 billion, especially in universities. The present study aims to identify varying characteristics of FW generated in a university hostel mess due to temporal and seasonal conditions. This study evaluates consumer attitudes and behaviors concerning FW, and artificial neural networks are also used to forecast the percentage of FW streams based on various characteristics. FW characters were found to vary with time and temperature. High moisture content during autumn and winter seasons was found to decrease destructible solids content, a key parameter governing biogas generation. Statistical assay of FW quantity shows that FW generation is high during the weekdays followed by Saturdays, whereas during festivals and Sundays, the generation is highly variable, which might be due to the presence of inmates during holidays. Based on data from six months sample data set, it is projected that 716.57 ​kgs of food were wasted per day with 1361.48 ​kgs carbon dioxide equivalent (CO2 eq.) related CF. It showed that parameters such as household wealth, meal contentment, meal days, education, sex, and food-saving efforts significantly impacted the CF of FW. The avoidable FW can be stopped nonetheless to prevent shadowed CF. It can be concluded that effective FW management can be done by varying number of collection points, where FW accumulation varies in a year, enabling an efficient source sorting process. This will help in transferring the FW to proper treatment and management process like anaerobic digestion and composting. The Anaerobic digestion pose an efficient methods of FW management due to its high potency in biogas production.

Agro-tactics for reducing carbon footprint in agricultural production systems: A review

Over the last half-century, global attention has focused on climate change, particularly changes in air temperature. Concerns about the sustainability of the Earth’s ecosystems and other human life on the land are increasing along with population growth, rising surface temperature, and higher greenhouse gas (GHG) emissions. Agriculture is responsible for ~18% of total GHG emissions. Therefore, mitigating the effects of climate change by reducing GHG emissions is essential and can be achieved by careful evaluation of the carbon footprint (CF). The goal of this study was to gain a better understanding of the changes in CF due to agricultural management practices. Carbon footprint is a popular concept in agro-environmental sciences owing to its role in the environmental impact assessments related to alternative solutions and global climate change. The CF of agricultural products is one of the most crucial indicators to assess the effectiveness and long-term viability of agricultural products. Soil-moisture content, soil temperature, porosity, and anoxic conditions are some of the soil properties directly related to GHG emissions. The GHG emissions are also affected by different land-use changes, soil types, and agricultural management practices. Globally, better soil-management techniques can alter atmospheric GHG emissions. Therefore, the relation between photosynthesis and GHG emissions is impacted by agricultural management practices, especially focusing on soil and related systems. When maximizing crop productivity, environmental factors, land use, and agricultural practices all should be considered in CF management. The current review highlights the importance of CF and its role in maintaining the sustainability of agricultural systems.

AI Carbon Footprint Management with Multi-Agent Participation: A Tripartite Evolutionary Game Analysis Based on a Case in China

AI is playing an important role in promoting sustainable development, but the carbon footprint caused by AI is scaling quickly and may partly offset the effort to reduce carbon emissions. However, recommendations for limiting the AI carbon footprint are lacking. In order to address this gap in the literature, this paper first constructs a tripartite evolutionary game model by taking governments, AI industry alliances, and consumers into consideration, and then exploring the impacts of key factors on these three players’ strategy selection based on the case of smart air conditioner consumption in China. The results show that the behavior of governments has an important influence on the behavior of AI industry alliances and consumers. The ideal consequence is that governments adopt an unregulated strategy, AI industry alliances adopt a green development strategy, and consumers adopt a green purchase strategy. Regulation by governments is indispensable for limiting the AI carbon footprint during an early stage but becomes dispensable when the system reaches an optimal state. Although a tendency toward green consumption, image benefit, regulatory cost, carbon price, and the subsidies given to consumers and AI industry alliances can largely influence the strategy selection of governments, governments are most sensitive to carbon prices and the subsidies given to consumers. AI industry alliances are not sensitive to subsidies, reputation improvement, and reputation loss but are most sensitive to carbon prices. Consumers are most sensitive to green consumption tendencies, self-satisfaction, and utility but are not sensitive to subsidies.

A systematic literature review of carbon footprint decision-making approaches for infrastructure and building projects

There is an urgent need for all industries to go beyond the existing set of policies against greenhouse gas (GHG) emissions to combat climate change. As the major producer (19%) of GHG, the construction industry needs to optimise its carbon footprint (CF) decision-making processes to provide better management solutions against global warming. Identification and evaluation of the key factors that affect CF decision-making are critical yet limited. Based on our knowledge, no existing study compares the different characteristics of construction projects’ CF management approaches through the whole life cycle phases (including assessment, optimisation, and comparison) to enable CF-related knowledge transfer between the building and infrastructure sectors. To meet these knowledge gaps, this paper reviewed 1,465 studies related to infrastructure and building CF projects and selected 31 studies to evaluate academic researchers’ contributions toward the different CF decision-making stages for the building and infrastructure projects’ whole lifecycle. The paper systematically reviewed and assessed the existing information in five key CF decision-making stages: project drafting stage, methodology choosing stage, data collection stage, CF analysis stage, and CF visualisation stage. A generalised CF decision-making framework is also developed to inform future CF management. The limitations of the existing studies and the benefits of the developed framework were summarised. This study identifies the key information required from the perspective of CF management decision-makers and contributes a universal CF decision-making framework for state-of-the-art CF management practice.

Carbon emissions modeling for smarter carbon footprint decisions: A systematic review

Climate change and environmental deterioration due to greenhouse gas emissions are a major concern around the globe today. This article aims to highlight how various authors have carried out carbon emissions modeling for smarter carbon footprint management and also proffer solutions to the greenhouse gas emissions issue, which is giving rise to global warming and natural disasters across the globe. This study makes use of the Systematic Literature Review (SLR) methodology for identifying, analyzing, and synthesizing articles published from 2015 to 2020, a period of 6 years, on the topic of carbon emissions modeling. The SLR results indicated that there has been a rising interest in the issue of carbon emissions from the period of 2015 to 2020, as seen by the evolution of publications in the area. This can be explained by the increased incidence of natural disasters occurring as a result of the global warming phenomenon due to greenhouse gas emissions. The various ways in which different models have been used for carbon emission analysis and management have been described, while explaining various means by which greenhouse gas emissions can be curtailed to stop the alarming rate of global warming and maintain a sustainable and habitable planet for all.

Consensus reaching mechanism with parallel dynamic feedback strategy for large-scale group decision making under social network analysis

With the scale of group decision making increasing, it is a crucial issue to get the utmost of collective intelligence for seeking the optimal solution. In this study, we propose an automatic consensus reaching process (CRP) for large-scale group decision making (LSGDM) based on parallel dynamic feedback strategy and two-dimensional scenario-based social network analysis (SNA) model. Firstly, individuals express their preferences by distributed preference relations (DPRs) which could keep the uncertainty of assessment and allow multi-attribute comparison. Secondly, SNA based on trust relationship and connection strength is implemented. Then a two-dimensional scenario-based SNA model is established, and a fuzzy clustering algorithm based on connection strength is designed to reduce the scale of decision makers (DMs). Finally, a two-phase CRP with identification rules and feedback strategy is constructed. Identification rules are used for activating different kinds of feedback mechanisms by identifying whether it reaches acceptable local or global consensus. The rules also identify which kind of social relationship for internal or external subgroups and what dominance does individual or subgroup has. Feedback strategy with parallel dynamic adjustment process is further designed based on opinion and trust adjustment factors and non-cooperative behaviors. A real illustrative case for selecting the optimal carbon footprint management provider is presented to demonstrate the validity of our proposed method, and further compare it with other current methods.

Carbon Footprint Management by Agricultural Practices.

Simple SummaryMinimizing the effects of climate change by reducing GHG emissions is crucial and can be accomplished by truly understanding the carbon footprint phenomenon. This study aims to improve the understanding of carbon footprint alteration due to agricultural management and fertility practices. It provides a detailed review of carbon footprint management under the impacts of environmental factors, land use, and agricultural practices. The results show that healthy soils have numerous benefits for the general public and especially farmers. These benefits include being stable and resilient, resistant to erosion, easily workable in cultivated systems, good habitat for soil micro-organisms, fertile and good structure, large carbon sinks, and hence lower carbon footprint. Intensive tillage is harmful to soil structure by oxidizing carbon and causing GHG emissions. If possible, no-till; if not, minimum tillage frequency and depth of tillage, and optimum moisture are recommended. The soil should be at an appropriate level of moisture when tillage takes place. Diverse cropping systems are better for the soil than monocultures. Minimizing machinery operations can help to avoid soil compaction. Building soil organic carbon in the most stable form is the most efficient practice of sustainable crop production.Global attention to climate change issues, especially air temperature changes, has drastically increased over the last half-century. Along with population growth, greater surface temperature, and higher greenhouse gas (GHG) emissions, there are growing concerns for ecosystem sustainability and other human existence on earth. The contribution of agriculture to GHG emissions indicates a level of 18% of total GHGs, mainly from carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Thus, minimizing the effects of climate change by reducing GHG emissions is crucial and can be accomplished by truly understanding the carbon footprint (CF) phenomenon. Therefore, the purposes of this study were to improve understanding of CF alteration due to agricultural management and fertility practices. CF is a popular concept in agro-environmental sciences due to its role in the environmental impact assessments related to alternative solutions and global climate change. Soil moisture content, soil temperature, porosity, and water-filled pore space are some of the soil properties directly related to GHG emissions. These properties raise the role of soil structure and soil health in the CF approach. These properties and GHG emissions are also affected by different land-use changes, soil types, and agricultural management practices. Soil management practices globally have the potential to alter atmospheric GHG emissions. Therefore, the relations between photosynthesis and GHG emissions as impacted by agricultural management practices, especially focusing on soil and related systems, must be considered. We conclude that environmental factors, land use, and agricultural practices should be considered in the management of CF when maximizing crop productivity.

Carbon footprint management: A review of construction industry

Climate change is happening now, it is increasing presently, it is affecting us even more, and it will have a massive impact on us unless immediate and systemic action is taken to reduce and respond to its devastating consequences. One of such actions is the management of carbon emission from the construction industry, as it is one of the major sectors that contributes a substantial amount of greenhouse gases into our environment. Several efforts were made by many researchers towards developing various standards, techniques, and tools to assist in the management of the greenhouse gas emission from the industry. Some of these efforts include the green building concept itself, development of various rating systems, and sustainable construction materials. As such, this paper reviewed the several contributions of these researchers across the globe towards this dimension. And, after a thoroughly analysis of some of these contributions, it was found that there are inadequate research findings on the interconnected relationship between different drivers that are linked to low-carbon construction, highlighting the significant need for the establishment of an internationally recognized rating system under the United Nations which will include the measurements and quantification of the carbon footprint as one of its main parameters.

Green Computing and Carbon Footprint Management in the IT Sectors

The focus of the current research is on making computers as energy-efficient as possible, and applying innovative ideas to energy-related computer technology. It is anticipated that green information technology (IT) will rapidly become a reality and official organizational policy. Thus, green IT is not merely restricted to environmental strategies but is concerned with the overall development of people and society as a whole. In this regard, collaboration is to be explored to optimize business. This article examines the importance of green computing in sectors such as IT, networking, industries, and corporations.