A review of assessments of the greenhouse gas footprint and abatement potential of information and communication technology

Bieser, Jan; Hintemann, Ralph; Hilty, Lorenz M.; Beucker, Severin

doi:10.1016/j.eiar.2022.107033

Cited by 33 publications

(10 citation statements)

References 62 publications

(105 reference statements)

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“…Besides, digital technologies themselves have a large environmental impact. Studies vary in their estimates, but it is reasonable to assume that in 2020, ICTs were accountable for 1.8 to 3.2% of global carbon emissions [35] which are expected to increase greatly in several decades. There is a big indeterminacy in the overall environmental impact of edge computing, distributed ledger technology (DLT) and 5G.…”

Section: Environmentmentioning

confidence: 99%

Major Green Technology Innovation and Implementation Mechanism

2023

Green Recovery With Resilience and High Quality Development

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Community renewal and carbon emissions. Community and block renewals will become the main method for Chinese urban renewal. Communities are the main places for city life and living. From international experience, improvements in the living quality of residents will generally lead to an increase in carbon emissions per capita. The core of community renewal and renovation, however, is to improve residents' living quality. Therefore, Chinese community/life carbon emissions may rise greatly in the future unless active interventions implementing green technologies and green lifestyles are adopted. If not, community renewal is likely to become a huge drag on achieving China's "Double Carbon" goal.The Chinese government advocates community green renovation. Since 2020, China has defined the renovation of urban old communities as significant livelihood projects and development projects [1], and put forward that by the end of the 14th Five-Year Plan, China will strive to complete the renovation of about 220,000 old, urban communities involving hundreds of millions of people, stimulating investment of up to one trillion RMB (≈ 154 billion USD). In July 2020, China printed and issued its Action Plan for Establishment of Green Communities, which advocates the idea of green development throughout the entire process of community design, construction, management, and service, and promoting environmental construction and renovation of communities by simple, moderate, green, low-carbon ways. With the gradual implementation of the Chinese urban carbon neutrality strategy, community green low-carbon renovation will gain more support from government policies and finance.Community green renovation is a key fulcrum of urban carbon neutrality solutions. Communities present themselves as the most practical and direct application

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Section: Environmentmentioning

confidence: 99%

Major Green Technology Innovation and Implementation Mechanism

2023

Green Recovery With Resilience and High Quality Development

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“…The development of digital technology is believed to enhance productivity. However, the improvement in resource (energy) efficiency may stimulate further expansion of energy demand (Pohl et al 2019, Wu et al 2023, Bieser et al 2023. The use of supercomputers shortens the research and development cycle, improves the efficiency of knowledge production and technological innovation, which may further increase the computational requirements in various fields, including science and industry.…”

Section: Mechanism Analysis and Research Hypotheses 221 Scale Effect-...mentioning

confidence: 99%

“…If the energy structure of the region is still dominated by fossil fuels, the construction of digital infrastructure will result in an increase in pollutant emissions. Moreover, digital technology may trigger environmental rebound effect, which is manifested in the reduction of product prices, stimulating consumer demand (Wu et al 2023, Bieser et al 2023. Alternatively, it may improve the efficiency of material and energy use, resulting in a swift expansion of production scale (Pohl et al 2019, Wu et al 2023, leading to a rapid increase in energy consumption and environmental pollution risks.…”

Section: Introductionmentioning

confidence: 99%

The impact of computing infrastructure on carbon emissions: an empirical study based on china national supercomputing center

Yang,

Wang

2023

Environ. Res. Commun.

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Digitalization is viewed as a potential solution to environmental sustainability issues. However, existing researches suggest that the environmental impact of digital technology is uncertain. This study focuses on the Chinese National Supercomputing Center (NSC), a large-scale computing infrastructure, and expands the correlation between digital infrastructure and green development from a computing perspective. We compare the carbon emissions of the NSC city with a group of synthetic cities created using synthetic control method, and find that the NSC may worsen regional carbon dioxide emissions. This result still holds true after a series of robustness tests. Mechanism examinations show that the NSC does not exhibit significant composition effect (energy structure improvement) and technology effect (green technology innovation), while scale effect (increase in energy demand and consumption) dominate the NSC's carbon emissions. Based on these findings, we consider that in addition to improving the energy efficiency of supercomputing centers, the adoption of cleaner renewable energy and the promotion of knowledge spillovers are crucial for achieving a green transformation for computing infrastructure.

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“…Although we can roughly describe the sources of the AI carbon footprint based on the perspective of the life cycle of AI devices, it is difficult to estimate the total amount of the AI carbon footprint now [8,12], because the boundary definition of the AI carbon footprint is blurry, and the related data and reliable evaluation methodology for estimating the quantity of the AI carbon footprint are also scarce [5]. We can only be sure that a substantial portion of carbon emissions from the ICT sector belongs to the AI carbon footprint [5].…”

Section: Sources Of the Ai Carbon Footprintmentioning

confidence: 99%

“…On the one hand, the application of AI can reduce worldwide greenhouse gas emissions [5]. On the other hand, the information and communication technology (ICT) sector, such as data centers, which are the critical infrastructure for training AI models, is generating a mass of carbon emissions [7,8]. Therefore, there has been a substantial need to combat climate change by using AI and limiting the carbon emissions from AI.…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Xie³

2023

Sustainability

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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.

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A review of assessments of the greenhouse gas footprint and abatement potential of information and communication technology

Cited by 33 publications

References 62 publications

Major Green Technology Innovation and Implementation Mechanism

Major Green Technology Innovation and Implementation Mechanism

The impact of computing infrastructure on carbon emissions: an empirical study based on china national supercomputing center

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

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