The scientific basis of ‘net zero emissions’ and its diverging sociopolitical representation

Becken, S.; Miller, G.; Lee, D.S.; Mackey, B.

doi:10.1016/j.scitotenv.2024.170725

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Hence, the CTM will start by investing in carbon reduction projects that lower the overall amount of anthropogenic greenhouse gas emissions released into the atmosphere and that generate profits both to maintain and update the CTM and to incentivize Service Providers to participate. We are aware that both parties involved (the Green Project that reduces its emissions and the stakeholders in the CTM that buy the carbon credits) should reduce their emissions, and that 'netting' with carbon offsets is increasingly problematic [43]. As the CTM becomes established, the profits generated may be used to cross-subsidize riskier and less profitable (but more needed) carbon removal projects that actively capture and remove carbon, storing it to prevent its release back into the atmosphere (sequestration).…”

Section: Carbon Investment: the Proposed Methodology To Finance Clima...mentioning

confidence: 99%

Using the Blockchain to Reduce Carbon Emissions in the Visitor Economy

Goean,

Font,

Xiong

et al. 2024

Sustainability

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The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization.

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Section: Carbon Investment: the Proposed Methodology To Finance Clima...mentioning

confidence: 99%

Using the Blockchain to Reduce Carbon Emissions in the Visitor Economy

Goean,

Font,

Xiong

et al. 2024

Sustainability

Self Cite

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“…All countries are facing tremendous pressure to reduce greenhouse gas (GHG) emissions (Wang et al, 2024), with most committing to targets that require reducing the GHG production of high-emitting individuals (Chakravarty et al, 2009;Becken et al, 2024). China ranked first as the largest contributor country for carbon emissions and, at the Paris Climate Conference, China proposed to achieve peak CO 2 emissions and to lower carbon emission intensity (CEI) by 60-65% by 2030 (Dong et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Exploring urban spatial heterogeneity and socio-environmental attributes of household greenhouse gas emissions

Yan,

Xu,

Liu

et al. 2024

Front. Sustain. Cities

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Understanding urban spatial heterogeneity of greenhouse gas (GHG) emissions from sectoral household consumption is crucial to facilitate moves towards low-carbon cities. In this study, we use Xiamen city of China as a case study to reveal the emission characteristics of household GHG as well as spatial heterogeneity. We conducted a face-to-face questionnaire survey and calculated GHG emissions of districts from household energy consumption, food consumption, transportation, housing, household waste and wastewater treatment. The GHG emissions and the amount of urban residential household consumption shows obvious spatial heterogeneity across districts. Total GHG emissions of Xiamen city were 8.39 Mt. CO2e, and average household and per capita of GHG emissions were 8.11 and 2.72 tCO2e, respectively. While total GHG emissions vary from 0.41 to 2.45 Mt. CO2e across six districts and range from 0.16 to 3.39 Mt. CO2e among six sectors. Household GHG emissions differ from 7.08 to 9.40 tCO2e, while the per capita emissions range between 2.41 to 3.14 tCO2e among districts. Results also showed that more urbanized areas with higher population density have larger total urban residential GHG emissions, whereas household emissions were comparatively lower in these areas. In contrast, our study did not show an (inverted-) U relationship or linear relationship between emissions and population, nor between emissions and income level. Household energy use is the largest sector emitting GHGs. These findings will be useful to underpin policy making towards low-carbon cities.

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