Agent-Based Modeling of Global Carbon Trading and Its Policy Implications for China in the Post-Kyoto Era

Zhu, Qin; Duan, Keran; Wu, Jing; Wang, Zheng

doi:10.1080/1540496x.2016.1152794

Cited by 15 publications

(9 citation statements)

References 16 publications

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“…Tang et al [22] explored the carbon emission trading scheme in China with an agent-based model. Zhu et al [23] simulated the global carbon trading system as well as impacts from various trading mechanisms. These studies point to the utility of agent-based simulations in modeling heterogeneous entities, complex behavior interactions, macro-pattern evolution, multi-hierarchical issues, etc.…”

Section: Introductionmentioning

confidence: 99%

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

Mohamed

Wang

2017

Sustainability

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Abstract:To assess whether China's emissions will peak around 2030, we forecast energy consumption and carbon emissions in China. We use an agent-based model driven by enterprises' innovation. Results show some differences in both energy consumption peaks and carbon emission peaks when we compare trends at different levels. We find that carbon emissions and energy consumption will peak in 2027 and 2028, respectively. However, the primary, secondary, and tertiary industries will reach energy consumption in different years: 2023, 2029, and 2022, respectively, and reach carbon emission peaks in 2022, 2028, and 2022, respectively. At the sectoral level, we find a wider range of energy consumption peaks and carbon emission peaks. Peak energy consumption occurs between 2020 and 2034, and peak carbon emissions between 2020 and 2032. Commercial and catering businesses, utilities and resident services, and finance and insurance achieve peak energy consumption and carbon emissions earliest in 2020, while building materials and other non-metallic mineral products manufacturing and metal products manufacturing are the two latest sectors to reach peak energy consumption and emissions, in 2034 and 2032, respectively.

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Section: Introductionmentioning

confidence: 99%

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

Mohamed

Wang

2017

Sustainability

Self Cite

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“…Other types of heterogeneity include distinct expectations about the profitability of investments (Kraan et al, 2018; Richstein et al, 2015; Zhu et al, 2018), different pricing rules due to specific mark‐ups or local monopolies (Wu et al, 2018), or even dissimilar R&D investment strategies (Chappin & Dijkema, 2009; D'Orazio & Valente, 2018; Isley et al, 2015; Lamperti et al, 2018). In addition, abatement options and costs may differ between firms (Lamperti et al, 2018; Lee & Han, 2016; Zhu et al, 2016; Zhu et al, 2018).…”

Section: Agents and Their Behavior In The Reviewed Studiesmentioning

confidence: 99%

“…Taxes (11) Gerst, Wang, Roventini, et al (2013), Chen et al (2013), van der Vooren and Brouillat (2015), Isley et al (2015), Monasterolo and Raberto (2016); Li (2017), Li and Strachan (2016); Kraan et al (2018), Wu et al (2018), Monasterolo and Raberto (2018), Rengs et al (2020) Emissions trading ( 11) Matsumoto (2008), Chappin and Dijkema (2009), Richstein et al (2014), Richstein et al (2015), Tang et al (2015), Isley et al (2015) Zhu et al (2016, Lee and Han (2016), Beckenbach et al (2018), Tang et al (2017), Zhu et al (2018) Subsidies ( 6 not assign it a main role. Exceptions are Walzberg et al (2017) and Safarzynska and van den Bergh (2018).…”

Section: Themes (# Studies) Policy Instruments Studiesmentioning

confidence: 99%

A review of agent‐based modeling of climate‐energy policy

Castro

Drews

Exadaktylos

et al. 2020

WIREs Climate Change

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Agent‐based models (ABMs) have recently seen much application to the field of climate mitigation policies. They offer a more realistic description of micro behavior than traditional climate policy models by allowing for agent heterogeneity, bounded rationality and nonmarket interactions over social networks. This enables the analysis of a broader spectrum of policies. Here, we review 61 ABM studies addressing climate‐energy policy aimed at emissions reduction, product and technology diffusion, and energy conservation. This covers a broad set of instruments of climate policy, ranging from carbon taxation, and emissions trading through adoption subsidies to information provision tools such as smart meters and eco‐labels. Our treatment pays specific attention to behavioral assumptions and the structure of social networks. We offer suggestions for future research with ABMs to answer neglected policy questions. This article is categorized under: Climate Economics > Economics of Mitigation

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“…The dynamic and constantly mutable ACE model is capable of properly simulating the economic system [32] using both theoretical and practical perspectives [33,34]. The ABM approach is applied in many fields and completely showed its ability to analyze social problems [35,36].…”

Section: Stimulating Interaction Between Demand and Supplymentioning

confidence: 99%

The Sustainable Existence of China’s Bicycle-Sharing Market: To Oversupply or to Disappear

Chen¹,

Qu²,

Chen³

et al. 2018

Sustainability

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Most cities in China benefit from having a commercial and public bicycle-sharing system. However, the bicycle-sharing markets still face unbalanced development problems, i.e., initial rapid expansion in most areas, and a recent disappearance in some local areas. Thus, the economic features and rules of this market need further exploration to introduce better management measures. Based on agent-based modeling, the current paper stimulated the interactions between supply and demand with two models to illuminate the supply characteristics of the bicycle-sharing market. The main findings included the following: (1) the bicycle-sharing market is governed by a set of objective laws which naturally require an oversupply, meaning that the attainment of a high level of user satisfaction depends on high supply; (2) based on each customer’s tolerance level, there is a supply density threshold that determines the existence and disappearance of the market; and (3) the width and elasticity of the supply density threshold are influenced by the tolerance of the customers, which, in turn, reflects their values and attitudes. The current research is a preliminary exploration of the interactive characteristics of supply and demand in the bicycle-sharing market. We believe that the current paper provides insights and implications to illuminate the law of existence in the bicycle-sharing market. It also includes a discussion on the sustainable development of the bicycle-sharing market in China.

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Agent-Based Modeling of Global Carbon Trading and Its Policy Implications for China in the Post-Kyoto Era

Cited by 15 publications

References 16 publications

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

A review of agent‐based modeling of climate‐energy policy

The Sustainable Existence of China’s Bicycle-Sharing Market: To Oversupply or to Disappear

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