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Interpreting low-carbon transition at the subnational level: Evidence from China using a Natural Language Processing approach

https://doi.org/10.1016/j.resconrec.2022.106636Get rights and content

Highlights

  • Investigated how subnational governments interpret low-carbon transition.

  • Identified the shared, primary and innovative interpretations using NLP.

  • Subnational governments recognize no “one size fits all” transition pathways.

  • The interpretations are embedded in local socioeconomic contexts yet flawed.

  • Just transition is a missing element in the interpretations.

Abstract

Subnational governments play an important role in low-carbon transitions around the world. However, the concept of low-carbon transition requires detailed interpretations. Our study sheds light on this important gap by drawing evidence from China's low-carbon provincial and city pilots (LCPCs) using three natural language processing algorithms. Our study found that low-carbon transition was interpreted collectively as an economy-centered process. Five primary foci and the corresponding clusters were identified, which indicate the preferred transition pathways of the LCPCs and imply that the pilots recognized no “one size fits all” transitions. Innovative interpretations were found among LCPCs, which were largely embedded in local contexts and tied to unique local resources and actors. However, innovative interpretations with local embeddedness might not translate into effective policies. And "just transition" has been largely missing from the interpretation. The concept of low-carbon transition may still remain vague to the subnational policymakers at a more detailed level.

Introduction

Low-carbon transitions have been an important policy concept for tackling climate change and achieving carbon neutrality. Subnational actors such as city, state or provincial governments are increasingly central to climate governance (Hale et al., 2021; Hsu et al., 2019). While important gaps remain between necessary national government actions and global warming goals (especially those to limit the temperature rise well to below 2°C) (Rogelj et al., 2016; Victor et al., 2017), subnational actors have proven to be effective in filling these gaps in many countries such as the United States and in the European Union (Andonova et al., 2017; Hsu et al., 2020; Hultman et al., 2020). Not only can they implement national low-carbon targets, but they can also go beyond current national climate pledges and raise climate ambition through voluntary and entrepreneurial actions (Anderton and Setzer, 2018; Hsu et al., 2018).

There are studies that focus generally on the actions or strategies of subnational governments for low-carbon transition (Hsu et al., 2020; Wu et al., 2021). However, it is still not entirely clear how these governments arrive at their judgements of low-carbon strategies since the definition of low-carbon transition is often ambiguous and lack explicit definition, which allows for interpretive freedom (Broto, 2012; De Jong et al., 2015; Evans and Jones, 2008; Hunt and De Laurentis, 2015). There are also multiple, similar sustainability concepts that could be confused with the concept of “low-carbon”, such as “eco-friendly”, “green” and “resilient” (De Jong et al., 2015). In practice, subnational governments have to interpret this concept before developing specific strategies, and their perceptions and values impact the uptake of transition strategies (Olazabal and Pascual, 2015). Therefore, the scale and scope of the resulting low-carbon transitions may vary across different governments.

How subnational governments interpret low-carbon transition is therefore a major research gap, and decision-making remains a black box in the existing literature. For example, low-carbon transition can be defined narrowly as the process by which a country changes from using high carbon energy to using low carbon energy (Wu et al., 2020). A government would then only focus on strategies to decarbonize the energy system based on this narrow interpretation. On the other hand, it can also be understood more broadly as structural economic change – i.e., to meet emissions-reduction targets, low-carbon sunrise industries must grow rapidly while high-carbon sunset industries must decline rapidly (Semieniuk et al., 2021). In this case, one could also incorporate the standards of “just and equitable transitions”, such as job security and job creation, into low-carbon transition (Heffron, 2021).

Policymakers often combine their interpretations with limited evidence in order to reduce ambiguity, choosing only one of several possible ways to understand and solve a problem (Cairney et al., 2016). Therefore, it is crucial to uncover how subnational governments interpret the concept of low-carbon transition, since these interpretations largely determine the scale and scope of corresponding practices and whether subnational governments are able to choose the most effective strategies for reaching carbon neutrality (Cohen et al., 2005; Matland, 1995; Yanow, 1995). However, few studies have paid attention to subnational climate actions from this angle. This study aims to address the knowledge gap by drawing evidence from the low-carbon province and city pilot projects (LCPCs) in China - the largest national emitter of greenhouse gasses.

Subnational governments – including provincial and city governments – have played a significant role in China's climate governance and in catalyzing the country's 2060 carbon neutrality target (Zhao et al., 2022). The National Development and Reform Commission (NDRC) launched three batches of low-carbon province and city pilots in the years 2010, 2012 and 2017 to encourage low-carbon transition at the subnational level, and to experiment in transition feasibility for scaling-up. To date, a total of 81 cities and 6 provinces have been selected as LCPCs (Table 1). The identification of these pilots was based on the following criteria: local government leaders’ awareness of low-carbon development, application enthusiasm, accumulation of low-carbon development experiences, regional balances, and potential to be good examples (Wang et al., 2015).

Notably, despite the fact that the program was launched by the central government, it had no clearly stated objectives and mandatory practices. The central government neither enforced mandatory requirements such as carbon emissions reduction or energy efficiency targets, nor provided any fiscal or financial support to these subnational governments. And there were no regular assessments of the performance of these pilots. The program aimed to boost local initiatives and policy innovation for low-carbon development goals and pathways (Tie et al., 2020). As a result, the governments of the LCPCs had significant discretion to customize their low-carbon transition strategies (Liu et al., 2021).

Our study aims to answer two key questions: (1) How did subnational governments – specifically the governments of the pilots in China – interpret low-carbon transition? (2) What were the similarities and differences of interpretation among these subnational governments? Section 2 reviews the current literature. Section 3 details the data collection and methodology used in this study. Section 4 presents the research findings, grouped into three primary results. Section 5 concludes by discussing the implications of the research findings and the limitations of this study (Fig. 1).

Section snippets

Current research on the LCPCs

Low-carbon pilots in China have attracted significant attention from the research community in recent years. Existing studies have explored this topic from various angles, yet few studies have paid attention to the conceptual ambiguity of low-carbon transition and how it has been interpreted by these pilots. Some studies have focused on the initiation and development of the LCPCs and investigated why and how this policy emerged and developed in China's climate agenda (Khanna et al., 2014;

Methodology

Identifying how subnational governments interpret or scope low-carbon transition can be challenging as it is usually difficult to obtain unbiased and reliable data that can be systematically analyzed across cities and regions. Moreover, these interpretations are not just the opinions of individuals but organizationally-shared perceptions. Yet conventional methods including interviews, surveys and case studies are inherently subjective, as qualitative data collected from these methods largely

Shared interpretations of low-carbon transition among LCPCs

We set the value range of the number of topic K as 1 to 10 and iterated the LDA algorithm for each K value in order to obtain the optimal number of topics, which indicate the number of shared interpretations of low-carbon transition among LCPCs. The pyLADvis package was used to identify the optimal K through its visualization function. As a result, we found that each topic can be best identified when K=3, as a good topic model usually has big and non-overlapping bubbles scattered throughout the

Discussion

This study provides a holistic analysis of how subnational governments interpret the concept of low-carbon transition, drawing evidence from LCPC pilot projects in China. By performing text analysis using NLP algorithms, we first identified three shared interpretations – greening industries, decarbonizing energy sector and facilitating economic growth - among the LCPC pilots. We then distinguished five clusters of the LCPCs, each defined by a dominant interpretation of low-carbon transition:

CRediT authorship contribution statement

Ming Tie: Conceptualization, Methodology, Software, Formal analysis, Data curation, Visualization, Writing – original draft, Writing – review & editing, Funding acquisition. Mengye Zhu: Conceptualization, Methodology, Software, Formal analysis, Data curation, Visualization, Writing – original draft, Writing – review & editing, Funding acquisition.

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Ming Tie reports financial support was provided by R&D Program of Beijing Municipal Education Commission. Ming Tie reports financial support was provided by Beijing Information Science and Technology University Foundation.

Acknowledgments

This research is supported by the R&D Program of Beijing Municipal Education Commission (SM202111232004), and Beijing Information Science and Technology University Foundation (2035014).

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