Critical transformation pathways and socio-environmental benefits of energy substitution using a LEAP scenario modeling

https://doi.org/10.1016/j.rser.2020.110116Get rights and content

Highlights

  • A LEAP-Zhang model is established to analyze energy-related socio-environmental dynamics.

  • The energy-related GHG emissions are estimated for the Olympic year and peak year.

  • The environmental, economic and employment effects of renewable energy transition are estimated.

  • Feasible energy transition pathways are proposed for achieving socio-environmental benefits.

Abstract

A successful transformation from conventional to renewable energy can contribute to climate change mitigation and regional development. As the co-host city of the 2022 Winter Olympic Games and the only National Renewable Energy Demonstration Zone in China, Zhangjiakou urgently needs to transform its conventional energy-dependent industries. This paper establishes a Long-range Energy Alternatives Planning System (LEAP)-Zhang model to examine the environmental and socio-economic effects of renewable energy development in Zhangjiakou by projecting the energy consumption and associated greenhouse gas emissions by various sectors over the 2016–2050 period. Two scenarios are designed, i.e., the business as usual scenario (BAU) and the integrated scenario (INT) (including three sub-scenarios, i.e., renewable energy alternatives scenario (REA), industrial structure optimization scenario (ISO) and energy saving facility scenario (ESF)). Results indicate that under the INT scenario, Zhangjiakou's greenhouse gas emissions would peak in 2030 with 13.23% of lower energy consumption when compared with the BAU scenario. Compared with the conventional energy, renewable energy shows competitive advantages in terms of greenhouse gas reduction, employment opportunities and economic costs. The total number of employees would reach 0.15 million by 2050 under the INT scenario, 1.71 times more than that in the BAU scenario. Feasible low-carbon pathways and co-benefits strategies associated with industrial transformation and renewable energy substitution should be pursued in future actionable plans. Results found in this study could provide importance information for achieving renewable energy transformation and associated socio-environmental benefits within and beyond China.

Introduction

Global climate change is a growing concern for the international community. In 2018, the Intergovernmental Panel on Climate Change (IPCC) issued a special report, Global Warming of 1.5 °C, which stated that if we do not make unprecedented efforts to reduce greenhouse gas (GHG) emissions, we may reach 1.5 °C of global warming by as early as 2030 [1]. And a further increase in temperature from 1.5 °C to 2 °C may increase risks across the energy, food and water sectors, creating more extreme hazards, exposures and vulnerabilities that may affect a large percentage of the global population and a large number of regions [1]. The GHG emitted by an extensive fossil energy-dependent industrial structure cannot be ignored in the age of urbanization. Thus, there is an urgent need to reduce GHG emissions from fossil fuels in order to curb global warming and address corresponding socio-economic problems.

The intensive use of conventional energy in the electricity sector has brought considerable challenges to emerging energy substitution and transformation. The United Nations Framework Convention on Climate Change (UNFCCC) pointed out that the moment had come to reduce fossil-fuel subsidies or redirect them toward clean energy [2]. Currently, renewable energy—as the core of energy transformation—is globally expected to mitigate climate change. It is necessary to develop renewable energy, such as hydroelectric power and wind power, with minimal environmental impacts [3]. Moreover, along with conservation of the environment, the large-scale adoption of renewable energy sources could provide financial and economic opportunities and enhance social prosperity [4]. Employment opportunities are a key consideration in a low-carbon society. Thus, many countries are giving priority to the development of renewable energy for achieving climate goals while pursuing broad socio-economic co-benefits.

With the growing concern about various environmental problems caused by extensive fossil energy use, policy makers have shifted their focus onto energy transformation, leading to a significant increase in research on the prediction of alternative energy demands and resulting GHG emissions. It is crucial to forecast energy demands and GHG emissions when formulating energy plans [5]. A range of methods have been used to investigate future trends and policy alternatives for energy-saving and GHG reduction [6]. These methods can be characterized as top-down and bottom-up models.

The top-down models focus mainly on macro-economic factors, such as gross domestic product (GDP), population, and price elasticity. Typical models include the computable general equilibrium model (CGE) [7,8], the groundings enterprises markets model (GEM) [9] and the log-mean divisia index model (LMDI) [10,11]. Hübler and Löschel (2013), for example, analyzed the low-carbon development roadmap of the European Union at the macroeconomic and sector levels based on a CGE model. These models, however, cannot fully account for detailed technical aspects [12]. The bottom-up models include the market allocation model (MARKAL) [[13], [14], [15]], the Asian-Pacific integrated model (AIM) [[16], [17], [18]], and the long-range energy alternatives planning system (LEAP) model [[19], [20], [21]]. These models allow us to describe the energy supply, use and conversion technologies by modeling specific technical and economic parameters. These models show that technological progress is the main driving force for energy savings and emission reductions when compared with structural adjustment. Compared with top-down models, bottom-up models depict energy substitution-related technologies and their environmental and economic effects more comprehensively. More specifically, the MARKAL model focuses on the study of market distribution rules with market demand being the driving factor, while the AIM model pays more attention to the choice of energy technologies. Thus, both the top-down models and the bottom-up models have advantages and disadvantages; their applicability should be evaluated on a case-by-case basis, considering especially the research objectives (Table 1).

The LEAP model was developed by the Stockholm Environment Institute for analyzing energy policies and associated environmental impact. It can be used for long-term forecasting and scenario analysis of energy demand and the associated environmental problems in integrated resources planning [22,23]. Due to its advantages in alternative predictions, quantitative dynamics and policy settings, the LEAP model has been widely on different scales, from national to regional and sectoral scales [24,25]. For example, the LEAP model has been used to project energy demand and resulting air pollutants in many urban sectors, such as the industrial sector [26], [27], power sector [[28], [29], [30]], transportation sector [31,32] and the commercial sector [33]. In terms of the energy–carbon relationships, these analyses have focused mainly on future reduction potential and low-carbon transition pathways [[34], [35], [36]], indicating that improvement in energy efficiency and changes in energy structure have a significant impact on regional development.

Currently, the application of the LEAP model is focused on the environmental aspects of energy technologies on different scales and in various sectors. The focus of research is shifting from energy utilization on the demand side to energy upgrade on the supply side and associated environmental and economic benefits. It is vital to stress the socio-economic accessibility and environmental suitability of energy flows. Existing methods can reflect energy dynamics and associated environmental effects, but they fall short of capturing the potential socio-economic benefits. Thus, cross-boundary energy transfers and emerging energy transitions, as well as the accompanying socio-economic benefits, may lead to new management issues. These gaps call for clarification through further study. In addition, it is worth thinking about a sustainable clean energy solution in developing economies, namely, from the efficient power generation of large-scale fossil energy in the short term to the shift toward power generation using renewable energy in the long term [37].

The development of the world's energy has transitioned from fuelwood, coal, oil and natural gas to improving energy efficiency and developing renewable energy (hydro, nuclear, wind, solar, etc.) with the main aim of reducing carbon emissions. China has been actively engaged in global cooperation to address climate change issues. Although China has been a main GHG emitter, the carbon intensity of its GDP has been decreasing. In 2018, China achieved its goal to reduce the carbon intensity of its GDP by 40–45% by 2020. In a word, China's GHG emissions grew slower than expected [38]. In China, low-carbon efforts have been pursued in various fields, such as pilot low-carbon provinces and cities, the national carbon emissions trading system and the construction of ecological civilization [23]. As the only state-level renewable energy demonstration zone in China, Zhangjiakou could develop low-carbon strategies for other cities and provide socio-environmental benefits for the Beijing-Tianjin-Hebei metropolitan region.

This paper is one of the first studies to project the total urban energy consumption of Zhangjiakou city, located in the Beijing-Tianjin-Hebei metropolitan region in North China, and determine its peak GHG emissions. It aims to identify the contributions of renewable energy in the city's sustainable development by establishing a bottom-up model to help identify an optimal low-carbon pathway. The results will provide insights into the environmental and socio-economic impacts of renewable energy, help set GHG mitigation targets, and help develop a low-carbon roadmap to address non-GHG emissions.

In this paper, the LEAP-Zhang model is established to estimate energy consumption-related GHG emissions in seven urban sectors of Zhangjiakou city. The main objectives of this paper are:

  • (1)

    To analyze the future trends in energy consumption and GHG emissions in Zhangjiakou city from 2016 to 2050 under two scenarios and three sub-scenarios;

  • (2)

    To project energy-driven GHG emissions in key years, that is, the Winter Olympic Games in 2022 and the peak year, and to analyze the energy–carbon dynamics;

  • (3)

    To uncover the social, economic, and environmental benefits of energy substitution;

  • (4)

    To discuss the implications for future policies concerning renewable energy substitution, and to recommend alternative long-term policies for the development of low-carbon energy in Zhangjiakou city.

The rest of this paper is organized as follows: In section 2, research methods are introduced, including the basic LEAP-Zhang model, scenario design, and sensitivity analysis. In section 3, the case study is introduced, as well as related parameters and data sources of the LEAP-Zhang model. Section 4 presents the results of the case study, including total energy consumption, energy-driven GHG emissions in 2022 and the peak year, and potential socio-environmental effects. Section 5 and section 6 present the discussion and summaries of this paper, respectively.

Section snippets

LEAP-Zhang model

The LEAP model includes six modules, namely, resource supply, conversion, end-use demand, demand prediction, environmental impacts and cost-benefit analysis. The model can simulate future energy demands according to regional energy supply, transformation and consumption. It can also predict the environmental impact of a given energy scheme and calculate its costs from the perspectives of resources, transformation and utilization, relying on the embedded environmental database [39]. Compared

Case study

Zhangjiakou, an ecological buffer and water source for Beijing city, is located in the northwest upwind outlet of the Beijing-Tianjin-Hebei metropolitan district. In 2016, Zhangjiakou had a population of 4.43 million and a regional GDP of 146.11 billion yuan (20.84 billion dollars). In 2015, Zhangjiakou and Beijing were jointly awarded the hosting rights to the 2022 Winter Olympic Games. As a traditional industrial city, Zhangjiakou faces a great challenge in hosting “Green Olympic Games” due

Energy demand forecast

The total energy consumption forecast in Zhangjiakou from 2016 to 2050 under the BAU and the INT scenarios is shown in Fig. 3. Under the BAU scenario, Zhangjiakou's energy consumption would increase 2.13-fold from 26.90 million ton coal equivalent (Mtce) in 2016 to 84.21 Mtce in 2050. After implementing a series of energy-saving and emission-reduction policies and measures, the energy consumption under the INT scenario would decrease significantly. In 2050, Zhangjiakou's energy consumption

Discussion

In this study, Zhangjiakou city, a co-host city of the 2022 Winter Olympic Games and the pilot and only National Renewable Energy Demonstration Zone in China, is chosen as a case study of the potential effects of renewable energy development, due to its characteristics in available renewable energy and its socio-ecological transformation background. The LEAP-Zhang model is established to identify socio-economic effects and GHG emission reduction potential of renewable energy use, driven by

Conclusions

The LEAP-Zhang model is established to examine the socio-economic effects, and project GHG emissions, of renewable energy substitution in Zhangjiakou city between 2016 and 2050. The potential for energy savings and GHG reductions varies between urban sectors. The renewable energy has many socio-environmental co-benefits when compared to conventional energy. The main results of this study are as follows:

  • (1)

    The total energy consumption would continue to rise in the future, but under the INT

Credit author statement

Dewei Yang: Conceived, reorganized, performed and edited the paper; Dandan Liu: Conceived and performed research, analyzed data; Anmin Huang: Reviewed and edited the paper; Jianyi Lin and Lingxing Xu: Methodology, formal analysis, reviewed and edited the paper. All authors have read and agreed to the published version of the manuscript.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research was supported by the National Water Pollution Control and Treatment Science and Technology Major Project (2017ZX07101001), the Major Program of Natural Science Foundation of China (41690142), the Fundamental Research Funds for the Central Universities (SWU019047) and the Subsidized Project for Postgraduates' Innovative Fund in Scientific Research of Huaqiao University (18011121003).

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    Yang, D. and Liu, D. contributed equally to this work.

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