Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness

Wang, Delu; Wan, Kaidi; Song, Xuefeng; Liu, Yun

doi:10.1016/j.eneco.2018.11.004

Cited by 39 publications

(19 citation statements)

References 25 publications

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“…To control for price and wage adjustments, we analyse the economic effects of a coal phase-out in Germany through the lens of a dynamic general equilibrium model (DGE) with multiple sectors and regions. We evaluate the economic effects for different regional timing structures, similar to Wang et al (2019).…”

Section: Figure 1: Greenhouse Gas Emissions Of Germanymentioning

confidence: 99%

Power generation and structural change: Quantifying economic effects of the coal phase-out in Germany

2021

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The responsibility for discussion papers lies solely with the individual authors. The views expressed herein do not necessarily represent those of IWH. The papers represent preliminary work and are circulated to encourage discussion with the authors. Citation of the discussion papers should account for their provisional character; a revised version may be available directly from the authors. Comments and suggestions on the methods and results presented are welcome.

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Section: Figure 1: Greenhouse Gas Emissions Of Germanymentioning

confidence: 99%

Power generation and structural change: Quantifying economic effects of the coal phase-out in Germany

2021

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“…Similarly, Chu et al (2019) regard the internal funds within a bank as limited resources and allocate the funds among the branch banks to improve the effectiveness of fund utilization. Wang et al (2019) calculate the amount of coal demand in China's future production process, and then distribute the total amount of coal among China's provinces to achieve the optimal provincial coal de-capacity target in China. Baouche et al (2018) adapt the Origin-Destination matrix dynamic model to evaluate the energy consumption of electric vehicles, to allocate the charging station resources along a giving route in a way that achieves the optimal income and efficiency.…”

Section: Pm 25 Controlmentioning

confidence: 99%

How to optimize provincial PM2.5 reduction targets and paths for emerging industrialized countries? Fresh evidence from China

Pan

Dong

2021

Environ Sci Pollut Res

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Taking China as an example, this paper aims to design a path to reduce haze pollution in newly industrialized countries. Combined the principles of efficiency and equity, this study develops a Game Cross Equity Fixed Cost Allocation Model (Game-EFCAM) to optimize provincial PM 2.5 reduction targets and put forward haze reduction paths. The main results are as follows: (1) Among the three egalitarian principles, pay-ability egalitarianism is the fairest, which serves as the convergence principle of Game-EFCAM. (2) The "two mountains and two rivers" area has the largest PM 2.5 emission quotas, while the provinces in western China have small PM 2.5 emission quotas. In addition, the distributions of PM 2.5 emission quotas per unit of population, per unit of gross domestic product, and per unit of area all show significant regional clustering. (3) Shandong and Hebei have the largest amount of PM 2.5 emission reduction requirements, while Tianjin and Hainan have the smallest. Xinjiang and Beijing have the largest PM 2.5 reduction pressure indexes, while Tianjin and Shanghai have the smallest. This study not only helps China optimize provincial PM 2.5 reduction goals, but the proposed allocation method is also applicable to the overall planning of national resources utilization, and provides a reference to newly industrialized countries of haze reduction.

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“…Its total proved reserves stood at 141. 6 Gt by the end of 2019, behind only the U.S., Russia, and Australia [5]. Whilst production capacity had a difficult time keeping in step with rapidly growing consumption in the 2000's, a growth of investment in coal mining capacity at 32% p.a.…”

Section: Factors Determining China's Demand For Coal Importsmentioning

confidence: 99%

An installation-level model of China's coal sector shows how its decarbonization and energy security plans will reduce overseas coal imports

Gosens¹,

Turnbull²,

Jotzo³

2021

Preprint

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China aims for net-zero carbon emissions by 2060, and an emissions peak before 2030. This will reduce its consumption of coal for power generation and steel making. Simultaneously, China aims for improved energy security, primarily with expanded domestic coal production and transport infrastructure.Here, we analyze effects of both these pressures on seaborne coal imports, with a purpose-built model of China's coal production, transport, and consumption system with installation-level geospatial and technical detail. This represents a 1000-fold increase in granularity versus earlier models, allowing representation of aspects that have previously been obscured.We find that reduced Chinese coal consumption affects seaborne imports much more strongly than domestic supply. Recent expansions of rail and port capacity, which reduce costs of getting domestic coal to Southern coastal provinces, will further reduce demand for seaborne thermal coal and amplify the effect of decarbonisation on coal imports. Seaborne coking coal imports are also likely to fall, because of expanded supply of cheap and high quality coking coal from neighbouring Mongolia.Reducing the consumption of coal, used primarily in power generation and steelmaking, is a key element of net-zero emissions plans or other long-term low-emissions strategies. This will affect the market outlook for coal exporting countries, in particular as countries with domestic coal mining industries may seek to limit negative effects on domestic coal mining industries [1]. China's decarbonization plans are particularly relevant in this respect, as it is the world's largest consumer of both thermal and coking coal, and a large source of revenue for key exporters in the region, in particular Australia and Indonesia (Fig. 1).Global coal markets have been the subject of much earlier research, and China has been a focal country in most such studies given its dominant share in global coal production, consumption and imports. Yet, exactly how Chinese coal imports depend on domestic market and other developments remains poorly assessed.In particular, such previous studies have typically used linear cost optimization with so-called multiregional models, or node-and-link type models, to represent transport infrastructure. It's important to accurately account for transport in such analyses, given the large share of transport in the total cost of coal to consumers, and because of the restrictions imposed by technical transport capacities of this infrastructure such as railways and ports. However, previous work for such analyses has always used highly simplified networks, with even the most granular models using a few dozen nodes representing continents in global analysis, or provinces in China-focused analyses. These nodes conflate provincial-level production and demand into single points, and inter-provincial transport infrastructure into single links. This casts doubt on just how accurately transport costs and capacity limits are really considered, and therefore how accurately the rel...

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Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness

Cited by 39 publications

References 25 publications

Power generation and structural change: Quantifying economic effects of the coal phase-out in Germany

Power generation and structural change: Quantifying economic effects of the coal phase-out in Germany

How to optimize provincial PM2.5 reduction targets and paths for emerging industrialized countries? Fresh evidence from China

An installation-level model of China's coal sector shows how its decarbonization and energy security plans will reduce overseas coal imports

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