Pursuing air pollutant co-benefits of CO 2 mitigation in China: A provincial leveled analysis

Dong, Huijuan; Dai, Hancheng; Dong, Liang; Fujita, Tsuyoshi; Geng, Yong; Klimont, Zbigniew; Inoue, Tsuyoshi; Bunya, Shintaro; Fujii, Minoru; Masui, Toshihiko

doi:10.1016/j.apenergy.2015.02.020

Cited by 227 publications

(75 citation statements)

References 33 publications

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“…In terms of the relationship between urbanization and industrial pollutant emissions, Kanada et al [21], Qin et al [22], and Dong et al [23] studied the way in which urban population growth impacted local pollution levels and indicated that as the urban population became richer, the demand of private transportation and electricity sharply increased; thus, the activities and demands of individuals exacerbated urban pollution externalities. However, Tao et al [24] obtained an opposite result arguing that the overall quantity of pollutant discharge decreased as cities became more economically developed during the period from 2000 to 2010, and they attributed such positive effect to higher urban production efficiencies.…”

Section: Literature Reviewmentioning

confidence: 99%

Urbanization and Its Effects on Industrial Pollutant Emissions: An Empirical Study of a Chinese Case with the Spatial Panel Model

Jin

2016

Sustainability

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Abstract:Urbanization is considered a main indicator of regional economic development due to its positive effect on promoting industrial development; however, many regions, especially developing countries, have troubled in its negative effect-the aggravating environmental pollution. Many researchers have addressed that the rapid urbanization stimulated the expansion of the industrial production and increased the industrial pollutant emissions. However, this statement is exposed to a grave drawback in that urbanization not only expands industrial production but also improves labor productivity and changes industrial structure. To make up this drawback, we first decompose the influence of urbanization impacts on the industrial pollutant emissions into the scale effect, the intensive effect, and the structure effect by using the Kaya Identity and the LMDI Method; second, we perform an empirical study of the three effects by applying the spatial panel model on the basis of the data from 282 prefecture-level cities of China from 2003 to 2014. Our results indicate that (1) there are significant reverse U-shapes between China's urbanization rate and the volume of industrial wastewater discharge, sulfur dioxide emissions and soot (dust) emissions; (2) the relationship between China's urbanization and the industrial pollutant emissions depends on the scale effect, the intensive effect and the structure effect jointly. Specifically, the scale effect and the structure effect tend to aggravate the industrial wastewater discharge, the sulfur dioxide emissions and the soot (dust) emissions in China's cities, while the intensive effect results in decreasing the three types of industrial pollutant emissions; (3) there are significant spatial autocorrelations of the industrial pollutant emissions among China's cities, but the spatial spillover effect is non-existent or non-significant. We attempt to explain this contradiction due to the fact that the vast rural areas around China's cities serve as sponge belts and absorb the spatial spillover of the industrial pollutant emissions from cities. According to the results, we argue the decomposition of the three effects is necessary and meaningful, it establishes a cornerstone in understanding the definite relationship between urbanization and industrial pollutant emissions, and effectively contributes to the relative policy making.

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Section: Literature Reviewmentioning

confidence: 99%

Urbanization and Its Effects on Industrial Pollutant Emissions: An Empirical Study of a Chinese Case with the Spatial Panel Model

Jin

2016

Sustainability

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“…air pollution, social welfare, resource efficiency, energy security, macroeconomic performance (e.g. Dong et al [28],Takeshita [29]and Zhang et al on air pollution [30], Xi et al [31]on environmental benefits, Dai et al [32]on economic benefits and Li & Lin, [33] on productivity benefits). These studies are generally case studies of a single country or a single impact and do not address methodological issues related to the difficulties of systematically assessing or integrating MIs.…”

Section: Limited Use Of Multiple Impacts In the Assessment Of Energy mentioning

confidence: 99%

“…Number of traffic-related injuries and deaths due to modal shift in passenger transport to low(er) carbon intensity modes Baseline level of modal split in the studied locality and the "safety in numbers" effect [75][76][77]; differences between short-term and longterm risks and effects [78], general transport/city infrastructure, local traffic, vehicle operation and transport safety regulations [76,78]; existence of pedestrian and cycling-friendly infrastructure [79], age of a person switching the transportation mode [80], cultural and behavioural norms in relation to cycling [77]. Avoided damage to human health, ecosystems and materials due to reduced air pollution emissions Technological and fuel mix, geographic and climatic conditions, atmospheric transport, distribution of receptors and pollution sources, baseline air pollution concentrations, atmospheric chemistry, variation in receptor sensitivity, height of emission stack, air pollution control technologies [81][82][83], energy prices [30] , GDP, industrial structure [28], developed vs. developing country context [29] Transaction costs Type and size of technologies, regulatory frameworks, complexity of transactions, and the maturity of policy instruments reducing transaction costs [84] …”

Section: Baseline Additionality and Context Dependencymentioning

confidence: 99%

Measuring multiple impacts of low-carbon energy options in a green economy context

Ürge-Vorsatz¹,

Kelemen²,

Herrero

et al. 2016

Applied Energy

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Wuppertal Institut | 1 AbstractThe economic assessment of low-carbon energy options is the primary step towards the design of policy portfolios to foster the green energy economy. However, today these assessments often fall short of including important determinants of the overall cost-benefit balance of such options by not including indirect costs and benefits, even though these can be gamechanging. This is often due to the lack of adequate methodologies.The purpose of this paper is to provide a comprehensive account of the key methodological challenges to the assessment of the multiple impacts of energy options, and an initial menu of potential solutions to address these challenges.The paper first provides evidence for the importance of the multiple impacts of energy actions in the assessment of low-carbon options.The paper identifies a few key challenges to the evaluation of the co-impacts of low-carbon options and demonstrates that these are more complex for co-impacts than for the direct ones. Such challenges include several layers of additionality, high-context dependency, and accounting for distributional effects.The paper continues by identifying the key challenges to the aggregation of multiple impacts including the risks of overcounting while taking into account the multitude of interactions among the various co-impacts. The paper proposes an analytical framework that can help address these and frame a systematic assessment of the multiple impacts.

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“…They find that energy efficiency measures and end-of-pipe options in China can achieve emission reductions at a relatively low cost. Dong et al (2015) combine the AIM/CGE model with the GAINS model to assess co-benefits at China's provincial level. They find that co-benefits exist at the provincial level and that regions with higher GDP will obtain higher cost-reduction co-benefits.…”

Section: Policy Choice Analysismentioning

confidence: 99%

“Lock-in” effect of emission standard and its impact on the choice of market based instruments

Qian

Tang

2017

Energy Economics

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Abstract:A country's existing emission standard policy will lead to a "lock in" effect. When the country plans to adopt new market-based instruments to control greenhouse gas emissions, it must consider this effect as it chooses among instruments to avoid larger efficiency loss. In this paper, we find that the "lock in" effect will cause a kink point to occur on the marginal abatement cost (MAC) curve. This change of shape for the MAC curve reminds us to be cautious in choosing market-based instruments when applying Weitzman's rule. We also introduce this concept into a dynamic multi-regional computable general equilibrium (CGE) model for China and simulate MAC curves for all regions. After applying Weitzman's rule, we propose a timeline for introducing price instruments under different marginal benefit (MB) curve scenarios.

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Pursuing air pollutant co-benefits of CO 2 mitigation in China: A provincial leveled analysis

Cited by 227 publications

References 33 publications

Urbanization and Its Effects on Industrial Pollutant Emissions: An Empirical Study of a Chinese Case with the Spatial Panel Model

Urbanization and Its Effects on Industrial Pollutant Emissions: An Empirical Study of a Chinese Case with the Spatial Panel Model

Measuring multiple impacts of low-carbon energy options in a green economy context

“Lock-in” effect of emission standard and its impact on the choice of market based instruments

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