Analysis on major drivers of cement consumption during the urbanization process in China

Cao, Zhi; Shen, Lei; Liu, Litao; Zhong, Shuai

doi:10.1016/j.jclepro.2016.05.130

Cited by 32 publications

(26 citation statements)

References 48 publications

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“…The conclusion is consistent with other studies, such as Lin et al [35], Wang and Zhao [31], Cao et al [38]. In Model 2, population, GRP per capita and energy intensity are still statistically significant, while industrialization level and foreign trade degree are not significant.…”

Section: Regression Resultssupporting

confidence: 91%

Effects of Population and Land Urbanization on China’s Environmental Impact: Empirical Analysis Based on the Extended STIRPAT Model

2017

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Abstract:China has been undergoing a very rapid but unbalanced urbanization, characterized by under-urbanization of its population and faster urbanization of the land. In such a situation, the urbanization of the population and the land may produce different effects on the natural environment. In addition, due to substantial inter-regional differences, the influence of urbanization on the environment is likely to vary across regions at different stages of economic and social development. This article expands the basic STIRPAT-Stochastic Impacts by Regression on Population, Affluence and Technology, model by adding industrialization level, foreign trade degree, population urbanization level and land urbanization level. Based on panel data from 2006 to 2014 and using this extended STIRPAT model, the article analyses the effects of the driving forces, especially population urbanization and land urbanization, on the environmental impact for the whole of China as well as on its eastern, middle and western regions. The results indicate that for the whole of China, population urbanization produces a significant negative effect on the environmental impact, while land urbanization has a small, but not statistically significant, positive effect. The effects of population urbanization and land urbanization vary across the eastern, middle and western regions, which are at different stages of economic and social development. Population urbanization and land urbanization have no significant influences on environmental impact in the eastern and middle regions, while in the western region population urbanization has a significant negative influence on environmental impact. The main driving factors of environmental impact remain population, affluence and energy intensity. This study also quantitatively calculates the actual contribution rate of each driving force for the 2006-2014 period. It contributes to understanding the characteristics and key driving forces in each region, allowing for appropriate policy recommendations.

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Section: Regression Resultssupporting

confidence: 91%

Effects of Population and Land Urbanization on China’s Environmental Impact: Empirical Analysis Based on the Extended STIRPAT Model

2017

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“…Climate Change Technology Program, the U.S. Climate Change Science Program Reilly, 1982, 1983;Edmonds et al, 1984), and the IPCC assessment reports (Reilly et al, 1987;Pachauri et al, 2014;Calvin et al, 2017). Most energy system models, including GCAM, take China as a whole section in simulations and fail to reflect the differences in regional or provincial energy and socioeconomic developments.…”

Section: The Gcam-china Modelmentioning

confidence: 99%

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

et al. 2020

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Abstract. Future trends in air pollution and greenhouse gas (GHG) emissions for China are of great concern to the community. A set of global scenarios regarding future socio-economic and climate developments, combining shared socio-economic pathways (SSPs) with climate forcing outcomes as described by the Representative Concentration Pathways (RCPs), was created by the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China's future anthropogenic emission pathways. The DPEC is designed to integrate the energy system model, emission inventory model, dynamic projection model, and parameterized scheme of Chinese policies. The model contains two main modules, an energy-model-driven activity rate projection module and a sector-based emission projection module. The activity rate projection module provides the standardized and unified future energy scenarios after reorganizing and refining the outputs from the energy system model. Here we use a new China-focused version of the Global Change Assessment Model (GCAM-China) to project future energy demand and supply in China under different SSP–RCP scenarios at the provincial level. The emission projection module links a bottom-up emission inventory model, the Multi-resolution Emission Inventory for China (MEIC), to GCAM-China and accurately tracks the evolution of future combustion and production technologies and control measures under different environmental policies. We developed technology-based turnover models for several key emitting sectors (e.g. coal-fired power plants, key industries, and on-road transportation sectors), which can simulate the dynamic changes in the unit/vehicle fleet turnover process by tracking the lifespan of each unit/vehicle on an annual basis. With the integrated modelling framework, we connected five SSP scenarios (SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and three pollution control scenarios (business as usual, BAU; enhanced control policy, ECP; and best health effect, BHE) to produce six combined emission scenarios. With those scenarios, we presented a wide range of China's future emissions to 2050 under different development and policy pathways. We found that, with a combination of strong low-carbon policy and air pollution control policy (i.e. SSP1-26-BHE scenario), emissions of major air pollutants (i.e. SO2, NOx, PM2.5, and non-methane volatile organic compounds – NMVOCs) in China will be reduced by 34 %–66 % in 2030 and 58 %–87 % in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important role in continuous emission reduction until 2050. In contrast, China's emissions will remain at a high level until 2050 under a reference scenario without active actions (i.e. SSP3-70-BAU). Compared to similar scenarios set from the CMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates of emission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in 2020–2030, but their emission ranges become similar in the year 2050.

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“…The building sector is one of the top three fields in total national energy consumption and creates an incredible energy demand explosion. As China becomes the largest emitter of greenhouse gas worldwide [1], Chinese building energy-efficiency work has faced strict challenges given that Chinese building sector is the second largest sector in Chinese national energy consumption. Chinese residential energy consumption (CREC) is a typical type of building energy consumption and accounts for over 80% of Chinese national building energy consumption in the current stage [2].…”

Section: Introductionmentioning

confidence: 99%

Estimating energy savings in Chinese residential buildings from 2001 to 2015: A decomposition analysis

Yan¹,

Ma²,

Pan³

2017

JESTR

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Evaluating energy savings in Chinese residential buildings (ESCRB) plays an important role in Chinese building energyefficiency work. However, the said work is currently challenged by the lack of effective method for estimating ESCRB data by summarizing all the quantifiable and unquantifiable impact factors. To overcome this problem, this study employed the equation of Human Impact, Population, Affluence, and Technology (IPAT), and the index decomposition of Logarithmic Mean Divisia Index (LMDI) to establish an effective ESCRB estimation method, and then calculated ESCRB data during the period of 2001-2015. Results of this study reflect that ESCRB has significantly accumulated with the rapid development of Chinese building energy-efficiency work in the past 15 years. In particular, ESCRB data

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Analysis on major drivers of cement consumption during the urbanization process in China

Cited by 32 publications

References 48 publications

Effects of Population and Land Urbanization on China’s Environmental Impact: Empirical Analysis Based on the Extended STIRPAT Model

Effects of Population and Land Urbanization on China’s Environmental Impact: Empirical Analysis Based on the Extended STIRPAT Model

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Estimating energy savings in Chinese residential buildings from 2001 to 2015: A decomposition analysis

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