How can technology and efficiency alleviate the dilemma of economic growth and carbon emissions in China's industrial economy? A metafrontier decoupling decomposition analysis

This paper attempts to explore the decoupling relationship and its drivers between industrial economic increase and energy-related CO_(2) emissions(ICE). Firstly, the decoupling relationship was evaluated by Tapio index. Then, based on the DEA meta-frontier theory framework which taking into account the regional and industrial heterogeneity and index decomposition method, the driving factors of decoupling process were explored mainly from the view of technology and efficiency. The results show that during2000-2019, weak decoupling was the primary state. Investment scale expansion was the largest reason hindering decoupling process of industrial increase from ICE. Both energy saving and production technology achieved significant progress, which facilitated the decoupling process. Simultaneously, the energy technology gap and production technology gap among regions have been narrowed, and played a role in promoting decoupling process. On the contrary, both scale economy efficiency and pure technical efficiency have inhibiting effects on decoupling process. The former indicates that the scale economy of China's industry was not conducive to improve energy efficiency and production efficiency, while the latter indicates that resource misallocation problem may exist in both energy market and product market.

Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City, China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.

Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator

Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition （EMD） algorithm and Teager energy operator （TEO） is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions （IMFs）, which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.

Revisiting the driving force underlying Chinese PM_(2.5)emissions:From the two perspectives of GVC and IDA

The depth and breadth of participation in the global value chain(GVC)significantly impacts a country's fine particulate contamination(PM_(2.5))emissions.First,based on the GVC accounting framework,the sources of PM_(2.5) emissions in China between 1990 and 2015 are identified and investigated considering production-side,consumption-side,and export-implied pollution.Then,index decomposition analysis(IDA)of emissions is conducted to further investigate the changes in and causes of air pollution in China.Throughout the analytical process,differences between the PM_(2.5) emissions in two time periods-one of rapid economic growth and another of the“new normal”economy-are compared.The results demonstrate that:China is embedded in high pollution links of GVCs;China transfers pollution to third-parties by importing intermediate products from resource-intensive countries in the global production system;extensive economic growth caused an increase in China's total PM_(2.5) emissions,but cleaner production technology can reduce the emissions intensity.Industrial restructuring under the“new normal”has increased China's short-term PM_(2.5) emissions intensity.These results suggest that China should optimize and upgrade its domestic economic structure and transform its export growth mode to deliver high added value and low pollution.Further,it should prioritize cooperation between the upstream and downstream value chain and accelerate the upgrading of its consumption structure in this new era.

Decomposition analysis applied to energy and emissions:A literature review

Decomposition analysis has been widely used to assess the determinants of energy and CO_(2)emissions in academic research and policy studies.Both the methodology and application of decomposition analysis have been largely improved in the past decades.After more than 50 years’developments,decomposition studies have become increasingly sophisticated and diversified,and tend to converge internally and integrate with other analytical approaches externally.A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda.To this end,this study presents a literature survey for decomposition analysis applied to energy and emission issues,with a focus on the period of 2016–2021.A review for three individual decomposition techniques is first conducted,followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole.The findings are expected to direct future research in decomposition analysis.

Trends in per capita ecological footprint and biocapacity in China 1949-2013

This paper proposes two concepts: the ecological footprint component index(EFCI) and the biocapacity component index(BCCI), based on the ecological footprint(EF) and Shannon entropy approaches. Per capita EFCI and BCCI in China 1949-2013 are analyzed using empirical mode decomposition(EMD). Nonlinear models of per capita EFCI and BCCI in China 1949-2013 are presented and their cycles and predictions from 2014 to 2023 are analyzed. The results over the last 65 years show:(1) EFCI in China has increased constantly with fluctuations, while BCCI has slowly decreased. Their annual change rates are 2.81% and-1.26%, respectively. The increasing EFCI indicates a gradual improvement in China's sustainable development potential; the decreasing BCCI indicates severe environmental and population challenges.(2) The cycles of per capita EFCI have periods of 5.4 and 16.3 years, while cycles of per capita BCCI have periods of 3.6, 13,and 21.7 years. The predictive models indicate that EFCI will first decrease, reaching 0.02725 in2014, and will subsequently increase to 0.03261 in 2021. BCCI will increase, reaching 0.01365 in2014 and 0.01541 in 2022. EFCI and BCCI will reach 0.03037 and 0.01537, respectively, in 2023.Policymakers should ensure that the EFCI and BCCI increase in 2023.

Decomposition of energy-related carbon emissions in Xinjiang and relative mitigation policy recommendations

Regional carbon emissions research is necessary and helpful for China in realizing reduction targets. The LMDI I （Logarithmic Mean Divisia Index I） technique based on an extended Kaya identity was conducted to uncover the main five driving forces for energy-related carbon emissions in Xinjiang, an important energy base in China. Decomposition results show that the affluence effect and the population effect are the two most important contributors to increased carbon emissions. The energy intensity effect had a positive influence on carbon emissions during the pre-reform period, and then became the dominant factor in curbing carbon emissions after 1978. The renewable energy penetration effect and the emission coefficient effect showed important negative but relatively minor effects on carbon emissions. Based on the local realities, a comprehensive suite of mitigation policies are raised by considering all of these influencing factors. Mitigation policies will need to significantly reduce energy intensity and pay more attention to the regional economic development path. Fossil fuel substitution should be considered seriously. Renewable energy should be increased in the energy mix. All of these policy recommendations, if implemented by the central and local government, should make great contributions to energy saving and emission reduction in Xinjiang.

Strategic Measures to Reduce China's Carbon Emissions: Based on an Index Decomposition Analysis of Carbon Emissions in Eight Industries

This article uses the refined Laspeyres index decomposition method to examine the overall trends and characteristics of carbon emissions in eight Chinese industries for the period 1994-2008. The results show that every one percentage point increase in economic scale will result in an average increase of 15 Mt （million tonnes） in carbon emissions. However, different industries vary greatly in terms of marginal carbon emissions caused by economic growth. The economic structure＇s bias toward heavy industry fuels the increase of carbon emissions： every one percentage point rise in the share of manufacturing industry produces an average of 56 Mt carbon emissions. Technological progress helps reduce energy intensity and serves as a core driver in reducing carbon emissions, in that every one percentage point decrease in energy intensity will cause an average reduction of 33 Mt in carbon emissions. Our coal-dominated energy structure has resulted in a persistently high level of carbon emissions, suggesting that the reduction effect brought about by changes in energy structureis not significant. Nevertheless, lowering the density of overall carbon emissions is a positive signal, indicating that China is optimizing its energy structure. Only by promoting industrial restructuring, optimizing energy structure, encouraging energy-saving technologies and technological innovation, and reorienting industry can China achieve low-carbon development and control pollution.

Metal release/accumulation during the decomposition of Potamogeton crispus in a shallow macrophytic lake

Changes in metal concentrations in the litter of Potamogeton crispus were monitored during a consecutive 40-day in situ decomposition experiment using the litterbag method.The accumulation index was calculated and used to indicate the changes in the metals in litter.The results showed that the concentrations of Al,Cd,Cr,Fe,Mn,and Pb in litter increased significantly during the decomposition,while Cu and Zn concentrations decreased dramatically.Significant positive correlations were found between the concentrations of Al,Cr,Fe,and Mn and between Cu and Zn.Moreover,Cu and Zn both negatively correlated with Al and Fe.The remaining dry mass was negatively correlated with Al and Fe concentrations but positively correlated with Cu and Zn concentrations.Generally the accumulation index values of metals other than Al were less than one,indicating that the litter of P.crispus acted as a source of metals to the surrounding water body.Al was the only metal that showed continuous net accumulation in litter.The net accumulation of Fe and Mn in litter during the last 10 days of the experiment may indicate the precipitation of Feand Mn-oxides.It was estimated that 160 g/m^2（dry weight）P.crispus was decomposed in40 days.This was equivalent to releasing the following amounts of metals：0.01 mg Cd,0.03 mg Cr,0.71 mg Cu,0.55 mg Mn,0.02 mg Pb and 13.8 mg Zn into surrounding water,and accumulating 149 mg Al and 11 mg Fe,in a 1 m^2 area.

Impacts of household living consumption on energy use and carbon emissions in China based on the input–output model

China must urgently accelerate its decrease of energy use,optimize its energy structure,reduce CO2 emissions,and promote the early realization of an ecological civilization.Simultaneously,meeting the growing consumer demand is one of the reasons for the increase in energy use.This study investigates the impacts of household consumption on energy use and CO2 emissions from the perspective of the lifestyle of Chinese residents.On the basis of the input–output model of 30 provinces,we analyze the current situation of energy use and CO2 emissions in different regions(spatial scale)with economic development and income improvement(time scale),investigate the pulling effect of household consumption in different provinces on industrial sectors,examine the influencing factors of indirect CO2 emissions from food,clothing,housing,and transportation in key regions,and explore the policy implications of the transition to a low-carbon lifestyle in different provinces.Results show that the fuel structure of Chinese residents should be optimized further.Total household energy consumption and total CO2 emissions considerably increased.In 2012,total household energy consumption accounted for nearly 30%of total energy consumption,while indirect CO2 emissions accounted for 66.3%of total household emissions.With regard to the structures of indirect household energy consumption,the housing sector accounted for the largest proportion,reaching 23.4%in indirect energy consumption in 2012.The pulling effect of the housing sector on industrial sectors was also evident.The decomposition analysis showed that the rapid increase in indirect household CO2 emissions was primarily due to the increase in per capita living expenditure.The consumption structures in different provinces produced various impacts,and the energy intensity effect was identified as an important factor for reducing indirect household CO2 emissions.

Analysis of driving forces behind diversified carbon dioxide emission patterns in regions of the mainland of China

China has large regional disparities in carbon dioxide CO_(2) emissions with economic development among its 31 provincial mainland regions.This paper investigates these disparities in CO_(2) emission patterns and identifies the factors underlying the differences.Results show that the 30 study China's mainland provinces(Tibet not included)can be divided into seven groups with three typical CO_(2) emission patterns.Index decomposition results indicate that changes in economic development,the industrial sector,and technology contribute far more to increased CO_(2) emissions than do population,energy structure,and other sectors.Close inspection reveals that different industry structures and technology contribute greatly to the differences observed in CO_(2) emissions between provinces with similar economic output.This study highlights the importance of region-specific industrial structure adjustment policies,especially for regions transitioning to heavy industry and for those still in the primary stages of industrialization.The potential application of a domestic carbon emissions trading system,to encourage regional investment in updated technology,is also discussed.