Decoupling economic growth from construction waste generation: Comparative analysis between the EU and China.

The reduction and management of construction waste is crucial for the sustainable development of the construction industry. This research aims to explore a comparative analysis on decoupling relationship between economic growth and construction waste generation on European Union (EU) and Chi et al., 2020 to 2020 in the construction industry, through an integrated method framework of "Tapio + Kaya + LMDI". The research results indicate that there are significant differences in construction waste generation among different countries. The growth rates of construction waste in the EU and China from 2004 to 2020 were 2.47 % and 10.5 %, respectively, showing an upward trend. The economic growth of the construction industry in most EU countries is in a decoupling and negative decoupling state with significant regional differences in decoupling status. The construction waste generation in China is mainly in a weak decoupling state. Economic and demographic factors are the main factors promoting the increase in construction waste generation, while technological factors are the main factors inhibiting construction waste generation in EU and China. However, the impact of each factor on construction was generation varies from EU countries. The research reveals the decoupling effect mechanism between construction waste generation and economic growth, and improves the theory of construction waste management, promotes sustainable development. These findings have feasible inspiration for construction waste management in developing countries with different economic growth levels.

Spatiotemporal drivers of agricultural non-point source pollution: A case study of the Huang-Huai-Hai Plain, China.

Agricultural non-point source pollution (ANPSP) poses a severe threat to ecological environments, especially in China's major grain-producing regions. Despite the increasing attention, existing studies often overlook the spatial heterogeneity and driving mechanisms of ANPSP within different functional regions. This study addresses this research gap by constructing a bottom-up regional inventory of ANPSP for the Huang-Huai-Hai Plain (HHHP) and applying the Logarithmic Mean Divisia Index (LMDI) decomposition method to analyse the spatio-temporal patterns of ANPSP from 2000 to 2020. Spatial econometric models were further applied to examine the spatial spillover effects of driving factors from the perspective of Major Function-oriented Zoning (MFZ). The results show that while ANPSP emissions in the HHHP have generally increased over the past two decades, a slight decrease has been observed since 2015. Grain yield capacity and cropping intensity were identified as the primary drivers of ANPSP growth, particularly in urbanised zones (UZs) and main agricultural production zones (MAPZs). The study also highlights significant spatial heterogeneity in the impact of driving factors on ANPSP across different MFZs, with marked differences in both the direct and spatial spillover effects of these factors. This underlines the need for differentiated environmental protection policies tailored to the functions and characteristics of each region. By integrating the LMDI decomposition method with spatial econometric models, this study offers a new framework for understanding the ANPSP dynamics within the context of MFZs, providing policymakers with valuable insights for designing effective, regionally coordinated governance strategies.

Tracking the change in Spanish greenhouse gas emissions through an LMDI decomposition model: A global and sectoral approach.

The reduction of GHG emissions to reverse the greenhouse effect is one of the main challenges in this century. In this paper we pursue two objectives. First, we analyze the evolution of GHG emissions in Spain in 2008-2018, at both the global and sectoral levels, with the variation in emissions decomposed into a set of determining factors. Second, we propose several actions specifically oriented to more tightly controlling the level of emissions. Our results showed a remarkable reduction (18.44%) in GHG emissions, mainly due to the intensity effect, but also to the production-per-capita effect. We detected somewhat different patterns among the various sectors analyzed. While the intensity effect was the most influential one in the agricultural, transport, and others sectors, the production-per-capita effect was predominant in the case of industry. The carbonization effect was revealed as crucial in the commerce sector. The above findings highlight the importance of the energy efficiency measures taken in recent years in the Spanish economy, also pointing to the need to deepen those strategies and to propose new measures that entail greater efficiency in emissions. Additional efforts in areas like innovation, R&D, diffusion of more eco-friendly technologies, and a greater use of greener energies all prove to be essential reduction actions to fight the greenhouse effect.

Agricultural Methane Emissions in China: Inventories, Driving Forces and Mitigation Strategies.

Identification of the spatial distribution, driving forces, and future trends of agricultural methane (AGM) emissions is necessary to develop differentiated emission control pathways and achieve carbon neutrality by 2060 in China, which is the largest emitter of AGM. However, such research is currently lacking. Here, we estimated China's AGM emissions from 2010 to 2020 and then decomposed six factors that affect AGM emissions via the LMDI model. The results indicated that the AGM emissions in China in 2020 were 23.39 Tg, with enteric fermentation being the largest source, accounting for 43.9% of the total emissions. A total of 39.3% of the AGM emissions were from western China. The main driver of AGM emission reduction was emission intensity, accounting for 59% and 33.7% of methane emission reduction in the livestock sector and rice cultivation, respectively. Additionally, higher levels of urbanization contributed to AGM emission reductions, accounting for 31.3% and 43.0% of the livestock sector and rice cultivation emission reductions, respectively. Based on the SSP-RCP scenarios, we found that China's AGM emissions in 2060 were reduced by approximately 90% through a combination of technology measures, behavioral changes, and innovation policies. Our study provides a scientific basis for optimizing existing AGM emission reduction policies not only in China but also potentially in other high AGM-emitting countries, such as India and Brazil.

Decoupling analysis between economic growth and aluminum cycle: From the perspective of aluminum use and carbon emissions.

Increasing aluminum demand under the clean energy and low-carbon transformation background increases the fuzziness of relationships between economic growth and aluminum use or aluminum related carbon emissions. To figure this out, this paper established an aluminum use and carbon emissions integrated decoupling model within the framework of anthropogenic aluminum cycle. A material flow analysis (MFA) during 2000-2020 for China's aluminum cycle was firstly conducted to quantify both aluminum flow and carbon emissions in each aluminum life-cycle process. Then, this paper evaluated and decomposed the decoupling index of aluminum use-economy and carbon emission-economy via the LMDI decomposition model. Results show that: (1) secondary aluminum has not become effective supplement for primary aluminum in China; (2) the expansive negative decoupling state was the most prevalent state. The decoupling effects of carbon emission were better than that of aluminum use; (3) technology improvement was an important impactor to decoupling process but didn't offset the growth in aluminum consumption or carbon emissions at most of the time. The government and industry organizers should implement active countermeasures to stimulate aluminum companies developing technology to improve aluminum use efficiency and reduce carbon emissions.

Prolonged war reverses carbon emissions from an early decline to a late increase - Evidence from Syria.

Given that war can have a serious impact on the climate, this article is aimed to discuss the impact of warfare on carbon emissions by examining changes in CO2 before and during the war in Syria based on the kaya constant equation and the LMDI decomposition method. In the decade before the war, population was the largest contributor, making up 32.64% of the total 51.02% increase in carbon emissions. The only factor that offsetting carbon emissions was energy intensity, making a 22.30% curbing effect. In the early stage of the war, carbon emissions decreased by 56.38%, in which per capita GDP contributed 37.55% of the total CO2 decline. Carbon intensive of energy was the only factor promoting the carbon increase with a 4.67% contribution. In the late war, carbon emissions start to resume slow increase with energy intensity and economy turning negative to positive. It can be speculated that the impact of the war on CO2 emissions: (i) in the first years of the war, CO2 would drop significantly at the cost of significant population decline and economic recession, the least desirable and the worst way to reduce carbon emissions. (ii) if evolves into a prolonged war, it would reverse carbon emissions from decline to increase, although the population and the economy are both falling. This research, therefore contends that once war is triggered, there is no other solution to prevent this worst-case scenario of Population Decline - Economic Recession - Increased Carbon Emissions from happening, unless the war is stopped immediately.

Decomposition, decoupling, and future trends of environmental effects in the Beijing-Tianjin-Hebei region: A regional heterogeneity-based analysis.

The green growth of Beijing-Tianjin-Hebei (BTH) urban agglomeration plays a leading and exemplary role in overcoming internal resource restrictions, addressing climate change, and supporting China's high-quality growth. From the standpoint of pollution reduction and carbon reduction, this paper first conducts a comprehensive evaluation of the environmental impact based on combined weighting technique. The Logarithmic Mean Divisia Index (LMDI) model is used to decompose the environmental impact drivers in distinct areas. A decoupling effort index is further constructed to measure the effect of various efforts on the decoupling of economic growth and environmental impact, the improved grey Markov model is applied to predict the future trend of regional decoupling efforts. The results of empirical analysis based on data of the BTH region during 2011-2018 show that: 1) the environmental impact index of Beijing is the lowest followed by Tianjin and Hebei; 2) environmental regulation exerts the most significant impact on reducing environmental pressure in Beijing while technology progress and energy intensity have the most significant effect on easing environmental pressure in Tianjin; 3) strong decoupling efforts have been found in Beijing, Tianjin and Hebei, however, such effect is more significant in Beijing; 4) Beijing's decoupling state is mostly driven by regulatory effect, intensity effect, and scale effect, while Tianjin and Hebei's decoupling states are primarily driven by improvements in environmental regulation and energy intensity; 5) according to the forecast outcome of the improved grey Markov technique, a state of strong decoupling effort will be maintained in the BTH area by 2025, and the decoupling effort index in Beijing will remain the highest while the index in Hebei will remain the lowest.

Decoupling analysis and peak projection of manufacturing CO2 emissions from the perspective of investment.

Reducing carbon emissions has become an urgent task in China. As the category with the largest economic and emissions contribution to the industry, the carbon emissions research of the manufacturing industry is particularly important. This paper uses the LMDI method to decompose manufacturing carbon emissions into seven influencing factors (i.e., population, urbanization, economic development, investment share, energy intensity, energy structure and emission intensity), in order to explore the factors driving manufacturing carbon emissions during 2003-2018. Then, the paper analyzes the decoupling relationship between manufacturing investment and carbon emissions in 30 provinces. Finally, three scenarios are developed to project future manufacturing emissions at the provincial level up to 2035, and whether manufacturing emissions in 30 provinces can realize peak is discussed. The paper results in three main findings. First, we find that energy intensity played the most important role in decreasing the manufacturing emissions during the whole study period, while the economic development and investment share were the main effect promoting manufacturing carbon emissions. Second, China experienced a process from weak decoupling to strong decoupling between manufacturing invest and emissions. Third, China's manufacturing carbon emissions can only achieve the carbon peaking target in 2030 under the High scenario, and 7 provinces cannot reach the peak before 2035 under the three scenarios. Supplementary Information: The online version contains supplementary material available at 10.1007/s10668-023-03047-w.

Decomposition of residential electricity-related CO2 emissions in China, a spatial-temporal study.

The COVID-19 pandemic brings a surge in household electricity consumption, thereby enabling extensive research interest on residential carbon emissions as one of the hot topics in carbon reduction. However, research on spatial-temporal driving forces for the increase of residential CO2 emissions between regions still remains unknown in terms of emissions mitigation in post-pandemic era. Therefore, we studied the residential CO2 emissions from the electricity consumption of China during the period 1997-2019. Afterward, the regional specified production emission factors, combining with electricity use pattern, living standard and household size, were modelled to reveal the spatial-temporal driving forces at national and provincial scales. We observed that the national residential electricity-related CO2 increased from 1997 to 2013, before fluctuating to a peak in 2019. Guangdong, Shandong and Jiangsu, from East China were the top emitters with 27% of the national scale. The decomposition results showed that the income improvement was the primary driving force behind the emission increase in most provinces, while the household size and production emission effects were the main negative effects. For the spatial decomposition, differences in the total households between regions further widen the gaps of total emissions. At the provincial scale of temporal decomposition, eastern developed regions exhibited the most significant decrease in production emissions. In contrast, electricity intensity effect showed negative emission influences in the east and central regions, and positive in north-eastern and western China. The research identified the different incremental patterns of residential electricity-related CO2 emissions in various Chinese provinces, thereby providing scientific ways to save energy and reduce emissions.

Assessing the sustainability of ecosystems over fourteen years of cultivation in Longnan City of China based on emergy analysis method.

Currently, the contradiction between the limited resources of China's cultivated ecosystems and population growth is becoming increasingly evident, and the negative impacts on the environment and human activities need to be curbed. Therefore, it is crucial to quantify the sustainability of cultivated ecosystems and determine these driving factors that affect their development. This study used the emergy method to quantify the input/output flow and sustainable development of the cultivated land ecosystem in Longnan City, combined with the logarithmic mean divisia index decomposition analysis (LMDI) method to evaluate the driving factors of sustainable development in the region. The results demonstrate that from 2004 to 2017, the total emergy input and output of Longnan City showed an upward trend, and non-renewable resources (N) were always in a dominant state in the total emergy (T) input, and their proportion rose from 59.69% to 66.92%. The emergy sustainability index (ESI) is less than 1, and the environmental pressure of the system is relatively higher. Comprehensive emergy production ratio (EPR), emergy investment ratio (EIR), the renewable fraction (R%), emergy yield ratio (EYR) and environmental load ratio (ELR), showed that the agricultural ecological economy in Longnan still has great development potential, and clean energy should be developed as far as possible to replace fossil fuels in future planning. LMDI results showed that the intensity factor ΔY'A is the main driving factor for the positive development of ESI. The government's ecological protection requirements can reduce waste emissions through reasonable farming system and advocating the use of organic fertilizer, so as to achieve the purpose of improving crop yield. Vigorous development of green ecological agricultural production patterns can improve the sustainability of arable ecosystems. This study can provide a theoretical basis for the sustainable development of cultivated ecosystems and the formulation of related agricultural production measures.

Decomposition and decoupling analysis of carbon emissions from agricultural economic growth in China's Yangtze River economic belt.

In this study, carbon emissions from agricultural energy consumption (CEAEC) are fully analyzed using data from the Yangtze River Economic Belt (YEB) between 2000 and 2017. First, generalized LMDI is adopted to decompose the drivers of CEAEC into five components. Then, the decoupling indicator and the decoupling effort indicator are constructed to quantify the decoupling degrees and examine the government's emission reduction efforts, respectively. The results show that (1) CEAEC in the YEB has shown a phased increase, reaching a peak at 1732.25104t in 2012. Except for some decreases found in Shanghai, Chongqing, and Guizhou, it is shown that all provinces' CEAEC have risen to varying degrees. In contrast, the intensity of CEAEC in the YEB has been declining since 2005. (2) The economic output effect acts as the major contributor to the growth of CEAEC, followed by the population effect. In contrast, both the energy intensity effect and the energy structure effect are the primary reasons for reductions in CEAEC. The spatial difference in CEAEC in the YEB increased significantly from 2000 to 2017. (3) There was an alternating change from decoupling to coupling and then to negative decoupling from 2000 to 2017. Based on the conclusions mentioned above, it is proposed that the formulation of low-carbon agricultural development strategies should consider the structural adjustment of agricultural energy consumption and the advancements of agricultural technology.

Spatiotemporal dynamics and decoupling mechanism of economic growth and carbon emissions in an urban agglomeration of China.

Carbon emissions and economic growth are two contradictions in urban development, and their decoupling is related to the sustainable development of cities. This paper took urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), China, as the study area. The Kaya model, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatiotemporal differentiation of carbon emissions, the decoupling of economic activities, and driving factors. The results indicate that (1) carbon emissions increased by 66% in the study period, but the growth momentum was curbed after 2015. Low level and medium level areas continue to decrease, and relatively high level area gradually become dominant. (2) Spatially, carbon emissions are in a pattern of middle-hot and east-cold. Jiangxi is in the sub-cold and coldspot area, while the hotspot area is driven by the transformation from Wuhan's single-core to Wuhan and Changsha's dual-core. (3) Since 2010, most cities have been in a good decoupling state, and weak decoupling cities have risen from 35.5% in the initial period to 87.1% in 2010-2011, but the decoupling situation of industrial cities with more high-energy-consuming industries still rebounded slightly. (4) The economic level and energy intensity effect had the most significant impact on the economic decoupling of carbon emissions, whose absolute contribution rates were greater than 35%. Urbanization and economic level both play a positive role in promoting carbon emissions, and the energy intensity plays a negative role in retarding carbon emissions. The population effect was mainly manifested in carbon increase from 2006 to 2011, and 45.2% of the cities from 2011 to 2017 turned into carbon suppression. Finally, we suggest that decoupling carbon emissions from economic growth requires developing green urbanization and a decarbonized economy, optimizing the structure of energy consumption and guiding rational population flow.

Comparison of end-of-life vehicles management in 31 European countries: A LMDI analysis.

In 2018, a total of 6,083,000 end-of-life vehicles (EVLs) with a total weight of 6,732,000 tonnes (including waste parts) were generated in the European Union. These vehicles are a subject of particular attention because of their bulky mass, the hazardous components they contain, and the valuable materials present. This article analyses the quantities of ELVs and parts of ELVs that have been recycled, energy recovered, disposed, and reused to assess the impact of the changes in these management options on the total quantities managed. The analysis covered the statistical data on EVLs in 31 European countries for the period 2006-2018, using a new extended version of the logarithmic mean divisia index (LMDI) analysis model, which allows analysts to compare and analyse different waste management options simultaneously. The results show that the changes in the waste intensities and household final consumption expenditure were the greatest drivers of changes in the total quantities managed, while changes in the quantities recycled, energy recovered, disposed of, and reused had the least impact. All countries met or were close to meeting the targets during the period analysed. Changes in the total quantities of waste managed depended on the economic activity, which influenced the quantities of ELVs generated and their subsequent management.

Structural and social-economic determinants of China's transport low-carbon development under the background of aging and industrial migration.

This paper aims to explore structural and social-economic determinants of China's transport CO2 emissions (TCEs) from 2004 to 2016, by using logarithmic mean Divisa index (LMDI). Compared with existing studies, two new factors, i.e., spatial pattern and age structure, that should have impacts on TCEs, are considered in this study. Results show that during 2004-2016: (1) transportation demand and urbanization were dominant in TCEs growth, while energy intensity and industrial structure were the key factors of CO2 emissions reduction. (2) The effects exerted by age structure and CO2 emission factor change were relatively mild. The former one has a stable promoting effect, while the latter one inhibits TCEs growth. Additionally, the influence of spatial pattern on the growth of CO2 emissions from transportation was limited. (3) Energy structure and energy intensity played more important roles in reducing emissions of the transport sector in the eastern region. The effects of population size on the eastern region were much greater than those of the central and western regions, presenting the phenomenon of "eastern agglomeration". (4) In Tianjin, energy intensity and energy structure did not perform well for TCEs.

How does industrial restructuring influence carbon emissions: City-level evidence from China.

This study addresses the question of why industrial restructuring towards light industries or services sometimes fails to achieve carbon emission mitigation goals. By employing a new perspective of dividing industry segments into emission-dominating and non-emission-dominating ones based on Logarithmic Mean Divisia Index (LMDI) decomposition method, this paper analyses city-level carbon dioxide emission reduction performance under three distinctive industrial restructuring directions. Results indicate that carbon dioxide emission dominating segments are relatively fixed across cities, regardless of the various city types in China. The key point to achieve emission reduction through industrial restructuring is to identify and control the emission-dominating segments, instead of economic-leading ones. Besides, emission reduction performance of industrial restructuring from emission-dominating industry segments to services is better than that to non-emission-dominating ones. More importantly, industrial restructuring not involving output scale controlling of emission-dominating segments, or that recklessly rushing towards services are likely to fail the emission mitigation goal. This paper presents a strong international reference that merits cities facing policy hesitation over industrial restructuring directions while in pursuit of emission mitigation. It suggests that cities first focus on identifying the carbon dioxide dominating segments, of which the output scale should be controlled. For cities whose emission-dominating segments are not economic-leading ones, it is necessary to carry out industrial restructuring towards services or non-emission-dominating segments; while for cities heavily dependent on emission-dominating segments, energy efficiency should also be improved.

Decoupling and decomposition analysis of industrial sulfur dioxide emissions from the industrial economy in 30 Chinese provinces.

As one of the largest emitters of sulfur dioxide (SO2), China has faced increasing pressure to achieve sustainable development. This study investigates the decoupling relationship between industrial SO2 emissions and the industrial economy in China during 1996-2015. According to the decoupling results, the study period is divided into four stages: 1996-2001, 2001-2006, 2006-2010, and 2010-2015. These four stages are closely aligned with the major adjustments of the national socio-economic policies. Then, the logarithmic mean Divisia index (LMDI) decomposition method is used to analyze the driving factors of industrial SO2 emissions. The results demonstrate that the SO2 generation intensity and SO2 abatement are the major contributors to reducing industrial SO2 emissions, while the economic activity effect is the primary inhibitory factor. Moreover, the provincial results show that most provinces with weak decoupling state since 2006 are located in less developed provinces with energy-intensive industries. Besides, the economic structure and SO2 generation intensity show negative contributions to reducing industrial SO2 emissions in some of these regions. Based on the results, the attention should be focused on cleaner production to reduce industrial SO2 emissions further, and environmental policies should be tailored to local conditions.

Atmospheric pollution reduction effect and regional predicament: An empirical analysis based on the Chinese provincial NOx emissions.

Atmospheric pollution emissions have become a matter of public concern in recent years. However, most of the existing researches on NOx pollution are from the natural science and technology perspective, few studies have been conducted from an economic point, and regional differences have not been given adequate attention. This paper adopts provincial panel data from 2006 to 2013 and the LMDI model to analyze the key driving factors and regional dilemmas of NOx emissions. The results show that significant regional disparities still exit on NOx emissions and its reduction effect 27 provinces didn't accomplish their corresponding reduction targets. Economic development factor is the dominating driving factor of NOx emissions during the study period, while energy efficiency and technology improvement factors offset total NOx emissions in the majority of provinces. In addition, the industrial structure factor plays a more significant role in reducing the NOx emissions after 2011. Therefore, the government should consider all these factors as well as regional heterogeneity in developing appropriate pollution mitigating policies. It's necessary to change NOx emissions control attitude from original key areas control to divided-zone control, not only attaches great importance to the reduction of the original key areas, but also emphasizes the new potential hotspots with high NOx emissions.

Decomposition analysis of the waste generation and management in 30 European countries.

An often suggested method for waste prevention is substitution of currently-used materials with materials which are less bulky, contain less hazardous components or are easier to recycle. For policy makers it is important to have tools available that provide information on the impact of this substitution on the changes in total amounts of waste generated and managed. The purpose of this paper is to see how much changes in the mix of 15 waste streams generated in eight economic sectors from 30 European countries have influenced the amounts of waste generated and managed in the period 2004-2012. In order to determine these impacts, two variations of the logarithmic mean Divisia index (LMDI) analysis model were developed and applied. The results show that the changes in the mix of waste streams in most cases did not have a considerable influence on the changes in the amounts of generated waste. In the analyses of waste sent for landfill, incineration without energy recovery, incineration with energy recovery and recovery other than energy recovery, the results also show that the changes in the mix of waste streams in most cases did not have the expected/desired influence on the changes in the amounts of managed waste. This paper provides an example on the possibilities of applying the LMDI analysis as a tool for quantifying the potential of effects which implemented or planned measures could have on the changes in waste management systems.

Two-step accelerated mineral carbonation and decomposition analysis for the reduction of CO2 emission in the eco-industrial parks.

Carbon dioxide (CO2) emissions are a leading contributor to the negative effects of global warming. Globally, research has focused on effective means of reducing and mitigating CO2 emissions. In this study, we examined the efficacy of eco-industrial parks (EIPs) and accelerated mineral carbonation techniques in reducing CO2 emissions in South Korea. First, we used Logarithmic Mean Divisia Index (LMDI) analysis to determine the trends in carbon production and mitigation at the existing EIPs. We found that, although CO2 was generated as byproducts and wastes of production at these EIPs, improved energy intensity effects occurred at all EIPs, and we strongly believe that EIPs are a strong alternative to traditional industrial complexes for reducing net carbon emissions. We also examined the optimal conditions for using accelerated mineral carbonation to dispose of hazardous fly ash produced through the incineration of municipal solid wastes at these EIPs. We determined that this technique most efficiently sequestered CO2 when micro-bubbling, low flow rate inlet gas, and ammonia additives were employed.

Energy and social factor decomposition to identify drivers impeding sustainable environmental transition in emerging countries: SDGs-2030 progress assessment using LMDI analysis.

The balance between human growth, economic prosperity, and the consumption of hydrocarbon energy factors has become a prerequisite for environmental sustainability. However, the complexities of these factors force researchers to work for more viable combinations of such a balance. Therefore, this study attempted to determine the factors driving environmental sustainability in leading populated economies. For this purpose, the Logarithmic Mean Division Index (LMDI) utilized to decompose critical factors such as activity, economy, real density, energy intensity, and suburban effects for the period 1999-2022. Both population and its consequences (economic activity) have been found to be the leading factors behind environmental fluctuations, and energy has a negative impact on hydrocarbon forms, while contributing positively to environmental sustainability with high efficiency and low intensity. Therefore, sustainable demographic and energy transitions can be leading pathways for environmental sustainability in developing economies.