Exploring the impact of economic growth and energy consumption on SO_(2) emissions in China based on the Environmental Kuznets Curve hypothesis

This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.

Influencing factors and contribution analysis of CO_(2) emissions originating from final energy consumption in Sichuan Province,China

Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.

Decoupling economic growth from CO_2 emissions: A decomposition analysis of China's household energy consumption

This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and economic growth based on a decoupling indicator.The results show that in 1994-2012, household CO_2 emissions grew in general and displayed an accelerated growth trend during the early 21 st century. Economic growth leading to an increase in energy consumption is the main driving factor of CO_2 emission growth(an increase of 1.078 Gt CO_2) with cumulative contribution rate of 55.92%, while the decline in energy intensity is the main cause of CO_2 emission growth inhibition(0.723 Gt CO_2 emission reduction) with cumulative contribution rate of 38.27%. Meanwhile, household CO_2 emissions are in a weak state of decoupling in general. The change in CO_2 emissions caused by population and economic growth shows a weak decoupling and expansive decoupling state, respectively. The CO_2 emission change caused by energy intensity is in a state of strong decoupling, and the change caused by energy consumption structure ?uctuates between a weak and a strong decoupling state.

Analysis on Carbon Emissions from Energy Consumption in Agriculture and Reduction Measures in Guangdong Province

[Objective] The aim was to study CO2 emissions from energy consumption in agricultural production in Guangdong Province and put forward feasible reduction measures.[Method] Based on the data from China Energy Statistical Yearbook and Guangdong Statistical Yearbook,CO2 emissions from agricultural energy use in Guangdong Province from 2000 to 2009 was estimated by using the formula of carbon emissions recommended by Intergovernmental Panel on Climate Change (IPCC),and corresponding reduction measures were put forward.[Result] With the rapid increase of agricultural output and energy consumption,CO2 emissions from energy consumption in agricultural production in Guangdong Province showed increasing trend from 2000 to 2009,that is to say,increasing from 423.63×104 t C million tons in 2000 to 605.99×104 t C in 2009,with annual growth rate of 4.1%.Meanwhile,carbon emissions intensity during energy consumption in agriculture went down in recent ten years,in other words,decreasing from 0.424 t C/×104 yuan in 2000 to 0.301 t C/×104 yuan in 2009,and its annual decreasing rate was 3.7%.The variation of CO2 emissions from energy consumption in agriculture mainly resulted from the increase of agricultural output,improvement of energy utilization efficiency,high carbonization in agricultural energy consumption structure and so forth.Therefore,in order to reduce CO2 emissions from energy consumption in agriculture,it is necessary to vigorously develop rural renewable energy,develop and popularize advanced technology for energy utilization,advance the energy conservation of agricultural machines,establish and improve the macroeconomic control mechanism for carbon emissions from the energy consumption in agricultural production in the further.[Conclusion] The study could provide references for the establishment of policy about reducing carbon emissions from agricultural energy consumption in Guangdong Province.

The relationship between energy consumption, economic growth and carbon dioxide emissions in Pakistan

Developing countries are facing the problem of environmental degradation.Environmental degradation is caused by the use of non-renewable energy consumptions for economic growth but the consequences of environmental degradation cannot be ignored.This primary purpose of this study is to investigate the nexus between energy consumption,economic growth and CO_(2) emission in Pakistan by using annual time series data from 1965 to 2015.The estimated results of ARDL indicate that energy consumption and economic growth increase the CO_(2) emissions in Pakistan both in short run and long run.Based on the estimated results it is recommended that policy maker in Pakistan should adopt and promote such renewable energy sources that will help to meet the increased demand for energy by replacing old traditional energy sources such as coal,gas,and oil.Renewable energy sources are reusable that can reduce the CO_(2) emissions and also ensure sustainable economic development of Pakistan.

Analysis and forecast of residential building energy consumption in Chongqing on carbon emissions

Carbon emissions mainly result from energy consumption. Carbon emissions inevitably will increase to some extent with economic expansion and rising energy consumption. We introduce a gray theory of quantitative analysis of the energy consumption of residential buildings in Chongqing,China,on the impact of carbon emission factors. Three impacts are analyzed,namely per capita residential housing area,domestic water consumption and the rate of air conditioner ownership per 100 urban households. The gray prediction model established using the Chongqing carbon emission-residential building energy consumption forecast model is sufficiently accurate to achieve a measure of feasibility and applicability.

The Energy Consumption of Heatingin the Northeast Rural Area of China from the Perspective of the Kang and Agricultural Waste

In China, the heating energy consumption patterns of rural housing are changing due to economic development. This study investigated domestic heating in rural areas of Dalian, a city in northeast China. In rural areas of the country, heating devices such as coal boiler, radiator, and/ or air-conditioner are typically used. The Kang, as the main heating system, has been used together with other heating methods for a long time in detached houses, one-story buildings, and quadrangles. Use of the Kang in collective housing is no longer observed. In addition to coal, agricultural wastes have been used to fuel the Kang; the associated CO2 emissions with agricultural fuels are lower than from other heating equipment. Even when a combination of the Kang and other equipment is used, with agricultural waste as fuel, CO2 emissions remain relatively low.

An estimation of energy consumption and CO_2 emissions in tourism sector of China

In 2009, nearly 900 million international tourist arrivals were counted worldwide. A global activity of this scale can be assumed to have a substantial impact on the environment. In this contribution, five major aspects such as the change of LUCC and the use of energy and its associated impacts had been recognized. Recently, the impact of tourism on environment and climate attracts the attention of international organizations and societies in pace with rapid development of tourism industry. Energy consumption and CO2 emissions in tourism sector are becoming a hot spot of international tourism research in recent five years. The use of energy for tourism can be divided according to transport-related purposes （travel to, from and at the destination） and destination-related purposes excluding transports （accommodation, food, tourist activities, etc.）. In addition, the transports, accommodation and foods are related to many other industries which are dependent on energy. Thus, the estimations of energy consumption and CO2 emissions in tourism sector have become a worldwide concern. Tourism in China grows rapidly, and the number of domestic tourists was 1902 million in 2009. Energy use and its impact on the environment increase synchronously with China’s tourism. It is necessary to examine the relationship between energy use and CO2 emissions. In this article, a preliminary attempt was applied to estimate the energy consumption and CO2 emissions from China’s tourism sector in 2008. Bottom-up approach, literature research and mathematical statistics technology were also adopted. According to the calculations, Chinese tourism-related may have consumed approximately 428.30 PJ of energy in 2008, or about 0.51% of the total energy consumptions in China. It is estimated that CO2 emissions from tourism sector amounted to 51.34 Mt, accounting for 0.86% of the total in China. The results show that tourism is a low-carbon industry and also a pillar industry coping with global climate change, energy-saving and CO2 emission reduction. Based on this, the authors suggested that tourism should become an important field in low-carbon economic development.

Iron ores matching analysis and optimization for iron-making system by taking energy consumption,CO2 emission or cost minimization as the objective

An optimization model for iron-making system covering sinter matching process to blast furnace process is established, in which the energy consumption, CO_2 emission and cost minimizations are taken as optimization objectives. Some key constraints are considered according to practical production experience in the modelling. The combination of linear programming(LP)and nonlinear programming(NLP) methods is applied. The optimal sinter matching scheme under given conditions and the optimization results for different objectives are obtained. Effects of sinter grade and basicity on all the optimal objectives and coke ratio in blast furnace process are analyzed, respectively. The results obtained indicate that compared with the initial values,the energy consumption/CO_2 emission of iron-making system decreases by 2.03% for objectives of energy consumption/CO_2 emission minimizations and 1.89% for the objective of cost minimization, the cost decreases by 17.88% and 18.13%, respectively.All the three criteria decrease with the increasing lump usage, coal powder injection, blast temperature, and decreasing coke ratio for the iron-making system.

Comparative study of energy consumption and CO2 emissions between Beijing and London

From the view of geographic location, climate and population status, this paper makes a comparative study of the economy structure, transport system, energy supply and carbon emissions among a few cities, especially between Beijing and London, two mega-cities in the world. The developed tertiary industry, consummate transport system and low-carbon energy supply system in London can be referenced to assist Beijing in establishing a low-carbon development pathway. The difference in the statistical coverage of population between these two cities also brings about the divergence of energy consumption per capita and CO2 emissions per capita between them.

On Estimating Transportation Energy Consumption and Carbon Dioxide Emissions from Off-shore Island Tourism——A Case Study of Haikou City, China

In the tourism industry, transportation is the greatest consumer of energy and contributes the largest amount of CO2 emissions （ECCE）. Airplane flights make up between 60% and 70% of all forms of tourism transport. Since airplane travel is the main way for tourists to access islands, airplane travel receives considerable attention in the study of the relationship between island tourism transportation, environment and economy. However, the pa- rameters adopted to estimate ECCE in the literature are usually either out-of-date or taken from papers not written in China. To improve the accuracy of estimates, all the parameters used in this paper are current and were obtained locally. Based on these parameters and a bottom-up approach, a more accurate estimation of ECCE for the off-shore island city of Haikou was obtained in 2012. The results indicate that 24.30% of the city＇s energy con- sumption, 33.89 P J, was due to tourism transportation, while CO2 emissions were 2.54 Mt. It is incorrect to assume that tourism is ＂an industry with no pollution＂. In Haikou, for example, tourism turns out to be the major form of en- ergy consumption in the city. This paper makes several suggestions intended to minimize the negative environ- mental impact from tourism transportation. These include recommending longer stays, a decrease in the number of flights, taxation of airplane emissions, and the setting up an environmental recovery fund.

Revisiting the nexus between fiscal decentralization and CO_(2)emissions in South Africa:fresh policy insights

The argument over fiscal decentralization and carbon dioxide emission(CO_(2))reduction has received much attention.However,evidence to back this claim is limited.Economic theory predicts that fiscal decentralization affects environmental quality,but the specifics of this relationship are still up for debate.Some scholars noted that fiscal decentralization might lead to a race to the top,whereas others contended that it would result in a race to the bottom.In light of the current debates in environmental and development economics,this study aims to provide insight into how this relationship may function in South Africa from 1960 to 2020.In contrast to the existing research,the present study uses a novel dynamic autoregressive distributed lag simulation approach to assess the positive and negative changes in fiscal decentralization,scale effect,technique effect,technological innovation,foreign direct investment,energy consumption,industrial growth,and trade openness on CO_(2)emissions.The following are the main findings:(i)Fiscal decentralization had a CO_(2)emission reduction impact in the short and long run,highlighting the presence of the race to the top approach.(ii)Economic growth(as represented by the scale effect)eroded ecological integrity.However,its square(as expressed by technique effect)aided in strengthening ecological protection,validating the environmental Kuznets curve hypothesis.(iii)CO_(2)emissions were driven by energy utilization,trade openness,industrial value-added,and foreign direct investment,whereas technological innovation boosted ecological integrity.Findings suggest that further fiscal decentralization should be undertaken through further devolution of power to local entities,particularly regarding environmental policy issues,to maintain South Africa’s ecological sustainability.South Africa should also establish policies to improve environmental sustainability by strengthening a lower layer of government and clarifying responsibilities at the national and local levels to fulfill the energy-saving functions of fiscal expenditures.

Modeling CO_(2)Emission in Residential Sector of Three Countries in Southeast of Asia by Applying Intelligent Techniques

Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large extent.In this regard,this sector must be considered in energy policy making related to the reduction of emission of CO_(2)and other greenhouse gases.In the present work,CO_(2)emission related to the residential sector of three countries,including Indonesia,Thailand,and Vietnam in Southeast Asia,are discussed and modeled by employing Group Method of Data Handling(GMDH)and Multilayer Perceptron(MLP)neural networks as powerful intelligent methods.Prior to modeling,data related to the energy consumption of these countries are represented,discussed,and analyzed.Subsequently,to propose a model,electricity,natural gas,coal,and oil products consumptions are applied as inputs,and CO_(2)emission is considered as the model’s output.The obtained R^(2) values for the generated models based on MLP and GMDH are 0.9987 and 0.9985,respectively.Furthermore,values of the Average Absolute Relative Deviation(AARD)of the regressions using the mentioned techniques are around 4.56%and 5.53%,respectively.These values reveal significant exactness of the models proposed in this article;however,making use of MLP with the optimal architecture would lead to higher accuracy.

中国东部地区能耗和SO_2排放趋势预测研究

在系统研究我国东部地区１８个省、市、自治区近年来能源消耗和ＳＯ２排放现状的基础上，利用国际上先进的ＬＥＡＰ模式和排放系数法，进行了２０００，２０１０和２０２０年三个时段的能耗和ＳＯ２排放趋势预测。研究中考虑了三峡工程和核电等的影响和各省之间的电平衡，以及有关部门的最新政策和数据。将大型火电厂单独作为点源考虑后，ＳＯ２排放的结果采用科学方法进行了按经纬度的网格化，可以直接作为远距离酸沉降模式的输入文件使用。最后还分析了东部地区的硫沉降趋势。

我国SO_2减排压力剖析及节能减排对策探讨

通过对我国未来能源消费形势的分析,从能源消费、单位产值能耗、人均能源消费量的变化趋势3个方面预测了我国2010和2020年的能源消费量,并结合当前我国节能减排工作所面临的形势与挑战,剖析了实现我国SO2减排目标及持续减排的压力,提出了相应的对策和建议。

FEASIBILITY OF AN OFF-GRID RENEWABLE ENERGY SOURCE FOR THE MERCANTILE SECTOR

Increased CO_(2),a Greenhouse Gas(GhG),emission and its accumulation in the atmosphere is a major climatic concern,creating an urgent need to control its rate of growth with the goal to reduce or reverse the growth.Reduction is being attempted at macro scales(large GhG producers but relatively small in number),at mezzo levels(mercantile stores which are large in numbers and relatively large consumers in scale)and at micro scales(individual dwelling units which are very large in number but relatively small on a GhG producer scale).This research identifies the strategies and challenges of adopting an off-grid renewable energy source for the mercantile sector(retail)at the mezzo level.A theoretical model for an off-grid renewable energy source considering a parking lot of a retail outlet was developed.In future work,a proposed physical model should be able to test the assumptions and hypothesis of the theoretical model presented.The proposed hybrid system uses two or more alternative renewable energy sources.In the proposed system,solar energy is integrated with a local bio gas plant,which treats waste to produce electricity.The excess energy can be sold to grid using net metering or dual metering or sold to charge plug-in vehicles to earn revenue.The renewable energy produced reduces the grid load on public utilities,thereby reducing the amount of CO_(2)emissions from the grid providers,thus bridging the current grid dependent system and a grid-independent(off grid,or net zero)goal.

CO_(2)捕捉技术在船舶减碳中的应用分析及展望

船舶碳捕集技术成为当前减少船舶碳排放的重要解决方案之一。针对短期内减少船舶尾气CO_(2)排放的问题,本文系统梳理了CO_(2)捕捉技术及其在船岸的应用和发展;通过对比分析法得出不同方式的CO_(2)捕捉技术的成熟度及优缺点,并在此基础上深入分析了目前CO_(2)捕捉技术在船舶应用中存在的捕捉效率不高、运行成本较高、政策标准不完善等方面的问题;提出了未来船舶尾气碳捕捉技术发展方向及建议,为商船碳捕集技术的更深入研究和推广应用提供更多思路和参考依据。

燃煤电厂CO_(2)捕集的减排效率研究与展望

为了客观评价不同CO_(2)捕集技术的能耗水平,判别CO_(2)捕集技术的有效性和经济性,提出减排效率概念和计算模型。CO_(2)减排效率表示某种CO_(2)捕集技术的有效减排能力,即捕集单位CO_(2)所发生的CO_(2)有效减排量,减排效率模型对CO_(2)捕集技术的能耗进行归集和平准化计算,其值越大表明减排效果越佳。利用减排效率模型测算,目前我国燃煤电厂CO_(2)捕集技术的减排效率理论极值为98%,燃烧前、燃烧中和燃烧后捕集技术的减排效率分别达到80%、70%和58%~68%。经工程应用实践验证,减排效率模型能满足评价要求。最后对CO_(2)捕集技术的发展进行了展望,认为未来随着捕集技术的不断进步和创新,CO_(2)减排效率将超过90%。

基于CPSONN-BP的校园节能减排数据融合

随着全球气候变化加剧,碳排放和能源消耗成为国际关注的焦点。在“双碳”目标背景下,高校节能减排的重要性日益凸显。基于此,研究了一种基于混沌粒子群优化的BP神经网络(CPSONN-BP)模型,用于校园节能减排数据的有效融合和分析。该模型利用多源异构数据,旨在建立一个精准综合的高校节能减排预测模型,以更有效应对双碳背景下的能源挑战和环境压力。通过对CPSONN-BP模型在校园节能减排数据融合方面的性能进行综合比较研究,发现该模型在准确度、收敛速度、稳定性和处理复杂数据能力上具有显著优势。与传统Excel预测方法和标准BP神经网络相比,CPSONNBP模型在处理多变量和非线性问题时表现出更快的收敛速度和更高的预测准确性。该模型在多次运行中表现出高度的可靠性和一致性,特别适用于解析高度非线性和多变量特征的数据。研究展示了CPSONN-BP模型在校园节能减排数据融合方面的优越性能,对于促进可持续发展,实现经济、环境和社会的协调发展具有重要意义。

中国旅游业CO_(2)排放因素分解：基于LMDI分解技术

本文基于＂自下而上＂法估算了1993~2012年中国旅游业能源消费和CO_2排放量,并对其总体变化趋势进行时间序列分析;以LMDI分解技术辨识与分解4个时段（1993~1997年、1998~2002年、2003~2007年和2008~2012年）中影响中国旅游业CO_2排放量变动的关键因素及其对CO_2排放量的贡献值。结果显示：20年来中国旅游业能源消费与CO_2排放量增长态势明显;其中旅游交通是中国旅游业能源消费和CO_2排放的核心部门,年平均比重分别为88.51%和77.42%,旅游住宿次之,旅游活动的贡献最小。LMDI分析结果显示,产业规模和空间结构是引起中国旅游业能源消费CO_2排放量增加的主要因素,能源强度是引起CO_2排放量减少的主要贡献因素;旅游业CO_2排放量增幅较大的省区多数位于东部地区,这是当前中国旅游业实行节能减排的重点区域。本文据此指出中国旅游业节能减排的主要方向、核心环节、重点区域和相应措施等。