Empirical Fuel Consumption and CO2 Emissions of Plug‐In Hybrid Electric Vehicles

Plug‐in hybrid electric vehicles (PHEVs) combine electric and conventional propulsion. Official fuel consumption values of PHEVs are based on standardized driving cycles, which show a growing discrepancy with real‐world fuel consumption. However, no comprehensive empirical results on PHEV fuel consumption are available, and the discrepancy between driving cycle and empirical fuel consumption has been conjectured to be large for PHEV. Here, we analyze real‐world fuel consumption data from 2,005 individual PHEVs of five PHEV models and observe large variations in individual fuel consumption with deviation from test‐cycle values in the range of 2% to 120% for PHEV model averages. Deviations are larger for short‐ranged PHEVs. Among others, range and vehicle power are influencing factors for PHEV model fuel consumption with average direct carbon dioxide (CO₂) emissions decreasing by 2% to 3% per additional kilometer (km) of electric range. Additional simulations show that PHEVs recharged from renewable electricity can noteworthily reduce well‐to‐wheel CO₂ emissions of passenger cars, but electric ranges should not exceed 200 to 300 km since battery production is CO₂‐intense. Our findings indicate that regulations should (1) be based on real‐world fuel consumption measurements for PHEV, (2) take into account charging behavior and annual mileages, and (3) incentivize long‐ranged PHEV.     

Examining the impact factors of urban residential energy consumption and CO2 emissions in China – Evidence from city-level data

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO₂ emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO₂ emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO₂ emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO₂ emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO₂ emissions.     

旅游交通碳排放的空间结构与情景分析

旅游业作为全球第一大产业,是影响气候变化的重要因素之一,旅游碳排放的相关研究近年来已经引起学者们的关注.选择了九寨沟风景区、西安碑林博物馆、南京珍珠泉风景区3个旅游交通模式差异明显的案例地为例,根据实地问卷调查数据估算了九寨沟风景区、西安碑林博物馆、珍珠泉旅游风景区2010年的旅游交通碳排放总量分别为654.18,108.44和15.92 Gg.通过比较九寨沟、西安碑林和珍珠泉的碳排放累积曲线,得出不同旅游平均距离的景区的碳排放结构均衡度有所不同,旅游平均距离偏低景区的碳排放结构最不均衡.同时,旅游景区的交通碳排放在距离上具有分段性,不同旅游平均距离的景区交通碳排放的空间结构具有明显的差异性.通过4种不同的交通情景分析发现,旅游平均距离高和距离中等的景区对飞机的碳减排敏感度较高,旅游平均距离偏低的景区自驾车的碳减排效果最为明显.研究结果为旅游管理部门根据碳排放结构有针对性的制定差异化的旅游交通碳减排政策提供了参考和借鉴.     

我国典型城市化石能源消费CO2排放及其影响因素比较研究

城市是化石能源消费和CO₂排放的主要区域。分析典型城市化石能源消费CO₂排放特征,明确不同城市CO₂排放动态及主要影响因素的差异,是开展城市减排行动的重要科学依据。采用IPCC推荐方法及中国的排放参数核算11个典型城市2006—2015年间化石能源消费产生的CO₂排放量。根据各城市经济发展和CO₂排放特征将之分为四类:经济高度发达城市(北京、上海、广州)、高碳排放城市(重庆、乌鲁木齐、唐山)、低排放低增长城市(哈尔滨、呼和浩特和大庆)和低排放高增长城市(贵阳、合肥),并运用对数平均迪氏指数法(Logarithmic Mean Divisia Index,即LMDI分解法)对比分析了四类城市CO₂排放量的影响因素。结果表明:(1)研究期内大部分城市CO₂排放总量有所增加,仅北京和广州呈下降趋势,工业部门CO₂排放在城市排放总量及其变化中占据主导地位;四类城市的人均CO₂排放量表现出与排放总量相...     

Life cycle of CO2-emissions from electric vehicles and gasoline vehicles utilizing a process-relational model

This article aims at estimating life cycle CO₂ emissions from electric vehicles (EV) and gasoline vehicles (GV), although the estimation in this study is not an LCA according to ISO14040s. For this purpose, a mathematical tool called the Process-relational model was developed. The Process-relational model is used for establishing life cycle inventories. The model has a structure which improved the principle of input-output analysis in econometrics that only one product is generated by one process. This model enabled us to overcome difficulties of LCA in retracing complicated repercussions among production systems. Then, life cycle CO₂, emissions from electric vehicles (EV) and gasoline vehicles (GV) were estimated with this model. Estimated results indicated that the manufacture and driving of EV resulted in less CO₂ emissions than chose of GV. However, the difference between EV and GV dramatically changed depending on traffic situations. Namely, the difference became larger as the average velocity of the vehicles became lower. We also compared CO₂, emission from manufacturing EV with that from driving EV. The share of manufacture was shown to increase in total CO₂, emissions as the average velocity of the EV became higher. In conclusion, we clarified the direction of research and development of EV and GV for reducing the life cycle CO₂.     

Model for the Part Manufacturing and Vehicle Assembly Component of the Vehicle Life Cycle Inventory

A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The model is based on a process‐level approach, accounting for all significant materials by their transformation processes (aluminum castings, polyethylene blow molding; etc.) and plant operation activities (painting; heating, ventilation, and air conditioning [HVAC], etc.) germane to VMA. Using quantitative results for these material/transformation process pairings, a percent‐by‐weight material/transformation distribution (MTD) function was developed that permits the model to be applied to a range of vehicles, both conventional and advanced (e.g., hybrid electric, light weight, aluminum intensive). Upon consolidation of all inputs, the model reduces to two terms: one proportional to vehicle mass and a plant overhead per vehicle term. When the model is applied to a materially well‐characterized conventional vehicle, reliable estimates of cumulative energy consumption (34 gigajoules/vehicle) and carbon dioxide (CO₂) emissions (2 tonnes/vehicle) with coefficients of variation are computed for the VMA life cycle stage. Due to the more comprehensive coverage of manufacturing operations, our energy estimates are on the higher end of previously published values. Nonetheless, they are still somewhat underestimated due to a lack of data on overhead operations in part manufacturing facilities and transportation of parts and materials between suppliers and vehicle manufacturing operations. For advanced vehicles, the material/transformation process distribution developed above needs some adjusting for different materials and components. Overall, energy use and CO₂ emissions from the VMA stage are about 3.5% to 4.5% of total life cycle values for vehicles.     

Regional assessment of local emissions of electric vehicles using traffic simulations for a use case in Germany

Purpose

In order to assess the global and local environmental impacts of different penetration rates of electric vehicles (EVs) within a region, we developed a life cycle approach based on a detailed traffic simulation assessing local emissions for individual roads with a high time resolution. The aim was to estimate the reduction potential of local emissions such as particulate matter within a region through a substitution of conventional with electric vehicles.

Materials and methods

The chosen approach assessing local emissions includes a detailed traffic simulation of a vehicle fleet composed of individual vehicles with a daily schedule. The driving pattern is modeled based on a survey of driving patterns in Germany. Incorporation of traffic density for each road and emissions of electric and conventional vehicles permits conclusions on the reduction potential for each street. Moreover, a feasible reduction potential for a particular region can be assessed. A case study for Aachen, Germany is presented within this paper. For the classification of the local emissions with the usual life cycle assessment approach, a comparison of EV, PHEV, and conventional vehicles has been conducted for Germany providing the results for impact categories according to CML 2001.

Results and discussion

Based on simulation results, an estimation of the reduction potential for Aachen for different penetration rates of electric vehicles including particulate matter (PM₁₀), carbon monoxide (CO), and nitrogen oxygen (NOx) is carried out. Electric vehicles possess the highest reduction potential for CO and NOx. Assuming 50?% of the total vehicle fleet in 2010 substituted by electric vehicles, local emissions of CO reduce by 46.6?%, for NOx by 38.8?%, and for PM₁₀ by 22.4?%. Due to fluctuations in driving patterns throughout a day, the results are highly time dependent. However, improvements in combustion engine technologies results in an increased reduction potential for conventional vehicles. The direct comparison between the vehicle types showed that the benefit of electric vehicles depends on the considered impact category.

Conclusions

Electric vehicles are able to reduce local emissions within a region. Moreover, this approach focusing on the use phase of vehicles within a regional assessment and the resulting local emissions as well as the detailed analysis of the driving behavior allows a distinguished assessment of the reduction potential of electric vehicles. Additionally, an assessment of policy measures such as drive restrictions for conventional vehicles can be simulated on the base of this approach.     

An integrated approach to improving fossil fuel emissions scenarios with urban ecosystem studies

The future trajectory of fossil fuel emissions is one of the largest uncertainties in predicting climate change. While global emissions scenarios are ultimately of interest for climate modeling, many of the factors that influence energy and fuel consumption operate on a local rather than global level. However, there have been relatively few comprehensive studies of the ecological and socioeconomic processes that will determine the future trajectory of net carbon dioxide (CO₂) emissions at local and regional scales. We conducted an interdisciplinary, whole ecosystem study of the role of climate, urban expansion, urban form, transportation, and the urban forest in influencing net CO₂ emissions in the Salt Lake Valley, Utah, a rapidly urbanizing region in the western U.S. Our approach involved a detailed emissions inventory validated with atmospheric measurements, as well as a system dynamics model of future CO₂ emissions developed in collaboration with local stakeholders. The model highlighted the importance of a positive feedback between urban land development and transportation investments that may strongly affect emissions by amplifying declines in developmental densities and increases in vehicular traffic. Simulations suggested that while doubling the density of tree planting would have a negligible effect on total urban CO₂ emissions, land use and transportation policies that dampen the intensity of the urban sprawl feedback could result in a 22% reduction in CO₂ emissions by 2030 relative to a business as usual scenario. We suggest that by advancing our mechanistic understanding of energy and fuel consumption regionally, this urban ecosystem approach has great potential for improving emissions scenario studies if replicated in other cities and urbanizing regions.     

A Study of Energy Consumption and Exhaust Emissions from Beijing's Civil Vehicles from Years 2008 to 2020

The number of Beijing's civil vehicles is growing rapidly due to the great support of the automobile industry and the Chinese government and the increasing average per capita income of China's people. Exhaust emissions from vehicles have already become the main source of Beijing's air pollution. Based on the Long-range Energy Alternatives Planning System (LEAP), this article predicts the energy consumption and exhaust emissions from Beijing's civil vehicles. Also, we estimated the reduction potentials of China's new fuel consumption standards and exhaust pollutants standards that will be implemented from 2008 to 2020. Two scenarios were developed: “Business as Usual” (BAU) and “New Standard” (NS). In the BAU scenario, the Chinese government would do nothing to improve the fuel consumption standards and exhaust pollutants standards in the future. In the NS scenario, the Chinese government would implement more strict fuel consumption standards and exhaust pollutants standards for Beijing's civil vehicles. By comparing the results of the two scenarios for year 2020, the energy consumption will experience a reduction of 7.8%, and the exhaust pollutants CO, HC, NO_X, PM, and the emissions of CO₂ would decrease by 43.3%, 36.4%, 60.3%, 81.2%, and 7.8%, respectively.     

Do nuclear and renewable energy improve the environment? Empirical evidence from the United States

The central focus of this article is to assess the dynamic effects of nuclear and renewable energy consumption on CO₂ emissions, for a given level of income and energy consumption. We apply an autoregressive distributed lag (ARDL) approach to cointegration to U.S. data from 1960 to 2010. We find that nuclear energy consumption indeed reduces CO₂ emissions in both the short- and long-run, while renewable energy consumption does only in the short-run. We also find that income increases CO₂ emissions in the long-run after showing the environmental Kuznets curve (EKC) initially in the short-run. Finally, energy consumption is found to have a negative impact on reducing CO₂ emissions in the short- and long-run.     

Greenhouse gas emissions from forestry in East Norway

Purpose

So far no calculations have been made for greenhouse gas (GHG) emissions from forestry in East Norway. This region stands for 80 % of the Norwegian timber production. The aim of this study was to assess the annual GHG emissions of Norwegian forestry in the eastern parts of the country from seed production to final felling and transport of timber to sawmill and wood processing industry (cradle-to-gate inventory), based on specific Norwegian data.

Methods

The life cycle inventory was conducted with SimaPro applying primary and secondary data from Norwegian forestry. GHG emissions of fossil-related inputs from the technosphere were calculated for the functional unit of 1 m³ timber extracted and delivered to industry gate in East Norway in 2010. The analysis includes seed and seedling production, silvicultural operations, forest road construction and upgrading, thinning, final felling, timber forwarding and timber transport on road and rail from the forest to the industry. Norwegian time studies of forestry machines and operations were used to calculate efficiency, fuel consumption and transport distances. Due to the lack of specific Norwegian data in Ecoinvent, we designed and constructed unit processes based on primary and secondary data from forestry in East Norway.

Results and discussion

GHG emissions from forestry in East Norway amounted to 17.893 kg CO₂-equivalents per m³ of timber delivered to industry gate in 2010. Road transport of timber accounted for almost half of the total GHG emissions, final felling and forwarding for nearly one third of the GHG emissions. Due to longer road transport distances, pulpwood had higher impact on the climate change category than saw timber. The construction of forest roads had the highest impact on the natural land transformation category. The net CO₂ emissions of fossil CO₂ corresponded to 2.3 % of the CO₂ sequestered by 1 m³ of growing forest trees and were compared to a calculation of biogenic CO₂ release from the forest floor as a direct consequence of harvesting.

Conclusions

Shorter forwarding and road transport distances, increased logging truck size and higher proportion of railway transport may result in lower emissions per volume of transported timber. A life cycle assessment of forestry may also consider impacts on environmental categories other than climate change. Biogenic CO₂ emissions from the soil may be up to 10 times higher than the fossil-related emissions, at least in a short-term perspective, and are highly dependent on stand rotation length.     

Toward a Carbon Dioxide Neutral Industrial Park

The industrial park of Herdersbrug (Brugge, Flanders, Belgium) comprises 92 small and medium‐sized enterprises, a waste‐to‐energy incinerator, and a power plant (not included in the study) on its site. To study the carbon dioxide (CO₂) neutrality of the park, we made a park‐wide inventory for 2007 of the CO₂ emissions due to energy consumption (electricity and fossil fuel) and waste incineration, as well as an inventory of the existing renewable electricity and heat generation. The definition of CO₂ neutrality in Flanders only considers CO₂ released as a consequence of consumption or generation of electricity, not the CO₂ emitted when fossil fuel is consumed for heat generation. To further decrease or avoid CO₂ emissions, we project and evaluate measures to increase renewable energy generation. The 21 kilotons (kt) of CO₂ emitted due to electricity consumption are more than compensated by the 25 kt of CO₂ avoided by generation of renewable electricity. Herdersbrug Industrial Park is thus CO₂ neutral, according to the definition of the Flemish government. Only a small fraction (6.6%) of the CO₂ emitted as a consequence of fossil fuel consumption (heat generation) and waste incineration is compensated by existing and projected measures for renewable heat generation. Of the total CO₂ emission (149 kt) due to energy consumption (electricity + heat generation) and waste incineration on the Herdersbrug Industrial Park in 2007, 70.5% is compensated by existing and projected renewable energy generated in the park. Forty‐seven percent of the yearly avoided CO₂ corresponds to renewable energy generated from waste incineration and biomass fermentation.     

Environmental impacts of hybrid and electric vehicles—a review

Purpose

A literature review is undertaken to understand how well existing studies of the environmental impacts of hybrid and electric vehicles (EV) address the full life cycle of these technologies. Results of studies are synthesized to compare the global warming potential (GWP) of different EV and internal combustion engine vehicle (ICEV) options. Other impacts are compared; however, data availability limits the extent to which this could be accomplished.

Method

We define what should be included in a complete, state-of-the-art environmental assessment of hybrid and electric vehicles considering components and life cycle stages, emission categories, impact categories, and resource use and compare the content of 51 environmental assessments of hybrid and electric vehicles to our definition. Impact assessment results associated with full life cycle inventories (LCI) are compared for GWP as well as emissions of other pollutants. GWP results by life cycle stage and key parameters are extracted and used to perform a meta-analysis quantifying the impacts of vehicle options.

Results

Few studies provide a full LCI for EVs together with assessment of multiple impacts. Research has focused on well to wheel studies comparing fossil fuel and electricity use as the use phase has been seen to dominate the life cycle of vehicles. Only very recently have studies begun to better address production impacts. Apart from batteries, very few studies provide transparent LCIs of other key EV drivetrain components. Estimates of EV energy use in the literature span a wide range, 0.10?C0.24?kWh/km. Similarly, battery and vehicle lifetime plays an important role in results, yet lifetime assumptions range between 150,000?C300,000?km. CO₂ and GWP are the most frequently reported results. Compiled results suggest the GWP of EVs powered by coal electricity falls between small and large conventional vehicles while EVs powered by natural gas or low-carbon energy sources perform better than the most efficient ICEVs. EV results in regions dependant on coal electricity demonstrated a trend toward increased SO _x emissions compared to fuel use by ICEVs.

Conclusions

Moving forward research should focus on providing consensus around a transparent inventory for production of electric vehicles, appropriate electricity grid mix assumptions, the implications of EV adoption on the existing grid, and means of comparing vehicle on the basis of common driving and charging patterns. Although EVs appear to demonstrate decreases in GWP compared to conventional ICEVs, high efficiency ICEVs and grid-independent hybrid electric vehicles perform better than EVs using coal-fired electricity.     

Local vehicles add nitrogen to moss biomonitors in a low-traffic protected wilderness area as revealed by a long-term isotope study

Public use of protected areas is typically encouraged, but visitors arriving by vehicles may alter the natural areas they seek. Vehicle emissions add nitrogen oxides (NO_x) and ammonia (NH₃) to the air, which can increase the amount of plant-available (reactive) nitrogen, a limiting nutrient. Changes in ecosystem processes as a result of increases in nitrogen availability are at odds with the goals of many protected wilderness areas that are typically accessed by vehicles. In this multi-year study (2003–2019), we tested whether emissions from local vehicles entered the forest ecosystem adjacent to a highway in a protected wilderness valley near a mid-sized city (Calgary, Alberta, Canada). We examined the concentration of NO₂ in the air and the abundance of combustion-derived nitrogen isotopes (δ¹⁵N) in naturally-occurring forest moss (Hylocomium splendens and Pleurozium schreberi) within 20 m of the highway as a function of traffic levels that varied independently at two scales: along the highway and among years. Within the valley, we observed a gradient in the number of vehicles that was greatest where vehicles enter the valley, with a corresponding pattern for NO₂ concentrations in air. Traffic volume also varied among years, with the highest year having almost twice as many vehicles in the summer as the lowest year. δ¹⁵N values in forest moss displayed similar patterns as traffic both within and among years, signalling that nitrogen from vehicle emissions entered the local ecosystem corresponding to local traffic levels. Because vehicle emissions enter natural ecosystems that are intended to be conserved, vehicle use must be considered in the management of protected natural areas.     

Estimating the environmental Kuznets curve for Spain by considering fuel oil prices (1874–2011)

We perform a structural analysis on an environmental Kuznets curve (EKC) for Spain by exploiting long time series (1874–2011) and by using real oil prices as an indicator of variations in fuel energy consumption. This empirical strategy allows us to both, capture the effect of the most pollutant energy on carbon dioxide (CO₂) emissions and, at the same time, preclude potential endogeneity problems derived from the direct inclusion of fuel consumption in econometric specification. Knowing the extent to which oil prices affect CO₂ emissions has a straightforward application for environmental policy. The dynamics estimates of the long and short-term relationships among CO₂, economic growth and oil prices are built through an autoregressive distributed lag (ARDL) model. Our test results support the EKC hypothesis. Moreover, real oil prices are clearly revealed as a valuable indicator of pollutant energy consumption.     

A new hybrid method for reducing the gap between WTW and LCA in the carbon footprint assessment of electric vehicles

Purpose

The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO₂ emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.

Methods

The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.

Results and discussion

A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.

Conclusions

The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.

     

CO2 emissions related to the electricity consumption in the european primary aluminium production a comparison of electricity supply approaches

The objective of this study is to estimate the specific CO₂ emissions related to the electricity consumption in the European primary aluminium production and to compare different choices of system boundaries of its electricity supply. The study covers all European aluminium smelters, except Russia and the Ukraine. The concepts of single power plant supply, contract mix, national mix and European grid mix are compared as alternative choices of system boundaries of the electricity supply. The calculations of the electricity consumption in the electrolysis are based on plant-specific information on technology, production and electricity supply. Detailed fuel and country-specific data on CO₂ emissions of the relevant types of electricity generation are used with a ‘from cradle to grave’ perspective. The specific emissions calculated for Europe fall into the range of 6-7 kg CO₂/kg Al depending on the choice of system boundaries.     

Impact of Grazing Intensity and Seasons on Greenhouse Gas Emissions in Tropical Grassland

Greenhouse gases (GHG) can be affected by grazing intensity, soil, and climate variables. This study aimed at assessing GHG emissions from a tropical pasture of Brazil to evaluate (i) how the grazing intensity affects the magnitude of GHG emissions; (ii) how season influences GHG production and consumption; and (iii) what are the key driving variables associated with GHG emissions. We measured under field conditions, during two years in a palisade-grass pasture managed with 3 grazing intensities: heavy (15 cm height), moderate (25 cm height), and light (35 cm height) N₂O, CH₄ and CO₂ fluxes using static closed chambers and chromatographic quantification. The greater emissions occurred in the summer and the lower in the winter. N₂O, CH₄, and CO₂ fluxes varied according to the season and were correlated with pasture grazing intensity, temperature, precipitation, % WFPS (water-filled pores space), and soil inorganic N. The explanatory variables differ according to the gas and season. Grazing intensity had a negative linear effect on annual cumulative N₂O emissions and a positive linear effect on annual cumulative CO₂ emissions. Grazing intensity, season, and year affected N₂O, CH₄, and CO₂ emissions. Tropical grassland can be a large sink of N₂O and CH₄. GHG emissions were explained for different key driving variables according to the season.     

Economic growth,electricity consumption,urbanization and environmental degradation relationship in United Arab Emirates

The present study explores the relationship between economic growth, electricity consumption, urbanization and environmental degradation in case of United Arab Emirates (UAE). The study covers the quarter frequency data over the period of 1975–2011. We have applied the ARDL bounds testing approach to examine the long run relationship between the variables in the presence of structural breaks. The VECM Granger causality is applied to investigate the direction of causal relationship between the variables. Our empirical exercise reported the existence of cointegration among the series. Further, we found an inverted U-shaped relationship between economic growth and CO₂ emissions i.e. economic growth raises energy emissions initially and declines it after a threshold point of income per capita (EKC exists). Electricity consumption declines CO₂ emissions. The relationship between urbanization and CO₂ emissions is positive. Exports seem to improve the environmental quality by lowering CO₂ emissions. The causality analysis validates the feedback effect between CO₂ emissions and electricity consumption. Economic growth and urbanization Granger cause CO₂ emissions.     

Can energy policies affect the cycle of carbon emissions? Case study on the energy consumption of industrial terminals in Shanghai,Jiangsu and Zhejiang

This paper proposes an approach to calculate the time series of cumulative carbon dioxide (CO₂) emissions between 1995 and 2014 based on industrial energy consumption data in three Eastern China jurisdictions in Shanghai, Jiangsu and Zhejiang during these two decades. Using the Hodrick-Prescott filter, the fluctuation components of the cumulative CO₂-emission time-series data in the three provinces are obtained. Subsequently, a grey correlation-based change-point search algorithm is used to determine change-points in these data. Additionally, the CO₂-emission time-series is divided into stages based on the change-points. The cycle characteristics of national energy policies, laws, and regulations are compared with those of the cumulative CO₂-emission cycle of the three provinces to analyse the impact of energy policies on CO₂ emissions. This study shows that, although the industrial structure and trends in the CO₂ emission time-series data of the three provinces are different, their cumulative CO₂-emission cycle remains the same from 1995 to 2014. The variation characteristics of the cumulative CO₂ emissions for each cycle during this period are well aligned with the stage characteristics of energy policies, laws, and regulations, indicating that energy policies play a consistent role in regulating such emissions. This study examines low-carbon production and sustainable energy development, and offers suggestions for issuing and perfecting energy policies, laws, and regulations, considering the indicators of energy consumption and CO₂ emissions.