Carbon Emission Pinch Analysis: an application to the transportation sector in Iskandar Malaysia for 2025

Energy sector had growth significantly over the year which cause serious global warming issues. This problem arises from the results of carbon emission. Thus, a proper mitigation strategies are needed to tackle this issues. This paper is aim to apply carbon emission pinch analysis (CEPA) for transportation sector in Iskandar Malaysia (IM). The modified method is applied to study the minimum requirement of electricity need to be generated to implement electric vehicle (EV) based on current policy available and to reach the new emission target by year 2025. The road transportation and rail transportation were considered in the transport composite curve. The alternatives available to reduce emission in IM are by increasing public transport modal share, fuel switching from petrol and diesel to natural gas and biofuels, and increase transport efficiency by plug-in hybrid and EV. As a results, the estimated total amount of 0.25 TJ of electricity is needed for EV to be implemented.

Owing to the lockdowns associated with the Coronavirus Disease 2019(COVID-19) pandemic, carbon emissions were significantly reduced. However, the accurate impacts on the personal transport sector since then remain unclear. To further investigate the influence of sudden public health emergencies on actual carbon emissions from personal electric vehicles, this paper examined the travel patterns and corresponding carbon emissions of plug-in hybrid electric vehicles (PHEVs) operating in Chongqing, China, before and after COVID-19. The results revealed that the pandemic has reshaped the travel patterns of vehicle drivers, with a 9 % reduction in the postpandemic fleet average daily travel mileage. Currently, the total daily carbon emissions of a PHEV with a range of 80 km (PHEV80) are 6.24 kg, which is 13 % lower than emissions from conventional vehicles and 32 % higher than those from electric battery-powered vehicles before the pandemic. Since COVID-19, there has been a 24 % decrease in carbon emissions from PHEV80 vehicles for the fleet and a 30 % maximum increase for individuals. Furthermore, considering the integration of 50 % renewable energy into China’s power grid by 2025, PHEVs can better mitigate the fluctuations in carbon emissions associated with sudden public health emergencies compared with conventional vehicles.

Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.

Land use changes lead to changes in the functions of different types of carbon sources and sinks, which are key sources of carbon emissions. The study of carbon emissions and its influencing factors in the Aksu River Basin from the perspective of land use change is of great importance for the promotion of integrated protection and restoration of mountains, water, forests, fields, lakes, grasslands, sand, and ice in the basin and to help achieve the goal of carbon peaking and carbon neutrality. Based on four periods of land use data and socio-economic data from 1990 to 2020, the total carbon emissions from land use were measured, and the spatial and temporal trajectories of carbon emissions and their influencing factors were explored. The results showed that:① from 1990 to 2020, arable land, forest land, construction land, and unused land showed a general increasing trend, whereas grasslands and water areas showed a decreasing trend. The spatial change in land use types was mainly characterized by the conversion of grasslands and unused land into arable land, and 83.58 % of the arable land conversion areas were concentrated in the southwest of Wensu, Aksu, and the northern part of Awat. ② The total net carbon emissions in the basin showed a continuous growth trend from 1990 to 2020, with a cumulative increase of 14.78×104 t. The increase in arable land was a key factor causing an increase in net carbon emissions in the basin. ③ The spatial distribution pattern of land use carbon emissions in the basin was high in the middle and low in the fourth, with significant changes in net carbon emissions mainly in the southern part of Wensu, Aksu, Awat, and Alaer. ④ Human activities had the strongest driving effect on land use carbon emissions, with their effects gradually increasing from east to west. The contribution of average annual temperature to land use carbon emissions was mainly concentrated in the eastern part of Aksu and the northern part of Awat, whereas average annual rainfall had a strong inhibitory effect on the northern part of Wensu and the western part of Aheqi.

The rising concerns over global climate change and depleting fossil fuel reserves are two of the main reasons for the ongoing efforts towards the electrification of the transportation sector. While greenhouse gases (GHGs) emissions from other sectors are generally falling, emissions from the road transport have increased over the past few decades, with both full electric vehicles (FEVs) and plug-in hybrid electric vehicles (PHEVs) being recognized as potential alternatives to combat climate change and reduce GHG emissions. However, wide-spread integration of FEVs and PHEVs will substantially increase the load on the power system which will eventually affect the reliability of existing power systems. In this paper, a probabilistic model for integrating FEVs and PHEVs with existing power grids is proposed that incorporates important FEV and PHEV characteristics, such as battery capacity, charge depleting distance, and charging rates. In addition, user behavior is taken into account through time of recharging, arrival and departure times, and daily miles driven. Furthermore, different charging strategies, i.e., opportunistic charging and controlled charging with and without vehicle-to-grid (V2G) scheme have been considered to evaluate the impact of FEVs and PHEVs on the composite power system. IEEE-RTS-79 system is used to examine the proposed probabilistic technique considering different FEV and PHEV penetration levels as well as charging strategies. Simulation results show that even a relatively low penetration level of FEVs or PHEVs might have a significant impact on the system reliability unless a proper charging and/or discharging schemes are utilized.

A comparative assessment of CO2 emission between gasoline, electric, and hybrid vehicles: A Well-To-Wheel perspective using agent-based modeling

This study examines the nexus between business strategy and carbon emissions by utilising a dataset of U.S. firms from 2007 to 2020. It focuses on two broad types of firms, that is, prospectors and defenders. Regarding carbon emissions, we consider total emissions (Scope 1 & 2), direct emissions (Scope 1) and indirect emissions (Scope 2). The results reveal a significant association between business strategy and total carbon emissions as well as direct carbon emissions. Notably, the results suggest that prospectors, compared to defenders, display higher levels of total and direct carbon emissions. Our findings contribute to the debate on whether prospectors in developed countries mismanage sustainability issues. The study offers valuable insights into the interplay between business strategy and carbon emissions and provides empirical evidence that business strategy is an important determinant of total and direct carbon emissions.

Impact of the electricity mix and use profile in the life-cycle assessment of electric vehicles

Fiscal decentralization is the source of China’s rapid economic growth, but inevitably leads to a surge in total carbon emissions. We verify whether the intermediary mechanism of real estate development and the urban construction investment bonds (UCIB) can share the fiscal pressure of local governments to provide empirical support to clarify and solve the realistic decentralization dilemma. This study conducted a spatial analysis of panel data from 266 Chinese prefecture-level cities from 2006 to 2019 and obtains the following findings. (1) Carbon emissions are spatially correlated, displaying the characteristics of ‘one glory and one loss’. (2) Fiscal decentralization drives an increase in carbon emissions over the entire spatial region. (3) The decomposition results show that although fiscal decentralization aggravates local carbon emission growth, it benefits the carbon emission reduction of neighboring regions. (4) The eastern regions’ fiscal decentralization does not significantly affect carbon emissions, whereas the central and western regions’ fiscal decentralization causes an upsurge in total carbon emissions. (5) Fiscal decentralization has promoted the prosperous development of the real estate industry, which positively influences carbon emissions. (6) The UCIB has a negative moderating effect on fiscal decentralization and carbon emissions, implying that it plays a role in alleviating financial pressure on local governments. Accordingly, we propose relevant countermeasures: adjusting the degree of decentralization, controlling real estate development, and issuing UCIB.

Effectively exploring the impacts of urban spatial structures on carbon dioxide emissions is important for achieving low-carbon goals. However, most previous studies have examined the impact of urban spatial structure on total carbon emissions based only on polycentricity. Fine-grained studies on subsectoral carbon emissions and other dimensions of urban spatial structure are lacking. Therefore, our study comprehensively explores the impact of urban dispersion and polycentricity on total carbon emissions and carbon emissions of four subsectors (industry, power, civilian, and transportation) from 2012 to 2017 while considering the effects of city size. Results reveal that the nighttime light data is useful for measuring urban spatial structure, and a polycentric, decentralized urban spatial structure correlates with the reduced total carbon emissions and transportation carbon emissions. Meanwhile, a decentralized urban spatial structure gives rise to lower industrial carbon emissions and civilian carbon emissions, whereas a multicenter urban spatial structure contributes to minimizing carbon emissions from power systems. However, in small and medium-sized cities, urban spatial structure differently affects the total carbon and transportation carbon emissions.

Electrified vehicles, including plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs), have the potential to reduce greenhouse gas (GHG) emissions from personal transportation by shifting energy demand from gasoline to electricity. GHG reduction potential depends on vehicle design, adoption, driving and charging patterns, charging infrastructure, and electricity generation mix. We construct an optimization model to study these factors by determining optimal design of conventional vehicles (CVs), hybrid electric vehicles (HEVs), PHEVs, and BEVs and optimal allocation of vehicle designs and charging infrastructure in the fleet for minimum lifecycle GHG emissions over a range of scenarios. We focus on vehicles with similar size and acceleration to a Toyota Prius under urban EPA driving conditions. We find that under today’s U.S. average grid mix, the vehicle fleet allocated for minimum GHG emissions includes HEVs and PHEVs with ~30 miles (48 km) of electric range. Allocating only CVs, HEVs, PHEVs, or BEVs will produce 86%, 1%, 0%, or 13+% more life cycle GHG emissions, respectively. Unlike BEVs, PHEVs do consume some gasoline; however, PHEVs can power a large portion of vehicle miles on electrical energy while accommodating infrequent long trips without need for a large battery pack, with its corresponding production and weight implications. Availability of workplace charging for 90% of vehicles optimistically reduces optimized GHG emissions by 0.5%. Under decarbonized grid scenarios, larger battery packs are more competitive and reduce life cycle GHG emissions significantly. Future work will relax modeling assumptions and address life cycle cost and cost-effectiveness of GHG reductions.

Estimating carbon emissions and assessing their contribution are critical steps toward China’s objective of reaching a “carbon peak” in 2030 and “carbon neutrality” in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs.

In the context of the "dual carbon" strategy, the transportation industry actively seeks a new development path of low-carbon transformation, which is one of the hot spots in China's carbon emission reduction. Based on the Tapio decoupling and logarithmic mean Divisia index （LMDI） models, this study analyzed the carbon emission characteristics, decoupling status, and driving factors of China's provincial transportation industry from multiple perspectives, such as overall, time period, and regional decomposition from 2012 to 2021. The results showed that China's total carbon emissions from transport sector exhibited an increasing trend with passing years overall, but growth rate showed decreasing trend. The spatial distribution pattern of carbon emissions from transportation industry was higher in the southeast and lower in northwest. During the past decade, 40.0% of the provinces achieved absolute decoupling between carbon emissions from transportation industry and economic development, and 53.3% of the provinces achieved relative decoupling. From the perspective of the transportation industry, economic growth, population size, and carbon emission coefficient promoted an increase in carbon emissions, while transportation energy intensity and industry scale inhibited the increase in carbon emissions. Therefore, during the process of realizing the "dual carbon" goal in China, each province should formulate differentiated reduction policies in regional carbon emissions according to local conditions, actively assume emission reduction responsibilities, increase efforts to promote the decoupling process, and promote the green and low-carbon transformation of the transportation industry.

Both automakers and electricity generators are facing increasingly more stringent greenhouse gas (GHG) emission targets. With the introduction of plug-in hybrid and electric vehicles, the transportation and electricity generation sectors become connected. This provides an opportunity for both sectors to work jointly to achieve cost efficient reduction of CO2 emissions. Due to the low cost and low carbon content of natural gas (NG), NG enabled vehicles are drawing increasing attention. With GHG targets rapidly decreasing, how to judiciously choose among plug-in hybrid vehicles, electric vehicles, NG-enabled vehicles, and gasoline vehicles to save societal cost is worth serious consideration. On the other hand, gasoline and NG prices play an important role in this decision-making process. In order to estimate the impact of gasoline and NG prices and quantify the benefit of the collaboration between automakers and electricity generators, an optimization model is developed to evaluate the total societal cost and CO2 emissions for both sectors. Various scenario analyses are conducted to understand the cost and capacity planning differences when gasoline and NG prices vary while the two sectors can work jointly or independently to meet the CO2 emission constraints. These results help us understand the impact of gasoline and NG prices in achieving GHG reduction targets for the two major sectors of CO2 emissions in the United States.

Techno-economic comparison of electrification for heavy-duty trucks in China by 2040