Electric vehicle adoption and local PM2.5 reduction: Evidence from China

Wu, Yingwen; Gu, Fengshou; Ji, Yangjian; Ma, Shaochao; Guo, Jianfeng

doi:10.1016/j.jclepro.2023.136508

Cited by 10 publications

(4 citation statements)

References 68 publications

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“…Relating to ENAW, previous work on biogas technology acceptance empirically proved that the relative advantage of innovative technology had central importance in Pakistan [22]. Moreover, Wu et al [21] verified a significant connection between ELV acceptance and PM2.5 emissions in China, verifying the existence of an empirical link between the two variables. Turning to SAELV, our results confirmed those of Sahoo et al [30] found in India.…”

Section: Structural Model Results and Discussionmentioning

confidence: 91%

“…In this respect, Sumrin et al [20] highlighted that the ENAW is dependent on a variety of sociological, environmental, and significant factors that aid in the improvement of SAELV and BBEN. Wu et al [21] utilized a fixed effects model to examine the links between PM2.5 emissions and ELV acceptance at China's provincial level. The authors revealed that ELV acceptance significantly reduced those emissions.…”

Section: Environmental Awareness Aspect (Enaw)mentioning

confidence: 99%

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Heterogeneous Factors Influencing Electric Vehicle Acceptance: Application of Structural Equation Modeling

Guo

Huang²,

Chen³

et al. 2023

WEVJ

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Since electric vehicle (ELV) deployment can contribute to overall renewable energy sources, exploration of the heterogeneous influence factors (HIFs) affecting the willingness to accept ELVs can assist in the realization of sustainable development goals, particularly universal access to affordable energy for all. In this research, we explored the HIFs that influence the willingness of individuals to accept ELVs (WAELV) within an integrated decision-making (IDM) framework. We established the IDM conceptual framework through the incorporation of HIFs, notably including the environmental and health benefits of ELVs, knowledge about innovation, and the benefits regarding the built environment and creating a comprehensive structure. We analyzed data gathered through questionnaires from urban and peri-urban areas of the Shandong province (China) by employing the partial least square structural equation modeling technique, which is an appropriate tool for analyzing data measured on a Likert scale. The key findings were as follows. Firstly, the capital cost of ELVs was found to be a significant barrier to the WAELV of individuals. Secondly, among other factors, the societal aspect of ELVs and the environmental awareness aspect were drivers of the WAELV of individuals across all the data samples. However, benefits for the built environment, knowledge about innovation, and the environmental and health benefits of ELVs only positively drove the WAELV of individuals in the urban setting and for the overall sample. Thirdly, these three HIFs were identified as neutral factors in the peri-urban areas. Thus, a clear disparity was detected between the urban and peri-urban areas in terms of factors influencing the WAELV of individuals. Finally, the social aspect of ELVs was revealed as the strongest driver, while benefits for the built environment turned out to be the weakest factor. Based on these findings, some crucial policies are here extracted.

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Section: Structural Model Results and Discussionmentioning

confidence: 91%

Section: Environmental Awareness Aspect (Enaw)mentioning

confidence: 99%

Heterogeneous Factors Influencing Electric Vehicle Acceptance: Application of Structural Equation Modeling

Guo

Huang²,

Chen³

et al. 2023

WEVJ

View full text Add to dashboard Cite

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“…The concentration of SOC, however, was almost unchanged, and thereby the SOC/OC ratio increased from 48.1% to 72.9%. TC/PM 2.5 decreased from 25.9% in 2015 to 15.4% in 2021, and CA/PM 2.5 decreased from 40.3% to 29.6%, possibly due to the control of emission sources such as biomass burning and vehicle emissions [76,77]. The strict mobility control of transportation and industrial activities in Guangzhou during the COVID-19 pandemic might also contribute substantially to the reduced EC emissions [78,79].…”

Section: Blh Ormentioning

confidence: 99%

Seasonal and Day–Night Variations in Carbonaceous Aerosols and Their Light-Absorbing Properties in Guangzhou, China

Su,

Zhang,

Liu

et al. 2023

Atmosphere

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Carbonaceous aerosols (CAs), including elemental carbon (EC) and organic carbon (OC), have become the dominant component in PM2.5 in many Chinese cities, and it is imperative to address their spatiotemporal variations and sources in order to continually improve air quality. In this study, the mass concentrations and light absorption properties of EC and OC in PM2.5 were investigated at diverse sites in Guangzhou, in the winter of 2020 and the autumn of 2021, using the DRI Model 2015 thermal–optical carbon analyzer. The results showed that total EC and organic matter (OM = OC × 1.8) could account for nearly 30% of the PM2.5 mass concentrations. Secondary production was the most important source for OC, with secondary OC (SOC) percentages in the OC as high as 72.8 ± 7.0% in autumn and 68.4 ± 13.1% in winter. Compared to those in 2015, OC and EC concentrations were reduced by 25.4% and 73.4% in 2021, highlighting the effectiveness of control measures in recent years. The absorption coefficient of brown carbon at 405 nm (babs,BrC,405) decreased by over 40%, and the mass absorption coefficient (MAC) at 405 nm of total carbon (TC) decreased by over 30%. EC and OC concentrations and the light absorption of black carbon (babs,BC,405) showed no significant diurnal differences in both autumn and winter mainly because the reduction in anthropogenic emissions at night was compensated by the lowering of the boundary layer. Differentially, babs,BrC,405 was significantly lower during daytime than at night in autumn, probably due to the daytime photobleaching effect. The sources of EC, OC, BC, and BrC were preliminarily diagnosed by their correlation with typical source markers. In autumn, babs,BrC,405 might be related to biomass burning and coal combustion, while babs,BC,405 were largely related to vehicle emissions and coal combustion. In winter, babs,BrC,405 was closely related to coal combustion.

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“…As of 2021, the use of electric vehicles in China had achieved a cumulative CO 2 reduction of 85.6 million tons [16]. Meanwhile, the emissions of pollutants such as PM and NO x have also been significantly reduced [17,18]. Since 2015, the number of zero-emission commercial vehicles in China has also increased, but the growth rate is relatively slow.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Actual Usage and Emission Reduction Potential of Electric Heavy-Duty Trucks: A Case Study of a Steel Plant

Dou,

Ke,

Liang

et al. 2023

Atmosphere

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In order to understand the driving characteristics of electric heavy-duty trucks in practical application scenarios and promote their usage to replace diesel trucks, this study analyzed the actual usage of electric and diesel heavy-duty trucks in a steel factory based on vehicle-monitoring data and remote online monitoring data and estimated the emission reduction potential of the application of electric trucks by using a mileage-based method and the greenhouse gas emission model. The results showed that the electric heavy-duty trucks in the steel factory mostly operated for over 14 h, with a vehicle kilometers traveled (VKT) of 50–300 km each day, which could meet most of the demands of the transportation of the steel industry. The average daily energy consumption for most trucks falls within the range of 210–230 kWh/100 km, with higher consumption in winter than in summer, which can save approximately 18–26% in operating costs compared with diesel trucks. It is estimated that the usage of these electric heavy-duty trucks can achieve an annual reduction of 115.8 tons of NOx emissions, 0.7 tons of PM emissions, and 18,000 tons of CO2 emissions. To further promote the application of electric heavy-duty trucks in China, several policy suggestions, such as introducing priority road-right policies, promoting vehicle and battery leasing markets, and exempting zero-emission vehicles during heavy pollution days, were proposed.

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Electric vehicle adoption and local PM2.5 reduction: Evidence from China

Cited by 10 publications

References 68 publications

Heterogeneous Factors Influencing Electric Vehicle Acceptance: Application of Structural Equation Modeling

Heterogeneous Factors Influencing Electric Vehicle Acceptance: Application of Structural Equation Modeling

Seasonal and Day–Night Variations in Carbonaceous Aerosols and Their Light-Absorbing Properties in Guangzhou, China

Analysis of the Actual Usage and Emission Reduction Potential of Electric Heavy-Duty Trucks: A Case Study of a Steel Plant

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