انتشار دی اکسید کربن
ترجمه نشده

انتشار دی اکسید کربن

عنوان فارسی مقاله: اثرات مازاد راه آهن و جاده بر انتشار دی اکسید کربن در چین: تجزیه و تحلیل فضایی زمانی
عنوان انگلیسی مقاله: Spillover effects of railway and road on CO2 emission in China: A spatiotemporal analysis
مجله/کنفرانس: مجله تولید پاک – Journal of Cleaner Production
رشته های تحصیلی مرتبط: مهندسی عمران، مهندسی محیط زیست
گرایش های تحصیلی مرتبط: مهندسی راه و ترابری، آلودگی هوا
کلمات کلیدی فارسی: شبکه حمل و نقل، اثر مازاد، تجزیه و تحلیل فضایی زمانی، انتشار دی اکسید کربن، مدل دوربین فضایی پویا
کلمات کلیدی انگلیسی: Transportation network، Spillover effect، Spatiotemporal analysis، CO2 emission، Dynamic spatial Durbin model
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.jclepro.2019.06.278
دانشگاه: School of Management, Harbin Institute of Technology, Harbin, 150001, China
صفحات مقاله انگلیسی: 13
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 7.096 در سال 2018
شاخص H_index: 150 در سال 2019
شاخص SJR: 1.620 در سال 2018
شناسه ISSN: 0959-6526
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: دارد
کد محصول: E13094
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1. Introduction

2. Mechanism analysis

3. Methods and data

4. Results and discussions

5. Conclusions and policy implications

Acknowledgements

Appendixes

References

بخشی از مقاله (انگلیسی)

Abstract

Estimating the impact of transportation factors on environmental pressure is essential to find decarbonization pathways for the transportation sector. Existing research mainly focused on the economic impact of transportation factors, the environmental impact is not fully involved. To identify the coupling effect of transportation factors, this study explored the spillover effects of multiple factors on CO2 emission using the panel data of 30 administrative regions in China. A hybrid model combining expanded Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) and Spatial Durbin Model (SDM) was used to estimate spillover effects of population, economic, technological and transportation factors on CO2 emissions. And CO2 emission was calculated by the carbon emission from fossil fuel consumption (coal, oil and gas) and cement production according to the Intergovernmental Panel on Climate Change (IPCC) accounting method. The estimation results indicate the spatial and time-lagged effects were both obvious for CO2 emission. In addition, transportation factors including the railway factor and the road factor were both found to have significant positive effects on CO2 emission, 0.344% and 0.129% influence respectively. Based on research findings three main policy implications were proposed including the joint decision-making, the cross-regional de-carbonization evaluation and the integrated management. This study not only reveals important experimental problems but expands a rigorous model specification process.

Introduction

As one of the fundamental infrastructures, transportation network has an enormous impact on local, national and international environmental and economic system (Guimera et al., 2005; Wandelt et al., 2017). With the rapid urbanization, more and more transportation infrastructures were constructed to support passenger and freight transport. According to the statistical data from the Organization for Economic Co-operation and Development (OECD), China’s passenger turnover and freight turnover volume ranked first in the world in 2015 (OECD, 2015). Huge transport capacity not only brings challenges to transportation network but impacts environmental conditions and economic activities. CO2 emission is the main environmental negative output during the expansion of transportation network coupling economic development (Xie et al., 2017). The International Energy Agency (IEA) estimates the transportation sector consumes approximately 19% global energy directly and accounts for 23% CO2 emission related to energy (Van der Hoeven, 2012). And it is predicted that CO2 emission in the transportation sector will increase by approximately 50% by 2030 (IEA, 2009). In addition, it has been proved that the transport infrastructure plays an increasingly important role in the evolution of city networks (Jiao et al., 2017), the human mobility (Lee et al., 2014) and the city accessibility (Shaw et al., 2014). Therefore, exploring the socio-environmental impacts of the transportation network is essential for understanding the role of the transportation network and finding sustainable pathways for the transportation sector.