Influence of Energy Use in Road Vehicles on Environmental Degradation: A Comparative Study of Pakistan and China
道路車両におけるエネルギー使用が環境悪化に与える影響：パキスタンと中国の比較研究 (AI 翻訳)
ALI H
🤖 gxceed AI 要約
日本語
この研究は、パキスタンと中国におけるエネルギー使用と自動車がCO2排出に与える影響を調査した。自己回帰分布ラグモデルを用い、GDP、登録車両数、都市化、再生可能・非再生可能エネルギー使用、自動車輸入の影響を分析。結果、非再生可能エネルギーは排出を増加させるが、再生可能エネルギーは減少させることを示し、政策として輸送部門での再生可能エネルギー優先と公共交通インフラ整備を提案する。
English
This study compares the impact of energy use and motor vehicles on CO2 emissions in Pakistan and China using ARDL on 2003-2023 data. It finds that GDP and non-renewable energy increase emissions, while renewable energy reduces them. The results suggest prioritizing renewable energy in vehicle fleets and developing public transport infrastructure.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本に直接関連は薄いが、パキスタン・中国の輸送部門脱炭素化の実証分析を提供。日本のアジア向け環境技術協力やSSBJにおけるScope 3排出の知見として活用可能。特に、非再生可能エネルギーと自動車輸入の相互作用が排出を増加させる点は、日本の自動車輸出戦略にも示唆を与える。
In the global GX context
This comparative study provides empirical evidence on transport decarbonization in developing economies. While not directly tied to TCFD/ISSB, it reinforces the need for renewable energy integration in transport, relevant for global climate policy and transition finance in emerging markets.
👥 読者別の含意
🔬研究者:Provides empirical evidence on transport emissions using ARDL with robustness checks.
🏛政策担当者:Supports policy for renewable energy in transport and public transit improvement.
📄 Abstract（原文）
Environmental degradation primarily driven by CO2 becomes an alarming issue particularly for the economies of developing countries such as Pakistan and China. Although motorized transport and energy are considered an important component of the economy, they also significantly contribute towards CO2 emissions. Therefore, this study investigates the interplay between energy use, motor vehicles and CO2 emissions under the comparative realm of two Asian countries specifically Pakistan and China. The Auto Regressive Distributed Lag (ARDL) Model was used on time series data from 2003-2023 to capture the relationship between GDP, registered vehicles, urbanization, non-renewable energy use, renewable energy use and motor vehicle imports and their combined effect. The robustness of the model is confirmed through Fully Modified Ordinary Least Square, Dynamic Ordinary Least Square and Canonical Cointegrating Regression. The result showed that GDP and non-renewable energy significantly raise CO2 emissions in both countries with a relatively stronger effect in China. In contrast, Renewable energy use potentially reduces emissions highlighting the movement towards SDGs. Notably, the non-renewable energy use interaction with Motor vehicle imports shows significantly positive effect on emissions whereas renewable energy use interaction with motor vehicle imports significantly reduces CO2 emissions for both Pakistan and China. Empirical results guide policymakers to prioritize renewable energy in vehicle fleets for better environmental quality. Moreover, it is also suggested that public transport infrastructure should be developed for lowering fossil fuel consumption in transport sector.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.22541/authorea.15005658/v1first seen 2026-07-10 04:42:26
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