This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 661–680 of 1041 papers
Natalie Crisci, Md Deluair Hossen, Andrew Muhammad +1
This study conducts a cost-benefit analysis of the EU CBAM specifically for fertilizer trade. It finds that under baseline assumptions the economic cost ($4.04B) exceeds the environmental benefit ($2.58B) annually, but sensitivity analysis …
Dr. Nafees Hashim Rizvi, D. Mehdi
This paper analyzes CBAM's impact on India-EU trade, focusing on iron, steel, and aluminum. Using a gravity model and EU ETS data (2023-2025), it finds that including Scope 2 emissions raises ad valorem equivalent burdens to 15-20% for stee…
Xianrui Mo, Zefang Liao
This study compares carbon surcharges and low-carbon certification as EU/UK border measures for China's seafood exports using a recursive dynamic CGE model over 10 years. It finds that certification, especially when paired with domestic gre…
Zhongrui Wang, Qinghua Wu
This study compares grandfathering and benchmarking carbon quota allocation mechanisms, analyzing competitive and cooperative carbon trading modes in single and dual supply chain models. Findings show benchmarking outperforms in emission re…
You Kong, Ling Xu, Qi Wu +1
This study develops a multi-objective bi-level programming model to analyze the impact of carbon trading mechanisms and electric autonomous container trucks (EACTs) on port collection-distribution networks. Using NSGA-II, the model generate…
S. Biswal, K. Kotecha, Neha Munjal
This paper proposes ADRGPNN-WSO, an integrated framework for carbon price forecasting. It uses FKMV for noise reduction, ADRGPNN for temporal and cross-feature modeling, WSO for optimization, and RB-DCHF for data provenance. Validated on th…
Qinghao Zheng
This study proposes an intelligent computing system for dynamic regulation of carbon emission rights markets using deep reinforcement learning (DRL). It integrates monitoring, prediction, and optimization models, creating a closed-loop 'mon…
Jialan Wang, J. Chavas, Jian Li +1
This paper investigates the evolving price risk in the EU ETS and the effectiveness of carbon futures as hedging instruments. Using a quantile vector autoregression and copula approach, it finds significant tail risk and proposes a novel Mi…
Huixiao Yang, Yifan Yang, Jian Cao +1
This paper analyzes how different emission regulations (carbon cap, carbon tax, cap-and-trade) affect a manufacturer's abatement investment and supply chain coordination. Modeling market frictions like bid-ask spreads and endogenous contrac…
Gaoxiang Lou, Zhangzhen Fang, Linsen Yin +2
This study examines three supply chain collaborative compliance strategies in an integrated carbon market: technology collaborative (TC), certified emission reduction (CER) investment collaborative (IC), and hybrid. Using game theory, the a…
Hai Shen, Jiawei Liu, Siyi Li +1
This paper constructs a decision-making model for dual-channel supply chains under different carbon trading policies, analyzing how carbon quota allocation methods impact profits. It finds manufacturer profit positively correlated with carb…
Xuefeng Ma, S. Fan
This study proposes a cooperative game-based scheduling method for multiple data centers under an electricity-carbon coupling trading framework. It integrates workload migration, energy storage, and carbon allowance trading to minimize cost…
Ram Ranjan
This study develops a blockchain-enabled bioeconomic model integrating forest growth, water services, invasive species dynamics, and fire risk. Token prices adjust to ecological indicators, creating incentives for communities to balance imm…
Zhikai Zhang, Yaojie Zhang, Yudong Wang +1
This paper proposes a time-weighted regularized combination (TWRC) method to forecast carbon price returns under structural breaks and model uncertainty. The TWRC identifies structural changes and mitigates uncertainty among factor-based fo…
Mengjie Zhao, Shijie Duan, Tianshuai Jiang +2
This paper develops a bidding equilibrium model for the joint electricity-carbon market using multi-agent reinforcement learning. It finds that tightening carbon benchmarks by ~14.21% increases thermal power costs by ~13.83%, and doubling r…
Yangjun Zeng, Hua Geng, Yiwei Qiu +14
This paper proposes a hierarchical carbon-driven incentive mechanism (PCIM) linking carbon and ammonia markets to boost renewable power-to-ammonia (ReP2A) competitiveness. Results show a 12.9% emission reduction with only a 1.8% revenue los…
M. Manguera
This paper analyzes the impact of the EU's Carbon Border Adjustment Mechanism (CBAM) on exports from ASEAN-6 countries. Using a gravity model, it finds that cement and iron/steel sectors are most sensitive to tariff adjustments, with the Ph…
Xiangyan Qian, Hongdian Jiang, Yun-Fei Yao +4
This study analyzes four carbon revenue recycling schemes in China's carbon neutrality path using a dynamic CGE model. Lump-sum transfers to households improve welfare and reduce urban-rural income gaps, while indirect tax cuts minimize GDP…
W. Qiu, Hebin Ruan, Xiaoxiao Yu +3
This study proposes a dual-agent deep reinforcement learning framework for low-carbon economic dispatch in wind-integrated microgrids. A PPO agent minimizes operating costs while a SAC agent targets carbon emission reduction, combined via a…
Shuwei An
This study evaluates the cost-effectiveness of China's Grain for Green Program for carbon neutrality. Using satellite data from 2001-2023, it finds forest area increased significantly and carbon sequestration costs averaged ~11 USD/tCO2, be…
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