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 21–40 of 50 papers
Luping Yu, Yongshan Zhang, Zihao Wang +2
This paper proposes a Bayesian Deep Reinforcement Learning framework for carbon credit pricing that combines probabilistic modeling, uncertainty propagation, and constraint-based reinforcement learning. Experiments across five datasets show…
Xiaohua Song, Tong Liu, Tianyu Wu +1
This paper develops a two-stage robust optimization method for park-level integrated energy systems with tiered carbon trading and bidirectional demand response. Case studies show 50.40% carbon emission reduction and 150 kW peak-valley diff…
Mengxue Ji, Mingsong Sun, S. Deng
This study examines whether China's carbon emissions trading system (CETS) reduces firms' air pollutant emissions. Using firm-level panel data from 1998-2014 and a staggered difference-in-differences design, the authors find that CETS reduc…
Shuyang Chen
This paper quantifies the health co-benefits of China's Emissions Trading Scheme (ETS) from reduced PM2.5 and O3 pollution using a Computable General Equilibrium model from 2025 to 2060. It finds that both pollutants negatively impact labor…
Süleyman Atılgan, M. Alım, R. Çöteli
This paper analyzes the impact of carbon pricing (carbon tax and emissions trading) on energy costs and security in Türkiye. Using the Levelized Unit Cost of Energy (LCOE) method under different carbon price scenarios, it finds that higher …
Hao Li, Yuxiao Lei, Nuo Li +2
This study uses China's pilot ETS as a quasi-natural experiment. Using panel data of 284 Chinese cities from 2003-2017 and a multi-period DID approach, it finds that the ETS effectively reduces total carbon emissions and carbon intensity th…
Yan Zhang
Using a multi-period DID model on Chinese A-share listed firms (2009-2022), this study finds that participation in China's carbon emissions trading scheme significantly improves firms' ESG performance, partially mediated by digital transfor…
Nergis Feride Kaplan Donmez
This study examines the effects of carbon taxes and emissions trading systems (ETS) on CO2 emissions in OECD countries from 2002 to 2023 using panel data analysis. Both instruments are found effective in reducing emissions in the long run b…
Chien‐Chiang Lee, G. Olasehinde-Williams
This paper examines the impact of the EU Emissions Trading System (ETS) on the carbon content of imported goods embedded in domestic final demand within the Eurozone. It provides evidence on carbon leakage and the effectiveness of emissions…
Xinyang Wei, Liangyu Chen, Yikun Lan +2
This paper analyzes spillover effects of the EU ETS on global equity markets from 2013 to 2021. Using contagion analysis and DCC-GARCH, it finds a positive association between EU carbon allowance prices and stock market performance worldwid…
Chen Lyu, Ke Wang, Bofeng Cai +1
Using a balanced panel of 1,957 thermal power units from 2018 to 2024, this study estimates the causal impacts of compliance pressure under China's national emissions trading scheme (CN ETS) on CO2 emissions. Units with allowance deficits r…
Xiaoqin Lu, Tianfen Yu, Yuanjun Huang +1
This study uses double machine learning to examine the impact of carbon emissions trading schemes (ETS) on corporate debt maturity structure. It finds that ETS may increase firms' reliance on short-term debt, highlighting how climate policy…
Diwei Zheng, Daxin Dong
This study evaluates the impact of China's carbon emissions trading scheme (ETS) on land surface ecological quality (LSEQ) using a difference-in-differences approach on 328 Chinese cities from 2005-2020. The ETS improved LSEQ by 0.0113 on a…
Bingzi Jin, Xiaojie Xu
This study proposes a novel Gaussian process regression (GPR) model optimized via Bayesian framework to forecast carbon prices in China's Emissions Trading Scheme (CHNTS). Using daily settlement data from July 2021 to April 2025, the model …
Yuehan Fang, Yan Li, Lei Chang +2
This study forecasts carbon prices under scenarios of expanding China's ETS to cover steel and electrolytic aluminum sectors using a VMD-SVR model. Results show market expansion causes short-term price increases but reduces volatility, with…
Dr. Deeksha S.
This paper proposes an institutional framework (Farmer-Corporate Carbon Institutional Model, FCCIM) for transforming farmer-managed agroforestry into verified carbon credits, addressing corporate Scope 3 emissions and smallholder income div…
Ranran Zhang
This paper systematically examines methodological challenges in empirically pricing corporate carbon risk under China's dual carbon goals (2030 peak, 2060 neutrality). It identifies three core issues: poor data reliability (e.g., omitted Sc…
Wenqi Chai
This paper empirically examines whether carbon pricing policies cause firm-level capital reallocation, focusing on China's emissions trading system. Using firm-level data, it estimates causal effects and provides evidence on the economic im…
V. D. Smirnov, I. D. Tyukhmeneva
This paper argues that mass demand for green products requires cost parity with conventional alternatives. It proposes using internal carbon pricing (ICP) as a strategic financial planning tool to integrate future environmental risks into p…
Song Chai, Jin Yang, Lin Tang +3
This study examines how China's Renewable Portfolio Standard (RPS) interacts with its Emissions Trading Scheme (ETS). Using provincial panel data from 1995-2021, it finds that higher RPS quotas dilute carbon price signals by compressing the…
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