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 461–480 of 1614 papers
Thais M. Rosan, Laura B. Vedovato, Viola Heinrich +4
Using remote sensing, this study analyzes aboveground carbon accumulation in regenerating Brazilian Atlantic Forests. Forest connectivity increases carbon accumulation rates by 43–69%, with highly connected landscapes accumulating over thre…
Jidan Zhi, Daqian Shi, Xiaozhen Ouyang
This paper examines how the geographical distance between firms and Environmental Protection Bureaus (EPBs) affects corporate carbon emissions using 455,063 Chinese industrial firm-year observations (1999-2013). Greater distance is associat…
Pedro Palma, Nikos Manias, Akis Apostoliotis +7
This report assesses the potential of building renovation and renewable energy integration for decarbonisation and energy poverty reduction in private multifamily buildings across three European pilot cities. Using DREEM simulations, it fin…
Kingsley Imandojemu, Aliyu Akorede Rufai, Felix Orole +1
This study examines the impact of entrepreneurship on the energy trilemma (energy security, equity, and environmental sustainability) using panel data from 64 countries (2011-2022). Results show entrepreneurship improves energy security and…
Jiaming Ke, Mohammad Subhan, Aamir Ahmad Teeli +1
This study empirically analyzes the impact of energy efficiency, production-based CO2 productivity, environment-related technologies, and institutional quality on sustainable development (SD) performance in EAGLE economies. Using MMQR and o…
Xinyue Liu, Shiguo Deng
This study integrates a coupling coordination model, Tapio decoupling model, and Generalized Divisia Index Method to analyze the dynamic interactions among urban transport, economic growth, and carbon emissions in Shanghai from 2000 to 2023…
Olga Tsapko-Piddubna
This paper analyzes 82 listed firms across five Nordic countries (2021-2024) to examine the relationship between ESG scores, carbon efficiency, and financial performance. Results show no meaningful association between conventional ESG score…
Xin Wang, Mengyu Wang, Jiahan Hu +2
This study evaluates the impact of China's Climate Adaptive Pilot Cities (CAPC) policy on urban pollution and carbon reduction using a staggered difference-in-differences approach on a panel of 273 Chinese cities from 2011 to 2023. The poli…
Lihong Zhao, Guochun Huang, Jiaying Cong +2
This study quantifies life-cycle stocks, flows, and GHG emissions of seven bulk materials across nine cities in the urban agglomeration on the west side of Taiwan straits using the IMAGINE materials model. Material demand peaks in 2036, and…
Ying Liu, C. H. FENG
Using cross-country panel data from 2000 to 2021, this study empirically examines the positive impact of climate legislation on green development. It finds that international environmental engagement and government readiness positively mode…
Joseph Sánchez-Balseca, Monserrat Ramírez-Melgarejo, Agustí Pérez Foguet
This paper proposes a machine learning approach for carbon accounting in wastewater systems, addressing missing data and improving emission estimates. Using real-world data, it demonstrates that ML models can enhance accuracy and support cl…
O. Drebot, Mykola Boiko, Ніна Петруха +2
This study proposes a Climate Risk Intelligence (CRI) framework linking competitive intelligence theory with climate governance and rural development. Focusing on Ukrainian rural territories, it reveals a 25-37% decline in agricultural prod…
O. Lopushanskyi
This review analyzes modern strategies for decarbonizing gas emissions in industry and energy, comparing CCS, electrification, hydrogen, and biogas. It evaluates economic feasibility and barriers, concluding that a combined approach is most…
Rebecca von Hellfeld, Jon Reid, Arkan Eddine-Lomas +6
This study demonstrates that life-cycle GHG emissions from onshore wind turbines in Great Britain are highly sensitive to wind speed, initial soil organic carbon, and grid decarbonisation. Using a novel spatial model (WindFor), it shows tha…
Xiaolong Xu, Suyun Yu, Hongmei Lu +4
This study conducts a life cycle carbon emission analysis of a nearly zero-energy office building in Shenyang, China, using LCA and carbon emission factor method. The average annual emission intensity is 56.36 kgCO2e/(m2·a), with the operat…
Zonglin Li, Xuanhao Hu, Tianhui Fang
This study evaluates the causal impact of EU climate mitigation policies on total-factor energy efficiency (TFEE) using synthetic control method. Results show significant TFEE improvement in the EU after 2004 compared to a synthetic counter…
Sinéad M. Crotty, Peter W. Reiners, Leah K. Clayton +5
This paper focuses on non-energy Biomass Carbon Removal and Storage (BiCRS) pathways, presenting a framework to assess the durability of solid and liquid carbon products stored in terrestrial environments. It organizes carbon products along…
Basri Rahman, Mozibur Rahman, R Rohit
This study examines the impact of renewable energy adoption on climate change mitigation and sustainable development in Bangladesh, analyzing the roles of energy security risk, private sector development, environmental policy stringency, ec…
Priscila de Morais Lima, Ida Sylwan, Oksana Valetska +1
Responding to the EU Farm-to-Fork strategy and HELCOM Baltic Sea nutrient recycling strategy, the CiNURGi project evaluated 11 bio-based fertilizer (BBF) value chains. A streamlined assessment method based on the Single Operation Unit Proce…
Abdelrahman Mohamed Mohamed Saeed, Muhammad Ali
This study develops a Compound Vulnerability Score for six low- and middle-income countries by fusing socio-economic indicators with climate risk data (2000–2024). Using unsupervised learning, graph neural networks, and reinforcement learni…
Browse by Topic