Xiaoyu Wang

Against the backdrop of the global energy transition and climate governance, engineering construction standards serve as institutional framework for infrastructure development in the oil and gas industry. The extent to which sustainability principles are embedded in these standards bears on the institutional foundations of the industry’s green and low-carbon transition. This study examines 6665 clauses from 33 engineering construction standards in the oil and gas industry. Drawing on sustainability assessment theory, life cycle sustainability assessment, and research on standards governance, we developed a sustainability assessment framework comprising five dimensions and 18 indicators. Based on this framework, we developed a coding protocol and designed zero-shot prompts. DeepSeek and Qwen then independently annotated the full set of clauses. We used a random sample of 469 clauses to construct an expert reference set of independent blind annotations following the same coding protocol. Results demonstrate that model–expert agreement on sustainability relevance (maximum κ= 0.717) approaches the level observed between two human experts (κ= 0.746). Annotation disagreements were systematically concentrated in clauses requiring implicit inference, indicating the need to explicitly represent uncertainty arising from annotation and conceptual boundary ambiguity. The expected composite score of sustainability-related textual embedding across the standard system was 0.414, ranging from 0.354 to 0.485 under alternative classification rules. Structurally, the standards emphasized safety-related provisions, whereas governance provisions were comparatively limited, and low-carbon requirements were largely implicit. Across the engineering life cycle, sustainability textual embedding follows a pattern of “high coverage at both ends and low coverage in the middle,” suggesting that sustainability provisions in construction and acceptance could be further strengthened. This study provides an auditable quantitative framework for assessing sustainability-related textual embedding in engineering construction standards and clause-level evidence for identifying revision priorities.

With the world facing increasingly severe environmental and energy challenges, the role of the construction industry in achieving the dual-carbon goals has become increasingly prominent. However, China’s existing text-based engineering construction standards system is insufficient in effectively supporting the realization of these goals. Therefore, based on the Model-Based Systems Engineering (MBSE) approach and utilizing the Systems Modeling Language (SysML), this paper proposes a new engineering construction standards system tailored to Chinese characteristics, addressing aspects including requirements, behavior, and structure. This system not only supports the construction standard requirements in the energy transition process but also aims to improve energy efficiency, emission reduction, and resource recycling in the building industry from both energy and environmental economics perspectives. The system is validated through carbon dioxide capture standards, and the results demonstrate that the MBSE-based engineering construction standards system holds significant application prospects in promoting energy economic sustainability and environmental protection. It can provide strong support for achieving green and dual-carbon goals.

The power sector accounts for about 41% of China's total carbon emissions from the energy sector, with thermal power being the main source of carbon emissions. The two-carbon target requires energy and power companies to follow a methodical approach to accelerate the diversification of energy supplies and clean, low-carbon, efficient reduction of energy use and electrification. Therefore, it is extremely important to develop a model to monitor and evaluate the carbon reduction process in the power sector. This paper constructs the monitoring index system of carbon emission reduction process in China's power industry from five dimensions: market, technology, social economy, power production and consumption. It then used a fuzzy comprehensive evaluation method to thoroughly assess the overall carbon reduction process across all five systems and the power sector. The results show that the carbon emission reduction process of China's power industry has improved steadily. After 2010, driven by the adjustment of the economic and energy consumption structure and the improvement of energy utilization efficiency, the overall performance of carbon emission reduction in the power industry has gradually improved from a poor level. After 2014, with the establishment of carbon trading market, technological progress and low-carbon transformation of social and economic structure, the process of emission reduction in the power industry has been accelerated, reaching a good level in 2020 and 2021.

The accurate and reasonable prediction of natural gas consumption is significant for the government to formulate energy planning. To this end, we use the multiverse optimizer (MVO) algorithm to optimize the parameters of the Nash nonlinear grey Bernoulli model (NNGBM (1,1)) and propose a hybrid MVO‐NNGBM model to predict the natural gas consumption in 30 regions of China. The results indicate that the prediction precision of the hybrid MVO‐NNGBM model is better than that of other grey‐based models. According to the forecast results, China’s natural gas consumption will grow rapidly over the next five years and reach 354.1 billion cubic meters (bcm) by 2020. Moreover, the spatial distribution of natural gas consumption will shift from being supply oriented towards being demand driven and will be mainly concentrated in coastal and developed provinces.