A method and system for co-warning of carbon emissions and atmospheric pollutants in the petrochemical industry
By constructing a three-dimensional dynamic benchmark model and adaptive weight calculation, the problem of multi-source data fusion for coordinated early warning of carbon emissions and air pollutants in the petrochemical industry was solved, achieving accurate coordinated early warning of pollution reduction and carbon reduction, and improving the accuracy and practicality of supervision.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TIANJIN UNIVERSITY OF FINANCE AND ECONOMICS
- Filing Date
- 2026-05-12
- Publication Date
- 2026-07-17
AI Technical Summary
The petrochemical industry suffers from several shortcomings in its early warning systems for carbon emissions and air pollutants. These include an imperfect multi-source data fusion mechanism, insufficient data consistency verification capabilities, and a lack of adaptive early warning capabilities for operating conditions. Consequently, existing systems are unable to achieve accurate and coordinated early warning for pollution reduction and carbon reduction, making it difficult to meet the technical requirements for high-quality supervision and in-depth governance.
A three-dimensional dynamic benchmark model of 'energy consumption-carbon emissions-pollutants' is constructed. An adaptive weight calculation and a four-level progressive judgment mechanism are adopted. Real-time operation data is obtained, cleaned and smoothed, a benchmark model is constructed, and a collaborative deviation index is calculated to achieve multi-dimensional collaborative early warning and false compliance identification.
It enables real-time and precise coordinated early warning of carbon emissions and air pollutant emissions, enhances the authority and penetration of environmental supervision, effectively identifies false compliance, and supports the refined management of petrochemical enterprises and the synergistic effect of pollution reduction and carbon reduction.
Smart Images
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