Jinyang Zhao

As global carbon emission regulations tighten and carbon border adjustment mechanisms (CBAM) take effect, the petroleum industry faces increasing pressure to reduce product carbon footprints (PCFs) and to develop more sustainable products. Traditionally, PCF reduction has relied on decreasing overall carbon intensity through the adoption of low-carbon technologies and the implementation of carbon capture and storage (CCS) systems—strategies that often require substantial capital investment. However, for blended products such as gasoline, additional PCF reductions can be achieved by optimizing the selection and allocation of blending components, providing more cost-effective mitigation opportunities. In practice, product blending and operations optimizing of petroleum companies rely on systems like PIMS (Process industry modeling system) and RPMS (Refinery and petrochemical modeling system). However, these systems suffer from two critical limitations: they lack the capability to systematically trace the PCF throughout the entire production process, and they fail to incorporate PCF optimization into operational decision-making. To address these challenges, this study proposes an integrated model framework that couples Life Cycle Assessment (LCA) with production planning optimization, building on advanced recursive algorithms and dual-linear programming solving technique, the framework establishes a systematic method for PCF calculation under different carbon footprint allocation principles. By treating PCF as a transferable physical attribute within the production process, the framework enables cradle-to-gate tracking of PCF from intermediate to final products, while facilitating optimization to minimize the PCF of targeted output. The proposed model framework is validated through a case study involving a refinery with an annual capacity of 10 million tons, located on the east coast of China. Results indicate that among all refinery outputs, polypropylene (PP) exhibits the highest PCF, followed by gasoline, whereas aviation kerosene shows the lowest PCF. Through optimizing blending strategies—specifically, increasing the proportion of low-PCF components such as light naphtha and raffinate, while reducing the proportion of high-PCF components including etherified gasoline, alkylate, and methyl tert-butyl ether (MTBE)—the PCF of gasoline products can be reduced by 27.2%, corresponding to a decrease of 0.23 tCO₂ per tons of product. This study demonstrates that targeted production planning offers an effective means to reduce the PCF of specific refinery products without significant cost escalation. Nonetheless, achieving broader, PCFs decreasing will continue to require complementary investments in advanced low-carbon technologies.