Connected Waters: How Digital Infrastructure Could Reshap Carbon Future of China’s Fisheries

China's growing network of 5G connections, smart sensors, cloud platforms and artificial intelligence tools may help its enormous fisheries sector lower carbon emissions without sacrificing aquatic food production. The study, titled 'Does New Digital Infrastructure Promote the Low-Carbon Transformation of Fisheries: Evidence from Carbon Emissions Across Chinese Provinces,' was published in the journal Frontiers in Marine Science by researchers Han Zeng and Xiaoyu Chen.

China produced 73.66 million tonnes of aquatic products in 2024, including 60.62 million tonnes from aquaculture and 13.05 million tonnes from capture fisheries, accounting for roughly 31% of global fisheries and aquaculture production. This scale makes the country's low-carbon transition important far beyond its own borders, since fishing vessels consume diesel, aquaculture farms need electricity for aeration and pumping, and processing plants depend on fuel, power and steam.

Two Decades of Provincial Data Reveal a Clear Carbon-Reduction Link

The researchers examined data from 30 provincial-level regions in mainland China between 2004 and 2024, excluding Tibet because information was unavailable for some years. Their dataset contained 630 province-year observations drawn from government work reports, national statistical publications, fishery yearbooks, marine and energy records, and official databases.

New digital infrastructure was measured through textual analysis of provincial government work reports. The researchers collected these documents through web crawling and manual searches, identified infrastructure-related keywords, calculated how frequently they appeared and standardized the results to account for differences in report length.

Fishery carbon emissions were calculated from operational energy use in capture fisheries, aquaculture and aquatic-product processing. The accounting included diesel consumed by fishing vessels and processors, electricity used for aquaculture equipment and processing, and steam required for products such as frozen seafood, surimi, dried aquatic foods and fishmeal.

A double machine learning model was used to handle the many economic, environmental and production factors that could influence emissions, including fishery development, aquaculture area, capital-to-labour ratios, worker productivity, feed production and environmental regulation. The main estimate showed a statistically significant negative relationship between digital infrastructure and fishery carbon emissions, with the fully controlled model producing a coefficient of -0.187.

The result remained stable when the researchers changed machine-learning algorithms, altered sample-splitting methods, used ordinary least squares, replaced the emissions measure with carbon-efficiency scores and created an alternative digital-infrastructure indicator based on artificial intelligence enterprises and patents.

Smart Tools Can Reduce Waste Across the Fishery Supply Chain

Digital infrastructure can make everyday fishery operations more precise. Sensors and connected equipment allow aquaculture farms to monitor water quality, animal growth and machinery in real time, helping operators adjust feeding, aeration and water exchange according to actual conditions instead of relying on fixed schedules that may waste feed and electricity.

Satellite positioning, vessel-monitoring systems and big-data analysis can help fishing crews choose productive fishing grounds, plan shorter routes and avoid repeated or unproductive voyages. Digital platforms can connect farms, fishing operations, processors, cold-storage facilities, transport providers and markets, reducing excess inventory, product losses and poorly coordinated shipments.

The pathway analysis found that stronger digital infrastructure was positively associated with three changes that can support lower emissions: technological progress, upgrading of the fishery industry and a cleaner energy structure.

Technological progress produced a strong positive coefficient of 0.818, reflecting the role of digital networks in spreading precision feeding, water monitoring and intelligent equipment. The energy-structure coefficient reached 0.867, suggesting that digital monitoring and scheduling can make renewable energy easier to match with the needs of vessels, farms and processing facilities. Industrial upgrading also showed a positive relationship, though its estimated effect was small, indicating that movement toward smart aquaculture, ecological fisheries, recreational activities and high-value services may take longer to unfold.

These pathway results identify strong associations rather than proving formal mediation, a distinction the researchers acknowledge in interpreting how the carbon-reduction effect may occur.

Benefits Extend Beyond the Provinces Building the Infrastructure

Fishery emissions were concentrated along China's eastern coast, the middle and lower reaches of the Yangtze River and southern China, where large fishing, aquaculture and processing industries consume substantial amounts of fuel and electricity. Northwestern provinces maintained lower emissions because limited water resources and smaller fisheries restricted production.

Digital infrastructure followed its own geographical pattern: Beijing, Shanghai, Tianjin, Guangdong, Jiangsu and Zhejiang held an early advantage because they had stronger economies, communication networks, investment and technical expertise. Development accelerated after 2015, spreading into Hubei, Hunan, Henan, Anhui, Sichuan, Chongqing, Yunnan and Guizhou, though a clear digital divide remained.

The estimated carbon effect was negative in both coastal and non-coastal regions: Statistical significance appeared only in the coastal sample, yet the coefficients were almost identical at -0.259 and -0.258. It means the evidence did not establish a meaningful difference between the two groups. Results from 2004–2014 and 2015–2024 were also similar in size, giving no firm proof that the effect strengthened after 2015.

Spatial modelling revealed that the benefits were not confined to the province installing the infrastructure. Local emission-reduction effects ranged from -0.370 to -0.456, while effects on geographically close or economically connected provinces ranged from -0.799 to -1.439. The larger indirect effects suggest that knowledge sharing, technology diffusion, workforce movement, industrial cooperation and shared digital platforms can spread low-carbon practices across regional boundaries.

Smarter Investment Must Be Paired With Better Carbon Accounting

The researchers recommend giving fishing ports, aquaculture waters, fishing villages and seafood-processing clusters priority in future digital-infrastructure plans. Regions with mature networks can focus on system coordination and practical applications, while less-connected areas need reliable access, data-collection systems and affordable intelligent equipment.

Greater cooperation among research institutions, technology companies and fishery operators could expand water-quality monitoring, disease detection, precision feeding, vessel scheduling, remote equipment control and clean-energy adoption. Shared regional platforms could provide production monitoring, environmental warnings and emissions information across coastal economic belts, river basins and major fishery-producing areas.

The study's carbon estimate does not represent the full footprint of aquatic food production. It excludes emissions from feed manufacturing, material inputs, equipment production, packaging, cold-chain transport, retail, consumption and waste treatment. Uniform conversion factors may also miss differences in local energy systems, machinery efficiency and production technologies.

Future studies using detailed activity records and life-cycle emission factors would provide a fuller picture. A well-planned digital infrastructure can become more than a tool for faster communication, offering fisheries a route toward smarter production, cleaner energy use and coordinated carbon reduction across entire regions.