中文Dr. Lu Dawei and his research partners made new progress in the source tracing application of isotopic big data related to particulate matter (PM). The related research findings, titled “Blockchain-based isotopic big data-driven tracing of global PM sources and interventions”, have been published in Nature Communications (DOI: 10.1038/s41467-025-59220-4).
PM pollution is a major environmental issue affecting global public health. Identifying PM emissions and evaluating the effectiveness of intervention measures are key to achieving high-level air quality protection. However, due to the non-linear relationships among “intervention → source → PM,” relying solely on PM concentrations and their chemical components to determine sources and assess intervention outcomes poses significant challenges. Hence, Lu et al.established the blockchain-based isotopic database dedicated to global atmospheric studies, enabling both retrospective evaluations and forward-looking projections. This curated dataset comprises 18,760 isotopic signatures of PM and its emissions, derived from 1,890 pollution episodes across 66 countries, offering an unprecedented opportunity to examine long-term trends and rates of change. Analysis of the data reveals that various types of PM originate from distinct sources, which evolve dynamically over time—often out of sync with related intervention measures. The study also quantitatively assesses the outcomes of control strategies aimed at coal combustion and industrial discharges, particularly for PM species containing carbon, nitrogen, and sulfur. Looking ahead, projections suggest that PM concentrations could decline under current climate action pathways. However, achieving the WHO-recommended level of 5 µg/m3 remains unlikely without further measures targeting natural sources such as biomass burning. These findings underscore the importance of leveraging isotopic big data to inform the design of next-generation pollution mitigation strategies.
This research was jointly conducted by the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, in collaboration with Shandong University, Yunnan University, the Max Planck Institute for Chemistry, Nanjing University, Purdue University, Qingdao University, and Jianghan University. The first author of this paper is Yuming Huang, a PhD student (Class of 2021) at the Sino-Danish College, University of Chinese Academy of Sciences. The corresponding authors are Dr. Dawei Lu from the Research Center for Eco-Environmental Sciences, CAS, Dr. Zheng Zong from Shandong University, and Dr. Jingwei Zhang from Yunnan University.
This work was supported by grants from the National Natural Science Foundation of China, the National Key R&D Program, and related programs of the Chinese Academy of Sciences.
→ Link to the paper: https://www.nature.com/articles/s41467-025-59220-4
