High-time-resolution source apportionment of PM 2.5 in Beijing with multiple models

Research output: Contribution to journalArticlepeer-review


  • Yue Liu
  • Mei Zheng
  • Mingyuan Yu
  • Xuhui Cai
  • Huiyun Du
  • Jie Li
  • Tian Zhou
  • Caiqing Yan
  • Xuesong Wang
  • Qiang Zhang
  • Kebin He

Colleges, School and Institutes

External organisations

  • Peking University
  • Chinese Academy of Sciences
  • Institute of Surface Earth System Science
  • Tianjin University
  • Division of Environmental Health and Risk Management
  • King Abdulaziz University
  • King Abdulaziz University
  • Tsinghua University


Beijing has suffered from heavy local emissions as well as regional transport of air pollutants, resulting in severe atmospheric fine-particle (PM 2.5 ) pollution. This study developed a combined method to investigate source types of PM 2.5 and its source regions during winter 2016 in Beijing, which include the receptor model (positive matrix factorization, PMF), footprint and an air quality model. The PMF model was performed with high-time-resolution measurements of trace elements, water soluble ions, organic carbon and elemental carbon using online instruments during the wintertime campaign of the Air Pollution and Human Health in a Chinese Megacity-Beijing (APHH-Beijing) program in 2016. Source types and their contributions estimated by PMF model using online measurements were linked with source regions identified by the footprint model, and the regional transport contribution was estimated by an air quality model (the Nested Air Quality Prediction Model System, NAQPMS) to analyze the specific sources and source regions during haze episodes. Our results show that secondary and biomass-burning sources were dominated by regional transport, while the coal combustion source increased with local contribution, suggesting that strict control strategies for local coal combustion in Beijing and a reduction of biomass-burning and gaseous precursor emissions in surrounding areas were essential to improve air quality in Beijing. The combination of PMF with footprint results revealed that secondary sources were mainly associated with southern footprints (53 %). The northern footprint was characterized by a high dust source contribution (11 %), while industrial sources increased with the eastern footprint (10 %). The results demonstrated the power of combining receptor model-based source apportionment with other models in understanding the formation of haze episodes and identifying specific sources from different source regions affecting air quality in Beijing.


Original languageEnglish
Pages (from-to)6595-6609
Number of pages15
JournalAtmospheric Chemistry and Physics
Issue number9
Publication statusPublished - 17 May 2019

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