Related Experiment Video
Updated: Dec 14, 2025

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Source apportionment of black carbon and the feedback effect on the meteorological factors in Beijing, China
Wei Wen1,2, Xin Ma3, Chunwei Guo2
1School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China.
Abstract:
Black carbon (BC) is a major light-absorbing component in the atmosphere and plays an important role in aerosol radiative forcing. In this study, the combination of monitoring data and the WRF-Chem model was used to study the source apportionment of BC in China during January 2017. Meanwhile, the aerosol-radiation interaction (ARI) effect of BC was also simulated. We found that the average BC/PM2.5 ratios were 4.8%, 4.2%, and 3.8% in Shijiazhuang, Tangshan, and Beijing, respectively. The source apportionment suggested that traffic emissions played a dominant role in the BC concentration over Beijing. The traffic, residential, industrial, and power contributions accounted for 41%, 32%, 25%, and 2% of total concentration, respectively. The BC concentration in Beijing was also affected by regional transport. During January, the contributions of monthly regional transport to BC and PM2.5 concentrations in Beijing were 41% and 49%, respectively. BC emissions decreased downward shortwave radiation (SWDOWN) at the surface, leading to a decrease in temperature. As a result, the planetary boundary layer height (PBLH) development was suppressed and the relative humidity increased. The stable meteorological conditions suppressed the dispersion of air pollutants and increased BC concentrations. Traffic emissions decreased the monthly SWDOWN by approximately 2.2 W/m2, decreased 2 m temperature (T2) by approximately 0.1 °C, increased 2 m relative humidity (RH2) by approximately 0.5%, and decreased PBLH by approximately 4.4 m.
Related Concept Videos
Global Climate Change
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...

