Studying the correlations of carbonaceous aerosols (element carbon, EC, and organic carbon, OC) from open biomass burning helps to reduce uncertainties in emission inventories and provides necessary constraints for model simulations. In the present study, we measured apparent elemental carbon (ECa) and OC concentrations at the summit of Mount Tai (Mt. Tai) during intensive open crop residue burning (OCRB) episodes using a Sunset OCEC analyzer. In the fine particle mode, OC and ECa showed strong correlations (r>0.9) with carbon monoxide (CO). Footprint analysis using the FLEXPART_WRF model indicated that OCRB in Central East China had a significant influence on ambient carbonaceous aerosol loadings at the summit of Mt. Tai. During campaign, δECa/δCO ratios of OCRB plumes were found to be 14.3±1.0ngm-3ppbv at Mt. Tai. This ratio was twice larger than those for urban pollution in CEC, demonstrating that significant emissions of soot particles emitted from OCRB. δOC/δCO ratio of OCRB plumes was found to be 41.9±2.6ngm-3ppbv averagely. The transport time of smoke particles was estimated using the FLEXPART_WRF tracer model by releasing particles from the ground layer inside geographical regions where large numbers of hotspots were detected by the MODIS sensor. The relationship between transport time and observed δECa/δCO and δOC/δCO ratios was fitted by an e-folding exponential function. Results showed that the loss rate of OC (normalized by CO) with transport was much quicker than that of ECa mass, and the corresponding lifetime of OC mass was estimated to be 28.0-44.2h (1.2-1.8 days), much shorter than that 98.4-136.9h (4.1-5.7 days) of ECa. Lifetime of ECa estimated for the OCRB events in CEC in the study was comparably lower than the values normally calculated by the transport models. Short lifetime of OC highlighted its vulnerability to cloud scavenging in the presence of water-soluble organic species from biomass combustion.
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Atmospheric Science