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Sensitivity of source apportionment results to mobile source profiles
Tianqi Cai1, James J Schauer2, Wei Huang3
1College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish Center for Education and Research, Beijing 100080, China.
Environmental Pollution (Barking, Essex : 1987)
|August 28, 2016
Summary
Using non-local mobile source profiles in chemical mass balance (CMB) models can impact source apportionment results, particularly for primary sources. However, secondary organic carbon (SOC) estimates remain consistent, suggesting feasibility of using US profiles in China.
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Air Quality Modeling
Background:
- Source apportionment models are crucial for identifying air pollution origins.
- Mobile source profiles are key inputs for these models, but their geographic relevance can be uncertain.
- Chemical mass balance (CMB) models are widely used for source apportionment.
Purpose of the Study:
- To investigate the sensitivity of CMB models to the use of non-local mobile source profiles.
- To assess the impact of using US and Chinese mobile source profiles in different geographic locations (St. Louis, USA, and Beijing, China).
- To compare secondary organic carbon (SOC) estimates derived from CMB models with different profiles against the EC tracer method.
Main Methods:
- Comparison of source apportionment results from CMB models using local versus non-local mobile source profiles.
- Application of US and Chinese mobile source profiles in St. Louis and Beijing, respectively.
- Validation of SOC estimates against the EC tracer method.
Main Results:
- Non-local mobile source profiles did not significantly affect apportionment of vegetative detritus and biomass burning.
- Primary source contributions were influenced by the use of non-local profiles.
- SOC estimates from CMB models were consistent with the EC tracer method, showing little bias.
- US mobile profiles were feasible for use in China, but Chinese profiles introduced bias in the US.
Conclusions:
- The choice of mobile source profiles can influence CMB model outcomes for specific primary sources.
- SOC estimation appears robust to the use of non-local mobile source profiles.
- Geographic transferability of mobile source profiles requires careful consideration, with US profiles showing more promise for use in China than vice-versa.
- Source apportionment studies should consider the temporal resolution of measurements, as monthly/annual averages show less sensitivity to profile choices than daily data.
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