Modeling the Long-Range Transport of Particulate Matters for January in East Asia using NAQPMS and CMAQ

Autor: Shigekazu Yamamoto, Zifa Wang, Zhe Wang, Itsushi Uno, Kei Tamura, Kazuo Osada, Syuichi Itahashi, Xiaole Pan, Tomoaki Nishizawa
Rok vydání: 2017
Předmět:
Zdroj: Aerosol and Air Quality Research. 17:3065-3078
ISSN: 2071-1409
1680-8584
DOI: 10.4209/aaqr.2016.12.0534
Popis: Two regional chemical transport models were applied to simulate high concentrations of particulate matters (PM) observed in East Asia in January 2015; the first model is the Nested Air Quality Prediction Modeling System (NAQPMS) and the second is the Community Multi-scale Air Quality Model (CMAQ). The variation of PM2.5 in both models showed well agreement with measurements over both eastern China and western Japan. Based on the model results and the aerosol compositions observed in Fukuoka in western Japan, three types of PM long-range transport (LRT) were identified: N-, S-, and D-type. The N episode showed higher fine-mode nitrate (fNO3–) concentrations than fine-mode sulfate (fSO42–), indicating the importance of NO3– LRT. The S episode showed the highest fSO42– concentrations (28.9 µg m–3), which were 3.4-fold higher than fNO3–, due to high relative humidity. During the D episode, dust stagnated in Fukuoka for three days, due to the influence of low- and high-pressure systems; thus, dust LRT is also important in winter besides spring. Both models reasonable explained variations in aerosol components during both N and S episodes; however, both underestimated fSO42– especially during D episode, suggesting that they may miss certain emissions or chemical mechanisms. High coarse-mode NO3– (cNO3–) concentrations (maximum: 6.3 µg m–3), and high cNO3–/fNO3– ratios (maximum: 1.2) were observed during D episode. NAQPMS successfully captured this cNO3– peak after including heterogeneous reactions on dust. Our results emphasize the importance of such heterogeneous processes for understanding the LRT of dust and anthropogenic pollutants over East Asia.
Databáze: OpenAIRE