Identification of weather patterns impacting 24-h average fine particulate matter pollution |
| |
| Authors: | Scott Beaver Ahmet Palazoglu Angadh Singh Su-Tzai Soong Saffet Tanrikulu |
| |
| Affiliation: | 1. University of Chinese Academy of Sciences, Beijing 100049, China;2. Huairou Eco-Environmental Observatory, Chinese Academy of Sciences, Beijing 101408, China;3. Beijing Institute of Aerospace Testing Technology, Beijing 100074, China;4. Peking University, College Environmental Science & Engineering, Beijing 100871, China;5. State Key Joint Lab Environmental Simulation & Pollution Control, Beijing 100871, China;1. Atmospheric, Oceanic and Planetary Physics, University of Oxford, United Kingdom;2. School of Earth and Environment, University of Leeds, United Kingdom |
| |
| Abstract: | Methods are presented to extract intra-seasonal meteorological patterns at three scales to explain 24-h fine particulate matter (PM2.5) pollution events: evolving large-scale meteorological scenarios, synoptic regimes driving diurnal variability near the surface, and localized meteorological triggers. The methods were applied to understand how winter weather conditions impacted PM2.5 around the San Francisco Bay Area (SFBA). Analyzing data across 12 winters (November–March) ensured robust characterization of the SFBA conditions. SFBA 24-h PM2.5 exceedances (35 μg m?3) required several simultaneous characteristics: a ridge of aloft high pressure moving over SFBA, providing weak surface pressure gradients over Central California; persistent easterly flows through SFBA extending vertically to around the 925-hPa pressure level; orographically channeled winds resulting from stability; enhanced nocturnal cooling under clear-sky conditions providing for enhanced drainage flows off the Central California slopes; and at least two consecutive days of these conditions. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
