| 英文摘要 |
The objectives and task of this project are: (1) to execute the operation and maintenance of the Micro-pulse lidar systems；(2) to build the lidar observation database；(3) to accomplish the operations of data QA/QC；(4) to integrate the observational data based on EPA MPL systems and air quality monitoring station, and further analyze the possible causes of high pollution events；(5) to establish the experience with lidar data and export its potential on air quality forecast；(6) to intensify the international collaborations cooperation with NASA MPLNET and implement MPL technology for air quality monitoring.
The important achievements from this project are listed as follows:
• We had established and execute standard maintenance procedures. We recorded the details of instrument maintenance status and scheduling. The issue of two new enclosures due to their bad temperature control has been discussed and improved significantly.
• We had executed the After Pulse and Dark Counts calibration and data QA/QC procedure on schedule to ensure the availability and stability of MPL data. The MPL data has been posted to webpages and database real time and completely.
• We spent lots of efforts to strengthen international collaboration with NASA MPLNET. MPLNET sent their A chief technical engineer from NASA MPLNET visited Taiwan in October. He guided us many MPL technology and knowledge. During his visit, our MPL systems have been upgrades with the capability of polarization and lower overlap (from 2 km down to 200 m) through installing the Wild-Field-Receiver (WFR). By doing that, our MPL systems should have higher accuracy and data reliability for near surface observation.
• We applied a statistical method to define the high pollution events in this year and set up a database for case studies. We systematically analyze those pollution events with observational data obtained from EPA MPL system and air quality monitoring stations in Taiwan. We explained the causes of high pollution events based on multiscale analysis including vertical and horizontal distribution of particulate matters and meteorological conditions. The results from those case studies significant improve our understanding on the air quality deterioration.
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