The work projects of this plan included maintaining and operating the EPA (Environmental Protection Administration) visibility monitoring network (VMN) in Banqiao, Xitun, and Xiaogang stations, implementing the data quality assurance and quality control, investigating the measured information between EPA air quality monitoring stations and VMN, and providing the analysis and application of the VMN optical monitoring data.
After the analysis of the data provided from this project, several results were investigated. First, the method to evaluate the visibility from the concentration of PM2.5 (Particulate Matter < 2.5 μm in diameter) and the RH (Relative Humidity) was established in this project. The evaluated visibility by this method could offer an easy and direct reference in order to determine the decreasing of the visibility for people. Second, in the application of the absorbance coefficient, the three-dimensional indicators of CO/NOx (Carbon monoxide / Nitrogen Oxides), AAE (Absorption Ångström Exponent) and BC/PM2.5 (Black Carbon / PM2.5) are verified by the pollutant events of EPA announcements to identify the characteristics of long-range transport pollutants, local pollutants, and traffic emissions. Third, the aerosol liquid water content (ALWC) simulated by the ISORROPIA model in the low humidity and PM2.5 environment correlated better with the nitrate than with the sulfate at Xiaogang station. The possible reason could be that the deliquescence relative humidity of nitrate was lower than sulfate. The great amount of ALWC after deliquescence caused the visibility degradation even at RH < 65%. The concentrations of nitrate were usually higher at Xiaogang station than other stations, which raised more attention on visibility degradation. Therefore, the concentration of nitrate was suggested to be concerned in pollution control policies in order to improve the visibility. Forth, in order to investigate the vertical variations of visibility, two optical paths of LPV-4 at low and high altitude, and LiDAR (Light Detection and Ranging) instrument were set up to measure in Taichung basin. Under the proper atmospheric conditions, the observations of LPV-4 transmissometers and the LiDAR instrument corresponded to each other. The fluctuations of atmospheric boundary layers would cause discrepancies between the human eye observations and the instrument measurements, which could be illustrate by the three-dimensional monitoring of the scanning LiDAR instrument and photos at low and high altitude. Fifth, the positive matrix factorization (PMF) was used at three stations for source apportionment of pollution. The results highlight the importance of nitrate pollution source control in improving visibility policies.
To sum up, the visibility could be roughly evaluated from the PM2.5 and the RH through the method established in this project. The LiDAR instrument could offer a better result for the three-dimensional atmosphere monitoring which is able to explain how the fluctuations of atmospheric boundary layers effect the visibility monitoring, and it is correlated to the result observed from the LPV-4 under proper conditions. According to results derived from the ISORROPIA model and the PMF method, the reducing of nitrate pollutant source is recognized as an important factor to improve the visibility.
