This research analyzed the weather information (temperature, wind velocity, visibility, and total cloudiness) from the Taipei and the Kaohsiung Weather Station of Central Weather Bureau, and air pollution from the Air Quality Monitoring Station of Environmental Protection Administration, Executive Yuan ( Shihlin, Shihlin, Jhongshan, Wanhua, Guting, Songshan¡A), Nanzih, Zuoying, Cianjin, and Siaogan ) to evaluate the feasibility of using visibility as the ambient air quality index by statistical analysis¡C In regard to the visibility in Taipei metropolis, the visibility between 1983~1992 showed a steady status between 5~11 kilometers. The visibility after 1993 has increased gradually between 6~16 kilometers, which indicated that the visual air quality has been improved year by year in Taipei metropolis. In regard to the visibility in Kaohsiung metropolis, the index has a trend of decreasing year by year from 10~24 kilometers to 2~12 kilometers, and the decrease was particularly obvious after 1993. Analyzing the air quality index greater than 100 in the metropolis, the visibility is categorized as the level of "poor", which means that the visibility is within 3 kilometers. When the air quality index ranges between 76~100, the visibility is categorized as the level of median, which means the visibility is within 4 kilometers. When the air quality index ranges between 50~75, the visibility is categorized as the level of "good", which means the visibility is within 7 kilometers. When the air quality index ranges between 20~49, the visibility is categorized as the level of "excellent", which means the visibility is beyond 7 kilometers.

This study aims to investigate the influence of air pollutant concentration and meteorological factors on the atmospheric visibility in Taipei basin. First of all, we collected air quality data measured by ambient air quality monitoring stations of EPA (Environmental Protection Administration) and the meteorological factors monitored by Tamsui and Taipei meteorological stations separately, based on the range of three observation directions. We then analyzed the data by PCA (principal component analysis) to determine the main effective factors on atmospheric visibility under low visibility condition. In order to comprehend the spatial and temporal distribution of atmospheric visibility, we collected the atmospheric visibility data from Taipei meteorological observation stations for the past twenty-two years (1984~2005), it showed that the atmospheric visibility increased gradually. The seasonal variation of visibility was also observed, the best season was autumn (10.7 km) and the worst season was spring (7.5 km). Furthermore, according to the monthly statistical results, the visibility trends in the Taipei Basin can be separated into three typical periods: low visibility period (January to May), transitional period (June to September), high visibility period (October to December). The average atmospheric visibilities observed at the Tamsui, Songshan, and Sindian directions were 10.66 km , 9.54 km and 8.44 km, respectively. In general, the visibility at the Tamsui direction was slightly higher than those from other two directions. The results showed that atmospheric visibility was influenced not only by air pollutant levels and meteorological factors, but also affected by local topography of Taipei Basin. This study revealed that the atmospheric visibility data led on the Tamsui, Songshan observation directions is better. Four intensive observations of atmospheric visibility were conducted during March 28~April 1, July 4~8, September 19~23, and November 14~18 in the year of 2006, respectively. The results showed that the atmospheric visibilities at Tamsui direction were generally higher than other two directions. The visibilities observed in the afternoon were generally higher than those in the morning. Results obtained from the principle component analysis showed that the atmospheric visibility in the Taipei Basin were mainly influenced by PM10, NOx and CO, that mobile sources was the main cause of low visibility in the Taipei Basin. In addition, Tamsui region were affected by PM10 and SO2 more than Songshan and Sindian regions, which was influenced by neighboring industrial and the power plants. In the meteorological factors, wind speed and temperature have more influence on atmospheric visibility, however, the relationship between atmospheric visibility and relative humidity was somehow irregular. The analysis of the spatial distribution of air pollutants showed that low visibilities can not be caused only by high air pollutant concentration within the region, it may caused by the rise of air pollutant concentration in the transition region.

In addition to air pollutants index (i.e. PSI), ambient air quality can be described by atmospheric visibility since it can be observed directly by general publics. In this study, atmospheric visibility observation, meteorological parameter monitoring, and aerosol particle sampling were conducted to investigate the influences of physicochemical properties of suspended particles and meteorological parameters on atmospheric visibility. This study further applied receptor model and multiple regression linear analysis to forecast atmospheric visibility and develop strategies for improving urban visual air quality at Taipei region. Results from regular visibility observation indicated that the average visibilities were 10.30, 8.05 and 6.00 km in the directions of Tamsui, Sonshan, and Shindian, respectively. Similar trend of visibility variation was also observed for intensive observation. Further analysis of synoptic chart and regular observation data during the period of January 2007¡VMarch 2008 showed that the lowest atmospheric visibility commonly occurred whenas the weather patterns were in sequence of eastward movement of rainy areas in southern China, southerly airstream, strong northeast monsoon, circus-sluice of high pressure outflow, and weak northeast monsoon. Results from chemical analysis of suspended particles at Taipei region indicated that major water-soluble ionic species were SO42-, NO3-, and NH4+ and followed by Cl-, while major metallic content were Ca and K. Carbonaceous analysis showed that the mass ratio of OC/EC ranged from 1.65 to 1.91 for PM2.5 and from 1.37 to 1.88 for PM2.5-10. Ammonium nitrate, organic carbon, and ammonium sulfate were the major chemical species that influenced atmospheric visibility at Taipei region. In this study, we choose the averaged atmospheric visibility in Sonshan as a dependent variable and PM10, NO2, SO2, O3, relative humidity (RH), wind direction (WD), and wind speed (WS) as independent variables to establish multiple linear regression models for forecasting the atmospheric visibility. Results of statistical analysis indicated that high correlation between forecasted and observed atmospheric visibilities was observed (R=0.7167). Furthermore, atmospheric visibility forecasting models were established for various weather patterns. The accuracies of atmospheric visibility verification (September~December, 2007) and forecasting (January~March, 2008) were 91.80% and 87.97%, respectively. This study further applied SPSS stastistic software to conduct factor analysis for atmospheric visibility. Results from factor analysis of visibility indicated that the top three factors (PM10, NO2, and SO2) accounted for 71.13% of variance. Furthermore, variable correlation analysis showed that atmospheric visibility had positive correlation with wind speed and negative correlation with other variables (PM10, NO2, SO2, O3, RH, and WD). Besides, for the significant levels of £\=0.01 or £\=0.05, all variables were proven to be significantly correlated with atmospheric visibility except O3. At Taipei region, the automobile tail emission was the major emission source causing low visibility, thus the most effective strategy for improving atmospheric visibility was to reduce the mission of automobiles and the formation of secondary aerosols containing ammonium nitrate and ammonium sulfate, which could effectively increase the atmospheric visibility at Taipei region.