1. Fig.6a,b. Simulation of wind fields and toluene plumes on (a) May 12 and (b) May 13. Red dot is the beach site. Very low level of toluene was observed in the period 5/12-5/13 (see Fig. 5) Strong easterly to northeasterly winds are blocked on the east side of the island by the central Mountain ranges (refer to Fig. 1b for topography). Diagnosis of Air Quality through Observation and Modeling of Volatile Organic Compounds (VOCs) as Pollution Tracers Wen-tzu Liu 1, Neng-huei Lin 2,Julius S. Chang 2, Sheng-po Chen 2, Hsin-cheng Hsieh 1, Jia-Lin Wang 1* 1.Department of Chemistry, National Central University, Chungli, Taiwan. 2.Department of Atmospheric Sciences, National Central University, Chungli, Taiwan Results and discussion A VOC speciated air quality model was employed to simulate both temporal and spatial distributions of VOC plumes. The model successfully captured the general features of the variations of toluene as a pollution tracer, which suggests that emissions and meteorology were reasonably well simulated in the model. Through validation by observation, the model can display both the temporal and spatial distribution of air pollutants in a dynamic manner. Thus, a more insightful understanding of how local air quality is affected by meteorology can be obtained. Conclusions We used large concentration variability of trace gases observed at a beach site in southern Taiwan to test model’s performance. Over 30 hydrocarbons (NMHCs) and chlorofluorocarbons (CFCs) were monitored for two months with hourly resolution. Large concentration variability was caused by the urban sources and inter-change of land-sea winds. Toluene was found to exhibit the greatest variability and concentrations, thus, was used as an indicator of land-based air masses. By contrast, CFCs were found to exhibit very small variability, suggesting emissions of anthropogenic CFCs have been largely ceased. The dataset was used to validate the VOC emissions of an air quality model, which in turn was used to simulate evolution of temporal and spatial distributions of pollutants. Study domain Objective Fig. 3. Time-series variability of three selected gases. While benzene, toluene, and other VOCs (not shown) varied considerably, CFC-113 (CCl 2 FCClF 2 ), which was banned by the Montreal Protocol, showed a constant level close to its background mixing ratios. Hence, the atmospheric CFC-113 was used as an internal reference to assure the quality of VOC measurements made by the self-made automated GC at the beach site. Fig. 1a, b. The study domain, southern Taiwan, is encircled by the box (a), the enlarged topography shows the locations of the urban site (labeled as 1) and the beach site (labeled as 2), with a straight distance of 80 km (b). A coastal highway (Shenbei Rd.) is about 2.5 km away from the beach site. Both sites measured VOCs and air-quality species (e.g., NOx, CO and O 3 ). (a) (b) Fig. 2. Three mobile labs were stationed at the beach site from 5/7 to 5/18, 2011. The middle freighter container, a “makeshift” lab, accommodated an in- situ GC/FID/ECD system measuring C 6 -C 12 NMHCs and CFCs with hourly resolution. The two containers on both sides were Taiwan EPA and NASA COMMIT mobile labs measuring air quality and aerosol properties. Fig.5. Compare the simulated toluene level (red dot) by the PAMS-AQM model with the observed level (blue line). The model was able to distinguish the monsoon period from the diurnal period, and simulated toluene concentration level close to the observed level. Two arrows indicate two time slots with very different weather conditions and, thus, toluene distributions, as illustrated in Fig. 6 and 7. Fig. 4. Mixing ratios of trace gases at the beach site. Three main features can be categorized during the period ： (1) The abrupt change in wind direction at the onset of northerly monsoon event (yellow block); (2) The sweeping effect by strong northerly winder monsoon winds as revealed by the loss of diurnal features (green block); (3) Back to typical calm weather conditions, as revealed by the repeated diurnal cycles due to the alternate land-sea wind breezes (pink block). Contact information ： cwang@cc.ncu.edu.tw Acknowledgements We thank Taiwan Environmental Protection Agency for providing the PAMS data. This project is under contracts: NSC-2111-M008-015 and EPA-99-FA11- 03-A097. Fig.7a,b. Simulation of the evolution of toluene plumes on 5/16. (a)Before the toluene plumes arrived at the beach site. The concentrations remained low (< 0.1 ppb). (b)hitting the beach site around noon causing a concentration rise for toluene (>2 ppb). (c) passing the beach site. The toluene level dropped rapidly. (b) (a) (b) (a) 80 km (c)