NOx is an important precursor of fine particulate matter (PM2.5) and O-3 and its oxidation product NO3- may be the main driver of PM2.5. In this study, 76 daily fine particle samples were collected from a site in South China, and the characteristics of NO3- were studied using an improved Bayesian mixing model based on delta N-15-delta O-18 compositions and online trace gas analysis. NO3- concentrations ranged from 0.60 to 21.7 mu g/m(3), accounting for 6.0 +/- 3.3% of total PM2.5 on average. delta N-15-NO3- values varied from -3.6 to 15.4 parts per thousand (average: 7.5 +/- 3.3 parts per thousand). Driven by changes in chemical pathways and environmental parameters, including equilibrium fractionation and thermodynamic effects, delta N-15-NO3- values were lowest in spring and highest in winter. delta O-18-NO3- values varied from 21.0 to 90.1 parts per thousand (average: 62.4 +/- 14.0 parts per thousand). In spring, the lowest delta O-18-NO(3)(-)values were observed due to high proportions originating from center dot HO2 and center dot OH reaction pathways, as well as changes in other parameters. In winter, the highest delta O-18-NO3- values were observed due to cold and dry weather, along with the lowest proportion from the center dot OH pathway. Moreover, the trace gases CO, O-3, NOx, SO2, and N2O5 were measured seasonally to determine the main drivers of seasonality in delta N-15-delta O-18 composition. Monte Carlo simulation was used to estimate the relative contributions of the gas-phase reactions of NO2 and center dot OH radicals and the hydrolysis of N2O5. The results showed that the center dot OH generation pathway was predominant throughout the year, with relative contributions of 72 +/- 18%, 76 +/- 16%, 63 +/- 17% and 39 +/- 15% in spring, summer, fall and winter, respectively. Coal combustion (50.1 +/- 13.8%) was the predominant source of NO3- identified using the Bayesian model, and originated from central and southern Guangdong Province, as indicated by potential source contribution function analysis
