Abstract. Tropospheric ozone is of great importance with regard to air quality, atmospheric chemistry, and climate change. In this paper we report the first continuous record of surface ozone in the background atmosphere of South China. The data were obtained from 1994 to 2007 at a coastal site in Hong Kong, which is strongly influenced by the outflow of Asian continental air during the winter and the inflow of maritime air from the subtropics in the summer. Three methods are used to derive the rate of change in ozone. A linear fit to the 14-year record shows that the ozone concentration increased by 0.58 ppbv/yr, whereas comparing means in years

1] In this paper, the accuracy performance of monthly streamflow forecasts is discussed when using data-driven modeling techniques on the streamflow series. A crisp distributed support vectors regression (CDSVR) model was proposed for monthly streamflow prediction in comparison with four other models: autoregressive moving average (ARMA), K-nearest neighbors (KNN), artificial neural networks (ANNs), and crisp distributed artificial neural networks (CDANN). With respect to distributed models of CDSVR and CDANN, the fuzzy C-means (FCM) clustering technique first split the flow data into three subsets (low, medium, and high levels) according to the magnitudes of the data, and then three single SVRs (or ANNs) were fitted to three subsets. This paper gives a detailed analysis on reconstruction of dynamics that was used to identify the configuration of all models except for ARMA. To improve the model performance, the data-preprocessing techniques of singular spectrum analysis (SSA) and/or moving average (MA) were coupled with all five models. Some discussions were presented (1) on the number of neighbors in KNN; (2) on the configuration of ANN; and (3) on the investigation of effects of MA and SSA. Two streamflow series from different locations in China (Xiangjiaba and Danjiangkou) were applied for the analysis of forecasting. Forecasts were conducted at four different horizons (1-, 3-, 6-, and 1 2-month-ahead forecasts). The results showed that models fed by preprocessed data performed better than models fed by original data, and CDSVR outperformed other models except for at a 6-month-ahead horizon for Danjiangkou. For the perspective of streamflow series, the SSA exhibited better effects on Danjingkou data because its raw discharge series was more complex than the discharge of Xiangjiaba. The MA considerably improved the performance of ANN, CDANN, and CDSVR by adjusting the correlation relationship between input components and output of models. It was also found that the performance of CDSVR deteriorated with the increase of the forecast horizon.

Guangzhou (GZ) is one of the highly industrialized and economically vibrant cities in China, yet it remains relatively understudied in terms of its air quality, which has become severely degraded. In this study, extensive air sampling campaigns had been conducted at GZ urban sites and in Dinghu Mountain (DM), a rural site, in the Pearl River Delta (PRD) during the spring of 2001 and 2005. Additionally, roadside and tunnel samples were collected in GZ in 2000 and 2005. Later, exhaust samples from liquefied petroleum gas (LPG)-and gasoline-fueled taxis were collected in 2006. All samples were analyzed for C 2 -C 10 non-methane hydrocarbons (NMHCs). NMHC profiles showed significant differences in the exhaust samples between gasoline-and LPG-fueled taxis. Propane (47%) was the dominant hydrocarbon in the exhaust of the LPG-fueled taxis, while ethene (35%) was the dominant one in that of gasoline-fueled taxis. The use of LPG-fueled buses and taxis since 2003 and the leakage from these LPG-fueled vehicles were the major factors for the much higher level of propane in GZ urban area in 2005 compared to 2001. The mixing ratios of toluene, ethylbenzene, m/p-xylene and o-xylene decreased at the GZ and DM sites between 2001 and 2005, especially for toluene in GZ, despite the sharp increase in the number of registered motor vehicles in GZ. This phenomenon was driven in part by the closure of polluting industries as well as the upgrading of the road network in urban GZ and in part by the implementation of more stringent emission standards for polluting industries and motor vehicles in the PRD region. r

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