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1. Introduction Human activities have led to several important air quality issues, such as elevated tropospheric ozone (O 3 ), particulate matter, and visibility problems, which affect human health and the natural environment. Anthropogenic increases in atmospheric concentrations of greenhouse gases also are increasing concerns about future climate change ( Houghton et al. 2001 ). Global warming could have detrimental effects on future air quality, such as increased frequency of harmful
1. Introduction Human activities have led to several important air quality issues, such as elevated tropospheric ozone (O 3 ), particulate matter, and visibility problems, which affect human health and the natural environment. Anthropogenic increases in atmospheric concentrations of greenhouse gases also are increasing concerns about future climate change ( Houghton et al. 2001 ). Global warming could have detrimental effects on future air quality, such as increased frequency of harmful
variation at frequencies less than 0.4 month −1 (i.e., the synoptic-scale or weather-induced variations) and the other having variations characterized by frequencies greater than 0.4 month −1 (i.e., the baseline or seasonal plus longer-term variations). As recommended by Rao et al. (1997) , we work with log-transformed ozone data to account for the multiplicative effects of weather on the ozone baseline. 1) Identification of meteorological variables inducing ozone baseline fluctuations By
variation at frequencies less than 0.4 month −1 (i.e., the synoptic-scale or weather-induced variations) and the other having variations characterized by frequencies greater than 0.4 month −1 (i.e., the baseline or seasonal plus longer-term variations). As recommended by Rao et al. (1997) , we work with log-transformed ozone data to account for the multiplicative effects of weather on the ozone baseline. 1) Identification of meteorological variables inducing ozone baseline fluctuations By
, 2000 : Spatial and seasonal patterns and temporal variability of haze and its constituents in the United States, Rep. III, 384 pp . Jiang , G. F. , and J. D. Fast , 2004 : Modeling the effects of VOC and NOX emission sources on ozone formation in Houston during the TexAQS 2000 field campaign. Atmos. Environ. , 38 , 5071 – 5085 . Lin , C. J. , T. C. Ho , H. W. Chu , H. Yang , S. Chandru , N. Krishnarajanagar , P. Chiou , and J. R. Hopper , 2005 : Sensitivity
, 2000 : Spatial and seasonal patterns and temporal variability of haze and its constituents in the United States, Rep. III, 384 pp . Jiang , G. F. , and J. D. Fast , 2004 : Modeling the effects of VOC and NOX emission sources on ozone formation in Houston during the TexAQS 2000 field campaign. Atmos. Environ. , 38 , 5071 – 5085 . Lin , C. J. , T. C. Ho , H. W. Chu , H. Yang , S. Chandru , N. Krishnarajanagar , P. Chiou , and J. R. Hopper , 2005 : Sensitivity
levels were higher. Predictions of daily averaged PM 2.5 concentrations were overestimated in all seasons when compared with filter-based measurements from FRM monitors in New York State, and there was little seasonal or interannual variation in model bias and model error ( Table 3 ). Next, the analysis for PM 2.5 was repeated with data stratification by land use and the results of this analysis are shown in Table 4 . This analysis reveals that the overprediction of total PM 2.5 mass for the
levels were higher. Predictions of daily averaged PM 2.5 concentrations were overestimated in all seasons when compared with filter-based measurements from FRM monitors in New York State, and there was little seasonal or interannual variation in model bias and model error ( Table 3 ). Next, the analysis for PM 2.5 was repeated with data stratification by land use and the results of this analysis are shown in Table 4 . This analysis reveals that the overprediction of total PM 2.5 mass for the
between a few tens of meters during the night and 2–4 km or even deeper during the day, especially during summer ( Kallos et al. 1998a ). The mixing layer over the Mediterranean Sea is almost stable during the diurnal cycle (∼300 m) and varies slightly with the seasonal cycle (200–350 m). An important feature of the coastal zones of the GMR is the formation of the internal boundary layer. The islands and the peninsulas act as chimneys and obstacles, causing abrupt changes in the mixing depth ( Kallos
between a few tens of meters during the night and 2–4 km or even deeper during the day, especially during summer ( Kallos et al. 1998a ). The mixing layer over the Mediterranean Sea is almost stable during the diurnal cycle (∼300 m) and varies slightly with the seasonal cycle (200–350 m). An important feature of the coastal zones of the GMR is the formation of the internal boundary layer. The islands and the peninsulas act as chimneys and obstacles, causing abrupt changes in the mixing depth ( Kallos
1. Introduction Polycyclic organic hydrocarbons (PAHs) belong to the so-called persistent organic pollutants (POPs), a group of substances with known adverse effects on ecosystems and human health. Single ones or mixtures of these compounds can, for example, cause cancer or impair reproduction ( Mumatz and George 1995 ). The concentrations of PAHs in the environment are relatively low, but they gain their extraordinary ecotoxicity from their persistency in various environmental compartments
1. Introduction Polycyclic organic hydrocarbons (PAHs) belong to the so-called persistent organic pollutants (POPs), a group of substances with known adverse effects on ecosystems and human health. Single ones or mixtures of these compounds can, for example, cause cancer or impair reproduction ( Mumatz and George 1995 ). The concentrations of PAHs in the environment are relatively low, but they gain their extraordinary ecotoxicity from their persistency in various environmental compartments
