A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed d...A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed dataset,from the aspects of the weather situation,vapor condition,dynamic factor,temperature stratification,and air quality the contribution of foggy conditions and air pollution in the fog process to continuous heavy fog were analyzed.The results showed that 1 000 hPa fluid flux divergence (FD),vertical velocity (ω) and divergence difference(△DIV) between 1 000 hPa and 500 hPa had not significantly correlative with visibility,while relative humidity (RH) near ground had significant negative correlative,temperature lapse rate (γ) near ground had significant positive correlation,therefore,RH≥85%,γ<0.2 ℃/100m could be regarded as the necessary conditions of fog formation.In addition,the lowest air visibility had intense negative correlation with daily averaged API in the meantime,'API rising up to 150' could be an important criterion of fog formation in Shanghai Hongqiao international airport.展开更多
The objective of this work is to analyze the temporal and spatial variability of the monthly mean aerosol index (AI) obtained from the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) in c...The objective of this work is to analyze the temporal and spatial variability of the monthly mean aerosol index (AI) obtained from the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) in comparison with the available ground observations in Nigeria during 1984-2013. It also aims at developing a regression model to allow the estimation of the values of AI in Nigeria based on the data from ground observations. TOMS and OMI data are considered and treated separately to provide continuity and consistency in the long-term data observations, together with the meteorological variable such as wind speed, visibility, air temperature and relative humidity that can be used to characterize the dust activity in Nigeria. The results revealed a strong seasonal pattern of the monthly distribution and variability of absorbing aerosols along a north to south gradient. The monthly mean AI showed higher values during the dry months (Harmattan) and lower values during the wet months (Summer) in all zones. From December to February, higher AI values are observed in the southern region, decreasing progressively towards the north, while during March-October, the opposite pattern is observed. The AI showed clear maximum values of 2.06, 1.93, and 1.87 (TOMS) and 2.32, 2.27 and 2.24 (OMI) in the month of January and minimum values in September over the north-central, southern and coastal zones, while showing maximum values of 1.76 (TOMS) and 2.10 (OMI) during March in the Sahel. New empirical algorithms for predicting missing AI data were proposed using TOMS data and multiple linear regression, and the model co-efficient was determined. The generated coefficients were applied to another dataset for cross-validation. The accuracy of the model was determined using the coefficient of determination R<sup>2</sup> and the root mean square error (RMSE) calculated at the 95% confidence level. The AI values for the missing years were retrieved, plotted and compared with the measured monthly AI cycle. It is concluded that展开更多
The driver’s visibility is degraded when weather conditions deteriorate, which affects the traffic flow and induces traffic congestion or accidents. In particular, traffic accidents can be?led to chain reaction colli...The driver’s visibility is degraded when weather conditions deteriorate, which affects the traffic flow and induces traffic congestion or accidents. In particular, traffic accidents can be?led to chain reaction collisions, with high rate of fatality, when fog occurs in contrast to other weather factors that may restrict visibility. For the development of a traffic risk index, a deviation of the vehicle’s speed was set for the traffic risk index by referring to previous study results. In addition, factors that affected the deviation in a vehicle’s speed were selected as independent variables based on the traffic flow analysis during occurrences of fog. The visible distance, traffic volume, and speed were selected as the independent variables to estimate the optimal parameters in the regression model. The traffic risk index model during occurrences of fog proposed in this study is an exponential model, with the visible distance and the traffic volume defined as independent variables. According to the study model, traffic risk increased as the visible distance decreased and the traffic volume was lower. Thus, the visible distance that can affect traffic flow during occurrences of fog can be determined in the future based on the results of this study. The study results will be expected to contribute to not only traffic safety improvements, but also the facilitation of traffic flow as drivers and traffic operation managers intuitively recognize the level of risk.展开更多
Based on daily visibility data obtained from 1980-2002 and air pollution index data from 2001-2004 in Xi＇an, long-term variations and relationships for daily horizontal extinction coefficient and mass concentration o...Based on daily visibility data obtained from 1980-2002 and air pollution index data from 2001-2004 in Xi＇an, long-term variations and relationships for daily horizontal extinction coefficient and mass concentration of PM10 have been evaluated. A decreasing trend was found in horizontal extinction coefficient during the past 23 years, with higher values observed in 1980s relative to 1990s, and the highest and lowest values in winter and summer, respectively. Significant correlation and similar seasonal variations existed between horizontal extinction coefficient and PM10 concentration, suggesting the high influence of PM10 to the visibility drop at a site in the Guanzhong Plain of central China during the past two decades.展开更多
文摘A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed dataset,from the aspects of the weather situation,vapor condition,dynamic factor,temperature stratification,and air quality the contribution of foggy conditions and air pollution in the fog process to continuous heavy fog were analyzed.The results showed that 1 000 hPa fluid flux divergence (FD),vertical velocity (ω) and divergence difference(△DIV) between 1 000 hPa and 500 hPa had not significantly correlative with visibility,while relative humidity (RH) near ground had significant negative correlative,temperature lapse rate (γ) near ground had significant positive correlation,therefore,RH≥85%,γ<0.2 ℃/100m could be regarded as the necessary conditions of fog formation.In addition,the lowest air visibility had intense negative correlation with daily averaged API in the meantime,'API rising up to 150' could be an important criterion of fog formation in Shanghai Hongqiao international airport.
文摘The objective of this work is to analyze the temporal and spatial variability of the monthly mean aerosol index (AI) obtained from the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) in comparison with the available ground observations in Nigeria during 1984-2013. It also aims at developing a regression model to allow the estimation of the values of AI in Nigeria based on the data from ground observations. TOMS and OMI data are considered and treated separately to provide continuity and consistency in the long-term data observations, together with the meteorological variable such as wind speed, visibility, air temperature and relative humidity that can be used to characterize the dust activity in Nigeria. The results revealed a strong seasonal pattern of the monthly distribution and variability of absorbing aerosols along a north to south gradient. The monthly mean AI showed higher values during the dry months (Harmattan) and lower values during the wet months (Summer) in all zones. From December to February, higher AI values are observed in the southern region, decreasing progressively towards the north, while during March-October, the opposite pattern is observed. The AI showed clear maximum values of 2.06, 1.93, and 1.87 (TOMS) and 2.32, 2.27 and 2.24 (OMI) in the month of January and minimum values in September over the north-central, southern and coastal zones, while showing maximum values of 1.76 (TOMS) and 2.10 (OMI) during March in the Sahel. New empirical algorithms for predicting missing AI data were proposed using TOMS data and multiple linear regression, and the model co-efficient was determined. The generated coefficients were applied to another dataset for cross-validation. The accuracy of the model was determined using the coefficient of determination R<sup>2</sup> and the root mean square error (RMSE) calculated at the 95% confidence level. The AI values for the missing years were retrieved, plotted and compared with the measured monthly AI cycle. It is concluded that
文摘The driver’s visibility is degraded when weather conditions deteriorate, which affects the traffic flow and induces traffic congestion or accidents. In particular, traffic accidents can be?led to chain reaction collisions, with high rate of fatality, when fog occurs in contrast to other weather factors that may restrict visibility. For the development of a traffic risk index, a deviation of the vehicle’s speed was set for the traffic risk index by referring to previous study results. In addition, factors that affected the deviation in a vehicle’s speed were selected as independent variables based on the traffic flow analysis during occurrences of fog. The visible distance, traffic volume, and speed were selected as the independent variables to estimate the optimal parameters in the regression model. The traffic risk index model during occurrences of fog proposed in this study is an exponential model, with the visible distance and the traffic volume defined as independent variables. According to the study model, traffic risk increased as the visible distance decreased and the traffic volume was lower. Thus, the visible distance that can affect traffic flow during occurrences of fog can be determined in the future based on the results of this study. The study results will be expected to contribute to not only traffic safety improvements, but also the facilitation of traffic flow as drivers and traffic operation managers intuitively recognize the level of risk.
文摘Based on daily visibility data obtained from 1980-2002 and air pollution index data from 2001-2004 in Xi＇an, long-term variations and relationships for daily horizontal extinction coefficient and mass concentration of PM10 have been evaluated. A decreasing trend was found in horizontal extinction coefficient during the past 23 years, with higher values observed in 1980s relative to 1990s, and the highest and lowest values in winter and summer, respectively. Significant correlation and similar seasonal variations existed between horizontal extinction coefficient and PM10 concentration, suggesting the high influence of PM10 to the visibility drop at a site in the Guanzhong Plain of central China during the past two decades.
