Statistical analysis of PM10 concentrations at different locations in Malaysia

Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.     

Monsoonal differences and probability distribution of PM10 concentration

There are many factors that influence PM₁₀ concentration in the atmosphere. This paper will look at the PM₁₀ concentration in relation with the wet season (north east monsoon) and dry season (south west monsoon) in Seberang Perai, Malaysia from the year 2000 to 2004. It is expected that PM₁₀ will reach the peak during south west monsoon as the weather during this season becomes dry and this study has proved that the highest PM₁₀ concentrations in 2000 to 2004 were recorded in this monsoon. Two probability distributions using Weibull and lognormal were used to model the PM₁₀ concentration. The best model used for prediction was selected based on performance indicators. Lognormal distribution represents the data better than Weibull distribution model for 2000, 2001, and 2002. However, for 2003 and 2004, Weibull distribution represents better than the lognormal distribution. The proposed distributions were successfully used for estimation of exceedences and predicting the return periods of the sequence year.     

陕西民俗文化旅游资源的保护与开发

陕西民俗文化旅游资源丰富,具有较高的社会价值和旅游价值,但由于政府部门的疏于重视和广大民众认识的浅薄,导致陕西民俗文化旅游资源受到严重的破坏,同时也造成不良风气的大量出现,使这些价值未能得以发挥.针对这一现状,以全国民俗文化的保护和开发为参照,结合陕西民俗文化旅游资源的自身特点,从保护和发展两个方面涉及的具体问题为出发点,就具体的问题提出了具体的建议,希望以此引起各方重视.参5.     

Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO₂) into ozone (O₃) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O₃ in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O₃ concentration was tested. Results indicated that the presence of NO₂ and sunshine influence the concentration of O₃ in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.