Temporal Relationship Between Particulate Matter (PM10) And Carbon Monoxide (CO) In Kuala Lumpur

Air pollution is now becoming a common feature in Kuala Lumpur city. It has assumed an important level to the proportion that the city populace recognises its presence. The future of air pollution in the city seems to be bleak. From one stand point, air pollution although dangerous and threatening to the quality of life and environment, it is a luxurious problem and relatively remote in priority to the general public. This research is carried out to understand the changes in trend of particulate matter (PM10) and carbon monoxide (CO) concentration within a set time frame or limit in the selected monitoring sites which is located in heavily trafficked urban area of Malaysia which is Kuala Lumpur. Hourly and daily concentration of particulate matter and carbon monoxide are collected over an 8-month period from January to August. By using the statistical and graphical analysis, the data will be analysed and as the results, the variation of concentration for both particulate matter (PM10) and carbon monoxide (CO) will be define from the analysis. From the research, the results shows that the ambient level of carbon monoxide was relatively low as compared to the particulate matter. Based on the analysis, it was found that the annual average CO value is 2.52 ug/m3 while the annual average PM10 value is 77.64 ug/m3. It was shows that average PM10 levels in Kuala Lumpur network are generally higher than average CO levels. The concentrations levels of CO were far below the maximum limit of 30 ppm for one hour averaging time set by the Malaysian Guidelines. On the other hand, the PM10 mean concentration was higher but still not exceed the maximum limit 150 ug/m3 for the 24 hour averaging time which also set by the Malaysian Guidelines

Modeling of ozone precursors and their transformation into ground-level ozone in urban environment in Malaysia

Ozone (O3) is one of the major problems of air pollution around the world due to its ability to cause adverse effect to human health and environment. Hence, it is important to develop O3 prediction model to give the early warning to public. The hourly observations of O3 and nitrogen oxides (NOx) concentrations together with the weather parameters were monitored from five study areas in Malaysia. The observations were obtained over five year period from 2003 to 2007. Times series plot was used to explain the transformation of nitrogen dioxide (NO2) into O3 at urban environment of Malaysia. The findings proved that the peak concentration of O3 occurs during noon when highest UVB intensity and temperature recorded. By using multiple linear regression analysis, O3 prediction daytime and night time models for each study areas were developed based on its precursors

Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique

This paper investigated the use of boosted regression trees (BRTs) to draw an inference about daytime and nighttime ozone formation in a coastal environment. Hourly ground-level ozone data for a full calendar year in 2010 were obtained from the Kemaman (CA 002) air quality monitoring station. A BRT model was developed using hourly ozone data as a response variable and nitric oxide (NO), Nitrogen Dioxide (NO2) and Nitrogen Dioxide (NOx) and meteorological parameters as explanatory variables. The ozone BRT algorithm model was constructed from multiple regression models, and the ‘best iteration’ of BRT model was performed by optimizing prediction performance. Sensitivity testing of the BRT model was conducted to determine the best parameters and good explanatory variables. Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. The performance of the O3 boosting models were assessed, and the fraction of predictions within two factor (FAC2), coefficient of determination (R²) and the index of agreement (IOA) of the model developed for day andnighttime are 0.93, 0.69 and 0.73 for daytime and 0.79, 0.55 and 0.69 for nighttime respectively. Results showed that the model developed was within the acceptable range and could be used to understand ozone formation and identify potential sources of ozone for estimating O3 concentrations during daytime and nighttime Results indicated that the wind speed, wind direction, relative humidity, and temperature were the most dominant variables in terms of influencing ozone formation. Finally, empirical evidence of the production of a high ozone level by wind blowing from coastal areas towards the interior region, especially from industrial areas, was obtained

A Framework For Monitoring And Modelling Of Btex In Various Development Statuses In Penang, Malaysia.

The development and urbanization process in Malaysia are believed to contribute to the deterioration of air quality. The rapid growth of the Malaysian economy lead to the increase of motor vehicles ownership, in 2006, there 6.91 million registered cars running on the roads in Malaysia. Benzene, Toluene, Ethylbenzene and Xylene (BTEX) form an important group of aromatic Volatile Organic Compounds (VOCs), emitted mainly from cars, where BTEX is a known carcinogenic

Different Approaches of Multiple Linear Regression (MLR) Model in Predicting Ozone (O3) Concentration in Industrial Area

Meteorological conditions and other gaseous pollutants generally impacted the development of ozone (O3) in the atmosphere. The purpose of this study was to create the best O3 model for forecasting O3 concentrations in the industrial area and to determine the variables that affect O3 concentrations. Five-year data of meteorological and gaseous pollutants were used to analyze and develop the prediction model. Based on three distinct techniques, three separate multiple linear regression (MLR) prediction models of O3 concentration were developed. MLR3 had the highest correlation coefficient of 0.792 during development as compared to models MLR1 and MLR2. MLR2 was deemed the best O3 prediction model, however, since it had the lowest error values of root mean square error (3.976) and mean absolute error (3.548) when compared to other models. The establishment of an O3 prediction model can offer local governments with early information that could help them reduce and manage air pollution emissions

Different Approaches of Multiple Linear Regression (MLR) Model in Predicting Ozone (O3) Concentration in Industrial Area

Meteorological conditions and other gaseous pollutants generally impacted the development of ozone (O3) in the atmosphere. The purpose of this study was to create the best O3 model for forecasting O3 concentrations in the industrial area and to determine the variables that affect O3 concentrations. Five-year data of meteorological and gaseous pollutants were used to analyze and develop the prediction model. Based on three distinct techniques, three separate multiple linear regression (MLR) prediction models of O3 concentration were developed. MLR3 had the highest correlation coefficient of 0.792 during development as compared to models MLR1 and MLR2. MLR2 was deemed the best O3 prediction model, however, since it had the lowest error values of root mean square error (3.976) and mean absolute error (3.548) when compared to other models. The establishment of an O3 prediction model can offer local governments with early information that could help them reduce and manage air pollution emissions

Time effects of high particulate events on the critical conversion point of ground-level ozone

Particulate matter (PM), especially those with an aerodynamic particle size of less than 10 μm (PM10), is typically emitted from transboundary forest fires. A large-scale forest fire may contribute to a haze condition known as a high particulate event (HPE), which has affected Southeast Asia, particularly Peninsular Malaysia, for a long time. Such event can alter the photochemical reactions of secondary pollutants. This work investigates the influence of PM on ground-level ozone (O3) formation during HPE. Five continuous air quality monitoring stations from different site categories (i.e., industrial, urban and background) located across Peninsular Malaysia were selected in this study during the HPEs in 2013 and 2014. Result clearly indicated that O3 concentrations were significantly higher during HPE than during non-HPE in all the sites. The O3 diurnal variation in each site exhibited a similar pattern, whereas the magnitudes of variation during HPE and non-HPE differed. Light scattering and atmospheric attenuation were proven to be associated with HPE, which possibly affected O3 photochemical reactions during HPE. Critical conversion time was used as the main determining factor when comparing HPE and non-HPE conditions. A possible screening effect that resulted in the shifting of the critical transformation point caused a delay of approximately of 15–30 min. The shifting was possibly influenced by the attenuation of sunlight in the morning during HPE. A negative correlation between O3 and PM10 was observed during the HPE in Klang in 2013 and 2014, with −0.87. Essentially, HPE with a high PM concentration altered ground-level O3 formation

Diurnal fluctuations of ozone concentrations and its precursors and prediction of ozone using multiple linear regressions

The chemical reaction of pollutants emitted into the atmosphere leads to a variety of oxidized products, which are commonly referred to as secondary pollutants. Ground level ozone is a known secondary photochemical pollutant of major importance possessing detrimental effects on health, agriculture, natural/urban ecosystems and materials. Ozone (O3) can irritate lung airways and cause inflammation much like sunburn. Hourly and monthly variations of O3 and their precursors – nitrogen oxides (NOx) and meteorological parameters (temperature and wind speed) were presented using time series plots. Possibility of employing multiple linear regression models as a tool for prediction of O3 concentration was also tested. Measurement was performed continuously in 2005 at two sampling stations located in the metropolitan area of Malaysia. Results indicated that the formation of O3 in the study area was influenced by NOx precursors and meteorological conditions. The hourly variation showed maximum O3 concentrations were recorded between 1300 to 1400 hours, while NOx and nitrogen dioxide (NO2) exhibited two maxima, at 0800-1000 and 2000-2100 hours. The daily cycle of highest O3 concentrations were revealed a lower night level and inverse relations between O3 and NOx. This is clear evidence of photochemical formation of O3. Temperature has the highest influence to the high O3 concentration

Relationship between AOTX Indices and Crops Response towards Ozone Concentration in Malaysia

Abstrac