Tujuan kajian ini adalah untuk memantau kepekatan partikel halus terampai (PM2.5) di Nibong Tebal. Tahap kepekatan PM2.5 dicerap menggunakan BAM (Beta Attenuation Monitor) mudah alih. Parameter meteorologi seperti suhu, kelembapan, kelajuan angin dan arah angin serta jumlah kenderaan juga dicerap dalam kajian ini. Kepekatan purata PM2.5 adalah 48.88 μg/m3 yang mana ianya tidak melebihi piawaian yang ditetapkan oleh United States Environmental Protection Agency. Dalam kajian ini, hubungan antara kepekatan PM2.5, jumlah trafik dan parameter meteorologi dianalisis dengan menggunakan komposit graf telah dikenal pasti. Kajian menunjukkan pengaruh jumlah trafik dan parameter meteorologi mempengaruhi tahap kepekatan PM2.5. Terdapat hubungan yang kuat antara kepekatan PM2.5 yang diperolehi dengan parameter meteorologi berbanding pengaruh jumlah trafik.. Analisis “scanning electron microscopy with energy dispersive x-ray” telah digunakan untuk mengenal pasti 12 unsur pada penapis yang terdiri daripada C, O, Na, Al, Si, S, Cl, K, Ca, Zn, Ba, dan Mg. Berdasarkan plot antara kepekatan PM2.5 yang diramalkan menggunakan model MLR dan kepekatan PM2.5 sebenar pekali penentuan R2 yang diperolehi bagi model MLR dibangunkan berdasarkan hari bekerja adalah 0.54. Ini bermakna model yang dibangunkan dapat menjelaskan 54% daripada jumlah kebolehubahan data. Untuk model MLR yang dibangunkan pada hari minggu, nilai R2 adalah 0.65.
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The purpose of this study is to monitor the concentration of fine particles (PM2.5) in Nibong Tebal. The level of concentration of PM2.5 was monitored using the portable BAM, "Environmental Beta Attenuation Monitor". Meteorological parameters such as temperature, relative humidity, wind speed and wind direction as well as a number of vehicles were also observed in the study. The mean concentration of PM2.5 is 48.88 μg/m3 which is not exceeded the United States Environmental Protection Agency standards. In this study, the relationship between concentrations of PM2.5, the traffic volumes and meteorological parameters were analyzed using composite plot has been identified. The results show the influence of traffic volume and meteorological parameters affect the PM2.5 concentration levels. PM2.5 concentration levels were more strongly correlated with the meteorological parameters rather than traffic volumes. There is a strong relationship between the concentration obtained PM2.5 with temperature and relative humidity. Scanning electron microscopy with energy dispersive analysis has been used to identify 12 elements on the filters that consist of C, O, Na, Al, Si, S, Cl, K, Ca, Zn, Ba, and Mg. Based on the plot between predicted PM2.5 concentration obtained by using the MLR model and the actual PM2.5 concentration the coefficient of determination, R2 for weekdays was 0.54. It shows that the model developed can explain 54% of the total variability of the data. For MLR model developed based on weekends, the R2 value was 0.65.
Concentration of fine particles (pm2.5) from roadside / Radziati Ramlee