Flood risk index pattern assessment: case study in Langat River Basin

Self Cite

This study identify the air pollutant that occurs in the kindergartens, to measure the le indoor air quality and also to analyze respiratory health symptoms. Three kindergartens were selected based on types of building J Fundam Appl Sci. 2017, 9(4S), 801-811 802The exposure history and respiratory health symptoms data among respondent in the study area were being collected by using questionnaire. Sampling for IAQ also being conducted and parameters involved for this purposed included carbon monoxide, carbon dioxide, temperature and humidity. Result shows that there is no significant difference of IAQ level between all kindergartens except for temperature and humidity (p≤0.05). The respiratory health symptoms also showed that only phlegm and chest illness show the significant difference in all kindergartens which (p≤0.05).

Section: Resultsmentioning

confidence: 99%

Assement on level of indoor air quality at kindergartens in Ampang Jaya, Selangor, Malaysia

Sarijuddin¹,

Saudi²,

Kamarudin³

et al. 2018

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“…This index ranged from 0-100 rate and the rate that was set at the risk 70 and above was the high rate of water level at risk of flood. The 70 and above set for UCL and CL value were set at 35-69 and down to LCL starting with 0-34 index for the range of flood risk index [25]. High risk was classified to all data which located greater than the UCL line in the control chart graph, followed by cautionary zone for data that were plotted between CL line and UCL line, low risk for data that were plotted between LCL line and CL line, and no risk for data that were plotted below the LCL line.…”

Section: Flood Risk Index (Fri) In the Study Areamentioning

confidence: 99%

New flood risk index in tropical area generated by using SPC technique

Saudi¹,

Ridzuan²,

Balakrishnan³

et al. 2018

This study applied four hydrology parameters. The findings from Principal Component Analysis confirmed that all selected parameters were significant to be taken as main tools for further analysis with result of R 2 > 0.7. SPC set up a new control limit for all selected parameters in the study area. For those data within or beyond the Upper Control Limit value, it was being considered as high risk for flood occurrence. New flood risk index within range from 0-100 was calculated using a combination of new algebraic equation and control limit values obtained from SPC analysis as variable. The accuracy of FRI was tested using ANN.The result showed the accuracy of FRI was more than 90%. It can be stipulated that the combination of chemometric techniques and SPC can produce a new standard FRI which is cost effective, accurate and flexible to be applied for the purpose of flood risk control in tropical area.

“…As reported by [19], who stated that PM 10 concentration is directly proportional to temperature reading but inversely proportional to humidity percentage. The existence of water [33][34] vapour can suspend the particulate matter away from ambient atmosphere, resulting low level of PM 10 and lowering the dispersion of air pollutants in atmosphere [19]. As well, reported by [25], it was extremely crucial to consider the meteorological states on air pollution since they specifically control the dispersion of air pollutants in atmosphere.…”

Section: U a Zakaria Et Al J Fundam Appl Sci 2017 9(4s) 772-788mentioning

confidence: 99%

The assessment of ambient air pollution pattern in Shah Alam, Selangor, Malaysia

Zakaria

Saudi

Abu

et al. 2018

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This study implements the statistical analysis to establish the association between air pollution trends with the industrial activities in Shah Alam, Selangor. PCA used to identify significant parameters contributing to air pollution and it sources of pollutions, whereas SPC used to determine the pattern and contribution each of most significa area and Spearman Correlation used to determine the relatio meteorological factors. The result identified the major possible sources of air pollution were 38.3% and 32.46% of total variance. The patterns for most significant parameters mo exceeding RMAAQG from 2009 to correlation between air pollutants and meteorological was significantly low.