DocumentCode :
3359974
Title :
Residential indoor environmental health risk assessment with stochastic theory in Changsha, Hunan
Author :
Liu, Jianlong ; Chen, Keliang ; Lin, Jianping ; Yang, Xiaodong
Author_Institution :
Coll. of Civil Eng., Hunan Univ. of Technol., Zhuzhou, China
fYear :
2010
fDate :
26-28 June 2010
Firstpage :
2073
Lastpage :
2076
Abstract :
Indoor environment is tightly related to the life of human beings. Urban residents spend over 90% of their daily time in indoor environments, among which over 50% is in residential environment. Therefore, the indoor air quality (IAQ) in residential environment will influence residents´ health and safety directly. How to appraise the risk of residential indoor environment quality and to create a comfortable and healthy residential environment will have momentous effect on residents´ health. This paper use a new residential health risk assessment method based on stochastic theory. In this new method, the multiple parameters uncertainty residential health risk assessment model is simulated with Monte Carlo simulation and electric sampling arithmetic, and some related parameters are optimized and improved. Consequently, the method overcomes the disadvantages of traditional single-point risk assessment, thus possesses more practical value for complicated health risk assessment. The author takes city family residence as object to investigate the stopover time in different indoor environment for people of different professions, stopover time in different function rooms of residences with well designed questionnaire, and detects the concentration of contaminants in different function rooms in residences. This investigation proves that residence is the indoor environment where people stay the longest time, illustrates the stay time of residents in different function rooms, and the distribution of the contaminant concentration in different function rooms. This paper focuses on the study of quantitative effects of uncertainty factors on risk assessment based on the statistical data. The author calculates the concentrations of formaldehyde and benzene and their impacts on residents´ health risk based on stochastic theory with resident health risk assessment scheme and model parameters optimization design based on the new method. The result shows that the maximum cancer risk - - for male due to exposure to formaldehyde for all types of rooms, with 90% confidence level, is the secondary bedroom (1.16E-04). And the maximum cancer risk due to exposure to benzene for all types of rooms, with 90% confidence level, is master bedroom (3.05E-05). The result shows that the maximum cancer risk for female due to exposure to formaldehyde for all types of rooms, with 90% confidence level, is the master bedroom (1.48E-04). And the maximum cancer risk due to exposure to benzene for all types of rooms, with 90% confidence level, is master bedroom (4.18E-05).
Keywords :
Monte Carlo methods; air pollution; cancer; hazardous materials; organic compounds; risk management; stochastic processes; Changsha; Hunan; Monte Carlo simulation; benzene concentration; electric sampling arithmetic; formaldehyde concentration; indoor air quality; multiple parameter uncertainty; parameters optimization design; residential indoor environmental health risk assessment; single point risk assessment; stochastic theory; Appraisal; Arithmetic; Cancer; Health and safety; Humans; Indoor environments; Risk management; Sampling methods; Stochastic processes; Uncertain systems; Indoor air quality; Monte Carlo simulation; Residence; Risk assessment; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
Type :
conf
DOI :
10.1109/MACE.2010.5536260
Filename :
5536260
Link To Document :
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