Classification of residential exposure to nitrogen dioxide |
| |
| Affiliation: | 1. Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, USA;2. Department of Animal Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, USA;3. Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA;1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China;2. The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China;3. Centre for Health Systems and Policy Research, JCSPHPC, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China;4. Department of Medicine and Therapeutics, Prince of Wales Hospital, Shatin, N.T. 999077, Hong Kong, China;5. Public Health Laboratory Centre, Centre for Health Protection, Kowloon 999077, Hong Kong, China;6. Department of Microbiology, Prince of Wales Hospital, Shatin, N.T. 999077, Hong Kong, China;7. Department of Rehabilitation Science, Faculty of Health and Social Science, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong, China;8. Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China;1. Department of Civil and Environmental Engineering, Hanyang University, 222 Wangsimni-Ro, Seoul 04763, Republic of Korea;2. Institute of Environmental and Energy Catalysis, School of Materials Science and Chemical Engineering, Xi''an Technological University, Xi''an, Shaanxi 710021, PR China;3. Shaanxi Key Laboratory of Optoelectronic Functional Materials and Devices, School of Materials Science and Chemical Engineering, Xi''an Technological University, Xi''an, Shaanxi 710021, PR China;4. School of Health and Environmental Science, Korea University, 145 Anam-Ro, Seoul 02841, Republic of Korea;5. Yangtze Delta Region Institute (Huzhou) & Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Huzhou 313001, PR China;6. Center for Environmental and Energy Research (CEER), Engineering of Materials via Catalysis and Characterization, Ghent University Global Campus, 119-5 Songdo Munhwa-ro, Yeonsu-gu, Incheon 406-840, Republic of Korea;7. Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium;1. Department of Pathology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil;2. Institute of Advanced Studies (IEA) Global Cities Program, University of São Paulo, São Paulo, Brazil;3. Chemical Analyses Laboratory, Institute for Technological Research (IPT), Sao Paulo, Brazil;4. Division of Research & Transfusion Medicine, Pro-Blood Foundation/Blood Center of São Paulo, Sao Paulo, Brazil;5. Laboratory of Medical Investigation in Pathogenesis and Targeted Therapy in OncoImmuno-Hematology (LIM-31), Department of Hematology, Hospital das Clínicas -HCFMUSP, Faculty of Medicine, University of São Paulo, São Paulo, Brazil;6. Department of Infectious and Parasitic Diseases, Faculty of Medicine, University of São Paulo, São Paulo, Brazil;7. Institute of Infectiology Emilio Ribas, Sao Paulo, Brazil;8. Chemical Analyses Laboratory, Institute for Technological Research (IPT), São Paulo, Brazil;9. Heart Institute (InCor), School of Medicine at Sao Paulo University, Sao Paulo, Brazil;1. Tianjin Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China;2. Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China;3. School of Civil Engineering, Dalian University of Technology, Dalian, China |
| |
| Abstract: | In epidemiological studies of indoor nitrogen dioxide (NO2) reported to date, only a limited number of measurements were made to estimate personal exposures. The accuracy of exposure estimates depends on the measurement error inherent in the samplers and in the sampling scheme. If categorical measures of exposure are used, the consequences of measurement error vary with classification rules. The effects of alternative measurement strategies on exposure classification were evaluated using NO2 diffusion sampler measurements from 653 residences with gas cooking ranges. A time-series of consecutive 2-week integrated measurements was obtained for each home. During the winter season, the standard deviation was 26% of the mean. The probability of misclassification, a function of the mean and the standard deviation per home, was examined for three concentration classes (<25, 25–50, ⩾50 ppb). The average probability of misclassification was 10% for three 2-week integrated measurements across the winter and decreased to under 5% for continuous sampling (i.e. 13 consecutive 2-week samples). The sensitivity and predictive value were improved by increasing the number of samples obtained. The misclassification is determined by the number of concentration classes and by the relationship of class boundaries to the distribution of true means. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
