Characterization of a High PM2.5 Exposure Group in Seoul Using the Korea Simulation Exposure Model for PM2.5 (KoSEM-PM) Based on Time–Activity Patterns and Microenvironmental Measurements
Abstract
:1. Introduction
2. Materials and Methods
2.1. Microenvironmental Concentration Measurements
2.2. Time–Activity Patterns
2.3. Kosem-PM
2.3.1. Estimation of Personal Exposure Levels of the 8072 Residents of Seoul
2.3.2. Simulation of Population Exposure to PM2.5
2.4. Statistical Analysis
3. Results
3.1. Microenvironmental PM2.5 Concentrations
3.2. Time–Activity Patterns of the 8072 Residents of Seoul
3.3. Personal Exposure Levels of the 8072 Residents of Seoul
3.4. Simulated Population Exposure to PM2.5
4. Discussion
4.1. Microenvironmental PM2.5 Concentrations
4.2. Time-Activity Pattens of the Surveyed Residents
4.3. Personal PM2.5 Levels of Surveyed Residents
4.4. Simulated Population Exposure
4.5. Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Variables | Low Exposure Group n = 7668 | High Exposure Group n = 404 | p-Value |
---|---|---|---|
Day of the week—no. (%) | 0.003 1 | ||
Weekdays | 4630 (60.4) | 219 (54.2) | |
Saturdays | 1497 (19.5) | 108 (26.7) | |
Sundays | 1541 (20.1) | 77 (19.1) | |
Sex—no. (%) | <0.001 1 | ||
Male | 3563 (46.5) | 223 (57.7) | |
Female | 4105 (53.5) | 171 (42.3) | |
Age, years—median (range) | 36 (10–93) | 35 (11–87) | 0.655 |
Marriage status—no. (%) | 0.473 | ||
Married | 4259 (55.5) | 217 (53.7) | |
Unmarried | 3409 (44.5) | 187 (46.3) | |
Education—no. (%) | <0.001 1 | ||
Middle school and below | 2156 (28.1) | 76 (18.8) | |
College and below | 2778 (36.2) | 166 (41.1) | |
University and above | 2734 (35.7) | 162 (40.1) | |
Industry—no. (%) | <0.001 1 | ||
Primary and secondary industry | 741 (18.0) | 25 (8.1) | |
Tertiary industry | 2227 (54.1) | 205 (66.3) | |
Other | 1151(27.9) | 79 (25.6) | |
Job—no. (%) | <0.001 1 | ||
Office worker | 1933 (46.9) | 91 (29.4) | |
Non-office worker | 2186 (53.1) | 218 (70.6) | |
Working hours, hour per week—median (range) | 18 (0–120) | 49 (0–105) | <0.001 1 |
Monthly income—no. (%) | 0.100 | ||
<$2000 | 6534 (85.2) | 332 (82.2) | |
≥$2000 | 1134 (14.8) | 72 (17.8) | |
House size, m2—median (range) | 66.1 (9.9–337.2) | 59.5 (16.5–198.3) | 0.025 1 |
Own house—no. (%) | 0.002 1 | ||
Yes | 4025 (52.5) | 179 (44.3) | |
No | 3643 (47.5) | 225 (55.7) | |
Own car—no. (%) | 0.595 | ||
Yes | 4900 (63.9) | 46 (11.4) | |
No | 2768 (36.1) | 358 (88.6) |
Variables | Coefficient | Standard Error | p-Value 1 | OR 3 (95% CI) |
---|---|---|---|---|
Day of the week | 0.044 2 | |||
(Weekdays) | ||||
Saturdays | 0.356 | 0.147 | 1.428 (1.701–1.903) | |
Sundays | −0.017 | 0.162 | 0.983 (0.715–1.350) | |
Sex | 0.240 | |||
(Male) | ||||
Female | −0.156 | 0.133 | 0.856 (0.660–1.110) | |
Age | −0.019 | 0.006 | 0.002 2 | 0.981 (0.969–0.993) |
Education | 0.173 | |||
(Middle school and below) | ||||
College and below | −0.148 | 0.190 | 0.863 (0.595–1.251) | |
University and above | 0.139 | 0.232 | 1.149 (0.729–1.810) | |
Industry | <0.001 2 | |||
(Primary and secondary industry) | ||||
Tertiary industry | 1.063 | 0.220 | 2.894 (1.880–4.454) | |
Other | 0.843 | 0.239 | 2.324 (1.454–3.716) | |
Job | <0.001 2 | |||
(Office worker) | ||||
Non-office worker | 0.797 | 0.161 | 2.220 (1.618–3.044) | |
Working hours | 0.028 | 0.003 | <0.001 2 | 1.029 (1.022–1.036) |
Monthly income | 0.199 | |||
(<$2000) | ||||
≥$2000 | −0.202 | 0.159 | 0.817 (0.599–1.115) | |
House size | 0.001 | 0.003 | 0.765 | 1.001 (0.996–1.006) |
Own house | 0.425 | |||
(Yes) | ||||
No | 0.108 | 0.136 | 1.114 (0.854–1.454) |
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Hwang, Y.; An, J.; Lee, K. Characterization of a High PM2.5 Exposure Group in Seoul Using the Korea Simulation Exposure Model for PM2.5 (KoSEM-PM) Based on Time–Activity Patterns and Microenvironmental Measurements. Int. J. Environ. Res. Public Health 2018, 15, 2808. https://doi.org/10.3390/ijerph15122808
Hwang Y, An J, Lee K. Characterization of a High PM2.5 Exposure Group in Seoul Using the Korea Simulation Exposure Model for PM2.5 (KoSEM-PM) Based on Time–Activity Patterns and Microenvironmental Measurements. International Journal of Environmental Research and Public Health. 2018; 15(12):2808. https://doi.org/10.3390/ijerph15122808
Chicago/Turabian StyleHwang, Yunhyung, Jaehoon An, and Kiyoung Lee. 2018. "Characterization of a High PM2.5 Exposure Group in Seoul Using the Korea Simulation Exposure Model for PM2.5 (KoSEM-PM) Based on Time–Activity Patterns and Microenvironmental Measurements" International Journal of Environmental Research and Public Health 15, no. 12: 2808. https://doi.org/10.3390/ijerph15122808