The risk of indoor air pollutants accumulation in the five housing types in Ho Chi Minh City (Vietnam) Thuy T. T. Tran 1,5 *, Diem T. K. Nguyen 1,5, Thanh Ng. Tran 2, Phong D. H. Dinh 2, Tan V. Le 1, Olivier Michel 3, Catherine Bouland 4, Jean-Marie Hauglustaine 5 1 Industrial University of Ho Chi Minh City, Vietnam 2 Pham Ngoc Thach University of Medicine, Vietnam 3 CHU-Brugmann, Université Libre de Bruxelles, Belgium 4 School of Public Health, Université Libre de Bruxelles, Belgium 5 Department of Sciences and Management of Environment, University of Liège, Belgium *Corresponding author: tranthithuthuy@hui.edu.vn SUMMARY This study identified the differences among 5 typical dwelling types in Ho Chi Minh City (HCMC) about the risk of indoor air pollutants accumulation (as explained in another paper [1]). Based on data collected from questionnaire, diary of occupants living in 100 houses, we organized a decision scheme evaluating the Risk of Indoor Air Pollutants accumulation for the Kitchen () ranging from high to low. The risk in the living space depends on the connection between the kitchen and the living room. So we continue to evaluate the risk for the living family space () also ranging from high to low. Among the five house types, rental house presents the highest. Concentrations of carbon dioxide (CO2), carbon monoxide (CO), fine particles (PM2.5) and humidity level during cooking confirm the difference between low and high groups in these houses. PRACTICAL IMPLICATIONS The study provided a database and summary information about housing characterisctics and pollutants to help further the understanding of the role of ventilation and human behaviour on indoor air quality and health symptoms. KEYWORDS Kitchen ventilation, living family space, cooking, relative humidity, CO, CO2, PM2.5 1 INTRODUCTION HCMC is one of the major economic, cultural centers of Vietnam has population was doubled shortly in just a 10-year term and this has created the development of many housing types providing for citizens with different lifestyles. Recently, increasing the airtightness of houses has become a significant issue. Therefore housings are made more airtight, internal pollution sources can be accumulated, especially in kitchens due to cooking activities. In fact, five typical housing types in HCMC usually were designed where family space integrated with cooking space or living room is closely linked to kitchen. The living room in which all family members and friends often gather to eat, drink, watching TV and socialize is the most important
space because occupants may experience adverse health effects due to the increased exposure everyday for a long time. A previous study by Willers [2] gives evidence that we can depend on characteristics of the kitchen to know the risk of accumulation of combustion products of the house. We used this information and organized a similar model based on kitchen s physical characteristics, ventilation features, and information on people activities to determine the risk of accumulation pollutants in the kitchen. After that depended on connection between living room and kitchen, we continued identifying the risk of accumulation pollutants in the family living area of the house. We compared the in a range of housing types and determine if the relationship between housing type and current persists. 2 MATERIALS/METHODS Housings have been divided into five categories, namely: tube house, apartment, rental house, slum house and rural house. All housing units includes five types for monitoring in each stratum; they have been chosen proportionately in various districts in HCMC, each group of houses share similar typology characteristics. The questionnaires, diaries of activities were completed in 100 homes but the measurements were done in 97 houses because 3 houses were omitted from the study due to accidents of devices or personal problems of occupants. The data of indoor environment has been collected for a period of 36 months. The indoor temperature and relative humidity levels were recorded automatically by using Testo 174H data loggers at a height of 1.1 m from floor level in the living room and in the kitchen of each home. All dataloggers were programmed to collect data at five minute intervals. Data collection continued for periods 21 days at each site. Outdoor relative humidity was obtained from the National Meteorological Station in HCMC. CO2, CO, PM2.5 concentrations were measured using 3M TM EVM series environmental monitor at one minute interval. The information from the survey, questionnaire and diary were used to define the following set of factors: the exhaust ventilation, kitchen type, air supply and extra ventilation (Table 1). The first scheme (Fig.1) leads to categories of houses with distinct levels of accumulation of cooking pollutants in the kitchen high or low. After making descriptions of the kitchen situation, the second scheme (Fig.2) for the was organized and validated by measurements of CO, CO2, PM2.5 and humidity in the living rooms which pollutants produced from fuel combustion in the cooking area. Data were expressed as mean and standard deviation. Because the data had a non-normal distribution, nonparametric tests were used to compare mean levels of CO2, CO, PM2.5 (during cooking) of homes with low with homes with high (Wilcoxon test). The significance level of all statistical analyses was 0.05.
Cooking Often Used During Cooking Door/Window to Outside Opened During Cooking Exhaust Ventilation Kitchen Type Fully Connected Partially Connected or Separated Door/Window to Outside Open During Cooking Extra Ventilation Fig. 1. Scheme according to the categories of homes with distinct levels of risk of accumulation of cooking pollutants in kitchen ( model). Connection Between Living Room And Kitchen Fully Connected Seperated Partially Connected Air Supply Insuffient Air Supply Suffient Fig. 2. Scheme according to connection between living room and kitchen leads to categories of homes with distinct levels of risks of accumulation of cooking pollutants in living room ( model).
Table 1. Variables entered into the schemes Set of variables Exhaust ventilation Often using the exhaust ventilation Category : the extractors (hood stove or exhaust fans) which have outlet to outside are present. Outside is defined as the part of space not obstructed by walls or roofs. : the extractors are absent : the exhaust ventilation is in high effectiveness, extractors often/always used during cooking : the exhaust ventilation is in low effectiveness, extractors never/seldom used during cooking Kitchen type Fully connected: connected fully to living room space without partition Partially connected: connected to living room space with partition Separated: segregated by walls and door with living room space or open air kitchen outside the house Air supply Suffient: presence of door/window in the kitchen which have outlet to outside. Insuffient: absence of door/window in the kitchen directly to outside Often using the air supply : the air supply is adequate, door/window in the kitchen that can be opened and regularly opened during cooking : the air supply is inadequate, door/window are normally never opened during cooking. Extra ventilation : presence of vent through wall or ceiling or presence of mechanical exhaust ventilation system : absence or not in using of something under yes during cooking 3 RESULTS 3.1. Household characteristics Pertinent household characteristics are included in Table. 1 Table 2. Summary of houses characteristics (n=100) House type Apartment (n=) Rental house (n=) Rural house (n=) Slum house (n=) Tube house (n=) Total (n=100) Connection between living room and kitchen Fully connected Partially connected House s age (years) Family living area (m 2 ) Kitchen area (m 2 ) Number of occupants Separated mean SD mean SD mean SD mean SD 7 13 0 9.7 13.7 18.9 10.9 6.7 2.6 3.8 1.5 17 0 3 9.1 4.4 10.5 4.1 3.0 2.4 2.8 1 1 9 10 16.6 15.9 25.4 6.0 15.8 7.5 4.1 1.4 7 7 6 27 13 13.3 4.5 6.0 5.3 4.6 2.7 4 14 2 17.6 14.9.4 12.6 11.7 5.9 5.1 3.1 36 (36%) 43 (43%) 21 (21%) 16.0 14.4 17.7 9.7 8.6 6.8 4 2.2 Looking at the housing characteristics presented in Table. 2, the respondents were living in 10.5 to 25 m 2 living spaces with an average kitchen area of 8.6 m 2. Most of the respondents had been living in the houses built more than 10 years, and nearly 80% of respondents were living in houses whose kitchens were fully or partially connected with other living spaces.
3.2 Risk of pollutants accumulation in the living family space According to the stratification scheme shown in Fig.1 and Fig.2 the binary parameters and were constructed and the, and values low and high in Tables 2 3. Table. 3. The values low and high Apartment Rental house Rural house Slum house Tube house Row Total high (a) 10 (b) 0.244 (c) 0.500 12 0.293 0.600 5 0.122 0.250 5 0.122 0.250 9 0.2 0.450 41 0.410 low 10 0.169 0.500 8 0.136 0.400 15 0.254 0.750 15 0.254 0.750 11 0.186 0.550 59 0.590 (d) 100 Column Total (e) 0.0 0.0 0.0 0.0 0.0 (a)-number of houses in groups; (b)- percentage of row; (c)- percentage of column; (d)-total number of column; (e)=(d)/100. Table. 4. The values low and high Apartment Rental house Rural house Slum house Tube house Row Total high 5 0.192 0.250 12 0.462 0.600 0 0.000 0.000 4 0.154 0.0 5 0.192 0.250 low Column Total 15 0.3 0.750 0.0 8 0.108 0.400 0.0 0.270 1.000 0.0 16 0.216 0.800 0.0 15 0.3 0.750 0.0 26 0.260 74 0.740 We found 41% of the total houses in high but just found 26% of the total houses in high. Among the five house types, rental house presents the highest risk (46.2%), followed by apartment and tube house (19.2%), slum house (15.4%), and the lowest risk in rural house (0%). 3.3 Pollutant concentrations in the living family space CO2, CO, PM2.5 and humidity may be generated in a short period of time during cooking in the kitchen and air exchange from room to room can bring such pollutants to the living space. The measurement of pollutant concentrations in the living rooms which make certain the difference between high and low groups. Besides of that, indoor levels of relative humidity were measured in the living rooms all the sampling houses using natural ventilation during cooking time. The linear regression analysis between indoor and outdoor humidity describes some relationships. The analysis results are given in Table. 5 and Fig. 3. 100
Table. 5. Difference in average levels of CO2, CO and PM2.5 during cooking N Mean (SD) P-value CO 2 by group high group low 8,810 14,960 537.75 ppm (±108.7) 440.82 ppm (±65.6) < 0.001 CO by group high group low 8,810 14,960 5.30 ppm (±3.45) 1.73 ppm (±2.09) < 0.001 PM 2.5 by group high group low 8,810 14,960 0.044mg/m 3 (±0.19) 0.057 mg/m 3 (±0.23) < 0.001 We found a significant difference in CO2 during cooking (P < 0.001) for low vs. high respectively. The mean levels of CO2 were generally below the WHO standard, but in homes with a high, higher concentrations of CO2 (mean = 537.75 ppm) were reached than in homes with a low (mean = 440.82 ppm). CO concentration between homes with a low and homes with a high was also different (P < 0.001). The mean levels of CO were generally below compared to the standards established by WHO, but in homes with a high, significantly higher concentrations of CO (mean = 5.30 ppm) were reached than in homes with a low (mean = 1.73 ppm). There was significant difference in PM2.5 (P < 0.001) for low vs. higher respectively. The mean levels of PM2.5 were both above the standard, but in homes with a high, lower concentrations of PM2.5 (mean = 0.044 mg/m 3 ) compared with a low (mean = 0.057 mg/m 3 ). Fig. 3. Correlations between indoor relative humidity in the living rooms and outdoor relative humidity for each of housing types during cooking time. The analysis results demonstrated that the statistical correlations between indoor and outdoor relative humidity during cooking in the houses with high was found low with the correlation coefficient R-squared less than 0.4 especially fell 0.12 in the rental houses. It can be inferred that the houses in high group are comparatively well airtight, which makes indoor
water vapour from cooking difficult to be exhausted. On the other hand, the slope of the straight line and the correlation coefficient R-squared around 0.7 in low groups tells in which degree indoor relative humidity varies as regards the outdoor humidity. 4 DISCUSSION We found 26% of the total houses in high lower than 41% in high due to air supply sufficient in the living rooms. There was a significant difference in the statistical correlations between indoor and outdoor relative humidity for high vs. low respectively. The houses with high are airtight which make indoor water vapour difficult to be exhausted while the correlations were stronger in the houses with low due to natural ventilation or opening windows are more frequently applied in most these house types, which make indoor humidity changes by the fluctuating outdoor humidity. This is also supported by the fact that a significant difference between the low and high groups was found for the mean accumulation CO2 as well as CO in the family living space during cooking, which is evidence of the values high and low according to our stratification scheme. Concerning PM2.5 concentration, there was also a meaning difference between the high and low groups but high concentration with the low and vs. That means the source of fine particles not relating to cooking activities or ventilation condition, may be from traffic jam outside. As next step, we need more data about PM2.5 concentration recorded indoor and outdoor to support to the model. 5 CONCLUSIONS There were significant differences for the high and low risk of accumulation of indoor air pollutants among five housing types. For CO2 as well as for CO and humidity, a noticeable difference between the high and low RIAP.L groups has been found for the mean concentration in the family living space during cooking. These facts are considered to be important evidence of the RIAP.L model able to be accepted for our study population. Rental house is the house type with the highest RIAP.L, followed by apartment and tube house, slum house and rural house, respectively. ACKNOWLEDGEMENT This study, involving Belgian (ULB, ULg) and Vietnamese Universities (IUH, UPNT), got the funding from the ARES (Académie de Recherche et Enseignement Supérieur for Wallonia and Brussels) organization. We would also like to thank all our colleagues at the Industrial University of Ho Chi Minh City for their help in collecting the data of the questionnaire survey. 6 REFERENCES [1] Thuy T. T. Tran, et al (16). Typology of houses and ventilation characteristics: a case study in Ho Chi Minh City (Vietnam), paper submitted to the Indoor air 16 International Conference to be held in Ghent (Belgium), 3-8 July, 16. [2] Willers, S. M., et al. (06). "Gas cooking, kitchen ventilation, and exposure to combustion products." Indoor Air 16(1): 65-73. [3] Willers, S. M., et al. (06). "Gas cooking, kitchen ventilation, and asthma, allergic symptoms and sensitization in young children the PIAMA study." Allergy 61(5): 563-568.
[4] Li, Y.-C., et al. (15). "Characteristics of PM2.5 emitted from different cooking activities in China." Atmospheric Research 166: 83-91. [5] Mullen, N. A., et al. (15). "Results of the California Healthy Homes Indoor Air Quality Study of 11 13: impact of natural gas appliances on air pollutant concentrations." Indoor Air: n/a-n/a. [6] Persily, A. (15). "Challenges in developing ventilation and indoor air quality standards: The story of ASHRAE Standard 62." Building and Environment 91: 61-69. [7] Pokhrel, A. K., et al. (15). "PM2.5 in household kitchens of Bhaktapur, Nepal, using four different cooking fuels." Atmospheric Environment 113: 159-168. [8] Kim, C., et al. (15). "Home kitchen ventilation, cooking fuels, and lung cancer risk in a prospective cohort of never smoking women in Shanghai, China." International Journal of Cancer 136(3): 632-638. [9] CPHSC, 10. The 09 Vietnam population and housing census: completed results. Ha i, Statistical Publishing House.