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Article

Probabilistic Prediction Models and Influence Factors of Indoor Formaldehyde and VOC Levels in Newly Renovated Houses

by
Wu-Ting Lin
1,2,
Ru-Yin Tsai
3,
Hsiu-Ling Chen
4,
Yaw-Shyan Tsay
3,† and
Ching-Chang Lee
1,5,*,†
1
Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
2
Architecture and Building Research Institute, Ministry of the Interior, New Taipei 704, Taiwan
3
Department of Architecture, National Cheng Kung University, Tainan 704, Taiwan
4
Department of Food Safety/Hygiene and Risk Management, Medical College, National Cheng Kung University, Tainan 704, Taiwan
5
Research Center of Environmental Trace Toxic Substances, National Cheng Kung University, Tainan 704, Taiwan
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Atmosphere 2022, 13(5), 675; https://doi.org/10.3390/atmos13050675
Submission received: 25 March 2022 / Revised: 17 April 2022 / Accepted: 21 April 2022 / Published: 23 April 2022
(This article belongs to the Special Issue Air Quality and Environmental Health: New Findings in COVID-19 Era)
Browse Figure
Review Reports Versions Notes

Abstract

:
Rapid urbanization has promoted house renovations and refurbishment in urban and rural cities. Indoor pollutants emitted through renovations and refurbishment processes have raised public concerns owing to their adverse effects on human health. In the present study, the sources of formaldehyde and specific volatile organic compounds (VOCs) are used to model the health effects associated with exposure to formaldehyde and specific VOCs and the loading factors of building materials for newly renovated homes. The present study is carried out to identify the sources of formaldehyde and specific VOCs in newly renovated houses and develop probabilistic prediction models of the health effects to explore the health risks of residents and the potential contributions of multilayer wood materials responsible for indoor pollutants. In living rooms and bedrooms, the average concentrations of formaldehyde and TVOCs in closed window conditions were higher than those in opened window conditions. Multi-layer wooden structures were a significant predictor of indoor VOC concentrations in houses. The 95 percentile values of Monte Carlo simulations (MCS P95) of the hazard index and cancer risk were lower and slightly higher than the acceptable level, respectively. Prediction models for the concentrations of formaldehyde and selected VOCs in newly renovated houses were first established using probabilistic and sensitive approaches. The multi-layer wood materials, including the wooden floor, cold paint multi-layer wooden materials, and multi-layer materials for system furniture, were responsible for the contribution of these levels of formaldehyde and selected VOCs in the newly renovated houses. Our results provide a strategy for eliminating indoor pollutants emitted from construction and building/furnishing materials.

1. Introduction

House renovations and refurbishments are highly associated with rapid urbanization in Taiwan. The adverse effects of formaldehyde and airborne volatile organic compounds (VOCs), emitted during the processes of renovation and refurbishment, on human health have raised public concerns [1,2,3]; moreover, 90% of our lifetime is spent indoors [4]. Among VOCs, benzene, ethylbenzene, toluene, styrene, and xylenes (BTX) have been identified as major indoor air pollutants and have been included in the priority list of indoor compounds, including acetaldehyde, acrolein, 1,3-butadiene, 1,4-dichlorobenzene, formaldehyde, naphthalene, nitrogen dioxide, 2-(2-ethoxyethoxy) ethanol, acetic acid, 1,2-propanediol, PM2.5, and new infectious agents of COVID-19 [2,5,6,7,8,9,10,11,12,13,14]. High abundant VOCs have been consistently recognized in newly occupied building than in already occupied houses or buildings [15,16,17,18,19]. The occurrence and concentrations of known VOCs vary among household rooms (i.e., living rooms or bedrooms) in different countries or cities. Formaldehyde [20] and benzene [21] have been identified to be carcinogenic to humans (Group 1) by the International Agency for Research on Cancer (IARC). Exposure to indoor BTX is of concern because BTX is a potent sensory irritant of the eyes, skin, mucous membranes, and respiratory tract, and is classified as a probable human carcinogen [22]. A limited number of studies has investigated the personal exposure to VOCs experienced by workers and residents in newly renovated rooms. Indoor air quality (IAQ) in newly renovated rooms is a serious public health issue that must be addressed.
The Taiwan Environmental Protection Authority (EPA) has adopted IAQ regulations as statutory regulations for IAQ management. In Taiwan, scientists have shown concern about the impact of IAQ on human health since the early 2000s, thus leading to the legislation of the Indoor Air Quality Management Act (IAQMA) on 23 November 2011 to protect public health. The IAQ standards for CO2, CO, formaldehyde, TVOC, bacteria, fungi, PM2.5 and PM10, and ozone are included in Article 3 of the Act. Consequently, the Ministry of the Interior (MOI) has regularly executed the Green Building Material (GBM) labeling system since 2004 under the authorization of the Building Act [23]. Composite panel materials for building and construction processes have been modified to achieve a high quality and meet the requirements for the airtightness of buildings [24,25]. These modern materials and products have been considered the primary sources of VOCs in indoor environments [2,10,12,15,16,17,18,19,25]. The main emission source of formaldehyde is urea–formaldehyde resins [26]. Wood-based materials may be more prone to becoming major sources of indoor air pollutants, such as formaldehyde, toluene, styrene, ethylbenzene, and xylene [27,28,29,30]. The area where materials are used is correlated with the concentration of formaldehyde and TVOCs, and wooden furniture showed the strongest correlation [31]. Wu et al. revealed that the load factors of traditional carpentry work have a positive correlation with HCHO and TVOC concentrations [32]. However, to date, few studies have investigated the consequences of formaldehyde and VOC emission and their correlations to the load factors of decoration materials in indoor environments of newly renovated houses [33,34,35,36,37]. In addition, limited studies construct health risk assessment using the practical application of load factors of decoration materials in newly renovated homes.
Therefore, a close inspection of previous investigations showed that the risk modelling of the health effects associated with the exposure to formaldehyde and specific VOCs and the load factors of building materials for newly renovated homes in Taiwan have rarely been evaluated. In this study, to evaluate the daily inhalation exposures and health risks of Taiwanese residents, a field survey of formaldehyde and selected VOC concentrations in 11 newly renovated houses and buildings is carried out to characterize the sources of multi-layer wood materials responsible for the contribution levels of formaldehyde and specific VOCs, using probabilistic and sensitive approaches. This study focuses on the seven most abundant VOCs, namely, formaldehyde, benzene, toluene, ethylbenzene, m/p/o-xylenes, and styrene. The features of our study could help designers to predict the concentrations of formaldehyde and specific VOCs, to control the rate factor of building material usage before starting the decoration works.

2. Materials and Methods

2.1. Field Environmental Sampling Locations

In this study, investigations were carried out between April and September 2018 in 11 new residences in Tainan and Kaohsiung, located in southern Taiwan. The selected residents were four houses and seven apartments that were newly renovated. Indoor air samples for formaldehyde (n = 20 and 20) and specific VOCs (n = 16 and 20) from the living room and bedroom areas were collected under opened and closed window conditions after decoration had been completed. The temporal levels of TVOCs, formaldehyde, and environmental conditions (temperature and humidity) in each room were recorded. Loading factors (the area of individual decoration material divided by total volume of each renovated room, presented as m2/m3) were calculated for six decoration materials, such as the cold paint multi-layer wooden material (CPM) composition of block boards with topcoating and undercoating, laminate hard plastic multi-layer materials (LHP), veneer multi-layer wooden material (VM) composition of veneer block boards, multi-layer materials for system furniture (SF) composition of particle boards, medium density fiberboard, polyvinyl chloride foam board, cement paint (CP), and wooden floor (WF) in each room.

2.2. Sampling Procedures and Chemical Analysis

Air samplers were centrally placed 1.3 m above the floor and 0.5 m from the walls, windows, or doors. The sampling duration was 3 h under closed and opened window conditions on the same day. Indoor CO2 concentration, relative humidity (RH), and temperature were recorded at 60 s intervals over the entire day with portable PMD01.

2.2.1. Formaldehyde

2,4-dinitrophenylhydrazine (DNPH) tubes were used for indoor air samples. DNPH tubes with a sampling rate of 100 mL/min were collected for 3 h for formaldehyde using an air-sampling pump (SKC Pocket Pump). Formaldehyde was collected using a sorbent tube (ORBOTM 555 LpDNPH) and analyzed using high-performance liquid chromatography (HPLC) with a C-18 column. The DNPH-carbonyl compounds were detected at 360 nm using a UV-VIS detector (Shimadzu, Japan). At the same time, the formaldehyde levels in the indoor environment were measured real-time with a portable PMD01 (model 8554, TSI Inc., Shoreview, MN, USA), and the QA/QC system of analytical results was performed according to ISO Guide 16000-3.

2.2.2. Volatile Organic Compounds

Twelve target VOCs were selected according to the Taiwan IAQ standard, and the chemicals included benzene, toluene, ethyl benzene, o-xylene, p-xylene, m-xylene, carbon tetrachloride, chloroform, styrene, trichloroethylene, 1,2-dichlorobenzene, 1,4-dichlorobenzene, dichloromethane, and tetrachloroethylene. The VOCs were collected for 3 h at a sampling rate of 100 mL/min using an air sampling pump equipped with a CarboTrap 349 absorption tube. A Dry-cal (MesaLabs, Defender) was used to calibrate the pump airflow before and after each sampling process. The sampled tubes were stored at 4 °C in a refrigerator until they were analyzed using gas chromatography-mass spectrometry (GC/MS). An DB-WAX capillary column (60 m, 0.25 mm, 0.25 µm) was used for GC. The initial oven temperature was maintained at 35 °C for 2 min, increased at 5 °C/min to 190 °C and kept for 1 mm, then increased at 10 °C/min to 230 °C, and maintained for 5 min. The compounds of interest were identified and quantified by their retention time and mass spectra of calibration VOC standards (COMPRESSED GAS, N.O.S UN 1956, 10 ppm, procured from Linde) under specified chromatographic conditions. A GC-MS system (Agilent GC-6890N, MSD-5977B) with an auto-thermal desorption (ATD-350, PerkinElmer International Corp., Waltham, MA, USA) was used to obtain the VOC concentrations, and the QA/QC system of analytical results was performed according to ISO Guide 16000-6.

2.3. Exposure and Health Risk Assessment

Daily doses (EDi in µg/kg/day), non-cancer risks of hazard quotient (HQ) and hazard index (HI), and cancer risk of formaldehyde and seven VOCs through the inhalation route of the selected populations were assessed and expressed using the following equation [38]:
E D i = C A × I R × A F B W × E T × E F A T
where CA is the concentration of air pollutants (μg/m3); IR is the inhalation rate (m3/day); AF is the absorption factor via inhalation (100% assumed); ET is the exposure time (h/d); ED is the duration of exposure (years); BW is the body weight (kg); EF is the exposure frequency (days/year); and AT is the average lifetime (years). The values and sources of the corresponding variables are presented in Table S1 [39,40,41].
For non-carcinogenic and carcinogenic risk assessment [42], the individual hazard quotient (HQi) was defined as the ratio of the exposure concentration received (EDi) to the reference dose (RfD) (mg/kg/day). The toxicity parameters of RfD and slope factor (SF) for formaldehyde and specific VOCs are listed in Table S2. HI can be calculated as the sum of the individual HQs of formaldehyde and specific VOCs based on their critical effects on the liver, urine, and development. An HQ or HI < 1 indicates that the daily exposure dose might not cause adverse health effects and vice versa. CRinhalation is the estimated inhalation cancer risk from formaldehyde and VOCs. SF is the inhalation slope factor (mg/kg/day) for formaldehyde and specific VOCs from the US EPA’s integrated risk information system (IRIS). Benzene, ethylbenzene, and formaldehyde were selected for cancer risk calculation in this study owing to the availability of SF, high frequency of occurrence, and carcinogenicity.

2.4. Uncertainty and Sensitivity Analysis

Exposures and risks were estimated using Monte Carlo simulations. Monte Carlo simulations and sensitivity analyses were conducted using @RISK Decision Tools Suite (Version 8.0, Palisade Corporation, Ithaca, NY, USA). The lognormal and normal distributions were optimized to describe the input data for the concentrations of VOCs and formaldehyde, inhalation rate (IR), exposure frequency (EF), and body weight (BW). An iteration size of 100,000 was randomly obtained to calculate the 95% confidence interval (MCS P95) of the inhalation exposures and health risks for each gender and age-specified population. A repeated sampling process from the probability distributions was used to derive the likelihood of the model outcomes. The prediction models for formaldehyde and specific VOC concentrations were developed using the characteristics of newly renovated houses and renovation materials. A sensitivity analysis was performed to illustrate and rank the variations in input variables (the concentrations of formaldehyde or specific VOCs, and the renovation materials) based on their relative contributions to model output variability and uncertainty [38].

2.5. Statistical Analyses

The characteristics of newly renovated houses and apartments, loading factor of construct materials, environmental conditions, formaldehyde, and 12 VOC concentrations were analyzed for descriptive statistics. Five of the twelve VOCs with detection frequencies below the detection limits were excluded. Multiple linear regressions (MLR) were used to select variables to establish prediction models for indoor formaldehyde and VOC concentrations. Prediction model performance was assessed using the coefficient of determination (R2) and root-mean-square error. In the MLR model, the input variables should not be correlated with each other (multi-collinearity). All predictor variables were force entered into the models for predicting formaldehyde and specific VOCs and evaluated simultaneously due to those nonmodifiable variables, including healthy green building materials, temperature control, and open window would imply the control strategies to reduce the potential health risks of formaldehyde and specific VOCs while renovating the newly house. Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS, Version 23, IBM Corp. Chicago, IL, USA).

3. Results

3.1. Characteristics of the Newly Renovated Houses

In Table 1, the mean area of 10 living rooms and 12 bedrooms were 33.7 and 22.0 m2, respectively. The indoor conditions with opened and closed windows, regarding CO2 levels, temperature, and relative humidity, were 561 and 509 ppm, 29.1 and 28.7 °C, and 71.9 and 74.4%, respectively. The loading rates of the CPM, LHP, VM, SF, CP, and WF were 0.05, 0.08, 0.10, 0.07, 1.00, and 0.11, respectively. The loading factors of six decoration materials were ranged from 0.05 to 1.00 m2/m3. The six decoration materials used in the living room and bedroom were in this order: CP > WF > LHP > VM > SF > CPM and CP > WF > VM > CPM > SF > LHP, respectively.

3.2. Indoor Formaldehyde and VOC comparison between Opened and Closed Window Conditions

In the opened window condition (Table 2), the average concentrations of formaldehyde and TVOCs in living rooms and bedrooms were 40.9 µg/m3 and 136.7 µg/m3 and 33.3 µg/m3 and 88.1 µg/m3, respectively. In the closed window condition, the average concentrations of formaldehyde and TVOCs in living rooms and bedrooms were 144.6 µg/m3 and 289.1 µg/m3 and 141.2 µg/m3 and 220.6 µg/m3, respectively. High levels of formaldehyde and specific VOCs in newly renovated buildings were found in living rooms and bedrooms in the closed window condition. In both conditions, the dominant VOC compound found was toluene, followed by styrene, in both living rooms and bedrooms.

3.3. Indoor Prediction Model for Formaldehyde and VOCs

The multiple linear regression model (MRL) was performed to estimate the coefficients of the selected predictors (room size, temperature, humidity, open rate of windows, and material load factors) on indoor concentrations of formaldehyde and specific VOCs (Table 3). We fitted the data of formaldehyde and specific VOC concentrations measured in an actual room (newly decorated within 1 month). The corresponding R2 of MRL (all p-value < 0.05) for formaldehyde, benzene, toluene, ethyl benzene, m-xylene, p-xylene, o-xylene, and styrene were 64.9%, 61.4%, 42.9%, 48.0%, 57.8%, 41.2%, 40.7%, and 50.1%, respectively. The significant predictors of the multiple linear regression models for formaldehyde, m-Xylene, p-Xylene, and o-Xylene were WF and open rate of window; for ethyl benzene and styrene were VM, WF, and open rate of window; for benzene were room size, indoor temperature, open rate of window, and CP; for toluene were indoor temperature, open rate of window, WF, CPM, and LHP. Wood panels/vinyl floor coverings were the largest indoor pollutant sources, followed by flooring, wall coverings, adhesives, and paints. Wood panels/vinyl floor coverings contributed nearly three times more to the indoor VOC concentrations than the paint [43]. The equations of the indoor prediction models for the concentrations of formaldehyde and specific VOCs were established based on multiple linear regressions (Table S3). The predicted concentrations of formaldehyde and specific VOCs were used to calculate inhalation exposure estimates and health risks based on the probabilistic approach.

3.4. Health Risks and Uncertainty and Sensitivity Analysis

Table S4 presents the average exposure dose calculated using the equation of chronic daily inhalation exposure to indoor formaldehyde and individual VOCs in the selected age groups (adult male 19–65 years, adult female 19–65 years, children male 6–12 years, children female 6–12 years). The average estimates of the chronic daily inhalation exposure to formaldehyde in adults and children were 3.16 × 10−6–4.48 × 10−2 mg/kg/day, and for specific VOCs in adults and children were 1.37 × 10−4–1.86 × 10−2 mg/kg/day. Possible uncertainties accompany a risk assessment, especially when only a single value is used to estimate the risk for the selected population. Therefore, the probabilistic distributions of the relevant parameters in the equation are given. The estimate by the Monte Carlo Simulation dose MCS P95 of formaldehyde in adults and children was 9.52 × 10−6−1.56 × 10−5 mg/kg/day and of benzene, toluene, ethyl benzene, m-xylene, p-xylene, o-xylene, and styrene in adults and children were 3.53 × 10−4−9.34 × 10−2 mg/kg/day.
The probabilistic distributions presented in Table 4 and Table S5 were obtained from Monte Carlo simulations for non-carcinogenic and carcinogenic risks. The individual HQs of formaldehyde and specific VOCs were 5.44 × 10−5–8.13 × 10−1 and 4.76 × 10−5–7.06 × 10−1 for male and female, respectively, and 7.70 × 10−5–3.55 × 10−1 and 4.76 × 10−5–3.61 × 10−1 for boy and girl, respectively. The MCS95 HIs of the incremental non-cancer risks for males and females living in newly renovated houses were 5.40 × 10−2 and 5.15 × 10−2 for hepatic effect, 0.815 and 0.707 for urinary effect, and 8.12 × 10−3 and 7.10 × 10−3 for developmental effect, respectively. For boys and girls, 9.18 × 10−2 and 9.12 × 10−2 were counted for hepatic effect, 1.148 and 1.170 for urinary effect, and 1.28 × 10−2 and 1.27 × 10−2 for developmental effect, respectively. The MCS95 values of HQs and HIs for adults and children were all below 1, indicating that there was no possible human health hazard while renovating the houses. For non-cancer risks of children and adults (Figure 1), the main contributors for predicting pollutant concentration were indoor temperature (0.50–42.2%), cold paint multi-layer wooden materials (0.30–18.6%), wooden floor (0.10–11.9%), open rate of window (0.20–11.1%), and room size (5.50–10.7%), except body weight (2.90–77.2%). The MCS95 of cancer risk for male adults and female adults living in newly renovated houses were 4.46 × 10−5 and 3.88 × 10−5; for boys and girls, they were 6.56 × 10−5 and 6.55 × 10−5. The MCS95 of cancer risk for adults and children were all observed to be above 10−6, indicating a potential human health hazard while renovating houses. For cancer risks in children and adults (Figure 1), the main contributors for predicting pollutant concentration were indoor temperature (19.6–34.9%), cold paint multi–layer wooden materials (11.6–18.6%), wooden floor (9.7–15.8%), and open rate of window (9.68–14.1%), except body weight (4.17–22.9%).

4. Discussion

Our results show that the indoor mean concentrations in the new residents in this study were in this order: toluene > styrene > benzene > p-xylene > o-xylene > ethylbenzene > m-xylene. High levels of formaldehyde and TOVCs (especially toluene) in the newly renovated buildings were detected in living rooms and bedrooms. The indoor air guideline values announced by Taiwan EPA for formaldehyde is 0.08 ppm (98.2 µg/m3). The World Health Organization (WHO) released IAQ guidelines for Europe [44] and the concentration value of TVOCs is 300 µg/m3. In this study, 5 (%) and 55 (%) of 20, which exceeded the guideline value of formaldehyde, were found in opened and closed window conditions and 5.5 (%) and 44.4 (%) of 18, which exceeded the guideline value of TVOCs, were found in opened and closed window conditions in the house. In Finland [16], eight new buildings with low-emitting materials had indoor air levels of formaldehyde and TVOCs at 19 µg/m3 and 780 µg/m3, respectively, and individual VOCs after six months recorded a mean concentration of less than 15 µg/m3. In Japan [45], the median of formaldehyde and TVOC concentrations of seven newly built houses were 8.2 and 550 µg/m3 in living rooms and 7.1 and 217 µg/m3 in bedrooms. In Korea [46], indoor concentrations of VOCs and formaldehyde were reported for 107 newly built apartments at a pre-occupancy stage, and formaldehyde was predominant in the indoor air samples. Toluene exhibited the highest emission concentration with a mean value of 184 µg/m3, followed by 1-propanol, 2-butanone, and m,p,o-xylene. In addition, formaldehyde concentrations of up to 400 µg/m3 were measured after completion, and the levels of formaldehyde and alpha-pinene were higher in the newly built wooden framed houses than in other houses in Japan [17]. Many studies have reported that benzene and toluene are widely used in a variety of industrial solvents and household products, such as paints, furniture wax, lubricants, glues, and nail polish removers [10,12,13,14,15,16,17,18,19].
Studies have completed cross-validation for prediction models [33,34,35,47,48]. In this study, we also conducted cross-validation, which revealed that R2 ranged from 40.7% to 64.9%. These correlations were significant, and the R2 values were moderately correlated, which indicates that the prediction model in this study could be used to estimate the indoor concentrations of formaldehyde and specific VOCs in the newly renovated buildings in Taiwan. Some studies developed indoor formaldehyde and specific VOC modeling according to complicated mechanisms (such as empirical, semi-empirical, adsorption, or mass transfer) and have been validated in the chamber [33,34,35]. In actual buildings, however, there will be many different dry building materials existing in the same room. When a variety of dry building materials release formaldehyde or VOCs at the same time, the indoor concentrations of formaldehyde or VOCs increase from individual building materials [35]. In agreement with Claire’s study [49], window opening/closing behavior significantly affected the error on the prediction model of indoor VOC concentration. However, one of the limitations in our models might be unable to account for the majority of the variance for ignoring some building characteristics or other human activities. Some studies determined prediction models for indoor air quality in households with machine learning approaches [33,35,48,50], but these studies reported temperature as the main predictor. The predictors in our study were similar to those in previous studies.
Based on the results of non-carcinogenic and carcinogenic risk assessments, the MCS95 values of HQs and HIs for urinary effect and carcinogenic risk in adults and children were all above the acceptable reference value, indicating a potential human health hazard while renovating houses. It can be concluded that, within a certain group of the population, the non-carcinogenic and carcinogenic risks in the newly renovated home were notably higher than in other indoor environments, since people spend most of their time in home. It is worth noting that the carcinogenic risk of formaldehyde, benzene, and ethyl benzene in households considered in this study is considerably higher than that evaluated in other countries. In United States, the cancer risks of formaldehyde and benzene in households were estimated for 1.30 × 10−5 and 2.90 × 10−5, respectively [51]. The incremental lifetime cancer risk of exposure to benzene in newly renovated homes in Guangzhou, China, was 6.8 × 10−6 [6]; of exposure to ethylbenze in newly renovated homes in Shanghai, China, was 1.04 × 10−6 [52]; of exposure to formaldehyde in households in Harbin, China, ranged from 9.75 × 10−4 to 1.41 × 10−3 [38]; and in Tehran, Iran, they ranged from 2.05 × 10−5 to 1.24 × 10−3 [53]. For the non-carcinogenic risk on the urinary effect, toluene was the dominant contributor in children; the HI values were above 1, suggesting that young children were more sensitive to toluene exposure than adults. The 95th percentile of non-carcinogenic risk for toluene was estimated to range from 4.16 × 10−4 to 2.53 × 10−2 at home [38]. The HQ of toluene and xylene in homes in Izmir, Turkey, was 0.015 and 0.317, respectively [54]. The HQs of toluene and xylene in the indoor air of homes at different microenvironments in north India ranged from 0.075 to 0.33 [55], respectively.
Our results show that wooden floors, cold paint multi-layer wooden materials, and multi-layer materials for system furniture were the three dominant contributors of VOC emissions in newly renovated houses. The positive contributions of indoor temperature [5,30,56], floor and wall coverings [56,57], paints and adhesives [57], and negative contribution of window opening rate [39,56] were all in agreement with those of previous studies. Hun et al. reported that new composite wood (such as medium-density fiberboard, particleboard, and hardwood plywood) were influential sources of formaldehyde [30]. These results imply that control strategies to reduce the potential health risks of formaldehyde and specific VOCs in newly renovated houses could be adopted by using healthy green building materials, temperature control, open windows, and air cleaners. Further research is required to confirm the effectiveness of these control strategies.
The present study represents the preliminary development of a risk-based probabilistic predicting model to characterize quantitatively the concentrations of formaldehyde and specific VOCs contributed by the decoration materials in newly renovated houses, and some shortcomings merit further investigation. First, simultaneous data could be used to calculate the emission rates of the decoration materials in real scenarios to reflect the critical effects of formaldehyde and specific VOC emissions when the window or door status. All the measurements were conducted in summer. The ranges of temperature and relative humidity measured for the indoor samples were narrow. The emission of the investigated indoor pollutants from decoration materials was revealed to have a high correlation to the local temperature. Future studies should take the above-mentioned factors into consideration, and develop an improved risk-based model that can cover most of the real-world scenarios for reducing the health risk of formaldehyde and specific VOC emissions in newly renovated houses.

5. Conclusions

Probabilistic and sensitive predicting models for formaldehyde and selected VOCs were established effectively to reduce health risks in newly renovated houses. The emission patterns of formaldehyde, toluene, and styrene in open-and closed-window scenarios varied for bedrooms and living rooms. Based on the recommended safety limits, the 95th percentile HIs of inhalation exposure to seven VOCs by residential groups (children and adults) is a significant current safety concern for the Taiwanese population. The estimated cancer risk from inhalation exposure to benzene, ethylbenzene, and formaldehyde for children and adults exceeded the acceptable level. The loading factor of multi-layer wood materials, such as wooden floors, cold paint multi-layer wooden materials, and multi-layer materials for system furniture, was responsible for the contribution levels of formaldehyde and specific VOCs. To avoid health hazards caused by air pollution, urgent preventive measures for reductions in effective sources are needed. To reduce VOC levels in indoor environments, it is necessary to eliminate the sources of chemicals through better choices of construction and building/furnishing materials.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/atmos13050675/s1, Table S1: Exposure parameters of the selected age groups in health risk assessment. Table S2: Toxic parameters of the selected age groups in health risk assessment. Table S3: The equation of indoor prediction models for the concentrations of formaldehyde and specific VOCs based on multiple linear regressions. Table S4: Exposure dose of indoor formaldehyde and individual VOCs in the selected age groups.

Author Contributions

Conceptualization, W.-T.L.; methodology, W.-T.L. and R.-Y.T.; software, W.-T.L. and H.-L.C.; validation, W.-T.L., H.-L.C. and Y.-S.T.; formal analysis, W.-T.L. and H.-L.C.; investigation, W.-T.L. and R.-Y.T.; resources, Y.-S.T. and C.-C.L.; data curation, W.-T.L. and H.-L.C.; writing—original draft preparation, W.-T.L. and Y.-S.T.; writing—review and editing, W.-T.L., Y.-S.T. and C.-C.L.; supervision, C.-C.L. and Y.-S.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are not publicly available due to protection of subjects’ privacy and confidentiality. The data presented in this study are available on request from the first author.

Acknowledgments

This study was supported by the Architecture and Building Research Institute of Taiwan for field measurements and chemical analysis.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chen, P.Y.; Kung, L.C.; Tsai, W.; Chieh, D.K.; Chang, W.H. The potential risk of sick building syndrome of the emergency department areas in a medical center in Taiwan. Health Technol. 2019, 3, 3. [Google Scholar] [CrossRef]
  2. Holøs, S.B.; Yang, A.; Lind, M.; Thunshelle, K.; Schild, P.; Mysen, M. VOC emission rates in newly built and renovated buildings, and the influence of ventilation—A review and meta-analysis. Int. J. Vent. 2019, 18, 153–166. [Google Scholar] [CrossRef]
  3. Lu, C.Y.; Tsai, M.C.; Muo, C.H.; Kuo, Y.H.; Sung, F.C.; Wu, C.C. Personal, Psychosocial and Environmental Factors Related to Sick Building Syndrome in Official Employees of Taiwan. Int. J. Environ. Res. Public Health 2017, 15, 7. [Google Scholar] [CrossRef] [Green Version]
  4. Worldwide Health Organization (WHO) Regional Office for Europe. Combined or Multiple Exposure to Health Stressors in Indoor Built Environments. 2014. Available online: https://www.euro.who.int/en/health-topics/environment-and-health/air-quality/publications/2014/combined-or-multiple-exposure-to-health-stressors-in-indoor-built-environments (accessed on 20 February 2022).
  5. Chi, C.C.; Chen, W.D.; Gun, M.; Wang, M.; Yang, G.; Shen, X.Y. Law and features of TVOC and Formaldehyde pollution in urban indoor air. Atmos. Environ. 2016, 132, 85–90. [Google Scholar] [CrossRef] [Green Version]
  6. Du, Z.J.; Mo, J.H.; Zhang, Y.P.; Xu, Q.J. Benzene, toluene and xylenes in newly renovated homes and associated health risk in Guangzhou, China. Build. Environ. 2014, 72, 75–81. [Google Scholar] [CrossRef]
  7. Rösch, C.; Kohajda, T.; Röder, S.; van Bergen, M.; Schlink, U. Relationship between sources and patterns of VOCs in indoor air. Atmos. Pollut. Res. 2014, 5, 129–137. [Google Scholar] [CrossRef] [Green Version]
  8. Logue, J.M.; McKone, T.E.; Sherman, M.H.; Singer, B.C. Hazard assessment of chemical air contaminants measured in residences. Indoor Air 2011, 21, 92–109. [Google Scholar] [CrossRef] [Green Version]
  9. Mandin, C.; Trantallidi, M.; Cattaneo, A.; Canha, N.; Mihucz, V.G.; Szigeti, T.; Mabilia, R.; Perreca, E.; Spinazzè, A.; Fossati, S.; et al. Assessment of indoor air quality in office buildings across Europe—The OFFICAIR study. Sci. Total Environ. 2017, 579, 169–178. [Google Scholar] [CrossRef] [Green Version]
  10. Worldwide Health Organization (WHO) Regional Office for Europe. Methods for Sampling and Analysis of Chemical Pollutants in Indoor Air. 2020. Available online: https://apps.who.int/iris/bitstream/handle/10665/334389/9789289055239-eng.pdf (accessed on 20 February 2022).
  11. Worldwide Health Organization (WHO) Regional Office for Europe. Report of the Regional Director: The Work of the WHO Regional Office for Europe in 2020–2021. 2021. Available online: https://apps.who.int/iris/handle/10665/346875 (accessed on 20 February 2022).
  12. Sérafin, G.; Blondeau, P.; Mandin, C. Indoor air pollutant health prioritization in office buildings. Indoor Air 2021, 31, 646–659. [Google Scholar] [CrossRef]
  13. Salonen, H.J.; Pasanen, A.L.; Lappalainen, S.K.; Riuttala, H.M.; Tuomi, T.M.; Pasanen, P.O.; Bäck, B.C.; Reijula, K.E. Airborne concentrations of volatile organic compounds, formaldehyde and ammonia in Finnish office buildings with suspected indoor air problems. J. Occup. Environ. Hyg. 2009, 6, 200–209. [Google Scholar] [CrossRef]
  14. Du, W.; Wang, G. Indoor Air Pollution was Nonnegligible during COVID-19 Lockdown. Aerosol Air Qual. Res. 2020, 20, 1851–1855. [Google Scholar] [CrossRef]
  15. Brown, S.K. Volatile organic pollutants in new and established buildings in Melbourne, Australia. Indoor Air 2002, 12, 55–63. [Google Scholar] [CrossRef] [PubMed]
  16. Järnström, H.; Saarela, K.; Kalliokoski, P.; Pasanenc, A.L. Reference values for indoor air pollutant concentrations in new, residential buildings in Finland. Atmos. Environ. 2006, 40, 7178–7191. [Google Scholar] [CrossRef]
  17. Park, J.S.; Ikeda, K. Variations of formaldehyde and VOC levels during 3 years in new and older homes. Indoor Air 2006, 16, 129–135. [Google Scholar] [CrossRef] [PubMed]
  18. Dai, H.X.; Jing, S.G.; Wang, H.L.; Ma, Y.G.; Li, L.; Song, W.M.; Kan, H.D. VOC characteristics and inhalation health risks in newly renovated residences in Shanghai, China. Sci. Total Environ. 2017, 577, 73–83. [Google Scholar] [CrossRef] [PubMed]
  19. Plaisance, H.; Vignau-Laulhere, J.; Mocho, P.; Sauvat, N.; Raulin, K.; Desauziers, V. Volatile organic compounds concentrations during the construction process in newly-built timber-frame houses: Source identification and emission kinetics. Environ. Sci. Process Impacts 2017, 19, 696–710. [Google Scholar] [CrossRef]
  20. International Agency for Research on Cancer (IARC). Formaldehyde, 2-Butoxyethanol and 1-tert-Butoxypropan-2-ol. IARC Monogr. Eval. Carcinog. Risks Humans. 2006, 88, 478. Available online: https://publications.iarc.fr/_publications/media/download/2757/c6a9fc1529ff03f196d3595caf6e198cb9b104ce.pdf (accessed on 20 February 2022).
  21. International Agency for Research on Cancer (IARC). Benzene. IARC Monogr. Eval. Carcinog. Risks Humans. 2017, 120. Available online: https://publications.iarc.fr/_publications/media/download/6043/20a78ade14e86cf076c3981a9a094f45da6d27cc.pdf (accessed on 20 February 2022).
  22. Niaz, K.; Bahadar, H.; Maqbool, F.; Abdollahi, M. A review of environmental and occupational exposure to xylene and its health concerns. EXCLI J. 2015, 14, 1167–1186. [Google Scholar] [CrossRef]
  23. Tsay, Y.S.; Liu, C.C.; Cheng, Y.L.; Lo, S.C.; Yau, J.T. Taiwan Green Building Material Labeling System and Its Application to Green Building Design. J. Archit. 2018, 106, 1–8. [Google Scholar] [CrossRef]
  24. Torres, J.; Garay-Martinez, R.; Oregi, X.; Torrens-Galdiz, J.I.; Uriarte-Arrien, A.; Pracucci, A.; Casadei, O.; Magnani, S.; Arroyo, N.; Cea, A.M. Plug and Play Modular Façade Construction System for Renovation for Residential Buildings. Buildings 2021, 11, 419. [Google Scholar] [CrossRef]
  25. Richter, M.; Horn, W.; Juritsch, E.; Klinge, A.; Radeljic, L.; Jann, O. Natural Building Materials for Interior Fitting and Refurbishment—What about Indoor Emissions? Materials 2021, 14, 234. [Google Scholar] [CrossRef] [PubMed]
  26. Hines, A.L.; Ghosh, T.K. Investigation of Co-Sorption of Gases and Vapors as a Means to Enhance Indoor Air Quality. Phase 2. Water Vapor Uptake and Removal of Chemical Pollutants by Solid Adsorbents. 1993. Available online: https://www.osti.gov/biblio/6884774 (accessed on 20 February 2022).
  27. Adamova, T.; Hradecký, J.; Pánek, M. Volatile Organic Compounds (VOCs) from Wood and Wood-Based Panels: Methods for Evaluation, Potential Health Risks, and Mitigation. Polymers 2020, 12, 2289. [Google Scholar] [CrossRef] [PubMed]
  28. He, Z.K.; Zhang, Y.P.; Wei, W.J. Formaldehyde and VOC emissions at different manufacturing stages of wood-based panels. Build. Environ. 2012, 47, 197–204. [Google Scholar] [CrossRef]
  29. Yu, C.W.F.; Kim, J.T. Long-term Impact of Formaldehyde and VOC Emissions from Wood-based Products on Indoor Environments; and Issues with Recycled Products. Indoor Built Environ. 2012, 21, 137–149. [Google Scholar] [CrossRef]
  30. Hun, D.E.; Corsi, R.L.; Morandi, M.T.; Siegel, J.A. Formaldehyde in residences: Long-term indoor concentrations and influencing factors. Indoor Air 2010, 20, 196–203. [Google Scholar] [CrossRef]
  31. Wu, G.H. A Study of Healthy Green Building Materials in Indoor Air Quality and Healthy Assessment. Master’s Thesis, Taipei University of Technology, Taipei, Taiwan, 2010. [Google Scholar]
  32. Li, Y.Y. A Study on the Management Strategy of Indoor Air Quality in Taiwan Office Buildings. Ph.D. Thesis, National Cheng Kung University, Tainan, Taiwan, 2004. [Google Scholar]
  33. Li, B.Z.; Cheng, Z.; Yao, R.M.; Wang, H.; Yu, W.; Bu, Z.M.; Xiong, J.; Zhang, T.W.; Essah, E.M.; Luo, Z.W.; et al. An investigation of formaldehyde concentration in residences and the development of a model for the prediction of its emission rates. Build. Environ. 2019, 147, 540–550. [Google Scholar] [CrossRef]
  34. Bourdin, D.; Mocho, P.; Desauziers, V.; Plaisance, H. Formaldehyde emission behavior of building materials: On-site measurements and modeling approach to predict indoor air pollution. J. Hazard Mater. 2014, 280, 164–173. [Google Scholar] [CrossRef]
  35. He, Z.; Xiong, J.Y.; Kumagai, K.K.; Chen, W.H. An improved mechanism-based model for predicting the long-term formaldehyde emissions from composite wood products with exposed edges and seams. Environ. Int. 2019, 132, 105086. [Google Scholar] [CrossRef]
  36. Huang, S.D.; Wei, W.J.; Wesschler, L.B.; Salthammer, T.G.; Kan, H.D.; Bu, Z.M.; Zhang, Y.P. Indoor formaldehyde concentrations in urban China: Preliminary study of some important influencing factors. Sci. Total Environ. 2017, 590, 394–405. [Google Scholar] [CrossRef]
  37. Zhang, Z.F.; Zhang, X.; Zhang, X.M.; Liu, L.Y.; Li, Y.F.; Sun, W. Indoor occurrence and health risk of formaldehyde, toluene, xylene and total volatile organic compounds derived from an extensive monitoring campaign in Harbin, a megacity of China. Chemosphere 2020, 250, 126324. [Google Scholar] [CrossRef] [PubMed]
  38. United States Environmental Protection Agency (US EPA), Guidelines for Human Exposure Assessment (EPA/ 630-P-03-001F). 2005. Available online: https://www.epa.gov/risk/guidelines-carcinogen-risk-assessment (accessed on 20 February 2022).
  39. Liu, Q.Y.; Liu, Y.J.; Zhang, M.G. Personal exposure and source characteristics of carbonyl compounds and BTEXs within homes in Beijing, China. Build. Environ. 2013, 61, 210–216. [Google Scholar] [CrossRef] [PubMed]
  40. Taiwan Health Promotion Administration (HPA), Compilation of Exposure Factor of the General Population in Taiwan; Ministry of Health and Welfare: Taipei, Taiwan, 2008.
  41. Taiwan Ministry of the Interior (MOI), Abridged Life Table in Republic of China Area. 2020. Available online: https://www.moi.gov.tw/english/cl.aspx?n=7780 (accessed on 30 December 2021).
  42. United States Environmental Protection Agency (US EPA), Guidelines for Carcinogen Risk Assessment (EPA/100/B-1/001). 2019. Available online: https://www.epa.gov/risk/guidelines-human-exposure-assessment (accessed on 20 February 2022).
  43. Shin, S.H.; Jo, W.K. Volatile organic compound concentrations, emission rates, and source apportionment in newly-built apartments at pre-occupancy stage. Chemosphere 2012, 89, 569–578. [Google Scholar] [CrossRef] [PubMed]
  44. Bluyssen, P.M.; de Richemont, S.; Crump, D.; Maupetit, F.; Witterseh, T.; Gajdos, P. Actions to reduce the impact of construction products on indoor air: Outcomes of the European project Healthy Air. Indoor Built Environ. 2010, 19, 327–339. [Google Scholar] [CrossRef] [Green Version]
  45. Suzuki, N.; Nakaoka, H.; Nakayama, Y.; Takaya, K.; Tsumura, K.; Hanazato, M.; Tanaka, S.; Matsushita, K.; Iwayama, R.; Mori, C. Changes in the concentration of volatile organic compounds and aldehydes in newly constructed houses over time. Int. J. Environ. Sci. Technol. 2020, 17, 333–342. [Google Scholar] [CrossRef] [Green Version]
  46. Kim, S.S.; Kang, D.H.; Choi, D.H.; Yeo, M.S.; Kim, K.W. Comparison of strategies to improve indoor air quality at the pre-occupancy stage in new apartment buildings. Build. Environ. 2008, 43, 320–328. [Google Scholar] [CrossRef]
  47. Guo, M.; Yu, W.; Zhang, S.; Wang, H.; Wei, S. A numerical model predicting indoor volatile organic compound Volatile Organic Compounds emissions from multiple building materials. Environ. Sci. Pollut. Res. Int. 2020, 27, 587–596. [Google Scholar] [CrossRef]
  48. D’Amico, A.; Pini, A.; Zazzini, S.; D’Alessandro, D.; Leuzzi, G.; Currà, E. Modelling VOC Emissions from Building Materials for Healthy Building Design. Sustainability 2021, 13, 184. [Google Scholar] [CrossRef]
  49. Fortenberry, C.; Walker, M.; Dang, A.; Loka, A.; Date, G.; De Carvalho, K.C.; Morrison, G.; Williams, B. Analysis of indoor particles and gases and their evolution with natural ventilation. Indoor Air 2019, 29, 761–779. [Google Scholar] [CrossRef]
  50. Wei, W.; Ramalho, O.; Malingre, L.; Sivanantham, S.; Little, J.C.; Mandin, C. Machine learning and statistical models for predicting indoor air quality. Indoor Air 2019, 29, 704–726. [Google Scholar] [CrossRef]
  51. Loh, M.M.; Levy, J.I.; Spengler, J.D.; Houseman, E.A.; Bennett, D.H. Ranking cancer risks of organic hazardous air pollutants in the United States. Environ. Health Perspect. 2007, 115, 1160–1168. [Google Scholar] [CrossRef]
  52. Gong, Y.; Wei, Y.; Cheng, J.; Jiang, T.; Chen, L.; Xu, B. Health risk assessment and personal exposure to Volatile Organic Compounds (VOCs) in metro carriages—A case study in Shanghai, China. Sci. Total Environ. 2017, 574, 1432–1438. [Google Scholar] [CrossRef] [PubMed]
  53. Hadei, M.; Hopke, P.K.; Rafiee, M.; Rastkari, N.; Yarahmadi, M.; Kermani, M.; Shahsavani, A. Indoor and outdoor concentrations of BTEX and formaldehyde in Tehran, Iran: Effects of building characteristics and health risk assessment. Environ. Sci. Pollut. Res. Int. 2018, 25, 27423–27437. [Google Scholar] [CrossRef] [PubMed]
  54. Sofuoglu, S.C.; Aslan, G.; Inal, F.; Sofuoglu, A. An assessment of indoor air concentrations and health risks of volatile organic compounds in three primary schools. Int. J. Hyg. Environ. Health 2011, 214, 36–46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Masih, A.; Lall, A.S.; Taneja, A.; Singhvi, R. Exposure profiles, seasonal variation and health risk assessment of BTEX in indoor air of homes at different microenvironments of a terai province of northern India. Chemosphere 2017, 176, 8–17. [Google Scholar] [CrossRef] [PubMed]
  56. Mečiarová, Ľ.; Vilčeková, S.; Krídlová Burdová, E.; Kiselák, J. Factors Effecting the Total Volatile Organic Compound (TVOC) Concentrations in Slovak Households. Int. J. Environ. Res. Public Health 2017, 14, 1443. [Google Scholar] [CrossRef] [Green Version]
  57. Bari, M.A.; Kindzierski, W.B.; Wheeler, A.J.; Héroux, M.È.; Wallace, L.A. Source apportionment of indoor and outdoor volatile organic compounds at homes in Edmonton, Canada. Build. Environ. 2015, 90, 114–124. [Google Scholar] [CrossRef]
Atmosphere 13 00675 g001 550
Figure 1. Sensitivity analysis of the influence parameters to the hazard index of hepatic toxicity (A), urinary effect (B), developmental toxicity (C) and cancer risk (D) in the selected age groups.
Figure 1. Sensitivity analysis of the influence parameters to the hazard index of hepatic toxicity (A), urinary effect (B), developmental toxicity (C) and cancer risk (D) in the selected age groups.
Atmosphere 13 00675 g001
Table
Table 1. Characteristics of the newly renovated houses and apartments (n = 11).
Table 1. Characteristics of the newly renovated houses and apartments (n = 11).
VariablesDescriptionMean ± SD (or n [%])
Building typeHouse4 (33.4)
Apartment7 (63.6)
Building floor level12 (18.2)
22 (18.2)
>37 (63.6)
Room typeLiving room10 (45.5)
Bedroom12 (54.5)
Room size (m2)Living room33.7 ± 9.2
Bedroom22.0 ± 14.9
The loading factor of the decoration material (m2/m3)Cold paint multi-layer wooden materials (CPM)0.05 ± 0.08
Laminate hard plastic multi-layer materials (LHP)0.08 ± 0.11
Veneer multi-layer wooden materials (VM)0.10 ± 0.13
Multi-layer materials for system furniture (SF)0.07 ± 0.12
Cement paint (CP)1.00 ± 0.39
Wooden floor (WF)0.11 ± 0.17
CO2 level (ppm)Open window509 ± 38.1
Close window561 ± 81.6
Temperature (°C)Open window28.9 ± 1.41
Close window28.7 ± 1.49
Relative humidity
(RH, %)		Open window71.9 ± 5.08
Close window74.4 ± 3.27
Table
Table 2. Summaries of formaldehyde and VOC concentrations (μg/m3) in open and close window scenarios in 11 newly renovated houses.
Table 2. Summaries of formaldehyde and VOC concentrations (μg/m3) in open and close window scenarios in 11 newly renovated houses.
Open WindowClose Window
CompoundDf (%)N aMeanSDMin50%MaxDf (%)N aMeanSDMin50%Max
Living rooms
Formaldehyde100.01040.936.72.430.9116.4100.010144.693.134.292.8295.5
Benzene87.571.81.30.31.43.887.57 3.7 3.7 0.3 1.9 10.5
Toluene100.08129.9172.73.486.7536.7100.08 235.9 189.5 8.1 275.0 532.8
Ethyl benzene25.020.70.90.30.32.762.55 2.5 3.1 0.3 1.3 8.9
m-xylene25.020.40.20.30.31.062.55 2.2 2.2 0.3 1.4 5.3
p-xylene37.530.70.80.30.32.587.57 4.6 4.8 0.3 2.8 11.9
o-xylene37.530.50.30.30.31.062.55 4.2 6.1 0.3 2.0 18.3
Styrene50.042.74.70.30.813.975.06 34.9 58.1 0.3 5.4 156.7
TVOCs100.08136.7177.06.889.4551.3100.08 289.1 255.1 10.3 290.2 740.5
Bedrooms
Formaldehyde100.01033.324.79.824.476.5100.010141.272.912.2127.8236.1
Benzene70.071.82.60.31.08.590.0 93.0 2.3 0.3 2.3 6.7
Toluene100.01083.679.62.050.5213.9100.0 10 185.6 160.2 7.7 143.6 455.0
Ethyl benzene10.010.30.10.30.30.660.0 6 2.0 2.4 0.3 1.6 8.2
m-xylene10.010.30.30.30.30.360.0 6 1.8 2.0 0.3 1.1 6.3
p-xylene40.040.50.40.30.31.390.0 9 4.0 4.3 0.3 2.8 14.4
o-xylene20.020.40.20.30.30.870.0 7 3.6 5.9 0.3 1.5 19.8
Styrene30.031.11.90.30.36.460.0 6 19.9 38.4 0.3 1.1 117.2
TVOCs100.01088.181.23.756.8217.9100.0 10 220.6 203.9 11.5 167.0 629.1
a Twenty indoor air samples for formaldehyde and sixteen indoor air samples for VOCs were collected in living rooms in opened and closed window conditions; twenty indoor air samples for formaldehyde and twenty indoor air samples for VOCs were collected in bedrooms in opened and closed window conditions. N.D.: Not detected; SD: Standard deviation; Df: detection frequency.
Table
Table 3. Multiple linear regression models for the predictions of indoor formaldehyde and specific VOC concentrations.
Table 3. Multiple linear regression models for the predictions of indoor formaldehyde and specific VOC concentrations.
Regression Coefficients (95% CI)
PredictorsFormaldehydeBenzeneTolueneEthyl Benzene
Room size (m2)−0.003 (−0.005~0.007)−0.001 (−0.001~0.000) *−0.010 (−0.032~0.012)0.001 (−0.001~0.001)
Indoor temperature (°C)0.015 (−0.006~0.037)0.003 (0.001~0.006) *0.273 (0.068~0.478) *0.002 (−0.002~0.006)
Indoor RH (%)−0.001 (−0.006~0.005)0.001 (−0.001~0.001)0.019 (−0.023~0.060) #0.001 (−0.001~0.001)
Cold paint multi-layer wooden materials (CPM)0.140 (−0.115~0.394)0.010 (−0.026~0.046)3.207 (0.663~5.752) *0.025 (−0.022~0.072)
Laminate hard plastic multi-layer materials (LHP)0.081 (−0.206~0.369)0.013 (−0.053~0.027)1.761 (1.023~4.546) *0.004 (−0.047~0.056)
Veneer multi-layer wooden materials (VM)0.190 (−0.103~0.484)0.010 (−0.047~0.068)1.569 (−2.472~5.611)0.002 (−0.019~0.076) #
Multi-layer materials for system furniture (SF)0.071 (−0.137~0.279)0.002 (−0.049~0.054)1.860 (−1.761~5.480)0.017 (−0.050~0.084)
Cement paint (CP)0.001 (−0.072~0.074)0.012 (0.002~0.026) *0.649 (−1.603~0.306)0.001 (−0.019~0.017)
Wooden floor (WF)0.283 (0.140~0.426) *0.008 (−0.015~0.031)0.447 (−1.160~2.053) *0.030 (0.002~0.059) *
Open rate of window (%)−0.114 (−0.159~−0.069) *−0.009 (−0.014 ~ −0.004) *−0.515 (−0.868~−0.161) *−0.010 (−0.160~−0.003) *
Adjusted R2 (%)64.961.442.948.0
p-Value for model<0.0010.0050.0060.040
Predictorsm-Xylenep-Xyleneo-XyleneStyrene
Room size (m2)0.001 (−0.001~0.001)0.001 (−0.001~0.001)0.001 (−0.001~0.001)0.001 (−0.005~0.008)
Indoor temperature (℃)0.001 (−0.002~0.004)0.002 (−0.004~0.007)0.002 (−0.006~0.010)0.014 (−0.045~0.073)
Indoor RH (%)0.001 (−0.001~0.001)0.001 (−0.001~0.001)0.001 (−0.002~0.001)−0.006 (−0.018~0006)
Cold paint multi-layer wooden materials (CPM)0.014 (−0.019~0.048)0.031 (−0.039~0.101)0.027 (−0.076~0.130)0.140 (−0.593~0.872)
Laminate hard plastic multi-layer materials (LHP)0.005 (−0.041~0.032)0.006 (−0.082~0.071)0.013 (−0.100~0.126)0.140 (−0.742~0.661)
Veneer multi-layer wooden materials (VM)0.001 (−0.053~0.053)0.004 (−0.115~0.107)0.023 (−0.186~0.141)0.050 (−0.013~1.114) #
Multi-layer materials for system furniture (SF)0.001 (−0.047~0.048)0.002 (−0.097~0.102)0.008 (−0.139~0.154)0.181 (−0.861~1.223)
Cement paint (CP)0.001 (−0.013~0.012)0.001 (−0.025~0.027)0.008 (−0.031~0.047)0.034 (−0.240~0.309)
Wooden floor (WF)0.022 (0.001~0.044) *0.051 (0.007~0.095) *0.064 (0.001~0.129) *0.630 (0.167~1.092) *
Open rate of window (%)−0.008 (−0.013~−0.003) *−0.017 (−0.027~−0.007) *−0.017 (−0.031~−0.003) *−0.132 (−0.234~−0.030) *
Adjusted R2 (%)57.841.240.750.1
p-Value for model0.0110.0080.0400.040
* p-value < 0.05. # p-value < 0.1.
Table
Table 4. Hazard index and lifetime cancer risk of exposure to indoor formaldehyde and specific VOCs in the selected age groups.
Table 4. Hazard index and lifetime cancer risk of exposure to indoor formaldehyde and specific VOCs in the selected age groups.
Adult (19–65 Years Old)Children (6–12 Years Old)
RiskMaleFemaleMaleFemale
Hazard index
Hepatic effect
MCS mean2.63 × 10−22.48 × 10−23.78 × 10−23.87 × 10−2
MCS P502.30 × 10−22.16 × 10−22.99 × 10−23.13 × 10−2
MCS P955.40 × 10−25.15 × 10−29.18 × 10−29.12 × 10−2
Urinary effect
MCS mean0.2680.2330.3540.364
MCS P500.1830.1580.2180.228
MCS P950.8150.7071.1481.170
Developmental effect
MCS mean3.95 × 10−33.43 × 10−35.23 × 10−35.36 × 10−3
MCS P503.48 × 10−33.01 × 10−34.15 × 10−34.35 × 10−3
MCS P958.12 × 10−37.10 × 10−31.28 × 10−21.27 × 10−2
Cancer risk
MCS mean1.81 × 10−51.56 × 10−52.39 × 10−52.43 × 10−5
MCS P501.41 × 10−51.21 × 10−51.72 × 10−51.77 × 10−5
MCS P954.46 × 10−53.88 × 10−56.56 × 10−56.55 × 10−5
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Lin, W.-T.; Tsai, R.-Y.; Chen, H.-L.; Tsay, Y.-S.; Lee, C.-C. Probabilistic Prediction Models and Influence Factors of Indoor Formaldehyde and VOC Levels in Newly Renovated Houses. Atmosphere 2022, 13, 675. https://doi.org/10.3390/atmos13050675

AMA Style

Lin W-T, Tsai R-Y, Chen H-L, Tsay Y-S, Lee C-C. Probabilistic Prediction Models and Influence Factors of Indoor Formaldehyde and VOC Levels in Newly Renovated Houses. Atmosphere. 2022; 13(5):675. https://doi.org/10.3390/atmos13050675

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Lin, Wu-Ting, Ru-Yin Tsai, Hsiu-Ling Chen, Yaw-Shyan Tsay, and Ching-Chang Lee. 2022. "Probabilistic Prediction Models and Influence Factors of Indoor Formaldehyde and VOC Levels in Newly Renovated Houses" Atmosphere 13, no. 5: 675. https://doi.org/10.3390/atmos13050675

APA Style

Lin, W. -T., Tsai, R. -Y., Chen, H. -L., Tsay, Y. -S., & Lee, C. -C. (2022). Probabilistic Prediction Models and Influence Factors of Indoor Formaldehyde and VOC Levels in Newly Renovated Houses. Atmosphere, 13(5), 675. https://doi.org/10.3390/atmos13050675

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