MODELLING THE EFFECTS OF VENTILATION AND THERMAL COMFORT IN OFFICE ROOMS
RESULTS AND DISCUSSION
Application of the process for data from two office rooms
Descriptive statistics for input and output variables are shown in Table 1. In 2016, daily average indoor T ranged between 20.2-25.8 oC in Rm1 and 20.4-26.0 oC in Rm2, and RH ranged between 2.0 - 46.8% in Rm1 and 0.6 - 48.5% in Rm2, correspondingly. Based on weather data, outdoor T ranged between -23.2 - 24.2 oC over the monitoring period.
Table 1. Descriptive statistics for daily indoor T, RH, max CO2, and estimated ventilation rate, thermal comfort, health, and performance outcomes.
Room 1 Room 2 Relative performance 216 0.99 (0.97-1.00), 0.01 234 0.99 (0.96-1.00), 0.01 Relative performance 197 1.02 (1.01-1.03), 0.01 129 1.03 (1.02-1.04), 0.00 Relative illness/sick- 197 0.62 (0.36-0.78), 0.08 129 0.37 (0.22-0.65). 0.10 Some of the RH values were very low: the lowest 5th and 10th percentiles were about RH 5% and 10%, correspondingly. However, based on statistical criteria, none of the values were outliers (i.e. indicative of an anomaly that would be a reason of concern from the analytical point of view). It was noted that values below the lowest 5th percentile occurred only at outdoor temperatures below -15 oC.
The PMV/PPD model predicted than on the average, about 7 % of persons were dissatisfied with thermal conditions over the year. As shown in Figure 1, PPD was slightly higher during the winter than during the rest of the year.
Mean relative performance based on indoor T was 0.99, ranging between 0.97-1.00 in Rm1 and 0.96-1.00 Rm2, indicating up to 3-4% performance lost due to non-optimal indoor T. No clear seasonal trend was observed (Figure 1).
Daily maximum CO2 concentrations were ranging from 460 to 2550 ppm. Estimated mean ventilation rates were 16.1 l/s-person for Rm1, and 42.5 l/s-person for Rm2. The estimates correspond with modelled relative performance ranges of 1.01-1.03 (mean 1.02) in Rm1 and 1.02-1.04 (mean 1.03) in Rm2, indicating up to 4% performance gains based on daily values.
Further on, relative illness/sick-leave prevalence estimates ranged between 0.36-0.78 (mean 0.62) and 0.22-0.65 (mean 0.37) for Rm1 and 2 correspondingly. As compared to rooms with no ventilation, the model predicts an average number of sick-leave days at 62 vs. 100 in Rm1 and 37 vs. 100 in Rm2.
According to Seppänen & Fisk (2006) /2/, there are many sources of uncertainty in the model used to relate ventilation rates to sick-leave, including limited data availability, the size, filtration rate, and deposition rate of infectious particles in typical buildings. It should also be noted that the estimated ventilation rates appear to be relatively high, which could be partially related to the peak approach possibly overestimating the ventilation rates.
Figure 1. Daily output variables throughout 2016: Percentages of Persons Dissatisfied, Relative Performance (T, VR), and Relative Illness/Sick-leave Prevalence (VR).
For a reference, the criteria for Class 1 based on classification for indoor air climate in Finland is 14 l/s·person for an office room with high occupant density /10/, which criteria was exceeded for majority of time. Despite the different sources of uncertainty, a rough accounting of the influence of ventilation rates on performance and sick-leave could support the decisions concerning building operation.
Summary of results from 92 office buildings
Estimated mean PPD across the sample of 92 office buildings throughout 2016 was 7%.
The average percentage of days when PPD was above 20% was 2% (range 0-100%, SD 13%) across all buildings. Four buildings had the daily average PPD above 20%.
Estimated mean relative performance was 0.99 (range 0.51-1.00) with respect to indoor T. Therefore, most of the buildings performed well in this respect, but the worst case would correspond to almost 50% lost performance.
With respect to ventilation, mean relative performance was 1.03 (range 0.99-1.04), corresponding to an average of 3% performance gain. Mean relative prevalence of illness / sick-leave was 0.46 (range 0.22-0.92), i.e. the model predicts an average number of sick-leave days at 46 as compared to 100 days in rooms with no ventilation. These results indicate that whereas non-optimal indoor temperatures may result in dissatisfaction and performance loss in Finnish offices, ventilation rates are usually relatively high, which in turn could contribute to improved performance and decreased number of sick-leaves.
CONCLUSIONS
An analytical process was developed using continuous data on indoor temperature, relative humidity and carbon dioxide, and quantitative relationships described in the scientific literature. The resulting estimates include occupant satisfaction with thermal conditions, as well as relative performance and short-term illness / sick-leave prevalence, which can be used to support decisions concerning building operation over time.
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