Air quality and passenger comfort in an air-conditioned bus micro-environment

Abstract

In this study, passenger comfort and the air pollution status of the micro-environmental conditions in an air-conditioned bus were investigated through questionnaires, field measurements, and a numerical simulation. As a subjective analysis, passengers' perceptions of indoor environmental quality and comfort levels were determined from questionnaires. As an objective analysis, a numerical simulation was conducted using a discrete phase model to determine the diffusion and distribution of pollutants, including particulate matter with a diameter < 10 μm (PM), which were verified by experimental results. The results revealed poor air quality and dissatisfactory thermal comfort conditions in Jinan's air-conditioned bus system. To solve these problems, three scenarios (schemes A, B, C) were designed to alter the ventilation parameters. According to the results of an improved simulation of these scenarios, reducing or adding air outputs would shorten the time taken to reach steady-state conditions and weaken the airflow or lower the temperature in the cabin. The airflow pathway was closely related to the layout of the air conditioning. Scheme B lowered the temperature by 0.4 K and reduced the airflow by 0.01 m/s, while scheme C reduced the volume concentration of PM to 150 μg/m. Changing the air supply angle could further improve the airflow and reduce the concentration of PM. With regard to the perception of airflow and thermal comfort, the scheme with an airflow provided by a 60° nozzle was considered better, and the concentration of PM was reduced to 130 μg/m.

A Review of Thermal Comfort Applied in Bus Cabin Environments

“…Zhu et al [14] in 2018 investigated the passenger comfort and air pollution status of an air-conditioned bus in China and the results of a simulation indicated that reducing or adding air vents would shorten the time needed to achieve stable conditions and would either weaken the airflow or decrease the temperature in the cabin.…”

“…Thermal sensation [5,9-11,13,14,18,31,46- According to Table 7, most thermal comfort studies in bus cabin environments focused on the thermal sensation aspect. Of the 16 research papers directed at the most investigated aspect, 12 analyzed only the passenger cabins [5,[9][10][11]13,14,31,[46][47][48]53,55], two observed only the drivers [18], one focused on passengers and drivers [49], and two sampled drivers and ticket collectors [50,52].…”

“…In the studies of Ismail et al [19,51], the environmental and personal parameters were not measured but rather presented as questions to the drivers and correlated with the driving activity through questionnaires. In the studies by Zhu et al [14], Velt and Daanen [15] and Lin et al [53], besides the measurable parameters listed in Table 8, the occupants were asked regarding subjective votes, such as the thermal sensation vote, the thermal preference vote, and the thermal acceptability vote, through questionnaires.…”

“…Overall, knowing these votes in thermal comfort studies is relevant due to two reasons: first, to know the operating adaptive methods of the users in adapting themselves to uncomfortable situations; second, to assess the predictive models through the discrepancies between analytical values and real subjective values. In bus cabin environments, these votes served to understand the occupants' adaptive behavior in choice of preferred seats, opening and inclination angle of the air outlets of the ventilation and air-conditioning systems, opening or closure of curtains due to solar radiation, and choice of clothing [14,15,53].…”

“…Due to high temperatures, the level perceived by the passengers was considered unsatisfactory and described in a field study conducted on buses with air conditioning during the night in China [11]. Moreover, the environmental parameters air temperature, air speed, and mean radiant temperature, considered inputs of standard models of thermal comfort like Fanger's Predicted Mean Vote-Predicted Percentage Dissatisfied (PMV-PPD) [12], and their adverse impacts on the passengers' health and well-being have drawn the attention of previous studies [13,14]. The other inputs of the mentioned predictive model are air relative humidity, metabolic rate, and clothing thermal insulation [12].…”