Indoor air quality control for improving passenger health in subway platforms using an outdoor air quality dependent ventilation system

doi:10.1016/j.buildenv.2015.05.010

Building and Environment

Volume 92, October 2015, Pages 407-417

https://doi.org/10.1016/j.buildenv.2015.05.010 Get rights and content

Highlights

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An outdoor air quality dependent ventilation system was proposed for subway platforms.
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The amount of outdoor PM₁₀ flowed into the platform was adjusted depending on outdoor air quality.
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The outdoor PM₁₀ amount flowed in the platform decreased by 29% using the proposed system.
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The proposed system saved 20% of the ventilation energy compared to manual system.
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The health concern of platform IAQ was improved using the proposed ventilation system.

Abstract

Indoor air quality (IAQ) ventilation systems are widely used to control air pollutants in subway platforms. When outdoor air is heavily contaminated by particulate matters (PMs), it enters the subway platform through the ventilation system, resulting in the deterioration of platform IAQ and adverse effects on passenger health. In this study, a new IAQ ventilation system that takes into account the outdoor air quality used for ventilating platform is proposed to control the platform PM₁₀ concentration. For this, the amount of PM₁₀ that flows from the outdoors into the subway platform is considered a manipulated variable of the proposed ventilation system. The influence of the platform PM₁₀ on passengers' health risk is evaluated using a comprehensive indoor air-quality index (CIAI). The CIAI level of platform PM₁₀ is compared using the manual and proposed ventilation systems, where the manual system operates at fixed ventilation inverter frequency without regard to the outdoor air quality. Experimental results from an underground subway platform showed that the proposed ventilation system can improve the platform PM₁₀ level, leading to the passengers’ exposure to the reduced PM₁₀ concentration (i.e., health risk reduction), and reduce the ventilation energy compared to the manual system by adjusting the ventilation inverter frequency and inflow of outdoor PM₁₀ into the subway platform depending on the outdoor air quality.

Introduction

Millions of people in metropolitan areas depend on the convenience of subway systems for transportation, which have been described as the “lifeline of urban development” by reducing traffic congestion above ground and providing environment-friendly transit [1], [2], [3]. Notwithstanding these advantages, there has been a growing concern over indoor air quality (IAQ) in subway systems, since people spend a considerable amount of time in the subway systems daily [4], [5]. Most subway systems are underground in a confined space where air pollutants are generated internally as well as enter from the outside atmosphere. Furthermore, due to heavy use and overcrowding, various types of hazardous pollutants which present a health risk to passengers and subway working staff are accumulated in subway systems [3], [6]. Therefore, to ensure passengers and subway workers good health, ventilation systems are necessary for controlling hazardous air pollutants in the subway systems.

Recently, several studies on ventilation of indoor air pollutants in different building spaces have been reported [7], [8], [9], [10], [11], [12]. Chao and Hu [8] have established a dual-mode demand control ventilation strategy that maintains the occupant-related and non-occupant-related indoor air pollutants at acceptable levels. Kolokotsa et al. [9] have proposed a bilinear model-based ventilation system to achieve the optimum indoor environmental conditions while minimizing energy cost. Liu et al. [10] have developed a model predictive control (MPC) based ventilation system in the subway station. They also have applied a multi-objective optimization algorithm to determine optimal set-points of the ventilation system which concurrently improve the IAQ and ventilation energy efficiency. Lim et al. [12] have proposed a new ventilation index, Net Escape Velocity (NEV), which directly provides information in behavior of the contaminants to the ventilation system. These researchers have assumed that the polluted indoor air is replaced with clean outdoor air by increasing the ventilation rate. In fact, if the outdoor air is strongly contaminated due to aeolian transportation of dust particles or yellow dust, its entry into the building spaces through the ventilation systems increases the air pollutants inside the building spaces [13], [14]. This article proposes a new approach that considers the outdoor air quality used for diluting indoor air pollutants. The development of ventilation control system, which takes the changes of outdoor air quality into account, is the central theme of the present study.

The ventilation under contaminated outdoor air conditions can increase the potential that the passengers in the subway systems will be exposed to health risk. Suppose the concentration of particulate matters (PMs) in the outdoor air is higher than usual (for example on megacities where the PMs concentration is far above the recommendations due to yellow dust etc., see Refs. [15], [16]). If the ventilation system is operated with the identical ventilation rate to the usual, then a larger amount of PMs enters the subway system through the ventilation under such contaminated outdoor air conditions [14], [17]. The PMs with aerodynamic diameters less than 10 μm (PM₁₀) and 2.5 μm (PM_2.5) deposit to trachea-bronchial compartment of the human respiratory system, and then, cause respiratory illnesses such as bronchial asthma, rhinitis and chronic bronchitis [18], [19]. As such, the ventilation with contaminated outdoor air has a large influence on the passengers' health risk. Therefore, to protect the passengers' health inside the subway systems, it is necessary to evaluate the influence of IAQ that is ventilated with the contaminated outdoor air. Another theme of this study is the evaluation of the influence of the ventilated IAQ on the passengers’ health risk depending on the consideration of outdoor air quality.

In the first part of this study, the ventilation control system is developed to keep the PM₁₀ concentration in the subway system at a comfortable and healthy range. To take the changes of outdoor air quality into account, the amount of PM₁₀ that is introduced from the outdoors to the subway system is used for developing the ventilation control system. Feedback and feed-forward ventilation control strategies are proposed to compensate for dynamic variations of the PM₁₀ concentration in the subway systems and effects of disturbances on the subway system's PM₁₀ concentration, respectively (for background on feedback and feed-forward control, see Bequette [20] and Seborg et al. [21]).

This article uses a comprehensive indoor air-quality index (CIAI) to evaluate the influence of the ventilated IAQ on the passengers' health risk inside the subway system. The CIAI describes ambient air quality based on the health risk of the air pollutants [18]. The variations of PM₁₀ level in the subway system are evaluated using the ventilation control system with and without the consideration of outdoor air quality, respectively. Then, the influence of PM₁₀ level on the passengers’ health risk is investigated using the CIAI. These methods are applied to an underground subway station at Seoul Metro, South Korea.

Section snippets

Comprehensive indoor air-quality index (CIAI)

A comprehensive indoor air-quality index (CIAI), of which the aim is to help the public understand the condition of current indoor air and the associated health effects, determines the health risk of indoor air pollutants using six levels of concern (good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, and hazardous) [18], [22]. The CIAI value of each indoor air pollutant is represented as: $CIAI = \frac{I_{HI} - I_{LO}}{{BP}_{HI} - {BP}_{LO}} (C_{P} - {BP}_{LO}) + I_{LO}$ where C_P is the current concentration of air

Description of the IAQ ventilation control system

Fig. 1 shows a schematic diagram of the IAQ ventilation control system in a subway platform. The ventilation control system generates control signals to ventilation inverter frequency to control the air pollutants inside the platform, where the inverter is an electronic device that regulates revolution speed of ventilation fan motor. Then, depending on the controlled inverter frequency, outdoor air with the massive PMs filtered out is distributed to the platform to dilute the polluted indoor

The proposed method

A proposed framework that develops the IAQ ventilation control system that considers the outdoor air quality and estimates its influence on the passengers’ health risk is shown in Fig. 2. The implementation of the proposed method consists of three parts: (1) identification of the IAQ process in the subway platform, (2) development of the IAQ ventilation control system, and (3) evaluation of the effects of the ventilated IAQ on passenger health risk.

Identification of IAQ process in the subway platform

Using the PEM method, three FOPTD process models that describe the dynamics of PM₁₀ concentration in the subway platform are identified. The process model from the manipulated variable (PM₁₀ amount introduced from the outdoors to platform) to the controlled variable (platform PM₁₀ concentration) is $G_{p} (s) = \frac{0.22658}{1 + 0.0641 s} \exp (- 0.44796 s)$ where the process gain, which explains how much the controlled variable changes in response to the variation of manipulated variable, is positive (K = 0.22658).

Conclusion

To keep the PM₁₀ concentration inside subway platforms at a healthy range, an IAQ ventilation control system consisting of one feedback and two feed-forward control strategies was investigated. The main contribution of this study is to investigate the effect of outdoor air quality diluting the platform air pollutants on the indoor air quality in a subway station. Moreover, the influence of ventilated IAQ on the passenger and subway worker's health was evaluated using a comprehensive indoor

Acknowledgments

This work was supported by a grant from a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (No. 2015R1A2A2A11001120).

References (32)

W. Hong et al.
A study on the energy consumption unit of subway stations in Korea
Build Environ
(2004)
M. Kim et al.
Sensor fault identification and reconstruction of indoor air quality (IAQ) data using a multivariate non-Gaussian model in underground building space
Energy Build
(2013)
M. Kim et al.
Monitoring and prediction of indoor air quality (IAQ) in subway or metro systems using season dependent models
Energy Build
(2012)
T. Moreno et al.
Subway platform air quality: assessing the influences of tunnel ventilation, train piston effect and station design
Atmos Environ
(2014)
E.V. Brauner et al.
Typical benign indoor aerosol concentrations in public spaces and designing biosensors for pathogen detection: a review
Build Environ
(2014)
M.-T. Ke et al.
Numerical simulation for optimizing the design of subway environmental control system
Build Environ
(2002)
C.Y.H. Chao et al.
Development of a dual-mode demand control ventilation strategy for indoor air quality control and energy saving
Build Environ
(2004)
D. Kolokotsa et al.
Predictive control techniques for energy and indoor environmental quality management in buildings
Build Environ
(2009)
H. Liu et al.
Multi-objective optimization of indoor air quality control and energy consumption minimization in a subway ventilation system
Energy Build
(2013)
S.M. Dutton et al.
Energy and indoor air quality implications of alternative minimum ventilation rates in California offices
Build Environ
(2014)

E. Lim et al.

Performance evaluation of contaminant removal and air quality control for local ventilation systems using the ventilation index net escape Velocity

Build Environ

(2014)

T. Marsik et al.

HVAC air-quality model and its use to test a PM_2.5 control strategy

Build Environ

(2008)

C.K.H. Yu et al.

Influence of mechanical ventilation system on indoor carbon dioxide and particulate matter concentration

Build Environ

(2014)

H.-L. Yu et al.

Spatial vulnerability under extreme events: a case of Asian dust storm's effects on children's respiratory health

Environ Int

(2013)

H.-R. Oh et al.

Long-range transport of air pollutants originating in China: a possible major cause of multi-day high-PM₁₀ episodes during cold season in Seoul, Korea

Atmos Environ

(2015)

A.T. Chan

Indoor-outdoor relationships of particulate matter and nitrogen oxides under different outdoor meteorological conditions

Atmos Environ

(2002)

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Indoor air quality control for improving passenger health in subway platforms using an outdoor air quality dependent ventilation system

Highlights

Abstract

Introduction

Section snippets

Comprehensive indoor air-quality index (CIAI)

Description of the IAQ ventilation control system

The proposed method

Identification of IAQ process in the subway platform

Conclusion

Acknowledgments

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