Indoor Air Pollution
- Abstract and Definitions
- Hazard ID
- Exposure Assessment
- Dose Response
- Risk Characterization
- Risk Management
This case study attempts to find the probability of acquiring Sick Building Syndrome given a magnitude of exposure to poor air quality, where the metric of air quality is defined by the ratio of the gases that comprise the air in the building in addition to any airborne particulate matter and microbial.
The World Health Organisation (Hedge and Ericson 1996, p. 3) defines Sick Building Syndrome as “a collection of nonspecific symptoms including eye, nose and throat irritation, mental fatigue, headaches, nausea, dizziness and skin irritations, which seem to be linked with occupancy of certain workplaces.”
A health risk with respect to air pollutants is defined as a potential effect of a pollutant on a human. In order to analyze the effect of a pollutant, we must first provide concise definitions of air pollution and pollutant.
- Air pollution is a change in the ratios of the components that comprise the atmosphere . Perfect air quality (i.e. unchanged ratios) is listed in table 3.1.
- A pollutant is a single entity that contributes to air pollution and is thus either a substance that is not present in table 3.1 or whose concentration exceeds the acceptable level, as listed in table 3.2 below.
The components of air pollution can be classified with respect to different properties. In particular, indoor air pollutants can be classified with respect to one of the following: physical properties, chemical properties, adverse health effects, or sources. We will classify according to physical properties; pollutants will be divided into (I) particles or (II) gas/vapors. The particles of interest in this study include particulate matter less than 10 μg/m3 (PM10).
Both tables are taken from .
Exposure Levels, Sources, and Pollutant Behavior
We defined a health risk as an adverse health effect of a pollutant on a human. To measure risk then is to access the effects of a pollutant on a human over a period of exposure. The levels of pollutant exposed to the human is not constant, but relies on several environmental factors such as
- air exchange rate source characteristics
- ventilation systems
- meteorology (temperature and relative humidity)
- age of the building
- building design
- type of indoor activities (e.g. cooking, smoking, and photocopying)
- sorption, desorption, and removal rate.
Furthermore, human reactions to pollutant exposure varies widely, and is highly dependent upon medical history and general health of the individual (e.g. is this person a smoker?). Each of the aforementioned factors are candidates of relevant parameters we will select to formulate an equation to measure the risk.
Exposure assessment is the step of the risk assessment framework that pertains to the identification of the pathway from the source of the hazard to the sink (host or patient), as well as the estimation of the concentration of the hazard exposed to the recipient. More formally, exposure assessment can be defined as the appraisal and quantification of the possible exposures in the environment that affect human health. Exposure itself is defined as any contact between a physical, chemical, or biological agent in the environment and the human body through inhalation, indigestion, or dermal or mucosal contact .
The collection and analysis of all possible hazards is infeasible due to expense, both fiscally and temporally. Therefore it is important to identify the hazards that are most likely to be a cause of the issue at hand. Because the symptoms that define Sick Building Syndrome are consistent with symptoms that can also arise from discomfort or anxiety, environmental factors such as temperature and relative humidity must be considered as possible direct sources as well as indirect contributors to a deeper problem.
- Identification of exposure pathways
- Identification of exposed group
- Estimation of exposure Concentrations
Particulate matter becomes airborne upon disturbance, and it follows that the heaviest concentration of airborne particulate matter and microbial occurs during periods of heavy activity. Possible sources of disturbance include human traffic, industrial fans, and equipment such as sweeping cars. We must consider the time line of each of these factors when scheduling our sampling.
To address the effect of human disturbance, we must record the passenger count throughout the day. Unfortunately the passenger count for the subway of interest is unavailable. Below is a passenger count of a subway in Norway. We assume similar volume fluctuation in our metro station.
According to the chart, there is moderate traffic between the hours of 9:00 and midnight, with the heaviest traffic spiking at the intervals of 6:00 through 9:00 and 16:00 through 18:00, consistent with the arrivals and departures that correspond to the average workday. There is a significant drop in traffic after midnight that continues until around 6:00 am.
To consider the effect of industrial fans on concentrations of airborne particulate matter, we must obtain the schedule of the fan operations. It is presumed that the fans run at night. The relatively low concentrations reported during this time supports this assumption.
It is unknown whether there is additional equipment activate in the subway.
Probability Distributions of Pollutants
Additional Notes on Detailed Analysis
Since air is in constant motion, the amount of pollutant exposed to the inhabitant is changing with time. Therefore to assess the risk we must model the behavior of the pollutants over the period of time of exposure. To accomplish this task, we must model the relationship of the pollutants to the fluid dynamics of the air. Our objective is to use this analysis to answer questions such as
- What is the probability that a given pollutant's concentration is above a given threshold?
- What is the probability that the concentration of the pollutant falls below or exceeds a specified threshold r times in t seconds/hours/days/etc?
- What is the distribution of the time between two surpassings of the threshold of interest?
Identification of exposure pathways
- Sources of pollutants and microbial
- Pathway: Model fluid dynamics of gas and the particulates/microbial attached to them
- Sinks: Inhalation
Identification of exposed group
Estimation of exposure Concentrations
- Markov Chain Monte-Carlo Methods
- Determine threshold values
- toxicity test
We aim to calculate the probability of response r given a dose d. The response is SBS. The dose is the amount of time (units are hours) that the human is exposed to the composite pollutant (m elements) = SUM(i=1, ..., m)(weight)(concentration of pollutant), where the weight corresponds to the magnitude of toxicity relative to the other components of the pollutant.
The actions taken to address Sick Building Syndrome (SBS) are typically either changes to the building structure or changes to the ventilation system. The decision of action requires an estimation of the construction price versus the costs of repercussions of SBS, which include liability costs and costs accumulated through loss of worker productivity. To measure the lost of productivity due to SBS, it is necessary to discover which employee positions are most affected by the poor air quality. This requires a comparison of the worker productivity between the station in question to the productivity of similar stations with superior air quality. Productivity could be measured in the speed of the crowd flow, in which case platform design must be taken into consideration, and the number of sick days taken by employees. Since employee position and the location within the station where the worker spends the majority of his or her shift is not provided, it is difficult to identify the positions and areas most affected by the poor air quality. A record of employee position included in the symptoms report may reduce the amount of information that must be collected, thus decreasing the time and cost of productivity evaluation.
- Abdul-Wahab, Sabah A. Sick Building Syndrome: In Public Buildings and Workplaces. Berlin: Springer, 2011. Internet resource.
- Pluschke, P. Indoor Air Pollution. The Handbook of Environmental Chemistry, Volume 4F, 2004. Internet resource
- Rodrigues, Eliane R, and Jorge A. Achcar. Applications of Discrete-Time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies. New York, NY: Springer, 2013. Internet resource.
- Williams PRD (2000) The risk analysis framework: Risk assessment, risk management, and risk communication. In Spengler JD, Samet JM, McCarthy JF (Ed.) Indoor Air Quality Handbook. McGraw-Hill, New York, NY.