Tracer Decay for Determining Kitchen Ventilation Rates in San ...

Max-04-4 

School of Public Health, UC Berkeley 

Tracer Decay for Determining Kitchen Ventilation Rates in San 

Lorenzo, Guatemala 

Shannon C. Cowlin 

School of Public Health 

University of California, Berkeley 

Maxwell Chair Student Projects (Max-04-4): Summer 2004 

Published April 2005 

Citation 

Cowlin SC, 2005, “Tracer Decay for Determining Kitchen Ventilation Rates in San Lorenzo, 

Guatemala,” Maxwell Student Projects, Max-04-4, EHS, School of Public Health, University of 

California, Berkeley. 

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Acknowledgements 

Completion of this study relied heavily on the support of the field team members at MERTU in 

San Lorenzo. I would particularly like to thank Anaite Diaz and Expedita Marroquín for their 

substantial contributions to make the sampling effort a success. Eduardo Canuz Castro, John 

McCracken, Lisa Thompson, Janet Diaz, and Gabrielle Martinez provided additional valuable 

support in San Lorenzo. I would also like to extend heartfelt thanks to Kirk Smith, who provided 

the access and opportunity, and The Brian and Jennifer Maxwell Endowed Chair in Public 

Health for funding the study. I would also like to thank William Nazaroff and Zohir Chowdhury 

for their insights on ventilation and measurement techniques, Seema Bhangar for sharing her 

experiences measuring ventilation in India, and Asheena Khalakdina for providing pre-departure 

support. 

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1. Introduction 

In homes burning solid fuels indoors as cooking and heating sources, pollution can reach levels 

that exceed standards set to protect human health. Indoor pollutant concentrations in these 

homes are largely dominated by the rate at which emissions are released to the indoor 

environment and the rate at which pollutants are removed by ventilation. As such, to understand 

the full range of potential of interventions to reduce human exposure, both indoor emissions and 

ventilation need to be considered along with other factors. 

One approach to reducing human exposure to combustion byproducts is to reduce emissions 

from the source. This can be accomplished by changing fuels, such as transitioning primary use 

from biomass to cleaner-burning gaseous fuels. Other ways to reduce emissions without 

changing fuel type are to modify the stove type to promote more effective combustion and/or add 

a chimney to emit the bulk of emissions to the outdoor environment. 

The strategies discussed above to reduce human exposure do not take into account the character 

of home construction, specifically the rate at which polluted indoor air is exchanged with lesspolluted 

outdoor air. In homes with relatively low indoor emission rates, pollutants can still 

build to unsafe levels if the ventilation rates are also low. It follows that increasing the 

ventilation rates can potentially reduce indoor exposure to harmful pollutants. This can be 

accomplished by opening doors or windows while cooking or by leaving open eaves for the 

pollutants to escape. Unfortunately, this may not be feasible for many households due such 

factors as weather, security, privacy, and pest control. Nevertheless, it is desirable to understand 

the ventilation properties of a home when assessing human exposure. 

This study seeks to test the appropriateness of using a tracer decay method of measuring 

ventilation in a rural developing-world setting. This study took place in villages near San 

Lorenzo, Guatemala, the site of a large, randomized stove-intervention trial 

(http://ehs.sph.berkeley.edu/guat/page.aspid=1 ). The participants in this study were a subset of 

those participating in the randomized trial. Measurements were made in kitchens containing 

improved plancha woodstoves, which vents most of the cookfire smoke outdoors through a 

chimney. These had been given to the households on a random basis to replace the open 

(unvented) firewood stoves traditionally used in the region. 

II. Description of Method 

The tracer decay method assumes the environment being studied is well approximated by a wellmixed 

box model. The method involves releasing a conserved pollutant at a known emission 

rate and observing the concentration over time. 

Choice of tracer gas 

To be appropriate for this method, the pollutant must not react to form secondary pollutants, 

deposit on surfaces, or be removed in any manner other than removal by ventilation. In this 

study, the tracer pollutant used was carbon monoxide (CO), which meets these criteria, and, 

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importantly, is easily and cheaply produced in quantity by burning wood or other simple solid 

fuels. 

2. Well-mixed box model with indoor emission source 

In indoor environments with indoor combustion sources, the concentration of pollutants can be 

defined by employing mass conservation laws. For a pollutant that does not react with surfaces 

or other airborne species, this description is simplified. Figure 1 presents a well-mixed box 

model of an indoor environment with non-reacting pollutant contributions from outside air and 

indoor emissions. By definition, pollutant concentrations are equal in all air parcels within this 

well-mixed box. 

Figure 1. Well-mixed box model of an indoor environment with an indoor 

emission source and pollutant contribution and removal by ventilation. 

C in (mass volume -1 ) 

V (volume) 

Q*C out 

(mass time -1 ) 

Q*C in 

(mass time -1 ) 

E (mass time -1 ) 

The rate of change in pollutant mass in the indoor environment presented in Figure 1 is described 

by (1), where C in and C out are the concentrations in the indoor and outdoor air (mass volume -1 ), E 

is the mass emission rate from indoor sources (mass time -1 ), V is the volume of the indoor 

environment (volume), and Q is the ventilation rate (volume time -1 ). 

d( 

CinV 

) 

= E + CoutQ 

− CinQ 

(1) 

dt 

Assuming that indoor concentrations are much greater than outdoor concentrations (C in >> C out ) 

in the presence of an indoor source, the quantity (C out -C in ) is well approximated by (-C in ). 

Applying this assumption and dividing through by V yields (2), which describes the time rate of 

change in concentration. 

dCin 

E Q 

= − Cin 

(2) 

dt V V 

In the absence of emissions, (2) simplifies to (3) where all pollutant losses from the indoor 

environment are due to removal by ventilation. 

dCin 

Q 

= − Cin 

(3) 

dt V 

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If Q and V are constant, (3) can be integrated from time t 0 = 0 to time t * to obtain an equation for 

the indoor concentration at time t * . This solution is shown in (4), where C 0 is the concentration 

at time t 0 . 

* ⎛ Q ⎞ 

( ) = ⎜ − 

* 

C in 

t C0 

exp t ⎟ (4) 

⎝ V ⎠ 

The air exchange rate, often reported as air changes per hour (ACH), is the quantity (Q/V) and 

has the units of inverse time. If the t * and the initial and final concentrations are known, the 

ventilation rate, in terms of ACH, can be calculated according to (5). 

* 

V ln[ C0 ] − ln[ C( t )] 

ACH = = 

(5) 

* 

Q t 

3. Experimental Design 

At time of enrollment in the larger stove intervention trial, all homes were assigned to a 

qualitative ventilation category based on observed home characteristics, such as construction 

type, open or closed eaves, and number of windows. The ventilation categories used were 

abierto, parcialmente, or cerrado (open, partially open, or closed). The project field office in 

San Lorenzo selected potential homes for this study. Field team members visited the homes to 

assess willingness to participate and to ensure that the previously assigned ventilation 

classifications were still applicable. The final study size involved two homes from each 

ventilation category, and all participating homes had planchas. As planchas were supplied to 

households on a random basis, however, other household characteristics should reflect those of 

the community as a whole. Each home was visited on one afternoon and one morning, and two 

experiments were conducted at each visit. 

Equipment used included 4 HOBO CO monitors (Onset Corporation, Bourne, MA), 1 Dräger CO 

monitor (Drägerwerk AG, Lübeck, Germany), one computer, two fire-resistant buckets, wood, 

and a self-supporting post with nails protruding at heights of 0.5, 1, 1.5, and 2 meters from the 

base. The HOBO monitors were launched in the morning prior to travel to the homes according 

to manufacturer instructions and set to collect CO concentrations at 1-minute intervals. After the 

first few days of experiments, the collection interval was shortened to 15-seconds. . Upon 

arrival at the home, all wood, coal, and ash were removed from inside the plancha, put in one of 

the fire-resistant buckets, and placed outside at downwind location. In the other fire-resistant 

bucket, wood was ignited to create an emission source that could easily be removed once the 

indoor CO levels were sufficiently high. The bucket was placed at the end of the plancha on the 

ground. 

While the emissions were being allowed to accumulate in the kitchen, the HOBO monitors were 

attached to the post. The post was positioned at a lateral distance of 0.5 m from the emission 

source, as this is approximately the distance a cook would stand from the centerline of the 

plancha. The monitor heights of 0.5 and 1.5 meters were chosen to approximate squatting and 

standing breathing heights, respectively. The two monitoring heights of 1 and 2 meters were 

included to collect additional information that might allow for better understanding of airflow in 

the kitchen. 

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The Drager has screen that displays real-time CO concentrations. This monitor was placed 

approximately 1 meter from the emission source and 0.5 meters from the post. Once the 

emissions had been allowed to accumulate in the kitchen for approximately 30 minutes, the 

Drager output was monitored until the indoor CO concentration exceeded 30 ppm. At that time, 

the emission source was removed from the kitchen and placed at a downwind location, and the 

start time of the experiment was noted. After the second experiment was complete, the wood 

was returned to the plancha and the data were downloaded from the monitors for analysis. 

4. Results 

For each experiment, the air exchange rates were calculated using 10 consecutive CO 

concentration measurements taken at evenly spaced time intervals. The natural log of each CO 

concentration was regressed against time, and the negative of the slope of this line is the 

computed air exchange rate. These values were computed for each monitor height for all 

experiments. 

Table 1 shows the mean of computed air exchange rates for each home and monitor height. Air 

exchange rates from the individual experiments are attached as Appendix A. Table 2 shows air 

exchange rates by household ventilation classification where the values reported are the average 

of all experiments and monitor heights. 

Table 1. Air exchange rates calculated using tracer decay in a well-mixed box model. ACH values are 

averages over all experiments and the values in parentheses are the coefficients of variation (SD/mean). 

ACH [hour -1 ] (COV) 

Monitor Height (m) 

Ventilation Classification and 

House Number 0.5 1 1.5 2 

Cerrado 

Parcialmente 

Casa 90 18 (0.55) 15 (0.11) 16 (0.12) 18 (0.25) 

Casa 328 11 (.50) 13 (0.09) 15 (0.10) 21 (0.11) 

Casa 247 18 (0.11) 17 (0.34) 22 (0.40) 20 (0.91) 

Casa 237 21 (0.50) * 16 (0.23) 15 (0.16) 17 (0.31) 

Abierto 

Casa 29 21 (0.27) 26 (0.25) 31 (0.24) 38 (0.37) 

Casa 37 18 (0.39) 26 (0.17) 41 (0.53) 50 (0.80) 

*For Casa 237, monitor height 0.5 m, the reported value is the mean of 

calculations from three experiments due to equipment failure. All other 

reported values are the mean of calculations from four experiments. 

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Table 2. Mean air exchange rates by household ventilation classification. 

Averages are over all experiments and monitor heights. 

6. Discussion 

Household Ventilation 

Classification 

ACH (COV) 

Abierto 29 

Abierto 34 

Parcialmente 17 

Parcialmente 19 

Cerrado 17 

Cerrado 15 

The quality of construction varied significantly between the homes, but all kitchens had open 

eaves. The cerrado homes tended to have more solidly constructed walls with no visible gaps, 

the abierto homes had significant fractions of the walls missing, and the walls of the 

parcialmente homes were between these two extremes. Though CO is a colorless and odorless 

gas, the wood fire also released significant amounts of particulate matter (PM), which allowed 

for visualization of plume dispersion. In all homes, the bulk of the plume was observed to rise 

and exit the home through the open eaves. The bulk plume removal via the eaves made the task 

of accumulating CO in the kitchen difficult, and it also resulted in the CO levels dropping below 

the HOBO limit of detection in under 10 minutes, the initially planned sampling duration. To 

ensure 10 data output readings for each experiment, the data-logging interval was shortened to 

15 seconds. 

Observable uneven distribution of PM in the kitchen suggested that the air was not well mixed. 

This observation is well supported by the differences in mean air exchange rates at various 

monitor heights shown in Table 1. For individual experiments, the difference in calculated air 

exchange rate between adjacent monitors ranged from 0 to 56 ACH, and the average difference 

was 6.6 ACH. 

Observations and measured data support the fact that the air in the kitchens was not well mixed, 

which indicates that the tracer method is inappropriate for use in homes of this and similar 

construction. It may be appropriate, however, to look at these measurements as effective local 

decay rates for air parcels at that location. This value would include the sum of diffuse and 

advective transport into and out of that air parcel from all adjacent air parcels. Additionally, the 

exchange rates calculated by this method did have a tendency to follow the qualitative ventilation 

classification of homes, as is shown in Table 2. Though the method is inappropriate for precise 

quantification of ventilation in these not well-mixed environments, it may be a useful way of 

assessing relative importance of ventilation in homes of this construction. 

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Appendix A: Air exchange rates for all experiments and all homes 

Casa 29: ACH (hour -1 ) 


Experiment 0.5 1 1.5 2 

1 26 27 29 32 

2 21 16 23 30 

3 23 28 41 59 

4 13 31 31 31 




1 20 26 28 27 

2 13 22 44 101 

3 13 32 22 11 

4 27 24 71 64 




1 29 15 14 13 

2 24 13 14 14 

3 9 16 17 20 

4 10 16 18 22 


Monitor Ht 


1 14 14 12 

2 9 12 13 13 

3 26 20 17 22 

4 28 19 18 22 


Monitor Ht 


1 16 13 18 9 

2 16 12 17 7 

3 20 20 18 17 

4 19 24 35 46 

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Monitor Ht 


1 11 12 16 22 

2 17 13 15 18 

3 4 12 13 24 

4 14 14 14 21 

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