Journal of African Earth Sciences 58 (2010) 648–651

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Journal of African Earth Sciences

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Study of indoor air pollution from household fuels in Gaborone, Botswana

T.S. Verma ⇑, S. Chimidza, T. MolefhiDepartment of Physics, University of Botswana, Pvt. Bag 00704, Gaborone, Botswana

a r t i c l e i n f o a b s t r a c t

Article history:Available online 31 August 2010

Keywords:AerosolsPollutionIndoor air qualityNumber concentrationParticlesCarbon monoxideSize distribution

1464-343X/$ - see front matter � 2010 Elsevier Ltd.doi:10.1016/j.jafrearsci.2010.07.008

⇑ Corresponding author. Tel.: +267 3552142; fax: +E-mail address: vermat@mopipi.ub.bw (T.S. Verma

This study monitored indoor air concentrations of CO and particulate matter of size range 0.3–5.0 lm in30 households representing different income groups from July to September 2007. Selected members ofthe households were interviewed to assess health effects resulting from the fuel used. Fuels that pro-duced more particles, especially those having the smallest diameters (0.3–0.5 lm), were found in thelow income group household. People from these households reported more health effects when com-pared with those in the medium and high groups. The fuels that emitted most particles produced morethan 10 times more particulate matter than the least emitting fuels. The particle number distributions forthe different fuels studied were investigated and the corresponding surface area and volume distribu-tions derived. Both the surface area and volume distributions were found to be bimodal with peaksaround 0.5 lm and 2.0 lm.

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1. Introduction

Indoor air pollution resulting from combustion of biomass fuelsis now recognized as a major contributor to the global burden ofdisease (Balakrishnan et al., 2002). By far the greatest threat of in-door pollution still occurs in the developing countries, where manypeople, mostly in rural areas, but also in many cities, continue torely on traditional fuels for cooking and heating (Barnes et al.,1994). Because of the lengths of time that they spend in close prox-imity to cooking fires, people who normally cook for the household(women in most cases) are usually the most vulnerable group.Acute respiratory infections (ARI) are among the leading causesof disease worldwide and have been causally linked with exposureto pollutants from domestic biomass fuels in developing countries(Ezzati and Kammen, 2001). When burned indoors in the absenceof adequate ventilation, the incomplete combustion of biomassfuels release smoke that contains numerous pollutants such as car-bon monoxide (CO), particulate matter and other organic com-pounds into the living environment (Sapra et al., 2005).

A number of studies on the relationship between indoor andoutdoor pollutants have been conducted and the results of thesestudies confirmed the importance of ambient air in determiningthe quality of indoor air (Naeher et al., 2000). A comprehensivestudy to monitor concentration of particles in environmental aero-sols produced as a result of biomass burning has been conducted inthe past by Jayaratne and Verma (2001). Verma and Thomas (2005,2007) carried out a study on environmental aerosol particle con-centration resulting from biomass burning in Gaborone, Botswana

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267 3185097.).

in 2002–2003 and 2003–2004. This work established that therewas an increased level of particle concentration of up to1894 cm�3, reflecting increased levels of biomass burning underwinter dry season conditions. These results are consistent withthose established previously by other workers (Zhang et al.,2008; Kaufman and Koren, 2006).

The aim of the present study is to investigate the effect of differ-ent cooking fuels on the concentration of particles and CO. Further-more, indications of possible health conditions such as stingingeyes, runny noses, irritations and shortness of breath that couldbe associated with the different fuel types were established. Thestudy was conducted by monitoring indoor air quality in 30 house-holds representing three different income groups and conductingshort interviews on the health conditions of the households’ mem-bers most closely involved in the cooking of food.

2. Methodology

The survey was carried out in Old Naledi, a residential area inGaborone (24�400S, 25�570E), Botswana, to investigate the levelsof indoor airborne particles and CO emitted by different cookingfuels. Measurements of particles and CO concentrations were car-ried out in 30 households representing low, middle and high in-come groups (10 households per group). The small number ofhigh income households in Old Naledi resulted in the randomselection of the low and middle income groups while for the highincome group all those that were willing to participate in the studywere selected. In some cases however, some of the houses initiallyselected in the low and medium income groups had to be replaced,again, randomly, when owners declined to participate in the study.

T.S. Verma et al. / Journal of African Earth Sciences 58 (2010) 648–651 649

The low income group households, in keeping with manyhomes in Old Naledi, where an appreciable number of people areeither in low paid jobs or are unemployed, cannot afford ‘clean’cooking fuels and use cow dung, wood only, wood and plastic bags,paraffin, and Chibuku beer cartons (made from card board with aninterior thin plastic film lining) for cooking. Households in the mid-dle income group use gas stoves (liquefied petroleum gas (LPG))and the high income group households use electricity.

Emission concentrations of particles and CO were measured bymeans of a handheld particle counter, HHPC-6, from Met One(Hach Ultra Analytics) and the Fluke CO-220 portable carbon mon-oxide meter, respectively. The particle counter measures particlesin the 0.3–5.0 lm diameter range.

The levels of pollutants recorded were then assessed in con-junction with health conditions reported by the people who regu-larly did the cooking in the households concerned. This was doneby means of a short interview and by the completion of a shortquestionnaire carried out before measurements commenced. Formost of the cooking time, no other members of the household werepresent within the cooking area.

The measurements were taken in the dry season between Julyand September, when the households were cooking their mainmeal of the day at midday (lunch). For each of the households vis-ited, five sets of readings for both particles and carbon monoxidewere taken as follows: (i) outside the house (so as to comparethe air inside to that outside), (ii) inside the kitchen before switch-ing the stove on, (iii) after the stove was switched on, (iv) duringthe cooking process and (v) after the cooking was completed. Read-ings (ii), (iii), (iv) and (v) were all taken inside the kitchen. For eachset, five measurements were made during short time periods (be-tween 2 and 3 min, depending on the concentrations) and the aver-age taken. The contribution of each fuel to concentrations wascalculated by subtracting reading (iii) from reading (ii).

0.0100.0200.0300.0400.0500.0600.0700.0

electr

icity

LPG

paraf

fin

chibu

ku ca

rtons

wood o

nly

wood+

plas

tic ba

gs

cow du

ng

fuel category

Part

icle

con

cent

ratio

n/cm

3

0.0

20.0

40.0

60.0

80.0

100.0

120.0

CO

(ppm

)

0.3- 0.5µm0.5-0.7µm0.7-1.0µm1-2.0µm2-5.0µm>5µmCO (ppm)

Fig. 1. Particle concentration and carbon monoxide values for different fuels fordifferent diameters.

3. Results and discussion

The weather was calm throughout the sampling period. Mini-mum daily temperatures ranged from 19 �C to 33 �C and the rela-tive humidity ranged from 19% to 53%. Disparities between thekitchens may have contributed either negatively or positively tothe concentration of both particles and CO that were studied. Thesedisparities were taken into consideration when selecting houses tobe sampled; the kitchens chosen were more or less the same interms of structure (those which had a door and some windowsor at least an opening to represent them) even if the location ofthe kitchen in terms of the rest of the house was not the same.For consistency in taking the readings it was ensured that the dis-tance from the particle counter and the CO meter (both the heightand horizontal distance) to the stove/fire was approximately thesame for all the households. No particle sources existed in thekitchen other than those derived from cooking during measure-ment of the particles. The particles that contributed to the concen-trations were thus only the cooking derived and those drifting infrom the dirt roads.

For most households and for all fuel types outdoor particle con-centrations (measurement (i)) were found to be higher than indoorconcentrations immediately upon entering the house and beforeswitching on the stove to conduct measurement (ii). This differ-ence was observed especially in respect of the larger particles (par-ticle diameter >1 lm), mainly because most houses were locatednear gravel roads and traffic during lunch times was heavy.Chimidza and Moloi (2000) and Van Dingenen et al. (2004) havedemonstrated that concentrations of large particles depend ontheir distance from source. Again, indoor concentrations (measure-ment (ii)) which were higher than or closer to those taken

outdoors, were observed when the windows were open and thewind speed higher, indicating that some of the particles might bedrifting in from outside.

The highest particle concentrations were recorded in thosehouseholds using cow dung, especially for particles having thesmallest diameters measured (0.3–0.5 lm), followed by wood plusplastic bags, wood only, and then Chibuku cartons. The lowest par-ticle concentrations in households belonging to this group were re-corded for paraffin users. The concentration of the larger particles(>5 lm) was very low when compared to that of smaller particles,whatever the category of fuel used. In general, emissions of parti-cles were lowest for the high income group homes, followed by themiddle income group, and the highest values were recorded for thelow income group. This was particularly the case for the small par-ticles (0.3–0.5 lm), where 96.3% of the particle concentrationsmeasured was contributed by fuels used by the low income group.The contributions of the fuels used by the middle income and highincome groups were 3.3% and 0.4%, respectively.

As shown in Fig. 1, the fuels used by the low income group con-tributed significantly more by way of particle emissions than dideither of those used (LPG and electricity) by the other incomegroups. Mean values for concentrations of particles recorded werelowest for lowest diameter ranges as compared to the higher diam-eter ranges. The aerosol particle concentration varied from over600 cm�3 in the range 0.3–0.5 lm to less than 0.10 cm�3 in therange greater than 5 lm for the fuel that emitted most particles.

Concentration of CO was also found to depend on fuel type, withthe low income group having high concentrations. The mean con-centration varied from 0 ppm for electricity and LPG to over100 ppm for cow dung. For the low income group, the lowest meanconcentration of 18.0 ppm was measured for paraffin followed by88.7 ppm for Chibiku cartons, 101.0 ppm for wood and plastic bags,103.0 ppm for wood only and then 105 ppm for cow dung. Theseconcentrations were found to be higher than the recommendedstandards. The high concentrations of CO are attributable to ineffi-cient burning of the fuel. In most cases there was a lot of smoke.

For both CO and particles, the findings shown in Fig. 1 are inagreement with those of Smith et al. (2004) when categorizing dif-ferent fuels according to the concentration of particles and CO theyemit when used. The concentrations obtained during the presentstudy conform to what is known as the energy ladder, where fuelsfrom high income households are termed cleaner fuels becausethey emit fewer particles than the fuels used by low income groupfamilies.

The concentrations of the particles during the cooking process(measurement (iv)), were found to be very high but they also de-pended on the type of food being cooked and the method of cook-

Table 1Typical values of indoor to outdoor ratios for randomly selected measurements. Foreach fuel two of the several measurements taken and averaged were used.

Fuel 0.3–0.5 lm

0.5–0.7 lm

0.7–1.0 lm

1.0–2.0 lm

2.0–5.0 lm

>5.0 lm

Electricity 0.00 0.04 0.10 0.05 0.02 0.04Electricity 0.00 0.00 0.00 0.02 0.07 0.03LPG 0.30 0.90 0.58 0.36 0.21 0.66LPG 0.14 0.73 0.59 0.32 0.12 0.34Paraffin 5.22 4.59 4.22 1.72 0.79 0.97Paraffin 9.67 3.18 1.68 0.71 0.28 0.18Chibuku cartons 8.51 4.47 3.87 1.34 0.45 0.96Chibuku cartons 7.97 8.32 3.76 2.33 0.70 0.99Wood 17.32 10.44 8.63 3.56 0.56 0.70Wood 20.23 15.27 12.22 5.19 0.60 0.90Wood + p/bags 12.13 9.93 8.37 3.34 1.32 0.30Wood + p/bags 37.52 17.63 12.90 7.35 0.76 0.31Cow dung 22.75 16.30 10.05 3.74 1.33 0.03Cow dung 23.13 20.48 19.08 7.07 1.64 0.91

650 T.S. Verma et al. / Journal of African Earth Sciences 58 (2010) 648–651

ing being used. High concentrations of particles are generated byfrying, and by cooking fatty foods. This was observed for all the in-come group households.

After the cooking process (measurement (v)), the concentra-tions were found to decline especially for the particles in the largerdiameter ranges for all the groups. Aerosol particles between 0.3and 1.0 lm (the accumulation mode) remain in the atmospherelonger than the other two size categories, nucleation mode andcoarse particles (Reid and Hobbs, 1998). Aerosol particles in thenucleation mode are subject to Brownian motion when higherrates of particle collision and coagulation increase the size of indi-vidual particles and remove them from the nucleation mode. Thecoarser particles (>1 lm radius) have higher sedimentation ratesthan the other two size ranges. Moreover, the particle size distribu-tion is not constant; as the fire gases cool, the sub-micrometer par-ticles agglomerate and the very large particles precipitate, which iswhy there was a reduction in the concentration of particles, even ofthe smaller ones.

Indoor to outdoor ratios (I/O) of particle concentrations weremany times >1 in the low diameter ranges for fuels which werefound to produce more particles and <1 for those which

0.0

500.0

1000.0

1500.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0D (micrometer)

dN/d

logD

0.000

50.000

100.000

150.000

200.000

0.0

dV/d

logD

wood only(a) (

(c)

Fig. 2. Representatives of size distributions of (a) number, (b) surfac

were found to produce less particles. Typical values obtained aftercalculations for households randomly selected from the sample forthe entire diameter ranges are shown in Table 1. Using the ratios asan indication of how clean the fuel is reveals that the high incomegroup fuels are the most clean followed by the medium incomegroup fuels. The low income group fuels, on the other hand, arenot clean, with some of the ratios being >30. At some places out-door values were higher than at other places depending on the dis-tance of the house from the busy gravel road, but as seen on thetable I/O values for the low income group were still found to bevery high. Unlike the individual concentrations for each fuel, thesevalues depended on particle concentration levels outside the kitch-en, but the evidence of the high particle emission of fuels in thelow income group is still very significant.

Fig. 2a shows the concentration of particles compared with par-ticle diameter for wood, where N (cm�3) is the concentration ofparticles larger than the diameter D (lm). As seen in the plot theconcentration of particles was found to be greater for the smalldiameter ranges as compared to the larger diameter ranges. Theconcentration falls by more than 10 orders of magnitude as size de-creases from 0.3 to 5 lm for fuels that produce more particles (lowincome group fuels). A similar pattern was also observed with allthe other fuels. The corresponding surface and volume distribu-tions are shown in Fig. 3b and c. In these two figures, S is the totalsurface area of all particles larger than D and V is the total volumeof all particles larger than D.

As the plots of particle distribution show, most particles are<0.5 lm. The surface size distributions for fuels that produce moreparticles show two modes at 0.5 lm and 2.0 lm. The volume dis-tributions for fuels that produce more particles also show twomodes, at 0.2 lm and at 2.0 lm, but these modes are displacedto >5 lm for fuels that produce less particles.

Fig. 3 shows examples of plots to find b, which is a measure ofthe degree of pollution and it is determined from the slope whenthe measurements are plotted in the form of a number distributioncurve drawn between log(dN/dlog D) and log D, where N is the con-centration with diameters greater than D. Its value generally liesbetween 2 and 4 (Wallace and Hobbs, 1977). The values of b forparaffin, Chibuku cartons, wood only, wood and plastic bags andcow dung were 2.79, 3.10, 3.14, 3.19 and 3.28 respectively. For

0.0200.0400.0600.0800.0

1000.01200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0D (micrometer)

dS/d

logD

1.0 2.0 3.0 4.0 5.0 6.0D (micrometer)

wood only

wood only

b)

e area and (c) volume size concentrations of particle for wood.

wood only

-2.0-1.00.01.02.03.04.0

-1.0 -0.5 0.0 0.5 1.0log D

log

(dN

/dlo

gD)

Fig. 3. Graph to determine b for wood.

Table 2The number of people (out of 10) who have given an indication of the listed healthconditions.

Fuel Number of people with the indicated conditions (out of 10)

Shortnessof breath

IrritatedSinuses

Coughing A runnynose

Stingingeyes

A scratchythroat

Electricity 0 0 0 0 0 0LPG 0 1 0 0 0 0Paraffin 9 8 9 9 8 9Wood only 8 8 8 8 7 8Wood and

plastic bags10 10 9 9 10 9

Chibukucartons

10 10 10 10 10 10

Cow dung 10 10 10 10 10 10

T.S. Verma et al. / Journal of African Earth Sciences 58 (2010) 648–651 651

fuels that produce less particles (LPG and electricity) b values were2.75 and 2.57 respectively.

Table 2 summarizes the responses to the questionnaire on indi-cations of possible health conditions. Most of the people from thelow income group reported more indications than did people cook-ing with gas and electricity (middle and high income group). Thepeople from low income groups are thus most probably inhalingemissions which affect their health adversely in many ways. Itwould be worthwhile investigating further the health effects ofthose doing most of the cooking for the low income group. Suchinvestigations could include analysis of the constituents of the in-haled smoke and correlating concentrations of the different con-stituents with the occurrence of diseases like asthma attacks,skin irritations, etc. Notwithstanding the fact that most of themuse the fuel not by choice but because it is the one available atthe time, the study could be used to advise the low income groupon fuels to use and how best and most safely to use them.

Some of the indications of possible health conditions that werereported by the household members in the present study weredizziness, shortness of breath and coughing, which are especiallyexperienced during the period when the fuel was burnt. Theindication could be due to the measured high concentrations ofCO. High concentrations of CO found in Kenyan Masai homeswere linked to the health effects on the people there (Bruceet al., 2002).

In most cases the symptoms reported during the present workwere short term effects resulting from working in the presenceof high concentrations of particles and CO. Some people from thelow income households, however, also reported what can be clas-sified as long term effects of using these fuels. One of them istuberculosis; thorough investigation into this would merit furtherresearch to be able to properly link these illnesses to use of solidfuels. Such a study would need large sample sizes for the resultsto be statistically significant.

4. Conclusion

From our study, Fuels that produced more particles, especiallythose having the smallest diameters (0.3–0.5 lm), were found inthe low income group household. People from these householdsreported more health effects when compared with those in themedium and high income groups. The fuels that emitted most par-ticles produced more than 10 times more particulate matter thanthe least emitting fuels. The particle number distributions for thedifferent fuels studied were investigated and the correspondingsurface area and volume distributions derived. Both the surfacearea and volume distributions were found to be bimodal withpeaks around 0.5 lm and 2.0 lm. The present study can beextended to calculation of exposures with the aid of additionalmeasurements during no cooking times and the collection oftime-activity records. These estimates could be used to build a re-gional exposure database and facilitate health risk assessments.

Acknowledgement

The authors greatly acknowledge the financial support of theUniversity of Botswana.

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