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date: 19 April 2018

Household Air Pollution in Low and Middle Income Countries

Summary and Keywords

Household air pollution from use of solid fuels (biomass fuels and coal) is a major problem in low and middle income countries, where 90% of the population relies on these fuels as the primary source of domestic energy. Use of solid fuels has multiple impacts, on individuals and households, and on the local and global environment. For individuals, the impact on health can be considerable, as household air pollution from solid fuel use has been associated with acute lower respiratory infections, chronic obstructive pulmonary disease, lung cancer, and other illnesses. Household-level impacts include the work, time, and high opportunity costs involved in biomass fuel collection and processing. Harvesting and burning biomass fuels affects local environments by contributing to deforestation and outdoor air pollution. At a global level, inefficient burning of solid fuels contributes to climate change.

Improved biomass cookstoves have for a long time been considered the most feasible immediate intervention in resource-poor settings. Their ability to reduce exposure to household air pollution to levels that meet health standards is however questionable. In addition, adoption of improved cookstoves has been low, and there is limited evidence on how the barriers to adoption and use can be overcome. However, the issue of household air pollution in low and middle income countries has gained considerable attention in recent years, with a range of international initiatives in place to address it. These initiatives could enable a transition from biomass to cleaner fuels, but such a transition also requires an enabling policy environment, especially at the national level, and new modes of financing technology delivery. More research is also needed to guide policy and interventions, especially on exposure-response relationships with various health outcomes and on how to overcome poverty and other barriers to wide-scale transition from biomass fuels to cleaner forms of energy.

Keywords: air pollution, exposure, biomass fuel, cookstove, indoor environment, health effects, sustainable development, sub-Saharan Africa

Solid Fuels

Biomass fuel is any plant or animal material that is burned for energy (Fullerton, Bruce, & Gordon, 2008) and includes wood, dung, or crop residues; wood (also referred to as firewood or fuel wood) is the most common form of biomass fuel. Together, biomass fuels and coal, referred to as solid fuels, are the main source of household energy for cooking and heating for almost half of the world’s population (International Energy Agency [IEA], 2011); 3 billion people lack access to modern energy1 with 2.7 billion relying on biomass fuels and 0.3 billion relying on coal. The use of biomass as fuel goes back to prehistoric times when humans first moved to temperate climates and it became necessary to construct shelters and use fire inside them for cooking, warmth, and light; the role of fire can be attested to by the soot found in prehistoric caves (Bruce, Perez-Padilla, & Albalak, 2000; Jones, 1999).

Historically, research and public health policies addressing population exposure to air pollution have focused mostly on urban outdoor settings. Early global and national concerns about use of biomass fuels concentrated on the impact on the environment, in particular deforestation driven by use of wood for fuel (Budds, Biran, & Rouse, 2001; Pearson & Stevens, 1989), rather than impact on health.

While household air pollution (HAP) has received attention in the developed world, and guidelines on household air quality have been developed (WHO, 2010), the issue has received less attention in many low and middle income countries (LMICs) until relatively recently. It was not until the 1980s and 1990s that evidence began to emerge showing the link between traditional cooking practices and health. Pioneering studies in Papua New Guinea, Nepal, Guatemala, India, China, and other countries in Oceania, Latin America, and Africa provided strong indications associating cooking smoke with household air pollution and adverse respiratory health outcomes (Bruce et al., 2000; Chen, Hong, Pandey, & Smith, 1990; Clearly & Blackburn, 1968; Dary, Pineda, & Belizán, 1981; Pandey, Boleij, Smith, & Wafula, 1989; Pandey, Regmi, Neupane, Gautam, & Bhandari, 1984). However, many of these studies had limitations. Most were observational and inadequately controlled for confounding factors (Bruce, Neufeld, Boy, & West, 1998); most also relied on proxy measures of exposures such as type of fuel used, tears while cooking, or carrying of children on the back while cooking (Ellegård, 1997).

Increasing numbers of studies suggesting a link between biomass fuel and health, coupled with evidence from outdoor air pollution, tobacco smoking, and environmental tobacco smoke exposure, led to increased global attention to the issue. The World Bank designated household air pollution in LMICs as one of the four most critical global environmental problems (Budds et al., 2001). The 2002 World Health Report (WHO, 2002) included household air pollution from biomass fuels as a major risk factor for disease, responsible for 1.6 million deaths, and as the second leading environmental contributor to ill health after unsafe water and sanitation. The evidence has continued to grow since, with better-designed studies, including randomized controlled trials, demonstrating the exposure-response relationship (Smith et al., 2011).

Current estimates (Lim et al., 2012) identify household air pollution from solid fuel use as the leading environmental contributor to ill health. The health risk is concentrated in LMICs where biomass is used as domestic fuel. Many of the most polluted domestic household environments are in remote settings in sub-Saharan Africa and South Asia where the majority of the population use traditional biomass fuels for cooking and heating (WHO and UNDP, 2009).

Sources of Household Air Pollution in Low and Middle Income Countries

There are a variety of sources of household air pollution in LMICs. The main sources are indoor combustion, primarily the use of solid fuels for cooking and heating. Other indoor combustion sources are lighting, for example, candles and kerosene lamps; tobacco smoking; use of incense and mosquito repellents; and cooking oils from high temperature frying. An estimated 80% of smokers reside in LMICs, where smokers are less likely to quit and less likely to have cessation programs or support available to them (Jha & Chaloupka, 2000). Pollution from neighboring households cooking with solid fuels (Figure 1) also has an important impact on household air pollution.

On a regional scale, it is estimated that household air pollution from solid fuel use accounts for 16% of ambient pollution levels (Lim et al., 2012). Land clearance for agriculture through burning, and burning of agricultural wastes (Figure 2), are additional outdoor pollution sources that affect the indoor environment, particularly in rural communities (Millennium Ecosystem Assessment, 2005).

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 2. Burning of sugarcane as part of the harvesting process in Malawi.

Photo credit: SEI ESPA Project.

Household air pollution sources are also associated with modernization in LMICs. For instance, a shift from biomass fuel to kerosene for cooking introduces a range of new pollutants such as black carbon. Similarly, as the housing stock shifts from highly permeable temporary structures to better sealed permanent ones, other household sources of air pollution become more prevalent, especially those related to building materials, household furnishings, and cleaning agents (EHEI, 2010). In urban settings, road traffic and industrial emissions have an impact on household as well as outdoor air quality, and tobacco smoking may also be more prevalent.

The major sources of household air pollution and the pollutants associated with each source are summarized in Table 1, focusing mainly on household-level sources.

Table 1. Household Sources and Types of Pollutants in Low and Middle Income Countries


Indicative pollutants

Solid fuel use (biomass and coal) for household cooking and heating

PM, CO, PAHs, NOx, VOCs, sulphur oxides, arsenic, fluorine, aldehydes

Kerosene stoves and lamps

PM, CO, NOx, SO2

Incense, mosquito coils, and candles

PM, CO, NOx, CH4, NMHC, VOCs, and carbonyl compounds

Tobacco smoke

Complex mixture of several compounds: more than 40 known or suspected human carcinogens, PAHs, N-nitrosamines, irritants, PM, CO

Cooking processes (e.g., high-temperature frying)

PM, organic compounds (fatty acids, diacids, and steroids), n-alkanes, and PAHs

Consumer products (e.g., paints, furniture and household fabrics, detergents, disinfectants)

VOCs, semi-VOCs

Construction materials used in remodeling or demolition

VOCs, semi-VOCs, aldehydes, asbestos, lead

Building characteristics related to moisture and ventilation

Biological pollutants (fungal spores, mites, endotoxins, glucans)

Outdoor pollution

PM10, NO2, SO2, O3

Note: PM: Particulate Matter; CO: Carbon Monoxide; PAHs: Polycyclic Aromatic Hydrocarbons; NOx: Nitrogen Oxides; VOCs: Volatile Organic Compounds; SO2: Sulphur Dioxide; O3: Ozone; NMHC: Non-Methane Hydro-Carbons

While all these household air sources of pollutants have important public health implications, cooking with biomass fuels remains the predominant source on a global scale and, in particular, in rural areas of LMICs. Consequently, household air pollution from this source is the main focus of the following sections.

Household Solid Fuel Use in Low and Middle Income Countries

Figure 3 shows the proportion of households in LMICs using different types of fuel for cooking; it also shows that wood is the predominant type of fuel used.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 3. Proportion of population in LMICs relying on different types of cooking fuels in 2007.

Source: WHO and UNDP (2009).

The shift from biomass fuels and coal to more modern and cleaner forms of energy is occurring at a very slow pace in low and middle income counties, with the slowest transition in sub-Saharan Africa. Even in African countries with significant fossil fuel resources, such as Angola, Gabon, and Nigeria, biomass fuels still constitute the main source of household energy for the majority of the population.

Biomass fuel use is strongly correlated with the level of economic development, so the overall proportions shown in Figure 3 differ considerably between regions in the developing world. While around 50% of the overall population in LMICs relies on biomass fuel, the proportion is around 80% in sub-Saharan Africa. Almost 33% of the population in LMICs overall is estimated to use liquefied petroleum gas for cooking, but in the least developed countries and sub-Saharan Africa, the proportion is below 10%. Even within regions there is significant variation in access to modern energy. For example, in Latin America and the Caribbean, 62% of the population does not have access to modern energy in Haiti compared with only 2% in Brazil. In sub-Saharan Africa, more than 95% of the population does not have access to modern energy in countries such as Burundi, Chad, and Liberia, compared with 25% in South Africa and 1% in Mauritius (WHO and UNDP, 2009).

Table 2 shows regional variations in biomass fuel use, with Asia having the highest number and sub-Saharan Africa having the highest proportion of people using biomass.

Table 2. Biomass Fuel Use by Region.


Population relying on traditional use of biomass

Percentage of population relying on traditional use of biomass



Developing countries






     Sub-Saharan Africa



     North Africa



Developing Asia









Latin America






Middle East






Source: IEA 2014

There is also major rural-urban disparity in population and, hence, in biomass fuel consumption in these regions. For example, around 68% of India’s population live in rural areas, where biomass fuels account for 78% of energy use (World Bank Statistics, 2015). In most sub-Saharan Africa countries, more than 80% of the population reside in rural areas (World Bank Statistics, 2015).

Economic factors, including household poverty and purchasing power, play an important role in limiting transition to modern energy, but other factors also play a role. Even where modern and cleaner fuels are available, some households continue to use biomass fuels. This reflects the complexity of the transition process at household level, which involves energy services demanded by users, the technologies used to provide those services, and the fuels required for the technology (Kowsari & Zerriffi, 2011). Factors other than cost that prevent people from changing their energy source include lack of access to modern fuels (Zhou et al., 2011); lack of modern energy technology options for burning fuels, such as clean cookstoves and efficient charcoal kilns; lack of access to credit to address high up-front costs; and poor reliability of supplies.

In addition to barriers to change, it is projected that the number of people using biomass fuels will rise as the population increases in sub-Saharan Africa and South Asia (IEA, 2011). Consequently, the health burden associated with household air pollution from biomass fuel use will remain an important research and development concern.

Pollutants in Biomass Fuel Emissions

Wood consists primarily of cellulose (50–70% by weight) and lignin (30% by weight). In addition, it has small amounts of low-molecular-weight organic compounds (for example, resins, waxes, and sugars), and inorganic salts. Wood combustion is complex and involves simultaneous chemical reactions in the liquid, solid, and gas phases (L’Orange et al., 2012). Four processes are involved: drying, pyrolysis, combustion, and surface oxidation, which occur at different temperatures.

Unlike coal, biomass contains no sulphur or mercury components and should burn cleanly, emitting only water vapor and carbon dioxide (CO2). However, clean combustion is not achieved with simple household combustion stoves (Figure 4), which only convert 10–15% of biomass into useful cooking energy. The rest is converted to what is known as the products of incomplete combustion (PICs), a complex mixture of chemical substances that can be present in the gas or particle phase (Naeher et al., 2007). Most of these substances are known pollutants that are highly regulated due to their health effects. Table 3 shows the typical chemical compounds emitted during biomass fuel combustion and their health effects.

Table 3. Main Constituents of Biomass Smoke and Health Effectsa



Health Effects

Inorganic gases

  • CO

  • NO2

  • Asphyxiant

  • Irritant, adverse respiratory effects


Acrolein, Formaldehyde

  • Eye and nasal irritation

  • Respiratory neoplasms, genotoxic and carcinogenic effects (nasal)

Free radicals

  • Semiquinone type

  • Radicals

Oxidative stress at sites of deposition resulting in lung damage


  • 1,3-butadiene

  • n-hexane

  • PAHs

  • Benzene

  • Respiratory irritations, reproductive and developmental effects, carcinogenic

  • Respiratory irritations, neurotoxicity

  • Carcinogenic

  • Neurological effects, blood disorders, aplastic anaemia (a risk factor for acute non-lymphocytic leukemia), excessive bleeding, suppressed immunity

Chlorinated organics

  • Methylene chloride and methyl chloride

  • Dioxin

  • Neurological effects; effects on the heart rate, blood pressure, liver, and kidneys

  • Liver, kidney, spleen, and central nervous system (CNS) effects.

  • Reproductive and developmental problems, damage to immune system, interference with hormones, carcinogenic

Particulate Matter

PM2.5 (particles with diameter smaller than 2.5 micrometres) and PM10 (particles with diameter smaller than 10 micrometres)

  • Premature death, cardiovascular disease, aggravated asthma, decreased lung function, and increased respiratory symptoms (e.g., irritation of the airways, coughing, and difficulty breathing)

  • Effects on breathing and respiratory system, damage to lung tissue, cancer, and premature death


Lung inflammation

a Compiled from various sources including IARC Monograph 95, a review of wood smoke health effects (Naeher et al., 2007) and USEPA IRIS website.

Household Concentrations and Exposure Levels

Measurement Methods and Concentrations

Exposure to air pollution from biomass fuel use indoors is a problem for three main reasons:

  1. 1) Activities involving biomass fuel use, such as cooking, are carried out on a daily basis and several times a day.

  2. 2) Pollutants are released at a time when people are indoors and usually near the pollution source; this includes the cook, as well as other family members, especially young children.

  3. 3) Ventilation is often poor, due to lack of chimneys or vents in kitchens or housing; this results in pollutants being retained indoors for long periods (Figure 5).

The number of studies that have measured household air pollution exposure from biomass fuel use is still relatively limited. Generally, studies have measured particles (Total Suspended Particles (TSP), PM10, PM2.5, and, more recently, ultrafine particles), and carbon monoxide.

Historically, the cost of including chemical measurements in large studies to determine direct individual exposure to household air pollution has been a major obstacle to accurate exposure assessments. In addition, in many LMICs, there is limited infrastructure to support air quality monitoring, for example, power supply, laboratory facilities, and skills for processing; and analyzing collected samples. Studies that have measured particles directly have had to transport samples to laboratories in high-income countries for analysis (Dionisio et al., 2008; Fullerton et al., 2009; Ochieng et al., 2017). Due to these challenges, studies have often opted to measure indirect exposure indicators. One review of studies linking household air pollution exposure and acute respiratory infection, the most studied health outcome, found only three studies that had measured actual pollution levels (Emmelin & Wall, 2007), and none of the three studies had included individual exposure measurement. A more recent review of studies on household air pollution exposure from biomass use in LMICs (Quansah et al., 2017) shows an increase in the number of studies that have entailed actual pollutant measurements, even though there is still a significant number that have utilized proxy measurements.

Figure 6 shows the types of measurements that have been used to characterize exposure to household air pollution in LMICs. The most basic type of measurement involves regional categorization by type of fuel use, for example, biomass fuels versus modern fuels. This type of measurement is usually done through surveys, such as the National Census or Demographic and Health Surveys. At household and individual levels, there can be direct or indirect measurements of exposure, or a combination of both.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 6. Exposure assessment pyramid.

Source: Smith, Mehta & Feuz (2004).

A number of studies of household exposure have focused on area measurements in cooking locations. Among the first of these was a Level 5 type of study in rural Kenyan households (Ezzati, Saleh, & Kammen, 2000), which combined area monitoring of PM10 in different micro-environments with time-activity diaries for individual household members. This study demonstrated that there are large variations in exposure of different household members within the same household, and that grouping individuals into a single exposure category (for example, biomass users) reduces the variability of the explanatory variable in the exposure-response relationship, thereby decreasing the reliability of the estimation of its parameters. In such settings, there are many inter- and intra-household variations in exposure that cannot be understood without detailed monitoring.

The number of studies involving detailed exposure characterization has, however, increased. An example is the Randomised Exposure Study of Pollution Indoors and Respiratory Effects (RESPIRE) studies in Guatemala. These, and other recent studies (Ochieng et al., 2013; Figure 7), have entailed individual measurements of exposure and even, in some instances, biomarkers of exposure such as metabolites in urine (Riojas-Rodriguez et al., 2011).

The findings of these studies support the need for measurement of individual exposure in order to be able to inform public health policy. For example, the studies found that use of an improved chimney stove was associated with a 90% reduction in indoor CO concentrations; however, reductions in personal exposure were more modest (50%) and the health benefits were not significant for severe pneumonia (Smith et al., 2011). Similarly, in Mexico, a 74% reduction in 48-h PM2.5 concentrations was observed in kitchens but only a 35% reduction in personal exposures (Cynthia et al., 2008).

One approach that has been taken to overcome the challenge of monitoring household air pollution in LMICs is the use of proxies that are easier to measure, such as CO as a proxy for PM10 or PM2.5. A number of studies have shown that CO and PM generally correlate well in the highly polluted conditions that characterize biomass fuel use (Naeher et al., 2001; Northcross, Chowdhury, McCracken, Canuz, & Smith, 2010). Furthermore, CO passive samplers (for example, Dragger Diffusion Tubes and Lascar CO Loggers) are a convenient means of measuring personal exposure to air pollution as they are portable, relatively inexpensive, and do not require an external power supply. Currently, passive samplers are the main method used to measure personal exposure in young children.

Biomonitoring is another approach that can reduce exposure misclassification. Levels of biomarkers represent the absorbed dose of a chemical, integrated across all micro-environments and routes of exposure (Riojas-Rodriguez et al., 2011). Those that have been evaluated as metrics of biomass smoke exposures include carboxyhemoglobin, exhaled CO, urinary methoxyphenol metabolites, and urinary PAH metabolites (Clark, Paulsen, Smith, Canuz, & Simpson, 2007; Riojas-Rodriguez et al., 2011; Simpson & Naeher, 2010; Torres-Dosal et al., 2008).

Table 4 summarizes the results of selected studies that have measured household air pollution from biomass fuel use and compares the concentrations measured with international air quality guidelines and standards. As Table 4 shows, use of biomass fuels indoors leads to levels of air pollution that are many times higher than international household air quality guidelines.

Table 4. Example of Pollutant Concentrations Indoors in Households Using Biomass and Recommended Guidelines

Study and country

Pollutant studied

Measured concentrations (24-hour means)

Air Quality Guidelines

WHO Indoor Air Quality Guidelines

U.S. National Ambient Air Quality Standards

EU Air Quality Standards

Ezzati and Kammen (2001); Kenya


3,000–10,000 µg/m3

50μ‎g/m3 (24-hour mean) 20 μ‎g/m3 (annual mean)

150 µg/m3 (annual mean)

50μ‎g/m3 (annual mean; not to be exceeded > 35 times a year)

Jiang and Bell (2008); China


100.6 µg/m3

25μ‎g/m3 (24-hour mean) 10 μ‎g/m3 (annual mean)

12 µg/m3 (annual mean) 35 µg/m3 (24 hour mean)

50μ‎g/m3 (annual mean)

Ochieng et al. (2013); Kenya


11.8 ppm 24-hour mean; peaks of 300 ppm

86 ppm (15 minutes average) 30 ppm (1 hour mean) 8.7 ppm (8 hour mean) 6 ppm (24 hours mean)

9 ppm (8 hour mean) 35 ppm (1 hour mean)

8.7 ppm (8 hour mean) 200 µg/m3 (1 hour mean)

Kumie et al. (2009); Ethiopia


97 µg/m3

200 μ‎g/m3 (1-hour mean)

100 µg/m3 (annual mean)

40 µg/m3 (annual mean)

Liu et al. (2007); China


500 µg/m3

20 μ‎g/m3 (24-hour mean)

75 ppb (99th percentile of 1-hour daily maximum concentrations)

125μ‎g/m3 (annual mean; not to be exceeded ≤3 times a year)

Sinha et al. (2006); India


75.4–83.2 µg/m3

No safe levels. The concentrations of airborne benzene associated with an excess lifetime risk of 1/10 000, 1/100 000 and 1/1000 000 are 17, 1.7 and 0.17 μ‎g/m3, respectively


5 µg/m3 (annual mean)

Sinha et al. (2006); India


3.1–9.5 µg/m3

0.00026 µg/m3 (weekly average)



Wang et al. (2008); China


72.1 to 554.4 ng/m3

No safe levels. Concentrations for lifetime exposure to B[a]P producing excess lifetime cancer risks of 1/10 000, 1/100 000 and 1/1 000 000 are approximately 1.2, 0.12 and 0.012 ng/m3, respectively


1 ng/m3 (annual mean; expressed as concentration of Benzo(a)pyrene)

Determinants of Exposure

Exposure refers to the concentration of pollution in the immediate breathing environment during a specified period of time. As highlighted earlier, poverty is a key determinant of fuel choice and, hence, of exposure to household air pollution in LMICs. Together with energy policies and market systems, they can be described as distal or macro-environmental determinants of exposure (IARC, 2010). These determinants can be tackled at national and international levels through policies and institutional frameworks, as discussed in the concluding sections of this article.

Three broad determinants of exposure operate at more proximal levels (micro-environmental determinants):

  1. 1) Pollutant concentration in a specific setting and time (micro-environment)

  2. 2) Distance from a pollution source

  3. 3) Time spent at this location

Pollutant concentrations and exposure can vary both temporally (morning and afternoon, day and night, cooking and non-cooking) and spatially (vertical stratification, near door, window). Exposure varies from day to day and from subject to subject (i.e., within and between subject variability). Table 5 provides an overview of important proximal determinants associated with measured pollutant concentrations in various settings.

Table 5. Determinants of Household Air Pollution From Biomass Fuel Use Assessed in Selected Studies


Associationa with pollutant measured






Stove & fuel use

Stove typeb



Ochieng et al. (2013)

Amount of fuel used


Riojas-Rodriguez et al. (2001)


Balakrishnan et al. (2004)

Fuel moisture content


Ochieng et al. (2013)

Cooking duration


Balakrishnan et al. (2004)

Number of meals


Balakrishnan et al. (2004)

Stove quality/maintenance



Clark et al. (2010)


Naeher et al. (2000)

Housing design & ventilation

Presence, number or size of windows/chimney/eave spaces/doors


Riojas-Rodriguez et al. (2001)


Dasgupta et al. (2006)



Rumchev et al. (2007)


Bruce et al. (2004)


Ochieng et al. (2013)

Kitchen size/volume



Rumchev et al. (2007)


Clark et al. (2010)


Bruce et al. (2004)

Kitchen construction material


Dasgupta et al. (2006)


Clark et al. (2010)

Number of rooms/partitions


Clark et al. (2010)

Population & behavior

Cooking location (indoor vs. outdoor)


Balakrishnan et al. (2004)


Albalak et al. (1999)

Opening doors and windows


Dasgupta et al. (2006)

Child location


Bruce et al. (2004)

Distance from stove


Ezzati and Kammen (2001)


Balakrishnan et al. (2004)

Cooking roles


Ezzati and Kammen (2001)


Balakrishnan et al. (2004)

Time spent at home


Balakrishnan et al. (2004)


Baumgartner et al. (2011)

Age (proxy for cooking roles)


Baumgartner et al. (2011)


Ochieng et al. (2013)

Environment & climate

Ambient pollution


Dasgupta et al. (2006)


Dionisio et al. (2010)



Balakrishnan et al. (2004)


Dionisio et al. (2010)


Baumgartner et al. (2011)

(a) In the table, ×is used to denote a positive association between the determinant of exposure (e.g., stove type) and the pollutant measured.

(b) There are several studies associating stove type with concentrations of various pollutants from biomass fuel combustion. For a more detailed review, see Ochieng et al., 2013.

Key determinants of pollutant emissions are fuel and stove types. The association between fuel type (clean vs. biomass) and exposure has been well established, and fuel type has been used in many studies as a proxy for exposure. For example, a study in Bangladesh found natural gas and kerosene users to have significantly lower exposure to PM10 than biomass fuels users (Dasgupta, Huq, Khaliquzzaman, Pandey, & Wheeler, 2006). However, households using clean fuels but living in close proximity to those using biomass fuels may experience elevated exposure to air pollution coming from other households. Similarly, in Accra, Ghana, cooking area PM concentrations were lowest in the neighborhood with higher socioeconomic status (proxy for use of clean fuels), but not for those households in close proximity with biomass fuel users (Dionisio et al., 2010). Living in a community where all households use biomass fuels was associated with 1.5–2.7 times higher PM concentrations after adjustment for other predictors of PM, and community prevalence of biomass use had a stronger association with PM concentration measured at the household level than the household’s own fuel choice.

Stove type (traditional or improved) is an important determinant of exposure to household air pollution. Many studies have shown significantly lower concentrations of PM and CO from use of improved stoves, but some studies have shown no significant improvement in household air quality associated with improved stove use. A number of factors determine stove performance, including design, quality, and how it is used.

Personal exposure patterns will also vary by individual characteristics such as age and gender, which determine activity patterns. Pollution from biomass fuel use has been shown to be highly episodic, with peak concentrations occurring when lighting the fire and adding fuel (Fullerton et al., 2009; Ochieng, 2013). Women’s exposure can be more than twice that of men within the same household because they tend to be responsible for cooking (Ezzati et al., 2000). Children also often experience high exposure because of being close to their mothers while they cook.

Housing characteristics and ventilation are equally important predictors of exposure. Whether or not doors or windows are opened can create substantial differences in exposure. In one study, households that did not open windows or doors while cooking had a 75% higher exposure relative to those who always ventilated their houses (Baumgartner et al., 2011).

Seasonal changes in fuel type, combustion frequency, and behavior have considerable impact on exposure. For instance, exposure tends to be higher in winter than summer, due to cooking indoors rather than outdoors, use of fires to heat the home, and keeping doors and windows closed.

As a result of these factors, there can be large variations in indoor pollutant concentrations and personal exposure within the same household and between households. Ignoring these factors may result in exposure misclassification, especially where area measurements or proxy measures of exposure are applied. At the same time, the range of factors that influence exposure offers scope for a range of interventions to tackle household air pollution although, since fuel and stove type remain the most important predictors of household air pollution in LMICs, these should be the main focus of intervention.

Impact of Household Solid Fuel Use on Health

Household air pollution from solid fuel use is the most important environmental risk factor for ill health in LMICs (Lim et al., 2012). Globally, it is the fourth leading risk factor for ill health, only exceeded by high blood pressure, tobacco smoking, and alcohol use (Lim et al., 2012).

WHO uses the Global Burden of Disease (GBD) to quantify the health impact of diseases, injuries, and risk factors, so that health systems can be improved and disparities eliminated. The GBD reflects both the prevalence of a given disease, injury, or risk factor and the relative harm it causes. The estimated burden of ill health from household solid fuel use has increased over time as the methodology used in the estimates and the body of evidence about health effects has developed. In the 2012 GBD estimates, the contribution of household air pollution2 from solid fuel use as a risk factor had doubled since the 2000 estimates (WHO, 2002), with 4.3 million deaths and 5.3% of global DALYs3 attributed to it (Lim et al., 2012). Household air pollution is now considered to be the leading risk factor for ill health in LMICs overall, at number one in South Asia and number two in sub-Saharan Africa (Lim et al., 2012; WHO, 2014).

Previous estimates of disease burden from household air pollution were mainly driven by acute lower respiratory infections (ALRI) in children and chronic obstructive pulmonary disease (COPD) in women, where consistent associations have been found between exposure and health outcomes. Globally, about 20% of all deaths in children under the age of 5 years are due to acute lower respiratory infections, with almost all of these deaths occurring in LMICs. A meta-analysis of 27 studies for morbidity endpoints in children from households using solid fuel reported an Odds Ratio of household air pollution and ALRI of 1∙78 (95% CI 1∙45–2∙18) (Dherani et al., 2008). A more recent meta-analysis of eight studies by Po and colleagues (Po, Fitzgerald, & Carlsten, 2011) reported a Risk Ratio for ARI of 3∙53 (1∙93–6∙43).

Chronic obstructive pulmonary disease is also a leading cause of morbidity and mortality, with WHO predicting in 2004 that it will be the third leading cause of death worldwide by 2030 (Mannino & Kiri, 2006). But according to GBD 2012, COPD is already the third leading cause of death worldwide. In developed countries, smoking is the main risk factor for COPD, accounting for 80% of cases, but 90% of COPD deaths globally occur in low and middle income countries, and these deaths are concentrated among non-smoking rural women. A meta-analysis of 23 studies (Kurmi et al., 2010) relating biomass fuel use to COPD showed an association with both lung function diagnosed COPD (OR 2.29, 95% CI 0.70–7.52) and doctor-diagnosed COPD (OR 2.96, 95% CI 2.01–4.37), with a combined OR of 2.80 (95% CI 1.85–4.23). The pooled effect estimate for chronic bronchitis was 2.32 (95% CI 1.92–2.80). A meta-analysis by Hu and colleagues (Hu et al., 2010) found that people exposed to biomass smoke have an OR of 2.44 (95% CI, 1.9–3.33) for developing COPD, relative to those not exposed to biomass smoke. These findings have been supported by a more recent meta-analysis of 25 studies relating biomass fuel use to respiratory diseases (Po et al., 2011). In this analysis, the OR for chronic bronchitis was 2.52 (95% CI 1.88–3.38), and for COPD was 2.40 (95% CI 1.47–3.93).


The substantial change in the risk estimates between 2000 and 2012 is due largely to improvement in measurement methods (for example, use of a pollutant-based approach to estimating the health risks as opposed to the previous fuel-based approach), to factoring in the contribution of household solid fuel use to outdoor air pollution, and to inclusion of additional health outcomes (for example, cardiovascular disease and lung cancer) not previously included due to lack of sufficient evidence. The RESPIRE studies in Guatemala (McCracken, Smith, Diaz, Mittleman, & Schwartz, 2007) and other recent studies have demonstrated an association between biomass smoke exposure and high blood pressure, a risk factor for cardiovascular disease. A meta-analysis comparing the exposure-response relationships between urban ambient particulate matter, passive cigarette smoking, and active cigarette smoking has shown a positive relationship with ischemic heart disease, cardiovascular disease, and cardiopulmonary disease interpolating the response across the range of exposures encountered in low and middle income country indoor settings (Burnett et al., 2014; Pope et al., 2009). In the 2010 GBD, household solid fuel use accounted for 18% of DALYs attributed to cardiovascular disease. Direct epidemiological evidence of the relationship between household air pollution and cardiovascular disease is needed to improve estimates of the cardiovascular disease burden of household solid fuel use.

Epidemiological evidence continues to accumulate linking exposure with other health outcomes, which are not included in the GBD estimates. One example is low birth weight, which is an important factor in under-five mortality. Carbon monoxide (CO) is the most abundant compound produced during biomass fuel combustion, and CO concentrations measured in homes burning biomass as fuel are comparable to CO levels from environmental tobacco smoke exposure, and in some instances, to active smoking (Bruce et al., 2000). The high population exposure to biomass fuel use in pregnancy and high prevalence of low birth weight in LMICs settings means that if the risk estimates of low birth weight are confirmed by further studies, the population-attributable risk associated with CO exposure from biomass fuel use would be substantial.

Other health outcomes for which there is epidemiological evidence suggesting a link with household air pollution from biomass fuel use include eye disease, tuberculosis, DNA damage, and neurological impairment in children of mothers exposed to high levels of smoke during pregnancy. For most of these outcomes, the results of different studies have been mixed and further studies are needed to strengthen the evidence. For instance, a case-control study in India (Tanchangya & Geater, 2011) that accounted for confounding raised uncertainties about the link between biomass fuel use and cataracts reported in an earlier India study.

Broader Impacts of Biomass Fuel Use

At the global level, household fuel use has impacts beyond health. Carbon dioxide (CO2) and other greenhouse gases that are present in the emissions from biomass cooking stoves, and their global warming potential, have been assessed in various studies (Bailis et al., 2003; Venkataraman & Rao, 2001). Emissions from household biomass fuel use also include methane (CH4) and other precursors of tropospheric ozone (O3), as well as black carbon emitted as soot. These three compounds are often referred to as short-lived climate pollutants (SLCPs) as they have a short lifetime in the atmosphere (from days to a decade) relative to CO2, and have substantial climate impacts. Black carbon is thought to be the second largest contributor to climate change after carbon dioxide (Ramanathan & Carmichael, 2008).

The global contribution of household burning of biomass to climate-influencing products of incomplete combustion (PICs) is still uncertain, due to wide distribution and often remote location of households, as well as relatively complex assessment methods required (Roden, Bond, Conway, & Pinel, 2006). More accurate emission estimates are needed to better understand the impact of household air pollution from solid fuel use on climate change.

On a more local scale, unsustainable use of wood for fuel can create large pressures on vegetation, leading to loss of ecosystems, deforestation, soil degradation, and erosion (Foell, Pachauri, Spreng, & Zerriffi, 2011). Collecting and processing biomass for fuel also has health and opportunity costs. Women and girls who are responsible for this can spend up to 50 hours a month walking to the fuel source and gathering fuel in rural areas (Parikh, 2011). Studies in South Asia and Africa have highlighted the associated health impacts, which include hardship, stress, physical exhaustion, and various body aches for women who often have to travel long distances in search of fuel (Matinga, 2010; Parikh, 2011). The opportunity cost can include less time available for child care and for participating in gainful economic activities.

Measures to Reduce Household Air Pollution From Solid Fuel Use

Interventions to reduce household air pollution from solid fuel use can be classified into three broad categories: changes to the pollution source (stove and fuel); changes to the living environment (housing and ventilation); and changes in user behavior. Each of these is discussed below.

Improved Cookstoves

Some authors have argued that there is no such thing as a dirty fuel, only dirty technology (Hulscher, 1998, in Budds et al., 2001). Improved cookstoves (Figure 8) are designed to provide better combustion, that is, clean burning; and to optimize heat transfer, that is, more energy reaching the pot. Better combustion contributes directly to reduced emissions of PICs. However, better combustion in itself does not appreciably reduce fuel use if only a small proportion of the energy released from the fuel makes it to the cooking pot (Bryden et al., 2005). Excess fuel use in turn leads to more emissions. On the other hand, better heat transfer from stove to cooking pot can lead to reduced emissions through reduced fuel use, as well as reducing the need to collect word for fuel. A well-designed stove should optimize both combustion efficiency and heat transfer.

In the past, improved stoves were promoted with the aim of addressing energy and environmental issues such as fuel shortages, deforestation, and desertification. Evaluation of their success was based on heat transfer efficiency, not on reducing household air pollution or health benefits. WHO underscored this point in a 2006 report, noting that “to date, only one study has investigated the impact of an improved stove on childhood pneumonia and women’s respiratory health. Therefore, we cannot yet draw clear-cut conclusions about which interventions are most effective in saving children’s and women’s lives . . .” (WHO, 2006b).

Use of the term “improved cookstoves” without qualification of the improved aspects, is no longer encouraged, given the variation in stove design and performance and in the aims of those designing and promoting them (Smith & Dutta, 2011). There are now guidelines for evaluating cookstove performance that reflect performance in the areas of fuel efficiency, household air quality, emissions of particulate matter and carbon monoxide, and safety; and work is underway to turn the guidelines into ISO standards.

RESPIRE was the first randomized controlled trial to measure the health benefits of an improved stoves intervention. The trial showed a highly nonlinear relationship between household air pollution exposure and pneumonia in children below 18 months, with the largest health benefits achieved with only very low levels of exposure (Smith et al., 2011). A key recommendation was that a switch to clean fuels or highly advanced biomass combustion stoves (e.g., with fans) could reduce the burden of pneumonia associated with household air pollution. Others have also argued that it is extremely difficult to burn cleanly a highly variable solid fuel like biomass in small, low-cost devices (Naeher et al., 2007; Smith & Sagar, 2014) and, in a recent editorial, Smith and Sagar (2014) reinforce this, noting that, in spite of 50 years of promotion of smokeless Chulha stoves in India, there has been no demonstrable impact on health.

The poor quality of many so-called improved stoves, lack of maintenance, and user behavior partly accounted for their variable performance. Several studies have observed parallel use of both traditional and improved stoves, which would dilute the exposure reduction potential for improved stove users (Adriana Teresa et al., 2009; Cynthia et al., 2008; Edwards et al., 2007; Ochieng et al., 2013; Romieu et al., 2009). Chimney stoves that vent smoke from indoor to outdoor locations where people still spend time would also not contribute to significant reduction of personal exposures. Even where improved stoves are used consistently, as was the case in RESPIRE study population, the 50% reduction in household air pollution observed did not translate to significant health benefits.

Fuel Switching

Switching from biomass to modern fuels, such as electricity or natural gas, offers the most effective means of reducing exposures to household air pollution in LMICs. A shift from cooking with biomass to clean fuel can reduce pollutant emissions per meal by a factor of 100 and more Jetter & Kariher (2009).

There are practical challenges with this option. These include access to and reliability of supplies—one billion people in LMICs do not have access to electricity supply and supplies of LPG tend to be intermittent. Affordability is also a challenge, in particular the recurrent cost of modern fuels compared with low or no monetary cost of biomass fuels, as is acceptability. A number of studies have also shown that people do not always make a complete switch to modern fuels; instead they prefer to use multiple fuel types for different purposes (Masera, Saatkamp, & Kammen, 2000). This is the case even in developed countries, where people use multiple devices and fuels for different specialized tasks. The energy ladder model (Leach, 1992), which hypothesizes that people shift from more polluting to less polluting fuels with increasing income has thus been found to be an oversimplification of energy use patterns in LMICs.

However, a near total switch to clean fuels is the only intervention that is known to lower household air pollution exposure to levels that would impact significantly on health, so the obstacles to accessing clean fuel need to be addressed. For countries like India, where 35% of the population already cook regularly with electricity and gas, efforts need to focus on extending supply to the remaining 65% who still depend on biomass. For countries in sub-Saharan Africa and other least developed countries where electricity and LPG penetration is low and the shift to clean fuels will take longer, improved cookstoves could provide a transitionary measure. Nevertheless, the long-term goal must still be to make modern energy accessible to all, given the evidence that shows that improved cookstoves offer only marginal health benefits. Achieving this goal requires concerted global efforts and policy measures, as discussed later in this article.

Other Interventions

Besides fuel and stove type, other determinants of household air pollution exposure include housing design, ventilation and behavioral practices. As shown in Table 5, several studies have found ventilation to have an important influence on exposure and mechanisms that remove smoke from the indoor environment have been seen as one way of tackling the challenge of household air pollution. Based on this, chimneys, flues, and hoods have been promoted in some settings. The extent to which they can reduce pollution and adverse health outcomes has, however, not been fully tested. Biomass fuel burning is associated with extremely high pollutant concentrations of short durations (up to 30,000 µg/m3 of PM2.5) when a fire is lit or fuel is added (Ezzati et al., 2000; Fullerton et al., 2009; Ochieng, 2013). Improving ventilation without making any changes to the stove or fuel, which is the source of these emissions, may not significantly reduce exposure for the person who is cooking, because the peak concentrations of pollutants during cooking have a strong influence on the overall mean exposures. It could, however, help to reduce exposure for other household members, including children, who may not be as close to the fire during peak emission episodes.

Housing and ventilation interventions are likely to face similar adoption challenges as improved cooking stoves. For example, in a program in Kenya that installed hoods over fireplaces practical challenges, including women hitting their head on the hoods due to the small size of and lack of light in kitchens and the time women had to spend on cleaning the hoods to remove accumulated soot, affected the success of the intervention. Social and cultural factors can also influence the acceptability and effectiveness of interventions related to housing and ventilation.

Behavioral interventions have also been tried to reduce exposure to household air pollution. These include keeping children away from the cooking area; drying or cutting wood into small pieces; and modifying cooking practices, for example, cooking outdoors rather than indoors. There is, however, limited evidence on the effectiveness of these interventions as few have been evaluated (Barnes, 2014). Behavior change communication in relation to household air pollution could support adoption and use of interventions such as clean cookstoves. Again however, due to limited research, it is not clear to what extent education is effective in achieving behavioral changes that will reduce exposure and improve health outcomes. A recent review has called for more rigorous studies that draw on behavior change theory and practice (Barnes, 2014).

A challenge with behavioral approaches is lack of awareness of the health risks associated with household air pollution. For example, one study found that, although cooks associated sore eyes, coughs, and runny noses with indoor smoke, they did not regard this as a major health risk (Budds et al., 2001; Matinga, 2010). While health concerns might not motivate behavior change, other concerns, for example, about smoke dirtying the house, clothes, and food, could potentially motivate change (Ochieng, 2013).

Tackling the Challenge of Biomass Fuel Use and Household Air Pollution

Role of Policy

Tackling household air pollution, and key underlying issues, such as poverty and reliance on biomass fuels, is complex and requires concerted policy action at international, national, and local levels.

Lack of access to modern energy is a key development issue. Although there was no Millennium Development Goal (MDG) on energy, the “percentage of population using solid fuels” was an indicator of progress, and several analyses have demonstrated that lack of energy access was a major barrier to achievement of the MDG targets (Rehfuess, Mehta, & Pruss-Ustun, 2006). In the post-2015 development agenda, energy has been given higher priority and provision of sustainable energy for all is one of the enablers that underpins the Sustainable Development Goals. The impact of lack of access to modern energy, on health, environment, livelihoods, and climate; and the fact that energy is an enabler of development, requires collaborative action across sectors.

More specifically, international action to reduce household air pollution from household solid fuel use in LMICs is motivated by the disproportionate impact of exposure on the most vulnerable population groups, in particular women and children in low-income settings. WHO has been one of the main global actors in efforts to reduce household air pollution from household use of solid fuels and its role includes research and evaluation, capacity building, generation of evidence for policy, and creation of databases. Evidence generation has included the GBD estimates and development of air quality guidelines. The 2005 global update of the WHO air quality guidelines (WHO, 2006b), although mainly focused on the outdoor environment, drew attention to the impact of household air pollution on health in LMICs. In 2010, WHO released international guidelines addressing indoor air quality (WHO, 2010). The guidelines include a number of compounds that are associated with household air pollution from biomass smoke (Table 4). In addition, complementary guidelines that focus on household fuel combustion have been developed (WHO, 2014), and these define unsafe levels of household air pollution related to biomass stoves commonly used in poor households of LMICs.

Although guidelines are not binding air quality standards, it is anticipated that countries will work toward transforming them into standards for public health protection. As can be seen in Table 4, measured air pollution concentrations are typically much higher than the guideline values and would require considerable investments to bring them down to acceptable levels. This presents a major challenge for LMICs since addressing household air pollution will require efforts that go beyond regulatory measures and monitoring to encompass poverty alleviation and increasing access to modern energy.

There are a number of ongoing global initiatives to address lack of energy access in LMICs. The United Nations has played a key role in creating global partnerships around energy access. The United Nations General Assembly declared 2012 the International Year of Sustainable Energy for All, recognizing that access to modern affordable energy services in LMICs is essential to development. In the same year, the United Nations launched the Sustainable Energy for All (SEFA) initiative. This aims to mobilize action from all sectors of society in support of three interlinked objectives to be achieved by 2030: providing universal access to modern energy services; doubling the global rate of improvement in energy efficiency; and doubling the share of renewable energy in the global energy mix.

More specifically, the United Nations has also supported the establishment of the Global Alliance for Clean Cookstoves (GACC), a public-private partnership led by the United Nations Foundation. GACC seeks to mobilize national and donor commitments to the goal of universal adoption of clean cookstoves and fuels and has an ambitious goal of fostering the adoption of clean cookstoves and fuels in 100 million households by 2020 by supporting the cookstove sector, funding research, and coordinating action to increase awareness of household air pollution.

National governments also have a crucial role to play in increasing access to clean fuels and stoves for the poor in order to reduce health risks. This role includes creating an enabling environment for relevant actors to deliver modern energy and more advanced technologies; establishing modalities for financing, quality assurance, distribution and marketing; and, more specifically, creating a low risk and stable environment for private sector investment (Kees & Feldmann, 2011) in these aspects of the modern energy supply chain. National poverty alleviation policies and programs would enable households to have the disposable income required to transition to cleaner energy or more efficient technologies. National rural electrification programs can also enable households to transition to clean energy. In addition, national governments can also play a role in extending access to credit and in supporting private sector efforts to increase access to micro-credits for poor households to help them to meet the high up-front costs of modern energy.

Affordable technology options for electric cooking are now on the market, such as highly efficient portable induction cookstoves, and these could provide a step up the energy ladder for lower middle and middle income households that still rely on biomass. In India, 400 million people are estimated to be living in middle income households that could be a target population for electricity and gas (Smith & Sagar, 2014). Advanced fan-assisted biomass cookstoves are also on the market, and these could provide clean burning for remote rural households that are unable to switch from biomass, although they require an electricity supply to operate the fans.

National and local governments also have a role in raising awareness on risks associated with household air pollution and risk reduction measures. Such knowledge is useful for motivating change toward adoption of behavioral measures of reduction, as well as technical measures such as improved cookstoves. This would enable the affected populations to also become actors in addressing the challenge of household air pollution exposure.

Role of Research

Further research is needed to strengthen the evidence base on the health effects of household air pollution and to strengthen the evidence base on effective interventions. Specifically, research is needed in the following key areas:

  1. i) Health Impacts of Household Air Pollution From Solid Fuel Use

    Further research in this area would help improve understanding of the range of health outcomes associated with household air pollution in LMICs. Equally important is research that demonstrates the exposure-response functions at ranges of concentrations typically measured in households using biomass fuels. For PM2.5 and cardiovascular mortality, Pope III et al. (2009) have shown a nonlinear exposure-response function that is relatively steep at low exposures (ambient air pollution levels) and relatively flat at higher exposures (tobacco smoking). The limitation of applying the exposure-response functions from Pope III et al. (2009) and similar studies to household air pollution exposures in developing countries have been discussed (Mestl & Edwards, 2011), the main critique being that they are not representative of exposures encountered in these settings. The exposure-response function between these two extremes where household air pollution would be found needs to be described. This would help toward establishing quantitative relationships between exposure reduction and health benefits for a range of outcomes.

  2. ii) Exposure Assessment

    Two recent reviews of interventions have highlighted the need for a standard method to evaluate interventions that includes exposure assessment (Quansah et al., 2017; Rehfuess et al., 2014). Better characterization of household air pollution in rural and urban settings in LMICs is needed to aid in design of interventions that reduce the exposure. This will require inexpensive exposure monitoring techniques that can perform reliably in challenging field conditions.

  3. iii) Interventions

    Recent studies including randomized control trials have now demonstrated a very low benefit of improved cookstove interventions for important health outcomes such as pneumonia (Gill, 2016). There is thus need to strengthen research on clean fuels, particularly on financing and delivery mechanisms that can enable them to reach the “last mile” populations in rural settings in LMICs. There is further need for qualitative research on the barriers and facilitators for adoption and continued use of household air pollution interventions.

Finally, greater efforts are also required to ensure that decision makers are aware of existing evidence and translate evidence into policy.


Photos from rural Western Kenya.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 1. Indoor air pollution as a source of outdoor air pollution.

Photo credit: Caroline Ochieng.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 4. Indoor air pollution exposure from traditional three-stone stove use.

Photo credit: Caroline Ochieng.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 5. Small hole on the wall as the form of kitchen ventilation/window.

Photo credit: Caroline Ochieng.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 7. Personal PM monitoring requires carrying of instruments as shown in this image (left), which can be challenging and impractical for young children. Proxy measurements such as carbon monoxide (right) that are easier to measure are therefore applied in most studies.

Photo credit: Caroline Ochieng.

Household Air Pollution in Low and Middle Income CountriesClick to view larger

Figure 8. A low-cost rocket mud stove designed to improve wood combustion efficiency.

Photo credit: Caroline Ochieng.

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(1.) Modern fuels include electricity, liquid fuels (such as kerosene and ethanol) and gaseous fuels (such as liquefied petroleum gas and natural gas).

(2.) Exposure to pollutants generated indoors through biomass fuel combustion also occurs outdoors. The terminology household air pollution is now used to account for this.

(3.) DALYs for a disease or health condition are calculated as the sum of the Years of Life Lost (YLL) due to premature mortality in the population and the Years Lost due to Disability (YLD) for people living with the health condition or its consequences.