Characterization of particulate matter size distributions and indoor concentrations from kerosene and diesel lamps: Indoor particulate matter concentrations from kerosene lamps
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UNLABELLED: Over one-quarter of the world's population relies on fuel-based lighting. Kerosene lamps are often located in close proximity to users, potentially increasing the risk for respiratory illnesses and lung cancer. Particulate matter concentrations resulting from cook stoves have been extensively studied in the literature. However, characterization of particulate concentrations from fuel-based lighting has received minimal attention. This research demonstrates that vendors who use a single simple wick lamp in high-air-exchange market kiosks will likely be exposed to PM(2.5) concentrations that are an order of magnitude greater than ambient health guidelines. Using a hurricane lamp will reduce exposure to PM(2.5) and PM(10) concentrations by an order of magnitude compared to using a simple wick lamp. Vendors using a single hurricane or pressure lamp may not exceed health standards or guidelines for PM(2.5) and PM(10), but will be exposed to elevated 0.02-0.3 μm particle concentrations. Vendors who change from fuel-based lighting to electric lighting technology for enhanced illumination will likely gain the ancillary health benefit of reduced particulate matter exposure. Vendors exposed only to ambient and fuel-based lighting particulate matter would see over an 80% reduction in inhaled PM(2.5) mass if they switched from a simple wick lamp to an electric lighting technology. PRACTICAL IMPLICATIONS: Changing lighting technologies to achieve increased efficiency and energy service levels can provide ancillary health benefits. The cheapest, crudest kerosene lamps emit the largest amounts of PM(2.5). Improving affordability and access to better lighting options (hurricane or pressure lamps and lighting using grid or off-grid electricity) can deliver health benefits for a large fraction of the world's population, while reducing the economic and environmental burden of the current fuel-based lighting technologies.
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Because kerosene lamps give dim light, people sit close to the source where pollutant concentrations are higher, which raises the intake fraction and makes lighting sources account for a larger share of total exposure than source emission rates alone would suggest.
“The dim light produced by kerosene lamps necessitates participants to sit in close proximity the light source where pollutant concentrations are higher20, increasing the pollutant intake fraction and leading lighting sources to account for a larger fraction of total exposure than might be assumed from source emission rates alone.”
From Effect of a solar lighting intervention on fuel-based lighting use and exposure to household air pollution in rural Uganda: A randomized controlled trial (2022) · cites this paper as [20]
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Experimental — accuracy not yet measuredOpen wick kerosene lamps in particular are strong indoor sources of PM2.5 that is largely black carbon.
“Kerosene lamps, particularly open (simple) wick lamps, are potent sources of indoor fine particulate matter (PM2.5) composed of mostly black carbon (BC) 20–22.”
From Effect of a solar lighting intervention on fuel-based lighting use and exposure to household air pollution in rural Uganda: A randomized controlled trial (2022) · cites this paper as [20]
The Particle size concentrations section reports that a single simple wick lamp produced PM2.5 concentrations at least an order of magnitude above the WHO 24-hour guideline in the test kiosk. The Conclusion says the crudest kerosene lamps emit the most PM2.5. Our copy does not establish that this particulate matter is mostly black carbon; it estimates particle mass using an assumed soot density rather than measuring its composition. (LLM, conf=0.88)
Experimental — accuracy not yet measuredNight kiosk vendors can inhale 1560 μg of fine particles per day emitted by kerosene lamps alone.
“An experimental study in Kenya estimated that night kiosk vendors can inhale 1560 µg of fine particles per day emitted by kerosene lamps alone (Apple et al., 2010).”
From Kerosene-based lighting: an overlooked source of exposure to household air pollution? (2020) · cites this paper as Apple et al., 2010
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- Authors
- Apple, J., Vicente, R., Yarberry, A., Lohse, N., Mills, E., Jacobson, A., & Poppendieck, D.
- Affiliations
- Cal Poly Humboldt (US)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Poppendieck, D.
- ORCID
- Poppendieck, D.
- Venue
- Indoor Air
- Publisher
- Hindawi Limited
- Published
- 2010-09-10
- Volume
- 20
- Issue
- 5
- Pages
- 399-411
- ISSN
- 0905-6947 (ISSN-L)
- OpenAlex
- W2157851737
- Cited by
- 72
- References
- 23
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 2 · 2022: 6 · 2021: 4 · 2020: 7 · 2019: 4 · 2018: 4 · 2017: 6 · 2016: 4 · 2015: 6 · 2014: 8 · 2013: 5 · 2012: 7
- FWCI
- 4.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Indoor Air (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- World Health Organization
- Blum Center for Developing Economies, University of California Berkeley
- Topics
- Physical Sciences › Environmental Science › Pollution › Energy and Environment Impacts
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Indoor Air Quality and Microbial Exposure
- Keywords
- particulate matter, PM2.5, PM10, kerosene lamps, indoor air quality, electric lighting, particle size distribution, respiratory health, cooking stoves
- MeSH terms
- Air Pollutants, Occupational, Developing Countries, Environmental Monitoring, Gasoline, Humans, Kenya, Kerosene, Lighting, Particle Size, Air Pollution, Indoor, Particulate Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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