Predictors of personal exposure to black carbon among women in southern semi-rural Mozambique
Open accessAbstract
Sub-Saharan Africa (SSA) has the highest proportion of people using unclean fuels for household energy, which can result in products of incomplete combustion that are damaging for health. Black carbon (BC) is a useful marker of inefficient combustion-related particles; however, ambient air quality data and temporal patterns of personal exposure to BC in SSA are scarce. We measured ambient elemental carbon (EC), comparable to BC, and personal exposure to BC in women of childbearing age from a semi-rural area of southern Mozambique. We measured ambient EC over one year (2014–2015) using a high-volume sampler and an off-line thermo-optical-transmission method. We simultaneously measured 5-min resolved 24-h personal BC using a portable MicroAeth (AE51) in 202 women. We used backwards stepwise linear regression to identify predictors of log-transformed 24-h mean and peak (90th percentile) personal BC exposure. We analyzed data from 187 non-smoking women aged 16–46 years. While daily mean ambient EC reached moderate levels (0.9 μg/m 3 , Standard Deviation, SD: 0.6 μg/m 3 ), daily mean personal BC reached high levels (15 μg/m 3 , SD: 19 μg/m 3 ). Daily patterns of personal exposure revealed a peak between 6 and 7 pm (>35 μg/m 3 ), attributable to kerosene-based lighting. Key determinants of mean and peak personal exposure to BC were lighting source, kitchen type, ambient EC levels, and temperature. This study highlights the important contribution of lighting sources to personal exposure to combustion particles in populations that lack access to clean household energy.
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Kerosene-based lighting was the strongest determinant of 24-h average and peak personal exposure to black carbon among women living in a semi-rural area of Mozambique.
“We previously reported that kerosene-based lighting was the strongest determinant of 24-h average and peak personal exposure to black carbon among women living in a semi-rural area of Mozambique (Curto et al., 2019).”
From Kerosene-based lighting: an overlooked source of exposure to household air pollution? (2020) · cites this paper as Curto et al., 2019
Section 3.5 reports higher 24-h mean and peak black-carbon exposure among women using kerosene lighting than among those using electricity. But Section 4.1 identifies lighting source alongside kitchen type, ambient elemental carbon and temperature as main predictors; it does not establish kerosene-based lighting as the single strongest determinant of both measures. (LLM, conf=0.84)
Experimental — accuracy not yet measuredWomen who used kerosene as the primary source of lighting had 93% higher peak personal black carbon exposure than those using electricity.
“Women who used kerosene as the primary source of lighting had 81% and 93% higher average and peak personal black carbon exposure, respectively, than those using electricity.”
From Kerosene-based lighting: an overlooked source of exposure to household air pollution? (2020) · cites this paper as Curto et al., 2019
Women who used kerosene as the primary source of lighting had 81% higher average personal black carbon exposure than those using electricity.
“Women who used kerosene as the primary source of lighting had 81% and 93% higher average and peak personal black carbon exposure, respectively, than those using electricity.”
From Kerosene-based lighting: an overlooked source of exposure to household air pollution? (2020) · cites this paper as Curto et al., 2019
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Kerosene-based lighting: an overlooked source of exposure to household air pollution?
Curto, A., & Tonne, C. (2020) · Clean Air Journal · doi:10.17159/caj/2020/30/1.8420 · Cited by 3 · see citing works
Self-citation
- Authors
- Curto, A., Donaire-Gonzalez, D., Manaca, M. N., González, R., Sacoor, C., Rivas, I., Gascon, M., Wellenius, G. A., Querol, X., Sunyer, J., Macete, E., Menéndez, C., & Tonne, C.
- Affiliations
- Universitat Pompeu Fabra (ES)
- Manhiça Health Research Centre (MZ)
- Consejo Superior de Investigaciones Científicas (ES)
- Brown University (US)
- Corresponding author
- Curto, Ariadna
- ORCID
- Venue
- Environment International
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 131
- Pages
- 104962
- ISSN
- 0160-4120 (ISSN-L)
- OpenAlex
- W2960791410
- Cited by
- 31
- References
- 7
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 3 · 2022: 4 · 2021: 9 · 2020: 3
- FWCI
- 1.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Environment International (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (publishedVersion, cc-by-nc-nd)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (acceptedVersion)
- Research Bank (Australian Catholic University) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Research Portal (King's College London) (submittedVersion, other-oa)
- RECERCAT (Consorci de Serveis Universitaris de Catalunya) (submittedVersion, cc-by-nc-nd)
- Funders
- Spanish Ministry of Economy and Competitiveness (RYC-2015-17402)
- Government of Mozambique
- AECID
- 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 › Toxic Organic Pollutants Impact
- Keywords
- black carbon, personal exposure, elemental carbon, household energy, women of reproductive age, ambient air pollution, incomplete combustion
- MeSH terms
- Adult, Air Pollutants, Air Pollution, Carbon, Environmental Exposure, Environmental Monitoring, Female, Humans, Mozambique, Rural Population, Linear Models, Particulate Matter, Soot
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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