Environmental justice beyond race: Skin tone and exposure to air pollution
Edited by Christopher Barrett, Cornell University, Ithaca, NY; received April 19, 2024; accepted December 22, 2024
Significance
Each year, outdoor air pollution claims three million lives worldwide. In Colombia, levels of particulate matter smaller than 2.5 μm (PM2.5) exceed the limits stipulated by World Health Organization guidelines. This study measures environmental disparities by skin tone. Using satellite-based PM2.5 estimates and the Colombian longitudinal household survey, it reveals a transformation: While in 2010, individuals with darker skin tones experienced lower pollution levels, by 2016, they faced significantly worse air quality. Satellite geolocation of fires reveals a persistent link between skin tone and fire-related pollution exposure. Decomposition analysis reveals that two-thirds of the exposure gap is attributable to individual characteristics. One-third remains unexplained, underscoring the need to further investigate the potential role of racial discrimination.
Abstract
Recent research, focused mostly on the United States and Western Europe, shows that marginalized communities often face greater environmental degradation. However, the ethnoracial categories used in these studies may not fully capture environmental inequality in the Global South. Moving beyond conventional ethnoracial variables, this study presents findings exploring the link between skin tone and fine particulate matter (PM2.5) exposure in Colombia. By matching household geolocations from a large-scale longitudinal survey with satellite-based PM2.5 estimates, we find that skin tone predicts both initial pollution exposure levels and their changes over time. Although average exposure levels remained stable during our study period, the environmental justice (EJ) landscape in Colombia contemporaneously underwent a complete transformation. In 2010, lighter-skinned individuals faced higher PM2.5 exposure, but darker-skinned individuals experienced steeper increases in the following years. By 2016, the EJ gap had reversed, with people with the darkest skin tones exposed to PM2.5 levels nearly one SD higher than those faced by people with the lightest skin tones. These patterns remain robust when controlling for a comprehensive set of theoretically relevant covariates, including ethnoracial self-identification and income. Disproportionate exposure to pollution from fires partially explains the observed disparities. Decomposition analysis shows that this variable, local collective action, and economic marginalization account for a sizeable share of the EJ gap. However, one-third of the gap remains unexplained by observable characteristics. With climate change intensifying fire incidence, the disproportionate disease burdens that vulnerable groups face might deepen unless policy measures are taken to reverse this trend.
Get full access to this article
Purchase, subscribe or recommend this article to your librarian.
Data, Materials, and Software Availability
Some study data are available: Most of ELCA information is open to the public and can be downloaded easily from (26). However, to comply with the Colombian Data Law and ensure the privacy of households, the Geolocalized information of the ELCA can only be accessed on-site at the Universidad de los Andes. To gain access, written permission and an agreement on the usage of the data is required. Please note that this information is available only in Spanish.
Acknowledgments
We thank Christopher Timmins, Danae Hernandez-Cortes, Luis Monroy-Gómez-Franco, and Manuel Pastor for their helpful comments on this paper. We are grateful to the editor and the three anonymous reviewers, whose suggestions greatly improved the paper. We also thank participants of the International Economic Association 2024 Conference and the Universidad Iberoamericana Economics Seminar for their comments and suggestions. Diana Millan-Orduz and David Chaparro-Alvarez provided excellent research assistance. We thank Samantha Eyler-Driscoll for her support in editing the manuscript.
Author contributions
S.A.-G. and J.C.C. designed research; S.A.-G., J.C.C., and R.S.D. performed research; S.A.-G. contributed new reagents/analytic tools; S.A.-G., J.C.C., and R.S.D. analyzed data; and S.A.-G., J.C.C., and R.S.D. wrote the paper.
Competing interests
The authors declare no competing interest.
Supporting Information
Appendix 01 (PDF)
- Download
- 2.20 MB
References
1
R. Burnett et al., Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. Proc. Natl. Acad. Sci. U.S.A. 115, 9592–9597 (2018).
2
J. Currie, J. G. Zivin, J. Mullins, M. Neidell, What do we know about short-and long-term effects of early-life exposure to pollution? Annu. Rev. Resour. Econ. 6, 217–247 (2014).
3
J. Graff Zivin, M. Neidell, Environment, health, and human capital. J. Econ. Lit. 51, 689–730 (2013).
4
C. A. Pope Iii et al., Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. Jama 287, 1132–1141 (2002).
5
D. W. Dockery et al., An association between air pollution and mortality in six US cities. N. Engl. J. Med. 329, 1753–1759 (1993).
6
WHO, Air Pollution and Child Health: Prescribing Clean Air (World Health Organization, 2016).
7
S. Aguilar-Gomez, H. Dwyer, J. Graff Zivin, M. Neidell, This is air: The “nonhealth” effects of air pollution. Annu. Rev. Resour. Econ. 14, 403–425 (2022).
8
M. de Ambiente, “Estrategia nacional de calidad del aire” (Tech. Rep.04, DIRECCIÓN DE ASUNTOS AMBIENTALES, SECTORIAL Y URBANA, 2019).
9
N. Fleisher, A. D. Roux, M. Alazraqui, H. Spinelli, F. D. Maio, Socioeconomic gradients in chronic disease risk factors in middle-income countries: Evidence of effect modification by urbanicity in Argentina. Am. J. Public Health 101, 294–301 (2011).
10
P. Hessel, P. Rodriguez Lesmes, D. Torres, Socio-economic inequalities in high blood pressure and additional risk factors for cardiovascular disease among older individuals in Colombia: Results from a nationally representative study. PLoS One 15, e0234326 (2020).
11
R. A. Pérez, C. A. O. Tejada, L. M. Triaca, A. D. Bertoldi, A. M. A. dos Santos, Socioeconomic inequality in health in older adults in Brazil. Dialogues Health 1, 100009 (2022).
12
L. Pulido, Geographies of race and ethnicity II: Environmental racism, racial capitalism and state-sanctioned violence. Prog. Hum. Geogr. 41, 524–533 (2017).
13
N. Brazil, Environmental inequality in the neighborhood networks of urban mobility in US cities. Proc. Natl. Acad. Sci. U.S.A. 119, e2117776119 (2022).
14
S. E. Chambliss et al., Local- and regional-scale racial and ethnic disparities in air pollution determined by long-term mobile monitoring. Proc. Natl. Acad. Sci. U.S.A. 118, e2109249118 (2021).
15
D. Hernandez-Cortes, K. C. Meng, Do environmental markets cause environmental injustice? Evidence from California’s carbon market. J. Public Econ. 217, 104786 (2023).
16
P. Mohai, D. Pellow, J. T. Roberts, Environmental justice. Annu. Rev. Environ. Resour. 34, 405–430 (2009).
17
S. Banzhaf, L. Ma, C. Timmins, Environmental justice: The economics of race, place, and pollution. J. Econ. Perspect. 33, 185–208 (2019).
18
D. Alexander, J. Currie, Is it who you are or where you live? Residential segregation and racial gaps in childhood asthma. J. Health Econ. 55, 186–200 (2017).
19
A. Aizer, J. Currie, P. Simon, P. Vivier, Do low levels of blood lead reduce children’s future test scores? Am. Econ. J. Appl. Econ. 10, 307–341 (2018).
20
J. M. Kohima, U. E. Chigbu, M. L. Mazambani, M. R. Mabakeng, (Neo-)segregation, (neo-)racism, and one-city two-system planning in Windhoek, Namibia: What can a new national urban policy do? Land Use Policy 125, 106480 (2023).
21
L. Melgaço, L. X. P. Coelho, Race and space in the Postcolony: A relational Study on Urban Planning under racial capitalism in Brazil and South Africa. City Community 21, 214–237 (2022).
22
J. Sundberg, Placing race in environmental justice research in Latin America. Soc. Nat. Resour. 21, 569–582 (2008).
23
L. Monroy-Gómez-Franco, Shades of social mobility: Colorism, ethnic origin and intergenerational social mobility. Q. Rev. Econ. Finance 90, 247–266 (2023).
24
E. Telles, Pigmentocracies: Ethnicity, Race, and Color in Latin America (UNC Press Books, 2014).
25
A. R. Dixon, E. E. Telles, Skin color and colorism: Global research, concepts, and measurement. Ann. Rev. Sociol. 43, 405–424 (2017).
26
Centro de Estudios sobre Desarrollo Económico (CEDE), Encuesta Longitudinal Colombiana de la Universidad de los Andes – ELCA. CEDE. https://datoscede.uniandes.edu.co/en/elca-eng/. Accessed 5 August 2022.
27
J. G. Canadell et al., Multi-decadal increase of forest burned area in Australia is linked to climate change. Nat. Commun. 12, 6921 (2021).
28
M. W. Jones et al., Global and regional trends and drivers of fire under climate change. Rev. Geophys. 60, e2020RG000726 (2022).
29
E. W. Butt et al., Achieving brazil’s deforestation target will reduce fire and deliver air quality and public health benefits. Earth Future 10, e2022EF003048 (2022).
30
D. Armenteras, L. Schneider, L. M. Dávalos, Fires in protected areas reveal unforeseen costs of Colombian peace. Nat. Ecol. Evol. 3, 20–23 (2019).
31
NASA, Earth Science Data and Information System. VIIRS-MODIS. https://www.earthdata.nasa.gov/learn/find-data/near-real-time/viirs. Accessed 18 July 2024.
32
NASA, Fire Information for Resource Management System - FIRMS. VIIRS-MODIS. https://www.earthdata.nasa.gov/data/tools/firms. Accessed 18 July 2024.
33
European Centre for Medium-Range Weather Forecasts, Era5-land: Ecmwf’s global reanalysis for land applications (2024). https://www.ecmwf.int/en/era5-land. Accessed 12 August 2024.
34
E. Telles, R. D. Flores, F. Urrea-Giraldo, Pigmentocracies: Educational inequality, skin color and census ethnoracial identification in eight Latin American countries. Res. Soc. Strat. Mobility 40, 39–58 (2015).
35
A. R. Dixon, Colorism and classism confounded: Perceptions of discrimination in Latin America. Soc. Sci. Res. 79, 32–55 (2019).
36
E. Telles, T. Paschel, Who is black, white, or mixed race? How skin color, status, and nation shape racial classification in Latin America Am. J. Sociol. 120, 864–907 (2014).
37
A. Van Donkelaar et al., Monthly global estimates of fine particulate matter and their uncertainty. Environ. Sci. Technol. 55, 15287–15300 (2021).
38
H. S. Banzhaf, L. Ma, C. Timmins, Environmental justice: Establishing causal relationships. Ann. Rev. Res. Econ. 11, 377–398 (2019).
39
European Centre for Medium-Range Weather Forecasts, How to calculate wind speed and wind direction from u and v components of the wind (2024). https://confluence.ecmwf.int/pages/viewpage.action?pageId=133262398. Accessed 22 July 2024.
40
H. K. Pullabhotla, M. Souza, Air pollution from agricultural fires increases hypertension risk. J. Environ. Econ. Manag. 115, 102723 (2022).
41
M. A. Rangel, T. S. Vogl, Agricultural fires and health at birth. Rev. Econ. Stat. 101, 616–630 (2019).
42
W. H. Organization, WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide (World Health Organization, 2021).
43
Secretaría de Ambiente de Bogotá, Inventario de Emisiones de Bogotá, Contaminantes Atmosféricos (Red de Monitoreo de Calidad del Aire de Bogotá-RMCAB, Bogotá, 2020).
44
D. F. Florez Trujillo, A. Valencia, B. Avendano-Uribe, Informal settlement fires in Colombia. Fire Technol. 1–24 (2023).
45
E. Giraldo Gómez, C. García, C. del Rosario, Manejo integrado de residuos sólidos municipales (Universidad de los Andes and Ministerio de Ambiente, 1997).
46
K. Ballesteros-González, A. P. Sullivan, R. Morales-Betancourt, Estimating the air quality and health impacts of biomass burning in northern South America using a chemical transport model. Sci. Total Environ. 739, 139755 (2020).
47
G. R. Van der Werf et al., Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009). Atmos. Chem. Phys. 10, 11707–11735 (2010).
48
B. Baptiste et al., Greening peace in Colombia. Nat. Ecol. Evol. 1, 0102 (2017).
49
R. Rocha, A. A. Sant’Anna, Winds of fire and smoke: Air pollution and health in the Brazilian Amazon. World Dev. 151, 105722 (2022).
50
M. Prem, S. Saavedra, J. F. Vargas, End-of-conflict deforestation: Evidence from Colombia’s peace agreement. World Dev. 129, 104852 (2020).
51
M. Prem, J. F. Vargas, D. Mejía, The rise and persistence of illegal crops: Evidence from a naive policy announcement. Rev. Econ. Stat. 105, 344–358 (2023).
52
J. I. Huertas, M. E. Huertas, S. Izquierdo, E. D. González, Air quality impact assessment of multiple open pit coal mines in northern Colombia. J. Environ. Manag. 93, 121–129 (2012).
53
D. L. Anderton, A. B. Anderson, J. M. Oakes, M. R. Fraser, Environmental equity: The demographics of dumping. Demography 31, 229–248 (1994).
54
L. Cain, D. Hernandez-Cortes, C. Timmins, P. Weber, Recent findings and methodologies in economics research in environmental justice. Rev. Environ. Econ. Policy 18, 116–142 (2024).
55
J. A. Bohren, P. Hull, A. Imas, “Systemic discrimination: Theory and measurement” (Tech. Rep. WP 29820, National Bureau of Economic Research 2022).
56
A. M. Ibáñez, A. Velásquez, El impacto del desplazamiento forzoso en Colombia: condiciones socioeconómicas de la población desplazada, vinculación a los mercados laborales y políticas públicas (Cepal, 2008).
57
J. Navarrete-Suárez et al., Heterogeneidad de la integración laboral en colombia: diferencias según el sexo y la pertenencia étnica de desplazados forzados y otros migrantes internos. Revista Latinoamericana de Población 14, 89–123 (2020).
58
J. T. Hamilton, Politics and social costs: Estimating the impact of collective action on hazardous waste facilities. The RAND Journal of Economics (Wiley, 1993), pp. 101–125.
59
N. Brooks, R. Sethi, “The distribution of pollution: Community characteristics and exposure to air toxics” in Distributional Effects of Environmental and Energy Policy, D. Fullerton, Ed. (Routledge, 2017), pp. 301–318.
60
E. M. Kitagawa, Components of a difference between two rates. J. Am. Stat. Assoc. 50, 1168–1194 (1955).
61
R. Oaxaca, Male-female wage differentials in urban labor markets. Int. Econ. Rev. 14, 693–709 (1973).
62
A. S. Blinder, Wage discrimination: Reduced form and structural estimates. J. Human Resour. 8, 436–455 (1973).
63
N. Fortin, T. Lemieux, S. Firpo, Decomposition methods in economics in Handbook of labor economics. Elsevier 4, 1–102 (2011).
64
O. Raaschou-Nielsen et al., Air pollution at the residence of Danish adults, by socio-demographic characteristics, morbidity, and address level characteristics. Environ. Res. 208, 112714 (2022).
65
C. König, Neighbourhood structure and environmental quality: A fine-grained analysis of spatial inequalities in urban Germany. Urban Stud. 61, 00420980231224224 (2024).
66
T. Rüttenauer, Neighbours matter: A nation-wide small-area assessment of environmental inequality in Germany. Soc. Sci. Res. 70, 198–211 (2018).
67
J. Pearce, S. Kingham, P. Zawar-Reza, Every breath you take? Environmental justice and air pollution in Christchurch, New Zealand. Environ. Plan. A 38, 919–938 (2006).
68
A. R. Germani, P. Morone, G. Testa, Environmental justice and air pollution: A case study on Italian provinces. Ecol. Econ. 106, 69–82 (2014).
69
L. Chakraborti, J. Voorheis, Is air pollution increasing in poorer localities of Mexico? Evidence from pm 2.5 satellite data Environ. Dev. Econ. 2024, 1–18 (2024).
70
S. Aguilar-Gomez, “Addressing environmental quality inequities: The role of information and collective action” in Equity in the Urban Built Environment, B Bereitschaft, Ed. (Routledge, 2024).
71
P. Christensen, C. Timmins, Sorting or steering: The effects of housing discrimination on neighborhood choice. J. Polit. Econ. 130, 2110–2163 (2022).
72
S. Aguilar-Gomez, N. M. Rivera, Pollution in the global south: An overview of its sources and impacts. University of Chile, Department of Economics Working Papers (2024).
73
S. Heft-Neal, J. Burney, E. Bendavid, M. Burke, Robust relationship between air quality and infant mortality in Africa. Nature 559, 254–258 (2018).
74
E. Dardati, R. de Elejalde, E. Giolito, On the short-term impact of pollution: The effect of PM 2.5 on emergency room visits. Health Econ. 33, 482–508 (2024).
75
D. Taylor, Toxic Communities in Toxic Communities (New York University Press, 2014).
76
L. Mateus-Fontecha et al., Understanding aerosol composition in an inter-andean valley impacted by sugarcane intensive agriculture and urban emissions. Atmos. Chem. Phys. Discuss. 2021, 1–36 (2021).
Information & Authors
Information
Published in
Classifications
Copyright
Copyright © 2025 the Author(s). Published by PNAS. This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Data, Materials, and Software Availability
Some study data are available: Most of ELCA information is open to the public and can be downloaded easily from (26). However, to comply with the Colombian Data Law and ensure the privacy of households, the Geolocalized information of the ELCA can only be accessed on-site at the Universidad de los Andes. To gain access, written permission and an agreement on the usage of the data is required. Please note that this information is available only in Spanish.
Submission history
Received: April 19, 2024
Accepted: December 22, 2024
Published online: March 4, 2025
Published in issue: March 11, 2025
Keywords
Acknowledgments
We thank Christopher Timmins, Danae Hernandez-Cortes, Luis Monroy-Gómez-Franco, and Manuel Pastor for their helpful comments on this paper. We are grateful to the editor and the three anonymous reviewers, whose suggestions greatly improved the paper. We also thank participants of the International Economic Association 2024 Conference and the Universidad Iberoamericana Economics Seminar for their comments and suggestions. Diana Millan-Orduz and David Chaparro-Alvarez provided excellent research assistance. We thank Samantha Eyler-Driscoll for her support in editing the manuscript.
Author contributions
S.A.-G. and J.C.C. designed research; S.A.-G., J.C.C., and R.S.D. performed research; S.A.-G. contributed new reagents/analytic tools; S.A.-G., J.C.C., and R.S.D. analyzed data; and S.A.-G., J.C.C., and R.S.D. wrote the paper.
Competing interests
The authors declare no competing interest.
Notes
This article is a PNAS Direct Submission.
Although PNAS asks authors to adhere to United Nations naming conventions for maps (https://www.un.org/geospatial/mapsgeo), our policy is to publish maps as provided by the authors.
†
While there are significant variations in skin color among the populations of the Americas, countries such as Mexico, Brazil, Bolivia, Ecuador, and Peru exhibit patterns in skin tones similar to those observed in Colombia. Ethnoracial categories are more related to skin color in some countries, such as Panama, than in others. However, both variables generally capture distinct information (36).
Authors
Metrics & Citations
Metrics
Altmetrics
Citations
Cite this article
Environmental justice beyond race: Skin tone and exposure to air pollution, Proc. Natl. Acad. Sci. U.S.A.
122 (10) e2407064122,
https://doi.org/10.1073/pnas.2407064122
(2025).
Copied!
Copying failed.
Export the article citation data by selecting a format from the list below and clicking Export.
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Personal login Institutional LoginRecommend to a librarian
Recommend PNAS to a LibrarianPurchase options
Purchase this article to access the full text.
Restore content access
View options
PDF format
Download this article as a PDF file
DOWNLOAD PDF