Air pollution exposure disparities across US population and income groups

Abstract

Air pollution contributes to the global burden of disease, with ambient exposure to fine particulate matter of diameters smaller than 2.5 μm (PM_2.5) being identified as the fifth-ranking risk factor for mortality globally¹. Racial/ethnic minorities and lower-income groups in the USA are at a higher risk of death from exposure to PM_2.5 than are other population/income groups^2-5. Moreover, disparities in exposure to air pollution among population and income groups are known to exist^6-17. Here we develop a data platform that links demographic data (from the US Census Bureau and American Community Survey) and PM_2.5 data¹⁸ across the USA. We analyse the data at the tabulation area level of US zip codes (N is approximately 32,000) between 2000 and 2016. We show that areas with higher-than-average white and Native American populations have been consistently exposed to average PM_2.5 levels that are lower than areas with higher-than-average Black, Asian and Hispanic or Latino populations. Moreover, areas with low-income populations have been consistently exposed to higher average PM_2.5 levels than areas with high-income groups for the years 2004-2016. Furthermore, disparities in exposure relative to safety standards set by the US Environmental Protection Agency¹⁹ and the World Health Organization²⁰ have been increasing over time. Our findings suggest that more-targeted PM_2.5 reductions are necessary to provide all people with a similar degree of protection from environmental hazards. Our study is observational and cannot provide insight into the drivers of the identified disparities.

Extended Data Figure A.1. Summary PM2.5 metrics across racial/ethnic and income groups:

a, Population-weighted average of ${\mathrm{P}\mathrm{M}}_{2.5}$ decreased by 40% from the year 2000 to 2016. b, Population-weighted ${\mathrm{P}\mathrm{M}}_{2.5}$ average concentration across the different racial/ethnic communities for 2000 to 2016. The ${\mathrm{P}\mathrm{M}}_{2.5}$ concentration across the racial/ethnic communities demonstrates that Black and Native American populations live in the most and least polluted areas respectively.c, Population-weighted ${\mathrm{P}\mathrm{M}}_{2.5}$ average concentration across racial/ethnic communities as a function of ZCTA racial/ethnic population (%) for 2016. When the racial/ethnic population % is equal to 0.2, the red curve includes every ZCTA where the Black population is 20% or more, and the blue curve includes every ZCTA where the white population is 20% or more. As ZCTA’s Black and Hispanic or Latino populations increase, the ${\mathrm{P}\mathrm{M}}_{2.5}$ concentration levels increase. The opposite effect is seen for the white and Native American communities. d, Population-weighted ${\mathrm{P}\mathrm{M}}_{2.5}$ average concentration across the income groups reveals that the low-income group is exposed to only slightly higher ${\mathrm{P}\mathrm{M}}_{2.5}$ levels than the high-income groups since 2004. e, The population-weighted ${\mathrm{P}\mathrm{M}}_{2.5}$ average concentration across the different racial/ethnic communities for 2000 to 2016 that are in the low-income group. f, The population-weighted ${\mathrm{P}\mathrm{M}}_{2.5}$ average concentration across the different racial/ethnic communities for 2000 to 2016 that are in the high-income group. Panels e and f show similar differences in ${\mathrm{P}\mathrm{M}}_{2.5}$ average concentrations across the racial/ethnic groups as those of panel b.

Extended Data Figure A.2. Average PM2.5 concentration across the US:

a, Distribution of ${\mathrm{P}\mathrm{M}}_{2.5}$ in 2000. b, Distribution of ${\mathrm{P}\mathrm{M}}_{2.5}$ in 2016. We also include a video that shows the change in the distribution of ${\mathrm{P}\mathrm{M}}_{2.5}$ concentration levels in the US from 2000 to 2016. (video 1).

Extended Data Figure A.3. Average PM2.5 concentration across ZCTAs where different racial/ethnic groups are overrepresented:

a, Distribution of ${\mathrm{P}\mathrm{M}}_{2.5}$ across five different maps each showing the ZCTAs where one race/ethnicity group is overrepresented for 2000. b, Distribution of ${\mathrm{P}\mathrm{M}}_{2.5}$ across five different maps each showing the ZCTAs where one race/ethnicity group is overrepresented for 2016. We also include an video that shows the change in the distribution of ${\mathrm{P}\mathrm{M}}_{2.5}$ concentration levels across the five maps from 2000 to 2016 (videos 2 and 3).

Extended Data Figure A.4. Distribution of racial/ethnic populations above a PM2.5 threshold of 8 μg/m³ for 2000 and 2016:

a, US ZCTAs for each race/ethnicity are ranked based on the ratio of the race/ethnicity population to the total ZCTA population. Dark blue indicates fractions close to 1 (ZCTAs where the corresponding race/ethnicity most lives), and light yellow indicates fractions close to 0 (ZCTAs where the corresponding race/ethnicity least lives). b, US ZCTAs above 8 μg/m³ in 2000. c, US ZCTAs above 8 μg/m³ in 2016. We also show the distribution of the different racial/ethnic groups across multiple ranges of ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations for 2000 and 2016 (videos 5–8).

Extended Data Figure A.5. Supplementary measures of relative disparities in exposure to PM2.5 concentrations from 2000 to 2016 among racial/ethnic groups:

a, The Atkinson index is computed to measure relative disparities among the racial/ethnic groups (Black, white, Asian, Native American and Hispanic or Latino). b, The Gini index is computed to measure relative disparities among the racial/ethnic groups (Black, white, Asian, Native American and Hispanic or Latino). The trends in both the Atkinson and Gini indices are similar to the one measured by CoV in figure 4: disparities in air pollution exposure among racial/ethnic groups relative to pollution levels at or below the EPA standard are increasing. The Atkinson and Gini indices were computed using the inequality package “ineq” in the R software. The input is the proportion of the racial/ethnic (or income) groups living above the set ${\mathrm{P}\mathrm{M}}_{2.5}$ threshold. We set the Atkinson aversion parameter = 0.75 [7], and the sensitivity of the index to different values of is shown in Extended Data Figure A.6.

Extended Data Figure A.6. Sensitivity of the Atkinson index to the inequality aversion parameter:

a, Sensitivity of the Atkinson index relative to a ${\mathrm{P}\mathrm{M}}_{2.5}$ threshold of 8 μg/m³. b, Sensitivity of the Atkinson index relative to a ${\mathrm{P}\mathrm{M}}_{2.5}$ threshold of 10 μg/m³. c, Sensitivity of the Atkinson index relative to a ${\mathrm{P}\mathrm{M}}_{2.5}$ threshold of 12 μg/m³. A consistent trend is shown across the parameter values.

Extended Data Figure A.7. Replication of main findings across urban and rural areas:

ZCTA’s population density is used as a metric to control for urbanicity in our study. We classify urban and rural areas based on the percentage of urban population in each ZCTA. Such percentages are available by the census bureau for the year 2010 and are used for the rural/urban classification. ZCTAs with more than 50% urban population are classified in the urban group while those with less than 50% are classified in the rural group. For nationwide, urban and rural US, we reproduce the main results of the manuscript, namely, the average ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations for the total population (a-c), for racial/ethnic groups (d-f), for income groups (g-i), and disparities across racial/ethnic groups (j-l). Similarities in the results across the national, urban and rural US are apparent and findings are consistent regardless of the urbanicity of ZCTAs. Note that in the case of rural US (l), we only compute disparities for the years where the proportion of the population exposed to ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations above the thresholds of interest is non-zero. For example, the proportion of population in rural US exposed to ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations above $T=12\mu \mathrm{g}/m^3$ reaches near zero levels in 2009, and hence disparities after such year are not computed.

Extended Data Figure A.8. Sensitivity of main findings to estimates of PM2.5:

We replicated our analysis with an independent pollution dataset [43, 44] and we show here the sensitivity of our findings to the new ${\mathrm{P}\mathrm{M}}_{2.5}$ estimates. a, Replication of Extended Data figure A.1b with the alternative pollution dataset. b, Replication of Extended Data figure A.1d with alternative pollution dataset. c, Replication of figure 4 with alternative pollution dataset. As can be seen, the main findings of the manuscript are robust and consistent across the two pollution datasets. Minor differences due to the different pollution estimates can be spotted as expected.

Figure 1. Average PM2.5 concentration in 2000 and 2016 across ZCTAs where Black and white populations are overrepresented:

We use the white population fraction of the ZCTA population to compute the average white population fraction (aWpf) across all ZCTAs (≈ 84%). Similarly, we compute the average Black population fraction (aBpf) (≈ 7%). The maps in panel (a) show ${\mathrm{P}\mathrm{M}}_{2.5}$ levels for the year 2000 in ZCTAs with a Black population fraction above aBpf (left) and in ZCTAs with a white population fraction above aWpf (right). High ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations exist in almost all ZCTAs with a Black population above aBpf, while a wide range of low and high ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations exist in ZCTAs with a white population above aWpf in 2000. Panel (b) shows the same information for the year 2016. Similar maps for the other racial/ethnic groups for 2000 and 2016 are shown in Extended Data figures 1.a and 1.b and videos 2 and 3 in supplementary material.

Figure 2. Average PM2.5 concentration in 2000 and 2016 across low- and high-income ZCTAs:

We assign all ZCTAs percentile ranks from 1 to 100 based on median household income and categorize them into ten income groups. We designate the lowest and highest three income groups as low-income and high-income respectively. The maps in panel (a) show ${\mathrm{P}\mathrm{M}}_{2.5}$ levels for the year 2000 in low-income (left) and high-income (right) ZCTAs. Panel (b) shows the same information for the year 2016. Disparities in exposure to ${\mathrm{P}\mathrm{M}}_{2.5}$ among the two groups are apparent and it can be visually seen that in both 2000 and 2016, low-income ZCTAs are exposed to higher ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations as compared to high-income ZCTAs (video 4 in supplementary material).

Figure 3. US ZCTAs with average PM2.5 concentration above 8 μg/m³ for the Black and white populations in 2000 and 2016:

The maps only show US ZCTAs with ${\mathrm{P}\mathrm{M}}_{2.5}$ levels above 8 μg/m³ in (a) 2000 and (b) 2016. The maps on the left are color-coded based on the fraction of the Black population in ZCTAs, while the maps on the right are color-coded based on the white population fraction. For example on the left map in panel (a), the dark-blue and light-yellow colors correspond to ZCTAs with the largest and smallest Black population percentages of the total ZCTA population respectively in 2000, or equivalently where the Black population is over- and under-represented respectively in 2000. The left map of (a) reveals that almost half of the ZCTAs with ${\mathrm{P}\mathrm{M}}_{2.5}$ levels above 8 μg/m³ in 2000 correspond to those where the Black population most lives (almost half of the map is dark-blue). However in 2016, ZCTAs that remained above 8 μg/m³ are only those that are dominated by the Black population (left map in panel b). In contrast, ZCTAs that still had ${\mathrm{P}\mathrm{M}}_{2.5}$ above 8 μg/m³ in 2016 are mainly those where the white population is under-represented (right map in panel b). Videos 5–8 show the distribution of the different racial/ethnic groups across multiple ranges of ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations in 2000 and 2016 respectively.

Figure 4. Relative disparities in exposure to PM2.5 among racial/ethnic groups (Black, white, Asian, Native American and Hispanic or Latino) from 2000 to 2016:

Disparities in exposure (as measured by CoV) to ${\mathrm{P}\mathrm{M}}_{2.5}$ concentrations above thresholds of 8, 10 and 12 μg/m³ for 2000 to 2016 among racial/ethnic groups (Black, white, Asian, Native American and Hispanic or Latino). The percentage of the US population living above the thresholds of 8, 10 and 12 μg/m³ is also shown. The trend reveals that the decrease in air pollution across the years has been accompanied by an increase in the relative disparities in exposure to air pollution among communities.