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Understanding Reductions of PM2.5 Concentration and Its Chemical Composition in the United States: Implications for Mitigation Strategies
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  • Chi Li*
    Chi Li
    Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
    *Email: [email protected]
    More by Chi Li
    Orcidhttps://orcid.org/0000-0002-8992-7026
  • Randall V. Martin
    Randall V. Martin
    Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
    More by Randall V. Martin
  • Aaron van Donkelaar
    Aaron van Donkelaar
    Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
    More by Aaron van Donkelaar
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ACS ES&T Air

Cite this: ACS EST Air 2024, 1, 7, 637–645
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https://doi.org/10.1021/acsestair.4c00004
Published May 9, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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Motivated by the recent tightening of the US annual standard of fine particulate matter (PM2.5) concentrations from 12 to 9 μg/m3, there is a need to understand the spatial variation and drivers of historical PM2.5 reductions. We evaluate and interpret the variability of PM2.5 reductions across the contiguous US using high-resolution estimates of PM2.5 and its chemical composition over 1998–2019, inferred from satellite observations, air quality modeling, and ground-based measurements. We separated the 3092 counties into four characteristic regions sorted by PM2.5 trends. Region 1 (primarily Central Atlantic states, 25.9% population) exhibits the strongest population-weighted annual PM2.5 reduction (−3.6 ± 0.4%/yr) versus Region 2 (primarily rest of the eastern US, −3.0 ± 0.3%/yr, 39.7% population), Region 3 (primarily western Midwest, −1.9 ± 0.3%/yr, 25.6% population), and Region 4 (primarily the Mountain West, −0.4 ± 0.5%/yr, 8.9% population). Decomposition of these changes by chemical composition elucidates that sulfate exhibits the fastest reductions among all components in 2720 counties (76% of population), mostly over Regions 1–3, with the 1998–2019 mean sulfate mass fraction in PM2.5 decreasing from Region 1 (29.5%) to Region 4 (11.8%). Complete elimination of the remaining sulfate may be insufficient to meet the new standard for many regions in exceedance. Additional measures are needed to reduce other PM2.5 sources and components for further progress.

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Synopsis

Regional variation in the reduction of PM2.5 across the US has been driven primarily by sulfate, but a stricter PM2.5 standard calls upon reducing other components.

Introduction

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Fine particulate matter (PM2.5) air pollution has adverse impacts on human health even at low levels (1,2) and is at present the second largest environmental risk factor to human health across the United States (US). (3,4) The Clean Air Act and subsequent amendments have led to sustained reductions of anthropogenic PM2.5 sources in the US for over three decades. (5−8) The responses of total PM2.5 are collectively determined by PM2.5 chemical composition changes that are driven by changes in specific sources. (7−10) As the US Environmental Protection Agency (EPA) recently reduced the annual PM2.5 standard from 12 to 9 μg/m3, it is important to reflect upon prior reductions in PM2.5 exposure to inform future mitigation strategies. Long-term dedicated monitoring of PM2.5 chemical composition (11) has been essential to attribute reduced anthropogenic emissions as the main driver of recent PM2.5 reductions across the US. (8−10,12−15) Characteristic spatial variation of these improvements, e.g., stronger reductions in PM2.5 over the eastern than the western US, (16) has also been revealed. These existing studies primarily focused on absolute trends at regional and national scales that are not independent of local pollution level; there is need to interpret relative trends in population-weighted (PW) PM2.5 concentrations and its chemical composition at fine spatial scales (e.g., county-level) across the contiguous US (CONUS) to better understand how changes in chemical composition affected population exposure.
Recent advances in satellite remote sensing and air quality modeling offer information to fill spatial gaps (17) of in situ monitoring and enable accurate estimation of high-resolution gapless PM2.5 and chemical composition across the CONUS. (18−20) Such data enable investigation and interpretation of PW-PM2.5 trends at the county-level. In this paper, we use timely and accurate estimates of PM2.5 and chemical composition to quantify and interpret PW-PM2.5 trends for 3092 counties across the CONUS during 1998–2019, focusing on relative PM2.5 trends (i.e., ΔPM2.5 in %/yr) that are normalized to mass concentrations and independent of local pollution level. We find strong regional variation of PW-PM2.5 reduction rates with an overall meridional gradient (i.e., weakening from the east to the west). Similar regional distributions are identified for the PM2.5 mass fraction of one chemical component─sulfate, which also exhibited the strongest reductions among all components in 2720 counties (76% of the CONUS population). We conclude that policies that reduced sulfur dioxide emissions have been the most responsible for these PW-PM2.5 reductions and their regional variation. We find that even complete elimination of sulfate would be insufficient to meet the new EPA standard; other measures are needed to sustain such progress in the future.

Materials and Methods

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PM2.5 Data

We use monthly estimates of PM2.5 mass concentration and its seven major chemical components (sulfate, ammonium, nitrate, organic mass (OM), black carbon (BC), dust, and sea salt) across the CONUS based on a recent study. (18) The original data (2000–2016) are revised using more recent satellite retrievals of aerosol optical depth (AOD) and updated long-term simulations using the GEOS-Chem model of atmospheric composition in its high-performance configuration (21,22) (Text S1). We use the “hybrid” PM2.5 and chemical composition during 1998–2019 that have merged information from satellite retrievals, modeling, and ground-based observations, achieving a high degree of consistency with observations (Text S1). To aid interpretation, we use the simulated contribution from open burning to further apportion the estimated OM and BC into concentrations from fire and other sources. Here we use the terms “OM” and “BC” to indicate their total mass concentrations, unless specifically referring to their fire or non-fire components. To focus on evaluation of long-term air quality regulations, we do not use years after 2019 to avoid impacts from COVID-19 lockdown (23,24) and extreme wildfire events in the western US in 2020 and 2021. (25−27)

Ground-Based Measurements

We use long-term monitoring data of PM2.5 and its chemical composition to develop, evaluate, and interpret trends from the gapless estimates. Description of these observations is provided in Text S2. We require at least 10 (3) months of data available for an annual (seasonal) mean to be calculated, and at least 17 (out of 22) years available for a trend during 1998–2019 to be estimated (i.e., “long-term” criteria). These completeness criteria yield >660 PM2.5 sites and >190 sites for chemical composition (e.g., Figures S1 and S2).

Population Data

We use population estimates at 1 km2 resolution from the Gridded Population of the World (GPW v4) database. (28) GPW is available every five years for 2000–2020. For each year during 1998–2019, we scale the GPW population distribution in the closest year by a constant factor to match the annual CONUS total population. (29)

Trend Analysis

We estimate 1998–2019 linear trends in the time series of PW-PM2.5 and chemical composition at county and regional levels based on a linear least-squares fitting approach. We investigate the linear slope (in μg/m3/yr), its 95% confidence interval (CI), as well as the p-value (two-tailed student’s t-test) at seasonal and annual scales. These multi-year slopes are less sensitive to abnormal years (i.e., versus differences between the beginning and ending years). We confirmed that the derived trends at county-level are highly consistent (R2 > 0.9) with those from a non-parametric (Mann–Kendall) trend estimation approach. (30,31) The linear slopes of PM2.5 are then normalized by multi-year mean PM2.5 to represent relative PM2.5 trends (ΔPM2.5) at each location. We tested this normalization for sensitivity to the choice of mean or median PM2.5 and found negligible changes in population-weighted monthly concentrations. We find that the sum of PW trends from the seven components is highly consistent with the trends in total PW-PM2.5 (typically within 5%) despite independent linear regressions, a feature that facilitates evaluation of contributions from each component to the derived relative PM2.5 trends. For in situ measurements, we conduct similar evaluations of component contributions by comparing composition trends vs PM2.5 trends from the nearest site (within 20 km). Not all sites provide simultaneous measurements of all seven components; e.g., the number of long-term sites with OM measurements are significantly fewer than sites with sulfate measurements (Figure S1). We therefore only perform the comparison among component trends over sites that have maintained long-term measurements for at least 4 main components (sulfate, ammonium, nitrate, and OM, contributing to >69% of annual PM2.5 mass for 95% pixels of the CONUS).

Results

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Spatially Varying PM2.5 Reduction Rates across the CONUS

Figure 1a shows the relative PM2.5 trends (%/yr) from the estimates (background) and in situ observations (points). We find that 95% of the CONUS population experienced significantly (p < 0.05) decreasing PM2.5 concentrations, while PM2.5 concentrations across the Mountain West exhibit insignificant or slightly positive trends. Except for several discrete locations (e.g., Greater Los Angeles, GLA), pixel-level relative PM2.5 trends exhibit an overall meridional gradient, increasing from near zero over the Mountain West to the strongest (<−3%/yr) reductions over the Central Atlantic states. This spatial distribution of relative PM2.5 trends from the hybrid estimates is highly consistent (R2 = 0.71) vs. observations. Absolute trends (in μg/m3/yr) are also stronger over the eastern US plus GLA (e.g., Figure S1) than over most of the west, as is already well established in previous studies. (16,32−34) However, if there were no strong spatial differences in historical PM2.5 mitigation effectiveness, relative PM2.5 trends should be similar across the CONUS, while the significant regional variability of relative PM2.5 trends in Figure 1a further illustrates that these absolute trends are not proportional to, and thus cannot be fully explained by, the spatially varying baseline pollution level (e.g., Figure S2).

Figure 1

Figure 1. Strong regional variation of PM2.5 relative trends (ΔPM2.5) across the CONUS. (a) Relative areal trends (%/yr) in annual mean PM2.5 during 1998–2019 from the satellite-derived estimates (background) and in situ measurements (points). Insignificant trends with p ≥ 0.05 are displayed with more transparent colors and smaller symbols. (b) Population (bin-width normalized distribution, blue line, left Y-axis) and 1998–2019 mean population-weighted (PW) PM2.5 chemical composition (right Y-axis, color-coded on the top) as a function of these trends. All components are presented at 35% relative humidity (RH) for consistency with PM2.5 mass concentration measurements. OM and BC are separated into contributions from open burning (Fire) and other sources (noFire). Vertical dotted lines are the thresholds to separate the four regions (Figure S4).

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As PM2.5 chemical composition is insightful about responses of PM2.5 to sources and has been important to interpret PM2.5 trends, (9,10,19) we investigate how PM2.5 speciation varies with relative PM2.5 trends (ΔPM2.5) to unveil possible drivers of this regional variation. We sort the CONUS pixels by local relative PM2.5 trends. Figure 1b (background) shows the 1998–2019 mean mass fraction for each PM2.5 chemical component for 200 ΔPM2.5 bins. It is evident that the locations with stronger negative trends coincide with stronger sulfate mass fraction in PM2.5 (red), which decreases from 33% to 9% as the relative PM2.5 trends weaken in magnitude. This decrease is nearly monotonic across pixels with negative PM2.5 trends, except for a transient reversal regime at −3.4%/yr < ΔPM2.5 < −2.5%/yr (dotted lines) where an enhanced nitrate (orange) contribution slightly disrupts this association of sulfate fraction versus relative PM2.5 trends. Over the entire figure, the fraction of fire-associated OM (brown) plus dust (yellow) increases from 9% to 36%, as the relative PM2.5 reduction weakens, and the fraction of the CONUS population (blue line) diminishes. Sulfate in the CONUS is dominantly formed by sulfur dioxide (SO2) emissions from coal combustion in power plants, (12,35,36) which has been substantially reduced for five decades as a primary target of regulatory policies; (37−39) meanwhile fire-OM and dust are overall less readily regulatable due to their primarily natural origins and sensitivity to climate change. (32,40,41) The regional variation of relative PM2.5 trends directly relates to such varying chemical composition and how effectively specific components have been reduced.
Table 1 summarizes the correlation coefficients between relative PM2.5 trends and the long-term mass fraction of the main PM2.5 components. Trends in the remaining components (BC, dust, and sea salt) do not make significant contributions to the total PM2.5 trends (e.g., Figure 2). Sulfate mass fraction exhibits the strongest anticorrelation (e.g., r = −0.78 at pixel level) with relative PM2.5 trends based on both the estimates and long-term in situ observations among all components, further indicating the driving role of PM2.5 speciation in the regionally varying reduction rates. Figure S1 shows that sulfate exhibits CONUS-wide reductions that are the strongest among all components, supported by both the estimates and in situ observations (i.e., R2 > 0.45 for co-located trends). CONUS-wide, the PW-PM2.5 reduction (±95% confidence interval) of −0.30 ± 0.03 μg/m3/yr is dominantly from PW decreases of sulfate (−0.11 ± 0.01 μg/m3/yr), OM (−0.08 ± 0.01 μg/m3/yr), ammonium (−0.05 ± 0.01 μg/m3/yr), and nitrate (−0.04 ± 0.01 μg/m3/yr).
Table 1. Correlation Coefficients (r) between the 1998–2019 Mean Mass Fraction of Major PM2.5 Chemical Compositions (Separated by Rows) and Relative PM2.5 Trends at Pixel (Column 2) and County (Column 3, population-weighted) Level, from in Situ Observational Sites (Column 4), and from Co-located Estimates at Observational Sites (Column 5), across the CONUSa
ComponentCorrelation (1 km2)Correlation (county)Correlation (in situ)Correlation (co-located)
Sulfate–0.78–0.79–0.56–0.62
Ammonium–0.44–0.38–0.48–0.49
Nitrate0.080.25–0.07 (0.4)–0.03 (0.7)
OM0.290.210.36 (0.001)0.34 (0.007)
a

Correlations with p < 0.001 are bold and otherwise are followed by the p-values in the brackets. For in situ observations, the nearest PM2.5 measurement (within 20 km) is used for each component observation to derive the mass fraction. Only locations with significant (p < 0.05) PM2.5 trends are investigated.

Figure 2

Figure 2. Sulfate dominates the PM2.5 reductions and its regional variation. On the left, circles and error bars (color-coded for the four regions) represent relative trends and 95% confidence intervals in annual mean regional PW PM2.5 (35% RH) over 1998–2019. Pixels in each region are further divided into four population bins (separated by purple lines and texts) following the overall PW-PM2.5 cases (the top four rows). Stacked bars indicate compositional trends (consistently normalized to multi-year mean PW PM2.5) to represent their contributions. Filled circles and bars are significant trends (p < 0.05) and empty ones are not. On the right, stacked bars represent compositional contribution to the multi-year mean PW PM2.5 for each case. OM and BC are separated into contributions from open burning (Fire) and other sources (noFire). All components are presented at 35% RH for consistency with PM2.5 mass concentration measurements.

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Figure S3 shows the binned PW speciated component fraction (similar to Figure 1b) as a function of relative PM2.5 trends (ΔPM2.5) for the start (a) and end (b) of the investigated period (1998–2019), as well as their corresponding changes (c). From 1998–2000 to 2017–2019, sulfate exhibits negative changes (by up to −9%) in its fraction in PW-PM2.5 across all ΔPM2.5 levels, and stronger magnitudes of this fractional reduction are associated with more negative relative PM2.5 trends. This reduced sulfate fraction is largely compensated by the OM fraction, the other main component across the CONUS with relatively slower reduction. The increase in OM fraction (by 3–9% across all bins) in PW-PM2.5 is dominated by non-fire sources (by up to 8%) for pixels with relative PM2.5 reductions stronger than −2%/yr, and by fire sources (by up to 23%) for locations with slower (e.g., >−1%/yr) relative reduction rates. Overall, Figure S3 implicates substantial changes in PW-PM2.5 chemical composition (i.e., Figure S3a vs S3b) during 1998–2019 due to divergent changes in each component, with sulfate and OM exhibiting the strongest changes in their mass fractions. Consequently, the CONUS-wide PW sulfate/OM ratio of 0.70 in 1998 decreased to 0.47 in 2019.
The above evidence supports the conclusion that the effectiveness of sulfate regulation contributes the most to this US-wide regional diversity in relative PM2.5 trends, followed by OM. Besides this overall CONUS pattern, regional component contributions to PM2.5 and its trends warrants additional investigation to further understand and interpret such diversity of PM2.5 reduction rates.

Regionally Varying Compositional Drivers of PM2.5 Trends

We further divide the CONUS counties into four characteristic regions (i.e., dotted lines in Figure 1b), with limits chosen based on the speciation of PM2.5 as a function of relative PM2.5 trends (ΔPM2.5). Region 1 (ΔPM2.5 < −3.4%/yr & and p < 0.05) has the strongest relative PM2.5 trends and 25.9% of the CONUS population, primarily located over the Central Atlantic states (Figure S4). Region 2 (−3.4 ≤ ΔPM2.5 < −2.5%/yr and p < 0.05) hosts the largest CONUS population (39.7%), including the GLA and most of the eastern US apart from Region 1. Region 3 (−2.5 ≤ ΔPM2.5 < −0.9%/yr and p < 0.05) broadly spans the western Midwest and parts of the Southwest, and includes 25.6% of the CONUS population. Region 4 (ΔPM2.5 ≥ −0.9%/yr or p ≥ 0.05) includes the Mountain West (8.9% population) that is usually prone to sources of fire or dust. Using the above thresholds (i.e., dotted lines in Figure 1b), the division of four regions is almost identical as determined based on county- or pixel-level (Figure S4), again reflecting the strong regional rather than local division of variability in relative PM2.5 trends. We use the county-level definitions throughout the discussion, which maintain better spatial separation for each region, and closer relevance with regulatory policies.
Figure 2 (top 4 rows) summarizes component contributions to annual mean PW-PM2.5 and its trends for each region (Figure S5 shows more detailed results at the county level). PW-PM2.5 over Regions 1–4 exhibit variable relative PM2.5 trends of −3.6 ± 0.4%/yr, −3.0 ± 0.3%/yr, −1.9 ± 0.3%/yr, and −0.4 ± 0.5%/yr (statistically insignificant), respectively, with the 1998–2019 regional mean sulfate mass fraction decreasing from 29.5% in Region 1 to 11.8% in Region 4. Regional mean PW-sulfate roughly accounts for 40%, 34%, and 35% of relative PM2.5 trends from Region 1 to Region 3, respectively (see also Figures S5 and S6), stronger than contributions from the other PM2.5 components. OM is the second largest contributor to PW-PM2.5 reductions in Regions 1–3 (27–28%, Figure S6), where the OM reductions are negligibly affected by fire (Figure 2). In contrast, the sulfate mass fraction and its reduction (−0.02 μg/m3/yr) are less dominant in Region 4, where the decreasing components are counteracted by (statistically insignificant) increases in OM from fire (0.02 μg/m3/yr) and dust (0.001 μg/m3/yr) to yield an insignificant PW-PM2.5 trend. At the county scale (Figure S5), the association of more sulfate contribution with higher PW-PM2.5 reduction remains strong (e.g., Table 1), and sulfate leads with the fastest absolute reductions among all components in 2720 counties (76% population), which are located mostly over Regions 1–3 (Figure S7a, background). This dominance of sulfate as the most effectively mitigated component is also consistently indicated by the in situ observations (Figure S7a, dots). OM exhibits the second strongest reductions in most of the CONUS which can surpass sulfate decreases at certain locations, as also consistently indicated by both the estimates and ground-based measurements (Figure S7b).
Figure 2(other rows) further divides pixels in each region into four bins of population density (Figure S8). Variation of relative PW-PM2.5 trends and their component contributions is consistently pronounced across regions, while differences between population bins within the same region are relatively smaller. This invariability among population bins is consistent with the sulfate dominance of these trends, since sulfate is a regional pollutant that can be secondarily formed at >1000 km downwind of SO2 sources (42) and exhibits the weakest urban/rural differences among PM2.5 components. (43) Only Region 4 exhibits a weakly systematic relation of relative PM2.5 trends with population bins, with reduced impacts from fire OM and dust as well as stronger reductions in PW-PM2.5 with increasing population density. Only in the relatively more populated places (e.g., >150/km2) is PW-PM2.5 significantly reduced in Region 4.
Figure S9 investigates the component contributions to the PW-PM2.5 mass and relative PM2.5 trends in winter (DJF) and summer (JJA). In winter, OM reductions become stronger than sulfate in all regions, reflecting both effective policies of reducing residential emissions of primary OM (44) and reduced photochemical formation of sulfate. (45) Nitrate also exhibits more pronounced reductions in winter due to the enhanced formation, (45,46) especially over Regions 2–4 where nitrate reductions compete with or in some cases surpass the sulfate reductions. In Regions 3 and 4, OM from fire and dust have enhanced impacts on PM2.5 mitigation in summer, leading to weaker relative PM2.5 trends than in winter. Meanwhile in the more populous Regions 1 and 2, PW-PM2.5 reduction rates are stronger in summer than winter, consistent with the seasonality of stronger sulfate contribution in summer, and with the overall leading role of sulfate reductions in driving the relative PM2.5 trends.

Importance of Reducing Other Components to Meet the New EPA Standard

As sulfate has already been substantially reduced, measures to reduce other components (e.g., OM and nitrate) will become increasingly important for further mitigation of PM2.5 air pollution to meet a stricter annual mean standard. Figure 3 illustrates this argument with a focus on the new EPA standard (9 μg/m3). Based on contemporary (2017–2019) PM2.5 concentrations, 21.9% of the CONUS population lives where annual mean PM2.5 concentrations exceed 9 μg/m3, with low sulfate mass fractions especially at high PW-PM2.5. The locations exceeding the new standard are mainly urban centers and fire-prone regions (Figure S10a). The PW-PM2.5 and PW-sulfate for these regions are 10.5 and 1.5 μg/m3 (Figure 3, pie chart on the right), respectively, indicating that even eliminating CONUS-wide anthropogenic sulfate sources (with interannual variability and remaining background sulfate) may be insufficient to meet the standard in many of these regions. In contrast, PW-OM (4.7 μg/m3, 1.0 μg/m3 from open burning for PM2.5 > 9 μg/m3) is more dominant over these nonattainment regions. Figure S10b indicates that reducing OM is especially critical over the fire-prone states of California, Arizona, Oregon, Washington, Idaho, Montana, and several metropolitan areas in the southeastern US (e.g., Atlanta). Furthermore, PW-nitrate (1.4 μg/m3 for PM2.5>9 μg/m3 and 1.9 μg/m3 for PM2.5>10 μg/m3) has greater contribution to PW-PM2.5 at higher PM2.5 levels (Figure 3), with particular relevance to achieve the new guideline over central and southern California, as well as cities near the Great Lakes (e.g., Chicago, Detroit, and Pittsburgh). Achieving the new standard will depend on enhanced measures to reduce these components in the future.

Figure 3

Figure 3. Future PM2.5 mitigation over the CONUS will require stronger measures to reduce components in addition to sulfate. Population (bin-width normalized distribution, blue line, left Y-axis) and 2017–2019 mean population-weighted (PW) PM2.5 chemical composition (right Y-axis, color-coded on the top) as a function of 2017–2019 mean PM2.5 concentrations. The vertical dotted line represents the new EPA standard (9 μg/m3). The two pie charts show the compositional fraction of PW-PM2.5 for pixels attaining (left) and violating (right) this standard based on the 2017–2019 mean concentrations. All components are presented at 35% RH for consistency with PM2.5 mass concentration measurements.

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Discussion

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Motivated by the tightening of the annual PM2.5 standard by the US EPA, we report a timely examination of the relative and absolute reductions of population exposure to PM2.5 and its chemical composition over the CONUS over the past two decades. We employed high-resolution estimates developed from a combination of satellite remote sensing, modeling of atmospheric composition, and in situ measurements, with complete coverage across the CONUS that enabled examination of population-weighted quantities. Interpretation of these high-resolution estimates together with in situ observations reveals that regional reductions have a clear connection with sulfate contributions to PM2.5, as sulfate has been the most successfully regulated PM2.5 component during 1998–2019. Locations more dominated by sulfate thus experienced stronger relative PM2.5 trends, an almost uniform CONUS-wide feature during the past two decades (e.g., Figures 1b and S4). This historical benefit from reduced sulfate becomes more prominent if jointly considering its partial contribution to mitigating OM during warm seasons by modulating secondary organic aerosol formation yields from biogenic volatile organic compounds (VOC) emissions. (47,48)
Our findings also highlight the necessity to improve the understanding and regulation of emissions and formation of the other PM2.5 components, especially OM and nitrate. Even complete elimination of sulfate may be insufficient for many regions to achieve the new annual mean PM2.5 standard of 9 μg/m3 (Figure 3). We find that OM has the second strongest reduction (Figures S6 and S7) broadly over the CONUS and is the driving component of PM2.5 reduction rates over certain locations (Figure S7a) and seasons (Figure S9a), with increasing dominance of PW-PM2.5 in recent years (Figure S3). The latter finding implies an increasing urgency to sustain and strengthen previous OM reductions. Regulation of anthropogenic emissions of primary OM has been attributed to 2/3 of these reductions. (44) However, VOCs from volatile chemical products (VCP) have recently become more pervasive than vehicle VOCs and the dominant source of secondary OM in the urban US. (49,50) Moreover, fire over the CONUS (especially in the west) has been and is predicted to become stronger, more frequent, and spatially broader, (51−53) as reflected by its uniformly increasing contribution to PW-PM2.5 (Figure S3c). Strategies are needed to deal with these emerging OM sources. (54−57) Locally, mitigation of nitrate, which comprises 13.3% of PW-PM2.5 in locations violating the new standard, has been critical to the successful air quality improvement over Region 2 (e.g., GLA and the Great Lakes, Figures 1b, S2, and S10c). Sustaining nitrate mitigation requires more stringent efforts to reduce traditionally unregulated ammonia emissions. (46,58,59) In addition, measures to better characterize and regulate sources of other components including ammonium, dust, and BC can further aid the mitigation success (60−62) and possibly meet the more rigorous WHO guideline (5 μg/m3). (63) Ongoing development of the combined ground- and satellite-based monitoring systems, together with advanced modeling capabilities, will be needed to assess and guide progress (Text S3). Following the growing recognition of health impacts of PM2.5 at low concentrations (e.g., < 10 μg/m3), (1) activities to sustain the air quality improvement in the US are increasingly crucial, calling upon improved understanding and mitigation actions of both combustion-related and traditionally unregulated sources.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestair.4c00004.

  • Complementary descriptions of the used data sets and uncertainties, figures, and table to support interpretation (PDF)

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Author Information

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  • Corresponding Author
  • Authors
    • Randall V. Martin - Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
    • Aaron van Donkelaar - Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
  • Author Contributions

    The manuscript was written through contributions of all authors. The conceptualization was initialized by CL and RVM. The data and methodology were developed by CL and AVD. CL performed the visualization of the results, which were analyzed by all the authors. CL wrote the original draft. All authors have reviewed, edited, and given approval to the final version of the manuscript.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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This work was supported by the National Aeronautics and Space Administration (Grant No. 80NSSC21K0508 and 80NSSC22K0200) and the National Science Foundation (Grant No. 2244984). The authors thank the teams responsible for collecting and making available the ground-based observations used in this work.

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  5. J. L. Hand, A. J. Prenni, S. M. Raffuse, N. P. Hyslop, W. C. Malm, B. A. Schichtel. Spatial and Seasonal Variability of Remote and Urban Speciated Fine Particulate Matter in the United States. Journal of Geophysical Research: Atmospheres 2024, 129 (23) https://doi.org/10.1029/2024JD042579
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Published May 9, 2024

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  • Abstract

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    Figure 1

    Figure 1. Strong regional variation of PM2.5 relative trends (ΔPM2.5) across the CONUS. (a) Relative areal trends (%/yr) in annual mean PM2.5 during 1998–2019 from the satellite-derived estimates (background) and in situ measurements (points). Insignificant trends with p ≥ 0.05 are displayed with more transparent colors and smaller symbols. (b) Population (bin-width normalized distribution, blue line, left Y-axis) and 1998–2019 mean population-weighted (PW) PM2.5 chemical composition (right Y-axis, color-coded on the top) as a function of these trends. All components are presented at 35% relative humidity (RH) for consistency with PM2.5 mass concentration measurements. OM and BC are separated into contributions from open burning (Fire) and other sources (noFire). Vertical dotted lines are the thresholds to separate the four regions (Figure S4).

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    Figure 2

    Figure 2. Sulfate dominates the PM2.5 reductions and its regional variation. On the left, circles and error bars (color-coded for the four regions) represent relative trends and 95% confidence intervals in annual mean regional PW PM2.5 (35% RH) over 1998–2019. Pixels in each region are further divided into four population bins (separated by purple lines and texts) following the overall PW-PM2.5 cases (the top four rows). Stacked bars indicate compositional trends (consistently normalized to multi-year mean PW PM2.5) to represent their contributions. Filled circles and bars are significant trends (p < 0.05) and empty ones are not. On the right, stacked bars represent compositional contribution to the multi-year mean PW PM2.5 for each case. OM and BC are separated into contributions from open burning (Fire) and other sources (noFire). All components are presented at 35% RH for consistency with PM2.5 mass concentration measurements.

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    Figure 3

    Figure 3. Future PM2.5 mitigation over the CONUS will require stronger measures to reduce components in addition to sulfate. Population (bin-width normalized distribution, blue line, left Y-axis) and 2017–2019 mean population-weighted (PW) PM2.5 chemical composition (right Y-axis, color-coded on the top) as a function of 2017–2019 mean PM2.5 concentrations. The vertical dotted line represents the new EPA standard (9 μg/m3). The two pie charts show the compositional fraction of PW-PM2.5 for pixels attaining (left) and violating (right) this standard based on the 2017–2019 mean concentrations. All components are presented at 35% RH for consistency with PM2.5 mass concentration measurements.

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