US Air Quality Research Articles

A Call to Action for Global Solutions to Air Quality Crisis: Urgent Actions and Innovative Solutions Needed

ABSTRACT Air pollution, specifically smog, has become a prevalent concern worldwide due to its association with various health risks including stroke, heart disease, lung disease, lower respiratory disorders, and cancer. The excessive use of fossil fuels and the rapidly increasing population have led to the rise in air pollution, which also increases the risk of other ailments such as diabetes and negatively impacts cognitive development in children as well as mental health. According to the World Health Organization, almost 7 million people die each year due to air pollution. According to the recent reports by the Swiss organization (IQAir) on October 22nd, 2024, accessed at (https://www.iqair.com) Lahore in Pakistan, Delhi in India, Kinshasa in Democratic Republic of the Congo, Milano in Italy, Belgrade in Serbia, Jakarta in Indonesia and Karachi in Pakistan have been identified as the top seven cities with the highest US Air Quality Index (AQI). The rising levels of air pollution pose significant health risks globally, necessitating immediate action from governments and communities. Implementing effective policies, investing in clean technologies, and fostering international collaboration are essential to mitigate the impacts of air quality deterioration on public health and the environment.

Modeling nonstationary surface‐level ozone extremes through the lens of US air quality standards: A Bayesian hierarchical approach

AbstractSurface‐level ozone (O) is a harmful air pollutant whose effects may be more deleterious when at its most extreme levels. Current US air quality standards are written in terms of the 3‐year average of the 4th highest annual daily maximum 8‐h O values; therefore, developing approaches based on extreme value theory may be useful. We develop a Bayesian hierarchical approach, where the ‐largest order statistics are parametrized by the generalized extreme value (GEV) distribution, while a Gaussian process is employed to characterize how the GEV parameters depend on the O precursors, namely nitrous oxides (NO) and volatile organic compounds (VOCs). The fitted model is then used to characterize the upper tail of the distribution of O and estimate O noncompliance probabilities. We illustrate the proposed method using data from an air quality station in Providence, Rhode Island (RI). The results suggest that the far upper tail of extreme O values is likely bounded, and the dependence of the upper tail distribution on NO and O is highly nonlinear, consistent with the known relationship, albeit not specifically for extreme values, in the existing scientific literature. A convolution‐based approach is used to estimate noncompliance probabilities for several covariate scenarios. Our results indicate that estimated noncompliance probabilities in recent years are much lower than in the mid‐1990s, primarily due to lower O precursor levels. However, the estimated noncompliance probabilities appear to rise sharply for hypothetical stricter O standards, even for the conditions observed in recent years.

Forecasting Daily Fire Radiative Energy Using Data Driven Methods and Machine Learning Techniques

AbstractIncreasing impacts of wildfires on Western US air quality highlights the need for forecasts of smoke emissions based on dynamic modeled wildfires. This work utilizes knowledge of weather, fuels, topography, and firefighting, combined with machine learning and other statistical methods, to generate 1‐ and 2‐day forecasts of fire radiative energy (FRE). The models are trained on data covering 2019 and 2021 and evaluated on data for 2020. For the 1‐day (2‐day) forecasts, the random forest model shows the most skill, explaining 48% (25%) of the variance in observed daily FRE when trained on all available predictors compared to the 2% (<0%) of variance explained by persistence for the extreme fire year of 2020. The random forest model also shows improved skill in forecasting day‐to‐day increases and decreases in FRE, with 28% (39%) of observed increase (decrease) days predicted, and increase (decrease) days are identified with 62% (60%) accuracy. Error in the random forest increases with FRE, and the random forest tends toward persistence under severe fire weather. Sensitivity analysis shows that near‐surface weather and the latest observed FRE contribute the most to the skill of the model. When the random forest model was trained on subsets of the training data produced by agencies (e.g., the Canadian or US Forest Services), comparable if not better performance was achieved (1‐day R2 = 0.39–0.48, 2‐day R2 = 0.13–0.34). FRE is used to compute emissions, so these results demonstrate potential for improved fire emissions forecasts for air quality models.

The GFDL Variable‐Resolution Global Chemistry‐Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

AbstractWe present a variable‐resolution global chemistry‐climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban‐to‐rural chemical regimes, mesoscale convective systems, and land‐surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi‐decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25‐km uniform‐resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal‐to‐diurnal cycles and extremes, notably reducing the central US dry‐and‐warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process‐level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land‐biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

Revisiting day-of-week ozone patterns in an era of evolving US air quality

Abstract. Past work has shown that traffic patterns in the USA and resulting NOx emissions vary by day of week, with NOx emissions typically being higher on weekdays than weekends. This pattern of emissions leads to different levels of ozone on weekends versus weekdays and can be leveraged to understand how local ozone formation changes in response to NOx emission perturbations in different urban areas. Specifically, areas with lower NOx but higher ozone on the weekends (the weekend effect) can be characterized as NOx-saturated and areas with both lower NOx and ozone on weekends (the weekday effect) can be characterized as NOx-limited. In this analysis, we assess maximum daily 8 h average (MDA8) ozone weekend–weekday differences across 51 USA nonattainment areas using 18 years of observed and modeled data from 2002–2019, using the following two metrics: mean MDA8 ozone and percentage of days with MDA8 ozone > 70 ppb (parts per billion). In addition, we quantify the modeled and observed trends in these weekend–weekday differences across this period of substantial NOx emission reductions in the USA. The model assessment is carried out using U.S. Environmental Protection Agency (EPA)'s Air QUAlity TimE Series Project (EQUATES) Community Multiscale Air Quality (CMAQ) model dataset. We identify three types of MDA8 ozone trends occurring across the USA, namely transitioning chemical regime, disappearing weekday effect, and no trend. The transitioning chemical regime trend occurs in a subset of large urban areas that were NOx-saturated (i.e., volatile organic compound (VOC)-limited) at the beginning of the analysis period but transitioned to mixed chemical regimes or NOx-limited conditions by the end of the analysis period. Nine areas have strong transitioning chemical regime trends using both modeled and observed data and with both metrics indicating strong agreement that they are shifting to more NOx-limited conditions: Milwaukee, Houston, Phoenix, Denver, the Northern Wasatch Front, the Southern Wasatch Front, Las Vegas, Los Angeles – San Bernardino County, Los Angeles – South Coast, and San Diego. The disappearing weekday effect was identified for multiple rural and agricultural areas of California which were NOx-limited for the entire analysis period but appear to become less influenced by local day-of-week emission patterns in more recent years. Finally, we discuss a variety of reasons why there are no trends in certain areas including complex impacts of heterogeneous source mixes and stochastic impacts of meteorology. Overall, this assessment finds that the EQUATES modeling simulations indicate more NOx-saturated conditions than the observations but do a good job of capturing year-to-year changes in weekend–weekday MDA8 ozone patterns.

Health and equity implications of individual adaptation to air pollution in a changing climate

Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM2.5), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyone's need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation.

COVID-19 perturbation on US air quality and human health impact assessment.

The COVID-19 stay-at-home orders issued in the United States caused significant reductions in traffic and economic activities. To understand the pandemic's perturbations on US emissions and impacts on urban air quality, we developed near-real-time bottom-up emission inventories based on publicly available energy and economic datasets, simulated the emission changes in a chemical transport model, and evaluated air quality impacts against various observations. The COVID-19 pandemic affected US emissions across broad-based energy and economic sectors and the impacts persisted to 2021. Compared with 2019 business-as-usual emission scenario, COVID-19 perturbations resulted in annual decreases of 10-15% in emissions of ozone (O3) and fine particle (PM2.5) gas-phase precursors, which are about two to four times larger than long-term annual trends during 2010-2019. While significant COVID-induced reductions in transportation and industrial activities, particularly in April-June 2020, resulted in overall national decreases in air pollutants, meteorological variability across the nation led to local increases or decreases of air pollutants, and mixed air quality changes across the United States between 2019 and 2020. Over a full year (April 2020 to March 2021), COVID-induced emission reductions led to 3-4% decreases in national population-weighted annual fourth maximum of daily maximum 8-h average O3 and annual PM2.5. Assuming these emission reductions could be maintained in the future, the result would be a 4-5% decrease in premature mortality attributable to ambient air pollution, suggesting that continued efforts to mitigate gaseous pollutants from anthropogenic sources can further protect human health from air pollution in the future.

More on Summer 2023 US Air Quality: Local Actions for a Physicist

<i>More on Summer 2023 US Air Quality: Local Actions for a Physicist</i>

Nuclear power generation phase-outs redistribute US air quality and climate-related mortality risk.

We explore how nuclear shut-downs in the United States could affect air pollution, climate and health with existing and alternative grid infrastructure. We develop a dispatch model to estimate emissions of CO2, NO x and SO2 from each electricity-generating unit, feeding these emissions into a chemical transport model to calculate effects on ground-level ozone and fine particulate matter (PM2.5). Our scenario of removing nuclear power results in compensation by coal, gas and oil, resulting in increases in PM2.5 and ozone that lead to an extra 5,200 annual mortalities. Changes in CO2 emissions lead to an order of magnitude higher mortalities throughout the twenty-first century, incurring US$11-180 billion of damages from 1 year of emissions. A scenario exploring simultaneous closures of nuclear and coal plants redistributes health impacts and a scenario with increased penetration of renewables reduces health impacts. Inequities in exposure to pollution are persistent across all scenarios-Black or African American people are exposed to the highest relative levels of pollution.

Ozone and childhood respiratory health: A primer for US pediatric providers and a call for a more protective standard.

Ground level ozone is a potent respiratory toxicant with decades of accumulated data demonstrating respiratory harms to children. Despite the ubiquity of ozone in the United States, impacting both urban and rural communities, the associated harms of exposure to this important air pollutant are often infrequently or inadequately covered during medical training including pulmonary specialization. Thus, many providers caring for children's respiratory health may have limited knowledge of the harms which may result in reduced discussion of ozone pollution during clinical encounters. Further, the current US air quality standard for ozone does not adequately protect children. In this nonsystematic review, we present basic background information for healthcare providers caring for children's respiratory health, review the US process for setting air quality standards, discuss the respiratory harms of ozone for healthy children and those with underlying respiratory disease, highlight the urgent need for a more protective ozone standard to adequately protect children's respiratory health, review impacts of climate change on ozone levels, and provide information for discussion in clinical encounters.

Air pollution a hidden scourge to cardiovascular health: insight from top polluted cities of Pakistan.

Dear Editor, A range of disorders impacting the cardiovascular system, which includes the heart and blood vessels, are referred to as cardiovascular diseases (CVDs). This mainly includes coronary artery disease, coronary heart disease, cerebrovascular disease, peripheral artery disease, and aortic atherosclerosis1. According to the WHO, 17.9 million deaths were due to CVDs in 2019, representing 32% of global deaths2. There are nine determining modifiable risk factors of CVD, namely smoking, diabetes mellitus, hypertension, obesity, psychosocial factors, unhealthy diet, lack of exercise, alcohol consumption, and apoB/apoA1 ratio3. Air pollution (AP) is known to be another risk factor and is associated with premature deaths in CVD patients in primarily low- and middle-income countries4. Furthermore, new research indicates that prolonged exposure to AP may raise the mortality risk of CVD patients5,6. It has been shown in a few studies that AP increases the chance of developing CVDs such as myocardial infarction, ischemic heart disease, cardiac arrhythmia, heart failure, or cardiac arrest5,6. Particulate matter measuring 2.5 µm in diameter or less (PM2.5) and particulate matter measuring 10 µm in diameter or less (PM10) concentration are used to determine AP. As per WHO 2021 Air Quality guidelines the highest recommended average annual emission level for PM2.5 was 5 μg/m3 and for PM10 was 15 μg/m37. A study by Choi et al.5 showed, in patients, a higher concentration of PM10 was associated with an increased risk of death due to CVD. Furthermore, a study was done by Pope and colleagues, showing a statistical association between PM2.5 and overall cardiovascular mortality. The risk of myocardial infarction, ischemic heart disease, arrhythmia, heart failure, or cardiac arrest death was increased in polluted areas6. Recently Pakistan ranked as the third most polluted country globally based on an annual average PM2.5 concentration in 2021, by the WHO guidelines. 2021 average PM2.5 concentration in Pakistan is 13.4 times the WHO annual air quality guidelines7,8. The US Air Quality Index declared Lahore an unhealthy city for sensitive groups to live in8. According to WHO data from 2016, about 19% of all deaths in Pakistan were due to heart diseases. However, in only 3 years, a 29% increase occurred in deaths caused by CVDs9. This shows a dire need to take measures to mitigate AP and prevent an increase in cardiovascular patients and cardiovascular mortality in the country. CVD patients need multifactorial interventions, especially more intensive measures to modify individual cardiovascular risk factors with diet, drugs, exercise, weight management, complete smoking cessation, and avoidance of secondhand smoke, or combinations thereof10. A concerted effort should be made by the government to educate healthcare providers and at-risk patients alike about the potential health hazards of elevated AP levels through awareness campaigns. Real-time air quality information should be available in local and national media for people as implemented by the United States Environmental Protection Agency which provides air quality forecasts and reports for particle pollution available in different cities10. This will inform people to wear masks more often in areas badly affected by AP. Furthermore, government authorities should set stringent National Air Quality standards to lower PM2.5 concentration and take measures to reduce such as but not limited to, restricting open burning of waste and regulations to mitigate emissions from vehicles and factories. The government should make policies to reduce the use of fossil fuels for energy and replace it with increased construction and use of solar power and hydropower plants. Pakistan needs to protect its vulnerable population from AP-associated CVDs, otherwise, the death rate through CVDs could increase from the already appalling 29% in the near future. HIGHLIGHTS Multiple studies have associated air pollution (AP) with an increased risk of CVDs and CVD-associated mortality. The mortality rate in Pakistan has seen a 29% increase over three years due to CVDs. This article calls out the Government and respective authorities to take precautionary measures as constantly striking AP may appall the CVD associated mortality in the near future. Ethical approval Not applicable. Sources of funding None. Authors’ contribution S.T.R. and A.I. conceived the idea. S.K., U.N., H.u.H., I.U., and M.S.A. collected the data. S.T.R. and M.S.A. analyzed and interpreted the data. I.U. and S.T.R. did write up of the manuscript. M.S.A. reviewed and revised the manuscript for intellectual content critically. All authors approved the final version of the manuscript. Conflicts of interest disclosure The authors declare that they have no financial conflict of interest with regard to the content of this report. Research registration unique identifying number (UIN) None. Guarantor Muhammad Sohaib Asghar. Provenance and peer review Externally peer reviewed, not commissioned.

Location-specific strategies for eliminating US national racial-ethnic PM2.5 exposure inequality

Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.

Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties

Abstract. Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (aerosol optical depth) and aerosol size (using Ångström exponent – AE; fine-mode fraction – FMF) over Korea during the 2016 KORUS-AQ (KORea–US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun-Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8 and geostationary satellites (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval – YAER, version 2) as well as from reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 1000 m show an average AOD at 501 nm of 0.36 and an average AE of 1.11 with large standard deviation (0.12 and 0.15 for AOD and AE, respectively), likely due to mixing of different aerosol types (fine and coarse mode). The majority of AOD due to fine-mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories match the South Korean regional average derived from GOCI. GOCI-derived FMF, which was found to be slightly low compared to AErosol RObotic NETwork (AERONET) sites (Choi et al., 2018), is lower than 4STAR's observations during KORUS-AQ. Understanding the variability of aerosols helps reduce uncertainties in the aerosol direct radiative effect by quantifying the errors due to interpolating between sparse aerosol observation sites or modeled pixels, potentially reducing uncertainties in the upcoming observational capabilities. We observed that, contrary to the prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and models for the entire KORUS-AQ period, the reduction in correlation by 15 % is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial–temporal homogeneity is the meteorological period. High spatiotemporal variability occurs during the dynamic period (25–31 May), and low spatiotemporal variability occurs during the blocking pattern (1–7 June). While AOD and FMF / AE are interrelated, the spatial variability and relative variability of these parameters in this study indicate that microphysical processes vary at scales shorter than aerosol concentration processes at which microphysical processes such as aerosol particle formation, growth, and coagulation mostly impact the dominant aerosol size (characterized by, e.g., FMF / AE) and to some degree AOD. In addition to impacting aerosol size, aerosol concentration processes such as aerosol emission, transport, and removal mostly impact the AOD.

North-South Displacement Effects of Environmental Regulation: The Case of Battery Recycling

This study examines the effect of a tightening of the US air quality standard for lead in 2009 on the relocation of battery recycling to Mexico and on infant health in Mexico. In the United States, airborne lead dropped sharply near affected plants, most of which were battery-recycling plants. Exports of used batteries to Mexico rose markedly. In Mexico, production increased at battery-recycling plants relative to comparable industries, and birth outcomes deteriorated within two miles of those plants relative to areas slightly farther away. The case provides a salient example of a pollution-haven effect between a developed and a developing country. (JEL F18, I12, J13, O15, Q51, Q53, Q58)

Field observational constraints on the controllers in glyoxal (CHOCHO) reactive uptake to aerosol

Abstract. Glyoxal (CHOCHO), the simplest dicarbonyl in the troposphere, is a potential precursor for secondary organic aerosol (SOA) and brown carbon (BrC) affecting air quality and climate. The airborne measurement of CHOCHO concentrations during the KORUS-AQ (KORea–US Air Quality study) campaign in 2016 enables detailed quantification of loss mechanisms pertaining to SOA formation in the real atmosphere. The production of this molecule was mainly from oxidation of aromatics (59 %) initiated by hydroxyl radical (OH). CHOCHO loss to aerosol was found to be the most important removal path (69 %) and contributed to roughly ∼ 20 % (3.7 µg sm−3 ppmv−1 h−1, normalized with excess CO) of SOA growth in the first 6 h in Seoul Metropolitan Area. A reactive uptake coefficient (γ) of ∼ 0.008 best represents the loss of CHOCHO by surface uptake during the campaign. To our knowledge, we show the first field observation of aerosol surface-area-dependent (Asurf) CHOCHO uptake, which diverges from the simple surface uptake assumption as Asurf increases in ambient condition. Specifically, under the low (high) aerosol loading, the CHOCHO effective uptake rate coefficient, keff,uptake, linearly increases (levels off) with Asurf; thus, the irreversible surface uptake is a reasonable (unreasonable) approximation for simulating CHOCHO loss to aerosol. Dependence on photochemical impact and changes in the chemical and physical aerosol properties “free water”, as well as aerosol viscosity, are discussed as other possible factors influencing CHOCHO uptake rate. Our inferred Henry's law coefficient of CHOCHO, 7.0×108 M atm−1, is ∼ 2 orders of magnitude higher than those estimated from salting-in effects constrained by inorganic salts only consistent with laboratory findings that show similar high partitioning into water-soluble organics, which urges more understanding on CHOCHO solubility under real atmospheric conditions.

Aerosol data assimilation and forecast using Geostationary Ocean Color Imager aerosol optical depth and in-situ observations during the KORUS-AQ observing period

ABSTRACT This study develops an aerosol data assimilation and forecast system using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and the three-dimensional variational (3D-VAR) data assimilation method. The system assimilates the aerosol optical depth (AOD) from the Geostationary Ocean Color Imager (GOCI) satellite and surface particulate matter (PM) observations. The simulation domain covers Northeast Asia at 15 km horizontal resolution, and the assimilation and forecast skill is evaluated for the Korea–US Air Quality (KORUS-AQ) intensive observing period. Observing system experiments (OSEs) are conducted to examine the changes in quality of assimilation and forecast skills sensitive to the assimilated observational input data. The baseline model simulation underestimates AOD and surface PM concentration in most regions, in which the assimilation of satellite and in-situ data improves the mean biases and spatial distribution. Moreover, it improves the forecast skill of the surface concentration of PM10 and PM2.5. The results from the OSEs indicate that the assimilation of GOCI AOD only slightly enhances the forecast skill. However, most of the skill improvement comes from the surface PM assimilation, showing a practically useful level of skill until 12 hours from the initial state. The marginal improvement in the PM10 forecasts by the GOCI AOD suggests the non-negligible difference between column-representing AOD and the surface PM concentration.

Long-term Exposure to Fine Particulate Matter is Causally Linked to Mortality Among the Elderly

BACKGROUND AND AIM: Many studies link long-term fine particle (PM2.5) exposure to mortality, even at levels below current US air quality standards (12 μg/m3). These findings have been disputed citing traditional approaches do not guarantee evidence of causality. METHODS: Leveraging 16 years of data—68.5 million Medicare enrollees and 570 million observations—we estimated the causal effect of annual PM2.5 exposure on mortality. We implemented five statistical approaches to estimate the effect of PM2.5 exposure on mortality, accounting for potential confounders. The two traditional approaches rely on regression modeling for confounding adjustment: 1) Cox proportional hazards model, and 2) Poisson regression. We also considered three approaches for causal inference that rely on the potential outcomes framework and generalized propensity scores (GPS). RESULTS:We found that an increase of 10 μg/m3 PM2.5 leads to a statistically significant mortality risk increase, 6 to 8%. Lowering the standards to 10 μg/m3 would save 143,257 lives (95% confidence interval: 115,581–170,645) in one decade. CONCLUSIONS:Our study provides the most robust and reproducible evidence to date of the causal link between long-term PM2.5 exposure and mortality even at levels below the standards KEYWORDS: air pollution, methods

Chinese Regulations Are Working—Why Is Surface Ozone Over Industrialized Areas Still High? Applying Lessons From Northeast US Air Quality Evolution

AbstractObservational data indicate increasing trends of surface ozone (O3) in China, despite emission controls that have resulted in reductions of precursor emissions. Here, we explore the cause of this contradiction, through analysis of surface observations (2014–2019) in China and historical observation record in the United States (US, 1990–2019). Our observation‐based analysis indicates that the reductions of nitrogen oxides (NOx) emissions led to increase of surface O3 in North China Plain (NCP) and Yangtze River Delta (YRD) of around 8 ppb. However, NOx controls resulted in shift of O3 chemical regimes over NCP and YRD, with turning points between NOx‐ and volatile organic compound (VOC)‐limited regimes around 2019, while model simulations suggest transitional or NOx‐limited regimes over the rest of China. The impacts of high fine particles (PM2.5) on O3 formation has declined because of the reduction of PM2.5 concentrations. Stricter NOx controls can mitigate O3 pollutions over industrialized areas in China.

Long-term Baseline Ozone Changes in the Western US: A Synthesis of Analyses

Quantification of the magnitude and long-term changes of ozone concentrations transported into the US is important for effective air quality policy development. We synthesize multiple published trend analyses of western US baseline ozone, and show that all results are consistent with an overall, non-linear change – a rapid increase (~5 ppb/decade) during the 1980s that slowed in the 1990s, maximized in the mid-2000s, and was followed by a slow decrease (~1 ppb/decade) thereafter. This non-linear change accounts for ~2/3 of the variance in 28 published linear trend analyses; we attribute the other 1/3 of the variance to unquantified autocorrelation in the analyzed data sets that result primarily from meteorologically-driven interannual ozone variability. Recent systematic changes in baseline ozone at the US West Coast have been relatively small - the standard deviation of the 2-year means over the 1990-2017 period is 1.5 ppb. International efforts to reduce anthropogenic precursor emissions from all northern mid-latitude sources could possibly reduce baseline ozone concentrations, thereby improving US ozone air quality. Implications Statement Ozone is an air pollutant with significant human and ecological health impacts. Air masses transported into the western US from over the Pacific Ocean carry ozone concentrations that are, on average, a large fraction of the US health standard. The US EPA policy assessment conducted for the recent review of the ozone National Ambient Air Quality Standard (NAAQS) found that 2016 regional average MDA8 ozone concentrations in the western US maximized in summer at ~52 ppb and that ~40 ppb of that maximum was contributed by ozone of natural and transported anthropogenic contributions. Thus, quantifying these trans-boundary background ozone concentrations has been identified as an important issue for a complete understanding of US air quality (e.g., see discussion in Introduction of Jaffe et al., 2018). Published analyses of temporal trends of these transported ozone concentrations vary widely, from early reports of increases to more recent reports of decreases. We show that the long-term ozone changes have been nonlinear, with substantial concentration increases (as large as ~5 ppb/decade) before the mid-2000s when a maximum was reached, followed by a small decrease of ~1 ppb/decade) thereafter. Superimposed on the overall changes is significant interannual variability that makes accurate determination of systematic trends over decade-scale time periods uncertain. The end of the previously increasing trends, and the recent decreases in transported ozone concentrations is good news for US air quality, as it eases the difficulty of achieving the ozone air quality standard.

A novel approach to the development of 1‐hour threshold concentrations for exposure to particulate matter during episodic air pollution events

Episodic air pollution events that occur because of wildfires, dust storms and industrial incidents can expose populations to particulate matter (PM) concentrations in the thousands of µg m-3. Such events have increased in frequency and duration over recent years, with this trend predicted to continue in the short to medium term because of climate warming. The human health cost of episodic PM events can be significant, and inflammatory responses are measurable even after only a few hours of exposure. Consequently, advice for the protection of public health should be available as quickly as possible, yet the shortest averaging period for which PM exposure guideline values (GVs) are available is 24-h. To address this problem, we have developed a novel approach, based on Receiver Operating Characteristic (ROC) statistical analysis, that derives 1-h threshold concentrations that have a probabilistic relationship with 24-h GVs. The ROC analysis was carried out on PM10 and PM2.5 monitoring data from across the US for the period 2014–2019. Validation of the model against US Air Quality Index (AQI) 24-h breakpoint concentrations for PM showed that the maximum-observed 1-h PM concentration in any rolling 24-h averaging period is an excellent predictor of exceedances of 24-h GVs.