Smog's metallic fingerprint: Nickel, vanadium, sulfates most strongly linked to asthma hospitalizations

It is known that fine particles PM2.5 increase the risk of asthma exacerbations. But PM2.5 is a mixture of dozens of components (metals, inorganic salts and organics), and until now it was unclear which "building blocks" of the mixture are the most dangerous. The authors of the new work suggested looking not at one pollutant, but at the mixture at once and assessing its contribution to hospitalizations for asthma. The study was published on August 29, 2025 in the American Journal of Respiratory and Critical Care Medicine.

Background of the study

Asthma is one of the most common noncommunicable diseases in the world and a leading cause of hospitalization in children; according to WHO, ~262 million people lived with asthma in 2019, and 455,000 died from its consequences. Even with the availability of effective inhalation therapy, the disease burden remains high and sensitive to air quality: exacerbations are associated with weather, viruses, and especially environmental air pollutants. The GINA guidelines emphasize that reducing exposure to fine particles and gases is an important part of exacerbation prevention at both the patient and city policy levels.

The key "trigger" for asthma is fine particles PM2.5, but this is not a single substance, but a mixture of dozens of components: secondary sulfates and nitrates (formed from SO₂/NOₓ emissions with the participation of ammonia), organic and elemental carbon, metals, etc. The sources vary: coal-fired thermal power plants and other sources of SO₂ feed sulfate aerosols; transport and agriculture provide NOₓ/NH₃ for nitrates; nickel and vanadium are typical for the combustion of heavy oil products (fuel oil, marine fuel) and often serve as "tracers" of such emissions. The contribution of secondary particles to the PM2.5 mass in cities can reach tens of percent, and metal-containing fractions are associated with increased toxicity of the aerosol for the respiratory tract.

Most early epidemiological studies examined “single” pollutants (e.g., PM2.5 as a whole or as a single gas), but in real life we inhale a mixture of components that are correlated with each other. Due to collinearity and “substitution” of sources, the analysis of one substance may underestimate or distort the contribution of others. Therefore, weighted quantile sum (WQS) regression methods are increasingly used to estimate the combined effect and “weights” of individual components. They construct a mixture index and allow simultaneous assessment of both the overall risk and the relative contribution of the mixture “building blocks.” With growing evidence linking long-term PM2.5 exposure to asthma risk in children and adults, such approaches are becoming the standard for studies targeting controlled sources.

This is where a new paper in the American Journal of Respiratory and Critical Care Medicine fits in, assessing the long-term (annual) impact of PM2.5 mixtures on asthma hospitalizations in the United States using large hospital databases and ZIP-code-level exposure models for 2002–2016. The mixture methodology (WQS) is important here not just for the formal sense, but for the practical sense: it highlights policy targets—the components whose reduction (e.g., metal-containing fractions from heavy fuel combustion and secondary sulfates/nitrates) are most likely to reduce asthma hospitalizations.

How the study was conducted

The team collected 469,005 asthma hospitalizations in 11 US states from 2002 to 2016 (HCUP hospital databases). For each zip code (ZIP), the authors obtained annual estimates of PM2.5 components and gases (NO₂, O₃) using data from previous measurement networks and machine learning algorithms. The final “cocktail” included, among others, bromine, calcium, copper, elemental carbon, iron, potassium, ammonium, nickel, nitrate, organic carbon, lead, silicon, sulfate, vanadium, zinc. Next, they applied the weighted quantile sum (WQS) method to estimate the combined effect of the mixture and the “weights” of the contribution of each component; children 0-18 years old and adults 19-64 years old were modeled separately, taking into account temperature and socioeconomic factors.

What we found (key figures)

For each shift of the mixture by one decile (10% step of the distribution), the number of asthma hospitalizations increased by 10.6% in children and by 8.0% in adults. The association was “pulled” to the greatest extent by nickel, vanadium, sulfate, nitrate, bromine, and ammonium - these are the components that gained the maximum “weights” in the WQS model. The authors' conclusion: long-term exposure to a mixture of pollutants is significantly associated with asthma hospitalizations, and both children and adults are vulnerable.

Where do the most "harmful" fractions come from?

• Nickel and vanadium are typical impurities of heavy grades of fuel oil/heating oil (large buildings, boiler houses).
• Sulfates are a product of coal combustion (and secondary formation in the atmosphere).
• Nitrate and ammonium are associated with the acid-base balance of aerosols and secondary inorganic particles formed from NOx/NH₃.
  The authors emphasize that these sources are controlled technologically (scrubbers at thermal power plants, switching to cleaner fuel, cleaning oils from metals).

Why this matters for politics and medicine

The work shifts the focus from “average” PM2.5 to specific mixing factors, providing targeted guidance for environmental regulation: reducing metals and sulfates may provide the greatest benefit to people with asthma. It provides additional support for clinicians to include environmental exposure in risk assessments and patient recommendations (e.g., using air purifiers during “polluted” seasons, avoiding outdoor activities during poor air quality forecasts, optimizing controller therapy).

What's new in methods

• Mix instead of singles: analysis of the mixture of components PM2.5 + NO₂ + O₃, rather than the effects of each separately.
• WQS regression: allows you to assign a weight to each component of the mixture and calculate the total impact.
• ZIP-level georeferencing: annual exposure estimates on a fine-grained grid, consistent with hospital data.

Limitations (things to remember)

This is an observational study with annual rather than daily component estimates (the authors specifically note the importance of daily measurements for studying short-term triggers). There may be residual confounding (behavior, intra-annual spikes, migration), although temperature and social factors were controlled for. Generalizability beyond the 11 states requires separate testing. However, the consistency of results in children and adults and the reproducibility of the “heavy” contributors to the mixture add credibility to the findings.

What's next?

• Monitor components by day: expand nickel, vanadium, sulfate, ammonium and nitrate measurement networks to catch short-term risk peaks.
• Targeted interventions: assess the effect of scrubbers, switching to low-sulfur/metal-free fuel, local bans on fuel oil during the heating season.
• Personalized prevention: research into the real-world effectiveness of air purifiers, smart risk alerts, and “asthma plans” on bad air days.

Study source: Am J Respir Crit Care Med (Sep 2025; 211(9):1636-1643): Bryan N. Vu et al. “Association of Annual Exposure to Air Pollution Mixture on Asthma Hospitalizations in the United States,” DOI: 10.1164/rccm.202409-1853OC.