Different sources of fine particle air pollution show distinct, subtle links to how the developing brains of children communicate, according to new nationwide research published in Journal of Environmental Psychology. Particles from traffic, coal burning, and agricultural fertilizers were each tied to their own patterns of connectivity in networks involved in sensory processing and higher-order thinking. The findings offer early evidence that where air pollution comes from may matter, not just how much of it children breathe.
Outdoor air pollution contains fine particulate matter, commonly known as PM2.5, which consists of airborne particles smaller than 2.5 micrometers across. Because these specks are tiny enough to inhale deep into the lungs and enter the bloodstream, they may reach the brain.
The brain coordinates its activities through large-scale functional networks, which are collections of brain regions in different locations whose activity tends to rise and fall together. Researchers can measure this synchrony with brain scans that track changes in blood flow while a person lies still and rests. During childhood and the transition into adolescence, these communication channels continue to reorganize as youth develop adult reasoning, sensory integration, and emotional control.
Past research has linked outdoor air pollution to differences in these communication patterns. In a 2023 longitudinal study, members of the team behind the new research used data from the Adolescent Brain Cognitive Development Study, a large national project following thousands of American youth. They found that children with higher exposure to fine particles and other pollutants showed differences in how their resting brain networks matured across early adolescence. Additionally, a study covered by PsyPost in 2023 found that briefly breathing diesel exhaust in a controlled experiment temporarily weakened connectivity within the default mode network, a set of regions most active during mind-wandering and self-reflection, in adults.
Fine particulate matter is not a single chemical substance, but rather a complex blend created by both natural processes and human activities. Addressing this complexity, a 2024 study by members of the same team, using data from the same national project, found that specific chemical ingredients and pollution sources had varying relationships with children’s memory and thinking skills. The new study uses the six pollution sources identified in that work. The investigation was led by Katherine L. Bottenhorn of the University of Southern California and Florida International University and Megan M. Herting of the University of Southern California.
For the new study, the authors again drew on data from the Adolescent Brain Cognitive Development Study, which spans 21 research sites across the country. Data from one site were dropped because of hardware problems, leaving 20 sites for the cross-sectional analysis; the longitudinal analysis was limited to the 12 sites that used the same brand of scanner. The researchers analyzed brain scans from 6,291 children who were between 9 and 11 years old, as well as a subset of 1,972 participants scanned on consistent magnetic resonance imaging equipment roughly two years later, between ages 11 and 13.
The participants’ resting-state brain activity was recorded while they relaxed with their eyes open. The scientists mapped interactions among 12 functional networks, encompassing primary sensory networks like vision and hearing, attention circuits, and higher-order systems. The salience network helps flag important events and shift attention, while the cingulo-opercular network, described here as a cognitive-control network, helps keep attention on a task.
The team used annual air quality models tied to each child’s home address to estimate their exposure to 15 chemical components of air pollution during 2016. By grouping these chemicals mathematically, the authors estimated exposure to six primary sources: crustal materials (such as soil and dust), ammonium sulfates (largely from coal combustion), biomass burning (such as wood smoke and wildfires), traffic emissions, ammonium nitrates (often linked to agricultural fertilizers), and industrial fuel combustion.
The researchers applied a machine learning method called connectome-based predictive modeling to identify connectivity patterns related to each pollution source. To see if the results could generalize across the country, the scientists trained models using participants from all study sites except one, and then tested how well that model predicted pollution levels for children living at the held-out site. The analyses adjusted for several potential confounding variables, including household income, race and ethnicity, perceived neighborhood safety, neighborhood population density, distance to major roads, urbanicity, physical activity, screen time, scanner hardware, and head movement inside the scanner.
The cross-sectional analysis at ages 9 to 11 identified consistent links between specific pollution sources and connectivity across sensory and motor networks. Greater exposure to traffic emissions related to weaker functional communication between visual and mouth-related motor networks, as well as between auditory and cognitive-control circuits. In contrast, higher exposure to ammonium sulfates was linked to stronger communication between sensory systems and higher-order cognitive networks, including the default mode network. Crustal materials, industrial fuel burning, and total particulate matter were each tied to a handful of sensory and attention-related connections, while biomass burning showed no consistent pattern at ages 9 to 11.
Higher-order networks, which are involved in introspective thought, stimulus processing, and, according to some researchers, vulnerability to mental health problems, were also tied to specific pollution sources. Exposure to ammonium nitrates was associated with stronger communication between salience and cognitive-control networks, but weaker communication within memory networks and between attention networks and other networks.
Over the following two years, the researchers found consistent patterns of change linked to three sources. Higher traffic exposure was tied to increasing connectivity over time between hand-movement networks and attention-related areas, but decreasing connectivity between auditory and cognitive-control networks. Higher biomass burning exposure was linked to increasing connectivity among attention-related networks, and higher ammonium sulfate exposure to weakening connectivity between an attention network and a hand-movement network, while crustal materials, ammonium nitrates, industrial fuel burning, and total particulate matter showed no consistent pattern of change.
Despite identifying consistent connections in the training data, the connectivity patterns accounted for less than 1 percent of the variation in children’s exposure at ages 9 to 11, and no more than about 2 percent for changes over time. When tested on children from held-out study sites, the models performed no better, and often worse, than simply guessing the average exposure. Prediction errors were largest at sites in the western United States and at sites where exposure levels varied more from child to child.
The authors concluded that, after accounting for other factors, these pollution sources likely play only a small role in differences in brain connectivity between children, and that the links may not apply to youth in other regions. They also note that the patterns for biomass burning and ammonium sulfates held up best across sites, while those for crustal materials and traffic emissions deserve more caution.
The findings are in line with a study covered by PsyPost earlier this year, which found that young teenagers exposed to elevated particulate pollution showed less brain network maturation over two years, though that previous research evaluated an overall brain maturity score rather than connectivity across specific functional networks and distinct pollution sources.
“This is an important and timely topic, and the paper complements a growing body of evidence that children’s physical environments in general, and air pollution exposure in particular, are associated with their neural and cognitive development,” said Monica Rosenberg, an associate professor of psychology at the University of Chicago, director of the Cognition, Attention, and Brain Lab, and a co-developer of the brain-modeling technique used in the study, who was not involved in the research.
“The longitudinal aspect of this work is unique and is a major strength—the authors didn’t just show associations between brain networks and pollution at a single time point but found that pollution predicts developmental trajectories of networks,” Rosenberg told PsyPost.
There are a few things to keep in mind when interpreting these findings. The study used observational data and statistical associations, meaning it cannot establish that breathing these specific particles directly caused the observed network differences. Because the research took place across many regions with varying environmental mixtures, local factors that were unmeasured might account for some of the geographic discrepancies.
The authors also did not apply a statistical correction for the many connections they tested at once, so some of the identified links could be false positives, and the analysis was exploratory, with no advance predictions about which networks would be affected. Because each study site used scanners from a single manufacturer, differences between regions cannot be fully separated from differences in scanning equipment.
Rosenberg noted that the geographic inconsistency represents an important caveat for understanding the results. “One caveat is that the primary predictive models did not successfully generalize across sites, meaning that associations between brain network patterns and air pollution were inconsistent across geographic locations,” she said. “In addition to the thorough analyses presented in the paper, it would be interesting to test whether the observed brain changes were associated with cognitive and/or attentional performance since the implications of neural changes alone aren’t always clear.”
Another caveat involves how exposure was measured. The researchers assigned air pollution levels based on each child’s home address during a single year, which does not capture personal daily habits such as indoor air filtration, ventilation, daily travel routes, or time spent exercising outdoors. In addition, the participants in this nationwide study were somewhat more likely to come from higher-income and non-Hispanic white households than the national average, and average particulate exposures across the sample were below current federal limits. Future studies will need to follow youth through later adolescence to evaluate whether these source-specific network patterns correspond with tangible differences in sensory function, attention, or mental health outcomes.
The study, “Sources of outdoor air pollution exposure and child brain network development across the United States,” was authored by Katherine L. Bottenhorn, Kirthana Sukumaran, Amanda C. Del Giacco, Hedyeh Ahmadi, Jordan D. Corbett, Alethea V. de Jesus, Carlos Cardenas-Iniguez, Rima Habre, Daniel A. Hackman, Joel Schwartz, Jiu-Chiuan Chen, and Megan M. Herting.