The stakes could hardly be higher. Methane is the second most significant anthropogenic greenhouse gas after carbon dioxide and is responsible for roughly one third of the rise in global mean surface air temperature between 1750 and 2019. Because it has a short atmospheric lifetime of about nine years but a global warming potential nearly 82 times that of carbon dioxide over a 20-year period, cutting methane emissions is one of the most powerful levers available for slowing near-term climate change. More than 150 countries have now committed, through the Global Methane Pledge and their Nationally Determined Contributions, to reduce methane emissions across all sectors by at least 30 percent below 2020 levels by 2030. Every credible pathway to limiting warming to 1.5 degrees Celsius depends on achieving that reduction.

Yet cities, where more than half of humanity already lives and where the proportion is projected to reach 70 percent by 2050, remain stubbornly difficult to audit. Urban methane comes from a tangle of sources: natural gas consumption, leaks from aging pipeline networks, landfills and wastewater treatment systems. Field studies have repeatedly found that official bottom-up inventories, which rely on activity data and emission factors, can underestimate urban methane emissions by a factor of two to three. Aircraft surveys, ground-based mobile monitors and tower networks can deliver accurate snapshots of a city’s emissions, but they cannot provide the continuous, repeatable monitoring needed to track progress year after year, and their spatial sensitivity is often limited.

Satellites promise to close that gap. The TROPOspheric Monitoring Instrument, or TROPOMI, flies aboard the polar sun-synchronous Sentinel-5 Precursor satellite, launched in October 2017 at an altitude of 824 kilometers with a consistent 13:30 local overpass time. The instrument retrieves the methane column by detecting solar backscattered light in the shortwave infrared absorption band at 2.3 micrometers, achieving daily global coverage at a spatial resolution of 7 by 5.5 square kilometers at nadir since August 2019. Previous studies have used TROPOMI to constrain urban methane inventories across 61 cities worldwide and to conduct a preliminary national analysis of urban emissions across North America, but a transparent, widely applicable framework with detailed error accounting has remained elusive.

The Manchester team, led by Huihui Long together with Maria Tsivlidou, Hugo Ricketts and Grant Allen, built their method on the concept of mass balance, refining the established source pixel approach. First, they remapped the heterogeneous Level-2 satellite pixels onto a regular 0.1 by 0.1 degree grid, treating each observation footprint as a surface polygon and calculating the fractional area of overlap with each grid cell, weighted by pixel area and retrieval error. This regularization allows orbit-level emission estimates that are directly comparable with gridded bottom-up inventories over the same spatial domain. Strict quality filters followed: only cloud-free retrievals with quality assurance values above 0.5, solar zenith angles below 70 degrees, smooth topography, low aerosol optical thickness and retrieval precisions better than 10 parts per billion were retained.

Two innovations distinguish the new framework. The first concerns wind. Conventional source pixel methods rely on 10-meter near-surface winds bundled with the satellite retrievals, but methane emitted at the surface is ventilated by winds throughout the planetary boundary layer, the turbulent lowest kilometer or so of the atmosphere where surface emissions mix and are advected across urban scales. The team therefore computed pressure-weighted average wind speed and direction across all ERA5 reanalysis pressure levels within the boundary layer, using hourly-resolved meteorology. The difference matters: over Los Angeles, the near-surface winds pointed from the north-northeast to east-northeast at speeds below 6 meters per second, while the boundary-layer-weighted winds blew predominantly from the west-southwest to south-southwest at up to about 10 meters per second. Since emission rate is conceptually proportional to mean boundary-layer wind speed, and wind direction determines where the upwind background lies, these discrepancies directly reshape the calculated emissions.

The second innovation is an upwind-based approach to defining the background methane concentration. Instead of assuming that the air surrounding a city is clean, the method defines a background region of equal area located immediately adjacent to the city along the boundary-layer-pressure-weighted mean upwind direction, with both boxes oriented so their sides lie perpendicular to the wind. Emissions in the background are implicitly accounted for and subtracted, so the background region need not be free of methane sources. The methane enhancement over the city is then the difference between the mean column mixing ratio over the source region and that over the upwind background, and the emission rate follows from a mass balance equation combining that enhancement, the mean boundary-layer wind, surface pressure and the dimensions of the source box. Coverage thresholds, requiring at least 25 percent valid data over the source region and at least 10 background observations, guard against statistically unreliable single-orbit estimates.

Applied to the three megacities, the method produced three-year mean emissions of 7.78 plus or minus 4.84 tonnes per hour for London, 47.19 tonnes per hour for Los Angeles, and 42.94 tonnes per hour for New York. London showed only a modest urban enhancement, averaging between 1.47 and 1.98 parts per billion across the study years, which made the estimate highly sensitive to background variability; roughly 80 percent of the total emission uncertainty there was attributable to the methane enhancement, and an anomalously low October in 2021, when background concentrations exceeded urban ones, dragged the annual figure down until it was excluded as an outlier. Los Angeles, by contrast, displayed a pronounced and persistent hotspot, with emissions rising from 26.21 tonnes per hour in 2021 to 62.77 tonnes per hour in 2023, though the large uncertainties mean a previously reported declining trend cannot be ruled out. In New York, emissions ranged from 30.85 to 44.77 tonnes per hour, with a more balanced uncertainty structure in which wind variability contributed about 40 percent.

The comparison with official inventories is sobering. Over identical spatial domains, EDGAR reported a mean of 20.07 tonnes per hour for Los Angeles, where landfills account for more than 90 percent of inventory emissions, and just 4.38 tonnes per hour for New York, roughly 11 percent of the satellite-derived figure. The UK’s National Atmospheric Emission Inventory underestimated London’s emissions by up to 45 percent in 2022, while the US EPA inventory fell short by approximately 56 percent for Los Angeles and 84 percent for New York. Encouragingly, when the team rescaled estimates from six previous top-down studies to the same urban domains, most fell within their uncertainty bounds, suggesting the new method is consistent with independent measurement-led approaches while being far simpler to repeat.

The authors are candid about the limitations. Cloud cover, coastal albedo heterogeneity and aerosol scattering eliminated the majority of overpasses, leaving as few as five valid orbits over New York in 2021 and almost no usable summer data for Los Angeles, where persistent marine boundary-layer clouds dominate. Such uneven sampling can introduce seasonal and inter-annual biases that must be weighed when comparing annualized emissions with inventories. Nevertheless, the team argues that the trade-off is necessary to preserve statistical reliability, and that the framework’s transparent uncertainty budgeting, combining retrieval, albedo, aerosol and wind uncertainties in quadrature, offers a repeatable path forward. With the Global Methane Pledge’s 2030 deadline approaching, the ability to audit cities from space, anywhere on Earth including poorly observed regions such as India and China where most of the global population resides, may prove essential for verifying whether stated methane targets are actually being met.

Subject of Research: Satellite-based quantification of urban methane emissions using TROPOMI observations and an improved source pixel method

Article Title: Satellite-based global monitoring of urban-scale methane emissions

Article References: Long, H., Tsivlidou, M., Ricketts, H., & Allen, G. (2026). Satellite-based global monitoring of urban-scale methane emissions. Atmospheric Measurement Techniques, 19(18), 6171-6191. https://doi.org/10.5194/amt-19-6171-2026

Image Credits: AI Generated

DOI: 10.5194/amt-19-6171-2026

Keywords: methane, TROPOMI, satellite monitoring, urban emissions, greenhouse gases, London, Los Angeles, New York, planetary boundary layer, EDGAR inventory, climate change, Global Methane Pledge

Volatile organic compounds, or VOCs, are a broad class of carbon-containing gases that evaporate easily at room temperature. They are emitted by an enormous range of everyday materials, including hairsprays, perfumes, disinfectants, paints, solvents, adhesives and even the building materials that make up homes and offices. Once released into the atmosphere, these compounds do not simply drift away harmlessly. In the presence of sunlight and nitrogen oxides, they participate in photochemical reactions that generate ground-level ozone, a respiratory irritant, and secondary organic aerosols, tiny particles that contribute to smog and haze. Because many VOCs are also associated with indoor air quality problems, they have traditionally been studied inside buildings rather than as major outdoor urban emitters. The new research demonstrates that this framing no longer reflects reality in summertime cities.

The study’s lead field measurements were gathered from a cellular tower using a technique known as eddy covariance, an approach that is rarely deployed in urban air quality research. Eddy covariance combines high-frequency wind measurements with continuous chemical monitoring to calculate the net flux of pollutants moving between the surface and the atmosphere. In essence, by tracking how swirling eddies of air carry chemicals upward from the city, scientists can directly determine emission rates for a wide variety of compounds without relying on indirect estimates. The method demands sophisticated instrumentation and a sampling height well above the surrounding buildings, which is why most urban field studies instead measure pollutant concentrations alone, a strategy that reveals what is in the air but not necessarily where it came from or how quickly it is being released.

By pairing the eddy covariance flux measurements with machine learning tools, the research team was able to disentangle the sources of reactive carbon rising from the urban surface. First author Michael Vermeuel, an assistant professor at Purdue University, emphasized how unusual and revealing this direct approach proved to be. According to the researchers, few field experiments have applied this technique in urban environments, and it exposed a broad chemical fingerprint of emissions that changed substantially between the summer and winter campaigns. In winter, the flux measurements pointed overwhelmingly toward vehicle exhaust and combustion-related sources, consistent with the long-standing picture of urban pollution. In summer, however, the dominant emissions shifted toward volatile chemical products and residential sources, a transition that current regulatory models simply do not capture.

Delphine Farmer, a chemistry professor at Colorado State University who helped lead the research, noted that volatile chemical products, including personal care items, paints, solvents and cleaners, along with building materials themselves, were major emissions from the city in summer. She explained that these sources are important but are not accurately included in the current models that cities and states use to predict and reduce air-quality events. That omission matters because air quality advisories, ozone action days and emissions regulations are all built on emission inventories and models that assume a particular mix of pollution sources. If the true summertime mix is dominated by products and buildings rather than tailpipes, then policies designed around traffic may deliver far less benefit than expected during the very season when ozone pollution is most dangerous to public health.

The underlying reason for this seasonal shift is a story of two converging trends. On one side, vehicles on United States roadways have become dramatically cleaner burning over recent decades, thanks to catalytic converters, improved fuel formulations and increasingly stringent emissions standards. As tailpipe emissions have fallen, other less-studied sources of urban air pollution have grown in relative importance. On the other side, many of these emerging sources are temperature-dependent: their emissions increase as conditions get hotter. Volatile chemical products evaporate more readily in warm weather, and the chemical reactions that transform emitted compounds into ozone and aerosols accelerate with sunlight and heat. Dylan Millet, a professor of atmospheric chemistry at the University of Minnesota and a co-author of the study, explained that because many of these emerging pollution sources increase when it is hotter, they are liable to intensify during heat waves and as the climate continues to warm.

This temperature sensitivity creates a troubling feedback loop at the intersection of air quality and climate change. Heat waves, which are becoming more frequent and more intense across North America, will simultaneously boost evaporative emissions from chemical products and building materials and speed up the atmospheric chemistry that turns those emissions into harmful pollutants. Cities that already struggle with summer ozone episodes could therefore face worsening air quality even if vehicle emissions continue to decline. The researchers caution that because current air quality models do not account for this temperature-dependent pollution, city and state agencies may be missing key information in their decision-making frameworks for managing and regulating air pollution, potentially misjudging both the magnitude of summertime pollution events and the most effective interventions.

The measurement site on Long Island offered an ideal natural laboratory for separating these source categories. The region experiences the full seasonal contrast between cold winters and hot, sunny summers, and its urban landscape blends traffic corridors with dense residential neighborhoods. By conducting identical measurement campaigns in both seasons from the same tower, the team could hold the location constant and isolate the effect of season on emission composition. The wintertime data confirmed the conventional understanding that vehicle emissions are the source of most wintertime air pollution. The summertime data, by contrast, revealed that air pollution largely arose from other sources, including chemical products and residences, fundamentally reshaping the picture of what a polluted summer city actually emits.

The implications extend beyond the New York metropolitan area. Volatile chemical products are used in cities across the country and around the world, and the trend toward cleaner vehicles is a global phenomenon driven by tightening standards everywhere. If the Long Island findings generalize, then urban emission inventories nationwide may systematically undercount the contribution of consumer products, paints, solvents and building materials during warm months. Correcting that gap could change how regulators prioritize pollution controls, potentially shifting attention toward product formulation standards, solvent regulations, building-sector emissions and consumer behavior, alongside the traditional focus on transportation. It could also refine the science behind ozone forecasts, giving public health officials better tools to warn vulnerable populations on high-pollution days.

For the research community, the study also represents a methodological milestone. Direct flux measurements of reactive carbon from an urban surface, combined with machine learning source attribution, offer a template for future campaigns in other cities and climates. As Vermeuel and his colleagues showed, measuring what the city actually exhales, rather than merely sampling what happens to be in the air, can overturn assumptions embedded in decades of modeling practice. As summers grow hotter and the vehicle fleet grows cleaner, the invisible emissions from hairspray bottles, paint cans, disinfectant sprays and building envelopes are poised to become an ever-larger share of the urban pollution burden. Recognizing that reality, the researchers argue, is the first step toward air quality policies that protect public health in the summertime cities of a warming world.

Subject of Research: Seasonal variation in urban volatile organic compound emissions from consumer products and buildings

Article Title: Summertime air pollutants often come from household products and buildings

Article References: Summertime air pollutants often come from household products and buildings. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: air pollution, volatile organic compounds, urban emissions, eddy covariance, ozone, heat waves, climate change, air quality models, consumer products, Colorado State University, Science Advances, secondary organic aerosols

The research team, led by Jiaqi Zhang and Zhenchuan Niu of the Institute of Earth Environment at the Chinese Academy of Sciences, sampled air at an urban site in Xi’an’s High-Tech Zone every day from December 23, 2021, to January 23, 2022, a window covering the city’s strict pandemic confinement. Rather than relying on total carbon dioxide readings, which mix natural and human sources, the researchers turned to isotopic forensics. Fossil fuels contain no carbon-14, the radioactive isotope of carbon that decays over tens of thousands of years, so carbon derived from coal, oil, and natural gas is distinctly radiocarbon-free. By measuring the carbon-14 composition of atmospheric carbon dioxide, the team could isolate the fossil component with precision, a technique long championed for monitoring megacity emissions.

The isotopic measurements were complemented by analysis of carbon-13, the stable heavy isotope of carbon. Different carbon sources carry different carbon-13 signatures: vehicle exhaust, coal combustion, and natural gas each leave a characteristic fingerprint in the carbon dioxide they release. By combining the two isotope systems, the researchers could not only quantify how much fossil carbon dioxide was in the air but also apportion it among its sources. This dual-isotope approach, normalized against a ventilation coefficient, formed the analytical backbone of the study and allowed the team to separate genuine changes in emissions from changes in how the atmosphere diluted them.

That ventilation correction proved to be the crux of the work. The ventilation coefficient, a classical concept in air pollution meteorology dating back to the work of Holzworth in the 1960s, combines the depth of the atmospheric mixing layer with the near-surface wind speed. When the mixing layer is shallow and winds are calm, pollutants emitted at the surface accumulate rapidly; when the boundary layer is deep and winds are brisk, the same emissions are swept away. Winter haze episodes in northern Chinese cities are typically triggered by exactly such stagnant conditions, with temperature inversions capping the boundary layer and trapping everything from fine particulate matter to greenhouse gases near the ground.

The Xi’an data captured this dynamic in dramatic fashion. During haze periods within the lockdown, fossil carbon dioxide concentrations were 159 percent, give or take 48 percent, higher than during non-haze periods, despite the fact that human activity, and presumably emissions, were suppressed throughout. In other words, the atmosphere itself, not the sources, was responsible for a large share of the variation observed at the sampling site. Without accounting for this meteorological amplification, an observer relying on concentration data alone would have dramatically misjudged how emissions were changing during the lockdown.

Once the team normalized the measurements with the ventilation coefficient, the true emissions signal emerged. Compared with the period after the lockdown ended, fossil carbon dioxide concentrations during well-ventilated, non-haze lockdown days fell by 63.0 percent, with an uncertainty of 10.6 percent. Averaged across the entire lockdown period, including hazy days, the ventilation-normalized decline was 48.8 percent, plus or minus 12.2 percent. These figures align with the substantial reductions in traffic and economic activity that characterized the confinement, and they demonstrate how powerful the isotope-based method can be when meteorological variability is properly handled.

The carbon-13 source apportionment added a second layer of insight into which activities drove the decline. Vehicle emissions dropped by 84.6 percent, with a relatively tight uncertainty of 4.7 percent, reflecting the near-standstill of urban traffic during confinement. Coal burning emissions, by contrast, decreased by only 31.2 percent, though with a much larger uncertainty of 20.3 percent. The asymmetry makes physical sense: private and commercial transport can be switched off almost entirely by lockdown orders, whereas residential and industrial coal combustion for heating continues through the frigid Shaanxi winter regardless of pandemic restrictions. Xi’an, like much of northern China, still depends significantly on coal for winter heating, and that dependence cushioned the overall emissions decline.

The study’s implications reach well beyond one city or one lockdown. Since the pandemic began, researchers have used atmospheric observations to estimate emissions changes from the COVID-19 confinement in locations from California to Hungary, and global datasets such as the Carbon Monitor have tracked near-real-time emission shifts worldwide. Many of these assessments rely on top-down approaches, in which measured atmospheric concentrations are converted into emission estimates using atmospheric transport models. The Xi’an results show that meteorological effects, particularly haze-induced stagnation, can substantially bias such top-down assessments if not explicitly corrected. A city might appear to have slashed its emissions when in fact stagnant air was simply concentrating them, or vice versa.

The methodological lesson is that concentration is not emission, and the gap between the two is governed by the vagaries of weather. For urban carbon monitoring networks being built to verify climate pledges, the Xi’an study suggests that radiocarbon measurements, paired with careful boundary-layer and wind observations, offer a robust path forward. The ventilation coefficient normalization used here is simple enough to be applied broadly, yet it transformed a potentially misleading haze signal into a clean measurement of a 63 percent emissions drop. As cities worldwide deploy increasingly dense greenhouse gas sensing networks, incorporating such meteorological corrections will be essential to distinguish real mitigation progress from atmospheric illusion.

There is also a human story embedded in the dataset. The authors acknowledge an e-bike courier who assisted with sample collection during the pandemic, a reminder that the daily air samples underpinning these isotope measurements were gathered under difficult confinement conditions. The work was supported by the National Natural Science Foundation of China, the Natural Science Basic Research Program of Shaanxi, and the Strategic Priority Research Program of the Chinese Academy of Sciences. Published on September 29, 2026, the study stands as both a detailed case study of a locked-down megacity and a methodological caution: when the air stagnates, the atmosphere can tell a story about emissions that is dramatically at odds with reality, and only isotope forensics combined with meteorological insight can set the record straight.

Subject of Research: Isotopic quantification of fossil fuel carbon dioxide emissions and meteorological haze effects during the COVID-19 lockdown in Xi'an

Article Title: Substantial increase of fossil carbon dioxide concentrations in haze time periods versus ventilated non-haze periods during the coronavirus lockdown in Xi’an

Article References: Zhang, J., Liang, D., Niu, Z., Zhou, W., Wang, P., Feng, X., Wu, S., Wang, G., Lyu, M., Lu, X., & Kong, X. (2026). Substantial increase of fossil carbon dioxide concentrations in haze time periods versus ventilated non-haze periods during the coronavirus lockdown in Xi’an. Environmental Chemistry Letters. https://doi.org/10.1007/s10311-026-01927-x

Image Credits: AI Generated

DOI: 10.1007/s10311-026-01927-x

Keywords: COVID-19 lockdown, fossil fuel CO2, carbon-14, carbon-13, haze, ventilation coefficient, source apportionment, urban emissions, Xi'an, meteorology, radiocarbon, air pollution