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	<title>methane emission factors in cities &#8211; Science</title>
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	<title>methane emission factors in cities &#8211; Science</title>
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		<title>Satellites Reveal Cities Are Leaking Far More Methane Than Official Inventories Admit</title>
		<link>https://scienmag.com/satellites-reveal-cities-are-leaking-far-more-methane-than-official-inventories-admit/</link>
		
		<dc:creator><![CDATA[Russell Cooper]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 09:35:20 +0000</pubDate>
				<category><![CDATA[Athmospheric]]></category>
		<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[atmospheric methane monitoring]]></category>
		<category><![CDATA[city-level greenhouse gas inventories]]></category>
		<category><![CDATA[climate change]]></category>
		<category><![CDATA[EDGAR inventory]]></category>
		<category><![CDATA[global methane emission assessment]]></category>
		<category><![CDATA[Global Methane Pledge]]></category>
		<category><![CDATA[greenhouse gases]]></category>
		<category><![CDATA[innovative satellite detection methods]]></category>
		<category><![CDATA[London]]></category>
		<category><![CDATA[Los Angeles]]></category>
		<category><![CDATA[methane]]></category>
		<category><![CDATA[methane emission discrepancies]]></category>
		<category><![CDATA[methane emission factors in cities]]></category>
		<category><![CDATA[methane leaks in major cities]]></category>
		<category><![CDATA[methane's impact on climate change]]></category>
		<category><![CDATA[New York]]></category>
		<category><![CDATA[planetary boundary layer]]></category>
		<category><![CDATA[remote sensing for urban emissions]]></category>
		<category><![CDATA[satellite methane measurement]]></category>
		<category><![CDATA[satellite monitoring]]></category>
		<category><![CDATA[TROPOMI]]></category>
		<category><![CDATA[urban emissions]]></category>
		<category><![CDATA[urban greenhouse gas reporting accuracy]]></category>
		<category><![CDATA[urban methane emissions]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=253041</guid>

					<description><![CDATA[A new satellite-based mass balance method using TROPOMI observations reveals that methane emissions from London, Los Angeles and New York substantially exceed official inventory estimates.]]></description>
										<content:encoded><![CDATA[<p>Cities have a methane problem, and it may be far larger than the official numbers suggest. A team of researchers at the University of Manchester has developed a new satellite-based method for measuring the methane escaping from entire cities, and when they applied it to London, Los Angeles and New York between 2021 and 2023, the results were striking. Satellite-derived emissions exceeded the widely used EDGAR inventory by factors of roughly 1.5 to 3.0 in London, 1.3 to 3.1 in Los Angeles, and a remarkable 7.0 to 10.2 in New York. The study, published in the journal Atmospheric Measurement Techniques, offers what the authors describe as a simple, efficient and globally applicable framework for quantifying urban-scale methane emissions from orbit, a capability that has long been missing from the climate monitoring toolkit.</p>
<p>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.</p>
<p>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&#8217;s emissions, but they cannot provide the continuous, repeatable monitoring needed to track progress year after year, and their spatial sensitivity is often limited.</p>
<p>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.</p>
<p>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.</p>
<p>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.</p>
<p>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.</p>
<p>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.</p>
<p>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&#8217;s National Atmospheric Emission Inventory underestimated London&#8217;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.</p>
<p>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&#8217;s transparent uncertainty budgeting, combining retrieval, albedo, aerosol and wind uncertainties in quadrature, offers a repeatable path forward. With the Global Methane Pledge&#8217;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.</p>
<p><strong>Subject of Research:</strong> Satellite-based quantification of urban methane emissions using TROPOMI observations and an improved source pixel method</p>
<p><strong>Article Title:</strong> Satellite-based global monitoring of urban-scale methane emissions</p>
<p><strong>Article References:</strong> Long, H., Tsivlidou, M., Ricketts, H., &amp; Allen, G. (2026). Satellite-based global monitoring of urban-scale methane emissions. <em>Atmospheric Measurement Techniques, 19</em>(18), 6171-6191. <a href="https://doi.org/10.5194/amt-19-6171-2026" rel="noopener noreferrer">https://doi.org/10.5194/amt-19-6171-2026</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.5194/amt-19-6171-2026" rel="noopener noreferrer">10.5194/amt-19-6171-2026</a></p>
<p><strong>Keywords:</strong> methane, TROPOMI, satellite monitoring, urban emissions, greenhouse gases, London, Los Angeles, New York, planetary boundary layer, EDGAR inventory, climate change, Global Methane Pledge</p>
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