The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) "Indicators" Tiger Team collaboration between NASA-supported scientists and civil society stakeholders aimed to develop satellite-derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge. Plain Language Summary Recent advances in satellite remote sensing enable observation-based tracking of climate change and air pollution with relatively high spatial resolution globally. The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) "Indicators" Tiger Team launched a collaboration between~20 NASA-supported scientists and civil society stakeholders to develop satellite-derived global air pollution and climate indicators. This Commentary demonstrates the range of air quality and climate change tracking uses for satellite data and shares our experience and lessons learned, which can inform future problem-driven science-stakeholder collaborative efforts. Together, the team developed methods to track wildfires, dust storms, pollen, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban fine particulate matter mortality. Lessons learned include that participatory knowledge production can lead to more actionable information for stakeholders but requires time and dedicated attention. Stakeholder engagement is valuable at each stage, from developing more nascent data sets to operationalizing mature data sets. Flexibility is critical, since stakeholder needs evolve and new synergies emerge when there are engagements across a wide range of stakeholders and teams. However, additional ground measurements are needed to ground truth satellite observations, and

Momentum to phase out unabated coal use is growing globally. This transition is critical to meeting the Paris climate goals but can potentially lead to large amounts of stranded assets, especially in regions with newer and growing coal fleets. Here we combine plant-level data with a global integrated assessment model to quantify changes in global stranded asset risks from coal-fired power plants across regions and over time. With new plant proposals, cancellations, and retirements over the past five years, global net committed emissions in 2030 from existing and planned coal plants declined by 3.3 GtCO2 (25%). While these emissions are now roughly in line with initial Nationally Determined Contributions (NDCs) to the Paris Agreement, they remain far off track from longer-term climate goals. Progress made in 2021 towards no new coal can potentially avoid a 24% (503 GW) increase in capacity and a 55% ($520 billion) increase in stranded assets under 1.5οC. Stranded asset risks fall disproportionately on emerging Asian economies with newer and growing coal fleets. Recent no new coal commitments from major coal financers can potentially reduce stranding of international investments by over 50%.

This study evaluates formaldehyde (HCHO) over the U.S. from 2006 to 2015 by comparing ground monitor data from the Air Quality System (AQS) and a satellite retrieval from the Ozone Monitoring Instrument (OMI). Our comparison focuses on the utility of satellite data to inform patterns, trends, and processes of ground-based HCHO across the U.S. We find that cities with higher levels of biogenic volatile organic compound (BVOC) emissions, including primary HCHO, exhibit larger HCHO diurnal amplitudes in surface observations. These differences in hour-to-hour variability in surface HCHO suggests that satellite agreement with ground-based data may depend on the distribution of emission sources. On a seasonal basis, OMI exhibits the highest correlation with AQS in summer and the lowest correlation in winter. The ratios of HCHO in summer versus other seasons show pronounced seasonal variability in OMI, likely due to seasonal changes in the vertical HCHO distribution. The seasonal variability in HCHO from satellite is more pronounced than at the surface, with seasonal variability 20–100% larger in satellite than surface observations. The seasonal variability also has a latitude dependency, with more variability in higher latitude regions. OMI agrees with AQS on the interannual variability in certain periods, whereas AQS and OMI do not show a consistent decadal trend. This is possibly due to a rather large interannual variability in HCHO, which makes the small decadal drift less significant. Temperature also explains part of the interannual variabilities. Small temperature variations in the western U.S. are reflected with more quiescent HCHO interannual variability in that region. The decrease in summertime HCHO in the southeast U.S. could also be partially explained by a small and negative trend in local temperatures.

A global phaseout of unabated coal use is critical to meeting the Paris climate goals. This transition can potentially lead to large amounts of stranded assets, especially in regions with newer and growing coal fleets. Here we combine plant-level data with a global integrated assessment model to quantify changes in stranded asset risks across locations and over time. With new plant proposals, cancellations, and retirements over the past five years, global committed emissions in 2030 from existing and planned coal plants declined by 3.3 GtCO2 (25%). While these emissions are now roughly in line with near-term (2030) Nationally Determined Contributions (NDCs) to the Paris Agreement, they remain far off track from longer-term climate goals. Building all proposed coal plants in the pipeline leads to a 24% (503 GW) increase in capacity and a 55% ($520 billion) increase in stranded assets under 1.5°C. Stranded asset risks fall disproportionately on emerging Asian economies with newer and growing coal fleets.