Significance: Drastic air pollution control in China since 2013 has achieved sharp decreases in fine particulate matter (PM _2.5 ), but ozone pollution has not improved. After removing the effect of meteorological variability, we find that surface ozone has increased in megacity clusters of China, notably Beijing and Shanghai. The increasing trend cannot be simply explained by changes in anthropogenic precursor [NO _x and volatile organic compound (VOC)] emissions, particularly in North China Plain (NCP). The most important cause of the increasing ozone in NCP appears to be the decrease in PM _2.5 , slowing down the sink of hydroperoxy radicals and thus speeding up ozone production. Decreasing ozone in the future will require a combination of NO _x and VOC emission controls to overcome the effect of decreasing PM _2.5 .

Significance: The North China Plain experiences severe summer ozone pollution, but ozone during winter haze (particulate) pollution events has been very low. Here, we show that the abrupt decrease in nitrogen oxide (NO _x ) emissions following the COVID-19 lockdown in January 2020 drove fast ozone production during winter haze events to levels approaching the air quality standard. This fast ozone production was driven by formaldehyde originating from high emissions of volatile organic compounds (VOCs). The COVID-19 experience highlights a general 2013 to 2019 trend of rapidly increasing ozone pollution in winter–spring in China as NO _x emissions have decreased. VOC emission controls would mitigate the spreading of ozone pollution into winter–spring with benefits for public health, crop production, and particulate pollution.

Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a⁻¹ for oil-gas and 32.7 ± 5.2 Tg a⁻¹ for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a⁻¹ or 18%.

We use satellite methane observations from the Tropospheric Monitoring Instrument (TROPOMI), for May 2018 to February 2020, to quantify methane emissions from individual oil and natural gas ($\mathrm{O}/\mathrm{G}$ ) basins in the US and Canada using a high-resolution (∼25 km) atmospheric inverse analysis. Our satellite-derived emission estimates show good consistency with in situ field measurements (R=0.96) in 14 $\mathrm{O}/\mathrm{G}$ basins distributed across the US and Canada. Aggregating our results to the national scale, we obtain $\mathrm{O}/\mathrm{G}$ -related methane emission estimates of 12.6±2.1 Tg a⁻¹ for the US and 2.2±0.6 Tg a⁻¹ for Canada, 80 % and 40 %, respectively, higher than the national inventories reported to the United Nations. About 70 % of the discrepancy in the US Environmental Protection Agency (EPA) inventory can be attributed to five $\mathrm{O}/\mathrm{G}$ basins, the Permian, Haynesville, Anadarko, Eagle Ford, and Barnett basins, which in total account for 40 % of US emissions. We show more generally that our TROPOMI inversion framework can quantify methane emissions exceeding 0.2–0.5 Tg a⁻¹ from individual $\mathrm{O}/\mathrm{G}$ basins, thus providing an effective tool for monitoring methane emissions from large $\mathrm{O}/\mathrm{G}$ basins globally.

We develop a statistical model using extreme value theory to estimate the 2000–2050 changes in ozone episodes across the United States. We model the relationships between daily maximum temperature (T_max) and maximum daily 8 h average (MDA8) ozone in May–September over 2003–2012 using a Point Process (PP) model. At ~20% of the sites, a marked decrease in the ozone‐temperature slope occurs at high temperatures, defined as ozone suppression. The PP model sometimes fails to capture ozone‐T_max relationships, so we refit the ozone‐T_max slope using logistic regression and a generalized Pareto distribution model. We then apply the resulting hybrid‐extreme value theory model to projections of T_max from an ensemble of downscaled climate models. Assuming constant anthropogenic emissions at the present level, we find an average increase of 2.3 d a⁻¹ in ozone episodes (>75 ppbv) across the United States by the 2050s, with a change of +3–9 d a⁻¹ at many sites.

We use 2005–2016 observations of formaldehyde (HCHO) columns over China from the OMI, GOME‐2, and SCIAMACHY satellite instruments to evaluate long‐term trends in emission inventories of volatile organic compounds (VOCs) that affect air quality. The observations show large increases over 2005–2016 in the North China Plain (+1.1 ± 0.5% a⁻¹ relative to 2005) and the Yangtze River Delta region (+1.5 ± 0.4% a⁻¹ relative to 2005), consistent with the trend of anthropogenic VOC emissions in the Multi‐resolution Emission Inventory for China (MEIC). Unlike other pollutants, VOC emissions have not been decreasing in recent years. An exception is the Huai River Basin in rural eastern China where the satellite data show rapidly decreasing VOC emissions since the early 2010s that appear to reflect bans on agricultural fires.