Quantification and attribution of long-term tropospheric ozone trends are critical for understanding the impact of human activity and climate change on atmospheric chemistry but are also challenged by the limited coverage of long-term ozone observations in the free troposphere where ozone has higher production efficiency and radiative potential compared to that at the surface. In this study, we examine observed tropospheric ozone trends, their attributions, and radiative impacts from 1995–2017 using aircraft observations from the In-service Aircraft for a Global Observing System database (IAGOS), ozonesondes, and a multi-decadal GEOS-Chem chemical model simulation. IAGOS observations above 11 regions in the Northern Hemisphere and 19 of 27 global ozonesonde sites have measured increases in tropospheric ozone (950–250 hPa) by 2.7 ± 1.7 and 1.9 ± 1.7 ppbv per decade on average, respectively, with particularly large increases in the lower troposphere (950–800 hPa) above East Asia, the Persian Gulf, India, northern South America, the Gulf of Guinea, and Malaysia/Indonesia by 2.8 to 10.6 ppbv per decade. The GEOS-Chem simulation driven by reanalysis meteorological fields and the most up-to-date year-specific anthropogenic emission inventory reproduces the overall pattern of observed tropospheric ozone trends, including the large ozone increases over the tropics of 2.1–2.9 ppbv per decade and above East Asia of 0.5–1.8 ppbv per decade and the weak tropospheric ozone trends above North America, Europe, and high latitudes in both hemispheres, but trends are underestimated compared to observations. GEOS-Chem estimates an increasing trend of 0.4 Tg yr⁻¹ of the tropospheric ozone burden in 1995–2017. We suggest that uncertainties in the anthropogenic emission inventory in the early years of the simulation (e.g., 1995–1999) over developing regions may contribute to GEOS-Chem's underestimation of tropospheric ozone trends. GEOS-Chem sensitivity simulations show that changes in global anthropogenic emission patterns, including the equatorward redistribution of surface emissions and the rapid increases in aircraft emissions, are the dominant factors contributing to tropospheric ozone trends by 0.5 Tg yr⁻¹. In particular, we highlight the disproportionately large, but previously underappreciated, contribution of aircraft emissions to tropospheric ozone trends by 0.3 Tg yr⁻¹, mainly due to aircraft emitting NO_x in the mid-troposphere and upper troposphere where ozone production efficiency is high. Decreases in lower-stratospheric ozone and the stratosphere–troposphere flux in 1995–2017 contribute to an ozone decrease at mid-latitudes and high latitudes. We estimate the change in tropospheric ozone radiative impacts from 1995–1999 to 2013–2017 is +18.5 mW m⁻², with 43.5 mW m⁻² contributed by anthropogenic emission changes (20.5 mW m⁻² alone by aircraft emissions), highlighting that the equatorward redistribution of emissions to areas with strong convection and the increase in aircraft emissions are effective for increasing tropospheric ozone's greenhouse effect.

The United States is the world’s largest oil/gas methane emitter according to current national reports. Reducing these emissions is a top priority in the US government’s climate action plan. Here, we use a 2010 to 2019 high-resolution inversion of surface and satellite observations of atmospheric methane to quantify emission trends for individual oil/gas production regions in North America and relate them to production and infrastructure. We estimate a mean US oil/gas methane emission of 14.8 (12.4 to 16.5) Tg a⁻¹for 2010 to 2019, 70% higher than reported by the US Environmental Protection Agency. While emissions in Canada and Mexico decreased over the period, US emissions increased from 2010 to 2014, decreased until 2017, and rose again afterward. Increases were driven by the largest production regions (Permian, Anadarko, Marcellus), while emissions in the smaller production regions generally decreased. Much of the year-to-year emission variability can be explained by oil/gas production rates, active well counts, and new wells drilled, with the 2014 to 2017 decrease driven by reduction in new wells and the 2017 to 2019 surge driven by upswing of production. We find a steady decrease in the oil/gas methane intensity (emission per unit methane gas production) for almost all major US production regions. The mean US methane intensity decreased from 3.7% in 2010 to 2.5% in 2019. If the methane intensity for the oil/gas supply chain continues to decrease at this pace, we may expect a 32% decrease in US oil/gas emissions by 2030 despite projected increases in production.

Surface ozone concentrations typically peak during the daytime, driven by active photochemical production, and decrease gradually after sunset, due to chemical destruction and dry deposition. Here, we report that nocturnal ozone enhancement (NOE, defined as an ozone increase of more than 5 ppbv h⁻¹ in 1 of any 2 adjacent hours between 20:00 and 06:00 LT, local time) events are observed at multiple monitoring sites in China at a high frequency, which has not been recognized in previous studies. We present an overview of the general characteristics of NOE events in China and explore the possible mechanisms based on 6 years of observations from the national monitoring network. We find that the mean annual frequency of NOE events is 41±10 % (i.e., about 140 d would experience an NOE event per year) averaged over all 814 Chinese sites between 2014 and 2019, which is 46 % larger than that over Europe or the United States. The NOE event frequency is higher in industrialized city clusters (>50 %) than in regions with lighter ozone pollution, and it is higher in the warm season (46 %) than in the cold season (36 %), consistent with the spatiotemporal evolution of ozone levels. The mean ozone peak during NOE events reaches 37±6 ppbv in the warm season. The ozone enhancements are within 5–15 ppbv h⁻¹ during 85 % of the NOE events; however, in about 10 % of cases, the ozone increases can exceed 20 ppbv h⁻¹. We propose that high photochemistry-induced ozone during the daytime provides a rich ozone source in the nighttime residual layer, determining the overall high frequency of NOE events in China, and that enhanced atmospheric mixing then triggers NOE events by allowing the ozone-rich air in the residual layer to mix into the nighttime boundary layer. This is supported by our analyses which show that 70 % (65 %) of the NOE events are associated with increases in friction velocity (planetary boundary layer height), indicative of enhanced atmospheric mixing, and also supported by the observed sharp decreases in surface NO₂ and CO concentrations with ozone increases in NOE events, a typical signal of mixing with air in the residual layer. Three case studies in Beijing and Guangzhou show that synoptic processes such as convective storms and low-level jets can lead to NOE events by aggravating vertical mixing. Horizontal transport of ozone-rich plumes may also be a supplementary driver of NOE events. Our results summarize, for the first time, the characteristics and mechanism of NOE events in China based on nationwide and long-term observations, and our findings emphasize the need for more direct measurements and modeling studies on the nighttime ozone evolution from the surface to the residual layer.

The recent 20 years (2000–2019) ozonesonde profiles recorded at the Hong Kong Observatory are analyzed to study the Tropospheric Ozone (TropO₃) variability over Hong Kong, South China. The TropO₃ profiles are described without the constraints of traditional monthly averages; they are clustered based on a Self‐Organizing Map (SOM) to explore the short‐term variability, and separated into two 10‐year periods to investigate the long‐term variability based on pooled statistical analysis. The roles of precursor emissions, dynamic transport, and photochemical formation in multiple‐timescale TropO₃ variability are further evaluated with the aid of meteorological and satellite data, surface observation, emission inventory, and backward trajectory analysis. The results suggest that TropO₃ over Hong Kong has a seasonal and vertical distribution featuring a widely recognized spring maximum. The SOM‐based clustering analysis emphasizes a strong dependence of short‐term variability in TropO₃ profile patterns on cross‐latitude transport conditions, including rich‐O₃ transport from midlatitude region and poor‐O₃ transport from tropics. However, high O₃ levels throughout the troposphere (usually in early spring) are largely due to the combination of stratospheric intrusion and biomass burning. During the whole study period, the O₃ concentrations have increased substantially in the lower troposphere. Springtime wildfire‐related emissions over the upwind Indochina Peninsula are responsible for the lower free‐tropospheric O₃ increases. In contrast, the boundary‐layer O₃ uptrends with a larger increasing rate near the surface are mostly attributed to the reduced NO titration effect due to the sharp reduction of NO_x emissions.

Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower in Guangzhou, the core megacity in South China, and interpret the measurements with a 1-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10, 118, 168, and 488 m, with the highest (488 m) measurement platform higher than the typical height of the nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with a vertical ozone gradient between the 10 and 488 m heights (ΔO${}_{\mathrm{3}}/\mathrm{\Delta }$ H_10–488 m) of 3.6–6.4 ppbv hm⁻¹ in nighttime and 4.4–5.8 ppbv hm⁻¹ in daytime. We identify a high ozone residual ratio, defined as the ratio of ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 69 %–90 % in January, April, and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer. The tower-based measurement also indicates that the nighttime surface O_x (O_x= O₃+NO₂) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both the nighttime and the following day's daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe a significant decrease in ozone and an increase in NO₂ and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to an NOE event by introducing ozone-rich and NO_x-poor air into the RL to enter the nighttime stable boundary layer. The CMAQ model simulations also demonstrate an enhanced positive contribution of vertical diffusion (ΔVDIF) to ozone at the 10 and 118 m heights and a negative contribution at the 168 and 488 m heights during the NOE event. We also observe a strong correlation between nighttime RL ozone and the following day's surface maximum daily 8 h average (MDA8) ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of a convective mixing layer, which is supported by the CMAQ diagnosis of the ozone budget, suggesting that the mixing of ozone-rich air from nighttime RL downward to the surface via the entrainment is an important mechanism for aggravating ozone pollution the following day. We find that the bias in CMAQ-simulated surface MDA8 ozone the following day shows a strong correlation coefficient (r= 0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics.