Regional Surface Ozone Research Articles

Contrasting Domestic and Global Impacts of Emission Reductions in China on Tropospheric Ozone

AbstractSustained near‐surface ozone pollution despite stringent emission controls in China has drawn wide attention. However, how such rapid regional emission reductions affect global tropospheric ozone remains unexplored. Here, using an ensemble of measurements and global model simulations, we find Chinese emission reductions during 2013–2020 have increased domestic surface ozone; particularly in North China, they have decreased the global tropospheric ozone burden by 2.7 Tg (54% of China's anthropogenic contribution and 7% of global anthropogenic contribution in 2019) and ozone radiative forcing by 8.8 mW m−2 (64% of China's anthropogenic contribution and 9% of global anthropogenic contribution in 2019). Nitrogen oxides (NOx) associated nonlinear chemistry and height‐dependent atmospheric transport patterns primarily cause the contrasting impacts. Future Chinese NOx emission controls would continue to decrease global tropospheric ozone, while regional surface ozone may still increase unless NOx reductions exceed ∼53% of the 2019 level. Our results reveal the substantial benefit of regional emission reductions in China on global tropospheric ozone mitigation.

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950–2014

Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the surface ozone concentration from CMIP6 climate model, and the long-term and large-scale surface ozone concentration of China during 1950–2014 is obtained. The long-term evolutions and trends of ozone and meteorological effects on interannual ozone variations are further analyzed. The results reveal that CMIP6 historical simulations have a large underestimation in ozone concentrations and their trends. The XGB-derived ozone are closer to observations, with R2 value of 0.66 and 0.74 for daily and monthly retrievals, respectively. Both the concentrations and exceedances of ozone in most parts of China have shown increasing trends from 1950 to 2014. The daily mean ozone concentration without climate change effects is estimated to be 117 ppb in the year 1950 averaged over China. It indicates that the increase in anthropogenic emissions of China has a significant contribution to ozone enhancement between 1950 and 2014. The higher ozone growth rates of XGB retrievals than those from the model indicate a regional surface ozone penalty due to the warming climate. The relatively significant increment in ozone are estimated in the Central and Western China. Seasonally, the ozone enhancement is largest in spring, indicating a shift in seasonal variation of ozone. Given the uncertainty in simulating historical ozone by climate model, we show that machine learning approaches can provide improved assessment of evolution in surface ozone, along with valuable information to guide future model development and formulate future ozone pollution prevention and control policies.

Radiative and Chemical Effects of Non‐Homogeneous Methane on Terrestrial Carbon Fluxes in Asia

AbstractMethane (CH4) plays a crucial role in shaping terrestrial ecosystems due to its radiative effect and atmospheric photochemical reactions. In this study, we employed an enhanced regional climate‐chemistry‐ecosystem model (RegCM‐Chem‐YIBs) to comprehensively evaluate the impacts of both radiative and chemical effects of CH4 on terrestrial carbon fluxes across the East, South, and Southeast Asia (EA, SA, SEA) during the year 2010. Our findings showed that the radiative effects of CH4 yielded a positive influence on carbon fluxes. Specifically, the EA region experienced a significant increase in the gross primary production (GPP), reaching up to 0.515 Pg C Yr−1. In comparison, the SEA region exhibited a decrease in the net ecosystem exchange (NEE) of approximately −0.066 Pg C Yr−1. Further analysis revealed that alterations in radiation and vapor pressure deficit (VPD) were dominant drivers. Conversely, the chemical effects of CH4 lead to heightened regional surface ozone (O3) concentrations (2.704–3.115 ppb) and generate a negative response in carbon fluxes. Within the SEA region, GPP observed a decrease of up to −0.144 Pg C Yr−1, while NEE displayed a significant increase of 0.022 Pg C Yr−1. Taken together, the combined radiative and chemical effects of CH4 indicated a positive impact on regional carbon fluxes, with GPP increasing by 0.632 Pg C Yr−1 and NEE decreasing by −0.09 Pg C Yr−1. This holistic perspective is crucial for comprehending the intricate interactions linking climate change, atmospheric pollution, and the global carbon cycle.

Impact of synoptic climate system interaction on surface ozone in China during 1950–2014

The effects of meteorological conditions controlled by specific synoptic patterns on regional surface ozone episodes have been widely discussed. However, the impacts of synoptic climate systems and their interaction on long-term variation of ozone are less known. In this study, we use the daily meteorological data and hourly surface ozone concentrations in the summer of 1950–2014 from CMIP6 to investigate the relationship between ozone variations and synoptic climate types (SCTs). Eight SCTs are identified by an objective circulation classification method of an R package called synoptReg. Our results show that the mainland of China is controlled by the low-pressure system for SCT1–5, while dominated by Siberian high for SCT6–8. During SCT1–5 days, the interactions of Asian continental low, Western Pacific Subtropical High (WPSH), warm ridge at 700 hPa, high-level shallow Asian trough, westerly belt, and topography lead to high surface temperature, low relative humidity, and poor diffusion over Northern China with frequent ozone exceedance days. However, the low-level ozone concentrations over Northern China are shown under SCT6–8, affected by the weakened Asian continental low, enhanced Siberian high, stronger WPSH, and denser westerly belt. While over Southern China, ozone concentrations are higher for SCT6–8 than SCT1–5, due to the significantly reduced cloud and precipitation affected by the delivery of cold dry air mass from high latitudes to the South. The interdecadal variabilities of ozone during all SCTs may be controlled by the large-scale climate system of the East Asian monsoon.

Deep Learning to Evaluate US NOx Emissions Using Surface Ozone Predictions

AbstractEmissions of nitrogen oxides (NOx = NO + NO2) in the United States have declined significantly during the past three decades. However, satellite observations since 2009 indicate total column NO2 is no longer declining even as bottom‐up inventories suggest continued decline in emissions. Multiple explanations have been proposed for this discrepancy including (a) the increasing relative importance of nonurban NOx to total column NO2, (b) differences between background and urban NOx lifetimes, and (c) that the actual NOx emissions are declining more slowly after 2009. Here, we use a deep learning model trained by NOx emissions and surface observations of ozone to assess consistency between the reported NOx trends between 2005 and 2014 and observations of surface ozone. We find that the satellite‐derived trends best reproduce ozone in low NOx emission (background) regions. The 2010–2014 trend from older satellite‐derived emission estimates produced at low spatial resolution results in the largest bias in surface ozone in regions with high NOx emissions, reflecting the blending of urban and background NOx in these low‐resolution top‐down analyses. In contrast, the trend from higher resolution satellite‐based estimates, which are more capable of capturing the urban emission signature, is in better agreement with ozone in high NOx emission regions, and is consistent with the trend based on surface observations of NO2. Our results confirm that the satellite‐derived trends reflect anthropogenic and background influences.

Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C−1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C−1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C−1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

Trends and variability in surface ozone over the United States

AbstractWe investigate the observed trends and interannual variability in surface ozone over the United States using the Global Modeling Initiative chemical transport model. We discuss the roles of meteorology, emissions, and transport from the stratosphere in driving the interannual variability in different regions and seasons. We demonstrate that a hindcast simulation for 1991–2010 can reproduce much of the observed variability and the trends in summertime ozone, with correlation coefficients for seasonally and regionally averaged median ozone ranging from 0.46 to 0.89. Reproducing the interannual variability in winter and spring in the western United States may require higher‐resolution models to adequately represent stratosphere‐troposphere exchange. Hindcast simulations with fixed versus variable emissions show that changes in anthropogenic emissions drive the observed negative trends in monthly median ozone concentrations in the eastern United States during summer, as well as the observed reduction in the amplitude of the seasonal cycle. The simulation underestimates positive trends in the western United States during spring, but excluding the first 4 years of data removes many of the statistically significant trends in this region. The reduction in the slope of the ozone versus temperature relationship before and after major emission reductions is also well represented by the model. Our results indicate that a global model can reproduce many of the important features of the meteorologically induced ozone variability as well as the emission‐driven trends, lending confidence to model projections of future changes in regional surface ozone.

Projections of summertime ozone concentration over East Asia under multiple IPCC SRES emission scenarios

We have developed the Integrated Climate and Air Quality Modeling System (ICAMS) through the one-way nesting of global–regional models to examine the changes in the surface ozone concentrations over East Asia under future climate scenarios. Model simulations have been conducted for the present period of 1996–2005 to evaluate the performance of ICAMS. The simulated surface ozone concentrations reproduced the observed monthly mean concentrations at sites in East Asia with high R2 values (0.4–0.9), indicating a successful simulation to capture both spatial and temporal variability. We then performed several model simulations with the six IPCC SRES scenarios (A2, A1B, A1FI, A1T, B1, and B2) for the next three periods, 2016–2025 (the 2020s), 2046–2055 (the 2050s), and 2091–2100 (the 2090s). The model results show that the projected changes of the annual daily mean maximum eight-hour (DM8H) surface ozone concentrations in summertime for East Asia are in the range of 2–8 ppb, −3 to 8 ppb, and −7 to 9 ppb for the 2020s, the 2050s, and the 2090s, respectively, and are primarily determined based on the emission changes of NOx and NMVOC. The maximum increases in the annual DM8H surface ozone and high-ozone events occur in the 2020s for all scenarios except for A2, implying that the air quality over East Asia is likely to get worse in the near future period (the 2020s) than in the far future periods (the 2050s and the 2090s). The changes in the future environment based on IPCC SRES scenarios would also influence the change in the occurrences of high-concentrations events more greatly than that of the annual DM8H surface ozone concentrations. Sensitivity simulations show that the emissions increase is the key factor in determining future regional surface ozone concentrations in the case of a developing country, China, whereas a developed country, Japan would be influenced more greatly by effects of the regional climate change than the increase in emissions.

Modelling future changes in surface ozone: a parameterized approach

Abstract. This study describes a simple parameterization to estimate regionally averaged changes in surface ozone due to past or future changes in anthropogenic precursor emissions based on results from 14 global chemistry transport models. The method successfully reproduces the results of full simulations with these models. For a given emission scenario it provides the ensemble mean surface ozone change, a regional source attribution for each change, and an estimate of the associated uncertainty as represented by the variation between models. Using the Representative Concentration Pathway (RCP) emission scenarios as an example, we show how regional surface ozone is likely to respond to emission changes by 2050 and how changes in precursor emissions and atmospheric methane contribute to this. Surface ozone changes are substantially smaller than expected with the SRES A1B, A2 and B2 scenarios, with annual global mean reductions of as much as 2 ppb by 2050 vs. increases of 4–6 ppb under SRES, and this reflects the assumptions of more stringent precursor emission controls under the RCP scenarios. We find an average difference of around 5 ppb between the outlying RCP 2.6 and RCP 8.5 scenarios, about 75% of which can be attributed to differences in methane abundance. The study reveals the increasing importance of limiting atmospheric methane growth as emissions of other precursors are controlled, but highlights differences in modelled ozone responses to methane changes of as much as a factor of two, indicating that this remains a major uncertainty in current models.

Implications of regional surface ozone increases on visibility degradation in southeast China

Long-term visibility (1968–2010) and air pollutant (1984–2010) data records in Hong Kong reveal that the occurrence of reduced visibility (RV, defined as the percentage of hours per month with visibility below 8 km in the absence of rain, fog, mist or relative humidity above 95%) in southeast China has increased significantly in the last four decades. The most pronounced rate of increase was observed after 1990 (nine times higher than that before 1990), when notable increases in surface ozone (O3) levels were simultaneously observed (1.06 µg m−3 per yr). The greatest increases in RV, and in O3, NO2 and SO2 concentrations are coincident in the autumn (1.47, 0.20 and 0.45 µg m−3 per yr respectively), when southeast China is strongly influenced by regional O3 formation and accumulation due to continental outflow of pollution from the east China coast under favourable meteorological conditions. Multiple regression revealed that the RV percentage correlated well (p<0.05) with NO2 and NOx in the 1980s, and with NO2, SO2 and O3 after the 1990s, suggesting that there have been changes in the predominant factors causing visibility degradation. In order to elucidate the reasons for these changes, the results were integrated with data from previous research. Possible impacts of elevated O3 on secondary particle formation and their effects on visibility degradation and aerosol radiative forcing in an oxidant-enhanced southeast China are highlighted. Other factors potentially leading to visibility degradation, such as ship emissions and biomass burning, are also discussed.

Analysis of regional meteorology and surface ozone during the TexAQS II field program and an evaluation of the NMM‐CMAQ and WRF‐Chem air quality models

This study examines meteorological conditions associated with regional surface ozone using data collected during the summer Second Texas Air Quality Experiment, and the ability of the Nonhydrostatic Mesoscale Model–Community Multi‐scale Air Quality Model (NMM‐CMAQ) and the Weather Research and Forecast (WRF) model coupled with Chemistry (WRF‐Chem) models to simulate the observed meteorology and surface ozone. The surface ozone data consist of 118 sites that are part of the U.S. Environmental Protection Agency Aerometric Information Retrieval Now (AIRNow) network, while the meteorological data came from a network of eleven 915‐MHz wind profilers with RASS temperatures and supporting surface meteorological stations. High and low 8‐h maximum ozone occurrences most frequently develop as regional events, with similar ozone concentration patterns across all of east Texas, allowing for a separate analysis of high‐ and low‐ozone day conditions. The ability of the NMM‐CMAQ and WRF‐Chem models to simulate the meteorologically distinct high‐ and low‐ozone events is analyzed. Histograms of surface ozone show that both the NMM‐CMAQ and WRF‐Chem models underpredict the full range found in the observations. For low ozone values, the analysis indicates that the models have a positive bias because of too large of an ozone inflow boundary condition value over the Gulf of Mexico. In contrast, the models have a negative bias for very high ozone values that occur mostly in Houston and Dallas, which suggests that the urban emissions and/or chemistry is misrepresented in the models.

Future Changes in Biogenic Isoprene Emissions: How Might They Affect Regional and Global Atmospheric Chemistry?

Abstract Isoprene is emitted from vegetation to the atmosphere in significant quantities, and it plays an important role in the reactions that control tropospheric oxidant concentrations. As future climatic and land-cover changes occur, the spatial and temporal variations, as well as the magnitude of these biogenic isoprene emissions, are expected to change. This paper presents a study of the change in biogenic isoprene emissions that would result from both anthropogenic land-cover and climate-driven changes. Annual global isoprene emissions were estimated to be 522 Tg yr−1 under current climatological and land-cover conditions. When climate-driven land-cover changes are predicted, but climate does not change, total global emissions did not change significantly, although regional impacts were important. However, the use of future temperature and land-cover drivers to estimate isoprene emissions produced a global estimate of 889 Tg yr−1. Anthropogenic land-cover changes, such as urbanization and changes of natural vegetation to plantation forests, can also have substantial impacts on isoprene emissions (i.e., up to 717 Tg yr−1, a 37% increase, when land-cover changes but temperature remains at current-day values). The Model for Ozone and Related Tracers, version 2 (MOZART-2) was run with the different isoprene emission scenarios to simulate the potential changes in global atmospheric chemical composition. The simulated regional surface ozone concentrations changed as much as −9 to 55 ppbv under certain emission and climate scenarios. These results were used to evaluate changes in the ozone production chemistry under different emission scenarios. As expected, the impacts of changing isoprene emissions are regionally dependent, with large changes in China, the Amazon, and the United States.