Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
Abstract. Nitrous acid (HONO) can strongly affect atmospheric photochemistry in polluted regions through the production of hydroxyl radicals (OHs). In January 2017, a severe pollution episode occurred in the Pearl River Delta (PRD) of China, with maximum hourly PM2.5, ozone, and HONO levels reaching 400 µg m−3, 150 ppb, and 8 ppb, respectively, at a suburban site. The present study investigated the sources and processes generating such high HONO concentrations and the role of HONO chemistry in this severe winter episode. Four recently reported HONO sources were added to the Community Multiscale Air Quality (CMAQ) model, including RH-dependent (relative humidity) and light-enhancing effects on heterogeneous reactions, photolysis of particulate nitrate in the atmosphere, and photolysis of HNO3 and nitrate on surfaces. The revised model reproduced the observed HONO and significantly improved its performance for O3 and PM2.5. The model simulations showed that the heterogeneous generation on surfaces (with RH and light effects) was the largest contributor (72 %) to the predicted HONO concentrations, with the RH-enhancing effects more significant at nighttime and the light-enhancing effects more important in the daytime. The photolysis of total nitrate in the atmosphere and deposited on surfaces was the dominant HONO source during noon and afternoon, contributing above 50 % of the simulated HONO. The HONO photolysis was the dominant contributor to HOx production in this episode. With all HONO sources, the daytime average O3 at the Heshan site was increased by 24 ppb (or 70 %), compared to the simulation results without any HONO sources. Moreover, the simulated mean concentrations of TNO3 (HNO3+ fine particle NO3-) at the Heshan site, which was the key species for this haze formation, increased by about 17 µg m−3 (67 %) due to the HONO chemistry, and the peak enhancement reached 55 µg m−3. This study highlights the key role of HONO chemistry in the formation of winter haze in a subtropical environment.
The impacts of surface ozone (O 3) on human health and vegetation have prompted O 3 precursor emission reductions in the European Union (EU) and United States (US). In contrast, until recently, emissions have increased in East Asia and most strongly in China. As emissions change, the distribution of hourly O 3 concentrations also changes, as do the values of exposure metrics. The distribution changes can result in the exposure metric trend patterns changing in a similar direction as trends in emissions (e.g., metrics increase as emissions increase) or, in some cases, in opposite directions. This study, using data from 481 sites (276 in the EU, 196 in the US, and 9 in China), investigates the response of 14 human health and vegetation O 3 exposure metrics to changes in hourly O 3 concentration distributions over time. At a majority of EU and US sites, there was a reduction in the frequency of both relatively high and low hourly average O 3 concentrations. In contrast, for some sites in mainland China and Hong Kong, the middle of the distribution shifted upwards but the low end did not change and for other sites, the entire distribution shifted upwards. The responses of the 14 metrics to these changes at the EU, US, and Chinese sites were varied, and dependent on (1) the extent to which the metric was determined by relatively high, moderate, and low concentrations and (2) the relative magnitude of the shifts occurring within the O 3 concentration distribution. For example, the majority of the EU and US sites experienced decreasing trends in the magnitude of those metrics associated with higher concentrations. For the sites in China, all of the metrics either increased or had no trends. In contrast, there were a greater number of sites that had no trend for those metrics determined by a combination of moderate and high O 3 concentrations. A result of our analyses is that trends in mean or median concentrations did not appear to be well associated with some exposure metrics applicable for assessing human health or vegetation effects. The identification of shifting
Abstract. The detection and attribution of high background ozone (O3) events in the southwestern US is challenging but relevant to the effective implementation of the lowered National Ambient Air Quality Standard (NAAQS; 70 ppbv). Here we leverage intensive field measurements from the Fires, Asian, and Stratospheric Transport−Las Vegas Ozone Study (FAST-LVOS) in May–June 2017, alongside high-resolution simulations with two global models (GFDL-AM4 and GEOS-Chem), to study the sources of O3 during high-O3 events. We show possible stratospheric influence on 4 out of the 10 events with daily maximum 8 h average (MDA8) surface O3 above 65 ppbv in the greater Las Vegas region. While O3 produced from regional anthropogenic emissions dominates pollution events in the Las Vegas Valley, stratospheric intrusions can mix with regional pollution to push surface O3 above 70 ppbv. GFDL-AM4 captures the key characteristics of deep stratospheric intrusions consistent with ozonesondes, lidar profiles, and co-located measurements of O3, CO, and water vapor at Angel Peak, whereas GEOS-Chem has difficulty simulating the observed features and underestimates observed O3 by ∼20 ppbv at the surface. On days when observed MDA8 O3 exceeds 65 ppbv and the AM4 stratospheric ozone tracer shows 20–40 ppbv enhancements, GEOS-Chem simulates ∼15 ppbv lower US background O3 than GFDL-AM4. The two models also differ substantially during a wildfire event, with GEOS-Chem estimating ∼15 ppbv greater O3, in better agreement with lidar observations. At the surface, the two models bracket the observed MDA8 O3 values during the wildfire event. Both models capture the large-scale transport of Asian pollution, but neither resolves some fine-scale pollution plumes, as evidenced by aerosol backscatter, aircraft, and satellite measurements. US background O3 estimates from the two models differ by 5 ppbv on average (greater in GFDL-AM4) and up to 15 ppbv episodically. Uncertainties remain in the quantitative attribution of each event. Nevertheless, our multi-model approach tied closely to observational analysis yields some process insights, suggesting that elevated background O3 may pose challenges to achieving a potentially lower NAAQS level (e.g., 65 ppbv) in the southwestern US.
The ability of current global models to simulate the transport of CO 2 by mid-latitude, synopticscale weather systems (i.e., CO 2 weather) is important for inverse estimates of regional and global carbon budgets but remains unclear without comparisons to targeted measurements. Here, we evaluate ten models that participated in the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP version 9) with intensive aircraft measurements collected from the Atmospheric Carbon Transport (ACT)-America mission. We quantify model-data differences in the spatial variability of CO 2 mole fractions, mean winds, and boundary layer depths in 27 mid-latitude cyclones spanning four seasons over the central and eastern United States. We find that the OCO-2 MIP models are able to simulate observed CO 2 frontal differences with varying degrees of success in summer and spring, and most underestimate frontal differences in winter and autumn. The models may underestimate the observed boundary layer-to-free troposphere CO 2 differences in spring and autumn due to model errors in boundary layer height. Attribution of the causes of model biases in other seasons remains elusive. Transport errors, prior fluxes, and/or inversion algorithms appear to be the primary cause of these biases since model performance is not highly sensitive to the CO 2 data used in the inversion. The metrics presented here provide new benchmarks regarding the ability of atmospheric inversion systems to reproduce the CO 2 structure of mid-latitude weather systems. Controlled experiments are needed to link these metrics more directly to the accuracy of regional or global flux estimates.Plain Language Summary Global flux estimate systems use CO 2 observations, atmospheric transport models, CO 2 flux models (emissions and absorption), and mathematical optimization methods to estimate biosphere-atmosphere CO 2 exchange. Accurate representation of atmospheric transport is important for a reliable optimization of fluxes in these systems. We use intensive aircraft measurements of wind speed, boundary layer height, and horizontal and vertical differences of CO 2 concentrations within 27 mid-latitude cyclones collected by the Atmospheric Carbon Transport (ACT)-America mission to evaluate the performance of ten global flux estimate systems from the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP). We find the models can simulate observed horizontal CO 2 differences between the warm and cold parts of cyclones with different degrees of success in summer and spring, but often underestimate the observed cross-frontal and vertical differences in CO 2 in winter and autumn. The models may underestimate the CO 2 differences between the boundary layer and the free troposphere due to model errors in boundary layer height and surface fluxes. These weather-oriented CO 2 metrics provide benchmarks for testing simulations of the CO 2 structure within cyclones. Future efforts are needed to link these metrics more directly to the accuracy of CO 2 flux esti...
The ability of current global models to simulate the transport of CO 2 by mid-latitude, synopticscale weather systems (i.e., CO 2 weather) is important for inverse estimates of regional and global carbon budgets but remains unclear without comparisons to targeted measurements. Here, we evaluate ten models that participated in the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP version 9) with intensive aircraft measurements collected from the Atmospheric Carbon Transport (ACT)-America mission. We quantify model-data differences in the spatial variability of CO 2 mole fractions, mean winds, and boundary layer depths in 27 mid-latitude cyclones spanning four seasons over the central and eastern United States. We find that the OCO-2 MIP models are able to simulate observed CO 2 frontal differences with varying degrees of success in summer and spring, and most underestimate frontal differences in winter and autumn. The models may underestimate the observed boundary layer-to-free troposphere CO 2 differences in spring and autumn due to model errors in boundary layer height. Attribution of the causes of model biases in other seasons remains elusive. Transport errors, prior fluxes, and/or inversion algorithms appear to be the primary cause of these biases since model performance is not highly sensitive to the CO 2 data used in the inversion. The metrics presented here provide new benchmarks regarding the ability of atmospheric inversion systems to reproduce the CO 2 structure of mid-latitude weather systems. Controlled experiments are needed to link these metrics more directly to the accuracy of regional or global flux estimates.Plain Language Summary Global flux estimate systems use CO 2 observations, atmospheric transport models, CO 2 flux models (emissions and absorption), and mathematical optimization methods to estimate biosphere-atmosphere CO 2 exchange. Accurate representation of atmospheric transport is important for a reliable optimization of fluxes in these systems. We use intensive aircraft measurements of wind speed, boundary layer height, and horizontal and vertical differences of CO 2 concentrations within 27 mid-latitude cyclones collected by the Atmospheric Carbon Transport (ACT)-America mission to evaluate the performance of ten global flux estimate systems from the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP). We find the models can simulate observed horizontal CO 2 differences between the warm and cold parts of cyclones with different degrees of success in summer and spring, but often underestimate the observed cross-frontal and vertical differences in CO 2 in winter and autumn. The models may underestimate the CO 2 differences between the boundary layer and the free troposphere due to model errors in boundary layer height and surface fluxes. These weather-oriented CO 2 metrics provide benchmarks for testing simulations of the CO 2 structure within cyclones. Future efforts are needed to link these metrics more directly to the accuracy of CO 2 flux esti...
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