ALBERT

Description: Surface ozone (O3) responds to varying global-to-regional precursor emissions, climate, and extreme weather, with implications for designing effective air quality control policies. We examine these conjoined processes with observations and global chemistry-climate model (GFDL-AM3) hindcasts over 1980–2014. The model captures the salient features of observed trends in daily maximum 8-hour average O3; (1) increases over East Asia (up to 2 ppb yr−1), (2) springtime increases at western US (WUS) rural sites (0.2–0.5 ppb yr−1) with a ‘baseline’ sampling approach, (3) summertime decreases, largest at the 95th percentile, and wintertime increases in the 50th to 5th percentiles over the eastern US (EUS). Asian NOx emissions tripled since 1990, contributing as much as 65 % to modeled springtime background O3 increases (0.3–0.5 ppb yr−1) over the WUS, outpacing O3 decreases attained via US domestic emission controls. Methane increases over this period raise WUS background O3 by 15 %. During summer, increasing Asian emissions approximately offset the effects of US emission reductions, leading to weak or insignificant observed O3 trends at WUS rural sites. While wildfire emissions can enhance summertime monthly mean O3 at individual sites by 2–8 ppb, high temperatures and the associated buildup of O3 produced from regional anthropogenic emissions contribute most to elevating observed summertime O3 throughout the USA. Rising Asian emissions and global methane under the RCP8.5 scenario increase mean springtime O3 above the WUS by ~ 10 ppb from 2010 to 2030. Historical EUS O3 decreases, driven by regional emission controls, were most pronounced in the Southeast with an earlier onset of biogenic isoprene emissions and NOx-sensitive O3 production. Regional NOx reductions also alleviated the O3 buildup during the recent heat waves of 2011 and 2012 relative to earlier heat waves (e.g., 1988; 1999). Without emission controls, the 95th percentile summertime O3 in the EUS would have increased by 0.2–0.4 ppb yr−1 over 1988–2014 due to more frequent hot extremes and rising biogenic isoprene emissions.

Description: Widespread efforts to abate ozone (O3) smog have significantly reduced nitrogen oxides (NOx) emissions over the past two decades in the Southeast U.S. (SEUS), a place heavily influenced by both anthropogenic and biogenic emissions. How reactive nitrogen speciation responds to the reduction in NOx emissions in this region remains to be elucidated. Here we exploit aircraft measurements from ICARTT (July–August, 2004), SENEX (June–July, 2013), and SEAC4RS (August–September, 2013) and long-term ground measurement networks alongside a global chemistry-climate model to examine decadal changes in summertime reactive nitrogen species and ozone over the Southeast U.S. We find that most reactive nitrogen species, including NOx, peroxyacetyl nitrate (PAN) and nitric acid (HNO3) decline proportionally with decreasing NOx emissions in this region, leading to a similar decline in exported NOy. This linear response is in part due to the nearly constant summertime supply of biogenic VOC emissions in this region. Our model captures the observed relative change of reactive nitrogen species and surface ozone from 2004 to 2013. Model sensitivity tests indicate that further reductions of NOx emissions will lead to a continued decline in surface ozone and less frequent extreme ozone events.

Description: An approach for analysis and modeling of global atmospheric chemistry is developed for application to measurements that provide a tropospheric climatology of those heterogeneously distributed, reactive species that control the loss of methane and the production and loss of ozone. We identify key species (e.g., O3, NOx, HNO3, HNO4, C2H3NO5, H2O, HOOH, CH3OOH, HCHO, CO, CH4, C2H6, acetaldehyde, acetone), and presume that they can be measured simultaneously in air parcels on the scale of a few km horizontally and a few tenths vertically. Six global models have prepared such climatologies (at model resolution) for August with emphasis on the vast central Pacific and Atlantic Ocean basins. We show clear differences in model generated reactivities as well as species covariances that could readily be discriminated with an unbiased climatology. A primary tool is comparison of multi-dimensional probability densities of key species weighted by frequency of occurrence as well as by the reactivity of the parcels with respect to methane and ozone. The reactivity-weighted probabilities tell us which parcels matter in this case. Testing 100-km scale models with 2-km measurements using these tools also addresses a core question about model resolution and whether fine-scale atmospheric structures matter to the overall ozone and methane budget. A new method enabling these six global chemistry-climate models to ingest an externally-sourced climatology and then compute air parcel reactivity is demonstrated. Such an observed climatology is anticipated from the NASA Atmospheric Tomography (ATom) aircraft mission (2015–2020), measuring the key species, executing profiles over the Pacific and Atlantic Ocean basins. This work is a core part of the design of ATom.

Description: We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating over the data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14,880 parcels along 180 W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10 % of parcels control 25–30 % of the total reactivities), but do not fully agree on which parcels comprise the top 10 %. Distinct differences in specific features occur, including the regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the 6 models tested here, 3 are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify 4, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

Description: Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1km2 resolution for 2011 over the Northeast USA by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12km2 horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly, to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5/AOD can explain more than 70% of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5/AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5/AOD lead to an error of 11μg/m3 in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8μg/m3. Using multi-platform ground, airborne and radiosonde measurements, we show that uncertainties of modeled PM2.5/AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model uncertainties of relative humidity and aerosol vertical profile shape contribute some systematic biases. The parameterization of aerosol optical properties, which determines the mass-extinction efficiency, also contributes to random uncertainty, with the size distribution the largest source of uncertainty, and hygroscopicity of inorganic salt the second. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.

Description: The unintended climatic implications of aerosol and precursor emission reductions implemented to protect public health are poorly understood. We investigate the precipitation response to regional changes in aerosol emissions using three coupled chemistry-climate models: NOAA Geophysical Fluid Dynamics Laboratory Coupled Model 3 (GFDL-CM3), NCAR Community Earth System Model (CESM1), and NASA Goddard Institute for Space Studies ModelE2 (GISS-E2). Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with fourteen individual aerosol emissions perturbation simulations (160–240 years each). We perturb emissions of sulfur dioxide and/or carbonaceous aerosol within six world regions and assess the significance of precipitation responses relative to internal variability determined by the control simulation and across the models. Global and regional precipitation mostly increases when we reduce regional aerosol emissions in the models, with the strongest responses occurring for sulfur dioxide emissions reductions from Europe and the United States. Precipitation responses to aerosol emissions reductions are largest in the tropics and project onto the El Niño-Southern Oscillation (ENSO). Regressing precipitation onto an Indo-Pacific zonal sea level pressure gradient index (a proxy for ENSO) indicates that the ENSO component of the precipitation response to regional aerosol removal can be as large as 20% of the total simulated response. Precipitation increases in the Sahel in response to aerosol reductions in remote regions because an anomalous interhemispheric temperature gradient alters the position of the Intertropical Convergence Zone (ITCZ). This mechanism holds across multiple aerosol reduction simulations and models.

Description: U.S. background ozone (O3) includes O3 produced from anthropogenic O3 precursors emitted outside of the U.S.A., from global methane, and from any natural sources. Using a suite of sensitivity simulations in the GEOS-Chem global chemistry-transport model, we estimate the influence from individual background versus U.S. anthropogenic sources on total surface O3 over ten continental U.S. regions from 2004–2012. Evaluation with observations reveals model biases of +0–19 ppb in seasonal mean maximum daily 8-hour average (MDA8) O3, highest in summer over the eastern U.S.A. Simulated high-O3 events cluster too late in the season. We link these model biases to regional O3 production (e.g., U.S. anthropogenic, biogenic volatile organic compounds (BVOC), and soil NOx, emissions), or coincident missing sinks. On the ten highest observed O3 days during summer (O3_top10obs_JJA), U.S. anthropogenic emissions enhance O3 by 5–11 ppb and by less than 2 ppb in the eastern versus western U.S.A. The O3 enhancement from BVOC emissions during summer is 1–7 ppb higher on O3_top10obs_JJA days than on average days, while intercontinental pollution is up to 2 ppb higher on average vs. on O3_top10obs_JJA days. In the model, regional sources of O3 precursor emissions drive interannual variability in the highest observed O3 levels. During the summers of 2004–2012, monthly regional mean U.S. background O3 MDA8 levels vary by 10–20 ppb. Simulated summertime total surface O3 levels on O3_top10obs_JJA days decline by 3 ppb (averaged over all regions) from 2004–2006 to 2010–2012 in both the observations and the model, reflecting rising U.S. background (+2 ppb) and declining U.S. anthropogenic O3 emissions (−6 ppb). The model attributes interannual variability in U.S. background O3 on O3_top10obs days to natural sources, not international pollution transport. We find that a three-year averaging period is not long enough to eliminate interannual variability in background O3.

Description: Peroxy acetyl nitrate (PAN) is the most important reservoir species for nitrogen oxides (NOx) in the remote troposphere. Upon decomposition in remote regions, PAN promotes efficient ozone production. We evaluate monthly mean PAN abundances from global chemical transport model simulations (HTAP1) for 2001 with measurements from five northern mid-latitude mountain sites (four European and one North American). The multi-model mean generally captures the observed monthly mean PAN but individual models simulate a factor of ~4–8 range in monthly abundances. We quantify PAN source-receptor relationships at the measurement sites with sensitivity simulations that decrease regional anthropogenic emissions of PAN (and ozone) precursors by 20% from North America (NA), Europe (EU), and East Asia (EA). The HTAP1 models attribute more of the observed PAN at Jungfraujoch (Switzerland) to emissions in NA and EA, and less to EU, than a prior trajectory-based estimate. The trajectory-based and modeling approaches agree that EU emissions play a role in the observed springtime PAN maximum at Jungfraujoch. The signal from anthropogenic emissions on PAN is strongest at Jungfraujoch and Mount Bachelor (Oregon, U.S.A.) during April. In this month, PAN source-receptor relationships correlate both with model differences in regional anthropogenic volatile organic compound (AVOC) emissions and with ozone source-receptor relationships. PAN observations at mountaintop sites can thus provide key information for evaluating models, including links between PAN and ozone production and source-receptor relationships. Establishing routine, long-term, mountaintop measurements is essential given the large observed interannual variability in PAN.

Description: Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J-values) throughout the remote Pacific and Atlantic Ocean basins. ATom made profiling circumnavigations of the troposphere over four seasons during 2016–2018. J-values are a primary chemical control over tropospheric ozone and methane abundances and their greenhouse effects. Clouds have been recognized for more than three decades as being an important factor in tropospheric chemistry. The ATom climatology of J-values is a unique test of how the chemistry models treat clouds. This work focuses on measurements over the Pacific during the first deployment (ATom-1) in August 2016. Nine global chemistry–climate or –transport models provide J-values for the domains measured in ATom-1. We compare mean profiles over a range of cloudy and clear conditions; but, more importantly, we build a statistical picture of the impact of clouds on J-values through the distribution of the ratio of J-cloudy to J-clear. In detail, the models show largely disparate patterns. When compared with measurements, there is some limited, broad agreement. Models here have resolutions of 50–200km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average the scattered sunlight, but only out to scales of 10s of km. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements.

Description: The climatic implications of regional aerosol and precursor emissions reductions implemented to protect human health are poorly understood. We investigate the mean and extreme temperature response to regional changes in aerosol emissions using three coupled chemistry–climate models: NOAA GFDL CM3, NCAR CESM1, and NASA GISS-E2. Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160–240 years each). We perturb emissions of sulfur dioxide (SO2) and/or carbonaceous aerosol within six world regions and assess the statistical significance of mean and extreme temperature responses relative to internal variability determined by the control simulation and across the models. In all models, the global mean surface temperature response (perturbation minus control) to SO2 and/or carbonaceous aerosol is mostly positive (warming) and statistically significant and ranges from +0.17 K (Europe SO2) to −0.06 K (US BC). The warming response to SO2 reductions is strongest in the US and Europe perturbation simulations, both globally and regionally, with Arctic warming up to 1 K due to a removal of European anthropogenic SO2 emissions alone; however, even emissions from regions remote to the Arctic, such as SO2 from India, significantly warm the Arctic by up to 0.5 K. Arctic warming is the most robust response across each model and several aerosol emissions perturbations. The temperature response in the Northern Hemisphere midlatitudes is most sensitive to emissions perturbations within that region. In the tropics, however, the temperature response to emissions perturbations is roughly the same in magnitude as emissions perturbations either within or outside of the tropics. We find that climate sensitivity to regional aerosol perturbations ranges from 0.5 to 1.0 K (W m−2)−1 depending on the region and aerosol composition and is larger than the climate sensitivity to a doubling of CO2 in two of three models. We update previous estimates of regional temperature potential (RTP), a metric for estimating the regional temperature responses to a regional emissions perturbation that can facilitate assessment of climate impacts with integrated assessment models without requiring computationally demanding coupled climate model simulations. These calculations indicate a robust regional response to aerosol forcing within the Northern Hemisphere midlatitudes, regardless of where the aerosol forcing is located longitudinally. We show that regional aerosol perturbations can significantly increase extreme temperatures on the regional scale. Except in the Arctic in the summer, extreme temperature responses largely mirror mean temperature responses to regional aerosol perturbations through a shift of the temperature distributions and are mostly dominated by local rather than remote aerosol forcing.