Melissa P. Sulprizio

Why do models overestimate surface ozone in the Southeast United States

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx ≡ NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NOx emissions. Upper tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Public health impacts of the severe haze in Equatorial Asia in September-October 2015: demonstration of a new framework for informing fire management strategies to reduce downwind smoke exposure

In September–October 2015, El Nino and positive Indian Ocean Dipole conditions set the stage for massive fires in Sumatra and Kalimantan (Indonesian Borneo), leading to persistently hazardous levels of smoke pollution across much of Equatorial Asia. Here we quantify the emission sources and health impacts of this haze episode and compare the sources and impacts to an event of similar magnitude occurring under similar meteorological conditions in September–October 2006. Using the adjoint of the GEOS-Chem chemical transport model, we first calculate the influence of potential fire emissions across the domain on smoke concentrations in three receptor areas downwind—Indonesia, Malaysia, and Singapore—during the 2006 event. This step maps the sensitivity of each receptor to fire emissions in each grid cell upwind. We then combine these sensitivities with 2006 and 2015 fire emission inventories from the Global Fire Assimilation System (GFAS) to estimate the resulting population-weighted smoke exposure. This method, which assumes similar smoke transport pathways in 2006 and 2015, allows near real-time assessment of smoke pollution exposure, and therefore the consequent morbidity and premature mortality, due to severe haze. Our approach also provides rapid assessment of the relative contribution of fire emissions generated in a specific province to smoke-related health impacts in the receptor areas. We estimate that haze in 2015 resulted in 100 300 excess deaths across Indonesia, Malaysia and Singapore, more than double those of the 2006 event, with much of the increase due to fires in Indonesias South Sumatra Province. The model framework we introduce in this study can rapidly identify those areas where land use management to reduce and/or avoid fires would yield the greatest benefit to human health, both nationally and regionally.

Organic nitrate chemistry and its implications for nitrogen budgets in an isoprene- and monoterpene-rich atmosphere: constraints from aircraft (SEAC 4 RS) and ground-based (SOAS) observations in the Southeast US

Formation of organic nitrates (RONO2) during oxidation of biogenic volatile organic compounds (BVOCs: isoprene, monoterpenes) is a significant loss pathway for atmospheric nitrogen oxide radicals (NOx), but the chemistry of RONO2 formation and degradation remains uncertain. Here we implement a new BVOC oxidation mechanism (including updated isoprene chemistry, new monoterpene chemistry, and particle uptake of RONO2) in the GEOS-Chem global chemical transport model with ∼25 × 25 km2 resolution over North America. We evaluate the model using aircraft (SEAC4RS) and ground-based (SOAS) observations of NOx, BVOCs, and RONO2 from the Southeast US in summer 2013. The updated simulation successfully reproduces the concentrations of individual gas- and particle-phase RONO2 species measured during the campaigns. Gas-phase isoprene nitrates account for 25-50% of observed RONO2 in surface air, and we find that another 10% is contributed by gas-phase monoterpene nitrates. Observations in the free troposphere show an important contribution from long-lived nitrates derived from anthropogenic VOCs. During both campaigns, at least 10% of observed boundary layer RONO2 were in the particle phase. We find that aerosol uptake followed by hydrolysis to HNO3 accounts for 60% of simulated gas-phase RONO2 loss in the boundary layer. Other losses are 20% by photolysis to recycle NOx and 15% by dry deposition. RONO2 production accounts for 20% of the net regional NOx sink in the Southeast US in summer, limited by the spatial segregation between BVOC and NOx emissions. This segregation implies that RONO2 production will remain a minor sink for NOx in the Southeast US in the future even as NOx emissions continue to decline.

Observing atmospheric formaldehyde (HCHO) from space: validation and intercomparison of six retrievals from four satellites (OMI, GOME2A, GOME2B, OMPS) with SEAC4RS aircraft observations over the southeast US

Formaldehyde (HCHO) column data from satellites are widely used as a proxy for emissions of volatile organic compounds (VOCs) but validation of the data has been extremely limited. Here we use highly accurate HCHO aircraft observations from the NASA SEAC4RS campaign over the Southeast US in August-September 2013 to validate and intercompare six retrievals of HCHO columns from four different satellite instruments (OMI, GOME2A, GOME2B and OMPS) and three different research groups. The GEOS-Chem chemical transport model is used as a common intercomparison platform. All retrievals feature a HCHO maximum over Arkansas and Louisiana, consistent with the aircraft observations and reflecting high emissions of biogenic isoprene. The retrievals are also interconsistent in their spatial variability over the Southeast US (r=0.4-0.8 on a 0.5°×0.5° grid) and in their day-to-day variability (r=0.5-0.8). However, all retrievals are biased low in the mean by 20-51%, which would lead to corresponding bias in estimates of isoprene emissions from the satellite data. The smallest bias is for OMI-BIRA, which has high corrected slant columns relative to the other retrievals and low scattering weights in its air mass factor (AMF) calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shape profiles for the AMF calculation and correcting this would eliminate its bias relative to the SEAC4RS data. Our results support the use of satellite HCHO data as a quantitative proxy for isoprene emission after correction of the low mean bias. There is no evident pattern in the bias, suggesting that a uniform correction factor may be applied to the data until better understanding is achieved.

Wildfire-specific Fine Particulate Matter and Risk of Hospital Admissions in Urban and Rural Counties.

Background: The health impacts of wildfire smoke, including fine particles (PM2.5), are not well understood and may differ from those of PM2.5 from other sources due to differences in concentrations and chemical composition. Methods: First, for the entire Western United States (561 counties) for 2004–2009, we estimated daily PM2.5 concentrations directly attributable to wildfires (wildfires-specific PM2.5), using a global chemical transport model. Second, we defined smoke wave as ≥2 consecutive days with daily wildfire-specific PM2.5 > 20 &mgr;g/m3, with sensitivity analysis considering 23, 28, and 37 &mgr;g/m3. Third, we estimated the risk of cardiovascular and respiratory hospital admissions associated with smoke waves for Medicare enrollees. We used a generalized linear mixed model to estimate the relative risk of hospital admissions on smoke wave days compared with matched comparison days without wildfire smoke. Results: We estimated that about 46 million people of all ages were exposed to at least one smoke wave during 2004 to 2009 in the Western United States. Of these, 5 million are Medicare enrollees (≥65 years). We found a 7.2% (95% confidence interval: 0.25%, 15%) increase in risk of respiratory admissions during smoke wave days with high wildfire-specific PM2.5 (>37 &mgr;g/m3) compared with matched non smoke wave days. We did not observe an association between smoke wave days with wildfire-specific PM2.5 ⩽ 37 &mgr;g/m3and respiratory or cardiovascular admissions. Respiratory effects of wildfire-specific PM2.5 may be stronger than that of PM2.5 from other sources. Conclusion: Short-term exposure to wildfire-specific PM2.5was associated with risk of respiratory diseases in the elderly population in the Western United States during severe smoke days. See video abstract at, http://links.lww.com/EDE/B137.

Development of a grid-independent GEOS-Chem chemical transport model (v9-02) as an atmospheric chemistry module for Earth system models

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been re-engineered to also serve as an atmospheric chemistry module for Earth system models (ESMs). This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of the GEOSChem scientific code, permitting the exact same GEOSChem code to be used as an ESM module or as a standalone CTM. In this manner, the continual stream of updates contributed by the CTM user community is automatically passed on to the ESM module, which remains state of science and referenced to the latest version of the standard GEOS-Chem CTM. A major step in this re-engineering was to make GEOS-Chem grid independent, i.e., capable of using any geophysical grid specified at run time. GEOS-Chem data sockets were also created for communication between modules and with external ESM code. The grid-independent, ESMF-compatible GEOS-Chem is now the standard version of the GEOS-Chem CTM. It has been implemented as an atmospheric chemistry module into the NASA GEOS5 ESM. The coupled GEOS-5–GEOS-Chem system was tested for scalability and performance with a tropospheric oxidant-aerosol simulation (120 coupled species, 66 transported tracers) using 48–240 cores and message-passing interface (MPI) distributed-memory parallelization. Numerical experiments demonstrate that the GEOS-Chem chemistry module scales efficiently for the number of cores tested, with no degradation as the number of cores increases. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemistry module means that the relative cost goes down with increasing number of cores in a massively parallel environment.

Burden of Disease from Rising Coal-Fired Power Plant Emissions in Southeast Asia

Southeast Asia has a very high population density and is on a fast track to economic development, with most of the growth in electricity demand currently projected to be met by coal. From a detailed analysis of coal-fired power plants presently planned or under construction in Southeast Asia, we project in a business-as-usual scenario that emissions from coal in the region will triple to 2.6 Tg a-1 SO2 and 2.6 Tg a-1 NOx by 2030, with the largest increases occurring in Indonesia and Vietnam. Simulations with the GEOS-Chem chemical transport model show large resulting increases in surface air pollution, up to 11 μg m-3 for annual mean fine particulate matter (PM2.5) in northern Vietnam and up to 15 ppb for seasonal maximum 1 h ozone in Indonesia. We estimate 19 880 (11 400-28 400) excess deaths per year from Southeast Asian coal emissions at present, increasing to 69 660 (40 080-126 710) by 2030. 9000 of these excess deaths in 2030 are in China. As Chinese emissions from coal decline in coming decades, transboundary pollution influence from rising coal emissions in Southeast Asia may become an increasing issue.

Future respiratory hospital admissions from wildfire smoke under climate change in the Western US

Background. Wildfires are anticipated to be more frequent and intense under climate change. As a result, wildfires may emit more air pollutants that can harm health in communities in the future. The health impacts of wildfire smoke under climate change are largely unknown. Methods. We linked projections of future levels of fine particulate matter (PM2.5) specifically from wildfire smoke under the A1B climate change scenario using the GEOS-Chem model for 2046–2051, present-day estimates of hospital admission impacts from wildfire smoke, and future population projections to estimate the change in respiratory hospital admissions for persons ≥65 years by county (n = 561) from wildfire PM2.5 under climate change in the Western US. Results. The increase in intense wildfire smoke days from climate change would result in an estimated 178 (95% confidence interval: 6.2, 361) additional respiratory hospital admissions in the Western US, accounting for estimated future increase in the elderly population. Climate change is estimated to impose an additional 4990 high-pollution smoke days. Central Colorado, Washington and southern California are estimated to experience the highest percentage increase in respiratory admissions from wildfire smoke under climate change. Conclusion. Although the increase in number of respiratory admissions from wildfire smoke seems modest, these results provide important scientific evidence of an often-ignored aspect of wildfire impact, and information on their anticipated spatial distribution. Wildfires can cause serious social burdens such as property damage and suppression cost, but can also raise health problems. The results provide information that can be incorporated into development of environmental and health policies in response to climate change. Climate change adaptation policies could incorporate scientific evidence on health risks from natural disasters such as wildfires.

Who Among the Elderly Is Most Vulnerable to Exposure to and Health Risks of Fine Particulate Matter From Wildfire Smoke

Wildfires burn more than 7 million acres in the United States annually, according to the US Forest Service. Little is known about which subpopulations are more vulnerable to health risks from wildfire smoke, including those associated with fine particulate matter. We estimated exposure to fine particles specifically from wildfires, as well as the associations between the presence of wildfire-specific fine particles and the amount of hospital admissions for respiratory causes among subpopulations older than 65 years of age in the western United States (2004-2009). Compared with other populations, higher fractions of persons who were black, lived in urban counties, and lived in California were exposed to more than 1 smoke wave (high-pollution episodes from wildfire smoke). The risks of respiratory admissions on smoke-wave days compared with non-smoke-wave days increased 10.4% (95% confidence interval: 1.9, 19.6) for women and 21.7% (95% confidence interval: 0.4, 47.3) for blacks. Our findings suggest that increased risks of respiratory admissions from wildfire smoke was significantly higher for women than for men (10.4% vs. 3.7%), blacks than whites (21.7% vs. 6.9%), and, although associations were not statistically different, people in lower-education counties than higher-educated counties (12.7% vs. 6.1%). Our study raised important environmental justice issues that can inform public health programs and wildfire management. As climate change increases the frequency and intensity of wildfires, evidence on vulnerable subpopulations can inform disaster preparedness and the understanding of climate change consequences.

Monitoring Global Tropospheric OH Concentrations using Satellite Observations of Atmospheric Methane

The hydroxyl radical (OH) is the main tropospheric oxidant and is the largest sink for atmospheric methane. The global abundance of OH has been monitored for the past decades with the methyl chloroform (CH3CCl3) proxy. This approach is becoming ineffective as atmospheric CH3CCl3 concentrations decline. Here we propose that satellite observations of atmospheric methane in the shortwave infrared (SWIR) and thermal infrared (TIR) can provide an effective 15 replacement method. The premise is that the atmospheric signature of the methane sink from oxidation by OH is distinct from that of methane emissions. We evaluate this method in an observing system simulation experiment (OSSE) framework using synthetic SWIR and TIR satellite observations representative of the TROPOMI and CrIS instruments, respectively. The synthetic observations are interpreted with a Bayesian inverse analysis optimizing both gridded methane emissions and global OH concentrations with detailed error accounting, including errors in meteorological fields and in OH distributions. 20 We find that the satellite observations can constrain the global tropospheric OH concentrations with a precision better than 1% and an accuracy of about 3% for SWIR and 7% for TIR. The inversion can successfully separate contributions from methane emissions and OH concentrations to the methane budget and its trend. We also show that satellite methane observations can constrain the interhemispheric difference in OH. The main limitation to the accuracy is uncertainty in the spatial and seasonal distribution of OH. 25 Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-467 Manuscript under review for journal Atmos. Chem. Phys. Discussion started: 29 May 2018 c