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Martin, Randall V.

Publications and source records attributed to Martin, Randall V..

At least 19 records

Constraining Present‐Day Anthropogenic Total Iron Emissions Using Model and Observations

Abstract Iron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long‐term, near‐source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub‐sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under‐ or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting‐related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long‐term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.

Meteorology & Atmospheric Sciences↗

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM 2.5 ) is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM 2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM 2.5 , and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM 2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM 2.5 -attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM 2.5 (>95 µg/m 3 ). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM 2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sources in South Asia.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. Methods: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ) and ground-level ozone (O 3 ), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ longterm exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. Results: Among the 151105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM 2.5 (1.70 µg/m 3 ), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO 2 . We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O 3 for hospital admission, ICU admission and death, respectively.

60 APPLIED LIFE SCIENCES↗

Source sector and fuel contributions to ambient PM 2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

54 ENVIRONMENTAL SCIENCES↗

Factors controlling marine aerosol size distributions and their climate effects over the northwest Atlantic Ocean region

Abstract. Aerosols over Earth's remote and spatially extensive ocean surfaces have important influences on planetary climate. However, these aerosols and their effects remain poorly understood, in part due to the remoteness and limited observations over these regions. In this study, we seek to understand factors that shape marine aerosol size distributions and composition in the northwest Atlantic Ocean region. We use the GEOS-Chem model with the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm model to interpret measurements collected from ship and aircraft during the four seasonal campaigns of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) conducted between 2015 and 2018. Observations from the NAAMES campaigns show enhancements in the campaign-median number of aerosols with diameters larger than 3 nm in the lower troposphere (below 6 km), most pronounced during the phytoplankton bloom maxima (May/June) below 2 km in the free troposphere. Our simulations, combined with NAAMES ship and aircraft measurements, suggest several key factors that contribute to aerosol number and size in the northwest Atlantic lower troposphere, with significant regional-mean (40–60∘ N and 20–50∘ W) cloud-albedo aerosol indirect effect (AIE) and direct radiative effect (DRE) processes during the phytoplankton bloom. These key factors and their associated simulated radiative effects in the region include the following: (1) particle formation near and above the marine boundary layer (MBL) top (AIE: −3.37 W m−2, DRE: −0.62 W m−2); (2) particle growth due to marine secondary organic aerosol (MSOA) as the nascent particles subside into the MBL, enabling them to become cloud-condensation-nuclei-sized particles (AIE: −2.27 W m−2, DRE: −0.10 W m−2); (3) particle formation and growth due to the products of dimethyl sulfide, above and within the MBL (−1.29 W m−2, DRE: −0.06 W m−2); (4) ship emissions (AIE: −0.62 W m−2, DRE: −0.05 W m−2); and (5) primary sea spray emissions (AIE: +0.04 W m−2, DRE: −0.79 W m−2). Our results suggest that a synergy of particle formation in the lower troposphere (particularly near and above the MBL top) and growth by MSOA contributes strongly to cloud-condensation-nuclei-sized particles with significant regional radiative effects in the northwest Atlantic. To gain confidence in radiative effect magnitudes, future work is needed to understand (1) the sources and temperature dependence of condensable marine vapors forming MSOA, (2) primary sea spray emissions, and (3) the species that can form new particles in the lower troposphere and grow these particles as they descend into the marine boundary layer.

54 ENVIRONMENTAL SCIENCES↗

Assessing Uncertainties of a Geophysical Approach to Estimate Surface Fine Particulate Matter Distributions from Satellite-Observed Aerosol Optical Depth

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 1 km2(exp) resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2(exp) 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 10 km 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 11 µg m−3(exp) in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3(exp). 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 representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. 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.

aerosol optical depth↗

Variation in Global Chemical Composition of PM2.5: Emerging Results from SPARTAN

The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM (sub 2.5). Our methods infer the spatial and temporal variability of PM (sub 2.5) in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM (sub 2.5), with a collocated nephelometer sampling air continuously. SPARTAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM (sub 2.5) and columnar aerosol optical depth (AOD). We have examined the chemical composition of PM (sub 2.5) at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2-26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM (sub 2.5) constituents across all sites (relative contribution plus or minus Standard Deviation) are ammoniated sulfate (20 percent plus or minus 11 percent), crustal material (13.4 percent plus or minus 9.9 percent), equivalent black carbon (11.9 percent plus or minus 8.4 percent), ammonium nitrate (4.7 percent plus or minus 3.0 percent), sea salt (2.3 percent plus or minus 1.6 percent), trace element oxides (1.0 percent plus or minus 1.1 percent), water (7.2 percent plus or minus 3.3 percent) at 35 percent relative humidity, and residual matter (40 percent plus or minus 24 percent). Analysis of filter samples reveals that several PM (sub 2.5) chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 microns per cubic meter (Buenos Aires, Argentina) to 17 microns per cubic meter (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 microns per cubic meter (Mammoth Cave, in summer) to 6.8 microns per cubic meter (Kanpur, dry season). Equivalent black carbon ranged from 0.7 microns per cubic meter (Mammoth Cave) to over 8 microns per cubic meter (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM (sub 2.5) (r squared equals 0.76, slope equals 1.12), daily sulfate (r squared equals 0.86, slope equals 1.03), and mean fractions of all major PM (sub 2.5) components (within 6 percent). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 percent for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn to Al ratios. The expected water contribution to aerosols is calculated via the hygroscopicity parameter kappa (sub v (volume)) for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 plus or minus 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM (sub 2.5) at 35 percent relative humidity by merging with nephelometer measurements. These hourly PM (sub 2.5) estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r squared equals 0.67 (number equals 3167), compared to r squared equals 0.62 when v (volume) was not considered. SPARTAN continues to provide an open-access database of PM (sub 2.5) compositional filter information and hourly mass collected from a global federation of instruments.

Snider, Graydon↗

Space-Based Detection of Missing Sulfur Dioxide Sources of Global Air Pollution

Sulfur dioxide is designated a criteria air contaminant (or equivalent) by virtually all developed nations. When released into the atmosphere, sulfur dioxide forms sulfuric acid and fine particulate matter, secondary pollutants that have significant adverse effects on human health, the environment and the economy. The conventional, bottom-up emissions inventories used to assess impacts, however, are often incomplete or outdated, particularly for developing nations that lack comprehensive emission reporting requirements and infrastructure. Here we present a satellite-based, global emission inventory for SO2 that is derived through a simultaneous detection, mapping and emission-quantifying procedure, and thereby independent of conventional information sources. We find that of the 500 or so large sources in our inventory, nearly 40 are not captured in leading conventional inventories. These missing sources are scattered throughout the developing world-over a third are clustered around the Persian Gulf-and add up to 7 to 14 Tg of SO2 yr(exp -1), or roughly 6-12% of the global anthropogenic source. Our estimates of national total emissions are generally in line with conventional numbers, but for some regions, and for SO2 emissions from volcanoes, discrepancies can be as large as a factor of three or more. We anticipate that our inventory will help eliminate gaps in bottom-up inventories, independent of geopolitical borders and source types.

OMI↗

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998−2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

aerosols↗

Interpreting the Ultraviolet Aerosol Index Observed with the OMI Satellite Instrument to Understand Absorption by Organic Aerosols: Implications for Atmospheric Oxidation and Direct Radiative Effects

Satellite observations of the ultraviolet aerosol index (UVAI) are sensitive to absorption of solar radiation by aerosols; this absorption affects photolysis frequencies and radiative forcing. We develop a global simulation of the UVAI using the 3-D chemical transport model GEOSChem coupled with the Vector Linearized Discrete Ordinate Radiative Transfer model (VLIDORT). The simulation is applied to interpret UVAI observations from the Ozone Monitoring Instrument (OMI) for the year 2007. Simulated and observed values are highly consistent in regions where mineral dust dominates the UVAI, but a large negative bias (-0.32 to -0.97) exists between simulated and observed values in biomass burning regions. We determine effective optical properties for absorbing organic aerosol, known as brown carbon (BrC), and implement them into GEOS-Chem to better represent observed UVAI values over biomass burning regions. The inclusion of absorbing BrC decreases the mean bias between simulated and OMI UVAI values from -0.57 to -0.09 over West Africa in January, from -0.32 to +0.0002 over South Asia in April, from -0.97 to -0.22 over southern Africa in July, and from -0.50 to +0.33 over South America in September. The spectral dependence of absorption after including BrC in the model is broadly consistent with reported observations for biomass burning aerosol, with absorbing Angstrom exponent (AAE) values ranging from 2.9 in the ultraviolet (UV) to 1.3 across the UV-Near IR spectrum. We assess the effect of the additional UV absorption by BrC on atmospheric photochemistry by examining tropospheric hydroxyl radical (OH) concentrations in GEOS-Chem. The inclusion of BrC decreases OH by up to 30% over South America in September, up to 20% over southern Africa in July, and up to 15% over other biomass burning regions. Global annual mean OH concentrations in GEOS-Chem decrease due to the presence of absorbing BrC, increasing the methyl chloroform lifetime from 5.62 to 5.68 years, thus reducing the bias against observed values. We calculate the direct radiative effect (DRE) of BrC using GEOS-Chem coupled with the radiative transfer model RRTMG (GC-RT). Treating organic aerosol as containing more strongly absorbing BrC changes the global annual mean all-sky top of atmosphere (TOA) DRE by +0.03Wm(exp -2) and all-sky surface DRE by -0.08Wm(exp -2). Regional changes of up to +0.3Wm(exp -2) at TOA and down to -1.5Wm(exp -2) at the surface are found over major biomass burning regions.

Air Pollution↗

Comparison of Remote Sensing and Fixed-Site Monitoring Approaches for Examining Air Pollution and Health in a National Study Population

Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6e10% increases in respiratory and allergic health outcomes per interquartile range (3.97 mg m3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20e64) in the national study population. Risk estimates for air pollution and respiratory/ allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05).

validation↗

Emissions Estimation from Satellite Retrievals: a Review of Current Capability

Since the mid-1990s a new generation of Earth-observing satellites has been able to detect tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary emitted species can be measured by one or more of the instruments. This review article addresses the question of how well we can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U.S. air quality managers. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic). Techniques that enhance the usefulness of current retrievals (data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc.) are discussed. Finally, we point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial (few km) and temporal (hourly) resolution.

air quality↗

Satellite-based Estimates of Ambient Air Pollution and Global Variations in Childhood Asthma Prevalence

Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter < 2.5 microm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone. Methods: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1deg × 0.1deg and modeled estimates of ozone at a resolution of 1deg × 1deg to 183 ISAAC centers. We used center-level prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001-2003). Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was -0.043 [95% confidence interval (CI): -0.139, 0.053] and 0.017 (95% CI: -0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was -0.116 (95% CI: -0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was -0.139 (95% CI: -0.347, 0.068). The corresponding association with ozone (per ppbV) was -0.171 (95% CI: -0.275, -0.067). Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.

Air pollution↗

A Satellite-Based Multi-Pollutant Index of Global Air Quality

Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing.

Cooper, Mathew J.↗

Application of OMI Observations to a Space-Based Indicator of NOx and VOC Controls on Surface Ozone Formation

We investigated variations in the relative sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NOx) as inferred from the ratio of the tropospheric columns of formaldehyde to nitrogen dioxide (the "Ratio") from the Aura Ozone Monitoring Instrument (OMI). Our modeling study suggests that ozone formation decreases with reductions in VOCs at Ratios less than 1 and NOx at Ratios greater than 2; both NOx and VOC reductions may decrease ozone formation for Ratios between 1 and 2. Using this criteria. the OMI data indicate that ozone formation became: 1. more sensitive to NOx over most of the United States from 2005 to 2007 because of the substantial decrease in NOx emissions, primarily from stationary sources, and the concomitant decrease in the tropospheric column of NO2. and 2. more sensitive to NOx with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. In cities with relatively low isoprene emissions (e.g .. Chicago). the data clearly indicate that ozone formation became more sensitive to NOx from 2005 to 2007. In cities with relatively high isoprene emissions (e.g ., Atlanta), we found that the increase in the Ratio due to decreasing NOx emissions was not obvious as this signal was convolved with variations in the Ratio associated with the temperature dependence of isoprene emissions and, consequently, the formaldehyde concentration.

Duncan, Bryan N.↗

The Sensitivity of U.S. Surface Ozone Formation to NOx, and VOCs as Viewed from Space

We investigated variations in the sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NO(x)) as inferred from the ratio of tropospheric columns of formaldehyde and nitrogen dioxide from the Aura Ozone Monitoring Instrument (OMI). The data indicate that ozone formation became: 1. more sensitive to NO(x) over most of the U.S, from 2005 to 2007 because of substantial decreases in NO(x) emissions primarily from stationary sources, and 2. more sensitive to NO(x) with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. Based on our interpretation of the data, current strategies implemented to reduce unhealthy levels of surface ozone should focus more on reducing NO(x) emissions, except in some downtown areas which have historically benefited from reductions in VOC emissions.

Duncan, Bryan N.↗