ABSTRACT
The hydroxyl radical (OH) fuels atmospheric chemical cycling as the main sink for methane and a driver of the formation and loss of many air pollutants, but direct OH observations are sparse. We develop and evaluate an observation-based proxy for short-term, spatial variations in OH (ProxyOH) in the remote marine troposphere using comprehensive measurements from the NASA Atmospheric Tomography (ATom) airborne campaign. ProxyOH is a reduced form of the OH steady-state equation representing the dominant OH production and loss pathways in the remote marine troposphere, according to box model simulations of OH constrained with ATom observations. ProxyOH comprises only eight variables that are generally observed by routine ground- or satellite-based instruments. ProxyOH scales linearly with in situ [OH] spatial variations along the ATom flight tracks (median r2 = 0.90, interquartile range = 0.80 to 0.94 across 2-km altitude by 20° latitudinal regions). We deconstruct spatial variations in ProxyOH as a first-order approximation of the sensitivity of OH variations to individual terms. Two terms modulate within-region ProxyOH variations-water vapor (H2O) and, to a lesser extent, nitric oxide (NO). This implies that a limited set of observations could offer an avenue for observation-based mapping of OH spatial variations over much of the remote marine troposphere. Both H2O and NO are expected to change with climate, while NO also varies strongly with human activities. We also illustrate the utility of ProxyOH as a process-based approach for evaluating intermodel differences in remote marine tropospheric OH.
ABSTRACT
The combination of air quality (AQ) data from satellites and low-cost sensor systems, along with output from AQ models, have the potential to augment high-quality, regulatory-grade data in countries with in situ monitoring networks and provide much needed AQ information in countries without them, including Low and Moderate Income Countries (LMICs). We demonstrate the potential of free and publicly available USA National Aeronautics and Space Administration (NASA) resources, which include capacity building activities, satellite data, and global AQ forecasts, to provide cost-effective, and reliable AQ information to health and AQ professionals around the world. We provide illustrative case studies that highlight how global AQ forecasts along with satellite data may be used to characterize AQ on urban to regional scales, including to quantify pollution concentrations, identify pollution sources, and track the long-range transport of pollution. We also provide recommendations to data product developers to facilitate and broaden usage of NASA resources by health and AQ stakeholders.
ABSTRACT
The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space-based and in-situ observations. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide hindcasts and 5-days forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community. Evaluation of GEOS-CF against satellite, ozonesonde and surface observations for years 2018-2019 show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to 0.3, normalized root mean square errors between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO2 and an overprediction of summertime O3 over the Southeast United States. GEOS-CF v1.0 generally overestimates aerosols by 20%-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions. The 5-days forecasts have skill scores comparable to the 1-day hindcast. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.
ABSTRACT
The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) "Indicators" Tiger Team collaboration between NASA-supported scientists and civil society stakeholders aimed to develop satellite-derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge.
ABSTRACT
Using the Community Multiscale Air Quality (CMAQ) model and the Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) tool, we estimate the benefits of anthropogenic emission reductions between 2002 and 2011 in the Eastern United States (US) with respect to surface ozone concentrations and ozone-related health and economic impacts, during a month of extreme heat, July 2011. Based on CMAQ simulations using emissions appropriate for 2002 and 2011, we estimate that emission reductions since 2002 likely prevented 10- 15 ozone exceedance days (using the 2011 maximum 8-hr average ozone standard of 75 ppbv) throughout the Ohio River Valley and 5- 10 ozone exceedance days throughout the Washington, DC - Baltimore, MD metropolitan area during this extremely hot month. CMAQ results were fed into the BenMAP-CE tool to determine the health and health-related economic benefits of anthropogenic emission reductions between 2002 and 2011. We estimate that the concomitant health benefits from the ozone reductions were significant for this anomalous month: 160-800 mortalities (95% confidence interval (CI): 70-1,010) were avoided in July 2011 in the Eastern U.S, saving an estimated $1.3-$6.6 billion (CI: $174 million-$15.5 billion). Additionally, we estimate that emission reductions resulted in 950 (CI: 90-2,350) less hospital admissions from respiratory symptoms, 370 (CI: 180-580) less hospital admissions for pneumonia, 570 (CI: 0-1650) less Emergency Room (ER) visits from asthma symptoms, 922,020 (CI: 469,960-1,370,050) less minor restricted activity days (MRADs), and 430,240 (CI: -280,350-963,190) less symptoms of asthma exacerbation during July 2011.Implications: We estimate the benefits of air pollution emission reductions on surface ozone concentrations and ozone-related impacts on human health and the economy between 2002 and 2011 during an extremely hot month, July 2011, in the eastern United States (US) using the CMAQ and BenMAP-CE models. Results suggest that, during July 2011, emission reductions prevented 10-15 ozone exceedance days in the Ohio River Valley and 5-10 ozone exceedance days in the Mid Atlantic; saved 160-800 lives in the Eastern US, saving $1.3 - $6.5 billion; and resulted in 950 less hospital admissions for respiratory symptoms, 370 less hospital admissions for pneumonia, 570 less Emergency Room visits for asthma symptoms, 922,020 less minor restricted activity days, and 430,240 less symptoms of asthma exacerbation.
Subject(s)
Air Pollutants/analysis , Air Pollution/prevention & control , Emergency Service, Hospital/statistics & numerical data , Extreme Heat , Hospitalization/statistics & numerical data , Ozone/analysis , Respiratory Tract Diseases/epidemiology , Baltimore , Humans , Ohio , Respiratory Tract Diseases/prevention & control , United States/epidemiologyABSTRACT
Air quality data from satellites and low-cost sensor systems, together with output from air quality models, have the potential to augment high-quality, regulatory-grade data in countries with in situ monitoring networks and provide much-needed air quality information in countries without them. Each of these technologies has strengths and limitations that need to be considered when integrating them to develop a robust and diverse global air quality monitoring network. To address these issues, the American Thoracic Society, the U.S. Environmental Protection Agency, the National Aeronautics and Space Administration, and the National Institute of Environmental Health Sciences convened a workshop in May 2017 to bring together global experts from across multiple disciplines and agencies to discuss current and near-term capabilities to monitor global air pollution. The participants focused on four topics: 1) current and near-term capabilities in air pollution monitoring, 2) data assimilation from multiple technology platforms, 3) critical issues for air pollution monitoring in regions without a regulatory-quality stationary monitoring network, and 4) risk communication and health messaging. Recommendations for research and improved use were identified during the workshop, including a recognition that the integration of data across monitoring technology groups is critical to maximizing the effectiveness (e.g., data accuracy, as well as spatial and temporal coverage) of these monitoring technologies. Taken together, these recommendations will advance the development of a global air quality monitoring network that takes advantage of emerging technologies to ensure the availability of free, accessible, and reliable air pollution data and forecasts to health professionals, as well as to all global citizens.
Subject(s)
Air Pollution/analysis , Environmental Monitoring/instrumentation , Environmental Monitoring/methods , Satellite Imagery/instrumentation , Air Pollutants/analysis , Humans , Particulate Matter/analysis , Patient Care , Societies, Medical , United StatesABSTRACT
Fossil-fuel CO2 emissions and their trends in eight U.S. megacities during 2006-2017 are inferred by combining satellite-derived NOX emissions with bottom-up city-specific NOX-to-CO2 emission ratios. A statistical model is fit to a collection NO2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NOX emissions. Decreases in OMI-derived NOX emissions are observed across the eight cities from 2006 to 2017 (-17% in Miami to -58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (-25% in Miami to -49% in Los Angeles), but there are some interannual discrepancies. City-specific NOX-to-CO2 emission ratios, used to calculate inferred CO2, are estimated through annual bottom-up inventories of NOX and CO2 emissions disaggregated to 1â¯×â¯1â¯km2 resolution. Over the study period, NOX-to-CO2 emission ratios have decreased by ~40% nationwide (-24% to -51% for our studied cities), which is attributed to a faster reduction in NOX when compared to CO2 due to policy regulations and fuel type shifts. Combining top-down NOX emissions and bottom-up NOX-to-CO2 emission ratios, annual fossil-fuel CO2 emissions are derived. Inferred OMI-based top-down CO2 emissions trends vary between +7% in Dallas to -31% in Phoenix. For 2017, we report annual fossil-fuel CO2 emissions to be: Los Angeles 113⯱â¯49 Tg/yr; New York City 144⯱â¯62 Tg/yr; and Chicago 55⯱â¯24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013-2016 average CO2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO2 emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments - with better spatial and temporal resolution - will better constrain the NOX-to-CO2 ratio and reduce the uncertainty in our method.
ABSTRACT
Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries.
ABSTRACT
We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618hPa) O3-CO correlations determined by the measurements from Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July-August). The model is driven by three meteorological data sets (fvGCM with sea surface temperature for 1995, GEOS4-DAS for 2005, and MERRA for 2005), allowing us to examine the sensitivity of model O3-CO correlations to input meteorological data. Model simulations of radionuclide tracers (222Rn, 210Pb, and 7Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O3 values are evaluated with climatological ozone profiles from ozonesonde measurements and satellite tropospheric O3 columns. Despite the fact that three simulations show significantly different global and regional distributions of O3 and CO concentrations, all simulations show similar patterns of O3-CO correlations on a global scale. These patterns are consistent with those derived from TES observations, except in the tropical easterly biomass burning outflow regions. Discrepancies in regional O3-CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O3-CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O3 and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NOx emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O3-CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O3-CO correlations than other emissions, but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O3 is consumed and CO generated during the atmospheric oxidation process of isoprene under low NOx conditions. We find that lightning NOx emissions degrade both positive correlations at mid-/high- latitudes and negative correlations in the tropics because ozone production downwind of lightning NOx emissions is not directly related to the emission and transport of CO. Our study concludes that O3-CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.
ABSTRACT
Aircraft observations and ozonesonde profiles collected on July 14 and 27, 2011, during the Maryland month-long DISCOVER-AQ campaign, indicate the presence of stratospheric air just above the planetary boundary layer (PBL). This raises the question of whether summer stratospheric intrusions (SIs) elevate surface ozone levels and to what degree they influence background ozone levels and contribute to ozone production. We used idealized stratospheric air tracers, along with observations, to determine the frequency and extent of SIs in Maryland during July 2011. On 4 of 14 flight days, SIs were detected in layers that the aircraft encountered above the PBL from the coincidence of enhanced ozone, moderate CO, and low moisture. Satellite observations of lower tropospheric humidity confirmed the occurrence of synoptic scale influence of SIs as do simulations with the GEOS-5 Atmospheric General Circulation Model. The evolution of GEOS-5 stratospheric air tracers agree with the timing and location of observed stratospheric influence and indicate that more than 50% of air in SI layers above the PBL had resided in the stratosphere within the previous 14 days. Despite having a strong influence in the lower free troposphere, these events did not significantly affect surface ozone, which remained low on intrusion days. The model indicates similar frequencies of stratospheric influence during all summers from 2009-2013. GEOS-5 results suggest that, over Maryland, the strong inversion capping the summer PBL limits downward mixing of stratospheric air during much of the day, helping to preserve low surface ozone associated with frontal passages that precede SIs.
ABSTRACT
Ozone exposure is associated with negative health impacts, including premature mortality. Observations and modeling studies demonstrate that emissions from one continent influence ozone air quality over other continents. We estimate the premature mortalities avoided from surface ozone decreases obtained via combined 20% reductions of anthropogenic nitrogen oxide, nonmethane volatile organic compound, and carbon monoxide emissions in North America (NA), EastAsia (EA), South Asia (SA), and Europe (EU). We use estimates of ozone responses to these emission changes from several atmospheric chemical transportmodels combined with a health impactfunction. Foreign emission reductions contribute approximately 30%, 30%, 20%, and >50% of the mortalities avoided by reducing precursor emissions in all regions together in NA, EA, SA and EU, respectively. Reducing emissions in NA and EU avoids more mortalities outside the source region than within, owing in part to larger populations in foreign regions. Lowering the global methane abundance by 20% reduces mortality mostin SA,followed by EU, EA, and NA. For some source-receptor pairs, there is greater uncertainty in our estimated avoided mortalities associated with the modeled ozone responses to emission changes than with the health impact function parameters.