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NASA NTRS2010

The Net Climate Impact of Coal-Fired Power Plant Emissions

Coal-fired power plants influence climate via both the emission of long-lived carbon dioxide (CO2) and short-lived ozone and aerosol precursors. Using a climate model, we perform the first study of the spatial and temporal pattern of radiative forcing specifically for coal plant emissions. Without substantial pollution controls, we find that near-term net global mean climate forcing is negative due to the well-known aerosol masking of the effects of CO2. Imposition of pollution controls on sulfur dioxide and nitrogen oxides leads to a rapid realization of the full positive forcing from CO2, however. Long-term global mean forcing from stable (constant) emissions is positive regardless of pollution controls. Emissions from coal-fired power plants until 1970, including roughly 1/3 of total anthropogenic CO2 emissions, likely contributed little net global mean climate forcing during that period though they may have induce weak Northern Hemisphere mid-latitude (NHml) cooling. After that time many areas imposed pollution controls or switched to low sulfur coal. Hence forcing due to emissions from 1970 to 2000 and CO2 emitted previously was strongly positive and contributed to rapid global and especially NHml warming. Most recently, new construction in China and India has increased rapidly with minimal application of pollution controls. Continuation of this trend would add negative near-term global mean climate forcing but severely degrade air quality. Conversely, following the Western and Japanese pattern of imposing air quality pollution controls at a later time could accelerate future warming rates, especially at NHmls. More broadly, our results indicate that due to spatial and temporal inhomogeneities in forcing, climate impacts of multi-pollutant emissions can vary strongly from region to region and can include substantial effects on maximum rate-of-change, neither of which are captured by commonly used global metrics. The method we introduce here to estimate regional temperature responses may provide additional insight.

Shindell, D.↗
NASA NTRS2011

Tests of the Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

Satellite lightning imagers such as the NASA Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS) and the future GOES-R Geostationary Lightning Mapper (GLM) are designed to detect total lightning (ground flashes + cloud flashes). However, there is a desire to discriminate ground flashes from cloud flashes from the vantage point of space since this would enhance the overall information content of the satellite lightning data and likely improve its operational and scientific applications (e.g., in severe weather warning, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters (one of which is the ground flash fraction), a scalar function was minimized by a numerical method. In order to improve this optimization, a Grobner basis solution was introduced to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. In this study, we test the efficacy of the Grobner basis initialization using actual lightning imager measurements and ground flash truth derived from the national lightning network.

Koshak, William↗
NASA NTRS2012

Using Satellite Remote Sensing and Modelling for Insights into N02 Air Pollution and NO2 Emissions

Nitrogen oxides (NO(x)) are key actors in air quality and climate change. Satellite remote sensing of tropospheric NO2 has developed rapidly with enhanced spatial and temporal resolution since initial observations in 1995. We have developed an improved algorithm and retrieved tropospheric NO2 columns from Ozone Monitoring Instrument. Column observations of tropospheric NO2 from the nadir-viewing satellite sensors contain large contributions from the boundary layer due to strong enhancement of NO2 in the boundary layer. We infer ground-level NO2 concentrations from the OMI satellite instrument which demonstrate significant agreement with in-situ surface measurements. We examine how NO2 columns measured by satellite, ground-level NO2 derived from satellite, and NO(x) emissions obtained from bottom-up inventories relate to world's urban population. We perform inverse modeling analysis of NO2 measurements from OMI to estimate "top-down" surface NO(x) emissions, which are used to evaluate and improve "bottom-up" emission inventories. We use NO2 column observations from OMI and the relationship between NO2 columns and NO(x) emissions from a GEOS-Chem model simulation to estimate the annual change in bottom-up NO(x) emissions. The emission updates offer an improved estimate of NO(x) that are critical to our understanding of air quality, acid deposition, and climate change.

Lamsal, L. N.↗
NASA NTRS2012

A New Retrieval Algorithm for OMI NO2: Tropospheric Results and Comparisons with Measurements and Models

Nitrogen oxides (NOx =NO+NO2) are important atmospheric trace constituents that impact tropospheric air pollution chemistry and air quality. We have developed a new NASA algorithm for the retrieval of stratospheric and tropospheric NO2 vertical column densities using measurements from the nadir-viewing Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. The new products rely on an improved approach to stratospheric NO2 column estimation and stratosphere-troposphere separation and a new monthly NO2 climatology based on the NASA Global Modeling Initiative chemistry-transport model. The retrieval does not rely on daily model profiles, minimizing the influence of a priori information. We evaluate the retrieved tropospheric NO2 columns using surface in situ (e.g., AQS/EPA), ground-based (e.g., DOAS), and airborne measurements (e.g., DISCOVER-AQ). The new, improved OMI tropospheric NO2 product is available at high spatial resolution for the years 200S-present. We believe that this product is valuable for the evaluation of chemistry-transport models, examining the spatial and temporal patterns of NOx emissions, constraining top-down NOx inventories, and for the estimation of NOx lifetimes.

Swartz, W. H.↗
NASA NTRS2012

Tropospheric Ozone as a Short-lived Chemical Climate Forcer

Tropospheric ozone is the third most important greenhouse gas according to the most recent IPCC assessment. However, tropospheric ozone is highly variable in both space and time. Ozone that is located in the vicinity of the tropopause has the greatest effect on climate forcing. Nitrogen oxides (NOx) are the most important precursors for ozone In most of the troposphere. Therefore, pollution that is lofted upward in thunderstorm updrafts or NOx produced by lightning leads to efficient ozone production in the upper troposphere, where ozone is most important climatically. Global and regional model estimates of the impact of North American pollution and lightning on ozone radiative forcing will be presented. It will be shown that in the Northern Hemisphere summer, the lightning effect on ozone radiative forcing can dominate over that of pollution, and that the radiative forcing signal from North America extends well into Europe and North Africa. An algorithm for predicting lightning flash rates and estimating lightning NOx emissions is being incorporated into the NASA GEOS-5 Chemistry and Climate Model. Changes in flash rates and emissions over an ENSO cycle and in future climates will be assessed, along with the resulting changes in upper tropospheric ozone. Other research on the production of NOx per lightning flash and its distribution in the vertical based on cloud-resolving modeling and satellite observations will be presented. Distributions of NO2 and O3 over the Middle East from the OMI instrument on NASA's Aura satellite will also be shown.

Pickering, Kenneth E.↗
NASA NTRS2012

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗
NASA NTRS2012

The Role of Lightning in Controlling Interannual Variability of Tropical Tropospheric Ozone and OH and its Implications for Climate

Nitrogen oxides (NO(x) = NO + NO2) produced by lightning make a major contribution to the production of the dominant tropospheric oxidants (OH and ozone). These oxidants control the lifetime of many trace gases including long-lived greenhouse gases, and control the source-receptor relationship of inter-hemispheric pollutant transport. Lightning is affected by meteorological variability, and therefore represents a potentially important tropospheric chemistry-climate feedback. Understanding how interannual variability (IAV) in lightning affects IAV in ozone and OH in the recent past is important if we are to predict how oxidant levels may change in a future warmer climate. However, lightning parameterizations for chemical transport models (CTMs) show low skill in reproducing even climatological distributions of flash rates from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) satellite instruments. We present an optimized regional scaling algorithm for CTMs that enables sufficient sampling of spatiotemporally sparse satellite lightning data from LIS to constrain the spatial, seasonal, and interannual variability of tropical lightning. We construct a monthly time series of lightning flash rates for 1998-2010 and 35degS-35degN, and find a correlation of IAV in total tropical lightning with El Nino. We use the IAV-constraint to drive a 9-year hindcast (1998-2006) of the GEOS-Chem 3D chemical transport model, and find the increased IAV in LNO(x) drives increased IAV in ozone and OH, improving the model fs ability to simulate both. Although lightning contributes more than any other emission source to IAV in ozone, we find ozone more sensitive to meteorology, particularly convective transport. However, we find IAV in OH to be highly sensitive to lightning NO(x), and the constraint improves the ability of the model to capture the temporal behavior of OH anomalies inferred from observations of methyl chloroform and other gases. The sensitivity of OH is explained using photochemical reaction rates which show a "magnification" effect of the initial lightning NO perturbation on OH primary production, HO(x) recycling, and OH loss frequencies. This influence on OH may represent a negative feedback, if lightning increases in a warming world..

Murray, Lee T.↗
NASA NTRS2012

Dirtier Air from a Weaker Monsoon

The level of air pollution in China has much increased in the past decades, causing serious health problems. Among the main pollutants are aerosols, also known as particulate matter: tiny, invisible particles that are suspended in the air. These particles contribute substantially to premature mortality associated with cardiopulmonary diseases and lung cancer1. The increase of the aerosol level in China has been commonly attributed to the fast rise in pollutant emissions from the rapid economic development in the region. However, writing in Geophysical Research Letters, Jianlei Zhu and colleagues2 tell a different side of the story: using a chemical transport model and observation data, they show that the decadal scale weakening of the East Asian summer monsoon has also contributed to the increase of aerosol concentrations in China. The life cycle of atmospheric aerosols starts with its emission or formation in the atmosphere. Some aerosol components such as dust, soot and sea salt are emitted directly as particles to the atmosphere, but others are formed there by way of photochemical reactions. For example, sulphate and nitrate aerosols are produced from their respective precursor gases, sulphur dioxide and nitrogen oxides. Aerosol particles can be transported away from their source locations by winds or vertical motion of the air. Eventually, they are removed from the atmosphere by means of dry deposition and wet scavenging by precipitation. Measurements generally show that aerosol concentrations over Asia are lowest during the summer monsoon season3, because intense rainfall efficiently removes them from the air. The East Asian summer monsoon extends over subtropics and mid-latitudes. Its rainfall tends to concentrate in rain belts that stretch out for many thousands of kilometres and affect China, Korea, Japan and the surrounding area. Observations suggest that the East Asian summer monsoon circulation and precipitation have been in decline since the 1970s4. In particular, a weaker East Asian summer monsoon is characterized by weaker southerly or southwesterly winds, a deficit in rainfall over northern China and larger rainfalls in southern China. By contrast, when the East Asian summer monsoon is strong, the southerly winds and strong rainfalls extend to northern China. The decadal scale decline in the strength of the East Asian summer monsoon since the 1970s would imply an increase in aerosol concentrations in northern China, north of 28deg N, and a decrease in southern China if emissions were kept the same. One obvious reason for this direction of aerosol change is that the reduction of monsoon rainfall in northern China would cause less wet scavenging of aerosols by precipitation. Zhu et al.2 investigated this relationship between aerosol concentrations and the strength of the East Asian summer monsoon and showed that the two parameters have strong negative correlations: the summer aerosol concentrations near the surface over eastern China.

Chin, Mian↗
NASA NTRS2012

Global Air Quality and Climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH4), ozone precursors (O3), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O3 precursor CH4 would slow near-term warming by decreasing both CH4 and tropospheric O3. Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NOx) emissions, which increase tropospheric O3 (warming) but also increase aerosols and decrease CH4 (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH4 volatile organic compounds (NMVOC) warm by increasing both O3 and CH4. Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O3 and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O3 and SOA.

ozone↗
NASA NTRS2014

NOx Emissions Performance and Correlation Equations for a Multipoint LDI Injector

Lean Direct Injection (LDI) is a combustor concept that reduces nitrogen oxides (NOx) emissions. This paper looks at a 3-zone multipoint LDI concept developed by Parker Hannifin Corporation. The concept was tested in a flame-tube test facility at NASA Glenn Research Center. Due to test facility limitations, such as inlet air temperature and pressure, the flame-tube test was not able to cover the full set of engine operation conditions. Three NOx correlation equations were developed based on assessing NOx emissions dependencies on inlet air pressure (P3), inlet air temperature (T3), and fuel air equivalence ratio (Ф) to estimate the NOx emissions at the unreachable high engine power conditions. As the results, the NOx emissions are found to be a strong function of combustion inlet air temperature and fuel air equivalence ratio but a weaker function of inlet air pressure. With these three equations, the NOx emissions performance of this injector concept is calculated as a 66 percent reduction relative to the ICAO CAEP-6 standard using a 55:1 pressure-ratio engine cycle. Uncertainty in the NOx emissions estimation increases as the extrapolation range departs from the experimental conditions. Since maximum inlet air pressure tested was less than 50 percent of the full power engine inlet air pressure, a future experiment at higher inlet air pressure conditions is needed to confirm the NOx emissions dependency on inlet air pressure.

He, Zhuohui J.↗
NASA NTRS2013

Impact of NO2 Profile Shape in OMI Tropospheric NO2 Retrievals

Nitrogen oxides (NOx NO + NO2) are key actors in air quality and climate change. Tropospheric NO2 columns from the nadir-viewing satellite sensors have been widely used to understand sources and chemistry of NOx. We have implemented several improvements to the operational algorithm developed at NASA GSFC and retrieved tropospheric NO2 columns. We present tropospheric NO2 validation studies of the new OMI Standard Product version 2.1 using ground-based and in-situ aircraft measurements. We show how vertical profile of scattering weight and a-priori NO2 profile shapes, which are taken from chemistry-transport models, affect air mass factor (AMF) and therefore tropospheric NO2 retrievals. Users can take advantage of scattering weights information that is made available in the operational NO2 product. Improved tropospheric NO2 data retrieved using thoroughly evaluated high spatial resolution NO2 profiles are helpful to test models.

OMI↗
NASA NTRS2013

Global and Regional Temperature-change Potentials for Near-term Climate Forcers

The emissions of reactive gases and aerosols can affect climate through the burdens of ozone, methane and aerosols, having both cooling and warming effects. These species are generally referred to near-term climate forcers (NTCFs) or short-lived climate pollutants (SLCPs), because of their short atmospheric residence time. The mitigation of these would be attractive for both air quality and climate on a 30-year timescale, provided it is not at the expense of CO2 mitigation. In this study we examine the climate effects of the emissions of NTCFs from 4 continental regions (East Asia, Europe, North America and South Asia) using results from the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model simulations. We address 3 aerosol species (sulphate, particulate organic matter and black carbon - BC) and 4 ozone precursors (methane, reactive nitrogen oxides - NOx, volatile organic compounds VOC, and carbon monoxide - CO). For the aerosols the global warming potentials (GWPs) and global temperature change potentials (GTPs) are simply time-dependent scaling of the equilibrium radiative forcing, with the GTPs decreasing more rapidly with time than the GWPs. While the aerosol climate metrics have only a modest dependence on emission region, emissions of NOx and VOCs from South Asia have GWPs and GTPs of higher magnitude than from the other northern hemisphere regions. On regional basis, the northern mid-latitude temperature response to northern mid-latitude emissions is approximately twice as large as the global average response for aerosol emission, and about 20-30% larger than the global average for methane, VOC and CO emissions. We also found that temperatures in the Arctic latitudes appear to be particularly sensitive to black carbon emissions from South Asia.

climate forcer↗
NASA NTRS2014

Variation of a Lightning NOx Indicator for National Climate Assessment

During the past couple of years, an analysis tool was developed by the NASA Marshall Space Flight Center (MSFC) for the National Climate Assessment (NCA) program. The tool monitors and examines changes in lightning characteristics over the conterminous US (CONUS) on a continual basis. In this study, we have expanded the capability of the tool so that it can compute a new climate assessment variable that is called the Lightning NOx Indicator (LNI). Nitrogen oxides (NOx = NO + NO2) are known to indirectly influence our climate, and lightning NOx is the most important source of NOx in the upper troposphere (particularly in the tropics). The LNI is derived using Lightning Imaging Sensor (LIS) data and is computed by summing up the product of flash area x flash brightness over all flashes that occur in a particular region and period. Therefore, it is suggested that the LNI is a proxy to lightning NOx production. Specifically, larger flash areas are consistent with longer channel length and/or more energetic channels, and hence more NOx production. Brighter flashes are consistent with more energetic channels, and hence more NOx production. The location of the flash within the thundercloud and the optical scattering characteristics of the thundercloud are of course complicating factors. We analyze LIS data for the years 2003-2013 and provide geographical plots of the time-evolution of the LNI in order to determine if there are any significant changes or trends between like seasons, or from year to year.

Koshak, William J.↗
NASA NTRS2014

Variation of a Lightning NOx Indicator for National Climate Assessment

In support of the National Climate Assessment (NCA) program, satellite Lightning Imaging Sensor (LIS) data is used to estimate lightning nitrogen oxides (LNOx) production over the southern portion of the conterminous US. The total energy of each flash is estimated by analyzing the LIS optical event data associated with each flash (i.e., event radiance, event footprint area, and derivable event range). The LIS detects an extremely small fraction of the total flash energy; this fraction is assumed to be constant apart from the variability associated with the flash optical energy detected across the narrow (0.909 nm) LIS band. The estimate of total energy from each flash is converted to moles of LNOx production by assuming a chemical yield of 10(17) molecules Joule(-1). The LIS-inferred variable LNOx production from each flash is summed to obtain total LNOx production, and then appropriately enhanced to account for LIS detection efficiency and LIS view time. Annual geographical plots and time series of LNOx production are provided for a 16 year period (1998-2013).

Koshak, W. J.↗
NASA NTRS2014

Variation of a Lightning NOx Indicator for National Climate Assessment

Lightning nitrogen oxides (LNOx) indirectly influences our climate since these molecules are important in controlling the concentration of ozone (O3) and hydroxyl radicals (OH) in the atmosphere [Huntrieser et al., 1998]. In support of the National Climate Assessment (NCA) program, satellite Lightning Imaging Sensor (LIS; Christian et al. [1999]; Cecil et al. [2014]) data is used to estimate LNOx production over the southern portion of the conterminous US for the 16 year period 1998-2013.

Koshak, William↗
NASA NTRS2013

The Observed Response of Ozone Monitoring Instrument (OMI) NO2 Columns to NOx Emission Controls on Power Plants in the United States: 2005-2011

We show that Aura Ozone Monitoring Instrument (OMI) nitrogen dioxide (NO2) tropospheric column data may be used to assess changes of the emissions of nitrogen oxides (NOx) from power plants in the United States, though careful interpretation of the data is necessary. There is a clear response for OMI NO2 data to NOx emission reductions from power plants associated with the implementation of mandated emission control devices (ECDs) over the OMI record (2005e2011). This response is scalar for all intents and purposes, whether the reduction is rapid or incremental over several years. However, it is variable among the power plants, even for those with the greatest absolute decrease in emissions. We document the primary causes of this variability, presenting case examples for specific power plants.

remote sensing↗
NASA NTRS2014

Surface Ozone Variability and Trends over the South African Highveld from 1990 to 2007

Surface ozone is a secondary air pollutant formed from reactions between nitrogen oxides (NOx = NO + NO2) and volatile organic compounds in the presence of sunlight. In this work we examine effects of the climate pattern known as the El Niño-Southern Oscillation (ENSO) and NOx variability on surface ozone from 1990 to 2007 over the South African Highveld, a heavily populated region in South Africa with numerous industrial facilities. Over summer and autumn (December-May) on the Highveld, El Niño, as signified by positive sea surface temperature (SST) anomalies over the central Pacific Ocean, is typically associated with drier and warmer than normal conditions favoring ozone formation. Conversely, La Niña, or negative SST anomalies over the central Pacific Ocean, is typically associated with cloudier and above normal rainfall conditions, hindering ozone production. We use a generalized regression model to identify any linear dependence that the Highveld ozone, measured at five air quality monitoring stations, may have on ENSO and NOx. Our results indicate that four out of the five stations exhibit a statistically significant sensitivity to ENSO at some point over the December-May period where El Niño amplifies ozone formation and La Niña reduces ozone formation. Three out of the five stations reveal statistically significant sensitivity to NOx variability, primarily in winter and spring. Accounting for ENSO and NOx effects throughout the study period of 18 years, two stations exhibit statistically significant negative ozone trends in spring, one station displays a statistically significant positive trend in August, and two stations show no statistically significant change in surface ozone.

NOx↗