L. N. Lamsal

Universities Space Research Association, Houston, Texas, United States

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Publications (59)141.96 Total impact

  • Z. Lu · D. G. Streets · B. de Foy · L. N. Lamsal · B. N. Duncan · J. Xing
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    ABSTRACT: Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially-modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate three-year moving-average emissions of summertime NOx from 35 US urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following the conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with wind speeds greater than 3–5 m s−1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s−1) are qualitatively better correlated with the surface NOx source strength in comparison to all-wind OMI maps; and therefore we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous, EMG-obtained, effective NO2 lifetimes (~3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h−1 produce statistically significant weak-wind signals in three-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49%, consistent with reductions of 43, 47, 49, and 44% in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., −6.8 to −9.3% yr−1) before 2010 and slower (i.e., −3.4 to −4.9% yr−1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements; and high correlations are found for all urban areas (median R = 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.
    Atmospheric Chemistry and Physics 05/2015; 15(10):14961-15003. DOI:10.5194/acpd-15-14961-2015 · 4.88 Impact Factor
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    ABSTRACT: Nitrogen dioxide retrievals from the Aura/Ozone Monitoring Instrument (OMI) have been used extensively over the past decade, particularly in the study of tropospheric air quality. Recent comparisons of OMI NO2 with independent data sets and models suggested that the OMI values of slant column density (SCD) and stratospheric vertical column density (VCD) in both the NASA OMNO2 and Royal Netherlands Meteorological Institute DOMINO products are too large, by around 10–40%. We describe a substantially revised spectral fitting algorithm, optimized for the OMI visible light spectrometer channel. The most important changes comprise a flexible adjustment of the instrumental wavelength shifts combined with iterative removal of the ring spectral features; the multistep removal of instrumental noise; iterative, sequential estimates of SCDs of the trace gases in the 402–465 nm range. These changes reduce OMI SCD(NO2) by 10–35%, bringing them much closer to SCDs retrieved from independent measurements and models. The revised SCDs, submitted to the stratosphere-troposphere separation algorithm, give tropospheric VCDs ∼10–15% smaller in polluted regions, and up to ∼30% smaller in unpolluted areas. Although the revised algorithm has been optimized specifically for the OMI NO2 retrieval, our approach could be more broadly applicable.
    Journal of Geophysical Research Atmospheres 05/2015; DOI:10.1002/2014JD022913 · 3.44 Impact Factor
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    ABSTRACT: Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O-3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O-3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O-3 concentrations by up to 80 ppb and improves O-3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NOx emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCDs) is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The region-based DKF inversion suggests increasing NOx emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO2 and O-3, while the sector-based DKF inversion tends to scale down area and nonroad NOx emissions by 50 %, leading to a 2-5 ppb decrease in ground 8 h O-3 predictions. Model performance in simulating ground NO2 and O-3 are improved using sector-based inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05, increases the model correlation with ground measurement in O-3 simulations, and makes O-3 more sensitive to NOx emissions in the O-3 non-attainment areas.
    Atmospheric Chemistry and Physics 02/2015; 15(4):1601-1619. DOI:10.5194/acp-15-1601-2015 · 5.51 Impact Factor
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    ABSTRACT: National emission inventories (NEIs) take years to assemble, but they can become outdated quickly, especially for time-sensitive applications such as air quality forecasting. This study compares multi-year NOx trends derived from satellite and ground observations and uses these data to evaluate the updates of NOx emission data by the US National Air Quality Forecast Capability (NAQFC) for next-day ozone prediction during the 2008 Global Economic Recession. Over the eight large US cities examined here, both the Ozone Monitoring Instrument (OMI) and the Air Quality System (AQS) detect substantial downward trends from 2005 to 2012, with a seven-year total of -35% according to OMI and -38% according to AQS. The NOx emission projection adopted by NAQFC tends to be in the right direction, but at a slower reduction rate (-25% from 2005 to 2012), due likely to the unaccounted effects of the 2008 economic recession. Both OMI and AQS datasets display distinct emission reduction rates before, during, and after the 2008 global recession in some cities, but the detailed changing rates are not consistent across the OMI and AQS data. Our findings demonstrate the feasibility of using space and ground observations to evaluate major updates of emission inventories objectively. The combination of satellite, ground observations, and in-situ measurements (such as emission monitoring in power plants) is likely to provide more reliable estimates of NOx emission and its trend, which is an issue of increasing importance as many urban areas in the US are transitioning to NOx-sensitive chemical regimes by continuous emission reductions.
    Atmospheric Environment 01/2015; 109. DOI:10.1016/j.atmosenv.2015.01.035 · 3.28 Impact Factor
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    ABSTRACT: The Airborne Compact Atmospheric Mapper (ACAM), an ultraviolet/visible/near-infrared spectrometer, has been flown on board the NASA UC-12 aircraft during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaigns to provide remote sensing observations of tropospheric and boundary-layer pollutants from its radiance measurements. To assure the tracegas retrieval from ACAM measurements we perform detailed characterization and verification of ACAM slit functions. The wavelengths and slit functions of ACAM measurements are characterized for the air-quality channel (similar to 304-500 nm) through cross-correlation with a high-resolution solar irradiance reference spectrum after necessarily accounting for atmospheric gas absorption and the ring effect in the calibration process. The derived slit functions, assuming a hybrid combination of asymmetric Gaussian and top-hat slit functions, agree very well with the laboratory-measured slit functions. Comparisons of trace-gas retrievals between using derived and measured slit functions demonstrate that the cross-correlation technique can be reliably used to characterize slit functions for trace-gas retrievals.
    Atmospheric Measurement Techniques 11/2014; 7(2):11415-11437. DOI:10.5194/amtd-7-11415-2014 · 3.21 Impact Factor
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    ABSTRACT: We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.
    Atmospheric Chemistry and Physics 11/2014; 14(21):11587-11609. DOI:10.5194/acp-14-11587-2014 · 5.51 Impact Factor
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    ABSTRACT: A method is developed to estimate global NO2 and SO2 dry deposition fluxes at high spatial resolution (0.1° × 0.1°) using satellite measurements from the Ozone Monitoring Instrument (OMI) on the Aura satellite, in combination with simulations from the GEOS-Chem global chemical transport model. These global maps for 2005–2007 provide a dataset for use in examining global and regional budgets of deposition. In order to properly assess SO2 on a global scale, a method is developed to account for the geospatial character of background offsets in retrieved satellite columns. Globally, annual dry deposition to land estimated from OMI as NO2 contributes 1.5 ± 0.5 Tg of nitrogen and as SO2 contributes 13.7 ± 4.0 Tg of sulfur. Differences between OMI-inferred NO2 dry deposition fluxes and those of other models and observations vary from excellent agreement to an order of magnitude difference, with OMI typically on the low end of estimates. SO2 dry deposition fluxes compare well with in situ CASTNET-network-inferred flux over North America (slope = 0.98, r = 0.71). The most significant NO2 dry deposition flux to land per area occurs in the Pearl River Delta, China at 13.9 kg N ha−1 yr−1, while SO2 dry deposition has a global maximum rate of 72.0 kg S ha−1 yr−1 to the east of Jinan in China's Shandong province. Dry deposition fluxes are explored in several urban areas, where NO2 contributes on average 9–36% and as much as 85% of total NOy dry deposition.
    10/2014; 28(10). DOI:10.1002/2014GB004805
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    ABSTRACT: To investigate the ability of column (or partial column) information to represent surface air quality, results of linear regression analyses between surface mixing ratio data and column abundances for O3 and NO2 are presented for the July 2011 Maryland deployment of the DISCOVER-AQ mission. Data collected by the P-3B aircraft, ground-based Pandora spectrometers, Aura/OMI satellite instrument, and simulations for July 2011 from the CMAQ air quality model during this deployment provide a large and varied data set, allowing this problem to be approached from multiple perspectives. O3 columns typically exhibited a statistically significant and high degree of correlation with surface data (R2 > 0.64) in the P-3B data set, a moderate degree of correlation (0.16 < R2 < 0.64) in the CMAQ data set, and a low degree of correlation (R2 < 0.16) in the Pandora and OMI data sets. NO2 columns typically exhibited a low to moderate degree of correlation with surface data in each data set. The results of linear regression analyses for O3 exhibited smaller errors relative to the observations than NO2 regressions. These results suggest that O3 partial column observations from future satellite instruments with sufficient sensitivity to the lower troposphere can be meaningful for surface air quality analysis.
    Atmospheric Environment 08/2014; 92:429–441. DOI:10.1016/j.atmosenv.2014.04.041 · 3.28 Impact Factor
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    ABSTRACT: Particulate organic matter is of interest for air quality and climate research, but the relationship between ambient organic mass (OM) and organic carbon (OC) remains ambiguous both in measurements and in modeling. We present a simple method to derive an estimate of the spatially and seasonally resolved global, lower tropospheric, ratio between OM and OC. We assume ambient NO2 concentrations as a surrogate for fresh emission which mostly determines the continental scale OM/OC ratio. For this, we first develop a parameterization for the OM/OC ratio using the primary organic aerosol (POA) fraction of total OM estimated globally from Aerosol Mass Spectrometer (AMS) measurements, and evaluate it with high mass resolution AMS data. Second, we explore the ability of ground-level NO2 concentrations derived from the OMI satellite sensor to serve as a proxy for fresh emissions that have a high POA fraction, and apply NO2 data to derive ambient POA fraction. The combination of these two methods yields an estimate of OM/OC from NO2 measurements. Although this method has inherent deficiencies over biomass burning, free-tropospheric, and marine environments, elsewhere it offers more information than the currently used global-mean OM/OC ratios. The OMI-derived global OM/OC ratio ranges from 1.3 to 2.1 (μg/μgC), with distinct spatial variation between urban and rural regions. The seasonal OM/OC ratio has a summer maximum and a winter minimum over regions dominated by combustion emissions. This dataset serves as a tool for interpreting organic carbon measurements, and for evaluating modeling of atmospheric organics. We also develop an additional parameterization for models to estimate the ratio of primary OM to OC from simulated NOx concentrations.
    Atmospheric Environment 04/2014; 87:34–40. DOI:10.1016/j.atmosenv.2013.11.065 · 3.28 Impact Factor
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    ABSTRACT: Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of >0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 03/2014; 14(7). DOI:10.5194/acp-14-3637-2014 · 5.30 Impact Factor
  • D.G. Streets · B. De Foy · B.N. Duncan · L.N. Lamsal · C. Li · Z. Lu
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    ABSTRACT: How accurately can the emissions from a coal-fired power plant be measured from space? Might it one day be possible for a satellite to determine whether a plant is in compliance with emission regulations? This article reviews the current capability of space-borne instruments to detect and quantify power plant emissions and comments on the possibility of enhanced capability in the next five to ten years.
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    W. Tang · D. S. Cohan · L. N. Lamsal · X. Xiao · W. Zhou
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    ABSTRACT: Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 11/2013; 13(21):11005-11018. DOI:10.5194/acp-13-11005-2013 · 5.30 Impact Factor
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    Atmospheric Chemistry and Physics 08/2013; 13(8):21609-21664. DOI:10.5194/acpd-13-21609-2013 · 4.88 Impact Factor
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    ABSTRACT: Concern is growing about the effects of urbanization on air pollution and health. Nitrogen dioxide (NO2) released primarily from combustion processes such as traffic is a short-lived atmospheric pollutant that serves as an air quality indicator, and is itself a health concern. We derive a global distribution of ground-level NO2 concentrations from tropospheric NO2 columns retrieved from the OMI satellite instrument. Local scaling factors from a three-dimensional chemistry-transport model (GEOS-Chem) are used to relate the OMI NO2 columns to ground-level concentrations. The OMI-derived surface NO2 data are significantly correlated (r=0.69) with in situ surface measurements. We examine how the OMI-derived ground-level NO2 concentrations, OMI NO2 columns, and bottom-up NOx emission inventories relate to urban population. Emission hot spots such as power plants are excluded to focus on urban relationships. The correlation of surface NO2 with population is significant for the three countries and one continent examined here: United States (r=0.71), Europe (r=0.67), China (r=0.69) and India (r=0.59). Urban NO2 pollution, like other urban properties, is a power law scaling function of the population size: NO2 concentration increases proportional to population raised to an exponent. The value of the exponent varies by region from 0.36 for India to 0.66 for China reflecting regional differences in industrial development and per capita emissions. It has been generally established that energy efficiency increases and therefore per capita NOx emissions decrease with urban population; here we show how outdoor ambient NO2 concentrations depend upon urban population in different global regions.
    Environmental Science & Technology 06/2013; 47(14). DOI:10.1021/es400744g · 5.48 Impact Factor
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    ABSTRACT: We describe a new algorithm for the retrieval of nitrogen dioxide (NO2) vertical columns from nadir-viewing satellite instruments. This algorithm (SP2) is the basis for the Version 2.1 OMI NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. The approach estimates the stratospheric NO2 directly from satellite data without using stratospheric chemical transport models or assuming any global zonal wave pattern. Tropospheric NO2 columns are retrieved using air mass factors derived from high-resolution radiative transfer calculations and a monthly climatology of NO2 profile shapes. We also present details of how uncertainties in the retrieved columns are estimated. The sensitivity of the retrieval to assumptions made in the stratosphere-troposphere separation is discussed and shown to be small, in an absolute sense, for most regions. We compare daily and monthly mean global OMI NO2 retrievals using the SP2 algorithm with those of the original Version 1 Standard Product (SP1) and the Dutch DOMINO product. The SP2 retrievals yield significantly smaller summertime tropospheric columns than SP1 and are relatively free of modeling artifacts and negative tropospheric NO2 values. In a re-analysis of an INTEX-B validation study, we show that SP2 largely eliminates a ∼20% discrepancy that existed between OMI and independent in situ springtime NO2 SP1 measurements.
    Atmospheric Measurement Techniques 02/2013; 6(1):1361-1407. DOI:10.5194/amtd-6-1361-2013 · 3.21 Impact Factor
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    Environmental Science & Technology 08/2012; 46(16):8523-4. DOI:10.1021/es302672p · 5.48 Impact Factor
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    ABSTRACT: Comparative studies between results from the CARIBIC airborne DOAS instrument on board of CARIBIC and satellite observations are presented. CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container, www.caribic.de) observes physical and chemical processes in the earth’s atmosphere using a fully automated measurement container aboard a Lufthansa Airbus 340-600. A special inlet system is mounted underneath the aeroplane with probes for trace gases, water vapour and aerosol particles. It also includes three telescopes of a DOAS (Differential Optical Absorption Spectroscopy) system for remote sensing. Enhanced sulphur dioxide (SO2) column densities were observed by CARIBIC DOAS after the eruptions of Kasatochi (Alaska, USA) and Eyjafjallajökull (Iceland) as well as downwind of the nickel smelter in Norilsk (Siberia). For all cases detailed studies were performed and the data were used for comparisons with products from several satellite instruments. To reduce the additional uncertainty caused by trajectory calculation, the satellite with the shortest time difference relative to the CARIBIC observation was validated. For the Kasatochi plume wind speeds were relevant for the comparison in view of a discrepancy in the timing of aeroplane and satellite overpass. In the case of a dedicated flight designed to intercept parts of the Eyjafjallajökull plume, also Bromine Monoxide (BrO) was detected. Due to high noise in both CARIBIC and GOME-2 (Global Ozone Monitoring Experiment) data a qualitative comparison of the BrO vertical column densities was not performed. For Norilsk, where NO2 enhancements were also detected, wind data were used to estimate the SO2 flux. The flux estimate based on CARIBIC data was in a good agreement with independent data including OMI (Ozone Monitoring Instrument) based results. In general, good agreement between CARIBIC and the satellite data was obtained.
    ATMOS 2012 – Advances in Atmospheric Science and Applications; 06/2012
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    S. W. Wang · Q. Zhang · D. G. Streets · K. B. He · R. V. Martin · L. N. Lamsal · D. Chen · Y. Lei · Z. Lu
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    ABSTRACT: Using OMI (Ozone Monitoring Instrument) tropospheric NO2 columns and a nested-grid 3-D global chemical transport model (GEOS-Chem), we investigated the growth in NOx emissions from coal-fired power plants and their contributions to the growth in NO2 columns in 2005-2007 in China. We first developed a unit-based power plant NOx emission inventory for 2005-2007 to support this investigation. The total capacities of coal-fired power generation have increased by 48.8% in 2005-2007, with 92.2% of the total capacity additions coming from generator units with size ≥300 MW. The annual NOx emissions from coal-fired power plants were estimated to be 8.11 Tg NO2 for 2005 and 9.58 Tg NO2 for 2007, respectively. The modeled summer average tropospheric NO2 columns were highly correlated (R2 = 0.79-0.82) with OMI measurements over grids dominated by power plant emissions, with only 7-14% low bias, lending support to the high accuracy of the unit-based power plant NOx emission inventory. The ratios of OMI-derived annual and summer average tropospheric NO2 columns between 2007 and 2005 indicated that most of the grids with significant NO2 increases were related to power plant construction activities. OMI had the capability to trace the changes of NOx emissions from individual large power plants in cases where there is less interference from other NOx sources. Scenario runs from GEOS-Chem model suggested that the new power plants contributed 18.5% and 10% to the annual average NO2 columns in 2007 in Inner Mongolia and North China, respectively. The massive new power plant NOx emissions significantly changed the local NO2 profiles, especially in less polluted areas. A sensitivity study found that changes of NO2 shape factors due to including new power plant emissions increased the summer average OMI tropospheric NO2 columns by 3.8-17.2% for six selected locations, indicating that the updated emission information could help to improve the satellite retrievals.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 05/2012; 12(10):4429-4447. DOI:10.5194/acp-12-4429-2012 · 5.30 Impact Factor
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    ABSTRACT: Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments. National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions. Calibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 μg/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls. We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health.
    Environmental Health 04/2012; 11(1):22. DOI:10.1186/1476-069X-11-22 · 2.71 Impact Factor

Publication Stats

648 Citations
141.96 Total Impact Points

Institutions

  • 2012–2015
    • Universities Space Research Association
      Houston, Texas, United States
    • NASA
      • Earth Sciences Division
      Вашингтон, West Virginia, United States
  • 2007–2011
    • Dalhousie University
      • Department of Physics and Atmospheric Science
      Halifax, Nova Scotia, Canada
  • 1620–2005
    • Universität Bremen
      • Institut für Umweltphysik (IUP)
      Bremen, Bremen, Germany