Global deposition of total reactive nitrogen oxides from 1996 to 2014 constrained with satellite observations of NO2 columns

Reactive nitrogen oxides (NOy) are a major constituent of the nitrogen deposited from the atmosphere, but observational constraints on their deposition are limited by poor or nonexistent measurement coverage in many parts of the world. Here we apply NO2 observations from multiple satellite instruments (GOME, SCIAMACHY, and GOME-2) to constrain the global deposition of NOy over the last 2 decades. We accomplish this by producing top-down estimates of NOx emissions from inverse modeling of satellite NO2 columns over 1996–2014, and including these emissions in the GEOS-Chem chemical transport model to simulate chemistry, transport, and deposition of NOy. Our estimates of long-term mean wet nitrate (NO3−) deposition are highly consistent with available measurements in North America, Europe, and East Asia combined (r = 0.83, normalized mean bias  = −7%, N = 136). Likewise, our calculated trends in wet NO3− deposition are largely consistent with the measurements, with 129 of the 136 gridded model–data pairs sharing overlapping 95% confidence intervals. We find that global mean NOy deposition over 1996–2014 is 56.0TgNyr−1, with a minimum in 2006 of 50.5TgN and a maximum in 2012 of 60.8TgN. Regional trends are large, with opposing signs in different parts of the world. Over 1996 to 2014, NOy deposition decreased by up to 60% in eastern North America, doubled in regions of East Asia, and declined by 20% in parts of western Europe. About 40% of the global NOy deposition occurs over oceans, with deposition to the North Atlantic Ocean declining and deposition to the northwestern Pacific Ocean increasing. Using the residual between NOx emissions and NOy deposition over specific land regions, we investigate how NOx export via atmospheric transport has changed over the last 2 decades. Net export from the continental United States decreased substantially, from 2.9TgNyr−1 in 1996 to 1.5TgNyr−1 in 2014. Export from China more than tripled between 1996 and 2011 (from 1.0 to 3.5TgNyr−1), before a striking decline to 2.5TgNyr−1 by 2014. We find that declines in NOx export from some western European countries have counteracted increases in emissions from neighboring countries to the east. A sensitivity study indicates that simulated NOy deposition is robust to uncertainties in NH3 emissions with a few exceptions. Our novel long-term study provides timely context on the rapid redistribution of atmospheric nitrogen transport and subsequent deposition to ecosystems around the world.This work was supported by NSERC and Environment and Climate Change Canada. We acknowledge the free use of tropospheric NO2 column data from the GOME, SCIAMACHY, and GOME-2 sensors from www.temis.nl. We further acknowledge the NADP, CAPMoN, EMEP, and EANET regional monitoring networks as well as the World Data Centre for Precipitation Chemistry for access to wet deposition data. (NSERC; Environment and Climate Change Canada)https://www.atmos-chem-phys.net/17/10071/2017/acp-17-10071-2017.pdfhttps://www.atmos-chem-phys.net/17/10071/2017/acp-17-10071-2017.pdfhttps://www.atmos-chem-phys.net/17/10071/2017/acp-17-10071-2017.pdfPublished versionPublished versio

Global deposition of total reactive nitrogen oxides from 1996 to 2014 constrained with satellite observations of NO2 columns

Reactive nitrogen oxides (NOy) are a major constituent of the nitrogen deposited from the atmosphere, but observational constraints on their deposition are limited by poor or nonexistent measurement coverage in many parts of the world. Here we apply NO2 observations from multiple satellite instruments (GOME, SCIAMACHY, and GOME-2) to constrain the global deposition of NOy over the last two decades. We accomplish this by producing top-down estimates of NOx emissions from inverse modeling of satellite NO2 columns over 1996–2014, and including these emissions in the GEOS-Chem chemical transport model to simulate chemistry, transport, and deposition of NOy. Our estimates of long-term mean wet nitrate (NO3−) deposition are highly consistent with available measurements in North America, Europe, and East Asia combined (r = 0.83, normalized mean bias = −7 %, N = 136). Likewise, our calculated trends in wet NO3− deposition are largely consistent with the measurements, with 129 of the 136 gridded model-data pairs sharing overlapping 95 % confidence intervals. We find that global mean NOy deposition over 1996–2014 is 56.0 Tg N yr−1, with a minimum in 2006 of 50.5 Tg N and a maximum in 2012 of 60.8 Tg N. Regional trends are large, with opposing signs in different parts of the world. Over 1996 to 2014, NOy deposition decreased by up to 60 % in eastern North America, doubled in regions of East Asia, and declined by 20 % in parts of Western Europe. About 40 % of the global NOy deposition occurs over oceans, with deposition to the North Atlantic Ocean declining and deposition to the northwestern Pacific Ocean increasing. Using the residual between NOx emissions and NOy deposition over specific land regions, we investigate how NOx export via atmospheric transport has changed over the last two decades. Net export from the continental United States decreased substantially, from 2.9 Tg N yr−1 in 1996 to 1.5 Tg N yr−1 in 2014. On the other hand, export from China more than tripled between 1996 and 2011 (from 1.0 Tg N yr−1 to 3.5 Tg N yr−1), before a striking decline to 2.5 Tg N yr−1 by 2014. We find that declines in NOx export from some Western European countries have counteracted increases in emissions from neighbouring countries to the east. A sensitivity study indicates that simulated NOy deposition is robust to uncertainties in NH3 emissions with a few exceptions. Our novel long-term study provides timely context on the rapid redistribution of atmospheric nitrogen transport and subsequent deposition to ecosystems around the world.https://www.atmos-chem-phys-discuss.net/acp-2016-1100/acp-2016-1100.pdfhttps://www.atmos-chem-phys-discuss.net/acp-2016-1100/acp-2016-1100.pdfhttps://www.atmos-chem-phys-discuss.net/acp-2016-1100/acp-2016-1100.pdfPublished versionPublished versio

Stratosphere-troposphere separation of nitrogen dioxide columns from the TEMPO geostationary satellite instrument

Separating the stratospheric and tropospheric contributions in satellite retrievals of atmospheric NO2 column abundance is a crucial step in the interpretation and application of the satellite observations. A variety of stratosphere–troposphere separation algorithms have been developed for sun-synchronous instruments in low Earth orbit (LEO) that benefit from global coverage, including broad clean regions with negligible tropospheric NO2 compared to stratospheric NO2. These global sun-synchronous algorithms need to be evaluated and refined for forthcoming geostationary instruments focused on continental regions, which lack this global context and require hourly estimates of the stratospheric column. Here we develop and assess a spatial filtering algorithm for the upcoming TEMPO geostationary instrument that will target North America. Developments include using independent satellite observations to identify likely locations of tropospheric enhancements, using independent LEO observations for spatial context, consideration of diurnally varying partial fields of regard, and a filter based on stratospheric to tropospheric air mass factor ratios. We test the algorithm with LEO observations from the OMI instrument with an afternoon overpass, and from the GOME-2 instrument with a morning overpass. We compare our TEMPO field of regard algorithm against an identical global algorithm to investigate the penalty resulting from the limited spatial coverage in geostationary orbit, and find excellent agreement in the estimated mean daily tropospheric NO2 column densities (R2=0.999, slope=1.009 for July and R2=0.998, slope=0.999 for January). The algorithm performs well even when only small parts of the continent are observed by TEMPO. The algorithm is challenged the most by east coast morning retrievals in the wintertime (e.g., R2=0.995, slope=1.038 at 14:00 UTC). We find independent global LEO observations (corrected for time of day) provide important context near the field-of-regard edges. We also test the performance of the TEMPO algorithm without these supporting global observations. Most of the continent is unaffected (R2=0.924 and slope=0.973 for July and R2=0.996 and slope=1.008 for January), with 90 % of the pixels having differences of less than ±0.2×1015 molecules cm−2 between the TEMPO tropospheric NO2 column density and the global algorithm. For near-real-time retrieval, even a climatological estimate of the stratospheric NO2 surrounding the field of regard would improve this agreement. In general, the additional penalty of a limited field of regard from TEMPO introduces no more error than normally expected in most global stratosphere–troposphere separation algorithms. Overall, we conclude that hourly near-real-time stratosphere–troposphere separation for the retrieval of NO2 tropospheric column densities by the TEMPO geostationary instrument is both feasible and robust, regardless of the diurnally varying limited field of regard.The authors are grateful to Kelly Chance, Xiong Liu, John Houck, Peter Zoogman, and other members of the TEMPO trace gas retrieval team for their input in preparation of this paper. Work at Dalhousie University was supported by Environment and Climate Change Canada. The authors also gratefully acknowledge the free use of TEMIS NO2 data from the GOME-2 sensor provided by http://www.temis.nl, last access: 12 November 2018, and the NASA Standard Product NO2 data from OMI provided by https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary, last access: 9 November 2018. (Environment and Climate Change Canada)https://www.atmos-meas-tech.net/11/6271/2018/Published versio

Seasonal and interannual variability of North American isoprene emissions as determined by formaldehyde column measurements from space

Formaldehyde (HCHO) columns measured from space by solar UV backscatter allow mapping of reactive hydrocarbon emissions. The principal contributor to these emissions during the growing season is the biogenic hydrocarbon isoprene, which is of great importance for driving regional and global tropospheric chemistry. We present seven years (1995-2001) of HCHO column data for North America from the Global Ozone Monitoring Experiment (GOME), and show that the general seasonal and interannual variability of these data is consistent with knowledge of isoprene emission. There are some significant regional discrepancies with the seasonal patterns predicted from current isoprene emission models, and we suggest that these may reflect flaws in the models. The interannual variability of HCHO columns observed by GOME appears to follow the interannual variability of surface temperature, as expected from current isoprene emission models

Application of empirical orthogonal functions to evaluate ozone simulations with regional and global models

Empirical orthogonal functions are used together with standard statistical metrics to evaluate the ability of models with different spatial resolutions to reproduce observed patterns of surface ozone (O3) in the eastern United States in the summer of 1995. We examine simulations with the regional Multiscale Air Quality Simulation Platform model (horizontal resolution of 36 km2) and the global GEOS-CHEM model (2° × 2.5° and 4° × 5°). As the model resolution coarsens, the ability to resolve local O3 maxima (O3 ≥ 90 ppbv) is compromised, but the spatial correlation improves. This result shows that synoptic-scale processes modulating O3 concentrations are easier to capture in models than processes occurring on smaller scales. Empirical orthogonal functions (EOFs) derived from the observed O3 fields reveal similar modes of variability when averaged onto the three model horizontal resolutions. The EOFs appear to represent (1) an east-west pattern associated with frontal passages, (2) a midwest-northeast pattern associated with migratory high-pressure systems, and (3) a southeast stagnation pattern linked to westward extension of the Bermuda High. All models capture the east-west and southeast EOFs, but the midwest-northeast EOF is misplaced in GEOS-CHEM. GEOS-CHEM captures the principal components of the observational EOFs when the model fields are projected onto these EOFs, implying that it can resolve the contribution of the EOFs to the observed variance. We conclude that coarse-resolution global models can successfully simulate the synoptic conditions leading to high-O3 episodes in the eastern United States

The Value of Bt Corn in Southwest Kansas: A Monte Carlo Simulation Approach

While most Corn Belt farmers consider planting Bt corn to control European corn borer, southwestern Kansas farmers must also take into account an array of other insect pests, including corn rootworm, spider mites, and southwestern corn borer. This research uses a decision analysis framework to estimate the expected economic value of Bt corn in southwest Kansas. Mean per acre Bt values ranged from $12.49 to$34.60, well above the technology fee assumed to be $14 per unit, or$5.25 per acre at a seeding rate of 30,000 seeds per acre. The minimum value over all scenarios was $8.69 per acre. Using Monte Carlo simulation, it was shown that European and southwestern corn borer infestation probabilities, expected corn price, and expected pest-free yields are important determinants of the value of Bt corn.Bt corn, decision analysis, European corn borer, integrated pest management, Monte Carlo simulation, southwestern corn borer, Crop Production/Industries,

Land cover change impacts on atmospheric chemistry: simulating projected large-scale tree mortality in the United States

Land use and land cover changes impact climate and air quality by altering the exchange of trace gases between the Earth's surface and atmosphere. Large-scale tree mortality that is projected to occur across the United States as a result of insect and disease may therefore have unexplored consequences for tropospheric chemistry. We develop a land use module for the GEOS-Chem global chemical transport model to facilitate simulations involving changes to the land surface, and to improve consistency across land–atmosphere exchange processes. The model is used to test the impact of projected national-scale tree mortality risk through 2027 estimated by the 2012 USDA Forest Service National Insect and Disease Risk Assessment. Changes in biogenic emissions alone decrease monthly mean O₃ by up to 0.4 ppb, but reductions in deposition velocity compensate or exceed the effects of emissions yielding a net increase in O₃ of more than 1 ppb in some areas. The O₃ response to the projected change in emissions is affected by the ratio of baseline NO[subscript x]: VOC concentrations, suggesting that in addition to the degree of land cover change, tree mortality impacts depend on whether a region is NO[subscript x]-limited or NO[subscript x]-saturated. Consequently, air quality (as diagnosed by the number of days that 8 h average O₃ exceeds 70 ppb) improves in polluted environments where changes in emissions are more important than changes to dry deposition, but worsens in clean environments where changes to dry deposition are the more important term. The influence of changes in dry deposition demonstrated here underscores the need to evaluate treatments of this physical process in models. Biogenic secondary organic aerosol loadings are significantly affected across the US, decreasing by 5–10 % across many regions, and by more than 25 % locally. Tree mortality could therefore impact background aerosol loadings by between 0.5 and 2 µg m⁻³. Changes to reactive nitrogen oxide abundance and partitioning are also locally important. The regional effects simulated here are similar in magnitude to other scenarios that consider future biofuel cropping or natural succession, further demonstrating that biosphere–atmosphere exchange should be considered when predicting future air quality and climate. We point to important uncertainties and further development that should be addressed for a more robust understanding of land cover change feedbacks.National Science Foundation (U.S.) (Grant AGC-1238109

Assessing Snow Extent Data Sets over North America to Inform and Improve Trace Gas Retrievals from Solar Backscatter

Accurate representation of surface reflectivity is essential to tropospheric trace gas retrievals from solar backscatter observations. Surface snow cover presents a significant challenge due to its variability and thus snow-covered scenes are often omitted from retrieval data sets; however, the high reflectance of snow is potentially advantageous for trace gas retrievals. We first examine the implications of surface snow on retrievals from the upcoming TEMPO geostationary instrument for North America. We use a radiative transfer model to examine how an increase in surface reflectivity due to snow cover changes the sensitivity of satellite retrievals to NO2 in the lower troposphere. We find that a substantial fraction (>50%) of the TEMPO field of regard can be snow covered in January, and that the average sensitivity to the tropospheric NO2 column substantially increases (doubles) when the surface is snow covered. We then evaluate seven existing satellite-derived or reanalysis snow extent products against ground station observations over North America to assess their capability of informing surface conditions for TEMPO retrievals. The Interactive Multisensor Snow and Ice Mapping System (IMS) had the best agreement with ground observations (accuracy of 93%, precision of 87%, recall of 83%). Multiangle Implementation of Atmospheric Correction (MAIAC) retrievals of MODIS-observed radiances had high precision (90% for Aqua and Terra), but underestimated the presence of snow (recall of 74% for Aqua, 75% for Terra). MAIAC generally outperforms the standard MODIS products (precision of 51%, recall of 43% for Aqua; precision of 69%, recall of 45% for Terra). The Near-real-time Ice and Snow Extent (NISE) product had good precision (83%) but missed a significant number of snow-covered pixels (recall of 45%). The Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data set had strong performance metrics (accuracy of 91%, precision of 79%, recall of 82%). We use the F score, which balances precision and recall, to determine overall product performance (F = 85%, 82(82)%, 81%, 58%, 46(54)% for IMS, MAIAC Aqua(Terra), CMC, NISE, MODIS Aqua(Terra) respectively) for providing snow cover information for TEMPO retrievals from solar backscatter observations. We find that using IMS to identify snow cover and enable inclusion of snow-covered scenes in clear-sky conditions across North America in January can increase both the number of observations by a factor of 2.1 and the average sensitivity to the tropospheric NO2 column by a factor of 2.7

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