Space-based constraints on biogenic soil NO emissions Rynda Hudman1, Neil Moore2,3, Randall Martin2, Ashley Russell1, Luke Valin1, Ron Cohen1 Fall AGU Meeting B42E-08 December 16, 2010 In this work we use space-based measurements of NO2 column densities from GOME and OMI to constrain totals and processes governing soil NOx emissions and look at their impact on tropospheric ozone air quality. 1 UC Berkeley, Dept of Chemistry 2 Dalhousie University, Dept of Physics and Atmospheric 3 now at University of Manitoba, Dept of Physics & Astronomy

NOx HAS WIDESPREAD CONSEQUENCES hv Acidification & eutrophication of soils and waterways Forest die-back Impacts carbon sequestration Secondary organic aerosol formation Impacts GHG lifetimes through its effect on OH Ozone air quality hrs - 1 day NO2 HNO3 NO

SOIL NOX EMISSIONS IMPACTS OZONE AIR QUALITY OZONE ENHANCEMENT DUE TO SOIL NOx JUNE 2006 For example, here I am showing a mean modeled max-8hr ozone enhancement due to soil NOx emissions for June 2006. As I will show June 2006 was a dry and warm year which lead to a 50% increase in soil NOx emissions as constrained by the space based OMI NO2 measurments. Soil NOx Ozone enhancement were predicted to be up to 8 ppbv with events reaching up to 16 ppbv. On a regional scale this comparable to the mean decreases of 5-8 ppbv expected from power plant reductions! Ozone enhancement due to soil NOx 8 ppbv, with events up to 16 ppbv Comparable to decreases predicted from power plant reductions! Hudman et al. [2010] 3

Most of what we know is based on point measurements, but effects are regional scale Point Measurments One day of OMI column NO2 Most of what we know about the processes responsible for soil NOx emissions is based on point measurements. These emissions are highly accurate and allow for multiple species and surveying of soil and atmospheric conditions. Soil emissions are highly variable, so scaling up from the meter scale to the 10s of km scale which impacts environmental pollution has proven difficult. Here I am showing one day of coverage from the OMI instrument aboard the AURA satellite. It has global daily coverage with a nadir resolution of 13x24 km2. In our work we examine the potential of using NO2 column densities from space to bridge this gap. Multiple Species/Soil Conditions Continuous Timeseries Limited Spatial Coverage (m) Highly variableDifficulty scaling up Global Daily Coverage (nadir = 13x24 km2) Multi-year Timeseries (late 2004-present) Can provide top-down constraints on regional scale

LARGE SOIL NOx SOURCE INFERRED FROM SATELLITES GOME Constraints on Natural Soil and Agriculture GLOBAL: 8.9 Tg N/yr N. MIDLATITUDES: 3.5 Tg N/yr TROPICS: 5.3 Tg N/yr ~22% of global NOx source ~60% higher than estimates used in current models The first study to use satelllite measurements to constrain soil NO emissions was in an inversion study by Lyatt Jaegle at the university of Washington. They inferred a global source of 8.9 Tg N yr (22% of the global NOx source). largest emissions are inferred over midlatitude fertilized regions and tropical grasslands. This estimate is 60% higher than used in current models which has important implications for the environmental issues I just mentioned. This study, however, only constrained the magnitude of the source. GOME has a nadir resolution is 40x320km2. Now with OMIs much finer resolution, can we constrain processes? X 1010 [molec cm2 s-1] [Jaeglé et al., 2005] This study constrains magnitude, but what about processes? GOME = 40 x 320 km2  OMI = 13 x 24 km2

NO IS A HIGHLY VARIABLE PRODUCT OF MICROBIAL ACTIVITY IN SOILS Processes not well understood, HUGE spatial variability, but best correlation w/ wfps, T, N avail. [Meixner and Yang, 2006] NO are produced during nitrification and denitrification in soils by bacteria. The processes are highly variable but best correlation on a regional scale is with SM, temperature, and N avail. The dependence on soil moisture is illustrated in this schematic. NO is primarily a product of nitrification in drier soils, while N2O, N2 are primarily products of denitrificaytion. If you were looking at NO as a timeseries you would expect to see it as a series of pulses…either by a reactivation of water deprived bacteria or a drying out of soils. ATMOSPHERE N2O(g), N2(g), NO(g) BIOSPHERE

SOIL NOx “EVENTS” pulsing over freshly fertilized Montana fields after rain event ENOx = f( T, biome, w/d, N) x Pulse (precip) x canopy uptake [Yienger and Levy, 1995] ENOx 2005-2007 [Bertram et al., GRL, 2005] Bertram et al., 2005 first showed that satellite measurements of NO2 from SCIAMACHY captured the pulsing behavior of a fertilized field over rural Montana. Here I am showing the blue squares are emissions derived from SCIAMACHY compared with the empirical scheme of Yeinger and Levy [1995]. This is an older model but is what is used in air quality forecasting and regional and global chemical transport models today. This scheme is a function of temperature & landtype, pulsing based on dry period length and precip, fertilizer and uptake by the canopy. Using local climate and fertilizer information they were able to tune these parameters to match observations. Here we extend this work using their modifications to the model driven precipitation and temperature from the North American regional reanalysis, and MODIS Landtype, month fertilizer emissions for 2005-2007 to examine the pulsing behavior and interannual variability in soil NOx from space. We extend this work to include U.S.: daily NARR Temp & Precip MODIS Landtype Fertilizer emissions [Potter et al., 2010]

MEAN MAY-JULY 2005-2008 MODELED SOIL NOx EMISSIONS Emissions range from 3-15 ng N m2 s-1 consistent with field observations Shown here are monthly mean modeled soil NOx emissions in ngN/m2/s for May – July 2005-2008. Values range from 3-5 ng N m2/s over the western grasslands and upt 15 ng N/m2/s over the fertilized central US. These are consistent with summer averages of field observations for these regions Mean Yearly Total: 0.62 Tg N/yr (Fert: 0.12 Tg N/yr) Hudman et al., [2010]

MODELED SOIL NOx EMISSIONS Dry, warm conditions  anomalously high June 2006 pulsed soil emissions Here I am showing monthly mean modeled soil NOx emissions May – July 2005-2007. For the most part May and July means for the different years are fairly similar. But June 2006 emissions 50% large than the other years. We extended this work to 2008 and including August, this is the largest predicted anomaly among any of the months. This is due to June 2006 being an anomalously warm and dry month, leading to predicted large fertilizer induced pulses over much of the central United States. Mean Yearly Total: 0.62 Tg N/yr (Fert: 0.12 Tg N/yr) Hudman et al., [2010]

OMI NO2 ANOMALY FOLLOWS PATTERN PREDICTED AND ARE TOTALS COMPARE WELL Modeled Soil NOx June 2006 OMI June 2006 Anomaly When we compare this with OMI. On the right I am showing the OMI NO2 anomaly for June 2006. You can really see spatial correlation between modeled soil NOx emissions and June 2006 anomaly in column NO2. Converting the OMI column to an emission these anomalies are of similar magnitude. This suggests the modified empirical model has some skill in capturing monthly scale soil NOx behavior. But does it capture the daily variability? Assuming a 1km BL 5 ng ~.5e15 Modified empirical model has some skill in capturing monthly scale soil NOx behavior, what about pulsing? Hudman et al. [2010]

PULSING OVER EASTERN SOUTH DAKOTA IN JUNE 2006 Avg. of NASA & DOMINO OMI NO2 Soil Model Improved Soil Model Standard Precipitation Looking at a case study over rural South Dakota. The top panel shows a timeseries of OMI tropospheric NO2 columns in black compared and predicted soil NOx in green and daily precipitation in red for June 2006. The SNOx model predicts a large soil NOx pulse in mid-June, following rain, corresponding to a large peak in the satellite data. The largest predicted pulse in the soil NOx model is June 14-18. An associated peak is June 15th in the satellite, with its peak reaching 5x1015 molec cm-2 NO2. Assuming a 1 km BL, this pulse would correspond to a ~2 ppbv surface concentration over the region. The modeled soil NOx pulse begins on June 14th and peaks on June 17th, following the observations by about 1 day. The discrepancy between modeled and observed timing is likely due to the model threshold for wet/dry soils and our assumption that subsequent pulses are additive. Recent literature suggests that the magnitude of pulses is a function of dry-spell length rather than amount of rainfall which would correct this discrepency. This timeseries suggests we can use OMI to test our understanding of pulsing triggers, lengths and magnitude for large pulsing events. Day in June Large enough to see, reaching up to 4.6x1015 molec cm2 (2 ppbv), We can use OMI to test understanding pulsing triggers Hudman et al. [2010]

GOME EMISSIONS LARGER THAN ORIGINAL MODEL Particularly at N. Midlatitudes and N. Tropical Africa GOME – ORIGINAL YIENGER AND LEVY [1995] MODEL GOME Total: 8.9 Tg N yr-1 Orig Model: 5.5 Tg N yr-1 we wanted to update our global model based on the results from this regional case study. Here I am showing the GOME derived emissions I showed earlier minus the original Y & L model as implemented into the GEOS-Chem model. The GOME total is 8.9 Tg N yr whereas the Orig model is 5.5 Tg N yr. The largest discrepency is seen over the fertilized N. Midlatitudes suggesting a misrepresentation of fertilizer emissions and over N. tropical Africa which suggests a misrepresentation of pulsing with the seasonal shifts of the ITCZ. Red regions are where GOME emissions > original model

AN UPDATED GLOBAL MODEL OF SOIL NOx ENOx = f( T, biome, WFPS, Fert) x Pulse (dryspell) x canopy uptake ENOx = f( T, biome, w/d, Fert) x Pulse (dryspell) x canopy uptake ENOx = f( T, biome, w/d, Fert) x Pulse (ppt) x canopy uptake ENOx = f( T, biome, w/d) x Pulse (dryspell) x canopy uptake + FERT IMPROVEMENTS: Update Fertilizer: new maps (include N deposition), MODIS EVI seasonality and treat like other N Update Pulsing Scheme: Yan et al., [2005] (shorter, stronger pulses) Update moisture treatment: soil moisture as a continuous variable To address these issues, We update fertilizer emisisons with new maps, include online- N deposition as a fertilizer source. We distribute the chemical fertilizer seasonally using changes in LAI using MODIS enhanced vegetation index. In current implementation of Y& L in GEOS-CHem model fertilizer is treated as independent of temp and precip, emitted equally throughout the season. Here (click) we treat fertilizerand deposited N like all other N. We update the pulsing scheme using Yan et al., 2005, which is based dry spell length and independent of ppt amount, based on latest estimates, and provide shorter and stronger pulses. Finally we change from using discrete wet/dry states to a more physically realistic model using a continuum of Soil moisture/

GOME EMISSIONS LARGER THAN ORIGINAL MODEL Particularly at N. Midlatitudes and N. Tropical Africa GOME – ORIGINAL YIENGER AND LEVY [1995] MODEL GOME Total: 8.9 Tg N yr-1 Orig Model: 5.5 Tg N yr-1 Here again is the comparison to the original model Red regions are where GOME emissions > original model

NEW MODEL MATCHES WITH GOME OBSERVATIONS IN A BROAD SENSE NEW MODEL – ORIGINAL YIENGER AND LEVY [1995] MODEL GOME Total: 8.9 Tg N yr-1 New Model: 7.5 Tg N yr-1 Here I am showing changes between the New Model and the Old Model. You can see as needed the new model increases emissions over the fertilized midlatitudes over the US, Spain, Eastern Europe and Asia and over N. Equatorial Africa. The model is still lower than the satellite observations, with global total of 7.5 Tg N/yr. Red regions are increases with updated model

INCREASES EMISSIONS BY 50% IN SUMMER & BETTER CAPTURES SEASONALITY Zooming in Here I am showing N. midlatitudes from 30-50N, black is GOME inferred emissions, red is the original model and blue is the new model. The new model is better able to capture the seasonal peak in July due to the improved seasonality of the fertilizer database and allowing fertilizer to respond to temp and moisture. Update Fertilizer: new maps (include N deposition), MODIS EVI seasonality and treat like other N

MODEL IMPROVES MAGNITUDE BUT SEASONALITY SHIFTED Over the Northern tropics, the magnitude is improved, but peaks one month early. This is due to the model soil moisture becoming inundated after the first rain, rather than being able to dry out. It suggests we can use satellite measurements, particularly with OMI examining pulsing events individually to constrain soil moisture in these models. Can we use satellite measurements to constrain soil moisture?

SOIL NOX IMPACT ON SURFACE OZONE MAXIMUM MONTHLY MEAN SOIL NOx OZONE ENHANCEMENT 2006 EPA 8-hr std =75 ppbv 40% of sfc ozone While some works is left to be done, our model shows much improvement in the representation of fertilized Northern midlatitudes and of N. equatorial Africa. We can use these estimates to drive the GEOS-Chem CTM to examine impacts on surface ozone air quality. Here I am showing the maximum monthly mean ozone enhancement due to soil NOx in the year 2006. Consistent with our previous study which was constrained by OMI, our updated model predicts 8-10 ppbv enhancement in ozone over the Agricultural Great Plains, this could have implications for putting regions over the top of the US EPA Oozne air quality standard. Over Europe the enhancement is 3-5 ppbv, this is equiv to the amount thought to be transported from N. America  Europe. Over Africa enhancements reach 16 ppbv equiv to 40% of the surface ozone budget. 8-10 ppbv over U.S. 3-5 ppbv over Europe 10-16 ppbv over Africa

CONCLUSIONS & FUTURE WORK OMI observations of NO2 column densities confirmed a X2 increase in pulse driven soil NOx emissions over the agricultural United States in June 2006. The OMI observations provide daily global coverage, which identifies soil pulsing and can be used to refine our understanding of pulsing triggers and also soil moisture in models. Updating a global soil NOx model improves the general agreement with GOME inferred soil NOx emissions for the fertilized midlatitudes  predicted 8-10 ppbv enhancement in ozone due to soil NOx over the U.S. comparable to power plant reductions. Updating a global soil NOx model improves magnitude of emissions in N. equatorial regions, but misrepresents timing due to soil moisture inundation on large grid cells. We predict up to 16 ppbv monthly mean enhancements in this region (40% of surface ozone).