Use of satellite data for quantification of urban and agricultural NO x emission in California
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1 Use of satellite data for quantification of urban and agricultural NO x emission in California Si-Wan Kim (siwan.kim@noaa.gov) and Regional Chemical Modeling group in NOAA/ESRL/CSD U. of Bremen, NASA, KNMI, UC Berkeley-Cohen group, Satellite NO 2 column retrievals CU-Volkamer group and Remote Sensing group (NOAA/ESRL/CSD), Twin-Otter and ground measurements Tropospheric Chemistry group (NOAA/ESRL/CSD), P-3 and ground measurements UC Berkeley-Harley group, California mobile emission inventory (Brian McDonald) EPA OAQPS and CARB, CalNex bottom-up emission inventories Outline 1. The Los Angeles Basin (based on the CalNex field campaign data) - Multiple emission inventories - Observations (satellite, airborne MAX-DOAS, aircraft in-situ, and surface data) - Model O 3 prediction vs. TOPAZ lidar and surface O 3 2. Urban and agricultural sources in California - Uncertainty and consistency in satellite retrievals
2 Year 2005 NEI05 (Bottom-up) Emission Inventories and Models Emission Inventories for 2005 and 2010 Year 2010 EPA10 (Bottom-up) CARB10 (Bottom-up) INV (CO, NO x Inversion, NEI05 VOC) INV2 (INV, Updated VOC) UCB10 (Fuel-use based method) On-road + point source CO, NO x NEI05 VOC Fine-resolution (4 km x 4 km) models WRF-Chem NEI05, CARB10, INV, INV2, UCB10 CMAQ EPA10 Simulation period May-July 2010 NO x emission trend (adapted from McDonald et al., 2012) 35%-41% reduction both in NO x emission and observations between 2005 and On-road mobile NO x emission reduction due to pollution control and recession
3 2010 NASA OMI A priori WRF-Chem WRF-NEI05 WRF-UCB10
4 NO x emission across the LA Basin Average (normalized to UCB10) Averages (All days) Emissions Satellite & models AMAX-DOAS & models Correlation between model and obs. P3 & models Observation With inversion (INV) or on-road mobile inventory (UCB10), model observation, correlation Model NO 2 using NEI05 (2005) needs to be reduced by 50%-70% to agree with observations in 2010 Error in emission from off-road/area/point source spatial distribution
5 NO x emissions from area/point/off-road sources LAX NEI05 NOx 09 PDT Large errors from Ship (port), Non-IPM area sources, Off-road Independent estimates (Millstein and Harley, 2009; McDonald et al., 2012) Ship ~96% reduction from NEI05 Long Beach Stationary (point+area) ~62% reduction Off-road ~84% reduction P3 Flight path Long Beach Port Industrial src. 6/20/2010 6/21/2010 TEMPO will help to constrain these type of sources. P3 Flight path LAX Industrial src.
6 NO x Ratio = Sunday/Weekday Reduced heavy duty truck activity (Harley et al., 2005) Weekday vs. Weekend Measurements : 50-60% NO x reduction in weekend compared to weekdays 30% weekend reduction in NEI05 and CARB10 is not enough. Model using INV and UCB10 (40% daily reduction, up to 70% reduction in hourly emission) agrees with observations from different platforms. Impact of weekly NO x cycle on surface O 3 is important. (e.g., Pollack et al., 2012) Decadal O 3 change Weekday Weekend Sunday O 3 (2.3 ppbv/yr decrease) Wednesday
7 VOC Emissions and Surface O 3 VOC emissions C 2 H 4 C 3 H 6 Xylene C 3 H 8, C 4 H 10 Surface O 3 Recent emission inventory CARB10, EPA10 have low VOC relative to NEI05 and INV2. NEI05 (too much NO x ) and CARB10 (low VOC) Under-prediction of O 3 A pilot study of constraining urban VOC emission with satellite HCHO column is on going. Greg Frost, Michael Trainer, and Rokjin Park (GEMS)
8 VOC Emissions and O 3 Profiles 6/7/2010 Banning Cajon High O 3 in eastern high terrains (Banning pass, Cajon pass) Low O 3 above boundary layer - influence of strong westerly Model O 3 using CARB10 generally underestimates peak observed O 3. - low VOC
9 Vertical profiles of observed and simulated O 3 in the LA Basin in May 29, 2010 Long-range transport + Stratospheric intrusion Lidar observed O 3 Model O 3 without influence of Asian emissions and stratospheric ozone intrusion Large discrepancy between the obs. and the model
10 Uncertainties in satellite tropospheric NO 2 retrievals BEHR or Recalculated NASA OMI NO 2 columns compared to original NASA OMI columns The Los Angeles Basin Unit: molec. cm -2 Unit: molec. cm -2 NASA OMI NO 2 columns are recalculated using the WRF-Chem NO 2 profiles during CalNex. New NASA OMI columns are persistently higher than old NASA OMI columns. On average, the impact of emissions on the retrievals are small. Remaining large difference between the BEHR and the new NASA OMI may be caused by the albedo differences (MODIS versus OMI albedo).
11 Multiple OMI NO 2 versus WRF-Chem (UCB10): pixel to pixel The Los Angeles Basin (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) The WRF-Chem results using the UCB10 emission agree with the airborne (point and column) and surface measurements for the LA Basin, Sacramento, and Bakersfield. BEHR columns (red) > KNMI columns (orange) > New NASA columns (blue)
12 Multiple OMI NO 2 versus WRF-Chem (UCB10): pixel to pixel Sacramento (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) Aircraft obs.
13 Multiple OMI NO 2 versus WRF-Chem (UCB10): pixel to pixel Bakersfield (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) Aircraft obs.
14 Multiple OMI NO 2 versus WRF-Chem (UCB10): pixel to pixel Soil NO x : Rice field (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) Rice field in North of Sacramento The model columns (or emission) are underestimated. The correlation between the satellite and model columns is weak.
15 Multiple OMI NO 2 versus WRF-Chem (UCB10): pixel to pixel Soil NO x : Cotton field (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) (Unit of columns: molec. cm -2 ) Cotton field in Central Valley The model columns (emission) are underestimated. The correlation between the satellite and model columns is low. More data and fine-resolution data will be helpful to characterize the emission.
16 Summary 1. Incorporating accurate temporal changes in on-road mobile emission is essential (e.g., annual trend, day of week cycle, diurnal cycle). 2. Substantial differences among emission inventories are found. Recent bottom-up VOC emission inventory under-predicts boundary layer O 3 and HCHO. 3. Uncertainties in satellite tropospheric NO 2 retrievals ~30% on average over the LA Basin Surface albedo is an important factor. 4. Constraining agricultural NO x with the satellite data across the U.S. will be important. - Discussions and collaboration with AQAST members
17 Paper in preparation Kim, S.-W., et al. (2014), Evaluation of NO x emission inventories over the Los Angeles Basin using satellite, airborne, surface observations, and regional model simulations during the CalNex 2010 field campaign. (under internal review) Kim, S.-W., et al. (2014), Use of satellite data for study of urban and agricultural NO x emissions in California. Acknowledgement NOAA Health of Atmosphere NASA ROSES ACMAP NASA GEO-CAPE Emissions Working Group
Method: Emission Inventories and Models
Evalua&on of NO x and VOC emission inventories for the LA Basin using satellite, aircra> and ground measurements and regional model simula&ons during the CalNex study Si-Wan Kim and Regional Chemical Modeling
J. Brioude. For further details, see J. Brioude et al. (2013, ACP)
Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO,NOx and CO2 and their impacts. J. Brioude Contributing authors:
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