Estimating anthropogenic NOx emissions over the US using OMI satellite observations and

WRF-Chem

Anne Boynard

Gabriele Pfister

David Edwards

AQAST June 2012

National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA

Motivation

Better quantify anthropogenic NOx emissions, which can have large uncertainty [e.g. Street et al., 2003]

NO2 satellite observations are a perfect source of information to constrain NOx emission estimates:

• Global coverage• Good spatial resolution• Sensitivity towards the surface• Short lifetime of NOx => short transport scale

Top-down Approach

ENOX

α

NO2_model NO2_satellite

= Adjustment of the emissions with satellite observations to reduce the disagreement between model and observation.

Assuming that horizontal transport of NOx is negligible, a posteriori emissions can be derived as following: α = ENOX_apriori / NO2_model

=> ENOX_aposteriori = α x NO2_satellite

Martin et al. [2003, 2006] Lamsal et al. [2011]

ENOX = anthropogenic NOx emissionsNO2_model= Modeled NO2 Tropospheric ColumnNO2_satellite= Satellite NO2 Tropospheric Column

Model & Data

A priori anthropogenic NOx emissionsUS EPA 2005 NEI

Satellite NO2 Tropospheric ColumnOMI DOMINO data

[Boersma et al., 2007]

• Average over 9 grid boxes (72km x 72km horizontal resolution)• α is applied only for grid boxes where anthropogenic NOx emissions > 90% Total emissions

Modeled NO2 Tropospheric ColumnWRF-Chem

24km x 24km 10 June – 10 July 2008

We acknowledge the free use of tropospheric NO2 column data from the OMI sensor from www.temis.nl

Larger discrepancy over cities

10 June – 24 June 2008

High polluted regions

Mean Bias Correlation

14±34% 0.84

OMI/WRF-chem (w/ 2005 NEI) comparison

Bias has significantly decreased but we still see large differences locally (e.g. in California)

10 June – 24 June 2008

High polluted regions

Mean Bias Correlation

-7±16% 0.86

OMI/WRF-chem (w/ a posteriori emissions) comparison

A priori versus A posteriori Emissions

Over the CONUS: reduction in anthropogenic emissions of ~7.5%=> Reduction in NOx emissions consistent with EPA Trend data & EDGAR database

A priori emission A posteriori emission

2.3Tg N / year 2.1 Tg N / year

10 June – 10 July 2008

Change in surface Ozone (20UTC)

Over most of the cities, when NOx emissions decrease, O3 increases=>This might have important policy implications for urban areas where NOx emissions are controlled

O3 w/ a posteriori – O3 w/ a priori

New Top-Down Approach: XNOX Method

Using the "total NO2”, we attribute the entire NO2 column to anthropogenic sources while it includes other sources (e.g. fire, biogenic sources)

Anthropogenic NO2 (XNO2) is tagged in our WRF-Chem simulation (chemically active species)

Idea: Using modeled anthropogenic NO2 Trop. Column instead of modeled total NO2 Trop. Column to estimate a posteriori emissions This method allows to get a well defined linear relation between

anthropogenic NOx emissions and anthropogenic NO2 Trop. Column

Question: How things change?

XNO2 contribution to NO2

XNO2 > 0.8 * NO2

10 June – 10 July 2008

When XNOX > 0.8 * NO2 : cities but also power plants show

This method indicates regions where the NOx emission constraint can be applied with high confidence

Martin et al. method versus XNOX method

Increase of NOx emissions of ~10 to 30% with the XNOX method

Anthropogenic NOx emissions Difference between XNOX and Martin et al. method

Summary

Anthropogenic NOx emissions were estimated over the US during summer 2008 using WRF-Chem and OMI satellite data

EPA 2005 NEI was constrained using a top-down approach Bias between model and observations was reduced by 8% using the

adjusted emission inventory The results indicated that EPA 2005 NEI might overpredict NOx

emissions over cities (up to 50%) – large impact on surface O3 Anthropogenic NO2 tracers indicated that this method really only

works well over high emission hot spots (cities – power plants)

THANK YOU!

Anne Boynard

Gabriele Pfister

David Edwards

AQAST June 2012

National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA