John C. Lin Deyong Wen

Transcription

1 Regional scale source apportionment using a timeinverted Lagrangian stochastic air quality model John C. Lin (John.Lin@utah.edu) Deyong Wen Rice University: Jan. 1

2 Source Apportionment: General Problem How to mitigate pollution How to identify Exceptional events Quantify cross-border pollution Setting non-attainment area boundaries Sources Receptor Where? How much? Which kinds?

3 Problems with Existing Source Apportionment Methods Statistical methods (e.g., chemical mass balance, positive matrix factorization) -drastic assumptions: constant emissions, known source profiles, non-reactive species -lack of info. regarding atmospheric transport -minimal consideration of chemical transformations Trajectory methods (e.g., potential source contribution function) -no consideration of turbulent dispersion (problematic for lower atmosphere & surface sources) Forward-time Gridcell-based tagged-species methods (e.g., tagged species source apportionment, particulate source apportionment technology) -computationally expensive -limited resolution in space and time Adjoint Gridcell-based method -difficulty of maintaining adjoint as code advances -linearization, numerical diffusion

4 The new Stochastic Lagrangian Apportionment Method (SLAM) BACKWARD Source Source Receptor Key idea: air parcels arriving at a receptor can be derived from backward-time runs Reverse time

5 The new Stochastic Lagrangian Apportionment Method (SLAM) FORWARD Source Receptor Chemical reactions and pollutant concentrations are then calculated FORWARD in time (using CB chem. mechanism, updated w/ CB5 rate constant updates in Yarwood et al. [5]) Source

6 Advantages of Stochastic Lagrangian Apportionment Method (SLAM) Availability of trajectory information Incorporates effects of turbulent dispersion High spatial/temporal resolution of apportioned sources Lack of numerical diffusion

7 χ E C C χ E 3 hr i= hr 18 hr 1 hr 6 hr hr i=1 ΔC i= i=3 i= i=5=t Boundary condition Net chemical loss Industrial emissions Deposition loss Agricultural emissions Receptor

8 SLAM is Built into New Lagrangian Air Quality System (STILT-Chem)

9 Application: source apportionment of ammonia (NH 3 ) and ammonium particulates (p-nh + ) Ammonia, after emitted into the atmosphere, gets transformed into ammonium particulates, which are a major component of PM.5 Q: How much of the ammonia and ammonium particulates are due to ammonia emissions at a certain location?

10 Ammonia (NH 3 ) Emission Grid Agricultural Non-Agricultural

11 Observed & Simulated, Apportioned NH Longwoods NH (µg/m 3 ) /11 11/11 1/11 1/1 11/1 1/1 1/9 11/9 1/9 1/8 11/8 1/8 1/7 11/7 1/7 1/6 11/6 1/6 Date Observed Simulated Agriculture Boundary Non agriculture

12 Observed & Simulated, Apportioned NH Longwoods NH (µg/m 3 ) /11 11/11 1/11 1/1 11/1 1/1 1/9 11/9 1/9 1/8 11/8 1/8 1/7 11/7 1/7 1/6 11/6 1/6 Date June 17 th, 6 Observed Simulated Agriculture Boundary Non agriculture

13 Observed & Simulated, Apportioned NH Longwoods NH (µg/m 3 ) /11 11/11 1/11 1/1 11/1 1/1 1/9 11/9 1/9 1/8 11/8 1/8 1/7 11/7 1/7 1/6 11/6 1/6 Date Nov. th, 6 Observed Simulated Agriculture Boundary Non agriculture

14 Source Apportionment for NH 3 Concentration NH 3 a) b)

15 Source Apportionment for p-nh + Concentration p-nh + a) b)

16 Comparisons against Brute-force Method (BFM) NH 3 predicted by SLAM (µg/m 3 ) r =.989 n = 6 NH 3 p-nh + y=.93x+. a) p-nh + predicted by SLAM (µg/m 3 ) NH 3 predicted by BFM (µg/m ) p-nh predicted by BFM (µg/m ) r =.961 n = 183 (by zeroing out ag emissions) y=1.378x+.1 b) Compares well against brute force method (BFM), with difference in the expected direction (indirect effects)

17 Summary/Conclusions Stochastic Lagrangian Apportionment Method (SLAM) is a technique that provides quantitative estimates of sources from different locations, times, and types with numerous advantages Remaining uncertainties: modeled transport, emissions, mixing SLAM enables air quality managers to -quantify cross-border transport -determine mitigation opportunities -identify exceptional events Incorporated within a newly-developed air quality model (STILT-Chem)