1. Multi-model and Observed PM Trends
ED Trends study
On behalf of EDT Team presented by Svetlana Tsyro
TFMM 17-th meeting
Utrecht, NL, May 18-20, 2016

2. Presentation Scope
Components: PM10, PM2.5 (just a few words about components)
Periods:
(PM obs available) - 3 models
/7 models
Methods/tools
EMEP, CHIMERE, LOTOS-EUROS for
above & MINNI, CMAQB, WRFC, POLYPHEMUS for 1990, 2000, 2010
EMEP monitoring data (ebas)
Mann Kendall test to detect the trend (significance level 0.1)
Theil-Sen’s slope
Questions
Can we see trends from model results? Observations?
Geographical differences? Where can we see (in)significant trends?
How well the models reproduce observed trends?
Agreements between the models?
Decadal differences for trend assessments
……. effect of meteorology, natural contribution, emissions??
Summary

3. How well do the models reproduce observations through the years 2001-2010 ?
PM10
PM2.5
“Robust” underestimation by 5-15% PM10 and 5-20% PM2.5; fair to good correlation
SO4 – LOTO underestimation 30-40%, EMEP (<-10%), CHIM (<+10%)
NO3 – all overestimate by 30 (2006) to 70%
NH4 – overestimation 15-30% EMEP & LOTO, 50-70% CHIM

4. Do the models agree/disagree with observations. Between themselves
Do the models agree/disagree with observations? Between themselves? PM10 annual series
Median
«Ensemble»
Mean
EMEP
CHIM
LOTO

5. Do the models agree/disagree with observations? Between themselves? PM2.5 annual series 2001-2010
Median
«Ensemble»
Mean
EMEP
CHIM
LOTO

6. Can we identify significant PM10 trends in models’ results and observations in 2001-2010?
µg m-3/yr
%/yr
«Ensemble»
µg m-3/yr
%/yr
EMEP
CHIM
LOTO

7. Can we identify significant PM2
Can we identify significant PM2.5 trends in models’ results and observations in ?
µg m-3/yr
%/yr
«Ensemble»
µg m-3/yr
%/yr
EMEP
CHIM
LOTO

8. Sen’s slopes (µg m-3/yr) for trend-sites in 2001-2010
Do the models agree/disagree about trend slopes with observations? Between themselves?
Sen’s slopes (µg m-3/yr) for trend-sites in
PM10
PM2.5
Smaller modelled trends vs. observed significant ones, also quite large modelled trends for some sites with insignificant observed

9. Do the models (dis)agree in the trend geography with observations
Do the models (dis)agree in the trend geography with observations? Between themselves?
Sen’s slopes (µg m-3/yr) for sites with observed significant trends in
AT02 AT05 CH02 CH03 CH04 CH05 DE01 ES07 ES10 ES11 ES13 ES14 FI50 SE12
PM10
ES ES ES ES ES ES IT SE12
PM2.5

10. Some EMEP sites’ examples for PM10
DE01
ES13
ES07
EMEP
CHIM
LOTO

11. Some EMEP sites’ examples for PM2.5
DE03
EMEP
CHIM
LOTO

12. What about PM composition?
Consistency btw the models? Agreement with Obs?

13. SO4 NO3 NH4 PPM LOTO EMEP CHIM
Relative contribution of SIA and primary PM trends to PM10 trends (95% probability) in as calculated by the EMEP, CHIM and LOTO models
SO4
NO3
NH4
PPM
EMEP
CHIM
LOTO

14. There is no observations to assess PM trends in Europe prior 2001
Thus, we rely upon our model calculations to estimate PM trends between 1990 and 2010

15. Mean relative trends and yearly series for 1990-2010
EMEP
CHIM
LOTO
PM10
PM2.5

16. What about “discrete” years calculations?
7 models: 1990, 2000, 2010
Can we use the differences in trend studies?
How different are these trends from Sen’s slopes?
How similar/different are the results from 7 models?

17. TEST with EMEP model for 2001 - 2010
Average trends from trend runs (Sen’s slopes)
Average trends from diffs

18. Average trends for PM10 from diffs 2000-2010
EMEP
LOTO
CHIM
CMAQB
WRFC
MINNI
POLYPH

19. Average trends for PM10 from diffs 2000-2010 using 2010 meteorology
EMEP
CHIM
LOTO
CMAQB
WRFC
MINNI
POLYPH

20. Average trends for PM2.5 from diffs 2000-2010
EMEP
LOTO
CHIM
CMAQB
WRFC
POLYPH
MINNI

21. Average trends for PM2.5 from diffs 2000-2010 using 2010 meteorology
EMEP
CHIM
LOTO
CMAQB
WRFC
MINNI
POLYPH

22. Average trends for PM10 from diffs 1990-2010 using 2010 meteorology
EMEP
CHIM
LOTO
CMAQB
WRFC
MINNI
POLYPH

23. Average trends for PM2.5 from diffs 1990-2010 using 2010 meteorology
EMEP
CHIM
LOTO
CMAQB
WRFC
MINNI
POLYPH

24. Summary
“Robust” models’ performance for PM: rather consistent overestimation by 10-20% and in ;
spatial corr for PM10, for PM2.5
Models calculate quite similar geographical patterns of mean trends, though some differences exist
The models calculate significant trends for more EMEP sites than identified by measurements
The models and observations indicate negative trends in : the modelled trends are 20-60% lower for PM10 and 20-80% lower for PM2.5 compared to observed (geographical variability)
First results indicate some differences in PM composition change according to the 3 models
Differences based on model results for 1990, 2000 and 2010 can be applied to derive mean trend, calculations with constant meteorology are recommended to diminish its effect (no changes in natural aerosols)

25. Augustin Colette, Bertrand Bessagnet, Florian Couvidat (INERIS)
Astrid Manders (TNO)
Marta Garcia Vivanco, Mark Theobald (CIEMAT)
Kathleen Mar (IASS)
Narendra Ojha, Andrea Pozzer (MPI)
Mihaela Mircea(ENEA)
Maria-Teresa Pay (BSC)
Yelva Roustan, Valentin Raffort (CEREA)
Kees Cuvelier (ex-JRC)
Hilde Fagerli, Peter Wind (met.no)
Wenche Aas (NILU)
THANK YOU!

26. Mean relative trends (%)
What are the trends in Emissions from 2001 to 2010?
Mean relative trends (%)
SOx
NOx
NH3
PPM2.5
Coarse PPM

27. Mean relative trends (%)
What are the trends in Emissions from 1990 to 2010?
Mean relative trends (%)
SOx
NOx
NH3
PPM2.5
Coarse PPM

28. Can we identify PM trends in 2001-2010 in models’ Ensemble results and observations?
µg m-3/yr
%/yr

29. Do the models agree/disagree with observations? Between themselves?
Sen’s slopes (µg m-3/yr) for trend-sites in
PM10
PM2.5

30. Same for PM2.5 trends
BSOA ASOA BSOA ASOA

31. Average trends for SO4 from diffs 2000-2010 using 2010 meteorology

32. Average trends for NO3 from diffs 2000-2010 using 2010 meteorology

33. Average trends for NH4 from diffs 2000-2010 using 2010 meteorology