PM source attribution and S/R relationships from HTAP global model experiments

Transcription

1 PM source attribution and S/R relationships from HTAP global model experiments Mian Chin1, Dan Bergman2, Huisheng Bian1,3, Thomas Diehl1,4, Eva Mancini5, Gianni Pitari5, Drew Shindell6, Michael Schulz7, Toshihiko Takemura7, Qian Tan1,4 1 GSFC, U 2DOE LLNL, U 3UMBC, U 4USRA, U 5U. degli Studi L'Aquila, Italy 6 GISS, U 7Met. Institute, Norway 8U. Kyushu, Japan Acknowledgment: HTAP organizers, Jülich data management

2 Global model experiments on aerosols for HTAP base year 21 Although HTAP mainly focuses on anthropogenic aerosol sources and transport, aerosols from other origins, such as soil dust and wild fires, have to be included in assessing the PM levels in the source receptor regions A few AeroCom models participated in the HTAP experiments performed additional SR simulations to consider pollution, smoke, and dust aerosol emissions and transport SR1: model simulations with all emissions (anthropogenic and natural) SR6: model simulations with anthropogenic emissions from particular regions reduced by 2% (SR6, SR6, SR6, SR6) SR6z: same as SR6 but zero-out anthropogenic emissions in a particular region (SR6z, SR6z, SR6z, SR6z SR6d: model simulations with dust emissions turned off from a particular dust source region (SR6dAF, SRd6ME, SR6dAS) SR6b: model simulations with biomass burning emissions turned off from particular burning regions (SR6bNE, SR6bSE, SR6bNW, SR6bSW)

3 Global model experiments on aerosols for HTAP 21 Although HTAP mainly focuses on anthropogenic aerosol sources and transport, aerosols from other origins, such as soil dust and wild fires, have to be included in assessing the PM levels in the source receptor regions 6 models participated in the HTAP experiments performed additional SR simulations coordinated by AeroCom to consider pollution, smoke, and dust aerosol emissions and transport Exp. SR1 SR6 SR6z SR6b SR6d Description model simulations for 21 with all emissions model simulations with anthropogenic emissions from particular regions reduced by 2% (SR6, SR6, SR6, SR6) same as SR6 but zero-out all anthropogenic emissions model simulations with biomass burning emissions turned off from particular burning source regions (SR6bNW, SR6bNE, SR6bSW, SR6bSE) model simulations with dust emissions turned off from particular dust source regions (SR6dAF, SR6dME, SR6dAS) (note: >1 models performed SR1 and SR6 experiments; results shown here only from the 6 models did all experiments)

4 Source and receptor regions Source regions: 4 pollution source regions:,,, 4 biomass burning regions: NW, NE, SW, SE 3 dust regions: AF, ME, AS Receptor regions: 5 regions:,,,, AR

5 Source attributions surface sulfate Surface conc. 21 avg Surface conc. from Surface conc. From Surface conc from (From GMI HTAP simulation)

6 Source attributions surface dust Surface conc. 21 avg Surface conc. from AF Surface conc. From ME Surface conc from AS (From GMI HTAP simulation)

7 Source attribution in the receptor regions from 6 model runs - species SO4 BC POM Dust BC_sfc (ug/m3) POM_sfc (ug/m3) SO4_sfc (ug/m3) DU_sfc (ug/m3) GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL AR GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL.8 AR 5 AR GI GM GO LL SP UL.12 AR GI GM GO LL SP UL.25 AR GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL NE NW SE SW AS ME AF Other NE NW SE SW AS ME AF Other NE NW SE SW AS ME AF Other NE NW SE SW AS ME AF Other

8 Source attribution in the receptor regions from 6 model runs - PM PM1 PM2.5 PM1_sfc (ug/m3) PM2P5_sfc (ug/m3) GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL 6 15 AR GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL AR GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL GI GM GO LL SP UL 2 AR NE NW SE SW AS ME AF Other NE NW SE SW AS ME AF Other Problems in determining receptor region average PM concentration in last HTAP assessment: Receptor regions contains large fraction of ocean sea salt contributes to a large fraction of PM includes part of northern Africa, making determination of PM origin tricky

9 Model diversity AR Dust POM BC SO4 There should be a vetting process to score models based on their performance Using median and percentiles are more appropriate than mean and standard deviation

10 Source-Receptor relationship 21 average, model median (quartile) base for parameterizing S/R? AR % Reduction of anthro emi. in source region POM BC SO4 % Reduction of surface concentration in receptor region Response is linear except SO4 response to SO2 emission which is slightly non-linear Reduction of own regional emission is most effective

11 Issues in the last HTAP experiments for aerosols Region domain: should not include part of N Africa Regional average concentration should be done over land only Model evaluation: Large diversity in model simulated surface concentrations, but little model evaluation performed against surface and satellite observations no vetting process of acceptance In the future run, the credibility of participating models should be shown before making future prediction PM components: Dust (and sea salt) masks the effects of changes of anthropogenic emissions Climate impact: Mostly done in the Impact chapter (Yu et al., 212); loose connection to the modeling session in terms of transport impact on vertical amount, which is much more significant than surface concentration

12 Future HTAP study of PM Emission projection: does emission community unanimously or overwhelmingly agree on the RCP scenarios, all of which show a rapid decrease of anthropogenic emissions in all source regions (except RCP6. in Asia before 25)? Natural sources: with such a decrease of anthropogenic emissions, natural sources will become increasingly important for PM (dust, biogenic, volcanic, etc.). For dust, anthropogenic dust source (e.g., from land use change, farming, deforestation) needs to be addressed Tagging geographic locations or emission sectors: I vote for geographic locations, at least in global model experiments Air quality vs. climate change: Should make stronger connections (radiative flux calculations should be performed) Model evaluation: an evaluation matrix needs to be established with a few basic criteria e.g., surface concentrations, AOD, vertical profiles, using ground-based and satellite data Deposition: BC and dust deposition on snow and ice should be addressed Coordination: with other related modeling activities, especially AeroCom

13 RCP emission scenarios for aerosol and precursors

14 Extra Extra

15 Multi-decadal trends changing source strengths in different regions

16 Black Carbon surface concentration vs. column loading, annual avg Surface: Similar to sulfate, BC concentrations are mainly from the regional pollution sources European pollution is the largest contributor of polluted BC over the Arctic, although its importance is continuously decreasing Column: Pollution sources from other regions are much more pronounced compared to the surface, especially the Asian pollution impact on the North America column BC loading Over the Arctic, pollution has become the most important contributor to the BC loading since 2 BC (mg m -2 ) BC (µg m -3 ) Other