Recommendations on fine scale emissions derived from HERMESv3 M. - PowerPoint PPT Presentation

Recommendations on fine scale emissions derived from HERMESv3 M. Guevara, Tena, C., Jorba, O., Pérez García-Pando, C. FAIRMODE technical meeting 09/10/2019 October 07 - 09, 2019 – Madrid, Spain

Motivation Modelled emissions Gridded emission inventories (a) (b) (c) (d) √ Gridded (fixed grid) √ Gridded (any grid or source level) X Not hourly (annual, monthly) √ Hourly X Not speciated √ Speciated Emission models Emission processing systems Implement detailed bottom-up Adapt the emission data to the air emission estimation methodologies quality model’s requirement

HERMESv3 A python-based, parallel and multiscale emission modelling framework that processes and estimates gas and aerosol emissions for use in atmospheric chemistry models.

HERMESv3 A python-based, parallel and multiscale emission modelling framework that processes and estimates gas and aerosol emissions for use in atmospheric chemistry models. global-regional module bottom-up module (HERMESv3_GR) (HERMESv3_BU) A processing system that calculates An emission model that estimates emissions through an automatic emissions at the source level combination of existing inventories combining state-of-the-art bottom- and user defined vertical, temporal up methods with local activity and and speciation profiles emission factors Guevara et al. (2019a, GMD) Guevara et al. (in preparation)

HERMESv3_GR: global-regional module Emission data library HERMESv3_GR output • Combination of multiple up-to-date gridded emission inventories • User defined destination working domain (multiple projections) • Application of country-specific scaling and masking factors • User defined vertical, temporal and speciation profiles per sector and pollutant • Outputs for multiple atmospheric chemistry models (CMAQ, WRF-Chem, MONARCH) • Available at the BSC git repository: https://earth.bsc.es/gitlab/es/hermesv3_gr

HERMESv3_BU: Bottom-up module user-dependent input internal input data meteorology data Bottom-up and process-based estimation methodologies A_PublicPower C_OtherStationary F_Roadtransport K_AgriLivestock G_Shipping B_Industry Comb L_AgriOthers H_Aviation I_Offroad Criteria pollutants: NO x , CO, SO 2 , Greenhouse gases: NMVOC, NH 3 , CO 2 , CH 4 PM 10 , PM 2.5

HERMESv3_GR: Temporal distribution • Specific monthly, weekly and diurnal profiles per sector and pollutant • Use of gridded profiles (variation not uniform across the space) 5.5 4.0 5.0 4.5 3.0 4.0 3.5 3.0 2.0 2.5 2.0 1.5 1.0 1.0 0.5 0.0 0.0 1 20 39 58 77 96 115 134 153 172 191 210 229 248 267 286 305 324 343 362 1 3 5 7 9 11 13 15 17 19 21 23 C_OtherStationaryCombution - Default Athens Barcelona Oslo C_OtherStationaryCombution - PM PM10 – EIONET Rural stations (December 2016)

HERMESv3_BU: Road transport Estimation of link-level vehicle emissions 𝑜 𝐹 𝑚,𝑗 ℎ = ෍ 𝐵𝐵𝐸𝑈(ℎ) 𝑤,𝑚 ∗ 𝐹𝐺(ℎ) 𝑤,𝑚,𝑗 𝑤=1 hot, cold-start, wear, evaporative, resuspension Amato et al. (2012) (speed and meteo dependent) Diesel passenger cars @ 28km/h [g/km] 1.0 0.8 0.6 0.4 0.2 0.0 Euro 2 Euro 3 Euro 4 Euro 5 Euro 6 COPERT IV COPERT V COPERT V (with degradation factor) RSD

HERMESv3_BU: Road transport Estimation of link-level vehicle emissions 𝑜 𝐹 𝑚,𝑗 ℎ = ෍ 𝐵𝐵𝐸𝑈(ℎ) 𝑤,𝑚 ∗ 𝐹𝐺(ℎ) 𝑤,𝑚,𝑗 𝑤=1 hot, cold-start, wear, evaporative, resuspension Amato et al. (2012) (speed and meteo dependent) Petrol passenger cars @ 28km/h [g/km] 1.0 0.8 0.6 0.4 0.2 0.0 Euro 2 Euro 3 Euro 4 Euro 5 Euro 6 COPERT IV COPERT V COPERT V (with degradation factor) RSD

HERMESv3_BU: Road transport Estimation of link-level vehicle emissions 𝑜 𝐹 𝑚,𝑗 ℎ = ෍ 𝐵𝐵𝐸𝑈(ℎ) 𝑤,𝑚 ∗ 𝐹𝐺(ℎ) 𝑤,𝑚,𝑗 𝑤=1 Low temperature NOx diesel emission penalty Grange et al. (2019)

HERMESv3_BU: Recreational boats • Total Spanish boat park > 200.000 • Large contribution to CO and NMVOC emissions in coastal areas • Emissions mainly occurring during summer season Total annual emissions • How are these emissions currently 3.5E+04 Port activities being treated in EMEP 0.1x01? 3.0E+04 Small boats 2.5E+04 t/year 2.0E+04 1.5E+04 1.0E+04 5.0E+03 0.0E+00 NOx SO2 CO NMVOC PM10 PM25

HERMESv3_BU: LTO cycles Main engines Brake and tyre wear Auxiliary Power Unit • • • Taxi out Approach Pre-taxi out • Landing • • Take off Landing • Post-taxi in • • Climb out Taxi in Not included in the EMEP/EEA guidelines Netcen (2004) 100% Morris (2007) 80% 60% 40% 20% 0% NOx CO PM10 PM2.5 NMVOC apu taxi takeoff climbout approach landing

HERMESv3_BU: Fertilizers Consideration of the spatial and temporal dynamical component of the emission processes. (𝑒− 𝜐 𝑑,𝑏 ) 2 3 𝑜 𝛾 𝑏,𝑑 2 Г(𝑦 𝑑 ∗ 𝐹𝐺(𝑦 𝑑 ∗ (𝑓 0.022∗𝑈(𝑒)+0.042∗𝑋𝑇(𝑒) ) ∗ ෍ −2∗𝜏 𝑑,𝑏 ) ) 𝐹 𝑦, 𝑒 = ෍ 𝐵(𝑦 𝑑 ∗ ൯ ∗ 𝑓 𝜏 𝑑,𝑏 ∗ 2 ∗ 𝜌 𝑑=1 𝑏=1 Soil properties NH 3 volatilization Crop distribution • • • pH and Cation Exhange Capacity 2m temperature Crop hectares • • Wind speed Land uses Local cultural techniques • Crop calendars Local cultural techniques • N application rate • Type of fertilizers Skjøth et al. (2011)

HERMESv3_BU: Fertilizers Consideration of the spatial and temporal dynamical component of the emission processes. (𝑒− 𝜐 𝑑,𝑏 ) 2 3 𝑜 𝛾 𝑏,𝑑 2 Г(𝑦 𝑑 ∗ 𝐹𝐺(𝑦 𝑑 ∗ (𝑓 0.022∗𝑈(𝑒)+0.042∗𝑋𝑇(𝑒) ) ∗ ෍ −2∗𝜏 𝑑,𝑏 ) ) 𝐹 𝑦, 𝑒 = ෍ 𝐵(𝑦 𝑑 ∗ ൯ ∗ 𝑓 𝜏 𝑑,𝑏 ∗ 2 ∗ 𝜌 𝑑=1 𝑏=1 Lleida HERMESv3 – NH 3 L_AgriOthers (2015) 120 100 80 t day-1 60 40 20 0 1 103 120 137 154 171 188 205 222 239 256 273 290 307 324 341 358 18 35 52 69 86 South of Castilla Leon 120 100 80 t day-1 60 40 20 0 1 18 35 52 69 86 103 120 137 154 171 188 205 222 239 256 273 290 307 324 341 358 Barley Maize Wheat Others

HERMESv3_BU: Livestock Use of the gridded Livestock of the World version 3 (GLWv3; Gilbert et al., 2018) HERMESv3 – NH 3 G_Livestock (2015) GLWv3 versus location of farms Murcia Galicia 55 55 50 50 45 45 40 40 t day-1 t day-1 35 35 30 30 25 25 20 20 15 15 10 10 5 5 0 0 1 19 37 55 73 91 109 127 145 163 181 199 217 235 253 271 289 307 325 343 361 1 19 37 55 73 91 109 127 145 163 181 199 217 235 253 271 289 307 325 343 361 Pigs Cattle Others Pigs Cattle Others

HERMESv3_BU: Livestock Use of the gridded Livestock of the World version 3 (GLWv3; Gilbert et al., 2018) HERMESv3 – NH 3 G_Livestock (2015) IASI-derived total NH 3 Van Damme et al. (2018, Nature) Total NH3 [t/year] 1.2E+05 HERMESv3 IASI 9.0E+04 6.0E+04 3.0E+04 0.0E+00 Aragon - Catalonia Murcia

Take home messages • Temporal variation of emissions: o It is important to consider differences across pollutants and regions • Road transport: o Measurements under real-world conditions are essential for the continuous improvement/refinement of the emissions (e.g. temperatura effect) • Agriculture: o Consideration of the spatial and temporal dynamical component of the emission processes is a key component. • Other mobile sources o LTO cycles: ensure that all the processes are considered (e.g. brake and tyre wear) o Recreational boats: Large source of VOCs in summer and coastal areas. The sector should be treated separately and not as part as the “ OtherMobileSources ”

THANK YOU! marc.guevara@bsc.es www.bsc.es