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Objective What is the effect of traffic scenarios to reduce CO 2 emissions

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Objective What is the effect of traffic scenarios to reduce CO 2 emissions

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  1. WP-Traffic“develop GIS method and support cities to assess the impact of traffic-related CO2 emission reduction scenarios on air quality and noise in 2020”Laura Perez/Stephan Trueeb (STI-Basel); Arja Asikainen/Marjo Niittynen (THL-Kuopio); Willem-Jan Okkerse (DCMR-Rotterdam)/Menno Keuken (TNO); Sandra Torras Ortiz (Uni Stuttgart)/Manfred Wacker (Uni Stuttgart-Stuttgart); Denis Sarigiannis/Periklis Kontoroupis/Spyros Karakitsi (CERTH-Thessaloniki); Junhan Liu/Hongshuang Lau/Xiaochuan Pan (Uni Peking-Xi’an City) and Haikun Wang (Uni Nanjing-Suzhou City)

  2. Objective What is the effect of traffic scenarios to reduce CO2 emissions on well being and health in 2020? • traffic scenarios: • 10% less traffic/ 50% electric cars: Rotterdam, Basel, Xi’an and Suzhou • Bundle of measures: Stuttgart • Biofuels: Kuopio • Extra metro: Xi’an and Thessaloniki • well-being: • noise (Lden > 55 dB): highly annoyed • health: • AQ: annual average: NO2, PM2.5, PM10 and EC • noise: (Lnight > 50 dB): sleep disturbed • exposure population: • streets: > 10 000/24-h; < 100 m motorways; rest population

  3. Method • Input: GIS road infrastructure; GIS traffic; emission factors; AQ background concentrations; meteorology • Dispersion modelling: 2010, 2020, 2020+CO2 reduction scenarios • Output: AQ and noise data to WP-Health • Innovation: • EC (“soot”) as traffic/health indicator • Spatial resolved health effects: streets, motorways and “rest” • Dispersion modelling in Chinese cities

  4. Results (1)CO2 emissions from road traffic

  5. Results (2)EC (µg/m3) in Kuopio 2010 2020 Cleaner vehicles: Euro-6!

  6. Results (3)EC (µg/m3) in Suzhou 2010 2020 Lower regional background: fly-ash removal coal plants!

  7. Results (4)EC (µg/m3) in Rotterdam: 2020 & 2020-50% electric

  8. Results (4)EC (µg/m3) in Rotterdam: 2020 & 2020-50% electric

  9. Results (5)EC (µg/m3) in busy streets and urban background in Basel, Rotterdam, Xi’an and Suzhou

  10. Results (6)Health impact assessment – WP-Health • Impact of change in air quality on all-cause mortality in Life Years Lost: • ~ one year per 10 µg m-3 PM2.5 • ~ one year per 1 µg m-3 EC

  11. Results (7)Peer-reviewed papers • “Impact of measures to reduce CO2 emissions from road traffic on air quality in Basel, Rotterdam, Xi’an and Suzhou” • “Health impact assessment for noise and air quality related to transport policies in Rotterdam” • “Health impact assessment of transport policies in Basel” • …..

  12. Lessons learned? • Urban traffic CO2 emissions in 2020 versus 2010? • 30-50% increase in China and stabilize in Europe • 2. Effect urban traffic measures on CO2 emissions? • 5% (I) and 25% (II) reduction from urban road traffic • Effect urban traffic measures on AQ and noise? • limited on AQ and noise (even) near busy street canyons • 4. AQ assessment in China and Europe? • similar approach is applicable with “open source data” in China but more validation with observations is required: # vehicles, fleet composition, emission factors, AQ data and source apportionment

  13. Policy implications? Most effective to reduce CO2 emissions from urban road traffic is more stringent CO2 emission standards (clean technology: all electric) Most effective localclimatepolicy is support/facilitate/stimulate electric vehicles: maximum reduction 50% CO2 emissions from urban road traffic Most effective local integratedpolicy is supporting/facilitating physical/public transport to improve air quality, health and well-being

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