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Long term trends in aerosol optical characteristics observed in Ispra * (*) unpublished results: please do not spread JP Putaud and ABC-IS people M Adam, C Belis, F Cavalli, A Dell’Acqua, K Douglas, C Gruening, S Martins Dos Santos, R Passarella, V Pedroni
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Long term trends in aerosol optical characteristics observed in Ispra* (*) unpublished results: please do not spread JP Putaud and ABC-IS people M Adam, C Belis, F Cavalli, A Dell’Acqua, K Douglas, C Gruening, S Martins Dos Santos, R Passarella, V Pedroni European Commission – Joint Research Centre – Air and Climate Unit & G Zibordi and his team Water Resources Unit
Outline: • Context • Objective • Results • Conclusions • Perspectives
EC • Context The role of short-lived atmospheric constituents in climate change has recently been further emphasized by the Clean Air and Climate Coalition Current other counties: Australia Benin Central African Republic Chile Colombia Cote d’Ivoire Denmark Dominican Republic Ethiopia Finland France Germany Ireland Israel Italy Japan Jordan Maldives Netherlands New Zealand Nigeria Norway Peru Poland South Korea United Kingdom Feb. 2012: United States Bangladesh Canada Ghana Mexico Sweden 1
Context The role of short-lived atmospheric constituents in climate change has recently been further emphasized by the Clean Air and Climate Coalition : www.unep.org/ccac/ “Pollutants that are short-lived in the atmosphere, such as black carbon (soot), methane, tropospheric ozone and some hydrofluorocarbons (HFCs), can have harmful impacts on human health, agriculture and ecosystems. These short-lived climate pollutants – or SLCPs – are also responsible for a substantial fraction of current global warming, as well as having regional climate impact”. 2
O3 +0.5 Wm-2 • Context IPCC AR5 BC +0.6 Wm-2 3
Ensemble mean surface ozone in 2000 (Dentener et al., 2006)* • Context • Radiative forcing by SLCPs is highly uncertain because of: • Very diverse (primary and secondary) sources • Short atmospheric lifetime (*) circles (upper part) indicate regional averaged measurements 4 1 1 1
Context • Radiative forcing by SLCPs is highly uncertain because of: • Very diverse (primary and secondary) sources • Short atmospheric lifetime Annual mean surface layer modelled BC (Vignati et al., 2010) 5
well internally mixed BC BC as a coated core externally mixed BC + 0.54 W m-2 + 0.27 W m-2 + 0.78 W m-2 • Context • Radiative forcing by SLCPs is highly uncertain because of: • Very diverse (primary and secondary) sources • Short atmospheric lifetime • Complex interaction with light (aerosol) M. Z. Jacobson, 2001 6
Context • Radiative forcing by SLCPs is highly uncertain because of: • Very diverse (primary and secondary) sources • Short atmospheric lifetime • Complex interaction with light (aerosol) • day time fraction solar constantatmosphere transmittancecloud fractionsurface albedo • aerosol single scattering albedoupper scatter fractionaerosol optical depth • There are very few accurate measurements of the aerosol optical property across the world Fa = -bFT T² (1-AC) [ωaa(1-RS)² - 2(1-ωa)RS] δa 7 1 1
2. Objective Detect changes in aerosol optical properties resulting from European policies from measurements (JRC Ispra) 2000 2005 2010 1985 1990 1995 Precipitation chemistry Gas phase pollutants (SO2, NOx, O3, CO,…) PM mass and inorganic constituents (SO4, NO3, NH4, …) OC + EC Aerosol scattering and absorption coefficients & number size distribution Aerosol vertical profile Aerosol hygroscopicity 8
3. Methods Measuring relevant variables with the suitable accuracy and precision Scattering () and backscattering (b)Nephelometer(1) Absorption ()Aethalometer(1) Aerosol optical depth (δa)Sunphotometer(2) Instruments are regularly calibrated at the WCCAP (1) or by AERONET (2) a = 0.08 + 1.85b– 2.97b² ωa = /(+) Fa = -bFT T² (1-AC) [ωaa(1-RS)² - 2(1-ωa)RS] δa 9
Measured scatt. and abs. coefficients Measured NSD Calculated scat. and abs. coefficients Mie equations Retrieved minst 3. Methods Scattering (and absorption) coefficients corrected for RH effects 10
Mean GF90 (165 nm) GFRH (165 nm) GF(RH) = (1-RH)-γ Mie equations 3. Methods Scattering (and absorption) coefficients corrected for RH effects Corrected scatt. and abs. coefficients (dry) x(RH) water volume fraction Retrieved minst NSD(RH) minst = x mH2O + (1-x) mdry • Corrections from intrument RH to 0%: • 17 ± 15 % for scattering, 2 ± 1 % for absorption, 2 ± 2 % for single scatering albedo 11 1 1 1
3. Methods Monthly data series are fitted (least squares) with the formula: time (month) constant slope seasonal cycle + higher frequency residual monthly mean for ~ normally distributed variables or ln(monthly mean) for ~ log-normally distributed variables e.g. Collaud-Cohen et al., 2013 12
4. Results Aerosol optical depth (sunphotometer) 13 1 1 1 1 1
4. Results Aerosol optical depth (sunphotometer) -4.5 ± 2.1 % yr-1 -3.1 ± 0.9 % yr-1 14
4. Results Light scattering and absorption by aerosols (in situ) 15
4. Results Light scattering and absorption by aerosols (in situ) -2.8 ± 0.5 % yr-1 16
4. Results Light scattering and absorption by aerosols (in situ) -1.2 ± 0.3 % yr-1 17
4. Results Aerosol single scattering albedo (in situ): ωa = /(+) -0.6 ± 0.2 % yr-1 18
4. Results Aerosol single scattering albedo (sunphotometer) -0.6 ± 0.1 % yr-1 -0.7 ± 0.2 % yr-1 19 1 1 1 1
4. Results Aerosol backscatter ratio (in situ) -0.1 ± 0.3 % yr-1 20
Mean GF90 (165 nm) GFRH (165 nm) GF(RH) = (1-RH)-γ Corrected scat. and abs. coefficients (ambient) x(RH) water volume fraction Retrieved minst NSD(RH) Mie equations minst = x mH2O + (1-x) mdry 3. (Methods) Conversion of measurements (0% RH) to ambient conditions 4. Results Fa = -bFT T² (1-AC) [ωaa(1-RS)² - 2(1-ωa)RS] δa Fa = -bFT T² (1-AC) [ωaa(1-RS)² - 2(1-ωa)RS] δa 21
4. Results (cont’d) Direct radiative forcing by aerosols average = -10 ± 4 W m-2 (1) 22
4. Results Direct radiative forcing by aerosols all: -(-0.9 ± 0.2) W m-2 yr-1 1 23
4. Results Direct radiative forcing by aerosols all: -(-0.9 ± 0.2) W m-2 yr-1 AOT: -(-0.8 ± 0.2) W m-2 yr-1 24 1
4. Results Direct radiative forcing by aerosols all: -(-0.9 ± 0.2) W m-2 yr-1 AOT: -(-0.8 ± 0.2) W m-2 yr-1 SSA: -(-0.3 ± 0.1) W m-2 yr-1 25 1 1 1 1
4. Results Direct radiative forcing by aerosols all: -(-0.9 ± 0.2) W m-2 yr-1 AOT: -(-0.8 ± 0.2) W m-2 yr-1 SSA: -(-0.3 ± 0.1) W m-2 yr-1 26
4. Conclusions • Long term observation of atmospheric variables may help assess the impact of AQ and CC policies, and develop smarter policies • Our data set suggests that the potential mitigation of global warming via the abatement of soot emissions is marginal • As the spatial representativeness of any measurement is limited, networks are essential 27
5. Perspectives • The formula does not account for the vertical distribution of aerosols • use of LiDAR and radiative transfer model • Also for investigating the radiative forcing by aerosols above clouds (also important for cloud formation and water cycle) • Make further use of networking to write more phenomenologies • The radiative forcing due to cloud adjustments to aerosols Fa = -bFT T² (1-AC) [ωaa(1-RS)² - 2(1-ωa)RS] δa 28
4. Perspectives • The formula does not account for the vertical distribution of aerosols • use of LiDAR and radiative transfer model • Also for investigating the radiative forcing by aerosols above clouds • Make further use of networking to write more phenomenologies • The radiative forcing due to cloud adjustments to aerosols • Emerging HFCs with huge global warming potential Fa = -bFT T² (1-AC) [ωaa(1-RS)² - 2(1-ωa)RS] δa 29
THANKS follow ABC-IS activities athttp://abc-is.jrc.ec.europa.eu/
4. Results (cont’d) Elemental carbon and Equivalent Black Carbon 30
4. Results (cont’d) “EC” absorption cross section 31