Emissions from main propulsion engine on container ship at sea

Agrawal, Harshit; Welch, William D.; Henningsen, Svend; Miller, John W.; Cocker, David R.

doi:10.1029/2009jd013346

Cited by 88 publications

(63 citation statements)

References 43 publications

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“…Agrawal et al (2008) performed exhaust gas measurements inside a container-ships' stack and found a value of f SO 4 = 3.7-5 % (positively correlated with engine load) for a fuel sulphur content of 2.05 %. These results are confirmed by Agrawal et al (2010) (f SO 4 = 2.4-5 % with fuel sulfur content of 3.01 %). Lack et al (2009) measured ship-emission plume compositions within 15 min post-emission and deduced f SO 4 = 1.4 ± 1.1 % and f SO 4 = 3.9 ± 2.0 % for low (< 0.5 %) and high (> 0.5 %) fuel sulphur content, respectively.…”

Section: Methodssupporting

confidence: 77%

Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM

et al. 2012

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Abstract. In this study, we employ the global aerosol-climate model ECHAM-HAM to globally assess aerosol indirect effects (AIEs) resulting from shipping emissions of aerosols and aerosol precursor gases. We implement shipping emissions of sulphur dioxide (SO 2 ), black carbon (BC) and particulate organic matter (POM) for the year 2000 into the model and quantify the model's sensitivity towards uncertainties associated with the emission parameterisation as well as with the shipping emissions themselves. Sensitivity experiments are designed to investigate (i) the uncertainty in the size distribution of emitted particles, (ii) the uncertainty associated with the total amount of emissions, and (iii) the impact of reducing carbonaceous emissions from ships.We use the results from one sensitivity experiment for a detailed discussion of shipping-induced changes in the global aerosol system as well as the resulting impact on cloud properties. From all sensitivity experiments, we find AIEs from shipping emissions to range from −0.32 ± 0.01 W m −2 to −0.07 ± 0.01 W m −2 (global mean value and inter-annual variability as a standard deviation). The magnitude of the AIEs depends much more on the assumed emission size distribution and subsequent aerosol microphysical interactions than on the magnitude of the emissions themselves. It is important to note that although the strongest estimate of AIEs from shipping emissions in this study is relatively large, still much larger estimates have been reported in the literature before on the basis of modelling studies. We find that omitting just carbonaceous particle emissions from ships favours new particle formation in the boundary layer. These newly formed particles contribute just about as much to the CCN budget as the carbonaceous particles would, leaving the globally averaged AIEs nearly unaltered compared to a simulation including carbonaceous particle emissions from ships.

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Section: Methodssupporting

confidence: 77%

Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM

et al. 2012

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“…Figure 13 and Table 4 show emission factors for CO in this study in comparison to other studies in the literature. Emission factors for carbon monoxide (EF CO ) are expected to drop with increasing ship engine load (speed) (Agrawal et al, 2008(Agrawal et al, , 2010Moldanová et al, 2009;Petzold et al, 2011;Jalkanen et al, 2012;Khan et al, 2012b;Cappa et al, 2014). EF CO in this study was in good agreement with other studies for which the vessel speed was very slow.…”

Section: Emission Factorssupporting

confidence: 80%

Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker <i>Amundsen</i> from the <i>Polar 6</i> aircraft platform

et al. 2016

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Abstract. Decreasing sea ice and increasing marine navigability in northern latitudes have changed Arctic ship traffic patterns in recent years and are predicted to increase annual ship traffic in the Arctic in the future. Development of effective regulations to manage environmental impacts of shipping requires an understanding of ship emissions and atmospheric processing in the Arctic environment. As part of the summer 2014 NETCARE (Network on Climate and Aerosols) campaign, the plume dispersion and gas and particle emission factors of effluents originating from the Canadian Coast Guard icebreaker Amundsen operating near Resolute Bay, NU, Canada, were investigated. The Amundsen burned distillate fuel with 1.5 wt % sulfur. Emissions were studied via plume intercepts using the Polar 6 aircraft measurements, an analytical plume dispersion model, and using the FLEXPART-WRF Lagrangian particle dispersion model. The first plume intercept by the research aircraft was carried out on 19 July 2014 during the operation of the Amundsen in the open water. The second and third plume intercepts were carried out on 20 and 21 July 2014 when the Amundsen had reached the ice edge and operated under ice-breaking conditions. Typical of Arctic marine navigation, the engine load was low compared to cruising conditions for all of the plume intercepts. The measured species included mixing ratios of CO 2 , NO x , CO, SO 2 , particle number concentration (CN), refractory black carbon (rBC), and cloud condensation nuclei (CCN). The results were compared to similar experimental studies in mid-latitudes.Plume expansion rates (γ ) were calculated using the analytical model and found to be γ = 0.75 ± 0.81, 0.93 ± 0.37, and 1.19 ± 0.39 for plumes 1, 2, and 3, respectively. These rates were smaller than prior studies conducted at mid-latitudes, likely due to polar boundary layer dynamics, including reduced turbulent mixing compared to midPublished by Copernicus Publications on behalf of the European Geosciences Union. 7900 A. A. Aliabadi et al.: Ship plume intercept using aircraft in the Arctic latitudes. All emission factors were in agreement with prior observations at low engine loads in mid-latitudes. Ice-breaking increased the NO x emission factor from EF NO x = 43.1 ± 15.2 to 71.6 ± 9.68 and 71.4 ± 4.14 g kgdiesel −1 for plumes 1, 2, and 3, likely due to changes in combustion temperatures. The CO emission factor was EF CO = 137 ± 120, 12.5 ± 3.70 and 8.13 ± 1.34 g kgdiesel −1 for plumes 1, 2, and 3. The rBC emission factor was EF rBC = 0.202 ± 0.052 and 0.202 ± 0.125 g kg-diesel −1 for plumes 1 and 2. The CN emission factor was reduced while ice-breaking from EF CN = 2.41 ± 0.47 to 0.45 ± 0.082 and 0.507 ± 0.037 × 10 16 kg-diesel −1 for plumes 1, 2, and 3. At 0.6 % supersaturation, the CCN emission factor was comparable to observations in mid-latitudes at low engine loads with EF CCN = 3.03 ± 0.933, 1.39 ± 0.319, and 0.650 ± 0.136 × 10 14 kg-diesel −1 for plumes 1, 2, and 3.

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“…load factors (Agrawal et al, 2008(Agrawal et al, , 2010Lack et al, 2008Lack et al, , 2009Moldanova et al, 2009;Murphy et al, 2009;Petzold et al, 2008Petzold et al, , 2010. Further studies have reviewed and compared emission factors (Buhaug et al, 2009;Dalsøren et al, 2009;Lack and Corbett, 2012).…”

Section: International Shipping and Aviationmentioning

confidence: 99%

Global anthropogenic emissions of particulate matter including black carbon

et al. 2017

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Abstract. This paper presents a comprehensive assessment of historical global anthropogenic particulate matter (PM) emissions including the consistent and harmonized calculation of mass-based size distribution (PM 1 , PM 2.5 , PM 10 ), as well as primary carbonaceous aerosols including black carbon (BC) and organic carbon (OC). The estimates were developed with the integrated assessment model GAINS, where source-and region-specific technology characteristics are explicitly included. This assessment includes a number of previously unaccounted or often misallocated emission sources, i.e. kerosene lamps, gas flaring, diesel generators, refuse burning; some of them were reported in the past for selected regions or in the context of a particular pollutant or sector but not included as part of a total estimate. Spatially, emissions were calculated for 172 source regions (as well as international shipping), presented for 25 global regions, and allocated to 0.5 • × 0.5 • longitude-latitude grids. No independent estimates of emissions from forest fires and savannah burning are provided and neither windblown dust nor unpaved roads emissions are included.We estimate that global emissions of PM have not changed significantly between 1990 and 2010, showing a strong decoupling from the global increase in energy consumption and, consequently, CO 2 emissions, but there are significantly different regional trends, with a particularly strong increase in East Asia and Africa and a strong decline in Europe, North America, and the Pacific region. This in turn resulted in important changes in the spatial pattern of PM burden, e.g. European, North American, and Pacific contributions to global emissions dropped from nearly 30 % in 1990 to well below 15 % in 2010, while Asia's contribution grew from just over 50 % to nearly two-thirds of the global total in 2010. For all PM species considered, Asian sources represented over 60 % of the global anthropogenic total, and residential combustion was the most important sector, contributing about 60 % for BC and OC, 45 % for PM 2.5 , and less than 40 % for PM 10 , where large combustion sources and industrial processes are equally important. Global anthropogenic emissions of BC were estimated at about 6.6 and 7.2 Tg in 2000 and 2010, respectively, and represent about 15 % of PM 2.5 but for some sources reach nearly 50 %, i.e. for the transport sector. Our global BC numbers are higher than previously published owing primarily to the inclusion of new sources.This PM estimate fills the gap in emission data and emission source characterization required in air quality and climate modelling studies and health impact assessments at a regional and global level, as it includes both carbonaceous and non-carbonaceous constituents of primary particulate matter emissions. The developed emission dataset has been used in several regional and global atmospheric transport and climate model simulations within the ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) project and beyo...

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Emissions from main propulsion engine on container ship at sea

Cited by 88 publications

References 43 publications

Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM

Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM

Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker <i>Amundsen</i> from the <i>Polar 6</i> aircraft platform

Global anthropogenic emissions of particulate matter including black carbon

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Emissions from main propulsion engine on container ship at sea

Cited by 88 publications

References 43 publications

Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM

Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM

Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker &lt;i&gt;Amundsen&lt;/i&gt; from the &lt;i&gt;Polar 6&lt;/i&gt; aircraft platform

Global anthropogenic emissions of particulate matter including black carbon

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Product

Resources

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Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker <i>Amundsen</i> from the <i>Polar 6</i> aircraft platform