scholarly journals Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations

2021 ◽  
Vol 21 (23) ◽  
pp. 18101-18121
Author(s):  
Sabour Baray ◽  
Daniel J. Jacob ◽  
Joannes D. Maasakkers ◽  
Jian-Xiong Sheng ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
Climate Change ◽  
Seasonal Pattern ◽  
Methane Emissions ◽  
Process Models ◽  
Anthropogenic Emissions ◽  
Natural Sources ◽  
National Inventory ◽  
Modelling Framework ◽  
Surface Data ◽  
Natural Emissions

Abstract. Methane emissions in Canada have both anthropogenic and natural sources. Anthropogenic emissions are estimated to be 4.1 Tg a−1 from 2010–2015 in the National Inventory Report submitted to the United Nation's Framework Convention on Climate Change (UNFCCC). Natural emissions, which are mostly due to boreal wetlands, are the largest methane source in Canada and highly uncertain, on the order of ∼ 20 Tg a−1 in biosphere process models. Aircraft studies over the last several years have provided “snapshot” emissions that conflict with inventory estimates. Here we use surface data from the Environment and Climate Change Canada (ECCC) in situ network and space-borne data from the Greenhouse Gases Observing Satellite (GOSAT) to determine 2010–2015 anthropogenic and natural methane emissions in Canada in a Bayesian inverse modelling framework. We use GEOS-Chem to simulate anthropogenic emissions comparable to the National Inventory and wetlands emissions using an ensemble of WetCHARTS v1.0 scenarios in addition to other minor natural sources. We conduct a comparative analysis of the monthly natural emissions and yearly anthropogenic emissions optimized by surface and satellite data independently. Mean 2010–2015 posterior emissions using ECCC surface data are 6.0 ± 0.4 Tg a−1 for total anthropogenic and 11.6 ± 1.2 Tg a−1 for total natural emissions. These results agree with our posterior emissions of 6.5 ± 0.7 Tg a−1 for total anthropogenic and 11.7 ± 1.2 Tg a−1 for total natural emissions using GOSAT data. The seasonal pattern of posterior natural emissions using either dataset shows slower to start emissions in the spring and a less intense peak in the summer compared to the mean of WetCHARTS scenarios. We combine ECCC and GOSAT data to characterize limitations towards sectoral and provincial-level inversions. We estimate energy + agriculture emissions to be 5.1 ± 1.0 Tg a−1, which is 59 % higher than the national inventory. We attribute 39 % higher anthropogenic emissions to Western Canada than the prior. Natural emissions are lower across Canada. Inversion results are verified against independent aircraft data and surface data, which show better agreement with posterior emissions. This study shows a readjustment of the Canadian methane budget is necessary to better match atmospheric observations with lower natural emissions partially offset by higher anthropogenic emissions.

scholarly journals Estimating 2010–2015 Anthropogenic and Natural Methane Emissions in Canada using ECCC Surface and GOSAT Satellite Observations

2021 ◽  
Author(s):  
Sabour Baray ◽  
Daniel J. Jacob ◽  
Joannes D. Massakkers ◽  
Jian-Xiong Sheng ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
Seasonal Pattern ◽  
Methane Emissions ◽  
Satellite Observations ◽  
Process Models ◽  
Anthropogenic Emissions ◽  
Natural Sources ◽  
Modelling Framework ◽  
Surface Data ◽  
Atmospheric Observations ◽  
Natural Emissions

Abstract. Methane emissions in Canada have both anthropogenic and natural sources. Anthropogenic emissions are estimated to be 4.1 Tg a−1 from 2010–2015 in the Canadian Greenhouse Gas Inventory. Natural emissions, which are mostly due to Boreal wetlands, are the largest methane source in Canada and highly uncertain, on the order of ~20 Tg a−1 in biosphere process models. Top-down constraints on Canadian methane emissions using atmospheric observations have been limited by the sparse coverage of both surface and satellite observations. Aircraft studies over the last several years have provided snapshot emissions that have been conflicting with inventory estimates. Here we use surface data from the Environment and Climate Change Canada (ECCC) in situ network and space borne data from the Greenhouse Gases Observing Satellite (GOSAT) to determine 2010–2015 anthropogenic and natural methane emissions in Canada in a Bayesian inverse modelling framework. We use GEOS-Chem to simulate anthropogenic emissions comparable to the Canadian inventory and wetlands emissions using an ensemble of WetCHARTS v1.0 scenarios in addition to other minor natural sources. We conduct a comparative analysis of the monthly natural emissions and yearly anthropogenic emissions optimized by surface and satellite data independently. Mean 2010–2015 posterior emissions using ECCC surface data are 6.0 ± 0.4 Tg a−1 for total anthropogenic and 10.5 ± 1.9 Tg a−1 for total natural emissions, where the error intervals represent the 1-σ spread in yearly posterior results. These results agree with our posterior using GOSAT data of 6.5 ± 0.7 Tg a−1 for total anthropogenic and 11.7 ± 1.2 Tg a−1 for total natural emissions. The seasonal pattern of posterior natural emissions using either dataset shows slower to start emissions in the spring and a less intense peak in the summer compared to the mean of WetCHARTS scenarios. We combine ECCC and GOSAT data to evaluate capabilities for sectoral and provincial level inversions and identify limitations. We estimate Energy + Agriculture emissions to be 5.1 ± 1.0 Tg a−1 which is 59 % higher than the National GHG Inventory. We attribute 39 % higher anthropogenic emissions to Western Canada than the prior. Natural emissions are lower across Canada with large downscaling in the Hudson Bay Lowlands. Inversion results are verified against independent aircraft data in Saskatchewan and surface data in Quebec which show better agreement with posterior emissions. This study shows a readjustment of the Canadian methane budget is necessary to better match atmospheric observations with higher anthropogenic emissions partially offset by lower natural emissions.

scholarly journals Methane emissions in the United States, Canada, and Mexico: Evaluation of national methane emission inventories and sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations

2021 ◽  
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Haolin Wang ◽  
Joannes D. Maasakkers ◽  
Yuzhong Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Inverse Analysis ◽  
The United States ◽  
Methane Emissions ◽  
Anthropogenic Emissions ◽  
Emission Inventories ◽  
South Central ◽  
The Us

Abstract. We quantify methane emissions and their 2010–2017 trends by sector in the contiguous United States (CONUS), Canada, and Mexico by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric methane observations. The inversion uses as prior estimate the national anthropogenic emission inventories for the three countries reported by the US Environmental Protection Agency (EPA), Environment and Climate Change Canada (ECCC), and the Instituto Nacional de Ecologia y Cambio Climatico (INECC) in Mexico to the United Nations Framework Convention on Climate Change (UNFCCC), and thus serves as an evaluation of these inventories in terms of their magnitudes and trends. Emissions are optimized with a Gaussian mixture model (GMM) at 0.5° × 0.625° resolution and for individual years. Optimization is done analytically using log-normal error forms. This yields closed-form statistics of error estimates and information content on the posterior (optimized) estimates, allows better representation of the high tail of the emission distribution, and enables construction of a large ensemble of inverse solutions using different observations and assumptions. We find that GOSAT and in situ observations are largely consistent and complementary in the optimization of methane emissions for North America. Mean 2010–2017 anthropogenic emissions from our base GOSAT + in situ inversion, with ranges from the inversion ensemble, are 36.9 (32.5–37.8) Tg a−1 for CONUS, 5.3 (3.6–5.7) Tg a−1 for Canada, and 6.0 (4.7–6.1) Tg a−1 for Mexico. These are higher than the most recent reported national inventories of 26.0 Tg a−1 for the US (EPA), 4.0 Tg a−1 for Canada (ECCC), and 5.0 Tg a−1 for Mexico (INECC). The correction in all three countries is largely driven by a factor of 2 underestimate in emissions from the oil sector with major contributions from the south-central US, western Canada, and southeast Mexico. Total CONUS anthropogenic emissions in our inversion peak in 2014, in contrast to the EPA report of a steady decreasing trend over 2010–2017. This reflects combined effects of increases in emissions from the oil and landfill sectors, decrease from the gas, and flat emissions from the livestock and coal sectors. We find decreasing trends in Canadian and Mexican anthropogenic methane emissions over the 2010–2017 period, mainly driven by oil and gas emissions. Our best estimates of mean 2010–2017 wetland emissions are 8.4 (6.4–10.6) Tg a−1 for CONUS, 9.9 (7.8–12.0) Tg a−1 for Canada, and 0.6 (0.4–0.6) Tg a−1 for Mexico. Wetland emissions in CONUS show an increasing trend of 2.6 (1.7–3.8) % a−1 over 2010–2017 correlated with precipitation.

scholarly journals Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

2020 ◽  
Vol 12 (3) ◽  
pp. 375 ◽  
Author(s):  
Rajesh Janardanan ◽  
Shamil Maksyutov ◽  
Aki Tsuruta ◽  
Fenjuan Wang ◽  
Yogesh K. Tiwari ◽  
...  
Keyword(s):  
United States ◽  
High Resolution ◽  
The United States ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Emissions ◽  
Observation Data ◽  
Scale Analysis ◽  
Uncertainty Range ◽  
Natural Emissions

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.

scholarly journals Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations

2022 ◽  
Vol 22 (1) ◽  
pp. 395-418
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Haolin Wang ◽  
Joannes D. Maasakkers ◽  
Yuzhong Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Inverse Analysis ◽  
The United States ◽  
Methane Emissions ◽  
Anthropogenic Emissions ◽  
Emission Inventories ◽  
South Central ◽  
The Us

Abstract. We quantify methane emissions and their 2010–2017 trends by sector in the contiguous United States (CONUS), Canada, and Mexico by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric methane observations. The inversion uses as a prior estimate the national anthropogenic emission inventories for the three countries reported by the US Environmental Protection Agency (EPA), Environment and Climate Change Canada (ECCC), and the Instituto Nacional de Ecología y Cambio Climático (INECC) in Mexico to the United Nations Framework Convention on Climate Change (UNFCCC) and thus serves as an evaluation of these inventories in terms of their magnitudes and trends. Emissions are optimized with a Gaussian mixture model (GMM) at 0.5∘×0.625∘ resolution and for individual years. Optimization is done analytically using lognormal error forms. This yields closed-form statistics of error covariances and information content on the posterior (optimized) estimates, allows better representation of the high tail of the emission distribution, and enables construction of a large ensemble of inverse solutions using different observations and assumptions. We find that GOSAT and in situ observations are largely consistent and complementary in the optimization of methane emissions for North America. Mean 2010–2017 anthropogenic emissions from our base GOSAT + in situ inversion, with ranges from the inversion ensemble, are 36.9 (32.5–37.8) Tg a−1 for CONUS, 5.3 (3.6–5.7) Tg a−1 for Canada, and 6.0 (4.7–6.1) Tg a−1 for Mexico. These are higher than the most recent reported national inventories of 26.0 Tg a−1 for the US (EPA), 4.0 Tg a−1 for Canada (ECCC), and 5.0 Tg a−1 for Mexico (INECC). The correction in all three countries is largely driven by a factor of 2 underestimate in emissions from the oil sector with major contributions from the south-central US, western Canada, and southeastern Mexico. Total CONUS anthropogenic emissions in our inversion peak in 2014, in contrast to the EPA report of a steady decreasing trend over 2010–2017. This reflects offsetting effects of increasing emissions from the oil and landfill sectors, decreasing emissions from the gas sector, and flat emissions from the livestock and coal sectors. We find decreasing trends in Canadian and Mexican anthropogenic methane emissions over the 2010–2017 period, mainly driven by oil and gas emissions. Our best estimates of mean 2010–2017 wetland emissions are 8.4 (6.4–10.6) Tg a−1 for CONUS, 9.9 (7.8–12.0) Tg a−1 for Canada, and 0.6 (0.4–0.6) Tg a−1 for Mexico. Wetland emissions in CONUS show an increasing trend of +2.6 (+1.7 to +3.8)% a−1 over 2010–2017 correlated with precipitation.

Country scale analysis of natural and anthropogenic methane emissions with a high-resolution inverse model using GOSAT and ground-based observations

2020 ◽  
Author(s):  
Rajesh Janardanan ◽  
Shamil Maksyutov ◽  
Aki Tsuruta ◽  
Fenjuan Wang ◽  
Yogesh Tiwari ◽  
...  
Keyword(s):  
United States ◽  
High Resolution ◽  
The United States ◽  
Methane Emissions ◽  
Inverse Model ◽  
Anthropogenic Emissions ◽  
Observation Data ◽  
Scale Analysis ◽  
Uncertainty Range ◽  
Natural Emissions

&lt;p&gt;Here, we present the results of a global high-resolution inversion study of methane emissions and their analysis for the large emitting countries. We employ a global high-resolution inverse model to optimize CH&lt;sub&gt;4&lt;/sub&gt; emissions using Greenhouse gas Observing Satellite (GOSAT) and surface observation data over the 2011-2017 period for the two main source categories of anthropogenic and natural emissions. As prior emissions, we used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission, scaled by country to match the national emissions reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimate a global total anthropogenic and natural methane emissions of 340.9 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt; and 232.5 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;, respectively. This agrees with recent Global Carbon Project (GCP) estimates of 357 and 215 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;, respectively. Country-scale analysis of the estimated anthropogenic emissions shows that for all the top-emitting countries, differences with their respective nationally reported inventories are within the uncertainty range of the inventories. Large emitting countries such as China, Russia and the United States have mean estimated anthropogenic emission of 45.7&amp;#177;8.6, 31.9&amp;#177;7.8 and 29.8&amp;#177;7.8 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1 &lt;/sup&gt;respectively. For natural emissions, we estimate large emissions for Brazil (39.8&amp;#177;12.4 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;), the United States (25.9&amp;#177;8.3 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;), Russia (13.2&amp;#177;9.3 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;), India (12.3&amp;#177;6.4 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;), and Canada (12.2&amp;#177;5.1 Tg CH&lt;sub&gt;4&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;). In both emission categories, natural and anthropogenic, the major emitting countries all had model corrections to their emissions that were within the uncertainty range of the inventories and the inverse model uncertainty. As a special case, we evaluate anthropogenic emissions estimated for India (24.2&amp;#177;5.3 Tg yr&lt;sup&gt;-1&lt;/sup&gt;) with aircraft observation data over urban regions over India. On average, the optimized profiles showed a better match with the observations compared to the prior profile confirming improved estimates by the model for India.&lt;/p&gt;

scholarly journals Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Kapitza ◽  
Pham Van Ha ◽  
Tom Kompas ◽  
Nick Golding ◽  
Natasha C. R. Cadenhead ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Integrated Modelling ◽  
Land Use Patterns ◽  
Economic Changes ◽  
Use Patterns ◽  
Modelling Framework ◽  
Avian Biodiversity ◽  
Biodiversity Change ◽  
Impacts Of Climate Change

AbstractClimate change threatens biodiversity directly by influencing biophysical variables that drive species’ geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.

scholarly journals Estimating economic damage from climate change in the United States

Science ◽  
2017 ◽  
Vol 356 (6345) ◽  
pp. 1362-1369 ◽  
Author(s):  
Solomon Hsiang ◽  
Robert Kopp ◽  
Amir Jina ◽  
James Rising ◽  
Michael Delgado ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Climate Science ◽  
The United States ◽  
Process Models ◽  
Economic Damage ◽  
Global Mean Temperature ◽  
Flexible Architecture ◽  
Econometric Analyses ◽  
Business As Usual

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors—agriculture, crime, coastal storms, energy, human mortality, and labor—increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).

Are there pre-Quaternary geological analogues for a future greenhouse warming?

2011 ◽  
Vol 369 (1938) ◽  
pp. 933-956 ◽  
Author(s):  
Alan M. Haywood ◽  
Andy Ridgwell ◽  
Daniel J. Lunt ◽  
Daniel J. Hill ◽  
Matthew J. Pound ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Future Climate ◽  
Future Climate Change ◽  
Anthropogenic Emissions ◽  
Earth System ◽  
System Sensitivity ◽  
Earth History ◽  
Scientific Papers

Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race’s current grand climate experiment . This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean–atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene–Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO 2 forcing—whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate—or the sensitivity of the climate system itself to CO 2 was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO 2 ) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO 2 concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO 2 thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate.

scholarly journals High Summertime Aerosol Organic Functional Group Concentrations from Marine and Seabird Sources at Ross Island, Antarctica, during AWARE

2018 ◽  
Author(s):  
Jun Liu ◽  
Jeramy Dedrick ◽  
Lynn M. Russell ◽  
Gunnar I. Senum ◽  
Janek Uin ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Austral Summer ◽  
Acid Group ◽  
Hydroxyl Group ◽  
Anthropogenic Emissions ◽  
Natural Factor ◽  
Natural Sources ◽  
Organic Composition ◽  
West Antarctic ◽  
The Fourier Transform

Abstract. From November 2015 to December 2016, the ARM West Antarctic Radiation Experiment (AWARE) measured submicron aerosol properties near McMurdo Station at the southern tip of the Ross Island. Submicron organic mass (OM), particle number, and cloud condensation nuclei concentrations were higher in summer than other seasons. The measurements included a range of compositions and concentrations that likely reflected both local anthropogenic emissions and natural background sources. We isolated the natural organic components by separating a natural factor and a local combustion factor. The natural OM was 150 times higher in summer than in winter. The local anthropogenic emissions were not hygroscopic and had little contribution to the CCN concentrations. Natural sources that included marine sea spray and seabird emissions contributed 56 % of OM in the austral summer but only 3 % in the austral winter. The natural OM had high hydroxyl group fraction (55 %), 6 % alkane, and 6 % amine group mass, consistent with marine organic composition. In addition, the Fourier transform infrared (FTIR) spectra showed the natural sources of organic aerosol were characterized by amide group absorption, which may be from seabird populations. Carboxylic acid group contributions from natural sources were correlated to incoming solar radiation, indicating that some OM formed by secondary pathways.

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