Deriving CO2 emissions of localized sources from OCO-3 XCO2 and TROPOMI NO2 satellite data

<p>Carbon dioxide (CO<sub>2</sub>) is the most important anthropogenic greenhouse gas and the main driver of global warming. Its atmospheric concentrations have risen more than 40% since pre-industrial times. Almost 90% of this increase results from fossil fuel combustion, emitting CO<sub>2</sub> predominantly from localized sources. In order to track the reduction efforts to comply with the objectives of the Paris Agreement, emissions need to be monitored. For this purpose, bottom-up emission estimates are regularly reported in the national greenhouse gas inventories. Top-down observation-based estimates can complement and verify these inventories. Satellite observations have an important role in this context, since they can provide global information.</p> <p>Due to CO<sub>2</sub>'s long lifetime and large fluxes of natural origin, the column-average concentrations resulting from anthropogenic emissions from individual source points are usually small compared to the background concentration, and these enhancements are often barely larger than the satellite's instrument noise. This makes the detection of CO<sub>2</sub> emission plumes and the quantification of anthropogenic fluxes challenging.</p> <p>NO<sub>2</sub> is co-emitted with CO<sub>2</sub> in the combustion of fossil fuels. It has a much shorter lifetime, and as a result, its vertical column densities can exceed background values and sensor noise by orders of magnitude in emission plumes. This makes it a suitable tracer for recently emitted CO<sub>2</sub>.</p> <p>The objective of this study is to quantify the CO<sub>2</sub> emissions from localized sources such as power plants by using XCO<sub>2</sub> (the column-averaged dry air mole fraction of CO<sub>2</sub>) retrievals from the Orbiting Carbon Observatory 3 (OCO-3) in its snapshot area mode. Our presentation describes a plume detection method using NO<sub>2</sub> as a tracer for recently emitted CO<sub>2</sub> and an inversion technique to quantify CO<sub>2</sub> emissions from detected CO<sub>2</sub> plumes.</p>

The analysis of carbon footprint of the settlement activity in the village of Pedurungan District, Semarang City, Central Java Province

Some important sectors influenced the increase of greenhouse gases, such as waste, transportation, settlement, and agricultural sectors. This research aimed to analyze the amount of CO2 emissions, map the carbon footprint, and analyze tree capability in reducing CO2 in 12 villages in Pedurungan district, Semarang city, Central Java. The method used was based on IPCC Guidelines for National Greenhouse Gas Inventories 2006 and Ministry of Environment 2012 about the Implementation of National Greenhouse Gas Inventories Guidelines. The carbon footprint was mapped using ArcGIS software. The results showed that the energy sector produced 13.723,35 tons CO2 Eq, the transportation sector emitted 1.624,58 tons CO2 Eq, and the waste sector emitted 7.677,08 CO2 Eq. The carbon footprint map was presented in three classifications of carbon footprint: lower, middle, and upper, represented by green, yellow, and red colors. An effort to reduce the carbon footprint was planting 300 trees of ten species in the Pedurungan district.

European anthropogenic AFOLU greenhouse gas emissions: a review and benchmark data

Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990–2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).

Analysis of Emission of Greenhouse Gases from Road Transport in Poland between 1990 and 2017

The paper provides the results of the inventory of greenhouse gases (GHGs) from road transport in Poland over the period 1990–2017. To estimate GHGs’ emission from road transport, a standardized methodology was applied, consistent with 2006 IPCC Guidelines for National Greenhouse Gas Inventories and EEA/EMEP Emission Inventory Guidebook 2019, as well as the COPERT 5 software. In the analysis, emissions of fossil carbon dioxide, methane and nitrous oxide were taken into account. Emissions of all considered GHGs were converted to equivalent carbon dioxide. Throughout the subsequent years of emission inventory, emissions of all GHGs revealed an increasing trend, except for methane. The main cause underlying this increase is the dynamic development of motorization in Poland. Thus, GHGs’ emissions were analyzed, taking into account the number of road vehicles and the intensity of their use. An increase in the average specific distance emission was found for fossil carbon dioxide (by ca. 5%) and for nitrous oxide (by ca. 10%), while for methane, there was a decrease (by more than 150%). The GHGs’ emissions from road transport in Poland could be significantly lower if more emphasis was placed on the use of fuels from renewable energy sources.

Tackling climate change reporting needs regarding soil C pool: SOC modelling under different land-use categories in Croatia

<p>Soil organic matter (SOM) is one of five mandatory pools used in reporting of national greenhouse gas inventories under UNFCCC and EU regulations. Reporting on net change in soil organic carbon (SOC) under different land uses over time is challenging. The 2006 IPCC Guidelines for National Greenhouse Gas Inventories suggest that all estimates, including carbon (C) in SOM, should be transparent and consistent throughout the time series. For some countries assessing net change of SOC is often not easy due to lack of data, infrastructure or funding. Consequently, for the mineral part of the soil, frequently used is the simplest approach of assessment (Tier 1) which assumes no change in mineral SOC stocks. However, this assumption should be substantiated.</p><p>There is a growing need for the use of higher tiers in reporting of C changes in SOM pool, by providing estimates from field measurements and modelling. While soil C modelling is cost-effective, and in some countries already found applicable for the purpose of reporting, field measurements of soil C stocks are expensive and time-consuming, but necessary for model calibration and validation.</p><p>In our research we used Biome-BGCMuSo model, a biogeochemical model that simulates the storage and flux of water, C, and nitrogen (N) in the soil-plant-atmosphere system. Biome-BGCMuSo is a new variant of the well‑known Biome-BGC model with an improved multilayer soil module. We performed spatial modelling of SOC down to 30 cm for four different land-use categories of: deciduous forests, evergreen forests, annual croplands and grasslands, for the period 1990-2014. Eco-physiological parameters for each biome (i.e. land-use) were obtained from the literature. Meteorological data was obtained from open-access meteorological database FORESEE. Management activities (i.e. thinning, planting, mowing, fertilizing, and ploughing) where estimated based on available data and consultations with the local experts. Modelling results of SOC stocks were compared to field measurements. Trends of soil C change in period 1990-2014 under different land-uses were discussed.</p>

Estimation of possible impact of black carbon emissions from 2019 large Siberian forest wildfires on the Arctic region

<p>The presented study is aimed to estimate the probability of black carbon transportation from large forest wildfires in Russian boreal taiga occurred in the summer 2019 to Arctic region and to estimate its deposition to ice surface and contribution to shortwave radiative forcing.</p><p>The extreme forest fires were observed in 2019 over the territories of Krasnoyarskiy region and Yakutia republic. The Russian Informational Remote monitoring System of the Federal Forestry Agency provides data on the areas of forest lands damaged by different types of fires. These data were used to choose ten most intensive and ten most continuous fires for each region. Estimation of fuel mass available for combustion including biomass, litter and deadwood were made using the growing stock data of the State Forestry Register differentiated for the regions of the Russian Federation applying country specific conversion coefficients [Schepaschenko et al. 2018]. Emission of black carbon from forest fires was carried out using the methodology and combustion coefficients from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories and the coefficient of black carbon emissions from Akagi et al. [2011].</p><p>The main factor determining the transfer of particles is the synoptic situation. Blocking anticyclones and cyclonic series affects the circulation regime and conditions for the transport of particles to the Arctic. For these regions climatic frequency of occurrence of Southern and South-Western winds in summer is about 30-40%. The probability of atmospheric trajectory transfer from each chosen fire event to the Arctic region was estimated by the trajectory model HYSPLIT, also real synoptic data for each chosen fire event were used to analyze the probability of emission cloud transfer to northern latitudes.</p><p>The black carbon effect including concentrations in the atmosphere, deposition on the ice surface, modification of surface albedo in the ice region of Arctic and influence of additional radiation forcing associated with BC emissions from forest fires were estimates using the climate model INMCM5 [Volodin et a.l., 2017]. Aerosol sources, advection, gravitational sedimentation, surface absorption, and scavenging by precipitation are taken into account to compute aerosol concentration variations. Radiation forcing caused by BC emission from forest fires was calculated using the SNICAR model.</p><p> </p><p>The study is supported by RFBR project No.18-05-60183.</p><p> </p><p>REFERENCES</p><p>Volodin E. M., Mortikov E. V., Kostrykin S. V., Galin V. Ya., Lykossov V. N., Gritsun A.S., Diansky N. A., Gusev A. V., Yakovlev N.G. Simulation of the present-day climate with the climate model INMCM5, Climate Dynamics, 2017, doi:10.1007/s00382-017-3539-7.</p><p>2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 4: Agriculture, Forestry and Other Land Use (IPCC, 2006</p><p>K. Akagi, R. J. Yokelson, C. Wiedinmyer, M. J. Alvarado, J. S. Reid, T. Karl, J. D. Crounse, and P. O. Wennberg, “Emission factors for open and domestic biomass burning for use in atmospheric models,” Atmos. Chem. Phys. 11 (9), 4039–4072 (2011).</p><p>Schepaschenko D., Moltchanova E., Shvidenko A., Blyshchyk V., Dmitriev E., Martynenko O., See L., Kraxner F. (2018) Improved Estimates of Biomass Expansion Factors for Russian Forests // Forests. – 9, 312. P. 1-23. – https://doi.org/10.3390/f9060312</p>