Errors and uncertainties in a gridded carbon dioxide emissions inventory

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO₂), gridded EI Open-source Data Inventory for Anthropogenic CO₂ (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges.

     

High-resolution spatial distribution of greenhouse gas emissions in the residential sector

The development of high-resolution greenhouse gas (GHG) inventories is an important step towards emission reduction in different sectors. However, most of the spatially explicit approaches that have been developed to date produce outputs at a coarse resolution or do not disaggregate the data by sector. In this study, we present a methodology for assessing GHG emissions from the residential sector by settlements at a fine spatial resolution. In many countries, statistical data about fossil fuel consumption is only available at the regional or country levels. For this reason, we assess energy demand for cooking and water and space heating for each settlement, which we use as a proxy to disaggregate regional fossil fuel consumption data. As energy demand for space heating depends heavily on climatic conditions, we use the heating degree day method to account for this phenomenon. We also take the availability of energy sources and differences in consumption patterns between urban and rural areas into account. Based on the disaggregated data, we assess GHG emissions at the settlement level using country and regional specific coefficients for Poland and Ukraine, two neighboring countries with different energy usage patterns. In addition, we estimate uncertainties in the results using a Monte Carlo method, which takes uncertainties in the statistical data, calorific values, and emission factors into account. We use detailed data on natural gas consumption in Poland and biomass consumption for several regions in Ukraine to validate our approach. We also compare our results to data from the EDGAR (Emissions Database for Global Atmospheric Research), which shows high agreement in places but also demonstrates the advantage of a higher resolution GHG inventory. Overall, the results show that the approach developed here is universal and can be applied to other countries using their statistical information.

     

Principles for retrofitting coal burners for oxy-combustion

Experiments were performed in a 1.5 MW pilot-scale furnace to investigate the differences between air- and oxy-fired flame behavior from a pulverized coal oxy-research burner designed for flexible operating conditions. The flame behavior was characterized by recording video images of the flames and by measuring radiation intensity along the flame length. Various strategies relating air- and oxy-fired operation of the burner primary register were investigated where the oxy-fired burner primary mass, momentum and velocity were matched to the air-fired conditions. Matching either burner primary mass or momentum under oxy-fired conditions with air-fired conditions resulted in a flame stabilized within the quarl. Matching primary velocity with air-fired conditions resulted in a detached flame indicating a delay in flame ignition for the oxyfired conditions. A decrease in primary velocity of 13% was necessary in order to stabilize a flame within the quarl similar to the air-fired case. Additional experiments also showed a flame could be stabilized with no oxygen enrichment of the primary (～3 vol.%, dry O₂ in the primary). Experiments where oxygen was injected at the burner face indicated injection at the boundary of the primary and secondary flow paths strongly attach a flame and injection at the coal rich primary flow path increased the radiative intensity of the flame.     

High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector

Mitigation and Adaptation Strategies for Global Change - Agricultural activity plays a significant role in the atmospheric carbon balance as a source and sink of greenhouse gases (GHGs) and has...     

Quantifying greenhouse gas emissions

Mitigation and Adaptation Strategies for Global Change - The assessment of greenhouse gases (GHGs) and air pollutants emitted to and removed from the atmosphere ranks high on international...     

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO₂, CH₄, N₂O, SO₂, NMVOC) as well as total emissions in the CO₂-equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.