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Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2009) (V. 2012)

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

54 ENVIRONMENTAL SCIENCES↗

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2010) (V. 2013)

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

54 ENVIRONMENTAL SCIENCES↗

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2011) (1950 - 2010)

The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

54 ENVIRONMENTAL SCIENCES↗

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude - 2015

The monthly, fossil-fuel CO2 emissions estimates from 1950-2011 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2015), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Andres, R.J.↗

Mexico city aerosol analysis during MILAGRO using high resolution aerosol mass spectrometry at the urban supersite (T0) - Part 2: Analysis of the biomass burning contribution and the non-fossil carbon fraction

Submicron aerosol was analyzed during the MILAGRO field campaign in March 2006 at the T0 urban supersite in Mexico City with a High-Resolution Aerosol Mass Spectrometer (AMS) and complementary instrumentation. Positive Matrix Factorization (PMF) of high resolution AMS spectra identified a biomass burning organic aerosol (BBOA) component, which includes several large plumes that appear to be from forest fires within the region. Here, we show that the AMS BBOA concentration at T0 correlates with fire counts in the vicinity of Mexico City and that most of the BBOA variability is captured when the FLEXPART model is used for the dispersion of fire emissions as estimated from satellite fire counts. The resulting FLEXPART fire impact factor (FIF) correlates well with the observed BBOA, acetonitrile (CH3CN), levoglucosan, and potassium, indicating that wildfires in the region surrounding Mexico City are the dominant source of BBOA at T0 during MILAGRO. The impact of distant BB sources such as the Yucatan is small during this period. All fire tracers are correlated, with BBOA and levoglucosan showing little background, acetonitrile having a well-known tropospheric background of {approx}100-150 pptv, and PM2.5 potassium having a background of {approx}160 ng m3 (two-thirds of its average concentration), which does not appear to be related to BB sources. We define two high fire periods based on satellite fire counts and FLEXPART-predicted FIFs. We then compare these periods with a low fire period when the impact of regional fires is about a factor of 5 smaller. Fire tracers are very elevated in the high fire periods whereas tracers of urban pollution do not change between these periods. Dust is also elevated during the high BB period but this appears to be coincidental due to the drier conditions and not driven by direct dust emission from the fires. The AMS oxygenated organic aerosol (OA) factor (OOA, mostly secondary OA or SOA) does not show an increase during the fire periods or a correlation with fire counts, FLEXPART-predicted FIFs or fire tracers, indicating that it is dominated by urban and/or regional sources and not by the fires near the MCMA. A new 14C aerosol dataset is presented. Both this new and a previously published dataset of 14C analysis suggest a similar BBOA contribution as the AMS and chemical mass balance (CMB), resulting in 13% higher non-fossil carbon during the high vs. low regional fire periods. The new dataset has {approx}15% more fossil carbon on average than the previously published one, and possible reasons for this discrepancy are discussed. During the low regional fire period, 38% of organic carbon (OC) and 28% total carbon (TC) are from non-fossil sources, suggesting the importance of urban and regional non-fossil carbon sources other than the fires, such as food cooking and regional biogenic SOA. The ambient BBOA/CH3CN ratio is much higher in the afternoon when the wildfires are most intense than during the rest of the day. Also, there are large differences in the contributions of the different OA components to the surface concentrations vs. the integrated column amounts. Both facts may explain some apparent disagreements between BB impacts estimated from afternoon aircraft flights vs. those from 24-h ground measurements. We show that by properly accounting for the non-BB sources of K, all of the BB PM estimates from MILAGRO can be reconciled. Overall, the fires from the region near the MCMA are estimated to contribute 15-23% of the OA and 7-9% of the fine PM at T0 during MILAGRO, and 2-3% of the fine PM as an annual average. The 2006 MCMA emissions inventory contains a substantially lower impact of the forest fire emissions, although a fraction of these emissions occur just outside of the MCMA inventory area.

09 BIOMASS FUELS↗

Exopaleontology and the search for a fossil record on Mars

Although present Martian surface conditions appear unfavorable for life as we know it, there is compelling geological evidence that the climate of early Mars was much more Earth-like, with a denser atmosphere and abundant surface water. The fact that life developed on the Earth within the first billion years of its history makes it quite plausible that life may have also developed on Mars. If life did develop on Mars, it is likely to have left behind a fossil record. This has led to the development of a new subdiscipline of paleontology, herein termed 'exopaleontology', which deals with the exploration for fossils on other planets. The most important factor enhancing microbial fossilization is the rapid entombment of microorganisms by fine-grained, stable mineral phases, such as silica, phosphate, or carbonate. The oldest body fossils on Earth are preserved in this way, occurring as permineralized cells in fine-grained siliceous sediments (cherts) associated with ancient volcanic terranes in Australia and South Africa. Modern terrestrial environments where minerals may precipitate in the presence of microorganisms include subaerial thermal springs and shallow hydrothermal systems, sub-lacustrine springs and evaporitic alkaline lakes, zones of mineralization within soils where 'hardpans' (e.g. calcretes, silcretes) form, and high latitude frozen soils or ground ice.

Farmer, Jack D.↗

Impacts of Wind and Solar on Fossil-Fueled Generators: Preprint

High penetrations of wind and solar power will impact the operations of the remaining generators on the power system. Regional integration studies have shown that wind and solar may cause fossil-fueled generators to cycle on and off and ramp down to part load more frequently and potentially more rapidly. Increased cycling, deeper load following, and rapid ramping may result in wear-and-tearimpacts on fossil-fueled generators that lead to increased capital and maintenance costs, increased equivalent forced outage rates, and degraded performance over time. Heat rates and emissions from fossil-fueled generators may be higher during cycling and ramping than during steady-state operation. Many wind and solar integration studies have not taken these increased cost and emissions impactsinto account because data have not been available. This analysis considers the cost and emissions impacts of cycling and ramping of fossil-fueled generation to refine assessments of wind and solar impacts on the power system.

01 COAL, LIGNITE, AND PEAT↗

sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields

The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, "A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.

Source record↗

Assessing Fossil Fuel and Feedstock Use in the U.S. Plastics and Rubber Sector: A Supply Chain Analysis

In plastics and rubber manufacturing, fossil fuels are consumed both as an energy source and as feedstocks that are converted to higher-value products. For example, in the manufacture of polyethylene, natural gas is consumed both as a fuel and as a feedstock during ethylene production. In this work, we expand on the U.S. Department of Energy's Bandwidth Study on Energy Use and Potential Energy Savings Opportunities in U.S. Plastics and Rubber Manufacturing, which quantified onsite fuel consumption and the potential for reducing fuel consumption by increasing energy efficiency in the plastics and rubber sector. The bandwidth study did not quantify fuel consumed upstream in the supply chain or as a feedstock; however, both contribute significantly to a plastic's total fossil fuel requirements. The U.S. Energy Information Administration's 2014 Manufacturing Energy Consumption Survey (MECS) estimates that fossil fuels consumed as feedstocks account for approximately 74% of total fossil fuel consumption in the U.S. plastic resin manufacturing sector (NAICS 325211). We employ the Materials Flows through Industry (MFI) supply chain modeling tool, developed at the National Renewable Energy Laboratory (NREL), to quantify process fuel and feedstock requirements within the supply chains of the same 10 categories of plastics and rubber commodities covered in the DOE bandwidth report. From these results, we identify supply chains that will have a high feedstock requirement even when energy efficiency is increased. We then use MFI to analyze several alternative plastics supply chains, including those utilizing biomass feedstocks and/or polyethylene terephthalate (PET) waste upcycling, to determine if these alternatives can potentially reduce both process fuel and feedstock requirements within the supply chains of interest. This presentation will include a case study comparison of supply chain energy consumption for petroleum-derived and bio-derived fiberglass reinforced plastic involving a novel waste PET upcycling technique recently discovered by NREL researchers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Toward Verifying Fossil Fuel CO2 Emissions with the CMAQ Model: Motivation, Model Description and Initial Simulation

Motivated by the urgent need for emission verification of CO2 and other greenhouse gases, we have developed regional CO2 simulation with CMAQ over the contiguous U.S. Model sensitivity experiments have been performed using three different sets of inputs for net ecosystem exchange (NEE) and two fossil fuel emission inventories, to understand the roles of fossil fuel emissions, atmosphere-biosphere exchange and transport in regulating the spatial and diurnal variability of CO2 near the surface, and to characterize the well-known ‘signal-to-noise’ problem, i.e. the interference from the biosphere on the interpretation of atmospheric CO2 observations. It is found that differences in the meteorological conditions for different urban areas strongly contribute to the contrast in concentrations. The uncertainty of NEE, as measured by the difference among the three different NEE inputs, has notable impact on regional distribution of CO2 simulated by CMAQ. Larger NEE uncertainty and impact are found over eastern U.S. urban areas than along the western coast. A comparison with tower CO2 measurements at Boulder Atmospheric Observatory (BAO) shows that the CMAQ model using hourly varied and high-resolution CO2 emission from the Vulcan inventory and CarbonTracker optimized NEE reasonably reproduce the observed diurnal profile, whereas switching to different NEE inputs significantly degrades the model performance. Spatial distribution of CO2 is found to correlate with NOx, SO2 and CO, due to their similarity in emission sources and transport processes. These initial results from CMAQ demonstrate the power of a state-of-the art CTM in helping interpret CO2 observations and verify fossil fuel emissions. The ability to simulate CO2 in CMAQ will also facilitate investigations of the utility of traditionally regulated pollutants and other species as tracers to CO2 source attribution.

CMAQ↗

Life cycle greenhouse gas emissions and energy use of polylactic acid, bio-derived polyethylene, and fossil-derived polyethylene

Bioplastics recently have become an attractive, viable, and popular alternative to conventional petroleum-based plastics, with the hope that replacing fossil-derived plastics with renewable alternatives will reduce greenhouse gas (GHG) emissions and fossil energy consumption (FEC). The bioplastic industry is encouraging creative designs and enhanced properties such as biodegradability, which is considered a sustainable solution for waste plastic management. However, biodegradability also means that carbon in the product is emitted to the atmosphere as GHG emissions. In this paper, a life cycle analysis (LCA) of biodegradable polylactic acid (PLA) and bio-polyethylene (bio-PE) plastics was conducted to understand the environmental effects of these bioplastics from feedstock production to product end-of-life (EOL). In particular, emissions from biodegradability (EOL emissions) are accounted for. The results were compared to those of conventional fossil-based plastics such as high-density polyethylene (HDPE) and low-density polyethylene (LDPE). Results showed that the lowest GHG emissions (-1.0 and 1.7 kg CO 2 e per kg for bio-PE and PLA with no biodegradation, respectively) and FEC (29 and 46 MJ per kg of bio-PE and PLA, respectively) were achieved with bio-derived plastics, particularly bio-PE plastic. However, despite the benefits of biogenic carbon uptake, when landfill and composting emissions were considered for the PLA pathway, the life cycle emissions of PLA increase significantly, from 16% to 163% depending on the biodegradation condition, compared to the case where there is no degradation in the landfill. This study also contributed to understand the effects on the GHG emissions of biodegradability in landfill and composting scenarios, regional electricity mix, and plastics manufacturing technologies. (C) 2020 The Authors. Published by Elsevier Ltd.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fossil and biogenic CO{sub 2} from waste incineration based on a yearlong radiocarbon study

Highlights: Black-Right-Pointing-Pointer Yearlong radiocarbon study on the share of biogenic CO{sub 2} from waste incineration. Black-Right-Pointing-Pointer Direct approach combining temporal integrating gas sampling and {sup 14}CO{sub 2} analysis by AMS. Black-Right-Pointing-Pointer Significant differences between incinerators with 43% and 54%Fos C. Black-Right-Pointing-Pointer No annual cycle of fossil CO{sub 2} for all, except one, of the included incinerators. - Abstract: We describe the first long-term implementation of the radiocarbon ({sup 14}C) method to study the share of biogenic (%Bio C) and fossil (%Fos C) carbon in combustion CO{sub 2}. At five Swiss incinerators, a total of 24 three-week measurement campaigns were performed over 1 year. Temporally averaged bag samples were analyzed for {sup 14}CO{sub 2} by accelerator mass spectrometry. Significant differences between the plants in the share of fossil CO{sub 2} were observed, with annual mean values from 43.4 {+-} 3.9% to 54.5 {+-} 3.1%. Variations can be explained by the waste composition of the respective plant. Based on our dataset, an average value of 48 {+-} 4%Fos C was determined for waste incineration in Switzerland. No clear annual trend in %Fos C was observed for four of the monitored incinerators, while one incinerator showed considerable variations, which are likely due to the separation and temporary storage of bulky goods.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Cost and Performance Baseline for Fossil Energy Plants - Volume 3b: Low Rank Coal to Electricity: Combustion Cases

The Cost and Performance Baseline for Fossil Energy Power Plants Study, Volume 3b: Low Rank Coal to Electricity establishes performance and cost data for fossil energy power systems, specifically pulverized coal (PC) and circulating fluidized bed combustor (CFBC) plants all with and without carbon capture and sequestration. The analyses were performed on a consistent technical and economic basis that accurately reflects current market conditions. The study serves as a benchmark to track the progress of DOE Advanced Power Systems R&D and as a baseline for analyzing fossil energy plant options.

01 COAL, LIGNITE, AND PEAT↗

Cost and Performance Baseline for Fossil Energy Plants - Volume 3c: Natural Gas Combined Cycle at Elevation

The Cost and Performance Baseline for Fossil Energy Power Plants Study, Volume 3b: Low Rank Coal to Electricity establishes performance and cost data for fossil energy power systems, specifically pulverized coal (PC) and circulating fluidized bed combustor (CFBC) plants all with and without carbon capture and sequestration. The analyses were performed on a consistent technical and economic basis that accurately reflects current market conditions. The study serves as a benchmark to track the progress of DOE Advanced Power Systems R&D and as a baseline for analyzing fossil energy plant options.

03 NATURAL GAS↗

Cost and Performance Baseline for Fossil Energy Plants - Volume 3a: Low Rank Coal to Electricity: IGCC Cases

The goal of Fossil Energy Research, Development, and Demonstration (RD&D) is to ensure the availability of ultra-clean (“zero” emissions), abundant, low-cost, domestic electricity and energy (including hydrogen) to fuel economic prosperity and strengthen energy security. A broad portfolio of technologies is being developed within the Clean Coal Program to accomplish this objective. Ever increasing technological enhancements are in various stages of the research “pipeline,” and multiple paths are being pursued to create a portfolio of promising technologies for development, demonstration, and eventual deployment. The technological progress of recent years has created a remarkable new opportunity for coal. Advances in technology are making it possible to generate power from fossil fuels with great improvements in the efficiency of energy use while at the same time significantly reducing the impact on the environment, including the long-term impact of fossil energy use on the Earth’s climate. The objective of the Clean Coal RD&D Program is to build on these advances and bring these building blocks together into a new, revolutionary concept for future coal-based power and energy production.

01 COAL, LIGNITE, AND PEAT↗

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction, A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

01 COAL, LIGNITE, AND PEAT↗

Low-Cost Sulfur Thermal Storage for Increased Flexibility and Improved Economics of Fossil-Fueled Electricity Generating Units (Final Report)

The US electric grid relies on conventional fossil fuel power plants for reliable and secure power, but these plants suffer from physical and financial strain due to the influx of inexpensive and variable solar and wind electricity. Conventional power plants need to generate electricity flexibly and on-demand to accommodate these renewable resources on the grid. Integrating a low-cost thermal energy storage (TES) gives fossil assets the ability to regulate their output efficiently and optimize the plant operation to maximize revenue in the wholesale electricity market. Element 16’s TES concept uses sulfur, a byproduct of the oil & gas industry, as the storage media that is 10 times cheaper than molten salt used in commercial two-tank TES technology. In this project, the team completed a detailed feasibility and technoeconomic study establishing the impact, cost and performance of molten sulfur TES system integrated with fossil assets.

20 FOSSIL-FUELED POWER PLANTS↗

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751 - 2008) (V. 2011)

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2008.html) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

54 ENVIRONMENTAL SCIENCES↗