Anthony J. Marchese
Other affiliations: Rowan University, Carrier Corporation, University College of Engineering ...read more
Bio: Anthony J. Marchese is an academic researcher from Colorado State University. The author has contributed to research in topics: Combustion & Natural gas. The author has an hindex of 32, co-authored 120 publications receiving 3343 citations. Previous affiliations of Anthony J. Marchese include Rowan University & Carrier Corporation.
Papers published on a yearly basis
Environmental Defense Fund1, University of Texas at Austin2, Pennsylvania State University3, Stanford University4, Harvard University5, National Institute of Standards and Technology6, University of Michigan7, Washington State University8, Colorado State University9, Princeton University10, Earth System Research Laboratory11, University of Colorado Boulder12, Carnegie Mellon University13, Purdue University14, University of Cincinnati15
TL;DR: The magnitude of this leakage was reassessed and it was found that in 2015, supply chain emissions were ∼60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions.
Abstract: Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.
01 Jan 2007
TL;DR: In this paper, a detailed chemical kinetic model has been used to study methyl butanoate (a model compound for biodiesel fuels) oxidation over a wide range of conditions and experimental results obtained in a jet stirred reactor (JSR) at 0.101 MPa, Φ = 1.13 and 800 T (K) < 1350 were obtained and used to test and modify an earlier model.
Abstract: A detailed chemical kinetic model has been used to study methyl butanoate (a model compound for biodiesel fuels) oxidation over a wide range of conditions. New experimental results obtained in a jet stirred reactor (JSR) at 0.101 MPa, Φ = 1.13 and 800 < T (K) < 1350 were obtained and used to test and modify an earlier model. In addition, new experimental data generated in an opposed-flow diffusion flame at 0.101 MPa and in the Princeton variable pressure flow reactor (VPFR) at 1.266 MPa, 0.35 < Φ < 1.5 and 500 < T (K) < 900 are presented and compared against the revised model. The numerical model consists of 295 chemical species and 1498 chemical reactions and gives a good description of the data. Experimentally, the oxidation of methyl butanoate shows very little low temperature and negative temperature coefficient behaviour, with hot ignition occurring at about 800 K. Modeling results show similar diminished low temperature oxidation character, but reasonably reproduce hot ignition behaviour found in the VPFR. At higher temperature conditions, the model well describes the intermediate species found in the jet stirred reactor and in opposed flow diffusion flame experiments.
TL;DR: In this paper, a semi-empirical mechanism for n-heptane oxidation and pyrolysis has been developed and validated against several independent data sets, including new flow reactor experiments.
Abstract: A new semi-empirical mechanism for n-heptane oxidation and pyrolysis has been developed and validated against several independent data sets, including new flow reactor experiments. Previous semi-empirical chemical kinetic mechanisms assumed that a generic n-alkyl radical, formed by abstraction of an H-atom from the parent fuel, thermally decomposes into a fixed ratio of methyl and propene. While such an approach has been reasonably successful in predicting premixed, laminar flame speeds, the mechanism lacks sufficient detail to quantitatively capture transient phenomena and intermediate species distributions. The new chemical kinetic mechanism retains significantly more detail, yet is sufficiently compact to be used in combined fluid-mechanical/chemical kinetic computational studies. The mechanistic approach is sufficiently general to be extended to a wide variety of large linear and branched alkane fuels.
Environmental Defense Fund1, Cooperative Institute for Research in Environmental Sciences2, University of Michigan3, Washington State University4, University of Houston5, Colorado State University6, Princeton University7, Carnegie Mellon University8, Purdue University9, University of Colorado Boulder10, National Oceanic and Atmospheric Administration11, University of Cincinnati12
TL;DR: This work reconciles top-down and bottom-up methane emissions estimates in one of the country’s major natural gas production basins using easily replicable measurement and data integration techniques and reduces uncertainty in top- down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution.
Abstract: Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency’s Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%.
TL;DR: The variation in methane emissions also appears driven by differences between inlet and outlet pressure, as well as venting and leaking equipment.
Abstract: Facility-level methane emissions were measured at 114 gathering facilities and 16 processing plants in the United States natural gas system. At gathering facilities, the measured methane emission rates ranged from 0.7 to 700 kg per hour (kg/h) (0.6 to 600 standard cubic feet per minute (scfm)). Normalized emissions (as a % of total methane throughput) were less than 1% for 85 gathering facilities and 19 had normalized emissions less than 0.1%. The range of methane emissions rates for processing plants was 3 to 600 kg/h (3 to 524 scfm), corresponding to normalized methane emissions rates <1% in all cases. The distributions of methane emissions, particularly for gathering facilities, are skewed. For example, 30% of gathering facilities contribute 80% of the total emissions. Normalized emissions rates are negatively correlated with facility throughput. The variation in methane emissions also appears driven by differences between inlet and outlet pressure, as well as venting and leaking equipment. Substantial venting from liquids storage tanks was observed at 20% of gathering facilities. Emissions rates at these facilities were, on average, around four times the rates observed at similar facilities without substantial venting.
01 Jul 2004
TL;DR: In this article, the authors developed a center to address state-of-the-art research, create innovating educational programs, and support technology transfers using commercially viable results to assist the Army Research Laboratory to develop the next generation Future Combat System in the telecommunications sector that assures prevention of perceived threats, and non-line of sight/Beyond line of sight lethal support.
Abstract: Home PURPOSE OF THE CENTER: To develop the center to address state-of-the-art research, create innovating educational programs, and support technology transfers using commercially viable results to assist the Army Research Laboratory to develop the next generation Future Combat System in the telecommunications sector that assures prevention of perceived threats, and Non Line of Sight/Beyond Line of Sight lethal support.
01 Jan 2018
TL;DR: In this paper, the updates implemented in EPA's 2020 inventory of U.S. GHG emissions and sinks for gathering and boosting (G&B) stations were discussed, and additional considerations for G&B were previously discussed in memoranda released November 2019 (Inventory of GHG Emissions and Sinks 1990-2018: Updates Under Consideration for Natural Gas Gathering & Boosting Station Emissions).
Abstract: This memorandum documents the updates implemented in EPA’s 2020 Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) for gathering and boosting (G&B) stations. Additional considerations for G&B were previously discussed in memoranda released November 2019 (Inventory of U.S. Greenhouse Gas Emissions and Sinks 1990-2018: Updates Under Consideration for Natural Gas Gathering & Boosting Station Emissions),1 October 2018 (Inventory of U.S. GHG Emissions and Sinks 1990-2017: Updates Under Consideration for Natural Gas Gathering & Boosting Emissions),2 and April 2019 (Inventory of U.S. GHG Emissions and Sinks 1990-2017: Updates to Natural Gas Gathering & Boosting Pipeline Emissions).3
Université Paris-Saclay1, Commonwealth Scientific and Industrial Research Organisation2, Goddard Space Flight Center3, Stanford University4, Yale University5, National Oceanic and Atmospheric Administration6, Netherlands Institute for Space Research7, VU University Amsterdam8, Chiba University9, Japan Agency for Marine-Earth Science and Technology10, Linköping University11, University of California, Irvine12, National Institute of Water and Atmospheric Research13, New York University14, Seconda Università degli Studi di Napoli15, École Polytechnique16, Stockholm University17, Skidmore College18, University of Victoria19, Babeș-Bolyai University20, National Institute of Geophysics and Volcanology21, California Institute of Technology22, Met Office23, University of Reading24, International Institute for Applied Systems Analysis25, National Institute for Environmental Studies26, City University of New York27, University of Bern28, Max Planck Society29, Purdue University30, European Centre for Medium-Range Weather Forecasts31, Lund University32, University of Bristol33, Geophysical Fluid Dynamics Laboratory34, University of Leicester35, Université du Québec à Montréal36, Peking University37, Massachusetts Institute of Technology38, Lawrence Berkeley National Laboratory39, Southern Cross University40, Auburn University41, Joint Global Change Research Institute42, Food and Agriculture Organization43, Finnish Meteorological Institute44, Imperial College London45, Technical University of Crete46, University of Rochester47, Royal Netherlands Meteorological Institute48, Scripps Institution of Oceanography49, University of Toronto50, University of Maryland, College Park51, Hohai University52
TL;DR: The second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modeling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations) as discussed by the authors.
Abstract: Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.
01 Jan 2015
TL;DR: In this paper, various technologies currently used for dewatering microalgal cultures along with a comparative study of the performances of the different technologies are reviewed and compared, as well as a comparison of the performance of different technologies.
Abstract: Microalgae dewatering is a major obstruction to industrial-scale processing of microalgae for biofuel prodn. The dil. nature of harvested microalgal cultures creates a huge operational cost during dewatering, thereby, rendering algae-based fuels less economically attractive. Currently there is no superior method of dewatering microalgae. A technique that may result in a greater algal biomass may have drawbacks such as a high capital cost or high energy consumption. The choice of which harvesting technique to apply will depend on the species of microalgae and the final product desired. Algal properties such as a large cell size and the capability of the microalgae to autoflocculate can simplify the dewatering process. This article reviews and addresses the various technologies currently used for dewatering microalgal cultures along with a comparative study of the performances of the different technologies.