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South Park, WY, United States

Consol Energy Inc. /kənˈsɒl/ is an American energy company with interests in coal and natural gas production headquartered in the suburb of Cecil Township, in the Southpointe complex, just outside of Pittsburgh, Pennsylvania. Consol Energy is the leading producer of high-BTU bituminous coal in the United States and the U.S.'s largest underground coal mining company. As of 2011, Consol had 4.4 billion tons of proven reserves, mainly in northern and central Appalachia and produced nearly 64 million tons of coal in 2010. The company has natural gas reserves totaling 3.7 trillion cu. ft. as of 2011 and employs more than 8,800 people. Wikipedia.


Winberg S.,CONSOL Energy Inc
28th Annual International Pittsburgh Coal Conference 2011, PCC 2011 | Year: 2011

• FutureGen is back on the fast track • FutureGen 2.0 represents one of the world's best prospects for a fully integrated near-zero emission project • Oxy-combustion • Minimum 90% capture on the entire plant • COs2 pipeline network • COs2 storage hub in deep saline formation • Positioned for success • >$1 billion in funding firmly allocated • Right partners with the right expertise • Strong community support • Liability management framework.


Bilonick R.A.,University of Pittsburgh | Connell D.P.,CONSOL Energy Inc | Talbott E.O.,University of Pittsburgh | Rager J.R.,University of Pittsburgh | Xue T.,University of Pittsburgh
Atmospheric Environment | Year: 2015

The objective of this study was to remove systematic bias among fine particulate matter (PM2.5) mass concentration measurements made by different types of samplers used in the Pittsburgh Aerosol Research and Inhalation Epidemiology Study (PARIES). PARIES is a retrospective epidemiology study that aims to provide a comprehensive analysis of the associations between air quality and human health effects in the Pittsburgh, Pennsylvania, region from 1999 to 2008. Calibration was needed in order to minimize the amount of systematic error in PM2.5 exposure estimation as a result of including data from 97 different PM2.5 samplers at 47 monitoring sites. Ordinary regression often has been used for calibrating air quality measurements from pairs of measurement devices; however, this is only appropriate when one of the two devices (the "independent" variable) is free from random error, which is rarely the case. A group of methods known as "errors-in-variables" (e.g., Deming regression, reduced major axis regression) has been developed to handle calibration between two devices when both are subject to random error, but these methods require information on the relative sizes of the random errors for each device, which typically cannot be obtained from the observed data. When data from more than two devices (or repeats of the same device) are available, the additional information is not used to inform the calibration. A more general approach that often has been overlooked is the use of a measurement error structural equation model (SEM) that allows the simultaneous comparison of three or more devices (or repeats). The theoretical underpinnings of all of these approaches to calibration are described, and the pros and cons of each are discussed. In particular, it is shown that both ordinary regression (when used for calibration) and Deming regression are particular examples of SEMs but with substantial deficiencies. To illustrate the use of SEMs, the 7865 daily average PM2.5 mass concentration measurements made by seven collocated samplers at an urban monitoring site in Pittsburgh, Pennsylvania, were used. These samplers, which included three federal reference method (FRM) samplers, three speciation samplers, and a tapered element oscillating microbalance (TEOM), operated at various times during the 10-year PARIES study period. Because TEOM measurements are known to depend on temperature, the constructed SEM provided calibration equations relating the TEOM to the FRM and speciation samplers as a function of ambient temperature. It was shown that TEOM imprecision and TEOM bias (relative to the FRM) both decreased as temperature increased. It also was shown that the temperature dependency for bias was non-linear and followed a sigmoidal (logistic) pattern. The speciation samplers exhibited only small bias relative to the FRM samplers, although the FRM samplers were shown to be substantially more precise than both the TEOM and the speciation samplers. Comparison of the SEM results to pairwise simple linear regression results showed that the regression results can differ substantially from the correctly-derived calibration equations, especially if the less-precise device is used as the independent variable in the regression. © 2014 Elsevier Ltd.


Connell D.P.,CONSOL Energy Inc | Lewandowski D.A.,Clean Energy Engineering | Ramkumar S.,Ohio State University | Phalak N.,Ohio State University | And 2 more authors.
Fuel | Year: 2013

The Calcium Looping Process (CLP) is being developed to facilitate carbon dioxide (CO2) capture during the production of hydrogen (H 2) from syngas. The process integrates CO2, sulfur, and halide removal with the water-gas shift (WGS) reaction in a single-stage reactor. In the CLP, a regenerable calcium oxide (CaO) sorbent is used to chemically react with and remove CO2 and other acid gases from syngas at high temperature (i.e., 550-700 °C). The removal of CO2 drives the WGS reaction forward via Le Chatelier's principle, obviating the need for a WGS catalyst and enabling the production of high-purity H2. The spent sorbent is heated in a calciner to regenerate CaO for reuse in the process and to release a concentrated CO2 stream, which can be dried and sequestered. The regenerated sorbent is then reactivated in a hydrator, to improve its recyclability, before being reintroduced into the H2 production reactor. Techno-economic analyses were performed to evaluate the application of the CLP to a coal-to-H2 plant, a steam methane reforming (SMR) plant, and an integrated gasification-combined cycle (IGCC) plant, all including ≥90% CO2 capture. In each case, use of the CLP resulted in a 9-12% reduction in the cost of H2 or cost of electricity when compared with the use of conventional CO2 capture and WGS technologies. The economic advantage afforded by the CLP is realized because of the large amount of high-quality heat produced in the process, which is recovered to raise steam for electricity generation. This heat arises from the combustion of supplemental fuel in the CLP calciner and from the exothermic CO2 removal, WGS, and hydration reactions, which are carried out at high temperature (i.e., ≥500 °C) in the CLP. As a result of recovering this heat, the CLP-based coal-to-H2 and SMR plants, which are designed to produce 26,000 kg/h H2, necessarily co-produce 320 MWe and 190 MWe of net electric power, respectively. Although the CLP can reduce the cost of producing H2 from coal, the resulting cost is still about 26% greater than the cost of H2 produced from natural gas using conventional WGS and CO2 capture technologies, assuming coal and natural gas prices of $1.55/GJ and $6.21/GJ, respectively. The lowest cost of H2 with CO 2 capture for these fuel prices is achieved by applying the CLP to an SMR plant. © 2012 Elsevier Ltd. All rights reserved.


Trademark
CONSOL Energy Inc | Date: 2014-06-25

Computer programs for use in measuring, modelling and analyzing eneregy use and performance and recommending energy efficiency improvements in structures, and user manuals provided as a unit; computer software for use in measuring, modelling and analyzing eneregy use and performance and recommending energy efficiency improvements in structures that may be downloaded from a global computer network, and user manuals provided as a unit. Promoting public awareness of the need for energy efficiency; providing information to promote energy efficiency and information concerning energy auditing and energy usage management on the global information network; computer services, namely providing interactive on-line information in the field of energy efficiency, energy auditing and energy usage management; energy usage management, namely, measuring, modelling and analyzing energy use and performance and recommending energy efficiency improvements in structures; association services, namely promoting the interest of energy efficiency analysts and raters. Inspections of energy efficiency in structures in the course of building construction. Training analysts and raters in the field of energy efficiency, energy auditing, energy usage and inspections of energy efficiency in structures. Consultation and research in the field of energy efficiency; inspections of energy efficiency in structures not in the course of building construction; measurement evaluations in the field of energy efficiency; reviewing standards and practices to assure compliance with building energy codes, laws and regulations.


Trademark
CONSOL Energy Inc | Date: 2015-06-09

Coal.

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