The world's energy challenges are multi-dimensional. Meeting growing demand, while also protecting the environment, will require an integrated series of solutions. Expanding all commercially viable energy sources, developing and deploying technology to help mitigate the growth of emissions, and accelerating gains in energy efficiency are all essential elements.
Energy efficiency is one of the largest and lowest-cost ways to extend our world's energy supplies and reduce greenhouse gas emissions. Between 1980 and 2005, nearly half the increase in global energy demand was met by improvements in energy efficiency. Further gains in energy efficiency through 2030 will curb demand growth by about 65 percent.
At ExxonMobil, we are taking actions to reduce energy usage and emissions in our own operations, and we are working on energy-efficient products and technologies that will help manufacturers and consumers do the same. On the operations side, we have invested 1.6 billion dollars since 2006 in activities that improve energy efficiency and reduce greenhouse gas emissions. Through our own actions, greenhouse gas emissions are down over 12 million tonnes since 2005, equivalent to removing about 2.5 million cars from U.S. roads.
Through deployment of our proprietary Global Energy Management System (GEMS), we have identified opportunities to improve the energy efficiency of our refineries and chemical plants by 15-20 percent. A strong focus on operation and maintenance of existing equipment, coupled with energy efficient design of new facilities, enabled us to achieve best-ever energy efficiency in 2010. We are on track to achieve our goal of improving energy efficiency across our worldwide refining and chemical operations by at least 10 percent from 2002-2012.
On the consumer side, we have developed a variety of technologies that are available today, including lighter-weight vehicle parts, improved tire liners, energy-efficient synthetic lubricants and lithium-ion battery separator films. We are also working on a number of breakthrough technologies to help power next generation lower-emission vehicles, and we continue to sponsor strategic research into ways to make alternatives like solar, hydrogen and biofuels more affordable for use on a broader scale.
Improving energy efficiency is more than just good business. It is a triple-winner that benefits companies, consumers, and the environment alike. More efficient operations extend the supply and affordability of conventional energy resources, while reducing plant operating costs and greenhouse gas emissions. Unlike other options, which may require trillions of dollars and decades to develop, improving energy efficiency can make a significant difference today.
CO2 capture and sequestration is inevitable. The concentration of the CO2 in the atmosphere is increasing continuously which will cause global warming among other consequences. Among storage options, the underground storage in depleted oil and gas reservoirs and unminable coals are considered the most economical storage options. On the other hand, natural gas consumption, which is considered to be a clean fuel, has increased significantly during the past years. Therefore seeking for new unconventional energy resources, especially gas seems to be inevitable. This goal is followed not only because of economical benefits but also because of environmental issues we are encountering these days.
The purpose of this study is to develop an Artificial Neural network (ANN) tool to predict the important performance indicators such as methane recovered and CO2 injected, which are critical in CO2 storage projects in coal seams. We have combined the simulation method with artificial intelligence tools to predict the complex behavior of coal bed methane (CBM) reservoirs.
In the first step a simulation is done using CMG software. A dual porosity model, which accounts for the optimum conditions during CO2 sequestration and consequently the optimum methane recovery from coal bed reservoirs was developed. Then the data extracted from the simulated CBM reservoir was employed to train the ANN model. Different parameters related to the coal seam such as porosity, permeability, initial pressure, thickness, temperature and initial water saturation are considered as the input for the network. The outputs are the CO2 injected and the recovered methane, which show the performance of the
CO2 injection project. The Back-Propagation learning algorithm was used and different transfer functions and numbers of hidden layers were tried to find the best model with the least error. The tested neural network predictions were plotted versus the real data available and also different error analyses were carried out to prove the accuracy of the model. The R-Squared for the predicted values for the CO2 injected and the recovered methane were 0.92 and 0.94; the average percent arithmetic deviations were 4.8% and 4.5% respectively.
Emissions associated to energy generation depend on the source of supply - which varies from polluting oil thermal units to clean renewables. This paper assesses the quality of supply in terms of associated emissions and, more importantly, load management strategies targeting a cleaner energy supply. We propose a framework where each consumer may know the impact of his (her) load management in terms of emissions and the associated economic costs. It will be then possible to clearly identify each consumer's possible "green initiative?? action and associated tariffs. We hope this will be the first step towards a transparent, society-supported sustainable future.
Index Terms--demand side management, smart green, green energy, carbon management, emission reduction
RENEWABLE energy's main benefits are well known: thermal displacement and associated emission reduction.
Moreover, smart grid advances open a whole new world on demand and network management, uncovering to consumers information about the emissions associated to their load and providing them an efficient control over their carbon footprint.
The green option, however, comes with a price: renewables may be more expensive than traditional thermal units. It is important to - far from deny it - know the price tag and build an incentive structure able to cover expenses.
This work is based on the "smart green"  concept and proposes a signal structure able to provide the consumer the whole picture: his impact on emissions and available cleaner options - of course, with the associated price.
The model targets initially the non-regulated clients, which concentrate the huge network consumption and are used to monitor and control their peak load. Further extensions could include residential and smaller consumers, after a wide and explanatory campaign.
CO2 injection and storage in deepwater sediments under water depths greater than 9,000 feet (˜2,750 meters) where high pressures and low temperatures result in the CO2 being denser than seawater and therefore being buoyantly trapped in the sediments pore-fluid, could provide an attractive sequestration option for countries and regions densely populated and emitting large quantities of anthropogenic CO2 such as East and West Coasts of the United States of America, Japan, the East Coast of China and Western Europe. In these places, public opinion, government regulatory agencies, a lack of space for CO2 injection sites and few depleted oil and gas fields available necessitate the application of alternative technologies to sequester CO2 in order to mitigate a significant part of the 30 billion tons of CO2 annually released in the Earth's atmosphere.
This paper presents the results of multiple reservoir simulations and parametric studies for different types of deepwater sediments located in various regions of the globe (Pacific Ocean, Atlantic Ocean, Japan Sea and Gulf of Mexico). Since not all regions and sediments deposited below 9,000 feet of ocean waters seem to be viable to permanently store CO2, this study focuses on the critical parameters that need to be considered to successfully inject and permanently store liquid CO2 in deepwater sub-seabed sediments.
In fact, when injecting liquid CO2 through an ultra-deepwater conduit (injection pressurized riser) within the first few hundreds of sediments, several uncertain variables such as temperature, sediment type, sediment thickness, permeability, porosity and CO2 injectability greatly influence the overall integrity of the buoyant trap. Very long-time reservoir simulations (e.g. 250 years) have been used to assess the effects of different decision and uncertain variables on the behavior and the evolution of the CO2 plume within the sediments. Also, experimental design and response surface methodologies have been used to quantify the risk associated with each of the critical parameters and to determine the optimal conditions for deepwater sediments CO2 storage. Finally, the essential findings of the paper provide the offshore and carbon sequestration industries with a high-level mapping of the world's oceans and deep seas best candidates for CO2 storage in deepwater sediments.
We present a new mathematical model for simulating the operation of a blast furnace with top gas recycling. The model of the blast furnace, a physical-chemical model, was built using commercial process flowsheeting software. All of the important reactions and processes were taken into account, e.g. iron oxide reduction, coke and coal combustion, coal gasification, heat transfer. Coke and coal are the fossil solid fuels used in blast furnaces, the former being made by baking the latter.
Steel industry contributes to about 6% of the anthropogenic greenhouse gas emissions, mostly through CO2. Reducing CO2 emission has become a priority in steel industry, as exemplified by the European ULCOS program, which targeted achieving mid-term >50% reduction through the use of new technologies. Recycling the exhaust top gas from blast furnace, the principal and most CO2 emitting steelmaking reactor, is one of the promising technologies selected by ULCOS. In a top gas recycling blast furnace, CO2 contained in the top gas is removed and the remaining stream, rich in reducing agents H2 and CO, is heated
and re-injected into the blast furnace at two levels, the shaft and tuyeres, at different temperatures and flow rates. Captured CO2 is then piped to be stored geologically.
We simulated different operations of the blast furnace, without top gas recycling and with recycling at one level (tuyeres) and at two levels (tuyeres and shaft). The higher the recycled flowrate, the lower the coke consumption. Up to 25% carbon (coke + coal) saving can be obtained with 90% recycling. These simulations were found to be in good agreement with reported data from a pilot blast furnace in Lulea, Sweden.
By using top gas recycling coupled with the storage of CO2, the blast furnace CO2 emissions could be reduced by 75%. Besides, the model developed provides us with a full inventory of the flows, which respects mass and heat balances. The next step is to use these results as the inventory for life cycle assessment to evaluate the global environmental impact of the new process in different configurations.
Keywords: CO2 emissions, blast furnace, mathematical model, process simulation, steelmaking, recycling, CO2 storage.
The Illinois Basin - Decatur Project (IBDP) plans to inject one million tonnes of carbon dioxide (CO2) into the Mt. Simon Formation over a three-year period, starting in late 2011. Uncertainty analyses that were conducted at successive stages of the project have been used to evaluate the impact of additional data on the uncertainty in reservoir performance predictions.
Reservoir simulators are predictive tools that help the project team evaluate the injectivity, storage capacity and containment capabilities of a reservoir for carbon capture and storage (CCS) projects. Simulation studies for IBDP started in 2008 using general regional data. Over time, reservoir models have increased in complexity and have become more representative of the Mt. Simon Formation as more data have been acquired.
An initial uncertainty analysis used models based on two-dimensional (2D) seismic data and available logs from a nearby well. After drilling the injection and monitoring wells at the storage site, petrophysical measurements were obtained that enabled a detailed sensitivity analysis to identify parameters that are critical to injectivity, CO2 migration, and corresponding pressure pulse evolution. This information helped reduce the number of uncertain parameters and their ranges for the second uncertainty analysis. Lastly, after gathering three-dimensional (3D) seismic data, results of special core analysis, and injectivity tests, the reservoir model and uncertainty ranges of other input parameters were updated for a final iteration of pre-injection uncertainty analysis.
Results of the first uncertainty analysis helped the project team identify an uncertainty envelope of possible CO2 migration scenarios. The second stage of uncertainty analysis targeted wide ranges in reservoir performance predictions, indicating several reservoir parameters on which to focus additional characterization efforts. A more complete, final round of uncertainty analysis produced manageable ranges of predicted uncertainties and a credible basis of reservoir performance expectations prior to the operational phase of the project. Results of this analysis can be used to identify the area of review (AoR) for permitting, priority and placement of monitoring tools, as well as timing of repeat surveys and scenarios for injection schemes in the near future.
Combustion and gasification of pulverized coal have been investigated experimentally for the conditions under high temperature gradient and CO2-rich atmospheres with 5% and 10% O2. Crushed coal samples were heated rapidly by a CO2 gas laser beam to give a high temperature gradient of order 100 °C!s-1 in order to simulate radiation heat transfer conditions expected in coal gasification furnaces. The rapid heating is able to minimize effects of coal oxidation and combustion compared with previous studies with a TG-DTA that requires much longer time to heat up with oxidation effect. Moreover, coal-water mixture samples with different water/coal mass ratio were used in order to investigate roles of water vapor on the combustion and gasification. The experimental results indicated that coal weight reduction ratio or coal conversion ratio to gases follows the Arrhenius equation with increasing coal temperature; in addition, coal weight reduction ratio of the sample was increased around 5% with adding H2O in CO2-rich atmosphere. Furthermore, generations of CO gas and Hydrocarbons gases (HCs) were mainly dependent on coal temperature and O2 concentration, however, those are also affected by chemical reactions including H2O. Especially, reactions generating CO and HCs gases were stimulated at temperature over 1000 °C in the CO2-rich atmosphere with 5% O2.
Keywords: coal, coal-water mixture; combustion and gasification; temperature gradient; CO2 gas laser beam
According to the IEA statistics (2007) , CO2 emission from fossil energy consumption in China was accounted for about 19% of global CO2 emission, of which coal-fired power plants occupied about 30% of total CO2 emission in China. Conventional coal fired boilers use air for combustion in which N2 gas is 79% in volume ratio, and it dilutes the CO2 gas concentration in the flue gas. CO2 capture cost from flue gases using amine stripping is expected to be relatively high . Consequently, a new zeroemission coal gasification with CO2 and Oxygen combustion technology has been studied for new coal fired power plants [3,4],
such as Integrated Gasification Combined Cycle (IGCC), including CO2 Capture and Storage (CCS). In this type of plants, recycled flue gas is used to control flame temperature and make up the volume of the missing N2 gas to ensure there is enough gas to generate energy in a gas turbine and heat in a steam boiler. As a consequence, a flue gas consisting mainly CO2 and water steam are generated, thus CO2 can be easily separated by condensation . In addition, pulverized coal fired power plants could be the best candidates to install CO2 capture system, of which oxy-fuel or CO2/O2 combustion technology is one of promising methods to evade problems of CO2 separation .
New Zealand is a comparatively "green?? country with respect to land-cover, with approximately 39% land area under pasture and 31% under exotic and native forest. Throughout New Zealand's history conversion between forest and pasture has been a major land-use change. Forests contain a large amount of carbon stored in the plant biomass compared with pasture; however, trees reflect less incoming radiation compared with grass. The reduction in albedo increases the radiative forcing and hence negates some of the benefit of carbon storage. This paper examines the relationship between the radiative forcing due to reduction of albedo and the CO2 absorption when converting pasture land to forest. Previous studies have used a linear approximation of the highly non-linear relationship in the analysis. However, this approximation significantly overestimates the amount of CO2 uptake required to compensate for typical changes in albedo. This paper describes three commonly used non-linear functions that can more accurately calculate CO2 uptake required to balance albedo changes. Results are presented for New Zealand plantation and indigenous forests. Five different forest types were investigated, and without accounting for the albedo effect the forests captured on average between 0.64 and 1.86 kg CO2/m2/yr over a 50-year period. Accounting for the increased radiative forcing due to the reduction in albedo by 7 % reduced the equivalent CO2 removal from the atmosphere to between 0.18 and 0.80 kg CO2/m2/yr. Changing albedo by only 5 % instead of 7 % will increase the equivalent CO2 removal rate from the atmosphere by 0.012 kg CO2/m2/yr.
Carbon capture and geological storage (CCS) is a core element in the global strategy to reduce greenhouse gas (GHG) emissions. This paper characterizes and contrasts the emission quantification methods associated with CCS projects from the perspective of voluntary emission reduction initiatives and recent regulatory reporting requirements under the U.S. Environmental Protection Agency (EPA) Greenhouse Gas Reporting Program (GHGRP).
From the regulatory perspective, the U.S. EPA is addressing the mandatory GHG reporting for CO2 injection and potential geological storage, providing a different approach for facilities that supply CO2 to the market, those that inject CO2 for purposes of enhanced oil and gas recovery, and those that are engaging in long-term geological storage. Information gathered under the GHGRP will enable EPA to track the amount of CO2 supplied to the market, injected, and/or stored by U.S. facilities. In addition, where the CO2 injection facilities are also associated with other oil and gas operations, the GHGRP requires quantifying and reporting GHG emissions from those operations where the facilities meet specified regulatory thresholds. This information will be a key element in providing baseline data and activity information for the development of future emission standards and control techniques for GHG emission mitigation in the U.S.
In addition to reporting initiatives, industry is providing guidance to support voluntary GHG reduction initiatives. The American Petroleum Institute (API) and the International Petroleum Industry Environmental Conservation Association (IPIECA) have collaborated on a guideline document to promote the credible, consistent, and transparent quantification of GHG emission reductions from CCS projects (IPIECA/API, 2007). This document emphasizes that the entire range of activities associated with CCS - capture, transport, injection and storage - must be considered in quantifying emissions and emission reductions from CCS operations.
This paper will examine common aspects and notable differences between the mandatory reporting programs and voluntary GHG emission reduction activities. It will specifically emphasize collateral characteristics such as the scope of emission sources, accuracy of quantification methods, reporting and monitoring requirements.
Introduction to CCS
CCS applies established technologies to capture, transport and store CO2 emissions from large point sources. Wide deployment of CCS techniques is viewed as essential for addressing climate change, while also providing energy security, creating jobs, and economic prosperity. The International Energy Agency (IEA) states that CCS could reduce global CO2 emissions by 19%, and that without CCS, overall costs to reduce emissions to 2005 levels by 2050 would increase by 70% (IEA, 2009).
CCS refers to the chain of processes that are designed to collect or capture a CO2 gas stream, transport the CO2 to a storage location, and inject the CO2 into a geological formation1 for long-term isolation from the atmosphere (See Figure 1). CCS involves avoiding the release of CO2 emissions to the atmosphere by injecting CO2 and ultimately storing it in a geological formation. The assessment of GHG emission reductions from CCS projects should address all of these elements.
The technology for EOR with CO2, well established for over 50 years, is now being used to mitigate carbon emissions through their capture and storage in deep geologic formations. Mobility control in CO2 flooding is critical for improving CO2 sweep efficiency and optimization of CO2 storage capacity. The potential weaknesses of surfactant-stabilized CO2 foam, such as lack of long-term stability and adsorption loss, increase the operation cost significantly. The results presented in this paper will provide an alternative for CO2 mobility control, in which the weakness caused by using surfactant, we believe, can be avoided.
In this paper, we present a process for generating nanoparticle-stabilized CO2 foam, in which nanoparticles, instead of surfactant, were used to generate and stabilize CO2 foam in a static solution. The paper also describes the effects of different factors such as particle concentration, brine salinity, pressure, temperature, and surfactant, on CO2 foam generation. The results of this research demonstrated that supercritical CO2 foam was successfully generated in a static sapphire tube with the aid of nanoparticles. Particle size was determined to be in the range of 100-150 nm. The experimental results revealed that stable CO2 foam was generated in a 0.5% nanosilica dispersion at 1500 psi and 25°C. The height of the foam in the observation cell was used to characterize CO2 foam stability. It was also observed that, as the nanosilica concentration was lower than 0.3% or higher than 1.0%, only a little CO2 foam was generated. Temperature and brine salinity were observed to have similar effects on CO2 foam generation. As the temperature and brine salinity increased, less CO2 foam was observed. On the contrary, pressure had a different effect on CO2 foam generation. When the pressure was increased from 1200 psi to 2000 psi, more CO2 foam was generated in the observation cell. With a small amount of surfactant adding to nanosilica dispersion can improve CO2 foam generation.