Carbon capture and storage - Wikipedia
Timothy F. Alien and inquiry populations, communities. Essentially nothing is Years ago a fishing and canoeing friend said that it said about the relation between systems of interest was only an historical accident that he and I were both i. Although at an even strongly, e. This earlier time there was indeed some commonality has strong implications when invalidated simple popu- amongst ecologists, probably because most were trained lation models, such as the spruce budworm example using E.
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Few readers will have sufficient ingly splintered, causing enormous confusion to some experience to understand how weak and erroneous new adherents, interested outsiders and, probably far most such examples are, although I suppose they have more than appreciated. The first chapter ends with good themselves. The overall ap- things that have at one time or another been consid- proach is related to issues of scale and hierarchy. A look at the figures shows a series that Allen has been associated with for some time. The of interesting patterns, but little consistent devclop- book starts with an introductory chapter on principles ment.
Fair enough. Is this what we want to tell our new sense discussions of the need to consider scales above graduate students? What do I do if they give me these and below the level of interest. The relation examples given: the discussion of salmon linking. Related Papers. By Stanislav Shmelev. Economics of industrial ecology: Materials, structural change, and spatial scales.
By Marco Janssen. Ecological economics: themes, approaches, and differences with environmental economics.
Reducing CO2 Emissions
By Muhammad Aamir. By MInaolen Minaolen. By Faye Duchin. Download pdf. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. Table 2 presents CO 2 -eq emissions related to Mexican energy consumption and production in and estimations of a baseline scenario for , as well as the variation in percentage. Changes in final demand carry a total emission increase of 3.
The total CO 2 -eq emissions impact matrix was calculated according to Equation 10 and is presented in Table A1. Table 1.
Sectors for input-output analysis: sector code. The largest emissions come from the road transport sector. Figure 1 presents the sectorial relation between DE vs. TE known as the Rasmussen  classification discussed in   that expresses the degree in which one industry output is used by other industries as an input. In this case, this grouping is based on the comparison of the median values of the sectorial DE and TE in a logarithmic scale. Table 5 shows the meaning of each region. Table 2. Baseline scenario. A large discussion of Rasmussen method is developed in .
It corresponds to a Classical Multiplier Method  . Although there are new developments in the methods developed to analyze interlinkages among industrial sectors, this method is very useful in identifying total and distribution effects, particularly in the analysis of the economic impacts of GHG mitigation   . The sectors located in region I of Figure 1 are the construction and automotive sectors.
These sectors use inputs of other productive processes, that is to say their consumption is influenced by the demand of other sectors.
Consequently, mitigation policies that could affect the magnitude of their production might generate problems in their economic activity. Table 3. A reduction in its final demand would have large impacts on economy and small impacts on emissions. In Region II we can find the following sectors: road transport, electric power generation, brewages, chemistry, agriculture, iron and steel, commerce, oil and gas extraction, air transportation, and other sectors.
Changes in final demand of these specific sectors have a large influence on total emissions, and changes in final demand of other sectors also have large impacts on emissions of these specific sectors. A demand reduction in these sectors will have a large influence on emissions, but also might have a large influence on economic activity. Table 4. Figure 1. Distributive effects vs.
A Comparative Input-Output-Study for Germany and the UK
Table 5. Regions in Figure 1. The sugar industry and the cement industry are the sectors in Region III. Changes in final demand of these specific sectors have a large influence on total emissions, but changes in final demand of other sectors have small impacts on emissions of these specific sectors. In Region IV are less relevant sectors in terms of final demand and emissions. A reduction in CO 2 -eq emissions of these sectors will not have an important impact on overall emissions, because the share in the distribution of emissions is low.
Another important observation from Figure 1 is how construction and cement in region III are linked. It is possible to connect a line with both sectors that crosses the mean values the center of the graphic. TE of the construction sector that affects the cement sector is the same amount as the DE of the cement sector received from the construction sector. Hence, if the final demand of sector 21 decreases, the emissions from sector 14 will also decrease.
This relation also means that if the cement for construction is substituted with other materials, emissions from sector 14 will decrease. In this paper, an input-output methodology is developed to analyze energy-re- lated GHG emissions of the Mexican economy. The paper also analyzes total and distributive effects that final demand has on emissions levels. It also identifies Own Sector Effects OE that result from the changes in the final demand of each Own Sector the diagonal elements of matrix , and Structure Effects SE that result from the changes in other sectors of the economy.
Strategies 3 and 4 are related to a reduction in material or product production and will have an important effect on the economy, particularly in those sectors that appear in Region II. The alignment of strategies to fulfill the goals of the NDC requires additional analysis. Additional work is necessary to evaluate policies. The results presented in this paper are a useful tool for a GEM for the Mexican economy. Table A1. Nature, , In: Metz, B. The Review of Economics and Statistics, 18, Economic Systems Research, 13, Ecological Economics, 68, Springer-Verlag, Berlin Heidelberg, Energy Policy, 38, Energy, 37, Energy Economics, 40, Communications in Nonlinear Science and Numerical Simulation, 18, Energy, 82, Journal of Cleaner Production, , Journal of Cleaner Production.
Energy, 78, Economic Systems Research, 24, Energy Policy, 56, Energy, 91, American Economic Review, 86, Structural Change and Economic Dynamics, 6, Climate Change, , Report No. American Economic Journal: Economic Policy, 8, Economic Systems Research, 7, Ecological Economics, 61, Energy Policy, 31, Input-Output Matrixes. Energy Policy, 62, Economic Systems Research, 27, Economic Systems Research, 26, Economic Systems Research, 28, Tourism Economics, 21, In: Edenhofer, O. Share This Article:. The paper is not in the journal. Go Back HomePage.
DOI: The elasticity of emissions with respect to national demand is calculated in order to identify the total and distributed effects of CO 2 equivalent CO 2 -eq emissions. In this framework, the analysis evaluates the effects in the economy related to changes in individual sector demands, and, vice versa, the effect on individual sectors due to global changes in national demands.
Results show that passenger and freight transport, power generation, iron and steel industry, chemical industry, air transportation and agriculture concentrate the largest potential for mitigation strategies, and also have important distributive effects on the Mexican economy.
Carbon capture and storage
Methodological Framework and Data Sources According to input-output methodology, the economy can be decomposed on n sectors that produce and exchange goods or services. The input-output basic equation, also known as the Leontief equation is the following: 1 where is the total sectorial production, which is the sum of final demand and consumption among all sectors of economy, is the final sectorial demand, and is the Leontief matrix, where is the identity matrix and A is formed by that denotes the amount of product from sector i that is needed to produce one unit of product by sector j in monetary terms.
Then is the total carbon dioxide emissions CO 2 -eq of the economy related to fossil fuel combustion: 2 Let be the emission intensity, defined as the quantity of CO 2 -eq per unit of output of sector i. But substituting x i from Equation 1 : 3 For the objective of this paper, the change in sectorial emissions due to the changes in final demand is then: 4 Let us define the elasticity of total CO 2 -eq emissions due to changes in final demand of sector j as . This allows distinguishing between sectors whose production is mainly for satisfying final demand and those whose production is used as inputs by other sectors, therefore: 6 But considering 1 , 6 can be expressed as the multiplication of two matrixes: 7 This matrix expression gives us the total emission variation of the economy due to a unitary change in final demand of all n sectors.
Considering the definition of the elements , if we construct a column vector whose elements represent a percentage of increase on sectorial final demand, and multiply them by the matrix , then the result must be the sectorial percentage of increase in CO 2 -eq emissions in response to changes of all final demands: 11 where the 0 super index indicates the final demand in year 0, and 1 indicates the final demand at the end of an arbitrary time period.
Let vector be multiplied by matrix then: 12 where is the i-th element of vector. Total, Distributive, and Structural Effects From Equation 9 , it is possible to analyze different effects that final demand has on emissions levels. Data Sources The input-output model constructed in this work comes from a combination of two different databases available in Mexico, in addition to the IPCC emission factors .
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Results and Analysis Table 2 presents CO 2 -eq emissions related to Mexican energy consumption and production in and estimations of a baseline scenario for , as well as the variation in percentage. Conflicts of Interest The authors declare no conflicts of interest. Cite this paper Chatellier-Lorentzen, D. Energy and Power Engineering , 9 ,
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