A pre-announcement of the launch of Call has been made on the Official Journal of the European Union here. A pre-announcement has also been made on the website of the Programme Manager her e. It is expected that full and final information on the Call, including the Description of Research Needs, will be published on the above websites and here on or before December 14, Remember Me.
The SDA in this research is based on the additive decomposition of the changes in emission determined by six multiplicative factors acting as accelerators or retardants of the emission dynamics.
Each term in the decomposition is a product of the change in one explicative factor and the level values of the other five factors, and thus represents the contribution of one explicative factor to the total change in emission. For example, in the term where population is the explicative factor, the values of consumption volume, production structure, consumption patterns, energy intensity and fuel mix are held unchanged and only population varies.
In this way, the SDA method allows us to quantify the contribution of each of the assessed factors to the trend in emissions. Details of our methodology and data sources are in the Methods section including Supplementary Methods.business.dom1.kh.ua/wp-content/2019-09-26/sirav-online-dating-business.php
European Retail Research: 2013, Volume 27, Issue I
We conclude that substitution of gas for coal has had a relatively minor role in the emissions reduction of US CO 2 emissions since Between and , US emissions increased by 7. Our analysis shows that the main factor behind this increase was an increase in consumption volume caused by growth in per capita consumption of goods and services in the United States. Indeed, increases in such consumption volume correspond to a contribution of a The next most important factor influencing CO 2 emissions over the same period was population growth. These population gains contributed to an 8.
Using as base year, the solid black line shows the percentage change in total CO 2 emissions. The other lines show the contribution to the change in emissions from consumption volume red , population yellow , consumption patterns green , production structure blue , energy intensity purple and fuel mix orange.
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However, other factors slowed the growth of emissions between and decreases in the energy intensity of GDP; changes in the consumption patterns of US consumers; shifts in production structure; and decreases in the use of coal as an energy source. All of these trends exerted a downward influence on emissions. Between and , changes in energy intensity, consumption patterns, production structure and fuel mix contributed to retarding emissions of 7.
Although all of the analysed factors except population contributed to the decrease in emissions during —, different factors dominated over shorter periods. Figure 3 subdivides into 2-year periods, showing that emissions fell by 9. But between and , consumption consump. Between and , increases in population and consumption volume again pushed emissions upward, but overall emissions decreased by 2. Not shown here, emissions increased by 1.
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In particular, Fig. Shown are changes in emissions related to household expenditures a , government expenditures b , capital investment c and exports d. In each panel, the solid black line shows the percentage change in CO 2 emissions triggered by changes in the corresponding final demand component, and the other lines show the contribution to the change in emissions from consumption volume red , population yellow , consumption patterns green , production structure blue , fuel mix orange and energy intensity purple.
As the US economy had slowly recovered from the global economic recession, between and , the average annual change in US emissions was small: a 0. Economic recovery is reflected by the upward influence of the volume of goods consumed on emissions during both — and — Between and , rising consumption volume, population growth, and increasing energy intensity urged emissions up by a combined 4. Increases in the supply of natural gas affect two of the factors in our analysis: the fuel mix of the energy sector and, to a lesser extent, the energy intensity of the US economy.
By decreasing gas prices, abundant gas encourages a shift in the fuel mix from more carbon-intensive coal to gas. The boom of natural gas from breakthroughs in hydraulic fracturing of shale deposits had only just begun to affect US gas supplies in ref. Thus, the decrease in emissions from changes in the fuel mix of the energy sector prior reflects an independent and longer-term trend of the declining use of coal in the US energy sector see, for example, Fig.
However, as seen in Fig. Although the decreases in emissions since have been relatively small, the influence of shale gas is visible. For example, about half of the 2. Yet the decrease in the energy intensity of the US economy was nearly twice as strong an influence on emissions over the same period purple bar in Fig.
Although a drop in the energy intensity exajoule per dollar output of the energy sector in accounts for roughly a third of the observed decrease in US energy intensity in —, the remaining two-thirds relate to changes in energy used by the transport and service sectors Fig. Three unrelated trends underlie the decreasing energy intensity of these sectors. Second, a mild winter in meant less energy was used for heating and thus reduced energy intensity of the service sector households also used less energy for home heating, which accounts for part of the drop in consumption volume 13 Supplementary Fig.
Last, there is evidence that manufacturing in the United States became more energy efficient: energy use by manufacturing was nearly constant — despite average annual growth in GDP of 2. Shifts in the production structure of the US economy between and have consistently exerted a downward influence on US emissions, as the volume and type of intermediate goods used by various industry sectors has evolved and become more efficient blue bars in Fig. Yet this structural shift also reflects the progressive offshoring of emissions-intensive industries to China and other developing countries over the analysed period Trade data for the — period is not yet available.
Between and , the share of US consumption of manufactured goods increased relative to services Fig. This result reveals that changes in the types of goods being consumed over time can have a significant impact on emissions 15 , 16 , and that it is not as simple as the balance of manufactured goods and services. Between and , US emissions grew steadily 0. The large decrease 9.
The recessionary belt-tightening may also have contributed to the significant efficiency gains in production structure. Since , the slow recovery of the US economy has urged emissions backup, but has been closely balanced by decreases in energy intensity, especially in the transport, manufacturing and service sectors Fig. The net effect has been very little change in emissions; between and ; US emissions have decreased by an average of 0. Contrary to conventional wisdom, our decomposition analysis shows that changes in the fuel mix of the energy sector including those related to the shale gas boom account for a relatively small portion of this decrease.
In addition to a more robust understanding of the factors influencing US emissions during —, our analysis may be helpful in assessing the efficacy of different forces to reduce US emissions in the future. For example, the modest effect of changes in the fuel mix of the energy sector on emissions in recent years suggests that further increase in the use of natural gas may be of limited benefit in decreasing emissions. This is because barring technology-specific policies for example, Renewable Portfolio Standards , recent studies have shown that gas does not substitute for coal only; growth of emission-free technologies such as solar, wind and nuclear energy is also limited while gas is cheap 17 , In these studies, future increases in natural gas use act to both reduce domestic coal use and slow the growth of renewable energy, resulting in little net change to cumulative CO 2 emissions 17 , 19 , 20 , Moreover, CO 2 emissions are not the only consideration; a growing number of studies also show that increased leakage of methane from new natural gas infrastructure can offset CO 2 reductions relative to coal 22 , Third, decreases in residential gas prices Supplementary Fig.
And finally, decreased domestic demand for coal has enabled an increase in US coal exports to eager and growing overseas markets. The US power sector consumed million fewer metric tons of coal in than in , during which period coal exports doubled even as coal prices rose Supplementary Fig.
European Retail Research - , Volume 27, Issue I | Hanna Schramm-Klein | Springer
Although CO 2 emissions from US coal burned elsewhere are generally attributed to the country where those emissions occur, the emissions nonetheless contribute to global climate change and in fact less energy may be produced per unit of CO 2 emissions when the coal is burned in countries with less-efficient power plants.
For all these reasons, further increases in the use of natural gas in the United States may not have a large effect on global greenhouse gas emissions and warming. Similarly, further emissions reductions due to decreases in energy intensity are not inevitable. As can be seen in Fig. The energy intensity of other industry sectors also shows no long-term decreasing trend Fig.
In contrast, any gas-driven recovery of US manufacturing, such as in the production of vehicles and heavy machinery 26 , will tend to increase the average energy intensity of the US economy. Although increased use of natural gas by the energy sector has helped to keep US CO 2 emissions from rising during the economic recovery of —, our decomposition analysis shows that decreases in the energy intensity of the manufacturing, transport and service sectors over the same period were even more important, and that the largest decrease in emissions was due to decreased consumption during the recession of — However, the recovering economy is now urging emissions backup, it is not clear whether decreases in energy intensity will continue, and the overall climate benefits of increased gas use are in question.
Future reductions in US emissions will depend upon policies for example, the Environmental Protection Agency Clean Power Plan that can lock-in the recessionary emissions reductions and ensure continued decarbonization of the US energy system by deployment of more efficient and low-carbon energy technologies Index decomposition analysis IDA and SDA are two decomposition methods that have been frequently used to calculate the contribution of different factors to the overall change in carbon emissions and energy consumption. IDA is often used in studies that aim to understand the drivers of energy use and emissions in a specific economic sector, while SDA is used primarily by input—output practitioners whose research focus on the changes in energy consumption and emissions of a whole economy, for example, a country, a region, or the whole world Due to its simplicity, transparency and lower data requirements, the IDA approach based on index theory 30 , 31 , 32 , 33 had been applied in numerous studies in the past 34 , However, these advantages of the IDA approach may mean limitations for more detailed in-depth analysis.
For instance, lower data requirements also mean less detailed decomposition of economic production structure 34 because the IDA approach cannot analyse the interdependency of different economic sectors Similarly, IDA does not distinguish intermediate and final consumption, and thus cannot capture indirect impacts of change in final consumption.
In this study, we opt to use SDA based on input—output analysis The SDA overcomes many of the static features of input—output models, enabling the evaluation of changes over time in economic structure, final demand components and categories. The SDA is capable of distinguishing a range of production effects and final demand effects that the IDA approach lacks 35 , and allows assessment of both direct and indirect effects along the entire supply chain across upstream and downstream industries Although the high level of data requirement by the SDA approach has been a barrier in the past in light of the fact that many countries publish input—output tables only once every 5 or more years, the recent development of global time series input—output databases for example, World Input—Output Database WIOD 37 and The EOAR multi-region IO database 38 and more regular publication of economic-structure data in countries like the United States now make time series SDA feasible.
SDA is a quantitative methodology based on input—output modelling.
SDA is a popular tool in assessing the contributions of different factors and industry sectors to changes in energy use and CO 2 emissions over time. The method has been applied to many different countries such as Australia 39 , Denmark 40 , 41 , India 42 , Korea 43 , Netherlands 44 , the United States 45 and China 15 , 35 , 46 , Input—output analysis is an accounting procedure that relies on national or regional input—output tables. Environmental input—output analysis illustrates the economy-wide environmental repercussions here we use CO 2 emissions as environmental indicator triggered by economic activity, and can be expressed mathematically as.
Changes in the production structure thus refer to changing input requirements of each sector or, in other words, industries using more or less intermediate inputs from each other. It has been widely discussed that both emissions per unit of energy consumption fuel mix and energy efficiency energy consumption per unit of economic output are vital to the emission intensity of an economy 49 , Therefore, equation 1 can be transformed to:. Over a given period of time, any changes in CO 2 emissions in a country can be represented by equation 2 , in which the seven factors of population, fuel mix, energy intensity, production structure, consumption patterns and consumption volume, plus household direct emissions, fully account for the changes in CO 2 emissions.
A total difference of equation 2 generates equation 3. Equation 3 converts six multiplicative terms in the first term of equation 2 into six additive terms. Each additive term in equation 3 represents the contribution to a change in CO 2 emissions triggered by a factor assuming all other factors are constant.
In the SDA, it is possible to compare different terms relative to any time point within a study period. However, there is no unique solution for the decomposition. In this study, we use the average of all possible first-order decompositions suggested by Dietzenbacher and Los 51 and Seibel 52 see Supplementary Methods and Supplementary Table 1 for a detailed discussion. The US input—output tables from to were collected from the Bureau of Economic Analysis which is in make-use format We convert the make-use table to symmetric input—output table following the method by Miller and Blair 48 and then aggregated them into 35 economic sectors to match the energy and emission data from the WIOD EIA only publishes energy and emission data at aggregate sectoral level including manufacturing, electric power, commercial and residential sectors.
We disaggregated energy use of these four sectors into 35 economic sectors according to the sectoral energy purchase collected from Bureau of Economic Analysis Our analysis focuses on US fossil fuel CO 2 emissions and does not include emissions of non-CO 2 greenhouse gases such as methane.
Fuel effects on the characteristics of particle emissions from advanced engines and vehicles Report no. Method for monitoring exposure to LPG containing small amounts of 1,3- butadiene Report no.