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Статті в журналах з теми "Emissions intensity"
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Chontanawat, Jaruwan, Paitoon Wiboonchutikula, and Atinat Buddhivanich. "Decomposition Analysis of the Carbon Emissions of the Manufacturing and Industrial Sector in Thailand." Energies 13, no. 4 (February 12, 2020): 798. http://dx.doi.org/10.3390/en13040798.
Повний текст джерелаАнотація:
Since the 1990s, CO2 emissions have increased steadily in line with the growth of production and the use of energy in the manufacturing sector in Thailand. The Logarithmic Mean Divisia Index Method is used for analysing the sources of changes in CO2 emissions as well as the CO2 emission intensity of the sector in 2000–2018. On average throughout the period, both the amount of CO2 emissions and the CO2 emission intensity increased each year relative to the baseline. The structural change effect (effect of changes of manufacturing production composition) reduced, but the intensity effect (effect of changes of CO2 emissions of individual industries) increased the amount of CO2 emissions and the CO2 emission intensity. The unfavourable CO2 emission intensity change came from the increased energy intensity of individual industries. The increased use of coal and electricity raised the CO2 emissions, whereas the insignificant change in emission factors showed little impact. Therefore, the study calls for policies that decrease the energy intensity of each industry by limiting the use of coal and reducing the electricity used by the manufacturing sector so that Thailand can make a positive contribution to the international community’s effort to achieve the goal of CO2 emissions reduction.
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Shen, Zijie, and Liguo Xin. "Characterizing Carbon Emissions and the Associations with Socio-Economic Development in Chinese Cities." International Journal of Environmental Research and Public Health 19, no. 21 (October 23, 2022): 13786. http://dx.doi.org/10.3390/ijerph192113786.
Повний текст джерелаАнотація:
Reducing carbon emissions in cities is crucial for addressing climate change, while the city-level emissions of different compositions and their relationships with socio-economic features remain largely unknown in China. Here, we explored the city-level emission pattern from the industrial, transportation, and household sectors and the emission intensity, as well as their associations with socio-economic features in China, using the up-to-date (2020) CO2 emissions based on 0.1° grid (10 × 10 km) emission data. The results show that: (1) CO2 emissions from the industrial sector were considerably dominant (78%), followed by indirect (10%), transportation (8%), and household (2%) emissions on the national scale; (2) combining total emissions with emission intensity, high emission–high intensity cities, which are the most noteworthy regions, were concentrated in the North, while low emission–low intensity types mainly occurred in the South-West; (3) cities with a higher GDP tend to emit more CO2, while higher-income cities tend to emit less CO2, especially from the household sector. Cities with a developed economy, as indicated by GDP and income, would have low emissions per GDP, representing a high emission efficiency. Reducing the proportion of the secondary sector of the economy could significantly decrease CO2 emissions, especially for industrial cities. Therefore, the carbon reduction policy in China should focus on the industrial cities in the North with high emission–high intensity performance. Increasing the income and proportion of the tertiary industry and encouraging compact cities can effectively reduce the total emissions during the economic development and urbanization process.
3
Mrówczyńska-Kamińska, Aldona, Bartłomiej Bajan, Krzysztof Piotr Pawłowski, Natalia Genstwa, and Jagoda Zmyślona. "Greenhouse gas emissions intensity of food production systems and its determinants." PLOS ONE 16, no. 4 (April 30, 2021): e0250995. http://dx.doi.org/10.1371/journal.pone.0250995.
Повний текст джерелаАнотація:
It is estimated that about 1/4th of all greenhouse gas (GHG) emissions may be caused by the global food system. Reducing the GHG emissions from food production is a major challenge in the context of the projected growth of the world’s population, which is increasing demand for food. In this context, the goal should be to achieve the lowest possible emission intensity of the food production system, understood as the amount of GHG emissions per unit of output. The study aimed to calculate the emission intensity of food production systems and to specify its determinants based on a panel regression model for 14 countries, which accounted for more than 65% of food production in the world between 2000 and 2014. In this article, emission intensity is defined as the amount of GHG emissions per value of global output. Research on the determinants of GHG emissions related to food production is well documented in the literature; however, there is a lack of research on the determinants of the emission intensity ratio for food production. Hence, the original contribution of this paper is the analysis of the determinants of GHG emissions intensity of food production systems. The study found the decreased of emission intensity from an average of more than 0.68 kg of CO2 equivalent per USD 1 worth of food production global output in 2000 to less than 0.46 in 2014. The determinants of emission intensity decrease included the yield of cereals, the use of nitrogen fertilizers, the agriculture material intensity, the Human Development Index, and the share of fossil fuel energy consumption in total energy use. The determinants of growth of emission intensity of food production systems included GDP per capita, population density, nitrogen fertilizer production, utilized agriculture area, share of animal production, and energy use per capita.
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Zhang, Xiufan, and Decheng Fan. "The Spatial-Temporal Evolution of China’s Carbon Emission Intensity and the Analysis of Regional Emission Reduction Potential under the Carbon Emissions Trading Mechanism." Sustainability 14, no. 12 (June 17, 2022): 7442. http://dx.doi.org/10.3390/su14127442.
Повний текст джерелаАнотація:
It is of great significance to study the regional differences and temporal and spatial evolution of China’s carbon emission intensity under the carbon emissions trading mechanism, and to explore the potential for regional emission reduction. This paper uses the Theil index and Moran index to analyze the regional differences and temporal and spatial evolution trend of carbon emission intensity in China from 2010 to 2019, further constructs the emission reduction effect standard of carbon emissions trading mechanisms, discusses the emission reduction effect of the trading mechanisms, and measures the regional emission reduction potential according to the environmental learning curve. The results showed that: (1) China’s overall carbon emissions continued to increase, but the carbon emission intensity showed an overall decreasing trend. There are strong regional differences in China’s carbon emission intensity. The carbon emission intensity in the western region is higher, and the overall regional difference is decreasing year by year. (2) China’s carbon emissions trading mechanism has a significant reduction effect, but the total quota slack of the Tianjin, Beijing, and Chongqing carbon emissions trading pilot markets is loose. (3) Shanghai, Shanxi, Jiangxi, Guizhou, Inner Mongolia, and Beijing are high-efficiency carbon emission reduction provinces (more than 35%), and Fujian and Xinjiang are low-efficiency carbon emission reduction provinces (less than 15%). It is necessary to further develop the demonstration effect of high emission reduction potential areas and increase the emission reduction efforts in low emission reduction potential areas.
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Zhu, Yong, and Congjia Huo. "The Impact of Agricultural Production Efficiency on Agricultural Carbon Emissions in China." Energies 15, no. 12 (June 19, 2022): 4464. http://dx.doi.org/10.3390/en15124464.
Повний текст джерелаАнотація:
With the rapid development of China’s economy, China has become the world’s largest carbon emitter. China not only has an obvious growth rate of industrial carbon emissions but also the intensity of agricultural carbon emissions is hovering at a high level. The development of China’s agricultural economy has largely come at the expense of high emissions. Currently, under the background of global warming and difficulty in controlling greenhouse gas emissions, the development of low-carbon agriculture is an important way to realize the harmonious development of the ecological environment and economic growth and to promote the sustainable development of agriculture. The agricultural production efficiency is the main factor affecting the intensity of agricultural carbon emissions. Based on provincial panel data of China from 2010 to 2019, this paper establishes an indicator system and uses the super-efficiency SBM model to measure agricultural production efficiency. The regional agricultural carbon emissions were estimated using carbon-emission-related agricultural production activities. In order to study the nonlinear relationship between agricultural production efficiency and agricultural carbon emission intensity in the narrow sense, this paper uses a threshold regression model with agricultural carbon emissions as the threshold variable. Based on the analysis of China’s agricultural production efficiency and agricultural carbon emissions from 2010 to 2019, an empirical test is conducted through a threshold regression model. The results show an “inverted U-shaped” relationship between agricultural production efficiency and agricultural carbon emission intensity. In areas with high agricultural production efficiency, the improvement of production efficiency can suppress the intensity of agricultural carbon emissions; in areas with low agricultural production efficiency, the improvement of production efficiency increases the intensity of agricultural carbon emissions. Finally, based on the research conclusions, this paper provides feasible suggestions and countermeasures for China’s agricultural carbon emission reduction and improvement of agricultural production efficiency.
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Zhang, Jianqing, Haichao Yu, Keke Zhang, Liang Zhao, and Fei Fan. "Can Innovation Agglomeration Reduce Carbon Emissions? Evidence from China." International Journal of Environmental Research and Public Health 18, no. 2 (January 6, 2021): 382. http://dx.doi.org/10.3390/ijerph18020382.
Повний текст джерелаАнотація:
Innovation agglomeration plays a decisive role in improving the input–output scale and marginal output efficiency of factors. This paper takes carbon emissions as the unexpected output and energy consumption as the input factor into the traditional output density model. The dynamic spatial panel Durbin model is used to analyze the mechanism for innovation agglomeration and energy intensity to affect carbon emissions from 2004 to 2017 in thirty Chinese provinces. Then, we test the possible mediating effect of energy intensity between innovation agglomeration and carbon emissions. The major findings are as follows. (1) The carbon emission intensity has time-dependence and positive spatial spillover effect. That is, there is a close correlation between current and early carbon emissions, and there is also a high-degree correlation between regional and surrounding areas’ carbon emissions. (2) Carbon emissions keep a classical inverted U-shaped relation with innovation agglomeration, as well as with energy intensity. However, the impact of innovation agglomeration on carbon emissions in inland regions of China does not appear on the right side of the inverted U-shaped curve, while carbon emissions are subject to a positive nonlinear promoting effect from energy intensity. (3) When the logarithm of innovation agglomeration is more than 3.0309, it first shows the inhibition effect on energy intensity. With the logarithm of innovation agglomeration exceeding 5.0100, it will show the dual effect of emission reduction and energy conservation. (4) Energy intensity could work as the intermediary variable of innovation agglomeration’s influence on carbon emissions. Through its various positive externalities, innovation agglomeration can produce a direct impact on carbon emissions, and through energy intensity, it can also affect carbon emissions indirectly.
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Fu, Liyuan, and Qing Wang. "Spatial and Temporal Distribution and the Driving Factors of Carbon Emissions from Urban Production Energy Consumption." International Journal of Environmental Research and Public Health 19, no. 19 (September 29, 2022): 12441. http://dx.doi.org/10.3390/ijerph191912441.
Повний текст джерелаАнотація:
Urban production energy consumption produces a large amount of carbon emissions, which is an important source of global warming. This study measures the quantity and intensity of carbon emissions in 30 provinces of China based on urban production energy consumption from 2005–2019, and uses the Dagum Gini coefficient, kernel density estimation, carbon emission classification and spatial econometric model to analyze the spatial and temporal distribution and driving factors of quantity and intensity of carbon emissions from China and regional production energy consumption. It was found that the growth rate of carbon emission quantity and carbon emission intensity of production energy consumption decreased year by year in each province during the study period. The imbalance of carbon emission was strong, with different degrees of increase and decrease, and there were big differences between eastern and western regions. The classification of carbon emissions differed among provinces and there was heterogeneity among regions. The quantity and intensity of carbon emissions of production energy consumption qwre affected by multiple factors, such as industrial structure. This study provides an in-depth comparison of the spatial and temporal distribution and driving factors of quantity and intensity of carbon emissions of production energy consumption across the country and regions, and provides targeted policies for carbon emission reduction across the country and regions, so as to help achieve China’s “double carbon” target quickly and effectively.
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Meng, Zhaosu, Huan Wang, and Baona Wang. "Empirical Analysis of Carbon Emission Accounting and Influencing Factors of Energy Consumption in China." International Journal of Environmental Research and Public Health 15, no. 11 (November 5, 2018): 2467. http://dx.doi.org/10.3390/ijerph15112467.
Повний текст джерелаАнотація:
China is confronting great pressure to reduce carbon emissions. This study focuses on the driving factors of carbon emissions in China using the Logarithmic Mean Divisia Index (LMDI) method. Seven economic factors, including gross domestic product (GDP), investment intensity, research and development (R&D) intensity, energy intensity, research and development (R&D) efficiency, energy structure and province structure are selected and the decomposition model of influencing factors of carbon emissions in China is constructed from a sectoral perspective. The influence of various economic factors on carbon emissions is analyzed quantitatively. Results show that the R&D intensity and energy intensity are the main factors inhibiting the growth of carbon emissions. GDP and investment intensity are the major factors promoting the growth of carbon emissions. The contribution of R&D efficiency to carbon emissions is decreasing. The impacts of energy structure and province structure on carbon emissions are ambiguous through time. Finally, some policy suggestions for strengthening the management of carbon emissions and carbon emission reduction are proposed.
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Dyer, James A., Xavier P. C. Verge, Raymond L. Desjardins, and Devon E. Worth. "A Comparison of the Greenhouse Gas Emissions From the Sheep Industry With Beef Production in Canada." Sustainable Agriculture Research 3, no. 3 (June 24, 2014): 65. http://dx.doi.org/10.5539/sar.v3n3p65.
Повний текст джерелаАнотація:
<p>Sheep production in Canada is a small industry in comparison to other livestock systems. Because of the potential for expansion of the sheep industry in Canada, the GHG emissions budget of this industry was assessed in this paper. The GHG emissions from Canadian lamb production were compared with those from the Canadian beef industry using the ULICEES model. The GHG emission intensity of the Canadian lamb industry was 21% higher than lamb production in France and Wales, and 27% higher than northern England. Enteric methane accounts for more than half of the GHG emissions from sheep in Canada. The protein based GHG emission intensity is 60% to 90% higher for sheep than for beef cattle in Canada. The GHG emission intensity for sheep in Eastern Canada is higher than for sheep in Western Canada. Protein based GHG emission intensity is more sensitive to the difference between sheep and beef than LW based emission intensity. This paper demonstrated that protein based GHG emission intensity is a more meaningful indicator for comparing different livestock species than live weight (LW) based GHG emission intensity.</p>
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Qin, Jiancheng, Hui Tao, Chinhsien Cheng, Karthikeyan Brindha, Minjin Zhan, Jianli Ding, and Guijin Mu. "Analysis of Factors Influencing Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China." Sustainability 12, no. 3 (February 4, 2020): 1089. http://dx.doi.org/10.3390/su12031089.
Повний текст джерелаАнотація:
Analyzing the driving factors of regional carbon emissions is important for achieving emissions reduction. Based on the Kaya identity and Logarithmic Mean Divisia Index method, we analyzed the effect of population, economic development, energy intensity, renewable energy penetration, and coefficient on carbon emissions during 1990–2016. Afterwards, we analyzed the contribution rate of sectors’ energy intensity effect and sectors’ economic structure effect to the entire energy intensity. The results showed that the influencing factors have different effects on carbon emissions under different stages. During 1990–2000, economic development and population were the main factors contributing to the increase in carbon emissions, and energy intensity was an important factor to curb the carbon emissions increase. The energy intensity of industry and the economic structure of agriculture were the main factors to promote the decline of entire energy intensity. During 2001–2010, economic growth and emission coefficient were the main drivers to escalate the carbon emissions, and energy intensity was the key factor to offset the carbon emissions growth. The economic structure of transportation, and the energy intensity of industry and service were the main factors contributing to the decline of the entire energy intensity. During 2011–2016, economic growth and energy intensity were the main drivers of enhancing carbon emissions, while the coefficient was the key factor in curbing the growth of carbon emissions. The industry’s economic structure and transportation’s energy intensity were the main factors to promote the decline of the entire energy intensity. Finally, the suggestions of emissions reductions are put forward from the aspects of improving energy efficiency, optimizing energy structure and adjusting industrial structure etc.
Дисертації з теми "Emissions intensity"
1
McMullan, Beth Mary. "Investment Decisions Under An Emissions Intensity Target." Thesis, Curtin University, 2020. http://hdl.handle.net/20.500.11937/79729.
Повний текст джерелаАнотація:
This thesis reports the results of a controlled laboratory experiment to test the effect of emissions price certainty on firm investments in clean technology when a regulator has set an intensity target. As fixed prices are associated with emissions closer to predictions, policymakers concerned with meeting specific targets might be more inclined to use a tax. Alternatively, if lowering emissions is a greater priority, then the market mechanism may be favoured.
2
Andres, Delgado Lidia. "Greenhouse gas emissions and energy intensity of the transport sector." Doctoral thesis, Universitat Autònoma de Barcelona, 2018. http://hdl.handle.net/10803/665197.
Повний текст джерелаАнотація:
Esta tesis analiza el tema del transporte y la presión medioambiental a través de tres variables relacionadas: las emisiones, la actividad y la intensidad energética del transporte. El Capítulo 2 analiza la importancia de la población, la actividad económica, el volumen de transporte y las características estructurales de la actividad de transporte —intensidad energética del transporte, participación de los diferentes modos de transporte y participación de las diferentes fuentes energéticas— como factores explicativos de las emisiones de GEI de la actividad de transporte en la Unión Europea-28 entre 1990-2014. El análisis se basa en el modelo STIRPAT, que se amplía para investigar el impacto en las emisiones del transporte de los cambios en dicha actividad y en los del conjunto de la economía. Utilizando técnicas econométricas de datos panel, se identifica la importancia de cada factor explicativo y el impacto de su cambio en las emisiones. El Capítulo 3 estudia el impacto del sector del subsistema de transporte y almacenamiento en las emisiones de GEI de la economía mediante el análisis de subsistemas basado en el modelo input-output de Ghosh. Esta nueva metodología tiene en cuenta toda la actividad del subsistema y no solo la actividad vinculada a su demanda final. Asimismo, las emisiones totales del subsistema se descomponen en cuatro componentes explicativos: el componente escala, el componente interno neto, el componente feed-back y el componente spillover, con el objetivo de conocer las interrelaciones en términos de emisiones entre los subsectores del subsistema y entre estos y la actividad del resto de sectores de la economía. La metodología se aplica empíricamente al sector del transporte y almacenamiento en España en 2014. El Capítulo 4 examina los factores que han influido en la tendencia de la intensidad energética del transporte de mercancías por carretera español durante el período 1996-2012. Se adapta la metodología ASIF con el fin de estudiar la intensidad energética y se completa el estudio con un análisis de descomposición LMDI. Además, el cambio en la intensidad energética se analiza cuantificando la contribución de cada mercancía transportada a través de la metodología de la atribución de cambios en los índices Divisia.
Los tres capítulos principales de esta tesis ofrecen varias contribuciones. El Capítulo 2 desarrolla metodológicamente el modelo STIRPAT al aplicar al estudio de las emisiones del transporte la participación de los diferentes modos de transporte y la participación de las diferentes fuentes de energía. En segundo lugar, contribuye a analizar empíricamente las emisiones de GEI del sector del transporte en la Unión Europea en el período 1990-2014. En tercer lugar, evalúa la efectividad potencial de las acciones promovidas en el Libro Blanco del Transporte de 2011. El Capítulo 3 desarrolla metodológicamente el modelo de subsistemas input-output desde la perspectiva de la oferta y este se amplía con el fin de estudiar el impacto medioambiental de sustancias contaminantes. En segundo lugar, ofrece una contribución empírica, ya que aplica el modelo al análisis de los efectos de la actividad del sector de transporte y almacenamiento en las emisiones de GEI de la economía en España en 2014. Finalmente, el Capítulo 4 adapta la metodología ASIF a fin de investigar la intensidad energética del transporte de mercancías por carretera y amplía el análisis mediante la descomposición LMDI. En segundo lugar, identifica el grado en que cada mercancía contribuye al cambio en la intensidad energética a través de la metodología de la atribución de cambios en los índices Divisia. En tercer lugar, investiga empíricamente la intensidad energética del transporte español de mercancías por carretera en el período 1996-2012.This dissertation analyses the topic of transport and environmental pressure through three closely related issues —transport GHG emissions, transport activity, and transport energy intensity. Chapter 2 analyses the importance of population, economic activity, transport volume, and structural characteristics of transport activity —in terms of transport energy intensity, of transport modes' share, and of energy sources’ mix— as driving factors of GHG emissions in transport activity in the European Union over the period 1990–2014. The analysis is based on the STIRPAT model, which is broadened to investigate in depth the impact on transport emissions of changes in the transport activity and in the whole economy. Using panel data econometric techniques, the significance of each factor and the impact of its change on emissions are identified. Chapter 3 studies the impact of the transport and storage subsystem sector on GHG emissions of the whole economy by using input–output subsystems analysis based on the Ghosh model. This new methodology that is developed in the chapter takes into account the whole activity of the subsystem and not only the activity linked to its final demand. Additionally, in the aim of learning the interrelations in terms of emissions between the subsectors of the subsystem and between them and the activity of the rest of the sectors of the economy, total emissions of the subsystem are decomposed into four explanatory components. These are scale component, net own internal component, feed-back component, and spillover component. The methodology is applied to the Spanish transportation and storage sector in 2014. Chapter 4 examines the factors that have influenced the energy intensity trend of the Spanish road freight transport of heavy goods vehicles over the period 1996–2012. The ASIF methodology is adapted to study it, and the chapter uses multiplicative LMDI decomposition analysis. Additionally, the change in energy intensity is analyzed in more depth by quantifying the role of each commodity transported using the methodology of the attribution of changes in Divisia indices. The three main chapters of this dissertation offer various contributions. Chapter 2 develops methodologically the STIRPAT model since it adds as driving factors of transport emissions the modal share and the energy consumption mix. Second, it empirically contributes to analyze the GHG emissions of the transport sector in the European Union in the period 1990–2014. Third, it evaluates the potential effectiveness of the actions promoted in the 2011 Transport White Paper. Chapter 3 develops methodologically an input–output subsystems model from the supply perspective and expands it in order to study the environmental impact of polluting substances. Second, it offers an empirical contribution, as it applies the preceding model with the purpose of studying the effects of the activity of the transportation and storage sector on GHG emissions of the whole economy in Spain in 2014. Finally, Chapter 4 adapts the ASIF methodology to energy intensity in the road freight transport and enhances it by applying decomposition analysis. Second, it identifies the degree to which each transported commodity has contributed to the change in energy intensity through the methodology of attribution of changes in Divisia indices. Four, it provides an empirical contribution through the analysis of energy intensity of Spanish road freight transport of heavy goods vehicles over the period 1996–2012.
3
Haukland, Eirik. "Trade and Environment: Emissions intensity of Norway's imports and exports." Thesis, Norwegian University of Science and Technology, Industrial Ecology Programme, 2004. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1416.
Повний текст джерелаАнотація:
An Environmental Input-Output Analysis (EIOA) have been performed in order to assess the importance of including foreign emission and economic data when estimating emissions attached to imports. The CO2, SOx and NOx emissions induced by total imports are calculated using both foreign and domestic inventory. The results show significantly higher emissions when using foreign data, especially for SOx.
Demand-specific emission intensities are established for both import and domestic production. A comparison of those for emissions of CO2, SOx and NOx indicates much higher values for the imports than for the domestic production.
In addition, analyses are conducted on a more detailed level, defined by the NACE-industry aggregation. Foreign inventory are used on the imports, and domestic inventory are used on the domestic production. The detailed demand-specific emission intensities show similar trends compared with the total results mentioned above. However, there are considerable differences between some of the NACE sectors.
Finally, a brief overview of the assumed emissions related to household consumption is performed. However, the analysis are not on such a detailed level that conclusions can be made.
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Arvidsson, Martins Mikael. "Convergence of CO2 emissions in the Americas." Thesis, Jönköping University, IHH, Nationalekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53137.
Повний текст джерелаАнотація:
Maintaining global warming to 2 degrees Celsius above pre-industrial levels is vital. Whether the convergence hypothesis holds for carbon dioxide emissions is important for policymakers facing this issue. This paper investigates the convergence behavior of carbon dioxide emissions for 39 countries in the Americas from 1960-2016. A linear regression test of convergence which looks for conditional sigma convergence is employed, and a clustering algorithm is used to identify convergence clubs. The results show evidence of convergence in the region for the long run. Convergence clubs are identified for the short run. The convergence clubs show some relation to spatial distribution and income level. Possible factors determining the formation of convergence clubs are investigated through logistic regression. Initial level of emissions and energy intensity were found to have the largest impact determining what convergence club a country belongs to. Per capita GDP, trade openness, and renewable energy were all found to be highly significant factors determining what convergence club a country belongs to as well. Different results were found for urbanization’s impact in determining the formation of convergence clubs. These findings show that policymakers should promote allocation schemes for carbon dioxide emissions. Policymakers should also aim to reduce carbon footprint based on the economy’s structural characteristics.
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Ekman, Oskar. "Dynamic pricing and carbon intensity in demand response functions." Thesis, Linköpings universitet, Energisystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-109633.
Повний текст джерелаАнотація:
The European power sector is facing significant challenges related to investments in grid infrastructure and generation capacity. The continued deployment of intermittent renewables also puts pressure on current grid conditions. Smart grids is seen as a cost-efficient way to overcome these challenges through a more efficient use of current capacity. Demand response is a corner-stone in smart grid development, and is implemented to introduce flexibility on the demand side. Most demand response programs have used dynamic pricing to incentivize consumers to shift consumption from peak to off-peak hours. In Stockholm Royal Seaport, where a sustainable energy system is envisioned, it has been proposed that dynamic pricing should be complemented with an indicator depicting carbon intensity of purchased electricity. This indicator is based on average emissions, which is one of two fundamental perspectives on assessing environmental impacts of electricity consumption. The aim of this study was to evaluate whether the approach used to quantify carbon intensity in Stockholm Royal Seaport is appropriate in the context of demand response. To achieve this, a literature review has been conducted regarding potential benefits of demand response, power system dynamics and carbon dioxide allocation methods. A quantitative analysis has also been conducted, where the signal proposed for Stockholm Royal Seaport has been modeled under different timeframes. The results show that the CO2-signal in Stockholm Royal Seaport is constructed in such a way that it is largely affected by hydro generation, which in turn makes it correlate negatively with price. As a result, the CO2-signal would counteract many of the predicted long-term benefits of demand response. Furthermore it seems unlikely that the signal would result in significant short-term emission reductions, since hydro generally is used to balance supply and demand in the Swedish and Nordic systems. Based on the literature review, it was concluded that marginal emissions would be a more appropriate environmental indicator than average emissions. However, it remains a difficulty to construct a day-ahead control signal based on this perspective because of system complexity and lack of data. Historical marginal carbon intensity was nevertheless modeled in this study using a linear regression model. The results indicate that price itself might be a sufficient indicator of marginal emissions. Finally, a model for a signal based on prognoses of intermittent renewable generation is proposed, where the rationale is that consumers should decrease consumption during hours of low renewable generation. This signal was modeled using data on renewable generation from Denmark since corresponding data in Sweden is not yet available. Results show that it would be possible to construct a rather accurate control signal in this way. There are also reasons to believe that demand response based on this type of signal would result in long-term environmental benefits.Den europeiska energisektorn står inför stora utmaningar, bland annat i form av investeringsbehov i nätinfrastruktur och produktionskapacitet för att säkra framtida leveranssäkerhet. Den fortsatta utbyggnaden av intermittent förnybar kraftproduktion ställer också nya krav på nätet och på aktörernas flexibilitet. Smarta nät ses som ett kostnadseffektivt sätt för att övervinna dessa utmaningar genom en mer effektiv användning av nuvarande kapacitet. En viktig del i detta är efterfrågerespons, som syftar till att minska belastningen på nätet under höglasttimmar genom att i högre grad än tidigare involvera konsumenten. De flesta initiativ inom efterfrågerespons har använt dynamisk prissättning för att uppmuntra konsumenter att flytta konsumtion från höglast- till låglasttimmar. I Norra Djurgårdsstaden, där visionen är att bygga ett hållbart och mer flexibelt energisystem, har det föreslagits att dynamisk prissättning bör kompletteras med en indikator som visar den inköpta elens koldioxidintensitet. Denna indikator är baserad på medelel, vilket är ett av två fundamentala sätt att miljövärdera el. Syftet med denna studie var att utvärdera om den metod som används för att kvantifiera koldioxidintensiteten i Norra Djurgårdsstaden är lämplig i samband med efterfrågerespons. För att uppnå detta har en litteraturstudie genomförts gällande potentiella fördelar med efterfrågerespons, hur kraftsystemet fungerar samt olika metoder för att miljövärdera el. En kvantitativ analys har också genomförts, där CO2-signalen i Norra Djurgårdsstaden har modellerats utifrån olika tidsperspektiv. Resultaten visar att CO2-signalen i Norra Djurgårdsstaden är konstruerad på ett sådant sätt att den till stor del påverkas av vattenkraftens produktionsvariationer, vilket i sin tur gör att signalen generellt rör sig i motsatt riktning mot prissignalen. Resultatet av detta är att CO2-signalen motverkar många av de långsiktiga fördelarna med efterfrågestyrning. Dessutom ter det sig osannolikt att signalen skulle leda till signifikanta utsläppsminskningar på kort sikt, eftersom lasten i Sverige främst balanseras av variationer i vattenkraft. Utifrån litteraturstudien kan man dra slutsatsen att marginalelens koldioxidintensitet skulle vara en lämpligare miljöindikator än genomsnittliga utsläpp i samband med efterfrågestyrning. Det är dock svårt att i praktiken konstruera en styrsignal baserat på detta perspektiv på grund av systemets komplexitet och brist på data. Historiska marginella utsläpp modellerades emellertid med hjälp av linjär regression. Resultaten från detta indikerade att priset kan vara en tillräcklig indikator även för variationerna i koldioxidintensitet utifrån ett marginalperspektiv. Slutligen föreslås en modell för en signal baserad på dagenföreprognoser om intermittent förnybar produktion, där budskapet skulle vara att användaren minskar sin konsumtion under timmar med låg förnybar produktion. Denna signal modellerades med hjälp av uppgifter om förnybar produktion från Danmark eftersom motsvarande uppgifter om Svensk produktion inte finns tillgängliga ännu. Resultaten visar att det skulle vara möjligt att konstruera en relativt träffsäker styrsignal på detta sätt. Det finns också skäl att tro att efterfrågerespons baserat på denna typ av signal skulle leda till miljömässiga fördelar på längre sikt.
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Reniers, Jorn. "Analysis of a real-time signal for greenhouse gas emissions of district heating consumption." Thesis, KTH, Industriell ekologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169508.
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The district heating system (DHS) of Stockholm is one of the largest systems in the world with a total yearly production of 10TWh of heat and 2TWh of electricity (through combined heat and power plants). Large amounts of greenhouse gasses (GHG) are emitted to produce this heat and electricity. Given the goal of the City of Stockholm to reduce the amount of GHG emissions to 3 ton per capita in 2015 and to keep reducing emissions at a similar rate after 2015, it is important to identify the potentials for further reductions. Numerous studies have been done on how the DHS can become more sustainable by installing new generation units. However, also the consumers have an influence on the DHS. After all, it are the consumers who decide when and how much heat or electricity they use. Most former studies and environmental guidelines for the DHS in Stockholm focussed on the producer side. This thesis looks at the consumer perspective of the (heat of the) district heating system. A real-time signal giving the greenhouse gas emissions of individual households is developed and its potential and challenges are discussed. With this signal, households that want to minimise their environmental impact have a tool to decrease their environmental impact by changing their consumption. This can be a first step to transform the DHS to a smart district heating system. First, generic models to calculate the dynamic greenhouse gas intensity of the heat production of district heating and to calculate the greenhouse gas emissions related to the heat consumption of households are suggested. Then the feedback signal with those real-time household emissions is calculated for representative households in Stockholm based on data of Stockholm’s DHS and data about hot tap water consumption in Sweden. Results indicate that variations in household level greenhouse gas emissions mostly reflect changes in consumption but can also result from changes by the producer. Intraday variations are mostly caused by changes in hot tap water consumption, while variations on a timescale of a few days are caused by changes in heating consumption (changing weather) and changes made by the producer (to use different fuels). Then several scenarios are calculated, each scenario looking at the actions a consumer can take to shift or reduce his/her consumption (decrease hot tap water usage, lower indoor temperature etc.). The real-time household emissions are calculated again to see if the signal gives the needed incentives (is the household rewarded for its effort? Does it get further incentives?). It was found that a strong time-incentive (to decrease consumption when it saves most emissions) is missing if the average perspective is used to calculate the emission intensity of the heat production. Also, the results confirmed the finding that the feedback signal might not reflect changes in consumption. Finally, challenges for the signal are discussed. One of the major hurdles is the fact that household consumption of heat (heating and hot tap water) can often not be measured on a household level. Thus, it has to be estimated but it seems very difficult to get this estimation accurate enough to give correct feedback to households, especially about the emissions saved by their efforts to reduce/shift their consumption. Secondly, the time resolution should be chosen well to still get accurate results but not make the signal to data-intensive. Finally, the result is heavily dependent on the chosen methodology (average or marginal perspective? Do you account for the electrical side of the DHS? How about the distribution losses? Etc.).
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Zaidi, Syed Haider Ali. "Modelling and forecasting energy intensity, energy efficiency and CO₂ emissions for Pakistan." Thesis, University of Leicester, 2017. http://hdl.handle.net/2381/39346.
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The aim of this thesis is to examine the significant environmental issues, especially, Green House Gases (GHGs) emissions and specifically Carbon Dioxide (CO₂) emissions which are mainly caused by energy use. This thesis consists of three core chapters. Chapters 2 and 4 discuss how to stabilize and forecast CO₂ emissions for Pakistan while chapter 3 discusses the energy efficiency of Asian developing countries. Exogenous Technical Change (TC) and endogenous TC models are considered in the chapter 2 for the stabilization of CO₂ emissions. Specifically, the estimated results show that endogenous TC model (which is estimated by following the Kalman Filter (KF) technique) does a better job in comparison. The results also point out the existence of a trade-off between GDP growth and fuel prices. Inter-fuel substitutions are estimated using the Almost Ideal Demand System (AID). Results suggest that stabilization can be achieved just in short run but it needs too much time for the implementation in the long run plans. In chapter 3, a parametric Stochastic Frontier model Approach (SFA) is used for a panel of 19 countries including Pakistan over the period of 1980 to 2013. The individual and relative energy efficiency over time of all counties is estimated. The focus is to find either energy intensity a good indicator of energy efficiency or not. According to the estimated results, energy intensity is not a good indicator of energy efficiency but the energy efficiency estimated using SFA after controlling for some of the economic factors (fuel prices, population, income, etc.) it is. In chapter 4, the relationship between CO₂ emissions and income, and energy consumption and income are found to support the Environmental Kuznets Curve (EKC) hypothesis. Univariate (Grey Prediction Model (GM), Exponential Smoothing (ES), Holt-Winter (H-W)) and multivariate model solving techniques are used to predict CO₂ emissions and their forecasting abilities are compared. A new technique, Out Of Sample Grey Prediction (OOSGP), is introduced after providing a critique of the GP model to get better forecast results. The findings of this study provide a valuable reference with which Pakistan’s government could formulate measures to reduce CO₂ emissions by curbing the unnecessary consumption of energy.
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Moutinho, Victor Manuel Ferreira. "Essays on the determinants of energy related CO2 emissions." Doctoral thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/15156.
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Doutoramento em Sistemas Energéticos e Alterações ClimáticasOverall, amongst the most mentioned factors for Greenhouse Gases (GHG) growth are the economic growth and the energy demand growth. To assess the determinants GHG emissions, this thesis proposed and developed a new analysis which links the emissions intensity to its main driving factors. In the first essay, we used the 'complete decomposition' technique to examine CO2 emissions intensity and its components, considering 36 economic sectors and the 1996-2009 periods in Portugal. The industry (in particular 5 industrial sectors) is contributing largely to the effects of variation of CO2 emissions intensity. We concluded, among others, the emissions intensity reacts more significantly to shocks in the weight of fossil fuels in total energy consumption compared to shocks in other variables. In the second essay, we conducted an analysis for 16 industrial sectors (Group A) and for the group of the 5 most polluting manufacturing sectors (Group B) based on the convergence examination for emissions intensity and its main drivers, as well as on an econometric analysis. We concluded that there is sigma convergence for all the effects with exception to the fossil fuel intensity, while gamma convergence was verified for all the effects, with exception of CO2 emissions by fossil fuel and fossil fuel intensity in Group B. From the econometric approach we concluded that the considered variables have a significant importance in explaining CO2 emissions and CO2 emissions intensity. In the third essay, the Tourism Industry in Portugal over 1996-2009 period was examined, specifically two groups of subsectors that affect the impacts on CO2 emissions intensity. The generalized variance decomposition and the impulse response functions pointed to sectors that affect tourism more directly, i. e. a bidirectional causality between the intensity of emissions and energy intensity. The effect of intensity of emissions is positive on energy intensity, and the effect of energy intensity on emissions intensity is negative. The percentage of fossil fuels used reacts positively to the economic structure and to carbon intensity, i. e., the more the economic importance of the sector, the more it uses fossil fuels, and when it raises its carbon intensity, in the future the use of fossil fuel may rise. On the other hand, positive shocks on energy intensity tend to reduce the percentage of fossil fuels used. In fourth essay, we conducted an analysis to identify the effects that contribute to the intensity of GHG emissions (EI) in agriculture as well as their development. With that aim, we used the 'complete decomposition' technique in the 1995-2008 periods, for a set of European countries. It is shown that the use of Nitrogen per cultivated area is an important factor of emissions and in those countries where labour productivity increases (the inverse of average labour productivity in agriculture decreases), emissions intensity tends to decrease. These results imply that the way to reduce emissions in agriculture would be to provide better training of agricultural workers to increase their productivity, which would lead to a less need for energy and use of Nitrogen. The purpose of the last essay is to examine the long and short-run causality of the share of renewable sources on the environmental relation CO2 per KWh electricity generation- real GDP for 20 European countries over the 2001-2010 periods. It is important to analyze how the percentage of renewable energy used for electricity production affects the relationship between economic growth and emissions from this sector. The study of these relationships is important from the point of view of environmental and energy policy as it gives us information on the costs in terms of economic growth, on the application of restrictive levels of emissions and also on the effects of the policies concerning the use of renewable energy in the electricity sector (see for instance European Commission Directive 2001/77/EC, [4]). For that purpose, in this study we use Cointegration Analysis on the set of cross-country panel data between CO2 emissions from electricity generation (CO2 kWh), economic growth (GDP) and the share of renewable energy for 20 European countries. We estimated the long–run equilibrium to validate the EKC with a new approach specification. Additionally, we have implemented the Innovative Accounting Approach (IAA) that includes Forecast Error Variance Decomposition and Impulse Response Functions (IRFs), applied to those variables. This can allow us, for example, to know (i) how CO2 kWh responds to an impulse in GDP and (ii) how CO2 kWh responds to an impulse in the share of renewable sources. The contributions of this thesis to the energy-related CO2 emissions at sectorial level are threefold: First, it provides a new econometric decomposition approach for analysing and developing CO2 emissions in collaboration with science societies that can serve as a starting point for future research approaches. Second, it presents a hybrid energy-economy mathematic and econometric model which relates CO2 emissions in Portugal based on economic theory. Third, it contributes to explain the change of CO2 emissions in important economic sectors in Europe, in particular in Portugal, taking normative considerations into account more openly and explicitly, with political implications at energy-environment level within the European commitment.
De uma forma geral, entre os fatores mais apontados para o crescimento das emissões de Gases de Efeito de Estufa (GEE), estão o crescimento económico e o crescimento das necessidades energéticas. Para identificar os determinantes das emissões de GEE, esta dissertação propôs e desenvolveu uma nova análise que liga a intensidade das emissões aos seus principais responsáveis. No primeiro ensaio, foi utilizada a técnica da ‘decomposição total’ para examinar a intensidade das emissões de CO2 e os seus componentes, considerando 36 setores económicos e o período entre 1996-2009 em Portugal. A indústria (em particular cinco setores industriais) contribui fortemente para os efeitos da variação da intensidade de CO2. Conclui-se, entre outros, que a intensidade das emissões reage mais significativamente a choques no peso dos combustíveis fósseis no consumo total da energia, comparativamente a choques em outras variáveis. No segundo ensaio, conduziu-se uma análise para 16 sectores industriais (Grupo A) e para o grupo dos cinco setores industriais mais poluentes (Grupo B), baseada no estudo da convergência para a intensidade das emissões e para os seus principais determinantes, bem como numa análise econométrica. Concluiu-se que existe convergência sigma para todos os efeitos, à exceção da intensidade dos combustíveis fósseis, enquanto a convergência gama se verificou para todos os efeitos com a exceção das emissões de CO2 por combustível fóssil e intensidade de combustível fóssil, no Grupo B. A partir da abordagem econométrica, concluiu-se que as variáveis consideradas têm uma importância significativa na explicação da intensidade das emissões de CO2. No terceiro ensaio foi analisada a indústria do turismo em Portugal durante o período de 1996-2009, em particular para dois grupos de subsetores que afetam a intensidade das emissões de CO2. A decomposição generalizada de variância e as funções de impulso-resposta apontaram uma causalidade bidirecional entre intensidade de emissões e intensidade de energia para setores que afetam o turismo mais diretamente. O efeito da intensidade de emissões é positivo na intensidade da energia e o efeito da intensidade da energia na intensidade das emissões é negativo. A percentagem de combustíveis fósseis utilizados reage positivamente à estrutura económica e à intensidade do carbono, isto é, quando um setor ganha importância económica, tende a usar mais combustível fóssil e quando aumenta a intensidade do carbono, no futuro, o uso de combustíveis fósseis pode aumentar. Por outro lado, choques positivos na intensidade de energia tendem a reduzir a percentagem de combustíveis fósseis utilizados. O objectivo do quarto ensaio é identificar os efeitos que contribuem para a intensidade dos gases de estufa na agricultura, bem como a sua evolução, Para isso, utilizou-se a técnica de ‘decomposição total’ no período 1995-2008 para um grupo de países europeus. Ficou demonstrado que o uso de nitrogénio por área cultivada é um fator importante nas emissões e naqueles países cuja produtividade do trabalho aumenta, a intensidade das emissões tende a aumentar. O resultado implica que o caminho para reduzir as emissões na agricultura pode passar por uma melhor formação dos trabalhadores ligados à agricultura para melhorar a sua produtividade, o que pode conduzir a uma menor necessidade e uso de nitrogénio. O objectivo do último ensaio é examinar a causalidade de longo e curto prazo da quota de fontes renováveis na relação ambiental entre o desenvolvimento económico (PIB) e as emissões de CO2 por KWh de eletricidade produzida num conjunto de 20 países Europeus no período de 2001-2010. Esta nova abordagem sugere que a quota de fontes renováveis na produção de eletricidade é um determinante importante para explicar as diferenças na relação Rendimento-emissões de CO2 por Kwh nos países Europeus e que as evidências empíricas suportam a relação ambiental da curva de Kuznets. As contribuições desta dissertação para os assuntos relacionados com as emissões de CO2 a um nível setorial são as seguintes: primeiro, oferece uma nova abordagem econométrica da decomposição para analisar a evolução das emissões de CO2 que pode servir como um ponto de partida para futuras investigações. Segundo, apresenta uma abordagem híbrida, juntando a matemática e a economia de energia e um modelo econométrico para relacionar as emissões de CO2 na Europa e, em particular, em Portugal com base em teorias económicas. Terceiro, contribui para explicar as mudanças nas emissões de CO2 em setores económicos importantes para Portugal, conjugando considerações normativas aberta e explicitamente, com implicações políticas no comprometimento europeu, ao nível energético-ambiental.
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Lueken, Roger Alan. "Reducing Carbon Intensity in Restructured Markets: Challenges and Potential Solutions." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/479.
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The U.S. electric power sector is in the early stages of transitioning from a reliance on carbon intensive generation sources to a system based on low-carbon sources. In this thesis, I present analyses of four different aspects of this transition, with an emphasis on the PJM Interconnection. The effects of bulk electricity storage on the PJM market I analyze the value of three storage technologies in the PJM day-ahead energy market, using a reduced-form unit commitment model with 2010 data. I find that large-scale storage would increase overall social welfare in PJM. However, the annualized capital costs of storage would exceed social welfare gains. Consumers would save up to $4 billion annually, largely at the expense of generator surplus. Storage modestly increases emissions of CO2 and other pollutants. The external costs and benefits of wind energy in PJM Large deployments of wind create external costs and benefits that are not fully captured in power purchase agreements. I find that wind’s external costs in the PJM market are uncertain but significant when compared to levelized PPA prices. Pollution reduction benefits are very uncertain but exceed external costs with high probability. The climate and health effects of a USA switch from coal to gas electricity generation I analyze the emission benefits created by a hypothetical scenario in which all U.S. coal plants are switched to natural gas plants in 2016. The net effect on warming is unclear; results are highly sensitive to the rate of fugitive methane emissions and the efficiency of replacement gas plants. However, the human health benefits of such a switch are substantial. The costs of building and operating new gas plants likely exceed the health benefits. Robust resource adequacy planning in the face of coal retirements Over the next decade, many U.S. coal-fired power plants are expected to retire, posing a challenge to system planners. I investigate the resource adequacy requirements of the PJM Interconnection, and how procuring less capacity may affect reliability. I find that PJM’s 2010 reserve margin of 20.5% was sufficient to achieve the stated reliability standard with 90% confidence. PJM could reduce reserve margins to 13% and still achieve levels of reliability accepted by other power systems.
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Moro, Alberto, and Laura Lonza. "Electricity carbon intensity in European Member States: Impacts on GHG emissions of electric vehicles." Elsevier, 2017. https://publish.fid-move.qucosa.de/id/qucosa%3A73241.
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The Well-To-Wheels (WTW) methodology is widely used for policy making in the transportation sector. In this paper updated WTW calculations are provided, relying on 2013 statistic data, for the carbon intensity (CI) of the European electricity mix; detail is provided for electricity consumed in each EU Member State (MS). An interesting aspect presented is the calculation of the GHG content of electricity traded between Countries, affecting the carbon intensity of the electricity consumed at national level. The amount and CI of imported electricity is a key aspect: a Country importing electricity from another Country with a lower CI of electricity will lower, after the trade, its electricity CI, while importing electricity from a Country with a higher CI will raise the CI of the importing Country. In average, the CI of electricity used in EU at low voltage in 2013 was 447 gCO2eq/kWh, which is the 17% less compared to 2009. Then, some examples of calculation of GHG emissions from the use of electric vehicles (EVs) compared to internal combustion engine vehicles are provided. The use of EVs instead of gasoline vehicles can save (about 60% of) GHG in all or in most of the EU MSs, depending on the estimated consumption of EVs. Compared with diesel, EVs show average GHG savings of around 50% and not savings at all in some EU MS.
Книги з теми "Emissions intensity"
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Environment, Alberta Alberta. Specified gas emitters regulation: Technical guidance for completing baseline emissions intensity applications. 2nd ed. [Edmonton]: Alberta Environment, 2009.
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Specified gas emitters regulation: Technical guidance document for baseline emissions intensity applications. [Edmonton]: Alberta Environment, 2007.
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Environment, Alberta Alberta. Specified gas emitters regulation: Frequently asked questions for baseline emissions intensity applications and compliance reporting. [Edmonton]: Alberta Environment, 2008.
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EIA analysis of draft climate change legislation: Hearing before the Committee on Energy and Natural Resources, United States Senate, One Hundred Tenth Congress, first session, on analysis recently completed by the Energy Information Administration, "Energy market and economic impacts of a proposal to reduce greenhouse gas intensity with a cap and trade system," January 24, 2007. Washington: U.S. G.P.O., 2007.
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Kolman, Peter. Vibration spectra and ion emission during fracture induced by high intensity sonic stresses. Sudbury, Ont: Laurentian University, 1994.
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Knittel, Christopher R. Carbon prices and automobile greenhouse gas emissions: The extensive and intensive margins. Cambridge, MA: National Bureau of Economic Research, 2010.
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Knittel, Christopher R. Carbon prices and automobile greenhouse gas emissions: The extensive and intensive margins. Cambridge, MA: National Bureau of Economic Research, 2010.
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UK, OdourNet. Odour impacts and odour emission control measures for intensive agriculture: Final report. Wexford: Environmental Protection Agency, 2001.
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Bhushan, Chandra. Challenge of the new balance: A study of the six most emissions intensive sectors to determine India's low carbon growth options. New Delhi: Centre for Science and Environment, 2010.
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Knox, Michael, and Jonathan D. Mark. Greenhouse Gas Emissions: Drivers of Intensity and Country Variances. Nova Science Publishers, Incorporated, 2012.
Знайти повний текст джерелаЧастини книг з теми "Emissions intensity"
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Urbanski, Shawn P., Susan M. O’Neill, Amara L. Holder, Sarah A. Green, and Rick L. Graw. "Emissions." In Wildland Fire Smoke in the United States, 121–65. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87045-4_5.
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AbstractThis chapter assesses the current state of the science regarding the composition, intensity, and drivers of wildland fire emissions in the USA and Canada. Globally and in the USA wildland fires are a major source of gases and aerosols which have significant air quality impacts and climate interactions. Wildland fire smoke can trigger severe pollution episodes with substantial effects on public health. Fire emissions can degrade air quality at considerable distances downwind, hampering efforts by air regulators to meet air standards. Fires are a major global source of aerosols which affect the climate system by absorbing and scattering radiation and by altering optical properties, coverage, and lifetime of clouds. A thorough understanding of fire emissions is essential for effectively addressing societal and climate consequences of wildland fire smoke.
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Teske, Sven, and Thomas Pregger. "Science-Based Industry Greenhouse Gas (GHG) Targets: Defining the Challenge." In Achieving the Paris Climate Agreement Goals, 9–21. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99177-7_2.
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AbstractBackground information is given on the Paris Climate Agreement and the role of nationally determined contributions and net-zero pledges. An overview of historical energy-related CO2 emissions since 1750 and how they relate to economic development, measured in gross domestic product (GDP), is provided, together with the cumulative energy-related CO2 emissions by region. The future energy demand if historical trends in energy efficiency and carbon intensity continue until 2050 is projected. The term ‘science-based target setting’ is defined, and how it relates to the carbon budget published in the Sixth Assessment Report of the IPCC is discussed. The energy-related CO2 emission pathway required to achieve the 1.5 °C target is outlined.
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Nkounga, W. M. "Energy in Development Objectives: How the Energy Ecological Footprint Affects Development Indicators?" In Sustainable Energy Access for Communities, 159–70. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-68410-5_15.
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AbstractAccess to affordable energy services remains a priority for eradicating poverty in developing countries. Energy services from conventional resources are necessary to power economic growth. However, they have a significant ecological footprint. In this study, we assess the impact of greenhouse gases (GHG) emitted by energy systems on some of the Sustainable Development Goals (SDG). The study explores the relationships between the carbon intensity of the energy sector, the energy intensity of the economy and the carbon intensity of the economic system. In a sample of African countries, we found a positive correlation between energy use per capita and greenhouse gas emissions per capita and per unit GDP (carbon intensity of the economy). However, the correlation is less conclusive between energy use per capita and GHG emissions and between energy use per capita and energy use per unit GDP (energy intensity of the economy). Our results support new perspectives on energy sustainability agendas that take into account the macroeconomic parameters of the Sustainable Development Goal number 7 (SDG-7).
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Liu, Chunmei, Maosheng Duan, and Tao Pang. "Research on the Selection between Absolute and Intensity-Based Limits of CO2 Emissions." In Advances in Intelligent and Soft Computing, 717–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27329-2_98.
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Adenuga, Olukorede Tijani, Khumbulani Mpofu, and Thobelani Mathenjwa. "Energy Efficiency for Manufacturing Using PV, FSC, and Battery-Super Capacitor Design to Enhance Sustainable Clean Energy Load Demand." In Lecture Notes in Mechanical Engineering, 259–70. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18326-3_26.
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AbstractEnergy efficiency (EE) are recognized globally as a critical solution towards reduction of energy consumption, while the management of global carbon dioxide emission complement climate change. EE initiatives drive is a key factor towards climate change mitigation with variable renewable technologies. The paper aimed to design and simulate photovoltaic (PV), fuel cell stack (FCS) systems, and battery-super capacitor energy storage to enhance sustainable clean energy load demand and provide significant decarbonization potentials. An integration of high volume of data in real-time was obtained and energy mix fraction towards low carbon emission mitigation pathway strategy for grid linked renewables electricity generation was proposed as a solution for the future transport manufacturing energy supplement in South Africa. The interrelationship between energy efficiency and energy intensity variables are envisaged to result in approximately 87.6% of global electricity grid production; electricity energy demand under analysis can reduce the CO2 emissions by 0.098 metric tons and CO2 savings by 99.587 per metric tons. The scope serves as a fundamental guideline for future studies in the future transport manufacturing with provision of clean energy and sufficient capacity to supply the demand for customers within the manufacturing.
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Zhao, Tao, and Xiao-song Ren. "The Empirical Research of the Causality Relationship Between CO2 Emissions Intensity, Energy Consumption Structure, Energy Intensity and Industrial Structure in China." In The 19th International Conference on Industrial Engineering and Engineering Management, 601–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38391-5_62.
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Mitrova, Tatiana. "Energy and the Economy in Russia." In The Palgrave Handbook of International Energy Economics, 649–66. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86884-0_32.
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AbstractThis chapter provides an overview of the Russian energy sector and its role in the Russian economy, also in the context of energy transition. Russia, ranking fourth in the world in primary energy consumption and in carbon dioxide emissions, adheres to the strategy of “business as usual” and relies on fossil fuels. Decarbonization of the energy sector is not yet on the agenda; a skeptical attitude to the problem of global climate change prevails among stakeholders. GDP energy intensity remains high, supported by relatively low energy prices and high cost of capital. The share of solar and wind energy in the energy balance is insignificant and is not expected to exceed 1% by 2035. The challenge for Russia in the coming years is to develop a new strategy for the development of its energy sector, which enters the zone of high turbulence—even in the absence of the influence of the climate change agenda—due to COVID-19, increasing global competition, growing technological isolation and financial constraints.
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Wooster, Martin J., G. L. W. Perry, B. Zhukov, and D. Oertel. "Estimation of Energy Emissions, Fireline Intensity and Biomass Consumption in Wildland Fires: A Potential Approach Using Remotely Sensed Fire Radiative Energy." In Spatial Modelling of the Terrestrial Environment, 175–96. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094001.ch9.
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Lefebvre, Cedric W., Jay P. Babich, James H. Grendell, James H. Grendell, John E. Heffner, Ronan Thibault, Claude Pichard, et al. "Positron Emission Tomography." In Encyclopedia of Intensive Care Medicine, 1794–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-00418-6_731.
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Hurmekoski, Elias, Antti Kilpeläinen, and Jyri Seppälä. "Climate-Change Mitigation in the Forest-Based Sector: A Holistic View." In Forest Bioeconomy and Climate Change, 151–63. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99206-4_8.
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AbstractForests and wood use can contribute to climate-change mitigation by enhancing carbon sinks through afforestation, reforestation and improved forest management, by maintaining carbon stocks through natural or anthropogenic disturbance prevention, by increasing offsite carbon stocks, and through material and energy substitution by changing the industry production structure and enhancing resource efficiency. As forests grow fairly slowly in Europe, increasing the wood harvesting intensity decreases the carbon stocks in aboveground biomass, at least in the short to medium term (0–50 years) compared to a baseline harvest regime. The key issue is the time frame in which the decreased carbon stock in forests can be compensated for by improved forest growth resulting from improved forest management and the benefits related to wood utilisation. Thus, there is a need to address potential trade-offs between the short- to medium-term and the long-term (50+ years) net emissions. An optimal strategy needs to be tailored based also on regional specificities related to, for example, local climatic and site conditions, the state of the forests, the institutional setting and the industry structures. This chapter presents a way to assess the effectiveness of forest-sector climate-change mitigation strategies across different contexts and time horizons, combining the climate impacts of forests and the wood utilisation of the technosphere. We identify potential ‘no-regret’ mitigation pathways with minimum trade-offs, and conclude with the research and policy implications.
Тези доповідей конференцій з теми "Emissions intensity"
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Gonzalez de Alaiza Martinez, Pedro, Luc Berge, Xavier Davoine, Arnaud Debayle, and Laurent Gremillet. "Photoionization versus plasma wakefield effects in laser-induced terahertz emissions at near-relativistic intensities." In High Intensity Lasers and High Field Phenomena. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/hilas.2016.hs2b.5.
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Said, Ahmed O., Ahmed E. E. Khalil, Daniel Dalgo, and Ashwani K. Gupta. "Impact of Oxygen Enriched Air on High Intensity Combustion and Emission." In ASME 2015 Power Conference collocated with the ASME 2015 9th International Conference on Energy Sustainability, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/power2015-49037.
Повний текст джерелаАнотація:
The influence of oxygen enriched air-methane flame under non-premixed and premixed fuel-lean combustion conditions is examined with focus on the emission of NO and CO, combustor exit temperature (Texit), and distribution of OH* chemiluminescence intensity. A cylindrical combustor was used at combustion intensity of 36MW/m3.atm and heat load of 6.25 kW. Results are also reported with normal air (21% oxygen). Oxygen enrichment provided stable combustion operation at lower equivalence ratios than normal air and also reduced CO emission. Increase in oxygen concentration from 21% to 25% and 30% increased the NO and decreased CO emissions at all equivalence ratios examined. Using 30% O2 enriched air in premixed case showed NO emissions of 11.4 ppm and 4.6 ppm at equivalence ratios of 0.5 and 0.4, respectively. Oxygen enrichment also reduced CO emission to 38 ppm at equivalence ratio of 0.5. Operating the combustor with normal air at these equivalence ratios resulted in unstable combustion. OH* Chemiluminescence revealed increased chemiluminescence intensity with the reaction zone to shift upstream at increased oxygen concentration. The exhaust temperature of the combustor increased with oxygen enrichment leading to lower CO concentration and increased combustion efficiency. The oxidizer injected at higher velocities mitigated the impact of reaction zone to move upstream that helped to reduce significantly both the NO and CO emission specifically under non-premixed combustion.
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Yoshizawa, Shin, Shin-ichiro Umemura, and Yoichiro Matsumoto. "Cavitation detection with subharmonic emissions by low intensity sustaining ultrasound." In 2008 IEEE Ultrasonics Symposium (IUS). IEEE, 2008. http://dx.doi.org/10.1109/ultsym.2008.0185.
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Khalil, Ahmed E. E., and Ashwani K. Gupta. "Impact of Internal Entrainment on High Intensity Distributed Combustion." In ASME 2015 Power Conference collocated with the ASME 2015 9th International Conference on Energy Sustainability, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/power2015-49034.
Повний текст джерелаАнотація:
Colorless Distributed Combustion (also referred to as CDC) has been shown to provide ultra-low emissions and enhanced performance of high intensity gas turbine combustors. To achieve distributed combustion, the flowfield needs to be tailored for adequate mixing between reactants and hot reactive species from within the combustor to result in high temperature low oxygen concentration environment prior to ignition. Such reaction distribution results in uniform thermal field and also eliminates any hot spots for mitigating NOx emission. Though CDC have been extensively studied using a variety of geometries, heat release intensities, and fuels, the role of internally recirculated hot reactive gases needs to be further investigated and quantified. In this paper, the impact of internal entrainment of reactive gases on flame structure and behavior is investigated with focus on fostering distributed combustion and providing guidelines for designing future gas turbine combustors operating in distributed combustion mode. To simulate the recirculated gases from within the combustor, a mixture of nitrogen and carbon dioxide is introduced to the air stream prior to mixing with fuel and subsequent combustion. Increase in the amounts of nitrogen and carbon dioxide (simulating increased entrainment), led to volume distributed reaction over a larger volume in the combustor with enhanced and uniform distribution of the OH* chemiluminescence intensity. At the same time, the bluish flame stabilized by the swirler is replaced with a more uniform almost invisible bluish flame. The increased recirculation also reflected on the pollutants emission, where NO emissions were significantly decreased for the same amount of fuel burned. Lowering oxygen concentration from 21% to 15% (due to increased recirculation) resulted in 80∼90% reduction in NO with no impact on CO emission with sub PPM NO emission achieved at an equivalence ratio of 0.7. Flame stabilization at excess recirculation can be achieved using preheated nitrogen and carbon dioxide, achieving true distributed conditions with oxygen concentration below 13%.
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Kay, Brian. "Direct Contact Steam Generation Reduces Carbon Intensity." In SPE Improved Oil Recovery Conference. SPE, 2022. http://dx.doi.org/10.2118/209350-ms.
Повний текст джерелаАнотація:
Abstract Steam for enhanced oil recovery is typically generated using Once-Through-Steam-Generators (OTSG) produced at large central facilities with the steam then pipelined to each injection well. As much as 50% of the energy can be lost before it reaches the well bore with the combustion emissions vented to atmosphere. Direct Contact Steam Generation (DCSG) injects both steam and hot combustion flue gases into the reservoir. Oil production is increased by reducing oil viscosity through heat while repressuring the reservoir with flue gases and improving miscibility with the CO2 that remains in the reservoir. This combination greatly improves the Steam-Oil-Ratio (SOR) for increased oil recovery as well as delivering environmental benefits related to reduced water requirements and lower emissions resulting in a much lower carbon intensity. DCSG water requirements are 11% less than OTSG methods as water is created by the combustion process, this water is then injected into the reservoir rather than lost to the atmosphere. As most of the DCSG process emissions are indirect, emissions can be further reduced by as much as 30% with the use of low carbon intensity grid electricity for compression. Pilot results show that DCSG used less water, with 70% of the CO2 retained in the formation. Lower SOR and CO2 retained in the reservoir demonstrates lower carbon intensity relative to OTSG. DCSG offers heavy oil operators a novel, viable, method to economically extract currently uncoverable reservoirs at a lower carbon intensity than traditional methods.
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Kay, Brian, Thomas Hartley, Stella Zhang, and Lisa Doig. "Direct Contact Steam Generation Reduces Carbon Intensity." In SPE Western Regional Meeting. SPE, 2022. http://dx.doi.org/10.2118/209287-ms.
Повний текст джерелаАнотація:
Abstract Steam for enhanced oil recovery is typically generated using Once-Through-Steam-Generators (OTSG) produced at large central facilities with the steam then pipelined to each injection well. As much as 50% of the energy can be lost before it reaches the well bore with the combustion emissions vented to atmosphere. Direct Contact Steam Generation (DCSG) injects both steam and hot combustion flue gases into the reservoir. Oil production is increased by reducing oil viscosity through heat while repressuring the reservoir with flue gases and improving miscibility with the CO2 that remains in the reservoir. This combination greatly improves the Steam-Oil-Ratio (SOR) for increased oil recovery as well as delivering environmental benefits related to reduced water requirements and lower emissions resulting in a much lower carbon intensity. DCSG water requirements are 11% less than OTSG methods as water is created by the combustion process, this water is then injected into the reservoir rather than lost to the atmosphere. As most of the DCSG process emissions are indirect, emissions can be further reduced by as much as 30% with the use of low carbon intensity grid electricity for compression. Pilot results show that DCSG used less water, with 70% of the CO2 retained in the formation. Lower SOR and CO2 retained in the reservoir demonstrates lower carbon intensity relative to OTSG. DCSG offers heavy oil operators a novel, viable, method to economically extract currently uncoverable reservoirs at a lower carbon intensity than traditional methods.
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Chovancova, J., and J. Fazekas. "Emission intensity of energy sector in V4 countries – decoupling analysis of GHG emissions and economic growth." In 2019 International Council on Technologies of Environmental Protection (ICTEP). IEEE, 2019. http://dx.doi.org/10.1109/ictep48662.2019.8969005.
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Govindaraj, Jagadeesh, and Sathyan Subbiah. "Experimental Investigation of Charged Particles Emission in Machining: Towards Process Monitoring." In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6670.
Повний текст джерелаАнотація:
Charged particles are emitted when a material undergoes plastic deformation and failure. In machining, plastic deformation and shearing of work piece material takes place continuously; hence, emission of charged particles can be expected. In this work, an in-situ sensor has been developed to capture the emitted positively (positive ion) and negatively (electron and negative ion) charged particles in real time in an orthogonal machining process at atmospheric conditions without the use of coolant. The sensor consists of a Faraday plate, mounted on the flank face of the cutting tool, to collect the emitted ions and the intensity of emissions is measured with an electrometer. Positively and negatively charged particles are measured separately by providing suitable bias voltage supply to the Faraday plate. Ion emissions are measured during machining of three different work piece materials (mild steel, copper and stainless steel) using a carbide cutting tool. The experimental results show a strong correlation between the emission intensity and variation in machining parameters and material properties. Increasing material removal rate in machining increases the intensity of charged particle emissions because of increase in volume of material undergoing shear, fracture, and deformation. It is found that emission intensity is directly proportional to the resistivity and strength of workpiece material. Charged particles emission intensity is found to be very sensitive to the machining conditions which enables the use of this sensor as an alternate method of tool condition monitoring.
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Mihajloski, Todor, Magdalena Lachowska, Christopher L. Bennett, and Ozcan Ozdamar. "Hearing level equalized otoacoustic emissions acquired by swept-tones: Intensity characteristics." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6090187.
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Di, Lei, Gaurav Manish Shah, Yiran Yang, and Cuicui Wei. "Greenhouse Gas Emission Analysis of Integrated Production-Inventory-Transportation Supply Chain Enabled by Additive Manufacturing." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-63822.
Повний текст джерелаАнотація:
Abstract The manufacturing industry is a major source of greenhouse gas emissions (GHG). Additive manufacturing, owing to its multiple advantages, plays a critical role in innovating the current manufacturing industry, especially from a supply chain perspective. Currently, the majority of research on GHG emissions in the manufacturing industry is focused on traditional manufacturing, either single processes in the supply chain or specific case studies, indicating the lack of models on GHG emissions in additive manufacturing-enabled supply chain structures. In this work, a mathematical model is established to estimate the GHG emissions in both traditional manufacturing and additive manufacturing-enabled supply chains. To explore the advantages of additive manufacturing in terms of fast production and reduced or even eliminated the need for assembly and labor involvement, a unique integrated production-inventory-transportation structure is investigated in additive manufacturing case studies. The results indicate that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the additive manufacturing technique in the supply chain. Also, the impacts of rush order rate, emission intensity, and vehicle GHG emission constant rate on the overall GHG emissions are investigated in the sensitivity analysis. Results indicate that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in additive manufacturing.
Звіти організацій з теми "Emissions intensity"
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Al Quayid, AlJawhara, Nourah Al Hosain, Yagyavalk Bhatt, and Paul Mollet. Political Feasibility of Enhancing India’s Midcentury Target for Emissions Intensity. King Abdullah Petroleum Studies and Research Center, September 2019. http://dx.doi.org/10.30573/ks--2019-dp71.
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Spano, Christian, Paolo Natali, Charles Cannon, Suzanne Greene, Osvaldo Urzúa, Carlos Sucre, and Adriana Unzueta. Latin America and the Caribbean 2050: Becoming a Global Low-Carbon Metals and Solutions Hub. Inter-American Development Bank, July 2021. http://dx.doi.org/10.18235/0003412.
Повний текст джерелаАнотація:
This report evaluates scope 3 emissions along the copper and iron ore value chains and the opportunities that Latin America and the Caribbean (LAC) has to become a low carbon metals and solutions hub. The report presents four carbon emission scenarios that represent different sets of decisions for policy-makers and investors. Two scenarios fall short of aligning with Paris targets: (1) the business as usual (BaU) scenario with no further abatement action; and (2) a BaU scenario with the current level of emission reduction potential from players in the value chain (BaU Possible). The other two scenarios deliver the required carbon reductions to be compliant with the Paris Agreement by 2060, but through different strategies: (3) the BaU Paris scenario. where alignment with Paris targets is achieved by keeping BaU volumes and reducing carbon intensity per tonne of metal; and (4) the Decoupled scenario, where carbon intensity reductions are relaxed and compensated by a reduction in primary supply to align the value chain emissions to a Paris trajectory. All scenarios require LACs leaders to consider investments in low-carbon technology in different degrees. The report argues that, given its competitive position in the cost curve for copper and iron ore and an abundance of enabling factors for low carbon strategies, the region could become a key source of low carbon metals and solutions as long as it is proactive in adopting all the necessary measures from public sector and industry perspectives. Finally, the report concludes that myriad opportunities exist for LAC, including new business models, technologies and products, and that these could yield a greater economic and social contribution to the region than the BaU trajectories.
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Koziel, Jacek, Yael Laor, Jeffrey Zimmerman, Robert Armon, Steven Hoff, and Uzi Ravid. Simultaneous Treatment of Odorants and Pathogens Emitted from Confined Animal Feeding Operations (CAFOs) by Advanced Oxidation Technologies. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7592646.bard.
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A feasibility study was conducted, aiming to explore the potential effectiveness of UV/TiO2/O3 photooxidation technologies for simultaneous treatment of odorant and pathogen emissions from livestock and poultry operations. Several key parameters were tested in laboratory (US) and semi-pilot (Israel) scale conditions including: the effects of light energy dose (treatment time and light intensity), relative humidity and air temperature, UV wavelength, presence of photocatalyst (TiO2) and the presence of ozone. Removal and conversion of odor, target gases (sulfur-containing volatile organic compounds S-VOCs, volatile fatty acids (VFAs), phenolics, and ammonia), and airborne pathogens was tested. Up to 100% removal (below method detection level) of S-VOCs, VFAs, and phenolics, the overall odor, and up to 64.5% of ammonia was achieved with optimized treatment. Treatments involving deep UV band (185 nm) and photocatalyst (TiO2) were more efficient in removal/conversion of odorous gases and odor. The estimate of the operational cost of treatment was based on measured emissions of several odorous VOCs from full scale, commercial swine farm ranges from $0.15 to $0.59 per finisher pig. This figure represents significantly lower cost compared with the cost of biofiltration or air scrubbing.
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Sheldon, Tamara, and Rubal Dua. How cost-effective are electric vehicle subsidies in reducing tailpipe-CO2 emissions? King Abdullah Petroleum Studies and Research Center, June 2021. http://dx.doi.org/10.30573/ks--2021-dp07.
Повний текст джерелаАнотація:
The transportation sector accounts for 24% of global greenhouse gas (GHG) emissions (IEA 2020). Road transport is the most utilized mode because of its convenience (Van Essen 2008). However, it is also the most emissions intensive mode, accounting for 75% of global transport GHG emissions, with roughly 44% coming from road passenger vehicles alone (IEA 2020).
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Aalto, Juha, and Ari Venäläinen, eds. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, June 2021. http://dx.doi.org/10.35614/isbn.9789523361355.
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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.
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Knittel, Christopher, and Ryan Sandler. Carbon Prices and Automobile Greenhouse Gas Emissions: The Extensive and Intensive Margins. Cambridge, MA: National Bureau of Economic Research, October 2010. http://dx.doi.org/10.3386/w16482.
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Brown K. A. Observations of Secondary Emission Chamber Efficiency Degradation For Very High Intensity Slow Extracted Beams. Office of Scientific and Technical Information (OSTI), August 1995. http://dx.doi.org/10.2172/1151325.
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Krinsky, Samuel. Analysis of Statistical Correlations and Intensity Spiking in the Self-Amplified Spontaneous-Emission Free-Electron Laser. Office of Scientific and Technical Information (OSTI), February 2003. http://dx.doi.org/10.2172/812642.
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Corriveau, Elizabeth, Ashley Mossell, Holly VerMeulen, Samuel Beal, and Jay Clausen. The effectiveness of laser-induced breakdown spectroscopy (LIBS) as a quantitative tool for environmental characterization. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40263.
Повний текст джерелаАнотація:
Laser-induced breakdown spectroscopy (LIBS) is a rapid, low-cost analytical method with potential applications for quantitative analysis of soils for heavy metal contaminants found in military ranges. The Department of Defense (DoD), Army, and Department of Homeland Security (DHS) have mission requirements to acquire the ability to detect and identify chemicals of concern in the field. The quantitative potential of a commercial off-the-shelf (COTS) hand-held LIBS device and a classic laboratory bench-top LIBS system was examined by measuring heavy metals (antimony, tungsten, iron, lead, and zinc) in soils from six military ranges. To ensure the accuracy of the quantified results, we also examined the soil samples using other hand-held and bench-top analytical methods, to include Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and X-Ray Fluorescence (XRF). The effects of soil heterogeneity on quantitative analysis were reviewed with hand-held and bench-top systems and compared multivariate and univariate calibration algorithms for heavy metal quantification. In addition, the influence of cold temperatures on signal intensity and resulting concentration were examined to further assess the viability of this technology in cold environments. Overall, the results indicate that additional work should be performed to enhance the ability of LIBS as a reliable quantitative analytical tool.
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Clausen, Jay, Richard Hark, Russ Harmon, John Plumer, Samuel Beal, and Meghan Bishop. A comparison of handheld field chemical sensors for soil characterization with a focus on LIBS. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43282.
Повний текст джерелаАнотація:
Commercially available handheld chemical analyzers for forensic applications have been available for over a decade. Portable systems from multiple vendors can perform X-ray fluorescence (XRF) spectroscopy, Raman spectroscopy, Fourier transform infrared(FTIR) spectroscopy, and recently laser-induced breakdown spectroscopy (LIBS). Together, we have been exploring the development and potential applications of a multisensor system consisting of XRF, Raman, and LIBS for environmental characterization with a focus on soils from military ranges. Handheld sensors offer the potential to substantially increase sample throughput through the elimination of transport of samples back to the laboratory and labor-intensive sample preparation procedures. Further, these technologies have the capability for extremely rapid analysis, on the order of tens of seconds or less. We have compared and evaluated results from the analysis of several hundred soil samples using conventional laboratory bench top inductively coupled plasma atomic emission spectroscopy (ICP-AES) for metals evaluation and high-performance liquid chromatography (HPLC) and Raman spectroscopy for detection and characterization of energetic materials against handheld XRF, LIBS, and Raman analyzers. The soil samples contained antimony, copper, lead, tungsten, and zinc as well as energetic compounds such as 2,4,6-trinitrotoluene(TNT), hexahydro-1,3,5-triazine (RDX), nitroglycerine (NG), and dinitrotoluene isomers (DNT). Precision, accuracy, and sensitivity of the handheld field sensor technologies were compared against conventional laboratory instrumentation to determine their suitability for field characterization leading to decisional outcomes.