How will Canada’s greenhouse gas emissions change by 2050? A disaggregated analysis of past and future greenhouse gas emissions using bottom-up energy modelling and Sankey diagrams

Davis, Matthew; Ahiduzzaman, Md.; Kumar, Amit

doi:10.1016/j.apenergy.2018.03.064

Cited by 63 publications

(22 citation statements)

References 37 publications

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“…With the advance of global socioeconomics, greenhouse gas emissions are continuously increasing [1,2]. It is generally known that greenhouse gas emissions have significant negative impacts on the sustainable development of humans worldwide [3,4].…”

Section: Introductionmentioning

confidence: 99%

What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

Wang

Gui-fen²,

Shi

2019

IJERPH

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With the advancement of society and the economy, environmental problems have increasingly emerged, in particular, problems with urban CO2 emissions. Exploring the driving forces of urban CO2 emissions is necessary to gain a better understanding of the spatial patterns, processes, and mechanisms of environmental problems. Thus, the purpose of this study was to quantify the driving forces of urban CO2 emissions from 2000 to 2015 in China, including explicit consideration of a comparative analysis between national and urban agglomeration levels. Urban CO2 emissions with a 1-km spatial resolution were extracted for built-up areas based on the anthropogenic carbon dioxide (ODIAC) fossil fuel emission dataset. Six factors, namely precipitation, slope, temperature, population density, normalized difference vegetation index (NDVI), and gross domestic product (GDP), were selected to investigate the driving forces of urban CO2 emissions in China. Then, a probit model was applied to examine the effects of potential factors on urban CO2 emissions. The results revealed that the population, GDP, and NDVI were all positive driving forces, but that temperature and precipitation had negative effects on urban CO2 emissions at the national level. In the middle and south Liaoning urban agglomeration (MSL), the slope, population density, NDVI, and GDP were significant influencing factors. In the Pearl River Delta urban agglomeration (PRD), six factors had significant impacts on urban CO2 emissions, all of which were positive except for slope, which was a negative factor. Due to China’s hierarchical administrative levels, the model results suggest that regardless of which level is adopted, the impacts of the driving factors on urban CO2 emissions are quite different at the national compared to the urban agglomeration level. The degrees of influence of most factors at the national level were lower than those of factors at the urban agglomeration level. Based on an analysis of the forces driving urban CO2 emissions, we propose that it is necessary that the environment play a guiding role while regions formulate policies which are suitable for emission reductions according to their distinct characteristics.

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Section: Introductionmentioning

confidence: 99%

What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

Wang

Gui-fen²,

Shi

2019

IJERPH

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“…In the demand side, LEAP was applied to estimate energy demand in the industrial, the transport, the commercial and the household sectors and to analyze the long-term energy policy, environmental impacts and GHG mitigation potential in many countries, i.e. Canada [ 30 ], China [ 31 ], Columbia [ 32 , 33 ], Nigeria [ 34 ], South Korea [ 35 ], Thailand [ 36 ], etc.…”

Section: Methodsmentioning

confidence: 99%

Thailand's long-term GHG emission reduction in 2050: the achievement of renewable energy and energy efficiency beyond the NDC

Misila

Winyuchakrit

Limmeechokchai

2020

Heliyon

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The sources of greenhouse gas (GHG) emissions in Thailand come from the energy sector, including power generation, transport, industries, buildings, and households. In 2016, the energy sector contributed 77 percent of total GHG emissions. Thailand's energy policies are the essential instrument to deal with GHG emission reduction under the United Nations Framework Convention on Climate Change (UNFCCC). The renewable energy (RE) plans aim at increasing the share of RE in final energy consumption while the energy efficiency (EE) plans aim at improving energy efficiency as well as reducing fossil-fuel consumption. GHG emission mitigation will result in several co-benefits such as increasing energy security and decreasing local air pollutants. Therefore, this study analyzes potentials of GHG emission reduction during 2015–2050 from utilization of renewable energy and increasing energy efficiency using the Long-range Energy Alternative Planning system (LEAP) model. Results include potentials of domestic RE and EE measures to achieve Thailand's nationally determined contribution (NDC). Moreover, it was found that to meet Thailand's first NDC of 20 percent GHG emission reduction target in 2030, targets in the RE plan and the EE plan must be achieved by at least 50 percent and 75 percent, respectively, or targets in the RE plan and the EE plan must be achieved by at least 75 percent and 50 percent. In addition, the extended NDC scenario in 2050 is analyzed in the long-term perspective of Thailand showing 30.4 percent reduction when compared to the BAU. The policy implication includes promotion of energy efficiency, acceleration of the deployment of renewable energy and advanced technologies such as CCS, completion of transmission network for renewable electricity, zoning of biomass sources, and public awareness in climate changes.

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“…Specifically, a portion of previous studies estimated the volume of GHGs for different industries, and studied emissions reduction strategies for an industry sector [ 11 , 12 , 13 , 14 , 15 , 16 ]. Additionally, a part of previous studies focused on GHGs in a particular region or in a group of regions [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Notably, considering that China was the world’s biggest emitter of GHGs, a large number of prior studies centered on measuring China’s GHGs, and investigated the corresponding reduction policies [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Evolution of Global Greenhouse Gas Emissions Transferring via Trade: Influencing Factors and Policy Implications

Zhong

Gao

2020

IJERPH

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Global climate change caused by greenhouse gas emissions (GHGs) from anthropogenic activities have already become the focus of the world. A more systematic and comprehensive analysis on the factors influencing the changes of global GHGs transferring via trade have not been fully discussed. To this end, employing spatial econometric regression models and multi-regional input-output models, this paper reveals factors influencing the GHGs transferring via trade changes in 39 major economies, so as to develop the relevant GHGs reduction policies. The results indicate that regions with the highest net outflow of GHGs transferring via trade are primarily Russia and Canada, and the adverse effects of promoting GHGs reduction on the national economy could be avoided by these regions owing to trade relations. Additionally, factors influencing the changes in GHGs transferring via trade have significant spatial autocorrelation, and population size and energy structure exert significant spatial spillover effects on the changes in the GHGs transferring via trade. On this basis, this paper suggests that one more effective way to prevent trade from the rigorous demands of environmental governance measures while preserving the economic benefits of international trade may be to facilitate cooperation between countries on GHGs mitigation. Further, we articulate more balanced environment governance policies, including conducting the sharing of advanced energy technologies and developing clearer production technologies.

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How will Canada’s greenhouse gas emissions change by 2050? A disaggregated analysis of past and future greenhouse gas emissions using bottom-up energy modelling and Sankey diagrams

Cited by 63 publications

References 37 publications

What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

Thailand's long-term GHG emission reduction in 2050: the achievement of renewable energy and energy efficiency beyond the NDC

Spatiotemporal Evolution of Global Greenhouse Gas Emissions Transferring via Trade: Influencing Factors and Policy Implications

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