Incorporation of electricity GHG emissions intensity variability into building environmental assessment

Cubí, Eduard; Doluweera, Ganesh; Bergerson, Joule

doi:10.1016/j.apenergy.2015.08.091

Cited by 32 publications

(18 citation statements)

References 6 publications

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“…Recent studies have generated a higher resolution of carbon EFs of electricity for Belgium (Messagie et al 2014) and Canada (Cubi et al 2015). However, the German grid system is somewhat unique in its sizeable share of vRES and the size of the power market, which renders the country an interesting case study for assessing the effect of the higher resolution on EF on quantifying carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

The trends of hourly carbon emission factors in Germany and investigation on relevant consumption patterns for its application

Kono

Ostermeyer

Wallbaum

2017

Int J Life Cycle Assess

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Purpose The share of variable renewable energy sources (vRES) in the German electricity grid has increased over the past few decades. Due to the nature of the generation pattern of vRES, the increase of vRES causes the emission factor (EF) to fluctuate on an hourly basis. This fluctuation raises concerns about the accuracy of quantifying emissions with the current metric of the annual average EF as the respective EF may change depending on the time at which it is consumed. Methods The study calculated the hourly EF of Germany from 2011 to 2015 and investigated the effect of an increase of vRES on the EF. The calculated hourly EF was clustered based on three aspects of time: the period of time, the time of a day, and the day of the week. Results and discussion The study showed a higher proportion of vRES on weekend daytimes while the weekday nighttimes resulted in a lower share than the annual average. The study highlighted potential underestimation and overestimation of emissions by using annual average EF which ranged from +22% (2015 weekday nighttime of October) to −34% (2015 weekend daytime of May). Conclusions The study suggested that the application of hourly EF may be necessary to quantify the respective emission from the consumers that use electricity during the weekend daytime and weekend nighttime. For consumer use at other times, the emissions could be quantified appropriately by using the conventional annual average EF.

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Section: Introductionmentioning

confidence: 99%

The trends of hourly carbon emission factors in Germany and investigation on relevant consumption patterns for its application

Kono

Ostermeyer

Wallbaum

2017

Int J Life Cycle Assess

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“…Nilsson et al [27] analyzed the change in residential electricity consumption through the possibility for the final customer to visualize the electricity prices in real-time. A similar path was followed by Cubi et al [28] in Canada, assessing the building environmental impacts related to the variability of the resources used during the day-time. Khan et al [29] approached the electricity mix environmental impacts with an analysis in which peak hours and off-peak hours were compared, leading to useful results for policy makers regarding Bangladesh's grid.…”

Section: Introductionmentioning

confidence: 82%

“…The functional unit for the environmental impact assessment is defined as one kWh of electricity produced and delivered to the grid, which is in line with previous studies of the environmental impacts of electricity generation [19,[26][27][28][29][30]. The impact category chosen for the assessment was global warming potential (GWP), using the CML 2015 life cycle impact assessment method [48].…”

Section: Goal and Scopementioning

confidence: 99%

“…Considering only the geographical borders avoids any possible misconception, as was also done by Khan [29]. Cubi et al [28] do not specify if imports and exports were counted, and Khan et al [30] did not include them. Furthermore, in a recent paper by Moro et al [44], four out of five targeted countries of this study (Bulgaria, Germany, Spain, and the Netherlands) had a very low carbon intensity variation of the electricity production after trading with other countries (−2%, +2%, −6%, and −1% respectively).…”

Section: Import/exportmentioning

confidence: 99%

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The Potential Role of Flexibility During Peak Hours on Greenhouse Gas Emissions: A Life Cycle Assessment of Five Targeted National Electricity Grid Mixes

et al. 2019

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On the path towards the decarbonization of the electricity supply, flexibility and demand response have become key factors to enhance the integration of distributed energy resources, shifting the consumption from peak hours to off-peak hours, optimizing the grid usage and maximizing the share of renewables. Despite the technical viability of flexible services, the reduction of greenhouse gas emissions has not been proven. Traditionally, emissions are calculated on a yearly average timescale, not providing any information about peak hours’ environmental impact. Furthermore, peak-hours’ environmental impacts are not always greater than on the base load, depending on the resources used for those time periods. This paper formulates a general methodology to assess the potential environmental impact of peak-hourly generation profiles, through attributional life cycle assessment. This methodology was applied to five different countries under the INVADE H2020 Project. Evaluation results demonstrate that countries like Spain and Bulgaria could benefit from implementing demand response activities considering environmental aspects, enhancing potential greenhouse gas reductions by up to 21% in peak hours.

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“…Buildings accounted for 32% of total global final energy use (equal to 117 ExaJoules), 19% of energy-related GHG emissions, 51% of global electricity consumption, 33% of black carbon emissions, and an eighth to a third of F-gases emission (large differences in F-gases data are due to differing accounting conventions) [2][3][4]. In particular, the building energy consumption in China recently surpassed the US building consumption, and it is expected to increase significantly in the next decades, pushed by the demand for new residential buildings [5][6][7][8]. In 2009, the building sector was responsible for one fifth of China's total primary energy consumption and 18% of the overall Chinese GHG emissions.…”

Section: Introductionmentioning

confidence: 99%

Decomposition and Decoupling Analysis of Life-Cycle Carbon Emission in China’s Building Sector

Jiang

2017

Sustainability

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Abstract:With accelerating urbanization, building sector has been becoming more important source of China's total carbon emission. In this paper, we try to calculate the life-cycle carbon emission, analyze influencing factors of carbon emission, and assess the delinking index of carbon emission in China's building sector. The results show: (i) Total carbon emission in China's building industry increase from 984.69 million tons of CO 2 in 2005 to 3753.98 million tons of CO 2 in 2013. The average annual growth rate is 18.21% per year. Indirect carbon emission from building material consumption accounted to 96-99% of total carbon emission. (ii) The indirect emission intensity effect was leading contributor to change of carbon emission. The following was economic output effects, which always contributed to increase in carbon emission. Energy intensity effect and energy structure effect took negligible role to offset carbon emission. (iii) Delinking index show the status between carbon emission and economic output in China's building industry during

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Incorporation of electricity GHG emissions intensity variability into building environmental assessment

Cited by 32 publications

References 6 publications

The trends of hourly carbon emission factors in Germany and investigation on relevant consumption patterns for its application

The trends of hourly carbon emission factors in Germany and investigation on relevant consumption patterns for its application

The Potential Role of Flexibility During Peak Hours on Greenhouse Gas Emissions: A Life Cycle Assessment of Five Targeted National Electricity Grid Mixes

Decomposition and Decoupling Analysis of Life-Cycle Carbon Emission in China’s Building Sector

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