The Chinese nonferrous metals industry—energy use and CO2 emissions

Wang, Yanjia; Chandler, William U.

doi:10.1016/j.enpol.2009.03.054

Cited by 55 publications

(15 citation statements)

References 1 publication

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“…Demand is growing due to both an increasing per capita appetite for commodities and global population growth, projected to reach 8.9 billion in 2050 (Coleman, 2004). Higher production, coupled with declining ore grades, is placing increasing pressure on the natural environment (Mudd, 2007(Mudd, , 2009Norgate and Haque, 2010;Yanjia and Chandler, 2010). Lower ore grades require more energy to process due to larger volumes of waste rock.…”

Section: Introductionmentioning

confidence: 98%

Life cycle assessment: a time-series analysis of copper

Memary

Giurco

Mudd

et al. 2012

Journal of Cleaner Production

101

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Section: Introductionmentioning

confidence: 98%

Life cycle assessment: a time-series analysis of copper

Memary

Giurco

Mudd

et al. 2012

Journal of Cleaner Production

101

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“…When considering the recycling process, data availability of EF per material in each location limits the estimation of GHG emissions. Moreover, comparison of GHG emissions is complex because of the differences encountered in the collection and recycling methods of materials according to the technological level applied [31] for different locations. However, different methods to obtain recycling EF per material are based on ISO 14067 and PAS 2050 standards, which is why emission factors are directly applied in the proposed methodology.…”

Section: Treatment Of Emissions Associated With Recyclingmentioning

confidence: 99%

A Cradle-to-Grave Multi-Pronged Methodology to Obtain the Carbon Footprint of Electro-Intensive Power Electronic Products

2019

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This paper proposes the application of a cradle-to-grave multi-pronged methodology to obtain a more realistic carbon footprint (CF) estimation of electro-intensive power electronic (EIPE) products. The literature review shows that methodologies for establishing CF have limitations in calculation or are not applied from the conception (cradle) to death (grave) of the product; therefore, this paper provides an extended methodology to overcome some limitations that can be applied in each stage during the life cycle assessment (LCA). The proposed methodology is applied in a cradle-to-grave scenario, being composed of two approaches of LCA: (1) an integrated hybrid approach based on an economic balance and (2) a standard approach based on ISO 14067 and PAS 2050 standards. The methodology is based on a multi-pronged assessment to combine conventional with hybrid techniques. The methodology was applied to a D-STATCOM prototype which contributes to the improvement of the efficiency. Results show that D-STATCOM considerably decreases CF and saves emissions taken place during the usage stage. A comparison was made between Sweden and China to establish the environmental impact of D-STATCOM in electrical networks, showing that saved emissions in the life cycle of D-STATCOM were 5.88 and 391.04 ton CO 2 eq in Sweden and China, respectively.

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“…However, the technological equipment that firms use ages; new equipment will often be needed to replace the old equipment. With technical progress of production processes, we assume that more‐advanced equipment is more energy efficient, producing less GHG emissions per output than less‐advanced equipment; examples are provided by Whitaker and colleagues () for coal‐fired electricity generation and Yanjia and Chandler () for the Chinese nonferrous metals industry. Hence, we expect that facilities that have undergone large investments in recent years will have lower specific emissions than those installed years ago.…”

Section: Hypotheses and Measuresmentioning

confidence: 99%

Estimating Corporate Carbon Footprints with Externally Available Data

Goldhammer¹,

Busse²,

Busch³

2016

J of Industrial Ecology

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Summary Corporate carbon footprints (CCFs) are a core tool in greenhouse gas emissions reporting. Established approaches for CCF calculation are based on an internal perspective that requires detailed corporate information. However, many firms do not publish information about their emissions. We seek to close this data gap by estimating scope 1 and 2 CCFs from an external perspective. The study uses a regression analysis approach, using actual firm‐internally computed CCFs to assess their degree of predictability from the outside. Data were collected from 93 European companies belonging to the chemicals, construction and engineering, and industrial machinery sectors. As predictors, we use five measures that are computed with publicly available corporate data: firm size; level of vertical integration; capital intensity; centrality of production; and carbon intensity of the national energy mix. The analysis shows that significant explanatory power for the CCF can be observed for size, capital intensity, and centrality of production. The best estimation results are achieved when data from different sectors are integrated into a comprehensive all‐sector model, while accounting for sector‐specific emission intensities by means of dummy variables. With an adjusted R² value of 0.817, the proposed procedure estimates CCFs in an accurate, yet also efficient, manner. Moreover, the study enhances trust in the current CCF calculation practices by showing that their results are plausible from a third‐party perspective.

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The Chinese nonferrous metals industry—energy use and CO2 emissions

Cited by 55 publications

References 1 publication

Life cycle assessment: a time-series analysis of copper

Life cycle assessment: a time-series analysis of copper

A Cradle-to-Grave Multi-Pronged Methodology to Obtain the Carbon Footprint of Electro-Intensive Power Electronic Products

Estimating Corporate Carbon Footprints with Externally Available Data

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