Energy Consumption and Greenhouse Gas Emissions During Ferromolybdenum Production

AbstractMolybdenum is mainly used as an alloy material in the iron and steel industry and typically in the form of ferromolybdenum (FeMo). The current study aims to evaluate the energy consumption and greenhouse gas emissions (GHG) of four ferromolybdenum production cases using inventory inputs from a process model based on mass and energy conservations. The total energy required for producing 1 tonne of FeMo can vary between 29.1 GJ/t FeMo and 188.6 GJ/t FeMo. Furthermore, the corresponding GHG emissions differ from 3.16 tCO2-eq/t FeMo to 14.79 tCO2-eq/t FeMo. The main variances are from the mining and beneficiation stages. The differences in these stages come from the beneficiation degree (ore grade) and the mine type (i.e., co-product from copper mining). Furthermore, the mine type has a larger impact on the total energy consumption and GHG emissions than the beneficiation degree. More specifically, FeMo produced as co-product from copper mining has a lower environmental impact measured as the energy consumption and GHG emission among all the four cases. The inventory, consumed energy or associated GHG emission is independent on the initial ore grade and mine type in the downstream production stages such as roasting and smelting. Also, transport has the least impact on the energy consumption and GHG emission among all production stages.

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Energy Consumption and Greenhouse Gas Emissions of Nickel Products

Energies ◽

10.3390/en13215664 ◽

2020 ◽

Vol 13 (21) ◽

pp. 5664

Author(s):

Wenjing Wei ◽

Peter B. Samuelsson ◽

Anders Tilliander ◽

Rutger Gyllenram ◽

Pär G. Jönsson

Keyword(s):

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Process Model ◽

Ghg Emissions ◽

Primary Energy ◽

Nickel Metal ◽

Gas Emissions ◽

Nickel Smelting ◽

Ore Grade

The primary energy consumption and greenhouse gas emissions from nickel smelting products have been assessed through case studies using a process model based on mass and energy balance. The required primary energy for producing nickel metal, nickel oxide, ferronickel, and nickel pig iron is 174 GJ/t alloy (174 GJ/t contained Ni), 369 GJ/t alloy (485 GJ/t contained Ni), 110 GJ/t alloy (309 GJ/t contained Ni), and 60 GJ/t alloy (598 GJ/t contained Ni), respectively. Furthermore, the associated GHG emissions are 14 tCO2-eq/t alloy (14 tCO2-eq/t contained Ni), 30 t CO2-eq/t alloy (40 t CO2-eq/t contained Ni), 6 t CO2-eq/t alloy (18 t CO2-eq/t contained Ni), and 7 t CO2-eq/t alloy (69 t CO2-eq/t contained Ni). A possible carbon emission reduction can be observed by comparing ore type, ore grade, and electricity source, as well as allocation strategy. The suggested process model overcomes the limitation of a conventional life cycle assessment study which considers the process as a ‘black box’ and allows for an identification of further possibilities to implement sustainable nickel production.

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The Correlation between Residential Density and Greenhouse Gas Emissions in Surabaya City

The Indonesian Journal of Planning and Development ◽

10.14710/ijpd.1.1.29-34 ◽

2014 ◽

Vol 1 (1) ◽

pp. 29

Author(s):

Rulli Pratiwi Setiawan ◽

Ema Umilia ◽

Ketut Dewi Martha Erli Handayeni

Keyword(s):

Energy Consumption ◽

Population Growth ◽

Total Energy ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Ghg Emissions ◽

Residential Density ◽

Medium Density ◽

Font Size ◽

Gas Emissions

Population growth is happening in cities, including Surabaya as the second largest metropolitan region in Indonesia. The population growth has an impact to the residential density, whereas residential is usually the largest part of land use in urban areas. In urabaya, residential use covers more than 60% of the total area. The intensive use of residential area has impacts on the environment. One significant issue is the consumption of energy that produces greenhouse gas emissions. This study is aimed at explaining the relationships between residential density and greenhouse gas emissions in Surabaya City, Indonesia. The residential density will be divided into three categories, i.e. low, medium and high density. The category of density is taken from the Identification Report of Surabaya Spatial Plan. The results of this study indicate that there are significant differences in the electrical energy consumption for the household sector in each residential density. These differences are mainly influenced by variables such as car ownership, ventilation system, the use of electrical power, cooking fuel and the way to use the home appliances. The highest total energy consumption per month exists in high density type. Although the average smallest energy consumption per household exists in medium density, the total energy consumption in medium density is much greater than that in the low density because the number of households in medium density is greater. The final result shows that the correlation between the total production of GHG emissions (CO2) and density has a direct or positive relationship, which means that the greater the density, the higher the production rate of GHG emissions (CO2).<br style="font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;" />

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Analysis of Embodied Energy Consumption and Greenhouse Gas (GHG) Emissions in Chinese Manufacturing Industry

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.616-618.1148 ◽

2012 ◽

Vol 616-618 ◽

pp. 1148-1153

Author(s):

Dong Sun ◽

Chu Xia Tong

Keyword(s):

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Manufacturing Industry ◽

Ghg Emissions ◽

Calculation Model ◽

Embodied Energy ◽

Gas Emissions ◽

Electric Equipment ◽

Chinese Manufacturing Industry

This paper attempts to discuss the embodied energy consumption and embodied greenhouse gas emissions in manufacturing industry. Based the on input-output theory, this paper establishes the calculation model, which gives the calculation of embodied energy consumption and embodied greenhouse gas emissions of 2002 and 2007 respectively. By comparison, it draws the conclusion that the total direct energy consumption of 2007 is much more than the year of 2002, while the total embodied energy consumption is less than the year of 2002. However, Non-metallic mineral products, Metal smelting and pressing and Electric equipment and machinery perform otherwise. The reason accounting for the calculation results is that the embodied energy intensity is greatly decreased.

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Calculation of GHG Emissions in the Selected Air Traffic Company

MATEC Web of Conferences ◽

10.1051/matecconf/201823602009 ◽

2018 ◽

Vol 236 ◽

pp. 02009

Author(s):

Martina Hlatka ◽

Maria Stopkova

Keyword(s):

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Ghg Emissions ◽

Air Traffic ◽

Gas Emissions ◽

Automotive Component ◽

Transport Services ◽

Manufacturing Company ◽

Component Manufacturing

The paper is dedicated to calculating and declaring energy consumption and greenhouse gas emissions in an automotive component manufacturing company. The calculation was carried out on the bases of EN 16258. By this Directive, it is set out a procedure for determining the energy consumption and greenhouse gas emissions from transport services of all transport sectors.

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Comparative analysis of greenhouse gas emissions from three beef cattle herds in a corporate farming enterprise

Animal Production Science ◽

10.1071/an15579 ◽

2016 ◽

Vol 56 (3) ◽

pp. 482 ◽

Cited By ~ 1

Author(s):

Chris Taylor ◽

Richard Eckard

Keyword(s):

Beef Cattle ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Ghg Emissions ◽

Ghg Emission ◽

Relative Time ◽

Gas Emissions ◽

Herd Management ◽

Cattle Herds ◽

Alternative Scenarios

This study provided a gate-to-gate Life Cycle Assessment that modelled the greenhouse gas emissions (GHG) of three herds bred and grown by an integrated beef cattle enterprise across northern Australia. It involved modelling the GHG emissions of current herd management by the enterprise as a ‘baseline’ compared with ‘alternative scenarios’ of herd management. There were three herds (one herd of steers and two herds of heifers) each consisting of 5000 head of cattle. The baseline consisted of the steer herd grazing on growing then backgrounding properties and being finished at a feedlot. The two heifer herds grazed one respective backgrounding property each and were finished in a feedlot for their respective baselines. The alternative scenarios involved the steer herd bypassing the growing property and spending increased time at the backgrounding property. The heifer herds bypassed their respective backgrounding properties and they were grown and finished at a feedlot. The results show a 14% reduction of GHG emission intensities between the baseline and alternative scenario for steers and reductions of 29% and 4% between the baseline and alternative scenarios for the respective heifer herds. The variance in GHG emissions between the heifer herds can be explained by relative time spent grazing on the respective backgrounding properties and associated liveweight gain, versus time spent being grown and finished in the feedlot. In our modelling, herd GHG emission reductions occurred in the scenarios when time grazing on the growing or backgrounding properties (and associated liveweight gains) in the respective baselines exceeded 225–229 days for the heifer herds and between 206 days for the steers (depending on the relative liveweight gains on the properties). This means that if the cattle herds were to spend a longer time grazing on a property in their respective baselines than the number of days noted in our analysis, bypassing these properties would then result in net reductions in GHG emissions for the herds.

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Perceptions of Food Retailers Regarding Climate Change and Greenhouse Gas Emissions

11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES - Global Conference on Business and Social Sciences Proceeding ◽

10.35609/gcbssproceeding.2020.11(73) ◽

2020 ◽

Vol 11 (1) ◽

pp. 73-73

Author(s):

Ayanda Pamella Deliwe ◽

Shelley Beryl Beck ◽

Elroy Eugene Smith

Keyword(s):

Climate Change ◽

South Africa ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Food Chain ◽

Ghg Emissions ◽

Ghg Emission ◽

Gas Emissions ◽

Food Retailers ◽

Earth’S System

Greenhouse gas (GHG) emission and its associated effects have been a debate in literature for many years (Hoffman, 2011:5; Williams & Schaefer, 2012:175; Whitmarsh, 2011:690). According to Jackson (2016), climate change is seen as a yearly change within the earth's climate that is a result of changes in its atmosphere, as well as interactions between the atmosphere and other chemical, geologic, geographic and biological factors within the earth's system. Climate change has primarily caused a warming effect of the earth's atmosphere that has affected all aspects of life (Pachauri & Reisinger, 2007:7). While there are limited studies that measure greenhouse gas emissions arising from the entire global food chain, there have been estimates of GHG emissions attributable to global agricultural production (Garnett, 2011:23). Energy consumption is one of the biggest challenges food retailers are facing as it not only increases overhead costs but also GHG emission (Tassou, Hadawey & Marriott, 2011). Garnett (2011) alleges that the food chain produces greenhouse gas (GHG) emissions at all stages in its life cycle, from the farming process and its inputs, through to manufacture, distribution, refrigeration, retailing, food preparation in the home and waste disposal. Technological improvements, while essential, will not be sufficient in reducing GHG emissions. The combination of population growth and rising per capita anticipated consumption of meat and dairy products will undermine the cuts that technological and managerial innovation can achieve. Over the last few years food retailers in South Africa started to focus their attention towards GHG emissions, but there is still no framework for food retailers to reduce GHG emissions in South Africa (Tassou et al. 2007:2988). Various studies have argued that the food and drink, transportation, and construction industry sectors are regarded as the most significant contributors to GHG emissions (European Commission, 2006; SEI, WWF & CURE, 2006 and UNEP, 2008). Significant changes in food production and increases in food transport have resulted. The production of food on farms has become increasingly mechanised, large-scale, and specialised; and food supply chains have become more complicated and transport-intensive (Roelich, 2008). Food retailers are contributing to GHG emissions by means of electricity usage through refrigerator equipment, lighting, heating, air conditioning, baking and other secondary services. There is no general strategy for food retailers to reduce GHG emission and minimal research has been done in this sector (Tassou et al, 2011). Keywords: climate change; food retailers; greenhouse gas emission; perceptions; strategies

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Future greenhouse gas emissions from metal production: gaps and opportunities towards climate goals

Energy & Environmental Science ◽

10.1039/d1ee02165f ◽

2021 ◽

Author(s):

Ryosuke Yokoi ◽

Takuma Watari ◽

Masaharu Motoshita

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Emission Intensity ◽

Ghg Emissions ◽

Ghg Emission ◽

Metal Production ◽

Gas Emissions ◽

Per Capita

The projected GHG emissions cannot reach the climate goal under any SSP. Further efforts on lowering per capita in-use metal stocks and GHG emission intensity of metal production and promoting recycling are the key to achieve the climate goal.

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A comprehensive dataset for global, regional and national greenhouse gas emissions by sector 1970–2019

10.5194/essd-2021-228 ◽

2021 ◽

Author(s):

Jan C. Minx ◽

William F. Lamb ◽

Robbie M. Andrew ◽

Josep G. Canadell ◽

Monica Crippa ◽

...

Keyword(s):

Land Use ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Co2 Emissions ◽

Ghg Emissions ◽

N2o Emissions ◽

Ghg Emission ◽

High Confidence ◽

Gas Emissions ◽

Emission Growth

Abstract. To track progress towards keeping warming well below 2 °C, as agreed upon in the Paris Agreement, comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions (GHG) is required. Here we provide a dataset on anthropogenic GHG emissions 1970–2019 with a broad country and sector coverage. We build the dataset from recent releases of the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases, and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with data on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three bookkeeping models. We provide an assessment of the uncertainties in each greenhouse gas at the 90 % confidence interval (5th–95th percentile) by combining statistical analysis and comparisons of global emissions inventories with an expert judgement informed by the relevant scientific literature. We identify important data gaps: CH4 and N2O emissions could be respectively 10–20 % higher than reported in EDGAR once all emissions are accounted. F-gas emissions estimates for individual species in EDGARv5 do not align well with atmospheric measurements and the F-gas total exceeds measured concentrations by about 30 %. However, EDGAR and official national emission reports under the UNFCCC do not comprehensively cover all relevant F-gas species. Excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are larger than the sum of the reported species. GHG emissions in 2019 amounted to 59 ± 6.6 GtCO2eq: CO2 emissions from FFI were 38 ± 3.0 Gt, CO2 from LULUCF 6.6 ± 4.6 Gt, CH4 11 ± 3.3 GtCO2eq, N2O 2.4 ±1.5 GtCO2eq and F-gases 1.6 ± 0.49 GtCO2eq. Our analysis of global, anthropogenic GHG emission trends over the past five decades (1970–2019) highlights a pattern of varied, but sustained emissions growth. There is high confidence that global anthropogenic greenhouse gas emissions have increased every decade. Emission growth has been persistent across different (groups of) gases. While CO2 has accounted for almost 75 % of the emission growth since 1970 in terms of CO2eq as reported here, the combined F-gases have grown at a faster rate than other GHGs, albeit starting from low levels in 1970. Today, F-gases make a non-negligible contribution to global warming – even though CFCs and HCFCs, regulated under the Montreal Protocol and not included in our estimates, have contributed more. There is further high confidence that global anthropogenic GHG emission levels were higher in 2010-2019 than in any previous decade and GHG emission levels have grown across the most recent decade. While average annual greenhouse gas emissions growth slowed between 2010–2019 compared to 2000–2009, the absolute increase in average decadal GHG emissions from the 2000s to the 2010s has been the largest since the 1970s – and within all human history as suggested by available long-term data. We note considerably higher rates of change in GHG emissions between 2018 and 2019 than for the entire decade 2010–2019, which is numerically comparable with the period of high GHG emissions growth during the 2000s, but we place low confidence in this finding as the majority of the growth is driven by highly uncertain increases in CO2-LULUCF emissions as well as the use of preliminary data and extrapolation methodologies for these most recent years. While there is a growing number of countries today on a sustained emission reduction trajectory, our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. We conclude by highlighting that tracking progress in climate policy requires substantial investments in independent GHG emission accounting and monitoring as well as the available national and international statistical infrastructures. The data associated with this article (Minx et al. 2021) can be found at https://doi.org/10.5281/zenodo.5053056.

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Optimization of energy consumption and its effect on the energy use efficiency and greenhouse gas emissions of wheat production in Turkey

Discover Sustainability ◽

10.1007/s43621-021-00035-w ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Muhammad Imran ◽

Orhan Ozcatalbas

Keyword(s):

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Energy Use ◽

Ghg Emissions ◽

Average Energy ◽

Green Economy ◽

Energy Output ◽

Gas Emissions ◽

Wheat Production

AbstractThis study aimed to model energy use, energy efficiency, and greenhouse gas emissions in rain-fed wheat production by using a nonparametric data envelopment analysis (DEA) method. Data were collected through face-to-face interviews with 140 wheat farmers in 4 districts of Antalya Province. The energy inputs (independent variables) were human labor, seeds, chemical fertilizers, herbicides, and diesel fuel, and the energy output was the dependent variable. The results showed that the average energy consumption and the output energy for the studied wheat production system were 21. 07GJ ha−1 and 50. 99 GJ ha−1, respectively, and the total GHG emissions were calculated to be 592.12 kg CO2eq ha−1. Chemical fertilizer has the highest share of energy consumption and total GHG emissions. Based on the results from DEA, the technical efficiency of the farmers was found to be 0.81, while pure technical and scale efficiencies were 0.65 and 0.76, respectively. The results also highlighted that there is a potential opportunity to save approximately 14% (2.93 GJ ha−1) of the total energy consumption and consequently a 17% reduction in GHG emissions by following the optimal amounts of energy consumption while keeping the wheat yield constant. Efficient use of energy and reduction in GHG emissions will lead to resource efficiency and sustainable production, which is the main aim of the green economy.

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Analysing Nexus between Economic Growth, GHG Emissions, and Energy Consumption for India

Journal of Resources Energy and Development ◽

10.3233/red-170101 ◽

2021 ◽

Vol 17 (1) ◽

pp. 1-16

Author(s):

Asim Hasan ◽

Rahil Akhtar Usmani

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Carbon Emissions ◽

Series Data ◽

Gas Emissions ◽

Current Time ◽

Causal Influence ◽

Integration Test

Rising greenhouse gas emissions is an important issue of the current time. India’s massive greenhouse gas emissions is ranked third globally. The escalating energy demand in the country has opened the gateway for further increase in emissions. Recent studies suggest strong nexus between energy consumption, economic growth, and carbon emissions. This study has the objective to empirically test the aforementioned interdependencies. The co-integration test and multivariate vector error correction model (VECM) are used for the analysis and the Granger Causality test is used to establish the direction of causality. The time-series data for the period of 1971–2011 is used for the analysis. The results of the study confirm strong co-integration between variables. The causality results show that economic growth exerts a causal influence on carbon emissions, energy consumption exerts a causal influence on economic growth, and carbon emissions exert a causal influence on economic growth. Based on the results, the study suggests a policy that focuses on energy conservation and gradual replacement of fossil fuels with renewable energy sources, which would be beneficial for the environment and the society.

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