Energy and greenhouse gas impacts of mining and mineral processing operations

20 - Life cycle assessment of iron ore mining and processing

Chapter 20 - Life cycle assessment of iron ore mining and processing

Analysis of life-cycle GHG emissions for iron ore mining and processing in China—Uncertainty and trends

Development of disaggregated energy use and greenhouse gas emission footprints in Canada’s iron, gold, and potash mining sectors

Simple SummaryLivestock accounts for an estimated 80% of total agricultural greenhouse gas emissions, making abatement of greenhouse gas emissions from livestock a high-priority challenge facing animal nutritionists. Mitigating greenhouse gases in ruminants without reducing animal production is desirable both as a strategy to reduce global greenhouse gas emissions and as a way of improving dietary feed efficiency. The inclusion of feed additives in the diets of ruminants can reduce energy losses as methane, which typically reduces animal performance and contributes to greenhouse gas emissions. The present study evaluated the abatement potential of nine essential oil blends to mitigate greenhouse gas emissions. The inclusion of the blends resulted in a reduction in greenhouse gas emissions and in vitro apparent dry matter digestibility with higher values noted for the control treatment. A similar trend was noted for in vitro truly dry matter digestibility with higher values noted in the control treatment. The efficiency of microbial production was greater for the blends. The inclusion of the blends affected the total and molar proportion of volatile fatty acid concentrations. Overall, inclusion of the blends modified the rumen function resulting in improved efficiency of microbial production.The current study evaluated nine essential oil blends (EOBs) for their effects on ruminal in vitro dry matter digestibility (IVDMD), efficiency of microbial production, total short-chain fatty acid concentration (SCFA), total gas, and greenhouse gas (GHG) emissions using two dietary substrates (high forage and high concentrate). The study was arranged as a 2 × 2 × 9 + 1 factorial design to evaluate the effects of the nine EOBs on the two dietary substrates at two time points (6 and 24 h). The inclusion levels of the EOBs were 0 µL (control) and 100 µL with three laboratory replicates. Substrate × EOBs × time interactions were not significant (p > 0.05) for total gas and greenhouse gas emissions. The inclusion of EOBs in the diets resulted in a reduction (p < 0.001) in GHG emissions, except for EOB1 and EOB8 in the high concentrate diet at 6 h and for EOB8 in the high forage diet at 24 h of incubation. Diet type had no effect on apparent IVDMD (IVADMD) whereas the inclusion of EOBs reduced (p < 0.05) IVADMD with higher values noted for the control treatment. The efficiency of microbial production was greater (p < 0.001) for EOB treatments except for EOB1 inclusion in the high forage diet. The inclusion of EOBs affected (p < 0.001) the total and molar proportion of volatile fatty acid concentrations. Overall, the inclusion of the EOBs modified the rumen function resulting in improved efficiency of microbial production. Both the apparent and truly degraded DM was reduced in the EOB treatments. The inclusion of EOBs also resulted in reduced GHG emissions in both diets, except for EOB8 in the high forage diet which was slightly higher than the control treatment.

The greenhouse gas impact of IPCC and ore-sorting technologies

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Low-carbon production of iron and steel: Technology options, economic assessment, and policy

This paper examines the water quality legacies of historic and current iron mining in the Mesabi Range, the most productive iron range in the history of North America, producing more than 42% of the world's iron ore in the 1950s. Between 1893 and 2016, 3.5×109t of iron ore were shipped from the Mesabi Range to steel plants throughout the world. We map historic sites and quantities of iron mining, ore processing, water use, and tailings deposition within subwatershed boundaries. We then map the locations of impaired lakes within HUC-12 subwatershed boundaries within the Mesabi Range, using government datasets created for US federal Clean Water Act reporting. Comparing watersheds with and without historic mining activity, watersheds with historic mining activity currently contain a greater percentage of impaired lakes than control watersheds within the same range. These results suggest that historic iron ore mining and processing in the Mesabi Range affected water quality on a landscape scale, and these legacies persist long after the mines have closed. This paper outlines a novel spatial approach that land managers and policy makers can apply to other landscapes to assess the effects of past mining activity on watershed health.

System Integration of Automated Mine Optimization System

Simple SummaryDairy farm system practices aimed at reducing nitrate leaching can also reduce emissions of the greenhouse gases methane and nitrous oxide. A study comparing ‘current’ and ‘improved’ grazed dairy system practices showed that ‘improved’ systems generally produced lower greenhouse gas emissions while milk production was maintained. The amount of feed eaten per hectare was the key driver of total greenhouse gas emissions per area, with ‘improved’ systems generally exhibiting lower total enteric methane and less N flowing through the herd.An important challenge facing the New Zealand (NZ) dairy industry is development of production systems that can maintain or increase production and profitability, while reducing impacts on receiving environments including water and air. Using research ‘farmlets’ in Waikato, Canterbury, and Otago (32–200 animals per herd), we assessed if system changes aimed at reducing nitrate leaching can also reduce total greenhouse gas (GHG) emissions (methane and nitrous oxide) and emissions intensity (kg GHG per unit of product) by comparing current and potential ‘improved’ dairy systems. Annual average GHG emissions for each system were estimated for three or four years using calculations based on the New Zealand Agricultural Inventory Methodology, but included key farmlet-specific emission factors determined from regional experiments. Total annual GHG footprints ranged between 10,800 kg and 20,600 kg CO2e/ha, with emissions strongly related to the amount of feed eaten. Methane (CH4) represented 75% to 84% of the total GHG footprint across all modelled systems, with enteric CH4 from lactating cows grazing pasture being the major source. Excreta deposition onto paddocks was the largest source of nitrous oxide (N2O) emissions, representing 7–12% of the total GHG footprint for all systems. When total emissions were represented on an intensity basis, ‘improved’ systems are predicted to generally result in lower emissions intensity. The ‘improved’ systems had lower GHG footprints than the ‘current’ system, except for one of the ‘improved’ systems in Canterbury, which had a higher stocking rate. The lower feed supplies and associated lower stocking rates of the ‘improved’ systems were the key drivers of lower total GHG emissions in all three regions. ‘Improved’ systems designed to reduced N leaching generally also reduced GHG emissions.

This dissertation explores the intersection between mining technology, industrial heritage, and environmental history, using iron mining in the Mesabi Range of the Lake Superior Iron District as its core case study. What impact did technological shifts in iron mining and ore processing have on the environment of the Lake Superior basin? How did the environmental changes wrought from low-grade iron ore mining and processing, such as the expansion of open-pits and the production of tailings, affect different communities in Minnesota’s Mesabi Range? And finally, how have the environmental legacies of iron mining been remembered and memorialized, or ignored and forgotten?

By-product and heat-recovery cokemaking technologies each offer the steelmaker different opportunities to develop the steelworks' energy balance with the aim to achieve a lower environmental footprint. This paper discusses the results of a Greenhouse Gas (GHG) footprint study completed by Hatch, comparing the GHG emissions of a conventional by-product coke plant with a heat-recovery coke plant within an integrated steel mill. Natural gas and fuel oil were considered as additional fuel sources where coke oven gas was not available. The study followed the Greenhouse Gas Protocol guidelines and reported direct and indirect GHG emissions from the steel plant. The following were the major findings of the study: A steel mill with a heat-recovery coke plant, a blast furnace that used 100% iron ore pellets and where natural gas was used to supplement the steel plant heat balance emitted the lowest total amount of CO2 (1.96 ton CO2/ton HRC). Total GHG emissions from steel mills with heat-recovery coke plants, using natural gas to supplement the steel plant heat balance were lower than those with by-product coke plants in similar steel mill configurations. Total GHG emissions from steel mills with heat-recovery coke plants, using fuel oil, to supplement the steel mill energy balance were also lower than those with comparable steel mills using a by-product coke plant. An integrated steel mill with a by-product coke plant had the lowest Scope 1 GHG emission that represents the emissions from the steel mill site itself. Evaluation of the electricity production as presented in the Scope 2 GHG emissions was essential to understand the complete carbon footprint story as this significantly improved the overall carbon footprint of the steel mill using a heat recovery cokemaking process. INTRODUCTION Iron and steelmaking are fossil fuel energy intensive processes with the global steel industry accounting for between 4% and 5% of total man-made greenhouse gases. The average CO2 intensity for the steel industry is approximately 2.0 tons of CO2 per ton of steel produced. Taking into consideration global steel production of more than 1.3 billion tons, the steel industry produces over two billion tons of CO2 annually. In the fast growing economies of countries such as Brazil, China and India, a major increase in the volume of steel used/produced is anticipated and as a consequence, increased CO2 emissions will result. In conventional steel production, the first step of ironmaking is to carbonize metallurgical coal into blast furnace coke in a coke plant. The resulting coke is charged together with iron ore (pellets and/or sinter) and fluxes (limestone and dolomite) into a blast furnace where iron ore is transformed or smelted into liquid hot metal and slag. The hot metal is then refined to make liquid steel that is cast and rolled into salable products. The main carbon emissions are from the ironmaking processes; cokemaking, sinter/pellet production and blast furnace ironmaking. To foster an energy-efficient process and reduce the carbon footprint, the steel industry improved existing processes and implemented new process technologies with a special focus on the ironmaking area. By-product and heat-recovery cokemaking technologies each offer the steelmaker different opportunities to develop the steelworks' energy balance with the aim of achieving a smaller environmental footprint. This paper compares the GHG emissions of a conventional by-product coke plant with SunCoke's heat-recovery coke plant within an integrated steel mill. Where coke oven gas was not available, natural gas and fuel oil were considered as additional fuel sources. The study followed the Greenhouse Gas Protocol guidelines and reported both direct and indirect GHG emissions from the steel plant. To objectively compare the effect of the cokemaking process on the overall steel mill carbon footprint, a coke plant, blast furnace, BOF-continuous caster and hot strip mill arrangement were considered. Plant arrangements with and without a sinter plant were evaluated. The steel mill capacity used for this study was 3.1 million ton/annum of hot rolled coil (HRC) based on an annual coke production of 1.1 million tons.

Deep Learning in Mining and Mineral Processing Operations: A Review

Economic Impact Analysis of Automated Mines in Australia