Land use change and related carbon emissions from metal mines in Canada: An industry-level review

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Land-use changes are critical for climate policy because native vegetation and soils store abundant carbon and their losses from agricultural expansion, together with emissions from agricultural production, contribute about 20 to 25 per cent of greenhouse gas emissions1,2. Most climate strategies require maintaining or increasing land-based carbon3 while meeting food demands, which are expected to grow by more than 50 per cent by 20501,2,4. A finite global land area implies that fulfilling these strategies requires increasing global land-use efficiency of both storing carbon and producing food. Yet measuring the efficiency of land-use changes from the perspective of greenhouse gas emissions is challenging, particularly when land outputs change, for example, from one food to another or from food to carbon storage in forests. Intuitively, if a hectare of land produces maize well and forest poorly, maize should be the more efficientuse of land, and vice versa. However, quantifying this difference and the yields at which the balance changes requires a common metric that factors in different outputs, emissions from different agricultural inputs (such as fertilizer) and the different productive potentials of land due to physical factors such as rainfall or soils. Here we propose a carbon benefits index that measures how changes in the output types, output quantities and production processes of a hectare of land contribute to the global capacity to store carbon and to reduce total greenhouse gas emissions. This index does not evaluate biodiversity or other ecosystem values, which must be analysed separately. We apply the index to a range of land-use and consumption choices relevant to climate policy, such as reforesting pastures, biofuel production and diet changes. We find that these choices can have much greater implications for the climate than previously understood because standard methods for evaluating the effects of land use4-11 on greenhouse gas emissions systematically underestimate the opportunity of land to store carbon if it is not used for agriculture.

Many of the sustainability concerns of bioenergy are related to direct or indirect land use change (LUC) resulting from bioenergy feedstock production. The environmental and socio‐economic impacts of LUC highly depend on the site‐specific biophysical and socio‐economic conditions. The objective of this study is to spatiotemporally assess the potential LUC dynamics resulting from an increased biofuel demand, the related greenhouse gas (GHG) emissions, and the potential effect of LUC mitigation measures. This assessment is demonstrated for LUC dynamics in Brazil towards 2030, considering an increase in the global demand for bioethanol as well as other agricultural commodities. The potential effects of three LUC mitigation measures (increased agricultural productivity, shift to second‐generation ethanol, and strict conservation policies) are evaluated by using a scenario approach. The novel modelling framework developed consists of the global Computable General Equilibrium model MAGNET, the spatiotemporal land use allocation model PLUC, and a GIS‐based carbon module. The modelling simulations illustrate where LUC as a result of an increased global ethanol demand (+26 × 109 L ethanol production in Brazil) is likely to occur. When no measures are taken, sugar cane production is projected to expand mostly at the expense of agricultural land which subsequently leads to the loss of natural vegetation (natural forest and grass and shrubland) in the Cerrado and Amazon. The related losses of above and below ground biomass and soil organic carbon result in the average emission of 26 g CO2‐eq/MJ bioethanol. All LUC mitigation measures show potential to reduce the loss of natural vegetation (18%–96%) as well as the LUC‐related GHG emissions (7%–60%). Although there are several uncertainties regarding the exact location and magnitude of LUC and related GHG emissions, this study shows that the implementation of LUC mitigation measures could have a substantial contribution to the reduction of LUC‐related emissions of bioethanol. However, an integrated approach targeting all land uses is required to obtain substantial and sustained LUC‐related GHG emission reductions in general.

The Brazilian Cerrado is a large and expanding agricultural frontier, representing a hotspot of land‐use change (LUC) from natural vegetation to farmland. It is known that this type of LUC impacts soil organic matter (SOM) dynamics, particularly labile carbon (C) pools (living and non‐living), decreasing soil health and agricultural sustainability, as well as increasing soil greenhouse gas (GHG) emissions, and accelerating global climate change. In this study, we quantified the changes in the quantity and quality of SOM and GHG fluxes due to changes in land use and cropland management in the Brazilian Cerrado. The land uses studied were native vegetation (NV), pasture (PA) and four croplands, including the following management types: conventional tillage with a single soybean crop (CT), and three no‐tillage systems with two crops cultivated in the same year (i.e., soybean/sorghum (NT SSo ), soybean/millet (NT SMi ) and maize/sorghum (NT MSo )). Soil and gases were sampled in the rainy season (November, December and January) and dry season (May, July and September). The highest soil C and nitrogen (N) stocks (6.7 kg C m −2 and 0.5 kg N m −2 , 0–0.3‐m layer) were found under NV. LUC reduced C stocks by 25% in the CT and by 10% in the PA and NT. Soil N stocks were 30% lower in the PA and NT MSo and 15% lower in the croplands with soybean compared to NV. δ 13 C values clearly distinguished between the C‐origin from NV (−25‰) and that from other land uses (−16‰). Soil (0–0.1 m) under NV also presented higher labile‐C (625 g C m −2 ), microbial‐C (70 g C m −2 ) and microbial‐N (5.5 g N m −2 ), whereas other land uses presented values three times lower. GHG emissions (expressed as C‐equivalent) were highest in the NV (1.2 kg m −2 year −1 ), PA (1.3 kg m −2 year −1 ) and NT MSo (0.9 kg m −2 year −1 ) and were positively related to the higher SOM turnover in these systems. Our results suggest that in order to maintain SOM, it is necessary to adopt “best” management practices, that provide large plant residue inputs (above‐ and belowground). This can be seen as a pathway to achieving high food production with low GHG emissions.

Dairy farming is a major source of greenhouse gas (GHG) emissions in agriculture. There are numerous scientific studies analysing GHG flows and testing GHG reduction methods in dairy farming, yet very few scientific papers cover all the relevant GHG flows. GHG flows that are difficult to quantify, such as C sequestration in soils, the effects of land-use change (LUC) or the energy input used to produce capital equipment, are not always considered.This paper describes the development and application of a model for energy and GHG accounting in dairy farming. This new model enables all relevant nutrient, energy and GHG flows to be modelled at farm level. This then forms the basis for system analysis and derivation of GHG mitigation strategies. The model was used on 18 organic and 18 con-ventional farms in Germany. Calculated CO2-eq emissions per kg of Energy Corrected Milk (ECM) were 995 g on average for organic farms (org) and 1,048 g on average for conventional farms (con). The largest contribution (55 % (org) and 43 % (con)) to total GHG emissions came from enteric methane emissions (549 g CO2-eq (kg ECM)-1 (org) and 449 g CO2-eq (kg ECM)-1 (con)). On the organic dairy farms, there was an increase in soil humus and therefore carbon storage and sequestration in soils, whereas the GHG emissions for the conventional farms included CO2 emissions from LUC due to soybean usage. The significantly higher energy input in the conventional systems resulted from the production of energy-intensive concentrates, mineral fertilisers and pesticides, and transportation (imported feed).This study shows that there are many factors that influence GHG emissions in dairy farming, and that these factors often interact with each other. An increase in productivity is one of several optimisation strategies; however, it must not be at the expense of productive lifetime or require an extremely high amount of concentrates. GHG reduction in dairy farming requires farm-specific optimisation approaches due to the heterogeneity of production systems.

Greenhouse gas (GHG) emissions resulting from the Land Use, Land-Use Change, and Forestry sector (LULUCF) are estimated and reported in National Communications to the United Nations Framework Convention on Climate Change (UNFCCC). By definition, the LULUCF sector is a “greenhouse gas (GHG) inventory sector that covers emissions and removals of greenhouse gases resulting from direct human-induced land use, land-use change and forestry activities”. In principle, the annual GHG national inventory should be transparent, consistent, comparable, complete, and accurate. Also, it should be able to systematically account for all changes in land use and forest cover over many years. In this context, it is essential to investigate the development of an automated approach for mapping local GHG emissions/removals from the LULUCF sector for integration at the national level. In view of that, the aim of this work was to develop a semi-automated model for estimating GHG emissions and removals form the LULUCF sector at the local level. The specific objectives were to 1) map changes in land use and forest cover between two consecutive years, and 2) assess GHG emissions and removals from the LULUCF sector. The methodology of work comprised the use of Geographic Object-Based Image Analysis (GEOBIA) for modelling changes in the LULUCF sector and, subsequently, estimating GHG emissions/removals between two consecutive years. The combined use of Very High Resolution (VHR) SPOT imagery (2.5 m colour) and field data was involved in identifying and mapping land-use changes between 2014 and 2015. Subsequently, GHG emissions and removals were estimated using customized features in GEOBIA and following the 2003 Intergovernmental Panel on Climate Change “Good Practice Guidance for Land Use, Land-Use Change and Forestry”, which adopts a land use category-based approach to estimate emissions/removals from all land categories and all relevant GHGs. An accuracy assessment of the initial classification was conducted with the use of reference data. The overall classification accuracy of the LULUCF mapping in 2014 was found to be 83%, while the Kappa Index of Agreement (KIA) was 0.74. The developed GEOBIA model estimated for the year 2015 net annual GHG removals of -1.613 Gg of CO2 eq. (i.e., an approximate increase of 12.7% in removals between 2014 and 2015). Future work will involve further development of the model to account for all possible changes in the LULUCF sector and test the transferability of the model to other sites.

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The land use, land use change and forestry (LULUCF) sector is a greenhouse gas (GHG) inventory sector that covers the emissions of GHGs from and their removal by terrestrial carbon stocks, living biomass, dead organic matter and soil organic carbon according to six main anthropogenic land use categories: Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land. According to the United Nations Framework Convention on Climate Change (UNFCCC), all Parties shall periodically report an update inventory of anthropogenic emissions and removals of GHGs using comparable methodologies provided by the Intergovernmental Panel on Climate Change (IPCC). Parties are also required to report and account for such emissions under the Kyoto Protocol (KP). These emission inventories are then factored into an international reduction target commitment. In recent years, international negotiations have resulted in the adoption of new rules for the second commitment period of the KP (CP2: 2013-2020), e.g. mandatory accounting of Forest management. Furthermore, Decision 529/2013/EU goes beyond the international UNFCCC negotiations by adding the mandatory accounting of Cropland management and Grassland management. All these changes pose new challenges that Member States (MS) will need to address from 2015 (i.e. the start of the CP2 reporting period). This report describes the actions undertaken in the context of the JRC’s “LULUCF MRV” (Monitoring, Reporting, and Verification) Administrative Arrangement with DG CLIMA, through a sequence of tasks (described in detail in the Annexes). The aim of the AA is to support MS in improving the quality and comparability of their LULUCF reporting during CP2, in line with IPCC methods and the new UNFCCC and EU rules. .

Life-cycle analysis (LCA) is an important tool used to assess the energy and environmental impacts of biofuels. Here, we review biofuel LCA methodology and its application in transportation fuel regulations in the United States, the European Union, and the United Kingdom. We examine the application of LCA to the production of ethanol from corn, sugarcane, corn stover, switchgrass, and miscanthus. A discussion of methodological choices such as co-product handling techniques in biofuel LCA is also provided. Further, we discuss the estimation of greenhouse gas (GHG) emissions of land use changes (LUC) potentially caused by biofuels, which can significantly influence LCA results. Finally, we provide results from LCAs of ethanol from various sources. Regardless of feedstock, bioethanol offers reduced GHG emissions over fossil-derived gasoline, even when LUC GHG emissions are included. This is mainly caused by displacement of fossil carbon in gasoline with biogenic carbon in ethanol. Of the ethanol pathways examined, corn ethanol has the greatest life-cycle GHG emissions and offers 30% reduction in life-cycle GHG emissions as compared to gasoline when LUC GHG emissions are included. Miscanthus ethanol demonstrates the highest life-cycle GHG emissions reductions compared to gasoline, 109%, when LUC GHG emissions are included.

The carbon emissions related to the land-use changes from 2000 to 2015 in Shenzhen, China: Implication for exploring low-carbon development in megacities.

At the UN climate change conference in Paris in November 2015, Norway committed itself to a 40% reduction in greenhouse gas (GHG) emissions by 2030 compared to 1990 levels. Agriculture accounts for 8% of Norway’s total GHG emissions. If GHGs from drained and cultivated wetland (categorized under land use, land use change and forestry) are included, the share is 13%; this for a sector that accounts for roughly 0.3% of GDP. As is the case in most countries, agriculture is currently exempt from emission reduction measures, including the European Union’s Emissions Trading System (ETS), in which Norway participates. But the country has recently signaled its intention to include agriculture in future emission reduction efforts. Consideration is being given to how best to achieve GHG reductions in the sector. A recent report by the Norwegian Green Tax Commission, established by the government to evaluate policy options for achieving emission reductions, (Government of Norway, 2015) emphasizes the importance of including agriculture. The Commission suggests that agricultural emissions should be taxed at the same rate as for other sectors. It also recommends that reductions in the production and consumption of red meat should be specifically targeted, through cuts in production grants to farmers and the imposition of consumption taxes. Unsurprisingly, this proposed policy shift is extremely controversial and faces resistance, particularly from the farmers’ unions. Farmers argue that the maintenance of domestic agricultural production is crucial for achieving national food security objectives, in addition to pursuing other aims such as the maintenance of economic activity in rural areas and landscape preservation. Food security, which has been a key policy objective since the end of the Second World War, has been interpreted in Norway as requiring high levels of selfsufficiency in basic agricultural commodities. To achieve this, substantial subsidies are provided to farmers and domestic prices of many commodities are kept at high levels by restricting imports. The Organization for Economic Cooperation and Development (OECD) estimates that the total financial support provided to Norwegian agriculture in 2015 was equivalent to 62% of the value of gross farm receipts, which made Norway (along with Switzerland) a leader in the amount of support provided to agriculture by the 50 OECD member and non-member countries monitored by the Organization (OECD, 2016). In this paper we analyze policy options for achieving a 40% reduction in agricultural GHG emissions, consistent with the economy-wide target, while imposing the restriction that national food production measured in calories should be maintained (the food security target). This is consistent with the way that the Norwegian government identifies the country’s food security objective. In section 2 we outline the current situation with respect to GHG emissions in Norwegian agriculture. In section 3 we illustrate the policy issues involved by considering two product aggregates that are intensive in the use of land for crop production (grainland) and grassland, respectively. The aggregates are based on data for the main commodities in Norwegian agriculture relating to GHG emissions, land use, caloric content, subsidies, and costs per unit of production. We show that even though the opportunity set (i.e., the production combinations that are possible within technical constraints) is narrow, a 40% cut in emissions is achievable by substituting from ruminant products that are intensive in the use of grassland to products based on grainland. We also show that the emissions reduction both reduces government budgetary costs and land use, i.e., ruminant products are characterized by relatively high subsidies and land use. Two-dimensional analysis ignores the fact that per unit emissions from dairy production are low compared to other ruminant products (i.e., beef and sheep production). Both in terms of production value and agricultural employment, dairy farming is the most important component of Norwegian agriculture. Consequently, milk production deserves to be separated from ruminant meat production. Finally in section 4, we present a detailed analysis 3 of policy options derived from a disaggregated model that includes all the major products in Norwegian agriculture. In the model-based analysis, we examine first the imposition of a carbon tax, while maintaining existing agricultural support policies and import protection, and achieving the food security (production of calories) target. Since the imposition of a carbon tax in agriculture presents both technical and political challenges, we then examine an alternative approach of changing the existing structure of agricultural support to approximate the same result. We show that it is possible to change current subsidy rates to mimic the carbon tax and calorie target solution. The explanation for this is that ruminant products not only generate high emissions per produced calorie, but they are also the most highly subsidized products. Meat from ruminants is relatively unimportant in achieving Norway’s food security objective of calorie availability.

Climate change is mainly anthropogenic mostly caused by urbanization, human activities in economics, industry, and transportation. The expansion of built-up land, deforestation and the loss of farmland are closely linked to land use and land use change. Greenhouse gas emissions produced by the land use sector can significantly affect global carbon budgets by changing the carbon storage level in terrestrial ecosystem vegetation and soil. In 2005, Indonesia was responsible for approximately 85% of carbon emissions. The Indonesian government is combating environmental issues by mandating local governments, including Palembang City, to conduct greenhouse gas inventories. Changes in land use and the amount of carbon stock in Palembang City can be taken into consideration by the Palembang City Government in dealing with climate change. Data analysis was carried out by interpreting satellite imagery SPOT-7 and classification of land use data into six classes based on AFOLU guidelines. The area derived from land use transition matrix of the period 2012-2018 is used as a basis to calculate greenhouse gas emissions. The greenhouse gas emissions were then calculated using the Gain-Loss method based on the IPCC journal as a reference. Due to land use and land use change from 2012 to 2018, Palembang City emits greenhouse gas as much as -149098.5827 Tonnes C/Year in total. Forest Land Category -26557.22425 Tonnes C/Year, Crop Land Category -112739.8894 Tonnes C/Year, Grass Land Category -32257.56413 Tonnes C/Year, Wetland Category -20721.68315 Tonnes C/Year, Settlement Category 43273.249 Tonnes C/Year and Other Land Category -95.4708 Tonnes C/Year. Inventories on greenhouse gas (GHG) emissions and absorption trends are crucial for climate change mitigation strategies in Palembang. One important strategy towards achieving net zero emissions by 2060, as initiated by the Government of Indonesia, is to curb carbon release associated with land use changes.

Due to the important role land use behaviors play in carbon emissions, research on land use related carbon emissions has gradually become an academic focus in recent years. However, few studies have been done on the comprehensive land use related carbon emissions at the provincial level, including both carbon emissions from the natural ecosystems caused by land cover changes and carbon emissions from anthropogenic sources carried by different land use types. This paper proposed a GIS based method for estimating comprehensive land use related carbon emissions. After that, application of this method was conducted with relevant data of Henan Province. The results proved this method to be feasible, and it was found that land use behaviors on urbanized land were responsible for more than 90% of the total carbon emissions of Henan Province in 2010.

Estimation of CO2 emissions in the life cycle of roads through the disruption and restoration of environmental systems

Land use change implications for large-scale cultivation of algae feedstocks in the United States Gulf Coast