scholarly journals Greenhouse gas accounting for inventory, emissions trading and life cycle assessment in the land-based sector: a review

2012 ◽  
Vol 63 (3) ◽  
pp. 284 ◽  
Author(s):  
Annette Cowie ◽  
Richard Eckard ◽  
Sandra Eady

Governments, organisations and individuals have recognised the need to reduce their greenhouse gas (GHG) emissions. To identify where savings can be made, and to monitor progress in reducing emissions, we need methodologies to quantify GHG emissions and sequestration. Through the Australian Government’s Carbon Farming Initiative (CFI) landholders may generate credits for reducing emissions and/or sequestering carbon (C). National GHG inventories for the United Nations Framework Convention on Climate Change, and accounting under the Kyoto Protocol use a sectoral approach. For example, fuel use in agriculture is reported in the transport component of the energy sector; energy use in producing herbicide and fertiliser is included in the manufacturing section of the energy sector; sequestration in farm forestry is reported in the land use, land-use change and forestry sector, while emissions reported in the agriculture sector include methane (CH4) from ruminant livestock, nitrous oxide (N2O) from soils, and non-carbon dioxide (CO2) GHG from stubble and savannah burning. In contrast, project-level accounting for CFI includes land-use change, forestry and agricultural sector emissions, and significant direct inputs such as diesel and electricity. A C footprint calculation uses a life cycle approach, including all the emissions associated with an organisation, activity or product. The C footprint of a food product includes the upstream emissions from manufacturing fertiliser and other inputs, fuel use in farming operations, transport, processing and packaging, distribution to consumers, electricity use in refrigeration and food preparation, and waste disposal. Methods used to estimate emissions range from simple empirical emissions factors, to complex process-based models. Methods developed for inventory and emissions trading must balance the need for sufficient accuracy to give confidence to the market, with practical aspects such as ease and expense of data collection. Requirements for frequent on-ground monitoring and third party verification of soil C or livestock CH4 estimates, for example, may incur costs that would negate the financial benefit of credits earned, and could also generate additional GHG emissions. Research is required to develop practical on-farm measures of CH4 and N2O, and methods to quantify C in environmental plantings, agricultural soils and rangeland ecosystems, to improve models for estimation and prediction of GHG emissions, and enable baseline assessment. There is a need for whole-farm level estimation tools that accommodate regional and management differences in emissions and sequestration to support landholders in managing net emissions from their farming enterprises. These on-farm ‘bottom-up’ accounting tools must align with the ‘top-down’ national account. To facilitate assessment of C footprints for food and fibre products, Australia also needs a comprehensive life cycle inventory database. This paper reviews current methods and approaches used for quantifying GHG emissions for the land-based sectors in the context of emissions reporting, emissions trading and C footprinting, and proposes possible improvements. We emphasise that cost-effective yet credible GHG estimation methods are needed to encourage participation in voluntary offset schemes such as the CFI, and thereby achieve maximum mitigation in the land-based sector.

2015 ◽  
Vol 37 (3) ◽  
pp. 273 ◽  
Author(s):  
Beverley K. Henry ◽  
D. Butler ◽  
S. G. Wiedemann

In life cycle assessment studies, greenhouse gas (GHG) emissions from direct land-use change have been estimated to make a significant contribution to the global warming potential of agricultural products. However, these estimates have a high uncertainty due to the complexity of data requirements and difficulty in attribution of land-use change. This paper presents estimates of GHG emissions from direct land-use change from native woodland to grazing land for two beef production regions in eastern Australia, which were the subject of a multi-impact life cycle assessment study for premium beef production. Spatially- and temporally consistent datasets were derived for areas of forest cover and biomass carbon stocks using published remotely sensed tree-cover data and regionally applicable allometric equations consistent with Australia’s national GHG inventory report. Standard life cycle assessment methodology was used to estimate GHG emissions and removals from direct land-use change attributed to beef production. For the northern-central New South Wales region of Australia estimates ranged from a net emission of 0.03 t CO2-e ha–1 year–1 to net removal of 0.12 t CO2-e ha–1 year–1 using low and high scenarios, respectively, for sequestration in regrowing forests. For the same period (1990–2010), the study region in southern-central Queensland was estimated to have net emissions from land-use change in the range of 0.45–0.25 t CO2-e ha–1 year–1. The difference between regions reflects continuation of higher rates of deforestation in Queensland until strict regulation in 2006 whereas native vegetation protection laws were introduced earlier in New South Wales. On the basis of liveweight produced at the farm-gate, emissions from direct land-use change for 1990–2010 were comparable in magnitude to those from other on-farm sources, which were dominated by enteric methane. However, calculation of land-use change impacts for the Queensland region for a period starting 2006, gave a range from net emissions of 0.11 t CO2-e ha–1 year–1 to net removals of 0.07 t CO2-e ha–1 year–1. This study demonstrated a method for deriving spatially- and temporally consistent datasets to improve estimates for direct land-use change impacts in life cycle assessment. It identified areas of uncertainty, including rates of sequestration in woody regrowth and impacts of land-use change on soil carbon stocks in grazed woodlands, but also showed the potential for direct land-use change to represent a net sink for GHG.


Vehicles ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 75-99
Author(s):  
Benjamin Blat Belmonte ◽  
Arved Esser ◽  
Steffi Weyand ◽  
Georg Franke ◽  
Liselotte Schebek ◽  
...  

We present an optimization model for the passenger car vehicle fleet transition—the time-dependent fleet composition—in Germany until 2050. The goal was to minimize the cumulative greenhouse gas (GHG) emissions of the vehicle fleet taking into account life-cycle assessment (LCA) data. LCAs provide information on the global warming potential (GWP) of different powertrain concepts. Meta-analyses of batteries, of different fuel types, and of the German energy sector are conducted to support the model. Furthermore, a sensitivity-analysis is performed on four key influence parameters: the battery production emissions trend, the German energy sector trend, the hydrogen production path trend, and the mobility sector trend. Overall, we draw the conclusion that—in any scenario—future vehicles should have a plug-in option, allowing their usage as fully or partly electrical vehicles. For short distance trips, battery electric vehicles (BEVs) with a small battery size are the most reasonable choice throughout the transition. Plug-in hybrid electric vehicles (PHEVs) powered by compressed natural gas (CNG) emerge as promising long-range capable solution. Starting in 2040, long-range capable BEVs and fuel cell plug-in hybrid electric vehicles (FCPHEVs) have similar life-cycle emissions as PHEV-CNG.


2018 ◽  
Vol 251 ◽  
pp. 249-258 ◽  
Author(s):  
Rui Chen ◽  
Zhangcai Qin ◽  
Jeongwoo Han ◽  
Michael Wang ◽  
Farzad Taheripour ◽  
...  

2010 ◽  
Vol 25 (4) ◽  
pp. 316-329 ◽  
Author(s):  
S. Hörtenhuber ◽  
T. Lindenthal ◽  
B. Amon ◽  
T. Markut ◽  
L. Kirner ◽  
...  

AbstractThe aim of this study was to analyze various Austrian dairy production systems (PS) concerning their greenhouse gas emissions (GHGE) in a life-cycle chain, including effects of land-use change (LUC). Models of eight PS that differ, on the one hand, in their regional location (alpine, uplands and lowlands) and, on the other hand, in their production method (conventional versus organic, including traditional and recently emerging pasture-based dairy farming) were designed.In general, the GHGE-reducing effect of a higher milk yield per cow and year in conventional dairy farming cannot compensate for the advantages of organic dairy production which requires lower inputs. This is shown both for GHGE per kg of milk and GHGE per ha and year of farmland. Especially when (imported) concentrates were fed, which had been grown on former forests or grassland, e.g. soybean meal and rapeseed cake, GHGE of conventional dairy farming rose due to the effects of LUC.GHGE per kg milk varied from 0.90 to 1.17 kg CO2-eq for conventional PS, while organic PS on average emitted 11% less greenhouse gases (GHGs), the values ranging from 0.81 to 1.02 CO2-eq per kg milk. Within each production method, PS with a higher milk output generally showed better results for GHGE per kg of milk produced than PS with a lower milk output. Nevertheless the latter showed clearly better results for GHGE per ha of land used, ranging from 5.2 to 7.6 Mg CO2-eq per ha and year for conventional PS and from 4.2 to 6.2 Mg CO2-eq per ha and year for organic PS. The results of this study emphasize the importance of a complete life-cycle assessment in the evaluation of impacts that dairy PS have on the climate.


2012 ◽  
Vol 03 (03) ◽  
pp. 1250014 ◽  
Author(s):  
AMANI E. ELOBEID ◽  
MIGUEL A. CARRIQUIRY ◽  
JACINTO F. FABIOSA

Even with a normalized and standardized biofuel shock, the wide range of land-use change estimates and their associated greenhouse gas (GHG) emissions have raised concern on the adequacy of existing agricultural models in this new area of analysis. In particular, reducing bias and improving precision of impact estimates are of primary concern to policy makers. This paper provides a detailed overview of the FAPRI-CARD agricultural modeling system, with particular emphasis on the modifications recently introduced to reduce bias in the results. We illustrate the impact of these new model features using the example of the new yield specification that now includes updated trend parameter, intensification and extensification effects, and a spatially disaggregated Brazil specification. The paper also provides a taxonomy of the many types of uncertainty surrounding any analysis, including parameter-coefficient uncertainty and exogenous variable uncertainty, identifying where specific types of uncertainty originate, and how they interact. Finally, FAPRI-CARD's long experience in using stochastic analysis is presented as a viable approach in addressing uncertainty in the analysis of changes in the agricultural sector, associated land-use change, and impacts on GHG emissions.


2021 ◽  
pp. 53-59
Author(s):  
Dennis G. A. B. Oonincx

Abstract This chapter discusses the environmental impact of insect rearing. Direct greenhouse gas (GHG) emissions from insects used as feed or food are discussed and data from life cycle assessments (LCAs) on commercially farmed insects are discussed per species. The relevance of the utilized feed on the environmental impact of insects and their derived products, including suggestions to lower this impact are also discussed. It is concluded that land use associated with insect production generally seems low, compared to conventional feed and food products. The EU (expressed as fossil fuel depletion) of insect production is often high compared to conventional products. To a large extent this is because several LCAs have been conducted for systems in temperate climates, which require extensive climate control.


2017 ◽  
Vol 57 (6) ◽  
pp. 1149 ◽  
Author(s):  
Stephen Wiedemann ◽  
Rod Davis ◽  
Eugene McGahan ◽  
Caoilinn Murphy ◽  
Matthew Redding

Grain finishing of cattle has become increasingly common in Australia over the past 30 years. However, interest in the associated environmental impacts and resource use is increasing and requires detailed analysis. In this study we conducted a life cycle assessment (LCA) to investigate impacts of the grain-finishing stage for cattle in seven feedlots in eastern Australia, with a particular focus on the feedlot stage, including the impacts from producing the ration, feedlot operations, transport, and livestock emissions while cattle are in the feedlot (gate-to-gate). The functional unit was 1 kg of liveweight gain (LWG) for the feedlot stage and results are included for the full supply chain (cradle-to-gate), reported per kilogram of liveweight (LW) at the point of slaughter. Three classes of cattle produced for different markets were studied: short-fed domestic market (55–80 days on feed), mid-fed export (108–164 days on feed) and long-fed export (>300 days on feed). In the feedlot stage, mean fresh water consumption was found to vary from 171.9 to 672.6 L/kg LWG and mean stress-weighted water use ranged from 100.9 to 193.2 water stress index eq. L/kg LWG. Irrigation contributed 57–91% of total fresh water consumption with differences mainly related to the availability of irrigation water near the feedlot and the use of irrigated feed inputs in rations. Mean fossil energy demand ranged from 16.5 to 34.2 MJ lower heating values/kg LWG and arable land occupation from 18.7 to 40.5 m2/kg LWG in the feedlot stage. Mean greenhouse gas (GHG) emissions in the feedlot stage ranged from 4.6 to 9.5 kg CO2-e/kg LWG (excluding land use and direct land-use change emissions). Emissions were dominated by enteric methane and contributions from the production, transport and milling of feed inputs. Linear regression analysis showed that the feed conversion ratio was able to explain >86% of the variation in GHG intensity and energy demand. The feedlot stage contributed between 26% and 44% of total slaughter weight for the classes of cattle fed, whereas the contribution of this phase to resource use varied from 4% to 96% showing impacts from the finishing phase varied considerably, compared with the breeding and backgrounding. GHG emissions and total land occupation per kilogram of LWG during the grain finishing phase were lower than emissions from breeding and backgrounding, resulting in lower life-time emissions for grain-finished cattle compared with grass finishing.


2010 ◽  
Vol 67 (1) ◽  
pp. 102-116 ◽  
Author(s):  
Carlos Clemente Cerri ◽  
Martial Bernoux ◽  
Stoecio Malta Ferreira Maia ◽  
Carlos Eduardo Pellegrino Cerri ◽  
Ciniro Costa Junior ◽  
...  

National inventories of anthropogenic greenhouse gas (GHG) emissions (implementation of the National Communications) are organized according to five main sectors, namely: Energy, Industrial Processes, Agriculture, Land-Use Change and Forestry (LUCF) and Waste. The objective of this study was to review and calculate the potential of greenhouse gas mitigation strategies in Brazil for the Agricultural and LUCF. The first step consisted in an analysis of Brazilian official and unofficial documents related to climate change and mitigation policies. Secondly, business as usual (BAU) and mitigation scenarios were elaborated for the 2010-2020 timeframe, and calculations of the corresponding associated GHG emissions and removals were performed. Additionally, two complementary approaches were used to point out and quantify the main mitigation options: a) following the IPCC 1996 guidelines and b) based on EX-ACT. Brazilian authorities announced that the country will target a reduction in its GHG between 36.1 and 38.9% from projected 2020 levels. This is a positive stand that should also be adopted by other developing countries. To reach this government goal, agriculture and livestock sectors must contribute with an emission reduction of 133 to 166 Mt CO2-eq. This seems to be reachable when confronted to our mitigation option values, which are in between the range of 178.3 to 445 Mt CO2-eq. Government investments on agriculture are necessary to minimize the efforts from the sectors to reach their targets.


Sign in / Sign up

Export Citation Format

Share Document