Integrated spatial technology to mitigate greenhouse gas emissions in grain production

https://doi.org/10.1016/j.rsase.2015.11.002Get rights and content

Highlights

  • A tool developed for the crop growing farmers in Western Australia.

  • Life cycle assessment, geographical information systems and remote sensing are integrated for the development of the integrated spatial technology.

  • Hotspot identification in agriculutral systems using the integrated spatial technology.

  • Cleaner production methods are used for the proposition of mitigation methods using the integrated spatial technology.

Abstract

The causes and implications of climate change are currently at the forefront of many researching agendas. Countries that have ratified the Kyoto Protocol are bound by agreements to focus on and reduce greenhouse gas emissions which impact on the natural and anthropogenic environment. Internationally agriculture contributes to environmental impacts such as land use change, loss of biodiversity, greenhouse gas emissions, increased soil salinity, soil acidity and soil erosion. To combat and control the greenhouse gas emissions generated during agricultural production, methodologies are being developed and investigated worldwide. Agriculture is the second largest emitter of greenhouse gases in Australia and consequently the integrated spatial technology was developed using data from a crop rotation project conducted by the Department of Agriculture and Food, Western Australia. The aim of the integrated spatial technology was to combine remote sensing, geographical information systems and life cycle assessment, to ascertain the component or system within the agricultural production cycle, generating the most greenhouse gases. Cleaner production strategies were then used to develop mitigation measures for the reduction of greenhouse gases within the integrated spatial technology.

Introduction

Food security has been defined by the Food and Agriculture Organization of the United Nations (FAO) as:

existing when all people, at all times, have physical and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life (FAO, 2014).

To reduce poverty and feed the projected world population of nine billion people by 2050 agricultural productivity needs to increase by 60–70% compared to 2006 levels. For increases in productivity to remain sustainable, agriculture should focus on minimal environmental degradation and its associated greenhouse gas (GHG) emissions (Food and Agriculture Organization of the United Nations (FAO), 2015). However, Darwin (2004) and Huang and Wang (2014) state that in the face of climate change, agricultural productivity has fallen, with greater fluctuations in crop yields and local food supplies expected. Furthermore it is widely accepted that fluctuations in crop yields will not be uniform across the entire globe but will vary according to regional temperatures, precipitation, soil types and agronomic practices (Darwin, 2004; FAO, 2014; FAO, WFP & IFAD, 2012; Huang and Wang, 2014). The fifth assessment report by the Intergovernmental Panel on Climate Change (IPCC) notes that climate change is having a negative impact on agriculture (Intergovernmental Panel on Climate Change (IPCC), 2014). Lee et al. (2014) and Vermeulen et al. (2012) also confirm that climate change can further destabilise current farming systems by a rise of 2 °C in global temperatures, and in turn this can transform the agricultural sector and place productivity under pressure.

In 2010 agriculture contributed to approximately 14.5% of global climate altering GHG emissions (, ). These GHG emissions were mainly comprised of emissions from soil N2O, CH4 from animal husbandry and CO2 from fertiliser products and the hydrolysis of urea (Biswas et al., 2010). In 2005, agricultural emissions of N2O and CH4 accounted for approximately 60% and 50% of the total global N2O and CH4 emissions, respectively (Smith et al., 2007). Generating 1.5% of the global total of 37,928 Mt carbon dioxide equivalents (CO2-e), Australia was ranked 12th in the world in 2010 with the agricultural sector emitting 18% of the national GHG emissions, of which 61% was CH4 and 39% was N2O (The Shift Project (TSP), 2015).

Changes in water availability, water quality and rising temperatures in Australia arising from climate change is expected to impact highly on agricultural productivity due to high levels of exposure and sensitivity (Garnaut, 2008). In order to sustain and evaluate the environmental impact of agricultural productivity and increase the efficiency of the agriculture and livestock sectors, the entire Australian agricultural sector requires different options for production to be investigated (, ). The FAO (2014) recommends that farmers respond to local and regional needs and vulnerabilities by developing and implementing mitigation and adaptation strategies, hence methodologies are being developed and trialled worldwide to combat and control the emissions generated during agricultural production. Farmers in Australia should focus on reducing N2O and CH4 as agriculture is the highest emitter of these two GHGs (National Greenhouse Gas Inventory (NGGI), 2013) and the second largest emitter of total GHGs.

In Australia the Emissions Reduction Fund (ERF) focuses on the development of programmes and methodologies that will enable Australia to meet its emissions reduction target of five percent below 2000 levels by 2020 (, ). It provides an incentive for the adoption of new practices and technologies that will enable businesses, land owners, state and local governments, community organisations and individuals to sell their CO2 abatement back to the Government (, ). Included in the ERF is the Carbon Farming Initiative (CFI), which enables individuals and entities to be issued with Australian carbon credit units (ACCUs), each ACCU represents one tonne of CO2-e (, ). The attainment of these ACCU׳s is achieved by implementing projects that fall into one of two categories – emissions avoidance, where GHG emissions are prevented from entering the atmosphere, and sequestration, where carbon is stored on the land (Clean Energy Regulator (CER), 2014). Methodologies such as manure management in piggeries, the establishment of environmental plantings, the capture and combustion of landfill gas and the management of savannah fires have been integrated in order to address these two categories (, ).

Adaptation and mitigation has been a primary focus of agricultural research in the face of climate change, as GHG emissions from the agricultural sector are major contributors to climate change, especially in Australia. To combat climate change, farmers are expected to reduce GHG emissions from their farms by implementing mitigation measures and adapting their farm management practices. Ideally no one system, whether mitigation or adaptation, exists that will work for all farms given that the soils, environmental conditions and the financial positions of farmers differ. It is therefore crucial for each farmer to identify individual strategies for overcoming problems and improving the efficiency of the farm (, ).

A user-friendly and comprehensive decision support tool, identifying the areas within the agricultural cycle generating the most GHGs for farmers, was not available in the literature reviewed to date. In contrast there are established methods wherein the industry and academic institutions are able to identify the concerning areas within the agricultural cycle. To track stages in the farming system most responsible for GHG emissions, a comprehensive environmental management tool known as the integrated spatial technology (IST) was thus developed using data from a crop rotation project conducted by the Department of Agriculture and Food, Western Australia (DAFWA) (, ). Prior to this, the IST was pre-tested using the published data of Biswas et al. (2008) (, ).

As a newly developed tool, the IST was applied for the first time in this current study by utilizing real world data from a Western Australian farm that met the requirements of the IST and identified hotspots for both the paddock and farm scales. Furthermore, it facilitates the selection of mitigation measures that are then remodelled within the IST to allow the user to make visual comparisons with the original results. As a simple, quick and easy to use tool, the purpose of the IST is to focus on farmers, government policy makers and agricultural researchers who have limited time at their disposal. Whilst it is beyond the scope of the current study, further research will enable the development of an application that can be downloaded onto a ‘tablet computer’ or a ‘smart phone’. This application will enable farmers to input their variables into the IST and then generate their carbon footprint, on site, to determine appropriate mitigation measures (Towie, 2013).

This article introduces the use of IST as a methodological approach, as previously presented and tested using a hypothetical example (Article title–‘An evaluation of Integrated Spatial Technology framework for Greenhouse Gas mitigation in Western Australia’ (Engelbrecht et al., 2013)). The IST applies the concept of cleaner production (CP) for the formulation and application of cost-effective GHG mitigation options from grain production in Western Australia. Additionally it allows for visual identification of the impact from the farm management systems used and is able to identify areas where mitigation measures may be applied. Finally it could be used to suggest appropriate CP strategies.

Section snippets

Materials

The IST is a tool designed by integrating RS, GIS and LCA (Fig. 1) to calculate the carbon footprint on grain farms in south-western Australia. The IST highlights the area in which the GHGs are the highest and most concerning (the hotspot) and can subsequently be used to select different mitigation scenarios based on CP strategies.

Methods and results

In the following section each of the components of the methodology are outlined separately, however it should be remembered throughout that these components should not be considered separate from each other as the process is an interactive process.

Application of the IST in real world situations

As stated by Towie (2013) various options exist for the use of the IST in the agricultural cycle and this article highlighted the use and acquisition of chemicals (including fertilisers) and how these contribute to GHG emissions through production, dosage control, the substitution of one chemical with another and the transportation of the chemicals. Further factors highlighted in this study were the GHG emissions from the use of farm machinery due to production costs and the combustion of fuel,

Limitations and recommendations

As the acquisition of high quality satellite imagery is costly and problematic, and the pre-processing limited to the availability of RS applications, the identification of the study area could be problematic and thus alternative means of obtaining satellite imagery, such as Google Earth, needs to be explored

The development of an LCI is a time-consuming task, especially if data records are incomplete. To reduce the time for data collection the farmers should be encouraged to maintain

Conclusions

Different methodologies have been developed and have been included in the CFI which mostly focus on mitigating GHGs in a few farming systems. No methodology was available for the farmer to quickly and easily establish the level of GHGs or test alternative strategies. Based on this shortcoming the IST was researched and developed to enable the farmer to ascertain the GHG emissions per farm or paddock, prior to, during or after the questioned farming cycle.

This article presented the concept the

Acknowledgements

I would like to thank all the staff concerned at DAFWA, the WANTFA and Liebe grower groups, the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for the provision of the satellite imagery and to the Australian Government for the Australian Postgraduate Award (APA) and Curtin University for the top-up award.

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