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Abatement potential and cost of agricultural greenhouse gases in Australian dryland farming system

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Abstract

Evaluating the cost-effectiveness of GHG mitigation in the dryland agricultural sector is needed in terms of designing and implementing detailed and efficient mitigation programs, which is currently rarely covered by the literature. In this paper, we use a parametric directional distance approach to explore the farm-level abatement potential and cost (shadow value) of GHG for dryland farms in southwestern Australia. The study indicates that dryland agriculture could abate substantial GHG emissions and save agricultural inputs simultaneously. For the years 2006–2013, the average abatement potential ratios fluctuated between 17 and 33%, with a mean value of 21%. The mean shadow price of dryland agricultural GHG was $17.60 per tonne CO2-e in 2013 Australian dollars. In general, the analysis supports that reducing GHG in dryland agriculture is relatively cost-effective.

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Notes

  1. A good example for such an increase is the rapid growing prices of livestock meat in China during the last several years. See https://www.euromeatnews.com/Article-Chinese-meat-prices-remain-high/3502 for more information.

Abbreviations

CO2 :

Carbon dioxide

CO2-e:

Carbon dioxide equivalents

DEA:

Data envelopment analysis

DDF:

Directional distance function

DODF:

Directional outputs distance function

EUA:

European Union Allowance

GWP:

Global warming potential

GHG:

Greenhouse gases

GSR:

Growing season rainfall

IPCC:

Intergovernmental Panel on Climate Change

MAC:

Marginal abatement costs

M&S:

Materials and services

CH4 :

Methane

N2O:

Nitrous oxide

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Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Funding

This work was supported by the Humanities and Social Sciences Project from the Ministry of Education of China (20YJCZH144, 20YJC790191), Guangdong Basic and Applied Basic Research Foundation (2019A1515010884) and Pearl River Talents Plan of Guangdong Province (20170133).

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Authors and Affiliations

  1. School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Kai Tang

  2. Graduate School of Chinese Academy of Social Sciences, Beijing, 102488, China

    Mingzhe Wang

  3. School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Di Zhou

Authors
  1. Kai Tang
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  2. Mingzhe Wang
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  3. Di Zhou
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Contributions

Conceptualization: Kai Tang, Mingzhe Wang; methodology: Kai Tang; formal analysis and investigation: Kai Tang, Mingzhe Wang; writing—original draft preparation: Kai Tang; writing—review and editing: Kai Tang, Mingzhe Wang, Di Zhou; funding acquisition: Kai Tang, Di Zhou; resources: Kai Tang; supervision: Kai Tang.

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Correspondence to Di Zhou.

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Appendix

Appendix

Modification on standard GHG emission estimation methodology

Note unless referenced otherwise, the methodology and parameter values presented here are from National Inventory (2012b). GHG emissions are converted to CO2-e by using a global warming potential (GWP) of 1 for CO2, 21 for CH4 and 310 for N2O (National Inventory 2012b).

Livestock enteric fermentation

The same equation and EFs in the National Inventory (2012a) are used to account for enteric emissions fermentation.

Livestock manure

The same equation and EFs in the National Inventory (2012a) are used to calculate CH4 emission from livestock manure.

For calculating N2O emissions from animal wastes, the EFs used in the National Inventory (2012a) are based on international evidence. The study region has semi-arid agro-climatic conditions that are not well represented by the EFs in the National Inventory Report (Barton et al. 2011). However, there is a lack of direct scientific data on N2O emissions in the study region.

A study in the Central Grainbelt of WA released the following EFs: 0.14% for urine and 0.01% for faeces (Thamo et al. 2013). Given that the study region has similar climate, soils and farming system characteristics, it seems reasonable to expect that EFs for the study region would be close to the Central Grainbelt. So, the same EFs are used in this study, though the dearth of field data is acknowledged.

An EF of 0.001 is used for estimating the leach of soil nitrogen from livestock manure as Li et al. (2011) suggested. This number was based on 37 years of meteorological data at Cunderdin in WA, where it has similar climate, soils and farming system characteristics as the study region.

Fertiliser application

The same equation and EFs stated in the National Inventory (2012a) are used to account for emissions from fertiliser application.

Crop residues

An EF of 0.001 is used for calculating the N2O emissions from crop residues based on the measurement result at Cunderdin in WA (Barton et al. 2011).

Nitrogen-fixing crops

There is a lack of data on N2O emissions from nitrogen-fixing crops, not only in the study region but also in the broadacre farming system in Australia. Therefore, the N2O emission factor for fertiliser in the Australian non-irrigated pasture production system (0.004) is used to replace the default value (National Inventory 2012b).

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Tang, K., Wang, M. & Zhou, D. Abatement potential and cost of agricultural greenhouse gases in Australian dryland farming system. Environ Sci Pollut Res 28, 21862–21873 (2021). https://doi.org/10.1007/s11356-020-11867-w

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