The impacts of local farming system development trajectories on greenhouse gas emissions in the northern mountains of Vietnam (original) (raw)

Abstract

The northern mountain region of Vietnam (NMR) is dominated by swidden/fallow farming systems. The fallow land of these systems is populated by small trees and bushes. Since the 1960s the government of Vietnam has tried to limit or stop swiddening and replace it with permanent upland agricultural fields, paddy, fruit trees and animal husbandry. Discussion in the policy debate and literature focuses on the impacts these changes have on local people’s livelihoods. There have been no attempts to evaluate the impact of these changes on greenhouse gas (GHG) emissions. This paper examines the realities of current farming system changes taking place at the hamlet level and other changes that could take place due to government land use policies and extension programs. The paper answers the following questions: How could farming system changes influence net GHGs? Which farming system changes in the NMR, the trajectories of changes that are currently observed or those that would be followed if farmers adhere strictly to government policies and programs, will have a greater affect on the GHG contributions from agriculture in the region? Could ‘clean development mechanism’ (CDM) projects make a difference in the profitability of the pathways mentioned? Results show: (1) if farming systems in the NMR continue along currently observed change trajectories there will be increases in GHG emissions; (2) if the NMR farming systems change according to government policies and programs there will be a net sequestration of carbon in regrowing vegetation during the initial 20 years; (3) over the longer term, in areas where systems change to fit government policies, increased GHG emissions from other changes in the farming systems (e.g. increased paddy and increased pig raising in sties) will overtake the amounts of carbon sequestered in vegetation; (4) CMD projects only make a difference if (a) maximum biomass potential of regrowing fallow can be reached; (b) a favourable baseline is chosen; (c) timing and length of the accounting period is correct; and (d) farmers do not take compensatory action in response to government policies. Given these conditions it does not appear that currently envisioned clean development mechanisms would be beneficial to farmers in the NMR.

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Acknowledgments

Research in Nghe An was funded by DANIDA under the University Support for Environmental Planning and Management Project. Research in Tat hamlet was funded by the Ford Foundation. Special thanks go to the researchers at the Center for Agricultural Research and Ecological Studies, Hanoi Agricultural University, in Hanoi, Vietnam, who helped carry out the research described in this paper. Also, the authors wish to thank Thilde Bruun for help with understanding and analyzing the soil data, Jens Jakobsen for insights into the situation in Que hamlet, and Nguyen Thanh Lam for help with organizing and carrying out the fieldwork.

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Author notes

  1. Stephen J. Leisz
    Present address: Bishop Museum, 1525 Bernice Street, Honolulu, HI, 96817, USA

Authors and Affiliations

  1. Institute of Geography, University of Copenhagen, Øster Voldgade 10, 1350, Copenhagen K, Denmark
    Stephen J. Leisz, Kjeld Rasmussen, Bo Elberling & Lars Christiansen
  2. Department of Agroecology, Danish Institute of Agricultural Sciences, Research Centre Foulum, Blichers Allé 20, P.O. BOX 50, 8830, Tjele, Denmark
    Jørgen E. Olesen
  3. Center for Agricultural Research and Ecological Studies, Hanoi Agriculture University, Gia Lam, Hanoi, Vietnam
    Tran Duc Vien

Authors

  1. Stephen J. Leisz
  2. Kjeld Rasmussen
  3. Jørgen E. Olesen
  4. Tran Duc Vien
  5. Bo Elberling
  6. Lars Christiansen

Corresponding author

Correspondence toStephen J. Leisz.

Appendices

Appendix 1: Methods for estimating GHG emissions

In the following, we briefly summarize the methods and parameters used in the estimation of the changes in GHG emissions caused by changes in agricultural practices in the four hamlets studied. The methods are based on the approach described in IPCC Guidelines for National Greenhouse Gas Inventories (1997, 2000).

1. Methane from enteric fermentation

The methane emissions from enteric fermentation depend mainly on animal type, production level, feed intake and feed quality. The IPCC methodology distinguishes methods with increasing detail. The simplest methodology, which is applied here, uses a fixed emission factor per animal. The emission factors that are used for the NMR of Vietnam are shown in Table 9.

Table 9 Enteric fermentation emission factors (kg CH4 per head/year) (IPCC 1997)

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2. Methane from manure management

Methane is emitted during storage of animal manure, and the emissions depend on manure type, storage conditions and climate. The emissions increase with increasing temperature, and IPCC (1997) therefore consider three different climates depending on mean annual temperature: cool (temperature below 15°C), temperate (temperature from 15 to 25 °C) and warm (temperature above 25°C). The NMR of Vietnam has an average yearly temperature of 23.2°(C), a temperate climate, heavily influenced by the fact that winter temperatures can average in the teens and come close to freezing at night during December, January and February.

The following types of manure management are considered:

(a) Grazing The manure from animals grazing on pastures or grasslands is allowed to lie as is. This applies to cattle and buffalo in the study area.

(b) Drylot Animals kept on unpaved feedlots where the manure is allowed to dry until periodically removed (dry climates). This is assumed to apply to pigs in the study area.

3. Nitrous oxide from manure management

Nitrous oxide will be emitted from faeces and urine excreted by animals, primarily during storage of the manure. The emissions are estimated using emission factors (kg N2O– per kg N excreted) that differ depending on the type of manure management. The same categories of manure management systems as applied for methane from manure management are used. No specific information on the amount of N excreted was available, so the values in Table 10 from IPCC (1997) for Asia were used.

Table 10 Default values for nitrogen excretion by livestock (kg N per head/year)

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4. Methane from rice production

The methane emissions from rice production strongly depend on the production system. The factors primarily affecting emissions include the water status of the rice system and the amount of plant residues applied. The emission factor is thus estimated as (IPCC 2000):

textEF=textEFc;textSFw;textSFo{\text{EF}} = {\text{EF}}_{c} \;{\text{SF}}_{w} \;{\text{SF}}_{o}textEF=textEFc;textSFw;textSFo

where EF is the resulting emission factor (kg CH4/ha), EF c is the seasonal integrated emission factor for continuously flooded fields without organic amendments (200 kg CH4/ha), SF w is a scaling factor to account for ecosystem and water management regime (Table 11), and SF o is a scaling factor to account for the amount of organic amendments applied (Table 12).

Table 11 Scaling factors (SFw) for rice ecosystem and water management regimes (IPCC 2000)

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Table 12 Scaling factors (SFo) for organic amendments (IPCC 2000)

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5. GHG-emissions from burning

In agricultural burning, the CO2 released should not be considered a net emission (IPCC 1997). The biomass burned is generally replaced by regrowth of the subsequent years, and an equivalent amount of CO2 will be removed from the atmosphere during this regrowth. However, the burning will also release non-CO2 greenhouse gases (CH4 and N2O). These emissions may be estimated following the IPCC methodology, where the emissions are proportional to the amount of carbon in the biomass burnt.

The methane emissions \( E_{{{\text{CH}}_{4} }} \) (kg CH4/ha) are calculated as

EtextCH4=C;RtextCH416/12E_{{{\text{CH}}_{4} }} = C\;R_{{{\text{CH}}_{4} }} 16/12EtextCH4=C;RtextCH416/12

where C is the carbon released by burning (kg C/ha) and R CH4 is the emission ratio, which is set to 0.004 for savannah burning and 0.005 for crop residue burning.

The nitrous oxide emissions \( E_{{{\text{N}}_{{\text{2}}} {\text{O}}}} \) (kg N2O/a) are calculated as

EtextNtext2textO=C;RtextNtext2textORNC44/28E_{{{\text{N}}_{{\text{2}}} {\text{O}}}} = C\;R_{{{\text{N}}_{{\text{2}}} {\text{O}}}} R_{{NC}} 44/28EtextNtext2textO=C;RtextNtext2textORNC44/28

where \( R_{{{\text{N}}_{{\text{2}}} {\text{O}}}} \) is the emission ratio (0.007), and R NC is the N/C ratio of the biomass burnt.

6. Nitrous oxide from fertilisers, manures and crop residues

All inputs of nitrogen to the cropping system will give rise to emissions of nitrous oxide. The emissions are estimated from the amount of nitrogen applied as input to the system multiplied with an emission factor, which varies depending on input type. The default emission factors are shown in Table 13.

Table 13 Default emission factors for N2O emissions for N applied to soils (kg N2O–N per 100 kg N) (IPCC 2000)

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The ammonia volatilisation is subtracted from mineral fertilisers and manures before applying the emission factor. An ammonia emission factor of 10% is used as default for fertilisers and 20% for manures.

The amount of crop residues and the N-fixation from crops with biological N fixation is estimated from the crop yields.

There are also nitrous oxide emissions from indirect sources, i.e. from ammonia volatilisation and nitrate leaching. These are also estimated using emission factors, and the amount of ammonia volatilisation and nitrate leaching may be estimated as a fraction of the nitrogen input.

7. CO2 and nitrous oxide from fertiliser production

The average GHG emissions associated with the supply of mineral N fertiliser representative for the conditions in Central Europe were used due to lack of local representative data (Patyk and Reinhardt 1997). The emissions also include N2O from fertiliser production. The emissions associated with production of 1 kg of fertiliser N is estimated at 2.85 kg CO2, 7 g CH4 and 15 g N2O.

Appendix 2: Assumptions concerning agricultural pathways

Using the methodology outlined in Appendix 1, emissions for each scenario may be calculated, based on assumptions concerning the extent of changes. The exact assumptions made are outlined in Tables 14 and 15.

Table 14 Assumptions concerning future changes in agricultural land use, crops and methods for each hamlet, based on the observed farming system change trajectory

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Table 15 Forecast agricultural changes for each hamlet if government policies were effectively implemented

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Appendix 3: Emissions from baseline, observed change trajectory, and government change trajectory farming systems

Emissions (in Gg CO2 equivalents) from the baseline-, O- and G-scenarios, computed using the IPCC Guidelines (Tables 16, 17, 18). Emissions from vegetation burning and from production of mineral fertilizers are not included because they are insignificant. Emissions from use of mineral fertilizers have not been included because of great uncertainty concerning future fertilizer use.

Table 16 Emissions from livestock and paddy in the baseline scenario

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Table 17 Emissions from scenario O

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Table 18 Emissions from scenario G

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Leisz, S.J., Rasmussen, K., Olesen, J.E. et al. The impacts of local farming system development trajectories on greenhouse gas emissions in the northern mountains of Vietnam.Reg Environ Change 7, 187–208 (2007). https://doi.org/10.1007/s10113-007-0037-1

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