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GHG emissions mitigation – case study in slope areas (deforested areas)

20 May 2021

On the 12th of May 2021 WWF Thailand attended the final meeting for “GHG emissions mitigation – case study in slope areas (deforested areas)” hosted by the National Science and Technology Development Agency (NSTDA). First commissioned in 2019, the study sought to compare two agricultural systems, monoculture and a mixed agriculture system (like the FLR349 agricultural model), in Mae Chaem District, Chiang Mai Province, Thailand.

While GHG emissions were the main focus, the study itself also focused on other topics and was divided into 5 sub-projects comparing the two types of agriculture based on 
  • Social
  • Economics
  • Governance 
  • Environment 
  • GHG emissions 
These sub-projects were examined using the Sustainability Assessment of Food and Agriculture systems or SAFA, an international standard adopted by many leading organisations including the FAO. 

To get the most definitive data for these sub-projects, the research was completed in collaboration with 
  • Thailand National Metal and Materials Technology Center (MTEC) - a subdivision of NSTDA 
  • Thailand Organic Agriculture Innovation Foundation (TOF) - an implementation partner of the FLR349 project
  • Ricult, an agrotech start-up that developed the traceability platform for the FLR349 project. 
  • Chiang Mai Social Enterprise 
  • SDG Move
  • Chiang Mai University 
  • Chulalongkorn University 
Dr. Thumrongrut Mungcharoen, energy and resource president at NSTDA, who acted as a sustainability consultant for the project, gave the opening remarks and welcomed all the attendees.

The online event was attended by 
  • WWF Thailand
  • NSTDA
  • the Bureau of Water Resources Policy and Planning from the Department of Water Resources
  • the Forest Research and Development Bureau from the Royal Forest Department (RFD),
  • the Department of Alternative Energy Development and Efficiency (DEDE),
  • the Land Development Department (LDD),
  • Air Quality and Noise Management Division from the National Pollution Control Department (PCD),
  • The Department of Science from King Mongkut’s University of Technology Thonburi (KMUTT)
  • Field and Renewable Energy Crops Research Institute (FCRI) from the Department of Agriculture  (DOA)
  • Bureau of Animal Husbandry and Genetic Improvement from the department of livestock
  • Thailand Greenhouse Gas Management Organization
The report has taken over two years and was due to be completed in 2020 but delayed due to complications in data collection and analysis caused by the Covid 19 pandemic. 

Many stakeholders were involved throughout the data collection and research process to ensure diverse and impartial results. The farmers, the stakeholders most affected, were contacted directly to get a first-hand account of their experiences.  This includes data collected through interviews, questionnaires, and surveys. Government data, stats, numbers were also used. 

The objectives of the study were to 
  • Study appropriate indicators for the comparison of two agricultural models in the area 
  • Determine sustainability dimensions for the two agricultural models
  • Determine the GHG emissions of the two agricultural models
  • Compare sustainability of the two agricultural models
  • Compare GHG emissions of the two agricultural models 

Social 

The ‘social’ section of the project was presented by Dr. Unruan Leknoi from Chulalongkorn University. The SAFA framework indicators focused on were
  • Decent livelihood 
  • Fairtrade practices 
  • Labour rights 
  • Equity 
  • Human safety and health 
  • Cultural diversity. 
Dr. Leknoi used these indicators to compare monoculture agriculture with a mixed agriculture system in Mae Chaem District. Based on the SAFA indicators, both monoculture and mixed showed worrying signs under ‘decent livelihood’ as the next generation did not express the desire to continue working in agriculture for either families in monoculture agriculture nor mixed. 

However, monoculture agriculture showed more issues in other areas. The NSTDA study revealed that monoculture farmers fared poorly under the fair trade practices indicator as often they have no choice but to sell to large agribusinesses who are able to determine the prices. Mixed agriculture farmers on the other hand were found to hold more negotiating power and were freer to choose more where their products were sold. 

Cultural diversity is another area where monoculture agriculture fared poorly based on the SAFA framework.  Due to economic demands, monoculture farmers in Mae Chaem are not able to use local/cultural knowledge or plant local seeds. Often they use maize   Mixed agriculture farmers on the other hand are able to do so. This is seen with the FLR349 agricultural model where the farmers are not only encouraged to use grow local crop varieties with local wisdom, but training and local saplings are provided to facilitate this. 



While a mixed agricultural system has more social benefits based on the SAFA framework, there are still needs to be a focus on improving the livelihood indicator, specifically getting the next generation to stay in the area  

Governance 

The governance portion of the study was conducted with Chula Unisearch. Governance is often overlooked when it comes to sustainability, but it is becoming more important both locally and internationally. The study revealed that smaller organisations are at a disadvantage compared to large corporations as they do not have the structure in place to have sustainable governance. This is the case for both agricultural systems. Currently, there are gaps in policies, structure, resources, funding, and knowledge which makes it difficult for the smallholder farmers to be sustainable in terms of governance. With a sustainable supply chain, PGS certification, and retail partners providing guaranteed market places and funding, the FLR349 project is able to fill in some of the gaps needed. 

Economics

The economics portion of the study was completed by Associate Professor Dr. Sate Sampattagul and Dr.Sarunnoud Phuphisith from Chiang Mai University, and the SAFA indicators focused on were
  • Investment 
  • Vulnerability 
  • Product quality and information
  • Local economy 
Through conducting field research in Mae Chaem District with interviews and surveys, Dr. Sampattagul and Dr. Phuphisith aimed to analyse
  • Investment in each type of agriculture
  • Stability in production, sales, and liquidation. 
  • Use of dangerous chemicals 
  • Use of local inputs 
Their research found that while both types of agriculture are generating investments, which includes internal investment, community investment, and long-term investments, mixed agriculture is generating investment from more diverse sources. 

When it comes to vulnerability, monoculture farmers were found to fare worse based on the research. This is because mixed agriculture had more stability due to the variety of product diversification as well as a higher guarantee of production levels. This helps diversify the sources of income for mixed agricultural farmers, whereas monoculture farmers have to rely on maize as their sole source of income. These problems for monoculture farmers are compounded by their limited market channels compared to mixed agriculture. Moreover, mixed agriculture farmers were also found to be more profitable as they were able to set the price of their outputs, something monoculture farmers are unable to do.  With more loan sources, mixed agriculture farmers also have a better safety net for cash flow problems. 





When it comes to product quality and information monoculture agriculture also fared more poorly. This is mainly due to the need for agrochemicals  This is not the case with mixed agriculture wherein systems like FLR349 agricultural model organic methods are taught and enforced in the project sites and PGS certifications are given to the sites. Where monoculture agriculture performed better than mixed based on the research is however traceability. Currently, it is easier for the buyers to trace monoculture products back to its source when compared to products from a mixed system, however, the FLR349 has collaborated with Ricult to develop a traceability system, mitigating this problem. 

While Dr. Sampattagul and Dr. Phuphisith were not able to find the impacts of monoculture on the local economy, however, they did find mixed agriculture farmers tend to purchase agriculture inputs from local stores, boosting the local economy

Environment

The environment portion of the study was completed by Assistant Professor  Dr Lekno and Pichaya Surapolchai. The SAFA indicators studied were 
  • Atmosphere 
  • Water 
  • Land 
  • Biodiversity 
  • Material and Energy 
When it comes to water the study found that apart from wasting more water, monoculture agriculture also leaves traces of chemicals in the water. Moreover, monoculture farmers in the study did not use organic fertilisers nor were they found to actively conserve topsoil, further degrading the land. This is emphasized by the lack of living organisms like earthworms in the soil, which is the result of stubble burning paired with chemicals, fertilisers, and insecticides.

By planting a mixture of crops, using organic fertilisers, and leaving the land to its regenerative purposes, the FLR349 agricultural model also promotes biodiversity.  



Mixed agriculture on the other hand often uses organic fertilisers, which help increase organic matter in the soil throughout the planting process. The planting of perennial plants also helps the soil recover naturally every planting season, improving soil structure and sustainability. 

The study found in Mae Chaem district, on average monoculture agriculture uses 60% more chemical fertilisers when compared to a mixed agricultural system, which incorporates natural fertilisers. This difference is even greater when compared to the FLR349 where chemical fertilisers are not used at all. 

The last environmental factor is 'atmosphere', and the study showed that a mixed agriculture system stores more and releases less carbon when compared to monoculture agriculture. These findings were further expanded in the GHG section. 

GHG Emissions 

The GHG section of the study was by Dr. Nongnuch Poolsawad Tassaneewan Chom-in Wanwisa Thanungkano from NSTDA

The findings show that maize plantations have a net carbon emission of 4,211.5 kg CO2eq ha-1 yr-1. Meaning after taking away the amount of carbon released, including carbon emitted when stubble is burnt, from the amount of carbon stored, maize plantations release 4,211.5 kg of carbon equivalent per hectare per year. The FLR349 agriculture model has a carbon balance of -2,789.88 CO2eq ha-1 yr-1. These results show while maize plantations in Mae Chaem District contribute to CO2 emissions and the annual haze pollution problems, the FLR349 agricultural model stores more carbon than it releases.

 
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