Livestock Research for Rural Development 31 (3) 2019 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Greenhouse gas emissions in smallholder dairy farms in Malawi

Patricia Mayuni1,2, Dan Chiumia2, Timothy Gondwe2, Liveness Banda2, Mizeck Chagunda3 and D Kazanga2,4

1 Department of Animal Health and Livestock Development, Box 2096, Lilongwe, Malawi
mamamayuni@yahoo.co.uk
2 Animal Science Department, Lilongwe University of Agriculture and Natural Resources, Box 219, Lilongwe,
3 Scottish Rural College, Dumfries, Scotland,
4 Heifer International Malawi, Private Bag 31508, Lilongwe

Abstract

The dairy sector in Malawi primarily comprises farmers who are organized into well – defined groups called Milk Bulking Groups (MBG) through government extension system. Notably, smallholder dairying is increasing in terms of number of farmers, animals and area of coverage. Milk yields per cow are, however, not according to breed potential, while both pure and crossbred dairy cows are kept. The increased dairy sector also translates into increased volume of feeds consumed, and subsequently more manure and energy outputs. Dairying is associated with GHG emissions that also relate to how efficient a system is. The FAO (2016) report on GHG emissions from the dairy sector states that the entire livestock food chain contributes 18% of total global anthropogenic GHG emissions (26 %) and that 4% of this is estimated to come from the global dairy sector. This study aims at assessing GHG emissions in the Malawi smallholder dairy sector associated with feeding practices and analyzing their effectiveness in terms of impacting productivity of different breeds and genotypes. The goal is to come up with recommendations for feeding practices that are cost effective, and that will increase dairy productivity while substantially reducing the dairy carbon foot print and increasing household income and food security. The study was undertaken under the small holder dairy production programme and enhanced breeding practices, a component promoted by the Capacity Building for Managing Climate Change (CABMACC) Programme under the project “Reducing dairy carbon foot-print through breeding and feeding based technologies for improved productivity (REDCAP). REDCAP is a project within CABMACC that has been in operation from 2015 to 2018. The project was designed to evaluate feeding and breeding technologies for optimal dairy productivity and reduced carbon emissions with focus on smallholder farmers in drought prone areas.

The data on the national herd in Malawi, the REDCAP baseline and the REDCAP intermediate results indicate that enteric gases are the major sources of greenhouse gas emissions followed by manure and energy use. The share by gases in total emissions was carbon dioxide 21%, methane 44% and nitrous oxide 35%. The lower GHG emissions per unit of milk protein from the REDCAP intermediate results probably reflect the better feeding practices exemplified by greater use of concentrates and forage trees.

Keywords: carbon footprint, GLEAM, manure, milk yield


Introduction

The dairy sector in Malawi primarily comprise small-scale farmers who are successfully organized into well-defined groups called Milk Bulking Groups (MBG) through the government extension system. In the era of setting up the dairy sector the Government invested in construction of production infrastructure and cooling facilities, distributed start up dairy animals and built the capacity to manage the facilities. The Government also built up the technical capacity of smallholder farmers through training in animal husbandry, group dynamics and agribusiness. Government has continued to develop the sector by conducting training and refresher courses for its frontline staff. It has established and operates a National Artificial Insemination Scheme (NAIS) facility at Mikolongwe, facilitates supply of AI equipment and training of both staff and farmer AI technicians (FAITs) to promote artificial insemination breeding technology. The dairy sub-sector is one of the critical livestock contributors to the Malawi economy, and smallholder dairy is the flagship of the Malawi livestock sector. Its contribution is estimated at 10 % of the total agriculture Gross Domestic Product (GDP) and about 3% of the country’s overall GDP. The dairy sector is estimated to contribute up to 45% of the livestock sub-sector GDP and plays an important role as a source of food, income and employment. The recent estimates indicate a milk production rate of 69,000 tonnes/year and on average 70% of the total production is marketed, while 30% is consumed by the producing households (CISANET 2014; MoAIWD 2015). It is worthy to note that dairying is significant in Malawi and has demonstrated that it can be an instrument of socio-economic change. The small holder dairy production programme and enhanced breeding practices are one component that is being promoted by the Capacity Building for Managing Climate Change (CABMACC) Programme under the project “Reducing dairy carbon foot-print through breeding and feeding based technologies for improved productivity (REDCAP). In addition, REDCAP provides training to farmers in the areas of animal health, feeds and feeding, marketing and general animal husbandry practices.

The background is that the growth of the dairy sector in Malawi translates into increased volumes of feed consumed by the dairy cattle, increased volumes of manure and energy use in both production and processing of milk. The FAO (2016) report on GHG emissions from the dairy sector states that the entire livestock food chain contributes 18% of total global anthropogenic GHG emissions and that 4% of this is estimated to come from the global dairy sector. The average global emissions from milk production, processing and transportation are estimated to be 2.4 kg of CO2 eq per kg of fat and protein corrected milk (FPCM) at farm gate. Sub-Saharan Africa was found to have highest life cycle emissions averaging 7.5 kg CO2-eq per kg of FPCM which vary based on feeding systems (Gerber 2013). Dairy farming must therefore be managed to make reductions in GHG emissions intensity through increased efficiencies, such as optimum animal performance and reduced inputs, whilst still maintaining productivity (Bell et al 2012). It is reported that the yield advantage of grade cattle is realizable only when combined with the appropriate dairy production management and secondly, that the potential for increased productivity of smallholder dairying can be realized only in conjunction with an efficient marketing system (Ngigi 2005). The large dependence of milk producers on the dairy processing industry has resulted in strong co-operatives in the milk marketing and milk processing sectors (Bell et al 2012) and this applies to the Malawi set up where these exist as associations at both regional and national level. The sector, however, lacks guidelines on feeding practices and genotypes that are cost effective in yielding more milk and less GHGs.

This study aims at assessing GHG emissions in the Malawi smallholder dairy sector associated with different feeding practices and analyzing their effectiveness in terms of impacting productivity of different breeds and genotypes. The goal is to come up with recommendations for feeds and feeding practices that are cost effective and that will increase dairy productivity while substantially reducing the dairy carbon foot print and increasing household income, food and nutrition security.


Methodology

The greenhouse gases were assessed using GLEAM i, a component of the Global Livestock Environmental Assessment (GLEAM) model. GLEAM is a modular framework that simulates the interaction of activities and processes involved in livestock production and the environment. The GLEAM was developed by the Animal Production and Health division of FAO to evaluate the environmental impact of the livestock sector and to assess intervention scenarios. It provides disaggregated and spatially explicit estimations of livestock production and GHG emissions based on Tier 2 methodologies of the Intergovernmental Panel on Climate Change (IPCC). Tier levels, according to the IPCC, correspond to a progression from the use of simple equations with default data (Tier 1 emission factors), to country-specific data in more complex national systems (Tier 2 and 3 emission factors). Tiers implicitly progress from least to greatest levels of certainty, as a function of methodological complexity, regional specificity of model parameters, spatial resolution and the availability of activity data (FAO 2016). The model was developed to assess livestock's impacts, adaptation and mitigation options at (sub) national, regional and global scale and assesses the adaptation and mitigation scenarios in a more sustainable agenda. It differentiates key stages along the livestock supply chains such as feed production, processing and transport; herd dynamics, animal feeding and manure management, animal products processing and transport, and captures the specific impacts of each stage. It also offers a comprehensive and disaggregated picture of the negative side effects of livestock production and provides valuable information for intervention. GLEAM-interactive (GLEAM-i) brings the core functionalities of GLEAM to the public in a single excel file. GLEAM-i is the first open, user-friendly, livestock specific, and climate change tool designed to support governments, project planners, producers, industry and civil society organizations to calculate emissions using Tier 2 methods. GLEAM-i can be used in the preparation of national inventories and in ex-ante project evaluation for the assessment of intervention scenarios in animal husbandry, feed and manure management. It benefits from the in-built GLEAM database of parameters and activity data, which can easily be adapted by the user to match specific conditions.

Data collection and analyses

The data analyzed in this study comprised national data and data collected from CABMACC project implementation area of Linthipe and Mayani EPAs, in Dedza District under Lilongwe Agriculture Development Division (LADD). CABMACC baseline data provided initial emissions to act as baseline, and this was compared with data collected after some interventions that included enhanced feeding practices. National data were extracted from national livestock estimates of populations and products for the 2015 / 2016 farming year. During the year, there were 84,700 dairy cattle, and these produced 235,000 metric tonnes of milk (with extended calving interval the milk year completes the 365 days). All data were based on mixed systems and from the following outputs:

All the data were fitted into the GLEAM – i Model that produced outputs presented in the following section.


Results

The analysis of the Malawi national dairy herd

Figure 1 shows the emission intensities for the national herd in Malawi. Total emission regardless of source is 120,647,829 tonnes of CO2 eq/year. The national output per kg of protein was 26 kg of CO 2 eq, compared to the regional value of 264 kg of CO2 eq per kilogram of protein.

The main sources of emissions were enteric gases, feed, manure and energy use (Table 1).

Figure 1. Total emissions by source for the national dairy herd



Figure 2. IPCC Tier 1 compared with GLEAM i for national dairy herd

Share by gases in total emissions

The gases targeted include Carbon dioxide 21%, Methane 44% and Nitrous oxide 35%. While the Carbon dioxide and the Methane mostly arise from the enteric fermentations, the Nitrous oxide mostly originate from the manure dumped in a pit at the farm (Figure 3).

 

Figure 3. Share by gases in national total emissions

Analysis of REDCAP baseline

Data collected at the inception of the REDCAP was analyzed. From the study area, milk production was estimated t 4.5 liters per cow per day. From this data, the emission intensities are 361 kg of CO2 eq per kilogram of protein. The national trend is observed in the herd under the REDCAP project, the main source being enteric gases, then feed utilization and processing, and manure (Figure 4). Similar observations were noted for share by gas emission (Figure 5).

Figure 4. Total Emissions by source for the baseline REDCAP herds


Figure 5. Share by gases for REDCAP baseline


Figure 6. REDCAP baseline IPCC Tier 1 compared with gleam i
REDCAP results

Interventions in the REDCAP implementation nclude feed supplementation with concentrates and agroforestry trees, the latter being higher in protein and in digestibility compared to the common feed of Napier grass. These feeding practices have resulted in the average production of milk increasing from 4.5 to 11 liters per day. Based on these data, milk production per annum was estimated at 336 tonnes from the total herd of 87 animals (GLEAM i. simulation results). This produced total emissions of 1,293,551 tonnes of CO2 eq (Figure 7).

Figure 7. Total Emissions by source under REDCAP interventions


Figure 8. The main sources of emissions REDCAP intermediary

Gas emissions were estimated to included Nitrous oxide 11%, Carbon dioxide 6% and Methane 83% (Figure 9).

Figure 9. Share by gas in total emissions REDCAP intermediate results
Comparison of national, baseline and intervention data

The major greenhouse gases being analyzed include Carbon dioxide, Methane and Nitrous oxide. Methane quantities were largest followed by Nitrous oxide and then Carbon dioxide (Figure 10).

Figure 10. Share by gas in total emissions REDCAP intermediate results

The main sources of emissions were enteric gases, feed, manure and energy use (Table 1).

Table 1. Source of emissions for National, REDCAP Baseline and Intermediate (kg CO2 eq/year)

National herd

REDCAP baseline

Intermediate

Feed

54545433

204581

162614

Enteric

52819225

1576662

960419

Manure

10234022

108386

88803

Energy use

3029148

3844

8539


Discussion

Dairy herds produce a mix of goods and services such as milk, manure, capital services, and eventually meat when slaughtered. The grassland and mixed farming systems are estimated to contribute around 50 percent to global milk production, However, grassland-based systems, on average, account for 60 percent of the global sector emissions, whereas mixed systems are characterized by a lower emission intensity, of only 40 percent of emissions (FAO 2016).

In the current study, the data analyzed for the national herd were sourced from agricultural production estimates and included all categories based on the GLEAM specifications. However, the data collected fell short of the GLEAM specification and this may affect the results of the analysis. The data for REDCAP were collected following CABMACC indicators, which also did not fully cover all the inputs for analyzing gas sources and shares under Gleam i. The feed and enteric gases are the major contributors both at national and at study area level. It was however observed that there were some differences amongst the three estimates in the intensities of the gas sources; the national herd was 26kg of CO2 per kg of protein, the REDCAP baseline was at 361kg of CO2 per kg of protein and for the intermediate result it was 35kg of CO2 per kg of protein. All these except those of the REDCAP baseline are lower than that of the region, which is at 264kg of CO2 per kg of protein. These differences might be arising due to levels of milk yield, which to an extent demonstrate an inverse relationship with gas emissions. The milk level of 4.5 yielded 361kg of CO2 per kg of protein and after interventions of feeding, milk levels increased to 11 kg and the gas emission intensities decreased to 35kg of CO2 per kg of protein. Further differences in the gas quantities emitted were observed between the REDCAP baseline and that of the intermediate results which were lower by 21% for feed, 39% for enteric gases, and 18% for manure. On the contrary emissions for energy use increased by 122%. The reduction in the emissions from the intermediate results is mainly alluded to the quality of feed provided to the animals being of improved digestibility and increased protein content, triggering increased milk yield. The increase in milk production results in the reduction of the emission intensity.

Studies have shown that some dietary practices reduce CH4 and these include the addition of ionophores, fats, the use of high quality forages, and the increased use of grains (Virginia 2017). This has also been demonstrated in the gas shares where the quantities for Methane and Carbon dioxide are lower in the intermediate results compared to the baseline. The emissions from energy use as between the REDCAP baseline and that of the intermediate results, have substantially increased more likely due to the increase in milk volumes resulting in more energy being used for cooling, transportation and processing.

GLEAM i monitors the manure disposal method and time period of manure storage before application. Emissions increase with open deposition and longer period before application. The assessment of the emissions regarding energy use and related greenhouse gas emissions on major post-farm activities include:

The GLEAM analysis on share by gases yielded carbon dioxide 21%, methane 44% and nitrous oxide 35% for the national level compared to nitrous oxide 39%, carbon dioxide 11% and Methane 50% for REDCAP. The levels of carbon dioxide at national level are double that of REDCAP, while for Nitrous and Methane percentages are higher in the REDCAP by 5% and 6% respectively compared to those of the national level. The intermediate results show that methane levels after interventions of feed practices were lowered by 5% and nitrous oxide emissions were lowered by 36% while those of carbon dioxide remained static. The share by gases is consistent with the life cycle assessment by FAO (2016), where methane is generally the most important contributor to the total greenhouse gas emissions from milk production, accounting for 50 percent or more of emissions. Nitrous oxide emissions range from 27 to 38 percent of the total emissions, while carbon dioxide plays a minor role in on-farm emissions, representing on average 5 to 10 percent of the total emissions (FAO 2016).


Conclusions


References

Bell M J, Eckard R J and Pryce J E 2012 Breeding Dairy Cows to Reduce Greenhouse Gas Emissions. Livestock Production, Chapter 3, pp.47–58.

Civil Society of Agriculture Network (CISANET) 2014 the Potential , Opportunities and Challenges of Dairy Processing and Value Addition in Malawi

FAO 2016a Global livestock environmental assessment model. Food and Agriculture Organization of the United Nations. Available at: http://www.fao.org/fileadmin/user_upload/gleam/docs/GLEAM_1.0_Model_description.pdf.

FAO 2016b Global Livestock Environmental Assessment Model (GLEAM). Food and Agriculture Organization of the United Nations. Available at: http://www.fao.org/gleam/results/en/.

Gerber Pierre, Vellinga Theun, Opio Caroline, Henderson B and Steinfield H  2013 ESAB Profile Cutting Systems, Available at: http://esab.westgatehitech.com.au/products/catId/24/itemId/80 [Accessed November 4, 2016].

MoIWD 2015 Department of Animal Health and Livestock Development 2014-2015 First quarter workplan and budget Agriculture sector Wide approach program, Multi-donor trust fund.

Ngigi M 2005 The Case of Smallholder Dairying in Eastern Africa. Ssrn, (February). 2033k, street, Nw, Washington

Virginia I 2008 Carbon, Methane Emissions and the Dairy Cow — Dairy Cattle Nutrition — Penn State Extension. Psu, (Table 1), pp.6–8. Available at: http://extension.psu.edu/animals/dairy/nutrition/nutrition-and-feeding/diet-formulation-and-evaluation/carbon-methane-emissions-and-the-dairy-cow.


Received 3 February 2019; Accepted 19 February 2019; Published 4 March 2019

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