Measuring Environmental Externalities to Agriculture in Africa Case Study: Ghana Palm Oil Sector

Audrey Suarez, Hanbit Kim, Haoaram Kim, Madhumitha Madhavan

May 2013

TABLE OF CONTENTS

ABBREVIATIONS ........................................................................................................... 1

BACKGROUND ............................................................................................................... 2

Agriculture and Environment ...................................................................................................... 2

Oil Palm ............................................................................................................................................. 3

METHODOLOGY AND FINDINGS ............................................................................. 5

Explanation of Indicators and EVM .......................................................................................... 7

Production Function Equation: Biomass as a Factor of Production ................................. 7

Other Externalities as Factors of Production ........................................................................... 9

CONCLUSION ............................................................................................................... 10

Recommendations ........................................................................................................................ 11

BIBILIOGRAPHY ......................................................................................................... 13

APPENDIX: Interviewee Information .......................................................................... 14

1

ABBREVIATIONS

AEI Agri-Environmental Indicator

AFD Agence Française de Développement

CoED Cost of Environmental Degradation

CSIR Council for Scientific and Industrial Research

DSR Driving Force-State Response

EPA Environmental Protection Agency

EVM Environmental Valuation Methodologies

EVRI Environmental Valuation Reference Inventory

FAO Food and Agriculture Organization

GDP Gross Domestic Product

GHG Greenhouse Gas

GOPDC Ghana Oil Palm Development Company

GSS Ghana Statistical Service

LSS Living Standards Survey

MAFAP Monitoring African Food and Agricultural Policies

NGO Non-Governmental Organization

OECD Organization for Economic Co-operation and Development

OPRI Oil Palm Research Institute

POME Palm Oil Mill Effluent

PSR Pressure-State-Response

STEPRI Science and Technology Policy Research Institute

UNCSD United Nations Commission on Sustainable Development

2

This case study report summarizes the findings and subsequent recommendations

resulting from the application of the proposed framework methodology for measuring

environmental externalities to agriculture in Africa (see Measuring Environmental

Externalities to Agriculture in Africa: Report on Framework Methodology) to a small-

scale case study on the palm oil sector in Ghana. This methodology was produced for the

Monitoring African Food and Agricultural Policies (MAFAP) project for potential

integration into the existing MAFAP methodology.

The selection of Ghana as the case study country was based on a combination of its

stability and low security concerns, as well as the availability of institutional support for

the field team offered by MAFAP’s close ties with the Council for Scientific and

Industrial Research’s Science and Technology Policy Research Institute (CSIR-STEPRI).

The MAFAP Commodity selected for field testing was palm oil, due to the availability of

institutional support from STEPRI’s ties with CSIR sister organisation, the Oil Palm

Research Institute (OPRI).

The case study consisted of off-site research and fieldwork in Ghana. The fieldwork

comprised a series of interviews and focus groups with a wide range of stakeholders

conducted over the course of two weeks in Accra and Kade. The goals of these interviews

were to verify the accuracy and appropriateness of the set of general externalities

described in the framework methodology, and to gather local data with which to populate

the model being field-tested.

BACKGROUND

Agriculture and Environment

In Ghana, agriculture is one of the most important economic sectors, employing more

than half of the population and accounting for almost half of the country’s GDP and

export earnings. Ghana produces a variety of agricultural crops, including oil palms,

yams, cocoa, grains, kola nuts, and timber, which form the base of Ghana’s economy1.

These crop productions are predominantly on a smallholder basis. The majority of farm

holdings (about 90 percent) are less than two hectares in size, although there are some

large plantations, particularly palm oil, coconut, rubber, rice, maize, and pineapples2. The

main farming system is traditional, using farming tools such as hoe and cutlass.

Agricultural production varies depending on the amount and distribution of rainfall and

quality of soil. Most food crops are intercropped whereas larger-scale commercial farms

are primarily associated with mono cropping, a practice which reduces biodiversity.

1 KPMG, Doing Business in Ghana (July 2012), Pg.20

http://www.kpmg.com/GH/en/Documents/Doing%20business%20in%20Ghana%20-2012.pdf

2 Ministry of Food and Agriculture, Agriculture in Ghana: Facts and Figures (May 2011), Pg.5

http://mofa.gov.gh/site/wp-content/uploads/2011/10/AGRICULTURE-IN-GHANA-FF-2010.pdf

3

In many locations, large areas of tropical forests and other ecosystems with high

conservation values have been cleared in order to create more space for plantations.

Globally, forest conversion by small and large plantation companies not only contributes

to deforestation but also climate change, producing around 20 percent of all human

induced greenhouse gas (GHG) emissions3. Especially, the practice of draining and

converting tropical peat forests is obstructing efforts to mitigate climate change, as more

carbon (per unit area) is stored in these carbon sinks than any other ecosystem in the

world4. Moreover, the burning of forests to clear land for plantations has been one of the

major sources of haze in the country, and this has caused serious health and

environmental problems in Ghana.

Chemical pesticides and fertilizers applied to increase agricultural productivity can

pollute the surrounding soil and water, causing health problems or even fatality to human,

animal, and plant populations downstream. Many smallholder farmers are not aware of

best practices for chemical application, and misuse chemicals in such a way as to increase

the likelihood of chemical runoff. Due to inadequate education policies in Ghana,

illiterate smallholders cannot understand literature distributed concerning best practices.

Some of these farmers are educated on best practices by agricultural extension agents, but

extension services are not adequately invested in, leaving such service providers unable

to reach the majority of farmers.

Oil Palm

The oil palm is indigenous to the coastal regions of West Africa and has been grown in

other parts of the world since the end of the 19th century. Its production is generally

limited to latitudes of approximately 10 degrees north and south of the equator, at

altitudes below 700 meters and with a minimum rainfall of 1600 mm per year5. Therefore,

the tropical high forest zone of Ghana is known to be well suited for the cultivation of oil

palm, particularly in the southern regions of Ghana, which have two rainy seasons (the

first from March to July, and a second from September to November). The oil palm

produces two types of oil: palm oil from the fibrous mesocarp (flesh) and lauric oil from

the palm kernel. Palm oil has various applications, including as food, oleochemicals,

energy/ biomass, and others.

Global production of palm oil was about 48.55 million metric tons in 2011, with African

countries producing about 5.4 percent of the global production total6. In 2011, Ghana

produced 120,000 tons of palm oil, making it the 17th

largest producer in the world.

3 WWF International, The Palm Oil Financing Handbook (2008), Pg.10

http://assets.panda.org/downloads/the_palmoil_financing_handbook.pdf

4 Ibid.

5 Ibid., Pg.8

6 FAOSTAT, http://faostat.fao.org/

4

Ghana exported 1,713 tons of palm oil with a total value of $ 617,000 (USD). However,

there is potential for greater investment in the palm oil sector in Ghana7.

The total land area under oil palm cultivation in Ghana was expected to be around

352,800 ha in 2009. Small-scale producers and processors far outnumber the major

producers of palm oil in Ghana. While private smallholders produce about 1.5 million

tons (71 percent of the country’s total), the five major producers produce about 0.6

million tons (28 percent). However, the average yield level (11,480 Yield/Ha) of the

major producers is more than twice as high as that of independent smallholdings (5,000

Yield/Ha)8.

In Ghana, the development of the palm oil industry is constrained by various factors.

Many smallholders do not use improved seed stock or fertilizers for several reasons,

primarily high monetary cost, inability to access such materials, or lack of awareness of

the potential benefits of fertilizer application. Additionally, small-scale farmers and

processors are still using traditional technologies which are highly labour intensive.

Moreover, lack of access to markets and infrastructure such as roads is another constraint

that hinders the development of the palm oil industry.

The expansion of oil palm production and processing has the potential to have significant

impacts on the environment. At the farm level, if production expansion leads to increased

use of chemical pesticides and fertilizers applied to increase oil palm productivity, the

application of such chemicals can pollute the surrounding soil and water. Similarly,

although irrigation is not currently practiced with regularity in Ghana, if increasingly

modernised production methods lead to increased use of irrigation in Ghana, habitat and

biodiversity could be adversely affected. Additionally, agricultural land expansion for oil

palm production can lead to deforestation, primarily of secondary forest and depleted

citrus groves. In cases where burning is the method used for clearing, the haze produced

by this burning hinders photosynthesis, reduces the activity of pollinating weevils, and

has negative short-term vision effects and short- and long-term health effects on the

labour force, which limits their ability to harvest the fruit, thereby reducing the overall

productivity of oil palm trees. Expansion of oil palm also stands to reduce biodiversity

locally. Normally, oil palm is cultivated as a mono-crop due to its high requirements for

light and fresh water in order to thrive. This trend may be somewhat mitigated by the

practice of intercropping with food crops in the first three years of the trees’ growth,

before the canopies become too dense to admit enough sunlight for most crops. Recently,

some farmers in Ghana have begun practicing intercropping more mature oil palm trees

with cocoa, which is typically cultivated under shade from thinned forest trees. One

major advantage of oil palm/ cocoa intercropping is that these two crops require different

labour calendars that do not overlap with each other. For oil palm, peak yield, and thus

7 MASDAR, Master Study on the Oil Palm Industry in Ghana (2011). Hampshire, UK.

https://docs.google.com/open?id=0B4fn1Fz6J8K9djY5X1JIaHVyeUE

8 Ministry of Food and Agriculture, Agriculture in Ghana: Facts and Figures (2009). Accra,

Ghana. http://foodsecurityghana.com/wp-content/uploads/2011/03/AGRICULTURE-IN-

GHANA-2009.pdf

5

the highest labour requirements, occur between February and July, whereas for cocoa,

peak yield is between September and March. Oil palm/ cocoa intercropping has been

proven to be biologically compatible in Nigeria, thus the practice of intercropping oil

palm and cocoa could expand in Ghana in the future. However, information on the

possible net benefits to biodiversity of such intercropping practices under Ghanaian

conditions is not sufficient at this time.

At the processing level, it has been observed that most of the palm oil mill effluent

(POME) produced by small-scale traditional processors undergoes little or no treatment.

It is usually discharged into the surrounding environment, which results in degradation of

water and soil. POME is considered non-toxic, but it is identified as a major source of

aquatic pollution as it depletes dissolved oxygen when discharged untreated into the

water bodies. Raw POME has biological oxygen demand values averaging around 25,000

mg/litre, making it about 100 times more polluting than domestic sewage9. However,

POME also contains vital nutrient elements for plant growth, and thus, it can be used as

fertilizer or animal feed substitute if it is treated properly. There are several ways to treat

POME to make it safe to use as fertilizer, such as aerobic and anaerobic digestion and

physicochemical treatment, but these biological practices are only applicable in the palm

oil mills which have large areas of land10

. Additionally, high processing costs and weak

political and legal support limit the practicability of such options.

METHODOLOGY AND FINDINGS

The proposed framework methodology for measuring environmental externalities to

agriculture in Africa (see “Measuring Environmental Externalities to Agriculture in

Africa: Report on Framework Methodology”) suggests two types of indicators for the

measurement of agricultural impacts on the environment – OECD’s Agri-Environmental

Indicators based on the Pressure-State-Response (PSR) Framework, which sets out the

possible externalities to agriculture; and Environmental Valuation Methodologies which

are used to calculate a monetary value for various aspects of the environment when faced

with these externalities.

In the framework document, the proposed list of externalities and the valuation

methodologies suggested to analyse them are intended to represent a comprehensive list

for all of MAFAP’s countries and commodities of operation. In order to apply the

framework methodology to the Ghanaian palm oil sector, the general set of indicators

9 Okwute, Loretta Ojonoma and Isu, Nnennaya R., The Environmental Impact of Palm Oil Mill

Effluent (POME) on Some Physico-chemical Parameters and Total Aerobic Bioload of Soil at a

Dump site in Anyigba, Kogi State, Nigeria (2007), Pg.656-662

http://www.academicjournals.org/ajar/pdf/Pdf2007/Dec/Ojonoma%20and%20Nnennaya.pdf

10 Rupani, Parveen Fatemeh, Rajeev Pratap Singh, M. Hakimi Ibrahim and Norizan Esa., Review

of Current Palm Oil Mill Effluent (POME) Treatment Methods: Vermicomposting as a

Sustainable Practice (2010), Pg.70-81 http://www.idosi.org/wasj/wasj11(1)10/12.pdf

6

would have to be culled to only those applicable to the case study, based on the

information gathered in the field.

In Accra, interviews and focus groups were conducted with the staff of various relevant

ministries and environmental NGOs. The case study team utilised a series of semi-

structured interview questions to ascertain from these technical experts information

regarding the general agricultural situation in Ghana, the general environmental situation,

and their opinions on what the environmental externalities to agriculture in their country

are. The goal of these interviews was to verify the accuracy and appropriateness of the set

of general externalities described in the framework methodology. Additionally, this was

an opportunity to add to that general set any externalities described by the interview

subjects which had not been included in the initial drafting of the general set. Because the

majority of technical experts interviewed in Accra were not oil palm specialists, their

expertise was useful in a general sense and for verifying indicators. In order to test the

application of the methodology to the palm oil sector, more specific data were gathered in

Kade.

In Kade, interviews and focus groups were conducted with a range of stakeholders: OPRI

staff and technical experts, local small-scale producers, and small- and medium-scale

processors. The field team also attempted to interview staff at a large scale producer/

processor, the Ghana Oil Palm Development Company (GOPDC), but the company

refused to grant an interview or release any information not currently published on its

website11

. Among the OPRI staff, a similar semi-structured interview to that used in

Accra was used, with a focus on the externalities of oil palm and government policies

targeting the palm oil sector. Among the producers and processors, interviews

concentrated on their methods of production, their experiences with government

agriculture and food policy, their opinions on the effects of oil palm on the natural

environment locally, and data specific to their inputs and outputs with which to source

the production function being field tested. In addition to the data gathered from these

field visits, the case study production function was also sourced with data from past

OPRI studies as well as data gathered off-site by the case study team.

It was decided that in applying the framework methodology, only the production (or

cultivation) of oil palm would be considered for the case study. Due to time and resource

constraints, it was not feasible to extend the case study to include the differing

environmental and market implications of the various methods of processing palm oil –

which vary based on both the facilities used for processing and the intended end use of

the palm oil. For the most accurate assessment of the environmental costs of palm oil

production in Ghana, more data would need to be collected over a greater period of time

(to ensure statistically significant results), and the environmental externalities would need

to be analysed along the entire palm oil value chain rather than solely with regard to the

cultivation of the oil palm trees.

11

GOPDC Ltd., http://www.gopdc-ltd.com/

7

Explanation of Indicators and EVM

In 1984 the United Nations Statistics Division proposed the Framework for the

Development of Environmental Statistics that set out a broad framework for measuring

and organizing environmental information. Moreover the UN Commission on Sustainable

Development (UN CSD) also developed a framework called the Driving Force-State

Response (DSR) framework, which was the basis for OECD’s PSR framework. In 2002,

FAO developed a handbook for identifying, prioritizing and measuring specific agri-

environmental indicators (AEIs) based on the issue and context.

Both the UN CSD as well as FAO already collect data for a number of these OECD AEIs

indicators. These indicators will be useful to determine important information such as the

degree and scale of threat to resources, prioritizing information regions with highest

threat, identifying management policies that could have the highest payoffs etc. Including

all of this information in country reports will be useful in informing policy makers in

prioritizing environmental issues and allocation of available resources.

The second set of indicators is based on the Environmental Valuation Methodologies

(EVM) framework that is based on assigning dollar value to environmental goods and

services. These methodologies have been extensively studied and very widely used. For

example, Environment Canada runs a database called the Environmental Valuation

Reference Inventory (EVRI) that collates a number of studies on the benefits transfer

approach to EVM, and Ghana’s Environmental Protection Agency (EPA) has recently

begun to use EVM to analyse agricultural and environmental statistics in Ghana. Of the

number of indicators that are based on the EVM framework, the market price method

would be most relevant to MAFAP’s methodology.

MAFAP’s current methodology attempts to measure the policy incentives and

disincentives to the agriculture sector and market development gaps. By measuring the

explicit impact of government policies as well as the implicit impact of gaps in the value

chain that affect the price of goods, MAFAP attempts to understand the signals provided

by the market to the agricultural sector. Since MAFAP’s current indicators are price

based, the market based methods would be the most relevant as they estimates the value

of environmental goods and services that are traded in the market.

The following sections illustrate the production function method of EVM, which is a part

of the market-based methodology.

Production Function Equation: Biomass as a Factor of Production

This method is used to estimate the value of ecosystem services in the production of

commercially marketed goods. In agriculture, the quality of land, water, labour etc can

directly affect productivity. It is possible to estimate the cost of this service provided by

land and water by determining the increase in revenue realised through greater

agricultural productivity.

Lopez (1997) developed a framework for measuring the impact of trade policies on

natural resources with respect to the agricultural sector in Ghana. The framework

includes biomass in the production function equation for agriculture to study the direct

8

impact of environmental deterioration on agricultural productivity. The Cobb-Douglas

production function equation including biomass as a factor of production as estimated by

Lopez is given below:

lnQijt = β0 + βx lnxijx + βl ln Lij + βθlnθjt + βkln kijt + Intercept dummies + εijt

Where,

Qijt is the output of farmer i in the village j at time t

xijt is land cultivated by farmer i

Lijt is labor

Θjt is biomass in village j at time t

Kijt is farm capital

εijt is the disturbance term

The intercept dummies are used to control for productivity changes through time. The

biomass value is calculated from the vegetation found on fallow land and the forest

vegetation surrounding the farm areas where the analysis is done. Oil palm has an

economic life of 20-25 years and does not require fallow land. In the above formula,

biomass is calculated as:

Biomass = (total village area under fallow X average vegetation density / acre

of fallow land) + (Forest area X density)

In the case of perennial crops like oil palm, the village area under fallow would simply be

assumed to be zero. By adding data calculated from Living Standards Survey (LSS) and

remote sensing data, the study calculated the double log production function for 139

households spread out over 12 villages in Ghana. Regression analysis was performed to

estimate the coefficients for the production function equation.

The coefficient for biomass factor was found to be between 15 and 20 percent; that is,

biomass contributes 15 to 20 percent of output in the agricultural sector. The coefficient

is comparatively lesser than other factors of production (namely: land, labour, and

capital). In the different regression analyses conducted, the coefficient was found to be at

least 10 percent, indicating that there exists a positive correlation between biomass in an

area and the productivity of the farmlands.

9

During the field visit, interviews were conducted with oil palm farmers in the Yankumase

district. Data were collected from the Yankumase district farmers on various expenditures

and costs involved in oil palm production. The following table summarizes the cost and

profits from nine farmers interviewed:

Farmers Farm Area

(acres)

Age of

Farm

(years)

Land

Clearing

Cost

(GNC/acre)

Transport

Cost

(GNC/ truck)

Pruning Cost

(GNC/year)

Harvesting (2 x / year)

GNC/acre * 2 persons/ acre

Fruit picking

and carrying

GNC/acre

Seedling Cost

GNC/Seedling

Total

Profit

GNC

Farmer 1 3 8 70 40 50 50 20 20 200

Farmer 2 4 8 70 40 50 50 20 20 150

Farmer 3 4 10 70 40 50 50 20 20 280

Farmer 4 3.5 10 70 40 50 50 20 20 250

Farmer 5 3 10 70 40 50 50 20 20 200

Farmer 6 15 10 70 40 50 50 20 20 700

Farmer 7 5 10 70 40 50 50 20 20 200

Farmer 8 70 7 70 40 50 50 20 20 600

Farmer 9 10 10 70 40 50 50 20 20 400

These data were obtained from the oral recall of farmers. Owing to the possibility of high

degree of error and the statistically insignificant number of interviews conducted, a

regression analysis using this data was not conducted. It is recommended that FAO either

conduct a study that will collect these data, on which a regression analysis can be

performed in STATA using the production function above, or partner with an

organisation that has already done a similar analysis in Ghana. The Strategic

Environment Assessment Programme at Ghana’s Environmental Protection Agency is

one such organisation.

Other Externalities as Factors of Production

The Framework Report outlines the overarching methodology for incorporating different

environmental quality terms as a factor of production in the Cobb-Douglas production

function equation. In the case of oil palm production in Ghana, our interviews with local

stakeholders indicated that due to inefficient markets, small holder farmers in Ghana

were unable to access fertilizers needed for oil palm in sufficient quantities. This is

10

consistent with FAO’s data12

that indicate that after the removal of support to the

agricultural sector due to structural reforms in the 1980’s, fertilizer use declined

drastically and is currently at a rate that is half of what existed in the 1970’s. At present,

fertilizer consumption averages at about 4kg of nutrients per ha of arable land in Ghana.

CONCLUSION

Based on the findings from the field work, the production function model used to analyse

the cost of palm oil production externalities was modified to better reflect the local

context and available data by focusing on biomass and downplaying the importance of

externalities such as fertiliser runoff, since they were discovered to not apply in the local

context.

Oil palm was not an ideal case study commodity, since its production in Ghana does not

contribute to many of the externalities being measured by the framework methodology

for environmental costs to agriculture. These results do not invalidate the framework

model however, as was verified by the more general interviews conducted in Accra. As in

the case of palm oil, when examining other MAFAP commodities, some of the general

externalities identified in the framework may not apply, or may need to be weighted

differently in the production function equation depending on context. We can nonetheless

recommend the adoption of the general framework methodology across the MAFAP

countries and commodities, as this will provide a pool of indicators from which to choose,

and a basic production function in which to plug the chosen variables, thus reducing the

amount of work needed to tailor an equation or set of equations for each specific case.

The production function equation illustrated in this case study is only one method of

valuing environmental goods and services. The Framework Report contains a database of

all available EVM methodologies and some other contextual indicators for measuring

environmental impacts of agriculture. Although the production function method is useful

for the MAFAP framework, other indicators could be used on a case-by-case basis to

help inform specific policy decisions. For example, if oil palm plantations were increased

in area leading to a direct decrease in forested area used for recreational purposes, the

travel price method could be used to estimate the value of the recreational site and

compare it directly with the projected profits from the expansion of oil-palm plantations.

It is important to note that no single indicator can provide a complete picture of the costs

and benefits to environment by agricultural activity.

Our interviews suggest that despite that fact that oil palm does not exemplify the

environmental costs to agriculture in Ghana, many of the general externalities identified

in the framework methodology do exist for other crops cultivated in the country, and they

have the potential to have significant impacts. We recommend looking into cocoa

production if further case studies are conducted to beta test this methodology in Ghana.

12

FAO, Fertilizer Use by Crop (2006). ftp://ftp.fao.org/agl/agll/docs/fpnb17.pdf

11

Recommendations

In order to apply the framework methodology for environmental costs to agriculture

across all of the MAFAP countries and commodities, similar fieldwork will need to be

conducted in those areas in order to tailor the general externalities in the production

function to the specific context. As was demonstrated in this case study, knowing the

externalities affecting a country at large, or the externalities resulting from a given

commodity’s production in a general or global context, may still not allow for an accurate

measurement of the environmental costs of a specific commodity in a specific country.

It may not be necessary for MAFAP to conduct original research in each case, however.

Other organisations may already be conducting similar research, and could partner with

MAFAP to save time and effort by sharing information. In the case of Ghana, interviews

with the Environmental Protection Agency revealed that the EPA’s Strategic

Environment Assessment Programme is already collecting data on agriculture, the

environment, and the economy, and is using a combination of several different

Environmental Valuation Methodologies to analyse them13

. The goal of Ghana’s EPA is

similar to that of MAFAP – to assign a monetary value to the costs of environmental

degradation in Ghana as a percent of GDP.

Since 2010, Ghana’s EPA has been working with a coalition of other government

agencies in the country including the Ghana Statistical Service (GSS) and the National

Development Planning Commission to gather and process data for this project, dubbed

the Cost of Environmental Degradation (CoED) within the National Natural Capital

Accounting Framework. CoED uses EVM techniques such as cost of illness (human

capital), avoided cost (averting expenditures), replacement cost, defensive/ preventive

cost, wage differentials, and maximum sustainable yield to measure the monetary costs of

mining degradation, forest depletion, fisheries depletion, environmental health damage,

and agricultural soils degradation. In the future, EPA plans to expand CoED to analyse

the sanitation sector, wildlife depletion, and air pollution14

. Many of these focus areas

will generate data directly applicable to MAFAP’s application, including forest depletion,

environmental health damage, agricultural soils degradation, sanitation, wildlife depletion,

and air pollution.

The results from the first year of the study have not yet been released to the pubic, nor

were they available for inclusion in this case study, as they are currently being vetted by

GSS before official publication. The initial results are scheduled for release later in 2013.

The CoED initiative is gaining buy-in at high levels, as it was recently mentioned in

Ghana’s 2013 national budget earlier this year. Despite governmental buy-in, funding for

the initiative, which had been provided by the Agence Française de Développement

(AFD), has since dried up so the EPA is searching for new donors and partners15

. For

13

GWU Capstone Team Interview with the Director of EPA’s Strategic Environmental

Assessment (March 7th 2013).

14 Ibid.

15 Ibid.

12

continued work on implementing the overall framework methodology in Ghana, we

recommend that MAFAP explore the possibility of partnering with the EPA.

13

BIBILIOGRAPHY

FAO. “Fertilizer Use by Crop.” FAO Fertilizer and Plant Nutrition Bulletin. Accessed

May 6, 2013. ftp://ftp.fao.org/agl/agll/docs/fpnb17.pdf

FAOSTAT. Data retrieved February 6, 2013 http://faostat.fao.org/

GOPDC Ltd, http://www.gopdc-ltd.com/

KPMG, “Doing Business in Ghana.” July 2012.

http://www.kpmg.com/GH/en/Documents/Doing%20business%20in%20Ghana%

20-2012.pdf

MASDAR. “Master Study on the Oil Palm Industry in Ghana.” Hampshire, UK. 2011.

https://docs.google.com/open?id=0B4fn1Fz6J8K9djY5X1JIaHVyeUE

Ministry of Food and Agriculture. “Agriculture in Ghana: Facts and Figures.” Accra,

Ghana. 2009. http://foodsecurityghana.com/wp-

content/uploads/2011/03/AGRICULTURE-IN-GHANA-2009.pdf

Ministry of Food and Agriculture. “Agriculture in Ghana: Facts and Figures.” May 2011.

http://mofa.gov.gh/site/wp-content/uploads/2011/10/AGRICULTURE-IN-

GHANA-FF-2010.pdf

Okwute, Loretta Ojonoma and Isu, Nnennaya R. “The Environmental Impact of Palm Oil

Mill Effluent (POME) on Some Physico-chemical Parameters and Total Aerobic

Bioload of Soil at a Dump Site in Anyigba, Kogi State, Nigeria.” African Journal

of Agricultural Research Vol. 2 (12). 2007.

http://www.academicjournals.org/ajar/pdf/Pdf2007/Dec/Ojonoma%20and%20Nn

ennaya.pdf

Rupani, Parveen Fatemeh, Rajeev Pratap Singh, M. Hakimi Ibrahim and Norizan Esa.

“Review of Current Palm Oil Mill Effluent (POME) Treatment Methods:

Vermicomposting as a Sustainable Practice.” World Applied Sciences Journal 11

(1). 2010. http://www.idosi.org/wasj/wasj11(1)10/12.pdf

WWF International. “The Palm Oil Financing Handbook.” Gland, Switzerland. 2008.

http://assets.panda.org/downloads/the_palmoil_financing_handbook.pdf

14

APPENDIX: Interviewee Information

Date Organisation Interviewee Title Comments

2013.03.04

Accra, Ghana Green Earth Organization Director

2013.03.05

Accra, Ghana

Ghana Ministry of Food and

Agriculture, Department of Crop

Services, Land and Water

Management Unit, Ghana

Environmental Resource

Management Project

Environmental Resource

Management Project Head;

Focus group with 3 participants Scientist, Plant Protection and

Regulatory Services Directorate;

Scientist, Animal Production

Directorate

2013.03.05

Accra, Ghana Third World Network

Analyst, Mining and

Development Department

2013.03.06

Accra, Ghana

UN Food and Agriculture

Organization, Sub-Regional Office

for West Africa and FAO

Representation in Ghana

Deputy Regional Representative

for Africa/ Officer in Charge for

West Africa

2013.03.07

Accra, Ghana

Ghana Environmental Protection

Agency

Director, Strategic Environment

Assessment;

Focus group with 3 participants Agriculture issues analyst,

Natural Resources Department;

Agricultural Economist

15

Date Organisation Interviewee Title Comments

2013.03.11

Kade, Eastern

Region, Ghana

CSIR-Oil Palm Research Institute

Oil Palm Research Programme

Coordinator;

Focus group with 5 participants Oil Palm/ Coconut Pathologist;

Agronomist;

Agronomist/ Soil Scientist;

Socio-Economist

2013.03.12

Subi, Eastern Region,

Ghana

artisanal palm oil processing mill at

Subi Processor

Small-Scale Artisanal Palm Oil

Processing Operation

2013.03.12

Subi, Eastern Region,

Ghana

Oro Oil Ghana LTD. General Manager Medium-Scale Mechanised Palm

Oil Processing Operation

2013.03.12

Kade, Eastern

Region, Ghana

Ministry of Food and Agriculture,

Kade Region Agriculture extension agents

Focus group with approximately

30 participants

2013.03.13

Yankumase, Eastern

Region, Ghana

Yankumase Small holder oil palm farmers Focus group with 9 participants