Forestry residue

 A global downturn in the demand for paper has resulted in the timber and pulp industry scaling back production. Causing the forestry industry to restructure and diversify its business operations, by tapping into non-traditional markets. 

This case study investigates the potential for forestry residue  (stalk, bark, stemwood) to produce bioenergy in Mpumalanga and KwaZulu-Natal Midlands.

 Authors: Caroline Mfopa, Marc Pienaar

Overview

South Africa’s forestry environment is a tapestry of commercial wood plantations or tree farms interwoven with natural areas of unplanted land to promote and protect biodiversity, grasslands, wetlands, and indigenous forests. South Africa has one of the highest levels of forest certification in the world, with the Forest Stewardship Council (FSC) certifying over 80% of the country’s wood plantations.

South Africa is forested with 1.3 million hectares of plantations (which is 1% of the country’s total surface area). In arid regions, some forestry plantations are found on the banks of rivers or within protected valleys. These forests are scattered eastwards from the Cape Peninsula through to the Tsitsikama Mountains and the coast of the Eastern Cape, and into KwaZulu-Natal. Northwards of the country, forests are distributed along Drakensburg Mountains and KwaZulu-Natal. The ownership pattern of South Africa’s forests is dominated by privately owned enterprises which account for 79.7%  of forestry plantations nationwide.  Private industry forestry owners include large corporations, small-scale growers, and medium-scale growers. Only 18% of farms are owned by the government and public sector through the Department of Agriculture Forestry and Fisheries (DAFF) and other government agencies. 

Forestry residue production occurs during forest harvesting and silvicultural activities/operations. Forest residues are a source of lignocellulose biomass. The South African pulp and timber industry has undergone restructuring in recent years. This restructuring and diversification of the industry can be steered towards bioenergy development utilizing forestry waste, considering that in South Africa, thinning and plantation waste can be utilized as early as four years after planting (Bowd et. al, 2018). One of the key aspects in dealing with implementing a new form of energy within communities is to assess the current energy utility price in these communities and compare it to the price of bioenergy products to make it competitive within the energy market.

This case study explores the techno-economic feasibility of commercially harvested forestry residue as a prospective bio-resource for generating modern energy products such as pellets, wood chips, biogas, and electricity from forestry waste. This case study centers around the ability of woody biomass residue to generate electricity in Mpumalanga and Kwa-Zulu Natal; which are our optimal biomass production  locations for forestry residue.

Available biomass feedstock

  • South Africa forestry information dashboard
  • Commercial forestry residue dashboard

Forestry residue to bioenergy

Ethanol production from sugarcane

This case study focuses on second-generation (2G) bioethanol facilities that would process lignocellulose from the leaf material and bagasse to produce bioethanol. A summary of 2G ethanol production from lignocellulosic biomass involves the following steps (Pereira et al., 2015):

(1) Pre-treatment to liberate cellulose by removing lignin or hemicellulose.

(2) Depolymerisation of carbohydrate polymers to produce free sugars by cellulase-mediated action.

(3)Fermentation of hexose and/or pentose sugars for ethanol production.

(4) Distillation of the ethanol.

The are several process technologies that are used to convert lignocellulose into ethanol. The associated table summarises the process conversion technologies and bioenergy output.

alexander-schimmeck-PSOXTEIYKeo-unsplash
Process technology Conversion technology Bioenergy output

Fermentation

Ethanol
Gasification
Diesel and gasoline
Fermentation
Ethanol
Gasification
Gasoline
Pyrolysis
Gasoline and diesel
Pyrolysis
Transport fuels
Pyrolysis
Transport fuels
Catalytic Conversion
Ethanol
Hydrocracking
Natural gas, diesel, aviatior

Techno-economic feasibility analysis

The techno-economic feasibility analysis for this case study determined optimal locations in Kwa-Zulu Natal province to place an ethanol or transport fuel-producing facility. The site allocation of the facility is based on the distribution and volumes of available feedstock.

The modeling process consisted of generating service regions for candidate facility locations, followed by ranking the sites based on the relative transport costs required for each candidate facility. Data regarding the number of facilities and the transport costs and distances per modeled facility location are presented below as cost summaries, transport distances, and facility spatial information.

Cost comparison per facility type

Comparisons of the unit cost of production for each technology and facility capacity used in this case study are presented below. A comparison between processing facility product output (ethanol and transport fuels) is shown between the two different feedstocks (bagasse and brown leaves). In each category tab, a unit cost of production is given per harvested tonne and processed tonne (left), and the corresponding cost/unit output (right) and the competitor range. All values are given in 2019 Rand equivalents. The competitor prices for ethanol come from the U.S. Grains Council 2019 ethanol cost reports (https://grains.org/ethanol_report/) and represent 2019 Rands equivalent costs for the Gulf, Pacific Northwest, and Brazil (the largest ethanol producers in the world combined). The competitor prices for transport fuels represent a range of fuel prices for petrol and diesel in 2019 Rand equivalents from the Department of Mineral Resources and Energy(http://www.energy.gov.za/files/media/Petroleum_Products.html)

In each figure, production costs (left) are the total costs estimated from the model and include the Capex and Opex of the conversion facility, as well as the transport costs and loading costs from feedstock locations to conversion facility (a more detailed costing of each category is given further down). Here, the production cost per processed tonne is dependent on the conversion efficiency of the processing technology (shown on the right-hand axis in the top row). The top row provides a more detailed comparison, while a range summary (per technology) is presented below.

In general, brown leaves have slightly higher expenses, mainly due to additional transport requirements from the sugarcane fields to a conversion facility. In both cases (bagasse and brown leaves), the cost of producing ethanol for these conversion technologies is much higher than the competitor range. The same is true for transport fuels, except for Hydropyrolysis (HPy) within the competitor range. Note that there was not enough brown leaves feedstock to meet some of the processing technologies capacity requirements for transport fuels.

Midlands

  • Forestry residue biogas
  • Forestry residue electricity
  • Forestry residue wood pellets
  • Forestry residue woodchips


 



Mpumalanga South

  • Forestry residue biogas
  • Forestry residue electricity
  • Forestry residue wood pellets
  • Forestry residue woodchips

Mpumalanga North

  • Forestry residue biogas
  • Forestry residue electricity
  • Forestry residue wood pellets
  • Forestry residue woodchips

Cost summaries per facility type

The charts below present detailed production costs for each conversion technology according to various cost categories (Capex, Opex, load costs, unloading costs, and transportation costs). The charts also present the costs per scenario (lifetime, average, and present value in 2019 Rands) in the top row and per facility in the bottom row. The total Rand value is given on the right-hand axis of each chart, with the cheapest production cost highlighted in bold.

Midlands

  • Forestry residue biogas
  • Forestry residue electricity
  • Forestry residue wood pellets
  • Forestry residue woodchips

Mpumalanga South

  • Forestry residue biogas
  • Forestry residue electricity
  • Forestry residue wood pellets
  • Forestry residue woodchips

Mpumalanga North

  • Forestry residue biogas
  • Forestry residue electricity
  • Forestry residue wood pellets
  • Forestry residue woodchips

 

 




Transport summaries per facility type

The transportation summaries below give details on the transportation requirements for each conversion technology. On the left are the ranges of distances required for each facility and transport mode (road and off-road). The mean distances per working day and year (per vehicle) are given. The total distances (for all vehicles) are summarised in the middle chart. Finally, the chart on the right provides the number of vehicles and facilities (these values are presented on the right-hand axis) for each conversion technology.

  • Biogas
  • Electricity
  • Wood pellets
  • Woodchips
  1. Midlands
  2. Mpumalanga South
  3. Mpumalanga North
  1. Midlands
  2. Mpumalanga South
  3. Mpumalanga North

 

  1. Midlands
  2. Mpumalanga South
  3. Mpumalanga North
  1. Midlands
  2. Mpumalanga South
  3. Mpumalanga North

Transport distances and facility spatial information

The figures below present a detailed summary of the transportation distances for each of the conversion technologies used in this case study, along with the location and routes from each feedstock location (including their catchment area) to the conversion facilities in each technology option. The road type attributes in the bar chart (top) are according to the attribute fields in South Africa’s National Geo-spatial Information (NGI) 2019 road layer (http://www.ngi.gov.za). The distances are given per road type in km/y and summarised as the total road, total off-road, and total distances that need to be travelled. Additional information and model assumptions are provided in the bottom image. These include the feedstock type; the total tonnes available from the feedstock per year (the minimum); the conversion technology and its processing capacity; the total distance that needs to be travelled; the number of road and off-road vehicles required (including assumptions about their cost per km, average travel speed, load capacity, and working days per year). The legend on the map provides further information on the number of facilities required for each scenario, the number of feedstock locations (roadside depots), and the number of catchments that supply the feedstock.

Midlands

  • BIGCC 59327
  • BIGCC 103937
  • BIGCC 247459
  • CBP-Chipping 500
  • CBP-Chipping 2786
  • CBP-Chipping 70000
  • CBP-Pelleting 24000
  • CBP-Pelleting 48000
  • CBP-Pelleting 84000
  • CFP-UP 164250
  • CFP-UP 328500
  • CFP-UP 657000
  • COMB-EL 69967
  • COMB-EL 349836
  • COMB-EL 3488361
  • TORR1 19200
  • TORR1 72000
  • TORR1 288000

Mpumalanga South

  • BIGCC 59327
  • BIGCC 103937
  • BIGCC 247459
  • CBP-Chipping 500
  • CBP-Chipping 2786
  • CBP-Chipping 70000
  • CBP-Pelleting 24000
  • CBP-Pelleting 48000
  • CBP-Pelleting 84000
  • CFP-UP 164250
  • CFP-UP 328500
  • CFP-UP 657000
  • COMB-EL 69967
  • COMB-EL 349836
  • COMB-EL 3488361
  • TORR1 19200
  • TORR1 72000
  • TORR1 288000

Mpumalanga North

  • BIGCC 59327
  • BIGCC 103937
  • BIGCC 247459
  • CBP-Chipping 500
  • CBP-Chipping 2786
  • CBP-Chipping 70000
  • CBP-Pelleting 24000
  • CBP-Pelleting 48000
  • CBP-Pelleting 84000
  • CFP-UP 164250
  • CFP-UP 328500
  • CFP-UP 657000
  • COMB-EL 69967
  • COMB-EL 349836
  • COMB-EL 3488361
  • TORR1 19200
  • TORR1 72000
  • TORR1 288000

Conclusions

The spatial logistical modeling platform developed for the BioEnergy Atlas of South Africa was utilized to develop scenarios for locations where ethanol-producing facilities can be built. Model outputs include spatial logistical information such as optimal biomass transportation routes from the biomass location to the modelled facility locations as well as cost summaries which include Capex, Opex and Transport costs.The modelled cost for each proposed facility location are compared to existing product market prices, allowing the price competitiveness for each location to be determined.

Model outputs show that the production cost (R /tonne) was above the competitor range for producing ethanol from bagasse and for producing transport fuels from bagasse, Hydropyrolysis (HPy) conversion technology production cost (R/t) was the only technology that was within the competitor range. The volume of biomass feedstock available annually is sufficient to support a maximum of 28 second-generation (2G) ethanol and transport fuel production facilities. 

The results of cost comparison of production costs showed that the production cost (R /tonne) was above the competitor range for producing ethanol from bagasse and for producing transport fuels from bagasse, Hydropyrolysis (HPy) conversion technology production cost (R/t) was the only technology that was below the competitor range. 

Data

Feedstock spatial information

Download the spatial information for sugarcane mill feedstock and  Brownfield field feedstock

Download feedstock spatial data

Feasibility Analysis Results

Download the results from the feasibility analysis

Download model outputs

Resources

Bibliography

  1. Farzad, S., Mandegari, M.A., Guo, M., Haigh, KF., Shah, N., Görgens,JF. 2017, Multi-product biorefineries from lignocelluloses: a pathway to the revitalization of the sugar industry, Biotechnology Biofuels 10<https://doi.org/10.1186/s13068-017-0761-9>
  2. Pereira, S.C., Maehara, L., Machado, C.M.M. 2015, ‘2G ethanol from the whole sugarcane lignocellulosic biomass’, Biotechnology for Biofuels volume 8, Article number 44. < https://doi.org/10.1186/s13068-015-0224-0 >
  3. SA canegrowers, 2017, ‘Cheap Imports sour SA’s sweet silver lining’, viewed 4 February 2021, < https://sacanegrowers.co.za/2020/11/17/cheap-imports-sour-sas-sweet-silver-lining/ >.
  4. Sikuka, W 2019, ‘South African Sugar Industry Crushed by Not So Sweet Tax’, Global Agricultural Information Network Grain Report, Number: SA1904. Available at https://www.fas.usda.gov/data/south-africa-south-african-sugar-industry-crushed-not-so-sweet-tax .(Accessed: 3 February 2021).
  5. South African Department of Mineral Resources and Energy (2021) Energy Statistics – Petroleum Products <http://www.energy.gov.za/files/media/Petroleum_Products.html>
  6. South African Sugar Association (SASA) 2020, Sugar industry statistical information, viewed 4 February 2021, <https://sasa.org.za/facts-and-figures/>.
  7. South African Government, 2012. The National Development Plan. p.218.
  8. Unites States Grain Council (2021) ETHANOL MARKET AND PRICING DATA <https://grains.org/ethanol_report/>