Climate Change

Search alternatives to increase carbon sequestration, reduce greenhouse gas emissions and contribute to the solution for the climate crisis, in addition to reducing and mitigating risks of this nature.

  • Air emissions in industrial operations

    Change view:

    • wdt_ID Air emissions, in tons NOx SOx Particulate matter (PM) Total reduced sulfur (TRS)
      1 Suzano 737.00 151.00 327.00 31.00
      2 Rio Verde¹ 25.00 n/d n/d n/d
      3 Limeira 1,158.22 922.75 557.48 9.18
      4 Jacareí 1,424,35 185,71 468,73 19.14
      5 Imperatriz 2,315.05 595.00 267.71 134.26
      6 Mucuri 2,034.87 61.02 803.00 143.00
      7 Aracruz 1,387.79 299.34 852.57 13.22
      8 Facepa Belém² 62.42 80.77 103.04 n/d
      9 Três Lagoas 4,597.86 158.23 951.02 105.21
      10 Total 13,717.56 2,453.82 4,330.55 455.01

    1. The Rio Verde unit produces only paper, i.e., there is no fiber line to produce pulp. Therefore, since there is no need, SOx, PM and TRS are not measured.

    2. At the Facepa Belém unit, TRS is not measured because there is no recovery boiler.

    Additional information:

    At the Facepa Fortaleza unit, there are no stationary emissions.

  • Biogenic CO₂ emissions (scope 1)

    Change view:

    • wdt_ID Indicator 2019
      1 Biogenic CO₂ emissions (scope 1), in t of CO₂ equivalent¹ 22,805,203.58

    1. The indicator considers the following gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs).

    Additional information:

    The following references of emission factors were used: FGV (2019), IPCC (2007), MCTIC (2016) and MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO₂e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    In 2019, we worked to consolidate the former systems and processes adopted by Suzano Papel e Celulose and Fibria in order to prepare the first Greenhouse Gas Inventory as Suzano S.A. Therefore, Therefore, aiming at continuous improvement of the process, the company is expected to increasingly improve the accuracy of the information reported. In this sense, as higher levels of accuracy are obtained, data and information reported may be adjusted over the next few years. Also, due to methodological differences, the comparison of current values with values presented in previous years by the former companies is imprecise and may only start to occur in 2021, when the comparison base for Suzano S.A. will already be unified.

    Direct biogenic emissions represented approximately 22.8 million tCO₂ equivalent. Most of these emissions are due to the use of black liquor and biomass to generate energy in industrial units (renewable sources).

  • Biogenic CO₂ emissions (scope 3)

    Change view:

    • wdt_ID Indicator 2019
      1 Biogenic CO₂ emissions (scope 3), in t of CO₂ equivalent¹ 30,489.47

    1. The indicator considers the following gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs).

    Additional information:

    The following references of emission factors were used: FGV (2019), IPCC (2007), MCTIC (2016) and MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO₂e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    Transportation and distribution emissions (both inputs and finished products) are the most representative among Suzano’s other indirect emissions (scope 3). Of these emissions, transportation from port to port, added to transportation from port to customer of the exported products, represents nearly 28%. Emissions from purchased goods and services (mainly from outsourced operations) and emissions from waste treatment are also significant.

  • Consumption of fuels from non-renewable sources

    Change view:

    • wdt_ID Consumption of fuels from non-renewable sources, in GJ 2019
      1 LPG 371,921.13
      2 Natural gas 20,943,264.27
      3 Gasoline 79,864.90
      4 Greases 59.53
      5 Lubricants 301,005.99
      6 Fossil methanol 206,021.23
      7 Heavy fuel oil 2,586,981.12
      8 Diesel - marine 313,820.00
      9 Diesel - road 3,246,443.87
      10 Total 28,049,382.05

    Additional information:

    Fuel consumption data – collected by Suzano in a mostly automated way – were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019).

  • Consumption of fuels from renewable sources

    Change view:

    • wdt_ID Consumption of fuels from renewable sources, in GJ 2019
      1 Anhydrous ethanol 29,525.42
      2 Hydrous ethanol 13,322.39
      3 Biodiesel (B100) 374,125.50
      4 Biomass 40,724,267.72
      5 Black liquor 172,730,784.12
      6 Renewable methanol 2,649,592.23
      7 Total 216,521,617.38

    Additional information:

    Fuel consumption data – collected by Suzano in a mostly automated way – were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019).

  • Direct (Scope 1) GHG emissions by unit

    Change view:

    • wdt_ID Direct (Scope 1) GHG emissions by unit, in t of CO₂ equivalent¹ 2019
      1 Offices (Headquarters and International) 991.96
      2 FuturaGene 0.19
      3 Stenfar and SPP (CDLs) 54.16
      4 Port terminals 2.61
      5 Forestry Units 138,185.99
      6 UNI Aracruz 281,110.14
      7 UNI Facepa – Belém and Fortaleza 9,107.65
      8 UNI Imperatriz 186,331.21
      9 UNI Jacareí 419,693.95
      10 UNI Limeira 145,870.62

    1. The indicator considers the following gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs).

    Additional information:

    The following references of emission factors were used: FGV (2019), IPCC (2007), MCTIC (2016) and MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO₂e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    In 2019, we worked to consolidate the former systems and processes adopted by Suzano Papel e Celulose and Fibria in order to prepare the first Greenhouse Gas Inventory as Suzano S.A. Therefore, Therefore, aiming at continuous improvement of the process, the company is expected to increasingly improve the accuracy of the information reported. In this sense, as higher levels of accuracy are obtained, data and information reported may be adjusted over the next few years. Also, due to methodological differences, the comparison of current values with values presented in previous years by the former companies is imprecise and may only start to occur in 2021, when the comparison base for Suzano S.A. will already be unified.

    Suzano’s main direct emissions (scope 1) are related to the consumption of fossil fuels in the stationary equipment at the industrial units. However, other sources of significant emissions can also be seen in forestry units, from the consumption of fossil fuels by mobile sources in forestry and harvesting operations, as well as through the use of nitrogen fertilizers and soil remediation (liming).

  • Energy consumed

    Change view:

    • wdt_ID Energy consumed, in GJ 2019
      1 Electricity 3,429,652.68 GJ
      2 Heating 0.00
      3 Cooling 0.00
      4 Steam 0.00
      5 Total 3,429,652.68 GJ

    Additional information:

    Fuel consumption data – collected by Suzano in a mostly automated way – were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019). Furthermore, the indicator includes only the value of electricity imported from the net, which means it does not consider the value of electrical energy produced internally.

  • Energy consumption outside of the organization

    Change view:

    • wdt_ID Indicator 2019
      1 Energy consumption outside of the organization, in GJ 9,214,404.36

    Additional information:

    Fuel consumption data were collected by Suzano in a mostly automated way – through data extraction via internal systems and control requests from suppliers and service providers – and were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019).

    The main sources of energy required outside the organization are related to fuel consumption for transportation and distribution of inputs and products.

  • Energy indirect (Scope 2) GHG emissions by unit

    Change view:

    • wdt_ID Energy indirect (Scope 2) GHG emissions from energy acquisition per unit, in t of CO₂ equivalent¹ 2019
      1 Offices (Headquarters and International) 58.44
      2 FuturaGene 1.52
      3 Stenfar and SPP (CDLs) 250.51
      4 Port terminals 166.44
      5 Forestry Units 121.97
      6 UNI Aracruz 3,661.91
      7 UNI Facepa – Belém and Fortaleza 2,532.78
      8 UNI Imperatriz 3,214.59
      9 UNI Jacareí 5,940.55
      10 UNI Limeira 24,985.97

    1. The indicator considers the following gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide.

    Additional information:

    The following references of emission factors were used: FGV (2019), IPCC (2007), MCTIC (2016) and MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO₂e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    Suzano’s Energy indirect (Scope 2) GHG emissions from energy acquisition occur due to the purchase of electricity from the National Interconnected System. These emissions are more representative in industrial units, especially for paper machines, which require a continuous supply of electricity.

  • Energy management in industrial operations

    Context:

    Suzano’s energy mix is mainly supported by renewable sources, such as: biomass composed of bark, logs and by-products of the wood chipping process; and liquid biomass, known as black liquor, responsible for generating the largest portion of energy. Also, some units have begun to use the energy from biological sludge in biomass boilers.

    Some production units generate surplus electricity, which is made available to the national grid (Interconnected System – SIN), contributing to the level of renewable energy in the Brazilian electricity mix.

    In this way, we reinforce the organization’s commitment to optimize its processes within the concepts of bioeconomics.

  • Energy mix

    Change view:

    • wdt_ID Breakdown of Suzano S.A.'s energy matrix¹ 2019 (%)
      1 Percentage of energy from non-renewable sources 11.65
      2 Percentage of energy from renewable sources 88.35
      3 Total 100.0

    1. Total energy consumed is calculated by adding the energy from the consumption of fuels from renewable and non-renewable sources and the energy consumed, less the total energy sold.

    Additional information:

    In 2019, we worked to consolidate the former fuel consumption measuring systems and processes used by Suzano Papel e Celulose and Fibria. Therefore, aiming at continuous improvement of the process, the company is expected to increasingly improve the accuracy of the information reported. In this sense, as higher levels of accuracy are obtained, data and information reported may be adjusted over the next few years. Also, due to methodological differences, the comparison of current values with values presented in previous years by the former companies is imprecise and may only start to occur in 2021, when the comparison base for Suzano S.A. will already be unified.

    The renewability of Suzano’s energy mix in 2019 proved to be significant, with 88.35% of its composition coming from renewable sources. The company’s main sources of renewable fuels are black liquor, biomass and methanol, all of which come from wood from sustainably planted forests. Additionally, in order to obtain our energy mix composition, it was considered that the electricity imported by the company from the public grid has 84,2% of its composition coming from renewable sources, according to a study on the Installed Capacity of Electricity Generation by the Brazilian Energy Balance (MCTIC, 2019). Furthermore, as an energy generator, Suzano exports a large amount of surplus electricity to the National Interconnected System, contributing to make the Brazilian electricity generation mix increasingly renewable.

    Fuel consumption data were collected by Suzano in a mostly automated way and were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019).

  • Energy sold

    Change view:

    • wdt_ID Energy sold, in GJ 2019
      1 Electricity 5,303,394.46
      2 Heating 0.00
      3 Cooling 0.00
      4 Steam 0.00
      5 Total 5,303,394.46

    Additional information:

    Fuel consumption data – collected by Suzano in a mostly automated way – were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019).

  • GHG emissions intensity

    Change view:

    • wdt_ID Indicator 2019
      1 GHG emissions intensity, in t of CO₂ equivalent/ton of product¹ 0.3369

    1. The indicator considers the following gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs). Moreover, it includes direct and indirect emissions (scopes 1, 2 and 3) and considers total pulp (market pulp, pulp for paper and fluff) and paper production (finished paper and tissue).

    Additional information:

    The following references of emission factors were used: FGV (2019), IPCC (2007), MCTIC (2016) and MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO₂e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    Suzano’s emission intensity in 2019 was 0.3369 (tCO2e/ton of pulp and paper), considering the company’s direct and indirect emissions (scopes 1, 2 and 3). The indicator helps to identify opportunities that provide better efficiency for Suzano’s production processes, especially with regard to reducing its emissions per ton of production.

  • Management of air emissions in industrial operations

    Context:

    In order to ensure the reduction of environmental impacts resulting from our operations, we manage our air emissions in full compliance with the legislation in force on the subject, that is, in accordance with CONAMA regulations, at national/federal levels, and with the environmental permits for the operations. In addition, the standards established by the Integrated Pollution Prevention and Control (IPPC) and the International Finance Corporation (IFC) are used internally as benchmarking scenarios and guidelines for us to optimize our management on this topic, even though the established goals are set out by a federal body. To this end, management of our emissions is continuously monitored. The data obtained are presented to regulatory agencies for each operation at the defined periodicity. In addition, data are verified in internal and external audit processes according to ISO 14001:2015.

  • Other emissions and climate change indicators

    Change view:

    • wdt_ID Other emissions and climate change indicators, in t of CO₂ equivalent - 2019¹ Suzano S.A. – planted forests Suzano S.A. – native vegetation Suzano S.A. – total
      1 Carbon stock 114,606,195.82 163,381,236.44 277,987,432.26
      2 Removals -28,826,714.24 -3,345,980.39 -32,172,694.63
      3 Balance² 0.00 0.00 -11,751,555.64

    1. Suzano’s emission values are expressed with a plus sign (+) to represent the flow of carbon to the atmosphere. Removals, as well as Suzano’s balance, are expressed with the minus sign (-) to represent carbon removals from the atmosphere.

    2. Suzano’s balance considers direct and indirect emissions (scopes 1, 2 and 3) and direct removals.

    Additional information:

    The following references of emission factors were used: FGV (2019), IPCC (2007), MCTIC (2016) and MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO2e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    In 2019, we worked to consolidate the former systems and processes adopted by Suzano Papel e Celulose and Fibria in order to prepare the first Greenhouse Gas Inventory as Suzano S.A. Therefore, Therefore, aiming at continuous improvement of the process, the company is expected to increasingly improve the accuracy of the information reported. In this sense, as higher levels of accuracy are obtained, data and information reported may be adjusted over the next few years. Also, due to methodological differences, the comparison of current values with values presented in previous years by the former companies is imprecise and may only start to occur in 2021, when the comparison base for Suzano S.A. will already be unified.

    Areas with planted forests and native vegetation contributed with direct removals of carbon from the atmosphere of 32.172 million tCO₂ equivalent. Thus, the balance between Suzano’s direct emissions and removals in 2019 was about 13.334 million tCO₂ equivalent removed. In addition, the areas with planted forests and native vegetation stored 278 million tCO₂ equivalent.

  • Other indirect (Scope 3) GHG emissions by unit

    Change view:

    • wdt_ID Other indirect (Scope 3) GHG emissions by unit, in t of CO₂ equivalent¹ 2019
      1 Offices (Headquarters and International) 1,036,603.62
      2 FuturaGene 37.39
      3 Stenfar and SPP (CDLs) 7,414.03
      4 Port terminals 2,166.61
      5 Forestry Units 162,797.70
      6 UNI Aracruz 1,575.37
      7 UNI Facepa – Belém and Fortaleza 1,619.35
      8 UNI Imperatriz 8,981.21
      9 UNI Jacareí 20,904.82
      10 UNI Limeira 14,833.42

    1. The indicator considers the following gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), Hydrofluorocarbons (HFCs ) and perfluorocarbons (PFCs).

    Additional information:

    The following references of emission factors were used: FGV (2019); IPCC (2007); MCTIC (2016); MMA (2014). The emissions of each greenhouse gas (GHG) were converted into tCO₂e by multiplying their respective Global Warming Potential (GWP – IPCC, 2007; FGV, 2019; WRI & WBCSD, 2017).

    The selection of the methodologies for quantification, data collection and use of emission factors was made based on the recommendations of the ABNT NBR ISO 14064-1 standard (ABNT, 2007). In addition, the following documents were used as a reference for preparing the company’s GHG inventory:

     

    • The Greenhouse Gas Protocol: the Corporate Accounting and Reporting Standard, WRI & WBCSD (2004);
    • guides, guidelines and calculation tools of the Brazilian GHG Protocol Program (PBGHGP) of FGV (2020);
    • 2006 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC (2006);
    • Calculation Tools for Estimating Greenhouse Gas Emissions from Pulp and Paper Mills, NCASI (2005).

     

    In accordance with the principles for preparing GHG inventories, whenever possible, measurement data and emission factors closer to the local reality were used.

    Transportation and distribution emissions (both inputs and finished products) are the most representative among Suzano’s other indirect emissions (scope 3). Of these emissions, transportation from port to port, added to transportation from port to customer of the exported products – which are contained in the Office (Headquarters and Internacional) category –, represents 28% (totalizing 1,031,345.99 tonCO2eq). Emissions from purchased goods and services (mainly from outsourced operations) and emissions from waste treatment are also significant.

  • Total energy consumed

    Change view:

    • wdt_ID Total energy consumed, in GJ¹ 2019
      1 Fuels from non-renewable sources 28,049,637.02
      2 Fuels from renewable sources 216,521,617.38
      3 Energy consumed 3,429,652.68
      4 Energy sold 5,303,394.46
      5 Total 242,697,512.61

    1. Total energy consumed is calculated by adding the energy from the consumption of fuels from renewable and non-renewable sources and the electrical energy consumed, less the total energy sold. Moreover, it is considered as electrical energy consumed only the value of energy imported from the net, which means it does not include the value of electrical energy produced internally already incorporated in the other categories, once the energy produced internally is generated mainly by the burning of biomass.

    Additional information:

    In 2019, we worked to consolidate the former fuel consumption measuring systems and processes used by Suzano Papel e Celulose and Fibria. Therefore, aiming at continuous improvement of the process, the company is expected to increasingly improve the accuracy of the information reported. In this sense, as higher levels of accuracy are obtained, data and information reported may be adjusted over the next few years. Also, due to methodological differences, the comparison of current values with values presented in previous years by the former companies is imprecise and may only start to occur in 2021, when the comparison base for Suzano S.A. will already be unified.

    The renewability of Suzano’s energy mix in 2019 proved to be significant, with 88.35% of its composition coming from renewable sources. The company’s main sources of renewable fuels are black liquor, biomass and methanol, all of which come from wood from sustainably planted forests. In addition, as an energy generator, Suzano exports a large amount of surplus electricity to the National Interconnected System, contributing to make the Brazilian electricity generation mix increasingly renewable.

    Fuel consumption data were collected by Suzano in a mostly automated way and were converted into energy consumption based on the lower basic density and calorific value of each fuel. In this sense, when available, we used data on the lower basic density and calorific value contained in the technical data sheet of the fuel used. When not available, the values presented by the National Energy Balance were used (MME, 2019).