Environmental Disclosures (GRI 300)

Broad indicators on management of environmental impacts, in aspects such as water, energy, emissions, materials, waste and biodiversity.

Related indicators
  • 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.

  • Areas adjacent to Conservation Units, by unit

    Related Material Themes:

    Change view:

    • wdt_ID Areas adjacent to Conservation Units, by unit, in ha 2019
      1 Bahia 109.056,68
      2 Espírito Santo 69,144.81
      3 Minas Gerais 0.00
      4 São Paulo 14,087.89
      5 Mato Grosso do Sul 1,716.82
      6 Maranhão 2,250.44
      7 Total 196,256.64
  • Areas destined for conservation in protected areas

    Related Material Themes:

    Change view:

    • wdt_ID Areas destined for conservation in protected areas, by unit, in ha 2019
      1 Bahia 2.291.18
      2 Espírito Santo 4.837.63
      3 Minas Gerais 1.709.48
      4 São Paulo 71.014.54
      5 Mato Grosso do Sul 0.00
      6 Maranhão 211.59
      7 Total 80.064,42
  • Areas undergoing restoration

    Related Material Themes:

    Change view:

    • wdt_ID Areas under restoration process per unit - 2019¹ São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Total area undergoing restoration process per unit² 54 108 458 58 678
      2 Total number of seedlings planted for restoration 390,000 49,800 9,980,000 15,200 10,435,000
      3 Size of area undergoing restoration process (km²) 115.28 6.38 202.30 1.23 325.20
      4 Size of area undergoing restoration process (hectares) 11,528.00 638.88 20,229.90 122.76 32,519.54

    1. The indicator considers the consolidated total restored up to 2019.

    2. São Paulo considers 54 areas, while Mato Grosso do Sul and Maranhão consider polygons; and Espírito Santo-Bahia, farms.

  • 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.

  • Biological oxygen demand (BOD) in effluents in industrial operations

    Related Material Themes:

    Change view:

    • wdt_ID Direct biochemical/biological oxygen demand (BOD) in effluents tons mg/L
      1 Suzano 564.87 24.00
      2 Rio Verde 9.10 25.00
      3 Limeira 162.64 9.40
      4 Jacareí 599.95 26.11
      5 Imperatriz 35.74 1.37
      6 Mucuri 284.05 6.56
      7 Aracruz 1,354.48 28.70
      8 Facepa Belém 39.90 45.50
      9 Três Lagoas 1,631.29 22.40
      10 Total 4,682.02 n/a
  • Chemical oxygen demand (COD) in effluents in industrial operations

    Related Material Themes:

    Change view:

    • wdt_ID Direct chemical oxygen demand (COD) in effluents - 2019 tons mg/L
      1 Suzano 5,027.76 215.00
      2 Rio Verde 53.00 145.00
      3 Limeira 3,619.74 209.60
      4 Jacareí 6,788.05 288.00
      5 Imperatriz 3,124.71 119.67
      6 Mucuri 10,439.62 241.10
      7 Aracruz 10,908.70 238.32
      8 Facepa Belém 63.69 71.85
      9 Três Lagoas 23,264.01 320.10
      10 Total 63,289.28 n/a
  • 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).

  • Disposal of hazardous waste by method in forestry operations

    Change view:

    • wdt_ID Disposal of hazardous waste by method, in tons - 2019 São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Reuse 3.73 0.00 0.00 0.00 3.73
      2 Recycling 49.46 23.76 0.00 27.69 100.92
      3 Composting 0.00 0.00 0.00 0.00 0.00
      4 Recovery (including energy recovery) 58.12 175.22 0.00 0.00 233.34
      5 Incineration (mass burn) 0.00 0.00 0.00 93.79 93.79
      6 Underground waste injection 0.00 0.00 0.00 0.00 0.00
      7 Landfill 0.00 0.00 937.70 0.00 937.70
      8 On-site storage 0.00 0.00 0.00 0.00 0.00
      9 Other 3.60 0.11 0.00 0.00 3.71
      10 Total 114.91 199.09 937.70 121.48 1,373.18

    Additional information:

    The disposal of hazardous waste is done directly by the organization or by third parties. In the latter case, Suzano monitors disposal to ensure that it is done in an environmentally sound manner.

  • Disposal of hazardous waste by method in industrial operations

    Change view:

    • wdt_ID Disposal of hazardous waste by method, in tons - 2019¹ Reuse Recycling Recovery (including energy recovery) Incineration (mass burn) Landfill On-site storage Other Total
      1 Suzano 0.00 0.00 0.00 0.00 0.00 0.00 153.40 153.40
      2 Rio Verde 0.00 0.00 0.00 0.00 0.00 0.00 39.69 39.69
      3 Limeira 0.00 0.00 8.91 0.00 0.00 13.70 163.80 186.41
      4 Jacareí 0.00 58.46 100.68 0.13 0.00 0.00 0.00 159.27
      5 Imperatriz 0.00 0.00 20.88 0.00 0.00 0.00 167.29 188.17
      6 Mucuri¹ 0.00 6.30 0.00 0.00 69.60 0.00 0.00 75.90
      7 Aracruz¹ 0.00 116.92 0.00 0.00 77.89 0.00 0.00 194.81
      8 Facepa Belém 0.00 0.00 0.00 0.00 0.00 0.00 36.07 36.07
      9 Facepa Fortaleza 0.00 0.00 0.00 0.00 0.00 0.00 8.55 8.55
      10 Três Lagoas¹ 55.48 11.78 158.56 0.00 8.19 0.00 0.00 234.01

    1. The hazardous waste from the Mucuri, Aracruz and Três Lagoas units was sent to duly-licensed external Class I landfills. In addition, at the Aracruz unit, oily waste is sold to companies that are duly licensed to co-process this waste.

  • Disposal of non-hazardous waste by method in forestry operations

    Change view:

    • wdt_ID Disposal of non-hazardous waste by method, in tons - 2019 São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Reuse 0.00 0.00 0.00 0.00 0.00
      2 Recycling 120.54 250.50 65.37 142.67 579.08
      3 Composting 0.00 0.00 0.00 0.00 0.00
      4 Recovery (including energy recovery) 0.00 153.72 0.00 0.00 153.72
      5 Incineration (mass burn) 0.00 0.00 0.00 0.00 0.00
      6 Underground waste injection 0.00 0.00 0.00 0.00 0.00
      7 Landfill 1.23 699.99 77.20 2.13 780.55
      8 On-site storage 0.00 0.00 0.00 0.00 0.00
      9 Other 0.00 0.00 0.00 0.00 0.00
      10 Total 121.77 1,104.21 142.57 144.80 1,513.36

    Additional information:

    The disposal of hazardous waste is done directly by the organization or by third parties. In the latter case, Suzano monitors disposal to ensure that it is done in an environmentally sound manner.

  • Disposal of non-hazardous waste by method in industrial operations

    Change view:

    • wdt_ID Disposal of non-hazardous waste by method, in tons Reuse Recycling Composting Recovery (including energy recovery) Landfill On-site storage Other Total
      1 Suzano 7,317.00 52,962.00 4,939.00 3,872.00 41,087.00 0 0 110,177.00
      2 Rio Verde 0 4,498.04 0 0 0 0 0 4,498,04
      3 Limeira 43,639.00 10,540.35 79,169.00 0 1,524.82 0 41,176.00 176,049.17
      4 Jacareí 0 79,964.14 0 0 29,809.00 0 0 109,773.14
      5 Imperatriz 28,009.79 49,052.90 0 0 86,770.96 0 0 163,833.65
      6 Mucuri 36,497.76 2,259.54 0 0 99,495.04 217,741.19 0 355,993.53
      7 Aracruz 0 65,006.26 0 0 58,491.19 0 0 123,497.45
      8 Facepa Belém 0 28 0 0 4,783.58 0 411.28 5,222.86
      9 Facepa Fortaleza 0 3.8 0 0 33.88 0 0 37.68
      10 Três Lagoas 70,144.00 36,505.12 0 128,451.00 40,270.00 0 0 275,370.12
  • 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 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).

  • Generation of hazardous waste in industrial operations

    Change view:

    • wdt_ID Generation of hazardous waste, in tons¹ 2019
      1 Suzano 153.40
      2 Rio Verde 39.69
      3 Limeira 186.41
      4 Jacareí 159.27
      5 Imperatriz 188.17
      6 Mucuri 75.90
      7 Aracruz 194.81
      8 Facepa Belém 36.07
      9 Facepa Fortaleza 8.55
      10 Três Lagoas 234.01

    1. The hazardous waste generated in the industrial units are: fluorescent lamps, batteries, medical waste, chemicals and parts and rags contaminated with oils and greases.

  • Generation of non-hazardous waste in industrial operations

    Change view:

    • wdt_ID Generation of non-hazardous waste, in tons 2019
      1 Suzano 110,177.00
      2 Rio Verde 4,498.04
      3 Limeira 176,049.17
      4 Jacareí 109,773.14
      5 Imperatriz 163,833.65
      6 Mucuri 355,993.53
      7 Aracruz 123,497.45
      8 Facepa Belém 5,222.86
      9 Facepa Fortaleza 37.68
      10 Três Lagoas 275,370.12
  • 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.

  • Location and size of operational sites owned, leased, managed in, or adjacent to, protected areas and areas of high biodiversity value outside protected areas

    Related Material Themes:

    Change view:

    • wdt_ID Location and size of operational sites owned, leased, managed in, or adjacent to, protected areas and areas of high biodiversity value outside protected areas - 2019¹ Own, leased, partnership areas, in ha Own, leased, partnership areas, in km²
      1 Within 80,064.42 800.64
      2 Adjacent 196,256.64 1,962.57

    1. In line with the concept of the indicator, Suzano adopts the buffer zone criterion to calculate adjacency. This criterion also applies to the ecological purpose of the buffer zones. In the 2012 analysis, a new definition for buffer was used for Conservation Units without a management plan. According to CONAMA Resolution No. 428, when the buffer zone is not defined in a management plan, a 3-kilometer area from the limits of the Conservation Unit is adopted. It should also be pointed out that some Conservation Units do not legally have buffer zones. We have four such cases:

    a) areas located within the boundaries of the Conservation Unit, as is the case of Fazenda São Gabriel, which is located in Núcleo Santa Virginia of the Serra do Mar State Park, in São Paulo, and others;

    b) areas within the buffer zone of the Conservation Unit, traverse included in its management plan published by decree in the form of law;

    c) areas within the 3-km range from the limits of the Conservation Unit, buffer zone in the Conservation Units that do not have their management plan published in the form of law;

    d) areas located within the 3-km range from the limits of the Conservation Unit , only when adjacent (abutting) to the Conservation Units that do not legally have buffer zones—this is the case of indigenous areas, Private Natural Heritage Reserves (RPPNs) and Environmental Protection Areas (APAs).

  • Management of water and effluents in forestry operations

    Related Material Themes:

    Context:

    The intelligent use of water is a priority in Suzano’s investments, as we understand that this is an important natural resource for the balance of our ecosystems and the continuity of our business. In this sense, we perform regular measurements of quali-quantitative parameters of the main river basins where we operate and adopt forest management technologies that favor the efficient use of water resources within these river basins, which helps us reduce the risks of water shortage in neighboring operations and communities.

    In order to better assess the effects of climate on the productivity of forests and to reduce risks in periods of water scarcity, the company has a network of 89 meteorological stations across all forest management units. The information generated is used to assess different scenarios about the impacts of climate change on our forest management and the availability of water resources. In addition, specific studies are conducted based on our Open Air Laboratories (Laboratórios a Céu Aberto), composed of a network of six flow towers (Eddy Covariance system), located in the forests in the states of São Paulo, Espírito Santo, Maranhão and Mato Grosso do Sul. This technological apparatus allows us to monitor in detail the growth of the forest and its interaction with the climate on a daily basis, enabling agile decision-making in the event of adversities.

    Also, in order to advance its processes and improve the notion that natural resources can and should be harmoniously shared with other users, Suzano has made a long-term commitment to implement specific actions in watersheds identified as critical, seeking to increase the availability of water in these locations. The assessment of supply and possible water scarcity is being conducted considering a historical series of water data, as well as environmental and social characteristics of all river basins in Suzano’s forest base. The results, to be released in 2020, will be used to prepare the baseline to gauge the evolution of the long-term goal.

  • Management of water and effluents in industrial operations

    Related Material Themes:

    Context:

    Committed to the protection of natural resources, our water management seeks greater efficiency in production processes and in new engineering projects, in addition to raising awareness among our employees on the use of water.

    In the industrial areas, we work to meet and exceed legal requirements while maintaining optimal operating conditions in the processes. To this end, we continuously monitor the control parameters, such as specific water abstraction, recirculation in processes and quality of the effluents treated. The information and data generated are reported periodically to the teams involved in implementing improvements. This is done through an integrated management system, formally communicated to state environmental agencies.

    In order to reduce water abstraction, our units work on various initiatives to raise awareness among the teams involved in managing these resources, encouraging the implementation of practical actions for recycling and reusing water and continuous process improvements through procedures, standards and technology.

    As an example of these fronts, the Mucuri unit focuses its initiatives on closing circuits, improving washing efficiency, using water from the air conditioning system, heat exchange systems and a strong environmental education process for the conscious use of this natural resource.

    In Jacareí, about 85% of the water abstracted is recirculated in the production process itself before being treated and returned to the environment. This recirculation takes place through internal reuse, such as with cooling water, condensates (steam), bleaching filtrates and white water from dryers, in addition to internal recirculations in the Water Treatment Plant (WTP).

    At the Três Lagoas unit, positive results were achieved after adjustments to the evaporative condenser, improvements in purging controls and implementation of cycle control in the cooling towers, in addition to internal water recovery at the WTP itself, with treatment and reuse of backwash water.

    Another very important action performed by Suzano in this regard is its participation in local river basin committees, to discuss the use of water together with representatives of the Government, companies and civil society. In this sense, through our local teams, we participate in the following committees:

     

    • Alto Tietê River Basin Committee (SP);
    • Rio Doce River Basin Committee (MG/ES);
    • Litoral Centro Norte River Basin Committee (ES);
    • Paraíba do Sul River Basin Committee (MG/RJ/SP);
    • Piracicaba, Capivari and Jundiaí River Basin Committee (SP).

     

    Also noteworthy is the participation in the Crisis Committee of the National Water Agency (ANA) for the Tocantins River.

    With regard to Suzano’s public commitments on this matter, in 2019, the company defined long-term goals related to the use of water resources in our operations, involving reduction in water abstraction and consumption in industrial units, as provided in “Long-term goals” of this Indicators Center (item “Water”).

  • Negative environmental impacts in the supply chain and actions taken

    Related Material Themes:

    Change view:

    • wdt_ID Suppliers identified as having negative environmental impacts¹ 2019
      1 Number of suppliers assessed 168
      2 Number of suppliers identified as having significant actual and potential negative environmental impacts. 7
      3 Number of suppliers identified as having significant actual and potential negative environmental impacts with which improvements were agreed upon as a result of assessment 5
      4 Percentage of suppliers identified as having significant actual and potential negative environmental impacts with which improvements were agreed upon as a result of assessment 71%
      5 Number of suppliers identified as having significant actual and potential negative environmental impacts with which relationships were terminated as a result of assessment 2
      6 Percentage of suppliers identified as having significant actual and potential negative environmental impacts with which relationships were terminated as a result of assessment 29%

    1. To compose the indicator, only critical suppliers were considered, i.e., suppliers of inputs and services that can generate significant impacts on quality, process performance, equipment safety and integrity, on the environment and on the health and safety of employees. The information was based on Fibria’s former database. Data from Suzano Papel e Celulose base are being mapped and will be evaluated in 2020.

    Additional information:

    The negative, actual and potential environmental impacts in the table include oil spills not addressed, lack of timely information regarding control of water/waste treatment, inadequate allocation of tires and inadequate response time to environmental events with the proper positioning.

  • New suppliers that were screened using environmental criteria

    Related Material Themes:

    Context:

    At Suzano, the process of registering and certifying new suppliers considers their scope of operation to define the criteria by which they will be analyzed. In this sense, suppliers selected based on environmental criteria are those whose activities have a direct relationship with this topic.

    In 2019, 100% of the new suppliers hired by Suzano whose scope of operation involves environmental aspects – i.e., 514 suppliers – were selected based on these criteria. This represents 26% of the total number of new suppliers hired by the company in the reporting period.

    Change view:

    • wdt_ID New suppliers that were screened using environmental criteria 2019
      1 Total number of new suppliers that were considered for hiring 1,953
      2 Total number of new suppliers that were hired using environmental criteria 514
      3 Percentage of new suppliers that were hired using environmental criteria (%) 26.32%
  • Non-compliance with environmental laws and regulations

    Related Material Themes:

    Change view:

    • wdt_ID Significant fines¹ and non-monetary sanctions for non-compliance with environmental laws and/or regulations 2019
      1 Total monetary value of significant fines paid in the period (R$) R$ 374,683.34
      2 Total monetary value of significant fines that are outstanding (R$) R$ 6,009,029.94
      3 Total number of non-monetary sanctions 1
      4 Total number of cases resolved through dispute mechanisms 0

    1. We consider significant fines to be those equal to or greater than US$ 10,000.00.

    Additional information:

    The fines were imposed for alleged non-compliance with legislation/regulation, under discussion by the company. The cases involve various topics, such as performing polluting activities or construction work without permits.

    As a practice, to avoid new occurrences, the company evaluates the infractions and, if applicable, makes the necessary adjustments in each case.

  • 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.

  • Protected habitats, by type

    Related Material Themes:

    Change view:

    • wdt_ID Protected habitats, by type, in ha¹ 2019
      1 Atlantic Rainforest 342,980
      2 Cerrado 307,612
      3 Mangrove 790
      4 Restinga 9,939
      5 Amazon 237,167
      6 Total 898,487

    1. The current biome and vegetation base established by the Brazilian Institute of Geography and Statistics (IBGE) was used for intersection of Suzano’s classes of vegetation. In this way, the Cerrado and Mangue classifications were readjusted. Moreover, the numbers used to compose this indicator were taken from the geoprocessing base of January 2020 (after unification of the systems) and, therefore, total conservation areas differs slightly from the total reported in the indicator “”Total area maintained by Suzano by type of land use“(base December 2019).

  • Protected habitats, by type and unit

    Related Material Themes:

    Change view:

    • wdt_ID Protected habitats, by type and forestry unit, in ha - 2019¹ Aracruz/Mucuri² São Paulo³ Três Lagoas⁴ Imperatriz⁵ Total
      1 Atlantic Rainforest 260,141 79,243 3,596 - 342,980
      2 Cerrado 908 36,058 130,989 139,657 307,612
      3 Mangrove 790 - - - 790
      4 Restinga 9,939 - - - 9,939
      5 Amazon - - - 237,167 237,167
      6 Total 271,777 115,301 134,585 376,823 898,487

    1. To compose this indicator, the current IBGE base of biomes and types of vegetation was used for intersection of Suzano’s classes of vegetation. In this way, the Cerrado and Mangue classifications were readjusted. In addition, the numbers used to compose this indicator were taken from the geoprocessing base of January 2020 (after unification of the systems) and, therefore, total conservation areas differs slightly from the total reported in the indicator “”Total area maintained by Suzano by type of land use“(base December 2019).
    2. The Aracruz/Mucuri unit includes areas in the States of Bahia, Espírito Santo and Minas Gerais.
    3. The São Paulo unit includes areas in the States of São Paulo, Minas Gerais and Rio de Janeiro.
    4. The Três Lagoas unit includes only areas in the State of Mato Grosso do Sul.
    5. The Imperatriz unit includes areas in the States of Maranhão, Piauí, Pará and Tocantins.

  • Significant impacts of activities, products, and services on biodiversity

    Related Material Themes:

    Context:

    Biodiversity conservation is an integral part of our forest management model. Currently, almost 40% of our forest base is set aside for conservation purposes, with different types of ecosystems located alongside rivers and among eucalyptus plantations, forming a mosaic landscape, with fragments of native vegetation interconnected by ecological corridors that help maintaining biodiversity in our areas.

    Suzano’s forestry activities follow its Forest Management Plan (FMP), a document that systematically describes the company’s forestry operations and the resources available to carry them out, as well as the practices and procedures adopted to sustainably achieve short, medium and long term management goals.

    In this sense, the construction and maintenance of roads and firebreaks, planting and maintenance of eucalyptus in areas of commercial planting, seedling production, forest harvesting, wood transport, and other support activities, including forest restoration and environmental monitoring, are part of forest management. All of these activities are subject to assessment through the Environmental Aspects and Impacts matrix and are audited annually by independent bodies, in order to comply with highly recognized certification mechanisms, which ensure that our forest management is environmentally correct and socially fair, besides being economically viable.

    Among the main aspects of forestry operations likely to cause impacts on biodiversity are: landscape modification, road kill of wild animals, as well as noise and accidental fires, leaks and spills that could alter wildlife and aquatic fauna, cause localized damage to the flora and temporary scaring of animals. For all negative aspects, there are defined control actions that involve awareness and training of involved parts, contractual requirements for suppliers, documented internal procedures, operational planning, socio-environmental recommendations and monitoring of biodiversity. On that basis, impacts related to fauna and flora are controlled and those considered relevant or significant are treated within the operational processes.

    On the other hand, based on our socio-environmental conduct, we also generate a positive impact in relation to maintaining biodiversity. In this sense, when we protect conservation areas and implement forest restoration where necessary, we maintain and improve the ecosystem services there, such as those for provision, regulation and support. Thus, in the monitoring of biodiversity that we carry out, we seek to acknowledge and understand the species and populations of native fauna and flora that inhabit our areas, so that we can implement measures that help protect them and favor the environmental quality of these places.

  • Size of areas with restoration process initiated per unit

    Related Material Themes:

    Change view:

    • wdt_ID Indicator São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Size of areas with restoration process started in 2019 per unit, in km² 12.89 1.10 14.24 0.15 28.38

    Additional information:

    The areas undergoing restoration maintained by Suzano were in different stages of the process at the end of 2019. In São Paulo, the areas are in the process of regeneration, following best conservation practices. In Mato Grosso do Sul, all areas in question are in the process of being restored, needing to meet the monitoring and maintenance schedule. In the states of Espírito Santo and Bahia, since there are numerous polygons (monitored according to two different methodologies), it is not possible to present the status in a descriptive form. Program indicators are monitored on a monthly basis, while ecological monitoring is conducted every two years. In the state of Maranhão, all areas are in the process of being restored, in very early stages.

    Some units are studying partnerships with third parties to restore certain areas of special interest. In São Paulo, for example, the Social and Environmental Development of the Forest Landscape Project is being developed, and eventual partnerships are also being made with the Serra do Mar State Park. The Espírito Santo and Bahia Forestry Unit has a Program called Nascentes do Mucuri, which promotes efforts in environmental education and qualification of local producers for the consolidation of a culture of preservation, fostering the design and consolidation of public policies and strategic partnerships to stimulate the entire chain involved in the process, in addition to the restoration of approximately 2,500 springs.

     

  • Total areas for development by type of land use

    Related Material Themes:

    Change view:

    • wdt_ID Total areas for development by type of land use, in hectares 2019
      1 Forest and available 133,538.70
      2 Areas for conservation 0.00
      3 Infrastructure 0.00
      4 Total 133,538.70
  • Total areas maintained by Suzano by type of land use

    Related Material Themes:

    Change view:

    • wdt_ID Total areas maintained by Suzano by type of land use, in hectares - 2019 Company areas Leased areas and partnerships Total
      1 Forest and available 699,128.50 576,187.11 1,275,315.61
      2 Areas for conservation¹ 481,042.86 405,757.96 886,800.82
      3 Infrastructure 57,066.40 47,331.71 104,398.11
      4 Total 1,237,237.76 1,029,276.78 2,266,514.54

    1. The numbers used to compose this indicator were taken from the December 2019 geoprocessing base and, therefore, the total value of areas set aside for conservation differs slightly from the number reported in the indicator “Protected habitats, by type and by unit” (base January 2020).

  • 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).

  • Total number of IUCN Red List species and national conservation list species with habitats in areas affected by operations, per biome

    Related Material Themes:

    Change view:

    • wdt_ID IUCN Red List species with habitats in areas affected by operations, per biome - 2019¹ São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Atlantic Rainforest 27 369 190 0 586
      2 Atlantic Rainforest/Cerrado 13 0 0 0 13
      3 Cerrado 0 27 0 6 33
      4 Amazon 0 0 0 39 39

    1. The Espírito Santo-Bahia and Maranhão units do not differentiate the species identified in the monitoring in near threatened (NT) or less concern (LC), since it is understood that it is the results of the categories with conservation status that contribute significantly to the critical analysis of monitoring.

  • Total number of IUCN Red List species and national conservation list species with habitats in areas affected by the operations of the organization, by level of extinction risk

    Related Material Themes:

    Change view:

    • wdt_ID Species included with habitats in areas affected by the operations of the organization, by level of extinction risk - 2019¹ São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Extinct (EX) 0 0 1 0 1
      2 Extinct in the Wild (EW) 0 0 0 0 0
      3 Critically at risk (CR) 0 0 19 2 21
      4 Endangered (EN) 2 1 55 8 66
      5 Vulnerable (VU) 11 14 115 30 170
      6 Near threatened (NT) 21 7 n/a n/a 28
      7 Least concern (LC) 6 374 n/a n/a 380

    1. The Espírito Santo-Bahia and Maranhão units do not differentiate the species identified in the monitoring in near threatened (NT) or less concern (LC), since it is understood that it is the results of the categories with conservation status that contribute significantly to the critical analysis of monitoring.

  • Total waste sent to landfill cell in industrial operations

    Change view:

    • wdt_ID Total waste sent to landfill cel in industrial operations, in tons¹ 2019
      1 Suzano 41,087.00
      2 Rio Verde 0.00
      3 Limeira 1,524.82
      4 Jacareí 29,809.00
      5 Imperatriz 86,770.96
      6 Mucuri 99,564.64
      7 Aracruz 58,569.08
      8 Facepa Belém 4,783.58
      9 Facepa Fortaleza 33.88
      10 Três Lagoas 40,278.19

    1. The indicator includes hazardous and non-hazardous waste.

  • Waste sent to landfill cell in industrial operations

    Change view:

    • wdt_ID Waste sent to landfill cell, in kg/ton on a dry basis 2019
      1 Suzano 33.00
      2 Rio Verde 0.00
      3 Limeira 0.00
      4 Jacareí 13.14
      5 Imperatriz 75.26
      6 Mucuri 45.80
      7 Aracruz 34.96
      8 Facepa Belém 120.00
      9 Facepa Fortaleza 8.90
      10 Três Lagoas 12.60
  • Water consumption in industrial operations

    Related Material Themes:

    Change view:

    • wdt_ID Water consumption, in m³ ¹ 2019
      1 Suzano 5,708,831.38
      2 Rio Verde 173,991.08
      3 Limeira 6,214,478.99
      4 Jacareí 2,644,595.99
      5 Imperatriz 5,344,902.75
      6 Mucuri 5,755,619.51
      7 Aracruz 8,819,978.32
      8 Facepa Belém 345,397.43
      9 Três Lagoas 9,336,635.66
      10 Total 44,344,431.11

    1. Water consumption is understood as the difference between the volume of water withdrawn by the units and the volume of water returned to the environment within the environmental parameters of the current legislation.

  • Water discharge (effluent discharge) in industrial operations

    Related Material Themes:

    Change view:

    • wdt_ID Total water discharge by source, in m³ 2019
      1 Suzano 23,375,767.30
      2 Rio Verde 369,261.92
      3 Limeira 17,150,715.54
      4 Jacareí 22,403,901.54
      5 Imperatriz 26,111,517.25
      6 Mucuri 43,300,529.49
      7 Aracruz 44,943,674.40
      8 Facepa Belém 886,424.99
      9 Três Lagoas 70,792,524.00
      10 Total 249,334,316.43
  • Water withdrawal by source in forestry operations

    Related Material Themes:

    Change view:

    • wdt_ID Water withdrawal by source, in m³ - 2019¹ São Paulo Mato Grosso do Sul Espírito Santo-Bahia Maranhão Total
      1 Surface waters, including wetlands, rivers, lakes and oceans 207,549.00 1,082,185.00 245,323.29 194,782.80 1,729,840.09
      2 Groundwater/water tables 6,823.00 0.00 0.00 14,621.00 21,444.00
      3 Total 214,372.00 1,082,185.00 245,323.29 209,403.80 1,751,284.09

    1. Suzano’s forestry operations do not withdraw from seawater sources, water produced and water from third parties. All water withdrawn is freshwater (≤ 1,000 mg/L of total dissolved solids).

    Additional information:

    Concepts/glossary:

    Groundwater: water that is being held in, and that can be recovered from, an underground formation.

    Produced water: water that enters an organization’s boundary as a result of extraction (e.g., crude oil), processing (e.g., sugar cane crushing), or use of any raw material, and has to consequently be managed by the organization. This definition is based on CDP, CDP Water Security Reporting Guidance, 2018.

    Surface water: water that occurs naturally on the Earth’s surface in ice sheets, ice caps, glaciers, icebergs, bogs, ponds, lakes, rivers, and streams. For this disclosure, it includes water from the oceans.

    Third-party water: municipal water suppliers and municipal wastewater treatment plants, public or private utilities, and other organizations involved in the provision, transport, treatment, disposal, or use of water and effluent.

     

  • Water withdrawal by source in industrial operations

    Related Material Themes:

    Change view:

    • wdt_ID Water withdrawal by source, in m³ - 2019¹ Surface waters, including wetlands, rivers, lakes and oceans Groundwater/water tables Total
      1 Suzano 29,084,598.68 0.00 29,084,598.68
      2 Rio Verde 543,253.00 0.00 543,253.00
      3 Limeira² 23,365,194.53 0.00 23,365,194.53
      4 Jacareí 25,048,497.53 0.00 25,048,497.53
      5 Imperatriz 31,451,602.45 0.00 31,451,602.45
      6 Mucuri 49,056,149.00 0.00 49,056,149.00
      7 Aracruz³ 53,763,652.72 0.00 53,763,652.72
      8 Facepa Belém 0.00 1,231,822.42 1,231,822.42
      9 Três Lagoas 80,125,244.66 3,915.00 80,129,159.66
      10 Total 292,438,192.57 1,235,737.42 293,673,929.99

    1. Most of the water withdrawn at Suzano units comes from sources of fresh surface water, except Facepa Belém, which only withdraws water from an underground source, and Três Lagoas, where a small portion of the water is withdrawn from this type of source.

    2. At the Limeira unit, the volume of water withdrawn from underground wells for human consumption was not considered. Only the volume of water that goes into the industrial process was considered.

    3. At the Aracruz unit, water is withdrawn from the Mãe Boa and Santa Joana reservoirs.

    Additional information:

    Concepts/glossary:

    Groundwater: water that is being held in, and that can be recovered from, an underground formation.

    Produced water: water that enters an organization’s boundary as a result of extraction (e.g., crude oil), processing (e.g., sugar cane crushing), or use of any raw material, and has to consequently be managed by the organization. This definition is based on CDP, CDP Water Security Reporting Guidance, 2018.

    Surface water: water that occurs naturally on the Earth’s surface in ice sheets, ice caps, glaciers, icebergs, bogs, ponds, lakes, rivers, and streams. For this disclosure, it includes water from the oceans.

    Third-party water: municipal water suppliers and municipal wastewater treatment plants, public or private utilities, and other organizations involved in the provision, transport, treatment, disposal, or use of water and effluent.