Biomethane potential over diesel sold, in energy, across São Paulo’s municipalities

Português · English

Plate No. 112, the second of five in the collection Bioenergy, crossed; the previous one is plate 111; the next, plate 113.

The collection crosses São Paulo’s bioenergy with what filling stations sell, with the countryside and with town halls, across the state’s 645 municipalities. The pairs came from a correlation screen between CP2B biomethane potential, fuel sales in the SEMIL Yearbook, plantation forestry, the cattle herd, the Agricultural Census, the vehicle fleet and MUNIC. Each pair went through raw and partial rank correlation (net of urbanisation, density and income), an effective sample corrected for spatial autocorrelation, Benjamini–Hochberg q values and bivariate LISA. The last plate is descriptive, with no test, and the text says so.

The map’s callouts point to Sertãozinho, where the potential would cover 135% of the diesel sold; Presidente Prudente, a city selling a lot of diesel (ratio 0.20) in an intermediate region that reaches 125%; and São Paulo, at 3%.

What the files contain

Layer (GPKG)	Geometry	Content
municipios	polygon	645 municipalities with cane and ethanol, biomethane and diesel, the fleet, native cover and pulpwood, cattle and organic fertiliser, distances to the pipeline, piped gas and the MUNIC answers on waste; classes b111, b113, b114, arranjo115 and clusters lisa111, lisa113, lisa114
gasodutos	line	transmission pipelines and distribution network (tipo)
regioes_intermediarias, limite_estadual	polygon	reference

The GPKG is the same for all five plates and carries a QGIS style for each. The CSV has the municipal table, without geometry. Empty fields are missing data, not zero. LISA clusters come as AA (high-high), BB (low-low), AB, BA and ns (not significant); the first letter is the municipality’s variable, the second its neighbours’.

Method

1. biometano_m3d: CP2B biomethane potential, v5.1, level N4 (accessible), reference scenario, in m³ a day (the same as plates 055 to 059).
2. diesel_l: litres of diesel oil sold in the municipality in 2024 (SEMIL/SP, Municipal Energy Yearbook 2025).
3. cobertura_diesel = biometano_m3d × 365 × 0.98 ÷ diesel_l. The factor of 0.98 L of diesel per m³ of biomethane equates their energy (lower heating value). Classes: under 0.1 (169); 0.1 to 0.25 (47); 0.25 to 0.5 (53); 0.5 to 1 (74); 1 to 2 (97); 2 or more (203); 2 with no diesel sales (Anhumas and Redenção da Serra).
4. By intermediate region: Presidente Prudente 125%; Araçatuba 108%; Ribeirão Preto 104%; Bauru 93%; Marília 93%; São José do Rio Preto 91%; Araraquara 72%; Sorocaba 29%; Campinas 23%; São Paulo 2%; São José dos Campos 2%.
5. caminhoes and onibus: lorries and tractor units, buses and minibuses registered in the municipality (SENATRAN, December 2025); the state has 978,415 lorries. Biomethane (log) × lorries per thousand people: Spearman rank correlation 0.35 (645 municipalities), partial 0.39, effective sample 522, p < 0.001, q < 0.001; biomethane × diesel per head: Spearman rank correlation 0.40 (644 municipalities), partial 0.35, effective sample 619, p < 0.001, q < 0.001; jobs at mills × diesel per head: Spearman rank correlation 0.43 (644 municipalities), partial 0.41, effective sample 643, p < 0.001, q < 0.001.
6. Partial correlation: the correlation between the residuals of each variable’s ranks regressed on the ranks of the controls, which are urbanisation (residents in urban areas), log of population density and log of income per head (2022 Census). Effective sample under spatial autocorrelation: n·(1 − Iₓ·Iᵧ)/(1 + Iₓ·Iᵧ), where Iₓ and Iᵧ are the Moran’s I of the residuals over a 6-nearest-neighbour neighbourhood; Benjamini–Hochberg q values across all pairs in the screen. Bivariate LISA: the municipality’s value against the mean of its 6 neighbours on the other variable, 999 permutations, seed 20261019, p < 0.05.

Limitations

• CP2B is a model: the potential estimates what residues would yield at level N4 (accessible, after collection, competing uses, storage and haulage), not biomethane actually produced.
• Sales are not consumption: the SEMIL Yearbook counts what filling stations and distributors sell in the municipality, including to people just driving through or to fleets based elsewhere. Towns on busy highways may sell far more diesel than they use.
• The ratio compares energy; it does not say biomethane would reach the state’s 978,415 lorries, which need gas engines or conversion kits, filling stations and logistics. Biomethane also has competing uses: grid injection, industry and power generation.
• Ecological reading: the map compares municipalities, not people or farms. A correlation between municipalities does not say that the same farms or drivers have both traits, nor that one causes the other.