globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2239
论文题名:
Payback time for soil carbon and sugar-cane ethanol
作者: Francisco F. C. Mello
刊名: Nature Climate Change
ISSN: 1758-1275X
EISSN: 1758-7395
出版年: 2014-06-08
卷: Volume:4, 页码:Pages:605;609 (2014)
语种: 英语
英文关键词: Environmental sciences
英文摘要:

The effects of land-use change (LUC) on soil carbon (C) balance has to be taken into account in calculating the CO2 savings attributed to bioenergy crops1, 2, 3. There have been few direct field measurements that quantify the effects of LUC on soil C for the most common land-use transitions into sugar cane in Brazil, the world’s largest producer 1, 2, 3. We quantified the C balance for LUC as a net loss (carbon debt) or net gain (carbon credit) in soil C for sugar-cane expansion in Brazil. We sampled 135 field sites to 1 m depth, representing three major LUC scenarios. Our results demonstrate that soil C stocks decrease following LUC from native vegetation and pastures, and increase where cropland is converted to sugar cane. The payback time for the soil C debt was eight years for native vegetation and two to three years for pastures. With an increasing need for biofuels and the potential for Brazil to help meet global demand4, our results will be invaluable for guiding expansion policies of sugar-cane production towards greater sustainability.

Energy crops have expanded significantly in Brazil during recent years. Between 2000 and 2012, nearly 5 Mha of sugar cane were added, bringing the current total to 9.7 Mha (ref. 5), half of which is used for the production of energy. This expansion has made sugar cane the main source of renewable energy in Brazil6.

However, the full impact of sugar cane on greenhouse gas (GHG) emissions requires that the effects of converting land to sugar cane also be considered. Several studies indicate that energy crop expansion may result in a carbon debt1, 2, 3 due to significant carbon losses as CO2, promoted by activities such as slash and burn of native vegetation7 or by the accelerated decomposition of soil organic matter (SOM) due primarily to the disturbance of the soil structure or reduced inputs8.

The replacement of degraded lands with low soil carbon (C) stocks, with high productivity energy crops, may reduce the payback period of the C debt incurred from land-use change (LUC), or even eliminate the payback1, 2, 3, resulting in a positive soil carbon balance or a biofuel carbon credit. Gains in soil C could be achieved with proper soil management and high rates of organic matter input from plant residues, allowing soils to contribute to GHG mitigation of biofuel-related land use and LUC9, 10.

Brazilian sugar-cane production is concentrated in the south-central region of the country, comprising almost 90% of the national production11. In terms of LUC to sugar cane, there are indications that more than 95% of recent expansion has been from pasture (~70%), grain crops (~25%) and citrus (~1%; refs 12, 13). The conversion of natural vegetation into sugar cane has occurred in the past, but represents less than 1% of the expansion in this area from 2000 to 200913.

Here we investigate the effect of LUC on soil C stocks and calculate the carbon payback time for sugar-cane ethanol production in Brazil. Measurements from 135 study sites, forming 75 comparison pairs (CP), and ~6,000 soil samples in south-central Brazil were analysed, for three types of land use conversion into sugar cane from: native vegetation, pastures and annual cropland. Measurements were taken for multiple soil depth increments to facilitate comparisons with previous studies, which are often restricted to surface layers (for example, 0–30 cm), but also to provide a more complete C inventory encompassing the near full depth of rooting (for example, 0–100 cm).

Measurements for the 75 CP were distributed across 13 regions in south-central Brazil (Fig. 1). The majority were areas in which sugar cane replaced pastures (57 CP) followed by conversions from annual cropland (13 CP) and cerrado (5 CP), known as Brazilian savannah. Soil C stocks were determined for each of the 75 CP for 0–30 cm, 0–50 cm and 0–100 cm depth increments (Supplementary Table 1). Soil C stock changes were calculated from response ratios, referred to as LUC factors, which represent the relative change in SOC stocks due to LUC. A response ratio equal to 1 represents no change, values <1 mean loss and values >1 mean gain. The LUC factors were derived for five-year time blocks, to coincide with sugar-cane regeneration cycles, for up to 20 years (IPCC timeframe to approximate equilibrium of soil C stocks). The LUC factors were calculated for a 20-year time span to estimate carbon debt (or credit) and payback times (Table 1).

Figure 1: Regions selected for soil sampling in south-central Brazil.
Regions selected for soil sampling in south-central Brazil.

São Paulo (SP; 1–7); Minas Gerais (MG; 8–9); Goiás (GO; 10); Mato Grosso do Sul (MS; 11); Paraná (PR; 12–13).

Detailed methods are given in the Supplementary Information. We evaluated the soil carbon stock changes due to sugar-cane expansion in the south-central part of Brazil and determined the associated C debt/credit for sugar-cane ethanol. The soil C data were used to determine LUC factors using a linear mixed effect regression30, 31 to determine C stock changes after 20 years.

Soil carbon stock changes.

Soil carbon stock changes were quantified based on the methodology outlined and recommended for national or regional GHG emissions due to LUC (ref. 20). The Tier 2 level was used to estimate soil carbon removal/inputs in south-central Brazil, for sugar-cane expansion.

Study site selection.

An extensive site selection process involved detailed interviews with professionals from the sugar-cane industry to find appropriate study areas. This selection was based on the presence of: historical land use information, available reference areas (pasture, annual cropping or natural vegetation) older than 20 years with similar geomorphic characteristics (topography, soil type and so on) and adjacency to the sugar-cane sites (Supplementary Fig. 1). This assessment identified 135 areas (75 sugar-cane fields, 45 pastures, 10 cropland and 5 cerrado areas) that were suitable for soil sampling. This gave a total of 75 comparison pairs (CP)—some of the reference sites were adjacent to multiple land uses and used for comparison with multiple sugar-cane fields. This approach covered 335,000 hectares evaluated with the selection process.

Soil sampling.

Sampling was undertaken from nine pits in a 3 × 3 grid for each study site over 100 m × 100 m representing 1 hectare (Supplementary Fig. 2). Six sampling pits were sampled every 10 cm from 0 to 30 cm, and three deeper sampling pits were sampled from 0–10, 10–20, 20–30, 40–50, 70–80, 90–100 cm to determine soil carbon and bulk density. Approximately 6,000 soil samples were taken and used to evaluate the LUC impact for sugar-cane conversions.

Soil carbon determination.

Subsamples of the soil were sieved (2 mm), and ground and sieved at 150 μm for carbon determination by dry combustion. Total carbon was determined on a LECO CN elemental analyser (furnace at 1350 °C in pure oxygen).

Soil carbon stocks.

The soil C stocks were determined by multiplying the carbon content by the soil bulk density and the layer thickness. Carbon stocks were estimated for the unsampled layers using the carbon contents derived from specific regression equations (per sampled site) and the bulk density was obtained using pedotransfer functions derived specifically for each land use (Supplementary Table 3). After calculating the soil C stocks for each soil depth, the stock was calculated for the site. The soil C stocks under sugar-cane sites were corrected according to the soil mass from reference sites (Supplementary Table 1).

Land use change factor.

The dataset was analysed with a linear mixed-effect modelling approach30, 31. A mixed-effects model consists of two parts—fixed effects and random effects. Fixed-effects terms are usually the conventional linear regression part and the random effects are associated with individual experimental units drawn at random from a population. The random effects have prior distributions whereas fixed effects do not. Our response variable was the ratio of the mean soil organic carbon (SOC, expressed in Mg ha−1) observed in the sugar-cane fields and the mean SOC found in the reference areas. The LUC factors were derived in a manner consistent with the IPCC soil C method20, which is based on the integrated effect of management for the top 30 cm of the profile after 20 years following the LUC to sugar-cane fields; however, to provide more complete information, factors were also derived for deeper layers (0–50 and 0–100 cm), and with different time spans, 5, 10, 15 and 20 years. This timeline was adopted based on the rotation cycle that sugar-cane fields undergo every five years. Uncertainty was based on the prediction standard deviation of the factor value. Statistical analyses were performed using SPLUS 8.0 software.

Payback time.

The substitution of the fossil fuels with sugar-cane ethanol has the potential to reduce GHG emissions. In this case, the payback time should be the time span that the conversion of a specific land into sugar cane would need to compensate emissions due to LUC with the offset associated with the replacement of fossil fuel by sugar-cane ethanol. To calculate the sugar-cane payback time, the average stock of soil carbon was derived for pastures, cerrado and annual cropping areas using the data in Supplementary Table 1. The LUC factors (Fig. 2) were applied to soil carbon stocks for each land use and depth range. The carbon debt (Mg CO2) was calculated as the difference between the stocks found in sugar cane and the corresponding reference land use and the payback time was the ratio of C debt to the offset for sugar-cane ethanol, estimated at 9.8 Mg CO2 ha−1 (ref. 1).

  1. Fargione, J., Hill, J., Tilman, D., Polasky, S. & Hawthorne, P. Land clearing and the biofuel carbon debt. Science 319, 12351238 (2008).
  2. Lapola, D. M. et al. Indirect land-use changes can overcome carbon savings from biofuels in Brazil. Proc. Natl Acad. Sci. USA 107, 33883393 (2010).
  3. Gibbs, H. K. et al. Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology. Environ. Res. Lett. 3, 034001 (2008).
  4. Goldemberg, J., Mello, F. F. C., Cerri, C. E. P., Davies, C. A. & Cerri, C. C. Meeting the global demand for biofuels in 2021 through sustainable land use change policy. Energy Policy 69, 1418 (2014).
  5. FAO—Food and Agriculture Organization of the United Nations (FAOSTAT, 2013; http://faostat.fao.org)
  6. Brazil-Ministry of Mines and Energy—Empresa de Pesquisa Energética, Balanço Energético Nacional 2013 - Ano base 2012 (EPE Publication, 2013); https://ben.epe.gov.br/BENRelatorioFinal2013.aspx
  7. Fearnside, P. M. et al. Biomass and greenhouse-gas emissions from land-use change in Brazil’s Amazonian arc of deforestation: The states of Mato Grosso and Rondônia. Forest Ecol. Manage. 258, 19681978 (2009).
  8. Cerri, C. E. P. et al. Predicted soil organic carbon stocks and changes in the Brazilian Amazon between 2000 and 2030. Agric. Ecosyst. Environ. 122, 5872 (2007).
  9. Lal, R. Soil carbon sequestration impacts on global climate change and food security. Science 304, 16231627 (2004). URL:
http://www.nature.com/nclimate/journal/v4/n7/full/nclimate2239.html
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/5098
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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Francisco F. C. Mello. Payback time for soil carbon and sugar-cane ethanol[J]. Nature Climate Change,2014-06-08,Volume:4:Pages:605;609 (2014).
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