Sugarcane residue management impact soil greenhouse gas

Impacto do manejo do resíduo de cana-de-açúcar na produção potencial de gases do efeito estufa no solo

ABSTRACT

Mechanized sugarcane harvest is replacing the historic practice of field burning, due to environmental concerns of the particulate and emissions during burning. However, the impact of these practices on soil greenhouse gas (GHG) production potential is not fully known. Thus, the present work quantified the potential production, in 1 g of soil, of greenhouse gases (GHG) in three systems of sugarcane management. The systems were: area with a history of burning sugarcane before harvest (B) and another with two systems of management of “green sugarcane” in two periods of implantation - 5 (G-5) and 10 years (G-10). A laboratory incubation experiment was used to assess the production potentials of carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) in 1g of soil samples by the different sugarcane management systems. The results of this study demonstrate that the sugarcane management systems had an impact on the potential production of CO2 in the soil. In addition, when the results of gases were divided from convex and concave areas, differences in CO2 patterns between areas B and G-10 were observed, with greater emission in the G-10 area, probably due the residue on the soil surface.

Index terms:
Sacharium officinarium; slope; CO₂; N₂O; CH₄.

RESUMO

O sistema de colheita mecanizado da cana-de-açúcar têm substituido o sistema de queima do canavial devido a preocupações ambientais como a emissão de partículas durante a queima e diversos malefícios ao solo. O impacto dessa prática no potencial de produção de gases do efeito estufa (GEE) no solo ainda demanda estudo. Assim, o presente trabalho quantificou a produção potencial, em 1 g de solo, de gases do efeito estufa em três sistemas de manejo de cana-de-açúcar. As áreas avaliadas foram: uma com histórico de queima do canavial antes da colheita (B) e outras com duas com sistemas de manejo de “cana crua” em dois períodos de implantação - 5 (G-5) e 10 anos (G-10). Um experimento de incubação em laboratório foi montado para avaliar os potenciais de produção de dióxido de carbono (CO₂), óxido nitroso (N₂O) e metano (CH₄) em de 1g de amostras de solo nos diferentes sistemas de manejo de cana-de-açúcar. Os resultados deste estudo demonstram que os sistemas de manejo de cana-de-açúcar apresentaram impacto na produção potencial de CO₂ no solo. Além disso, quando dividiu-se os resultados de gases oriundos de áreas convexas e concavas, observou-se diferenças nos padrões de CO₂ entre as áreas B e G-10, with greater emission in the G-10 area, possivelmente devido a presença de palhada na superífice do solo.

Termos para indexação:
Sacharium officinarium; declividade; CO₂; N₂O; CH₄.

INTRODUCTION

The management of crop residues has significant implications on the agronomic and economic aspects of sugarcane production. The historic technique of burning sugarcane fields prior to harvest (to facilitate cutting) was popularized in the 1940s. The temperature during sugarcane burning is around 160-200 °C at the soil surface, causing volatilization of soil nutrients such as phosphorus, sulfur and nitrogen (Britts; Silva; Abrita, 2016). It has been estimated that each 1 Mg of sugarcane burned releases 0.004 Mg of black carbon aerosols, as well as additional organic contaminants into the atmosphere (Macedo; Nogueira, 2014). This can lead to harmful human health impacts in surrounding populations (Paraiso; Gouveia, 2015). In response to these detrimental environmental effects, since 2000 (São Paulo state law number 11.241/2002), there has been a shift toward what is known as “green sugarcane harvesting”, which leaves the biomass residues in the field, thus burning should be gradually until 2021. Currently, the Sugarcane Industry Association of Brazil (UNICA) established a more aggressive target which will eliminate totally sugarcane burning in 2017 in the São Paulo state.

In addition to the direct health and climate impacts, burning also reduces the amount of plant nutrients that are returned to the soil. Not only are large quantities of organic carbon (C) are lost in the burning process, it also leads to lower soil N content, reduced microbial biomass, which can decrease yields compared to the maintenance of the crop residues in the soil surface (Souza et al., 2012). Another benefit is the decreased greenhouse gas (GHG) footprint of green harvest systems, largely from reducing the aerosol and particulate emissions (Oliveira Bordonal; Figueiredo; La Scala, 2011).

The authors have discussed the important influence of topography on soil GHG potentials, specifically CO₂, N₂O and CH₄ (Braum et al., 2013). Topographically low areas (those with a concave structure) are likely to collect surface run-off and thereby increase the amount of infiltrating moisture to the soil microbial population, resulting in higher rates of carbon mineralization and CO₂ emissions (Brito et al., 2010). Greater N₂O emissions observed in the topographically low positions have primarily been linked to higher soil moisture increasing the number of anaerobic sites and higher denitrification rates, which is directly linked to higher N₂O production (Vilain et al., 2010). Topographically high regions are thought to have higher rates of CH₄ oxidation and footslopes (low regions) are generally regions of reduced oxidation, consequently, increases CH₄ production, again due the increase soil moisture (Ball et al., 2013). Topographic research on the variability of CH₄ emissions has primarily focused on bogs (Algan et al., 2015) and landfills (Di Trapani; Di Bella; Viviani, 2013), since arable soils are more commonly CH₄ oxidizing environments (Flessa et al., 2008).

The influence of management practices on GHG emissions associated with sugarcane production has been the focus of numerous studies comparing conventional to reduced tillage (Packer et al., 2015), increasing soil organic matter (Oliveira et al., 2013), fertilizer applications (Signor; Cerri; Conant, 2013) and crop rotations (Oliveira Bordonal et al., 2013). The current studies that have examined alterations in the GHG balances have used life-cycle approaches. Converting sugarcane areas from burned to green harvest could reduce GHG emissions by 310.7 (not considering soil C sequestration) to 1484.0 kg CO₂ equiv. ha^-1 y^-1 (considering C sequestration) (Figueiredo; La Scala, 2011).

With the phase out of sugarcane burning already underway, the objective of this study was to determine the effect of sugarcane fields under conventional burning and green sugarcane systems and the influence of slope (convex and concave) on GHG production potential.

MATERIAL AND METHODS

Study area and treatments

This study focused on three areas of sugarcane cultivation to compare burn vs. green harvest management practices and was conducted on a sugarcane (Saccharum spp.) plantation, located in the municipality of Pradópolis, São Paulo state, Brazil (21.362° S; 48.07° W). Three fields were selected with a different residue management history (Table 1), but the same soil type (Latossolo Vermelho - Brazilian Classification) at three fields (Haplustox, USDA Soil Taxonomy). The regional climate is classified as B₂rB’4a’ by Thornthwaite system, indicating a mesothermal region with rainy summers and dry winters. The mean annual precipitation is approximately 1425 mm and is concentrated between October and March. The three areas presented differentiated slopes, with convex (high altitude) and concave points (low altitude) as described in Table 1.

Table 1:
Soil characterization in the three management areas of burned sugarcane (B), green sugarcane for five years (G-5) and green sugarcane for ten years (G-10).

Field Site	B	G-5	G-10
Average slope (%)	4.0	3.7	4.1
Year of conversion	--	2006	2001
	(>25 yr burned)	(5 years*)	(10 years*)
Convex area (m)	642	507	525
Concave area (m)	638	503	508
Organic carbon (g kg-1)	2.3	2.5	2.0
Cation exchange capacit (cmolc dm-3)	15.06	10.29	8.43
pH CaCl2	5.2	4.8	4.9
Phosphorus (mg dm-3)	16.66	36.3	35.55
Sulfur (mg dm-3)	0.81	0.82	0.51
Calcium (cmolc dm-3)	9.0	4.21	3.44

The burned sugarcane site (B) (slope = 4%), where plants were burned prior to harvest since the 1980s, was selected along with two green sugarcane harvest (without burn) sites; one that started the green sugarcane systems in 2006, called green sugarcane for 5 years (G-5) (slope = 3.7%) and the other cultivated green sugarcane since 2001, called green sugarcane for 10 years (G-10) (slope = 4.1%). Both G-5 and G-10 had previously used the traditional burning management practices prior to the switch to green harvesting. Besides the residue management, there were no other differences between these fields (i.e., fertilization, weed control, tillage).

To characterize spatial variability within each field, a 10,000 m² (1 ha) area was selected (100 x 100 m) and sampled with an 81-point grid was established in each field post-harvest (Figure 1). Soil samples were collected at 0-10 cm soil depths for all points on the grid to give a total of 243 individual soil samples (81 points x 3 areas). All samples were air dried outside for 1 week and sequentially stored in plastic bags.

Figure 1:
Sampling grid with 81 point spaced in 1, 2 and 10 m.

CO₂ flux measurement in field

CO₂ flux measurement in field was simultaneously performed in all areas using three chambers at all sampling grid points, during 10 days in August, 2011 at the mornings (7-11 a.m.) to standardization using soil chambers manufactured by LI-COR^® model LI-8100 (Nebraska, USA).

Soil incubation

Soil samples were then shipped to the USDA-ARS lab in Saint Paul, Minnesota (USA) for GHG production assessment. CO₂, N₂O and CH₄ production potentials were assessed through laboratory incubations using 243 soil sample (3 areas x 81 points). The incubation consisted of 1 g soil at 80% field capacity (1 cm³ of distilled water addition) in a previously oven-sterilized 25 cm³ serum vial (Wheaton Glass, Millville, NJ, USA). The soil was allowed to pre-incubate (unsealed) for a period of 24 h to avoid the irreproducible initial GHG production. The vials were then sealed with red butyl rubber septa (Grace, Deerfield, IL, USA) and analyzed on a headspace-gas chromatography GC, model 7694 (Foster City, USA) system to quantify gas production over a 3-d incubation period, which was sampled daily. This period of 3 d was selected based on initial incubations which were run for 21 d and there was no significant difference observed in the calculated GHG production rates from 3 to 21 d.

Analysis

A customized headspace-gas chromatograph system with 3 detectors (flame ionization, thermal ionization, and electron capture detector) was used (Spokas et al., 2009). Briefly, the GC system consisted of a headspace sampler that was modified to allow the injection of 3 separate gas samples unto 3 different analytical columns, which permitted the analysis of O₂, N₂, CO₂, CH₄, and N₂O, simultaneously from the same incubation. The system was calibrated against NIST traceable gas standards (Minneapolis Oxygen, Minneapolis, MN).

The total GHG impact over a 100 year time span was estimated using the emission factor proposed by IPCC for a 100 yr horizon (Myhre et al., 2014):

$${\text{Total GHG Production Impact = CO}}_2{\text{Production Potential + 298*N}}_2\text{O Production Potential +}{\text{, 25*CH}}_4\text{Production Potential}$$

where total GHG production impact is in µg CO₂ eq. g_soil ^-1d^-1.

soil microbial biomass was measured using the fumigation-extraction method (Vance; Brookes; Jenkinson, 1987), where soil moistures were adjusted to 70% field capacity and samples were incubated 24 h at 22 ^oC. Soil organic carbon and microbial C determination were performed according to the Walkey-Black method (Nelson; Sommer, 1982).

Statistics

Values of GHG production potential were the averages of triplicates runs for each soil sample. Descriptive statistics of CO₂, N₂O and CH₄ emissions were obtained with the SAS program (Version 9.4) and was used the Dunn’s test 5% to multiple comparisons among means. The results from the fields were initially compared based on local topography (convex vs. concave) within each area. Geospatial kriging was used as an interpolation method for the measured variables. The spatial variability models were derived (GS+ 9 software; Gamma Design Software, Version 9) and kriging maps were produced (Surfer; Version 9.0, Golden Software). The studied properties were submitted to one-way analysis of variance (ANOVA) and means were compared by t test at 5% probability (SAS, Version 9.4).

RESULTS AND DISCUSSION

CO₂ production and emission rates

CO₂ production rates from the different management treatments were tightly clustered, within one order of magnitude of one another. The average CO₂ production potentials of all 81 points across the treatments were 101, 105 and 148 µg C-CO₂ g soil^-1d^-1, respectively for B, G-5, and G-10 (Figure 2). The average CO₂ production rates in this study was significantly higher in the G-10 field, potentially influenced by longer term sugarcane residue being incorporated into the soil. This practice would provide higher amounts of organic carbon and stimulate microbiology activity, thus increasing soil CO₂ emissions.

Figure 2:
Total predicted average production rate of CO₂, N₂O, and CH₄ in the burned sugarcane (B), green sugarcane for 5 years (G-5), and green sugarcane for 10 years (G-10) (n: 81). Means were evaluated across the treatments, and those followed by the same letter are not statistically different (P<0.05).

We also compared field CO₂ emissions data with the laboratory production potentials (Table 2) with greater CO₂ emission in both methodology in the G-10 area. These instantaneous measurements have been well correlated to the longer term static chamber flux measurements in studies comparing different soil managment in southern Brazil (Chavez et al., 2009).

Table 2:
Comparison of field measured CO₂ emissions and comparison to the laboratory derived CO₂ production rates.

Treatments	Field measurement	Laboratory production rate
	(µg CO2 m-2s-1)	(µgC-CO2 g soil-1day-1)
B	455 b	100.9 ± 25.7 b
G-5	647 b	105.1 ± 32.0 b
G-10	791 a	148.4 ± 35.2 a

• SD: standard desviation for laboratory production rate data. Mean followed by the same letter within a column do not differ from each other by Student’s t-test at the 5% probability level.

Since the field sites were not identical (i.e., not paired blocks), results from fields were initially compared based on local slope (convex vs. concave) within each area for normalization (Table 3). When analyzing the results from convex and concave terrains the results showed different trends in each management system as a function of slope. For the convex areas in each field, CO₂ production rate were 35.4, 39.8 and 94.8 µgC-CO₂ gsoil^-1day^-1 for the B, G-5 and G-10, respectively. In concave area, CO₂ production were 61.5, 48.2 and 63.8 µgC-CO₂ gsoil^-1day^-1 for the B, G-5 and G-10, respectively. However, no significant differences between B and G-10 were found.

Table 3:
Descriptive statistics of soil CO₂, N₂O and CH₄ production rates from field sites at high and low topography in 0-10 cm soil depth for burned sugarcane (B), green sugarcane for 5 years (G-5) and green sugarcane for 10 years (G-10) sites.

		Convex position			Concave position
	B	G-5	G-10	B	G-5	G-10
	CO2 (µg C-CO2 g soil-1 day-1)
Mean	35.4 b	39.8 b	94.6 a	61.5 ab	48.2 b	63.8 a
SD	6.7	11.4	23.0	13.0	20.4	14.5
N	13	13	11	10	21	38
CI	31 - 39	32 - 46	78 - 111	52 - 70	38 - 57	60 - 67
Dunn’s test 5%		P < 0.001			P < 0.001
	N2O (ƞg N-N2O g soil-1 day-1)
Mean	42.4	10.2	29.8	33.6	14.5	12.9
SD	42.8	6.9	34.4	40.7	20.8	15.0
N	13	13	11	10	21	38
CI	16 - 68	6 - 14	6 - 53	0 - 67	3 - 25	9 - 16
Dunn’s test 5%		P = 0.278			P = 0.207
	CH4 (ƞg C-CH4 g soil-1 day-1)
Mean	16.7 a	17.0 a	17.6 a	15.9 a	16.5 a	17.1 a
SD	0.8	0.3	0.5	2.1	0.8	1.6
N	13	13	11	10	21	38
CI	16 - 17	16 - 17	17 - 18	14 - 17	16 - 16.8	16 - 17.5
Dunn’s test 5%		P = 0.002 P < 0.001			P < 0.001
	Soil microbial activity (µg C g-1 kg-1)
Mean	197.6	187.83	212.82	237.09	181.9	179.25
SD	53.5	123.89	58.47	56.4	67.84	126.1

• SD: standard desviation; CI: confidence interval.

In the convex areas, CO₂ was statistically different in the B and G-10 areas, with higher CO₂ emissions in the G-10 area, probably due to the presence of residue in soil surface that maintains soil moisture and to microbial activity. This is in agreement, with the observations of higher CO₂ emissions in high position-shaped landforms when compared to the linear-shaped ones from a Brazilian green sugarcane soil field (10yr) (Brito et al., 2010). However, in the area B, without residue, soil water tends to migrate to favorable areas of accumulation (concave positions), stimulating CO₂ emissions in these specific locations. Soil moisture is known to increase CO₂ production by the stimulates microbial activity (Schimel; Bilbrough and Welker, 2004). In the concave area, had significate difference only between G-5 and G-10 with more CO₂ production in the G-10 due the more straw in this area. However, some conclusion of CO₂ flux in G-5 is precipitated because this area can be considerate a transition of B to G-10.

A possible explanation for the variation in the CO₂ production with change in slope could be related to the soil microbial biomass (SMB). In the G-10 treatment both (convex and concave) CO₂ production and SMB were correlated to slope (Table 3).

CO₂ production potential in G-10 may be influenced by the crop residues left from previous harvests, which increased soil organic carbon contents and stimulated microbial activity and in turn increased microbial respiration (i.e. CO₂ production) (Varella et al., 2004). The soil organic carbon maps (Figure 3) possess the same spatial tendency as CO₂ production potential and SMB, which supports the hypothesized linkages.

Figure 3:
Spatial distribution of soil carbon (g C kg^-1) in burned sugarcane (A), green sugarcane 5 years (B) and green sugarcane 10 years (C) at 0-20 cm soil depth (n: 81).

At the burned field, SMB and CO₂ production rates were elevated at the concave position (compared to the convex in the green harvest areas) (Table 3, Figure 4A). Because the B treatment effectively removes the residues, the soil in this field has greater erosive potential, which means that water and nutrients will collect in concave position more quickly than with either green sugarcane management (residues hinder erosion and water flow). Thereby, this results in altering the spatial distribution of soil organic matter with time, with more soil carbon in the concave in the B and convex in the G-10 (Figure 3).

Figure 4:
Spatial distribution of soil A - CO₂ emission (ƞgC-CO₂ gsoil^-1 d^-1); B - N₂O emission (ƞgN gsoil^-1 d^-1) and C - CH₄ emission (ƞgC gsoil^-1 day^-1) (C) in burned sugarcane, green sugarcane 5 years and green sugarcane 10 years (n: 81).

N₂O production rates

The greater value of N₂O emission was 118,7 ƞg gsoil^-1 day^-1 (0,11µg gsoil^-1 day^-1), this is very low rates (Figure 2) and can be explained by anaerobic processes occurring to reduce the amount of N₂O in the headspace. Oliveira et al. (2013) reported negative values for N₂O (meaning a larger consumption rate of N₂O than production pathways) from soil with green harvest (7 yr) compared to burned sugarcane treatments.

It has been reported that N₂O emissions from soil are related to the C:N ratio of residues. Residues with a C:N ratio less than 25 are less stable in soil, meaning they are mineralized more quickly promoting the N in the soil and N₂O production (Dambreville et al., 2006; Figueiredo; La Scala, 2011), but the sugarcane crop residues, on average, have a C:N ratio close to 100, an immobilization of soil N is expected (Trivelin et al., 2002; White et al., 1988), which consequently leads to lower N₂O emissions.

It is important to note that in this experiment no manure or fertilizers is applied to the field. This may have influenced the low emissions measured because the input of N into the soil from applications of organic or synthetic fertilizer has been found to stimulate the denitrification processes (Oliveira et al., 2013; Signor; Cerri; Conant, 2013).

Analyzing the convex and concave area, was no possible to compare the N₂O production rate between areas due the P value was > 5% of probability by Dunn’s test, this means that the difference in the median values among the treatments groups are not great enough to exclude the possibility that the difference is due to random sampling variability, there is not a statistically significate difference. Despite this, the maps of N₂O production showed that the little gas concentration was similar with CO₂ production (Figure 4). However, this does not universally hold across all field measurements, with some studies showing no relationship with topography (Paré; Haughn, 2012).

CH₄ Production Rate

Overall, CH₄ production rates were not statistically different between treatments with an overall average of 15 ng C g_soil ^-1day^-1 across the three sites (Table 3; Figure 4C). One explanation for the low CH₄ concentrations observed and the similarity of data among the three sites may be related to the natural tendency of these iron-rich soils to absorb CH₄ (Oliveira et al., 2013). No significant trends between convex and concave topography with CH₄ production were observed, consistent with the results obtained in a study by (Paré; Haughn, 2012). Soil CH₄ emissions are more frequent in flooding areas (anaerobic conditions), because the gas is produced by the methanogenic microorganisms during anaerobic decomposition of organic substances (Thangarajan et al., 2013). As already mentioned, the soil properties at these sites do not promote anaerobic conditions.

Estimated net GHG impact

GHG production impact was the highest in the G-10 field in the convex position and the burned management had the highest GHG in the concave (Table 3). However, this was mainly due to the higher CO₂ emission, due to the increased microbial mineralization activity. The more interesting observation is that the B field had the highest non-CO₂ GHG contribution in both landscape positions (Table 4). It is important to note that in this study, the CO₂ emission is correlated to soil biological activity. Sugarcane can return about 15-20 Mg ha^-1 of organic matter, containing 6-8 Mg ha^-1 of carbon to the soil surface (Thangarajan et al., 2013). Cultivation methods affect the magnitude and pattern of CO₂, N₂O and CH₄ emissions, by influencing the supply of organic C and N to soil microorganisms (Wang; Bettany, 1995). And in this case, residue management imposed this control on the field sites. Management practices that result in changes in soil organic matter and influence the physical and chemical soil directly affect microbial activity and hence GHG emissions.

Table 4:
Greenhouse gases impact of soil in burned sugarcane (B), green sugarcane for 5 years (G-5) and green sugarcane for 10 years (G-10).

	Convex position			Concave position			Total	% Non-CO2
	CO2	Non-CO2	Total	CO2	Non-CO2	Total
	µg CO2eq gsoil -1 d-1			µg CO2-equiv gsoil -1 d-1
B	35.37	13.05	48.42	61.50	38.34	99.83	148	35%
G-5	38.85	3.47	43.32	48.23	16.15	64.37	108	18%
G-10	94.75	9.34	104.08	63.88	4.29	68.17	173	8%

Contradicting this result, the study of Figueiredo and La Scala (2011) calculated more CO₂eq. emission in burned sugarcane (3103.9 kg CO₂eq ha^-1year^-1) compared with green sugarcane (1619.8 kg CO₂eq ha^-1 year^-1), but considered the carbon sequestration from soil. Similar to our results, elevated CO₂ emission (1331 kt CO₂ year^-1) was observed in green residue sugarcane treatments in Australia when compared with bare sugarcane soil (1058 kt CO₂ year^-1) (Blair et al, 1998). In Brazil, a study showed that the sugarcane trash increased CO₂ emission rate by 380% compared to the bare soil (Weier, 1996). Therefore, since CO₂ production and emission are highly temporally dynamic these relationships will change as a function of soil moisture and temperature as well as timing of field operations.

CONCLUSIONS

The conventional burning and green harvest practices have significantly different GHG soil production profiles. The slope area was observed to have a significant influence on the distribution of GHG emissions. Higher CO₂ production from the G-10 soils were presumably related to soil microbial activity, and therefore indicate improved soil quality in the G-10 compared to the B field. On the other hand, the B management had the highest contribution of non-CO₂ GHG to the total GHG impact. Despite the higher numeric GHG impact of the green harvest (10 year).

ACKNOWLEDGEMENTS

São Paulo Research Foundation (FAPESP 2012/10.444-1) for financial support; to USDA-ARS lab of Saint Paul, Minnesota (USA) for gases analysis and to the São Martinho/Brazil ethanol mill for providing access to the study area.

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Publication Dates

• Publication in this collection
  Mar-Apr 2018

History

• Received
  17 July 2017
• Accepted
  01 Feb 2018