Quantification Of CH4 Emissions Research Articles

Factors affecting methane emissions from rice production in the Lower Mississippi river valley, USA

Rice (Oryza sativa L.) plays a key role in sustaining global food security; however, rice production also accounts for a significant proportion of global methane (CH4) emissions, a major greenhouse gas involved in altering global climate. Many previous studies have quantified the proportion of CH4 emissions by independently evaluating factors such as soil texture and cultivars – an approach that has led to potentially biased estimates of their actual contribution to total emissions. Most of these studies have not considered the influence of the preceding crop or growing-season weather that could lead to a significant variation in carbon budgets. The main objective of this study was to identify the key edaphic, cultivar, and environmental factors and determine their proportional contributions towards CH4 emissions in direct-seeded, rice-based cropping systems. A multiple regression model was developed to quantify CH4 emissions as a function of temperature (both day and night independently and in combination) and other weather variables, soil (silt-loam-surface-textured Albaqualf and clay-surface-textured Epiaquert), cultivar (conventional and hybrid), and cropping system (rice-rice and soybean [Glycine max L.]-rice). Results showed that (i) the Albaqualf emitted 211% more CH4-C than the Epiaquert (P<0.01; (ii) inbred cultivars accounted for 55 to 70% more CH4-C emissions than hybrid cultivars (P<0.01); (iii) soybean-rice rotations produced 58% less CH4-C emissions than rice-rice rotations (P<0.01); and (iv) future warming scenarios increased CH4-C emissions by up to 53%. To mitigate CH4 emissions, future research and crop production strategies that prioritize rice production on clay-surface-textured soils and use alternatives to a rice-rice rotation are recommended.

Sludge-Drying Lagoons: a Potential Significant Methane Source in Wastewater Treatment Plants.

"Sludge-drying lagoons" are a preferred sludge treatment and drying method in tropical and subtropical areas due to the low construction and operational costs. However, this method may be a potential significant source of methane (CH4) because some of the organic matter would be microbially metabolized under anaerobic conditions in the lagoon. The quantification of CH4 emissions from lagoons is difficult due to the expected temporal and spatial variations over a lagoon maturing cycle of several years. Sporadic ebullition of CH4, which cannot be easily quantified by conventional methods such as floating hoods, is also expected. In this study, a novel method based on mass balances was developed to estimate the CH4 emissions and was applied to a full-scale sludge-drying lagoon over a three year operational cycle. The results revealed that processes in a sludge-drying lagoon would emit 6.5 kg CO2-e per megaliter of treated sewage. This would represent a quarter to two-thirds of the overall greenhouse gas (GHG) emissions from wastewater-treatment plants (WWTPs). This work highlights the fact that sludge-drying lagoons are a significant source of CH4 that adds substantially to the overall GHG footprint of WWTPs despite being recognized as a cheap and energy-efficient means of drying sludge.

Top‐down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin

AbstractMethane (CH4) is the primary component of natural gas and has a larger global warming potential than CO2. Recent top‐down studies based on observations showed CH4 emissions in California's South Coast Air Basin (SoCAB) were greater than those expected from population‐apportioned bottom‐up state inventories. In this study, we quantify CH4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use the FLEXible PARTicle‐Weather Research and Forecasting (FLEXPART‐WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH4 using a Bayesian least squares method in a four‐dimensional inversion. Simulated CH4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R2 = 0.5). The emission estimates for CH4 in the posterior, 46.3 ± 9.2 Mg CH4/h, are consistent with published observation‐based estimates. Changes in the spatial distribution of CH4 emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. We estimate that dairies contributed 5.9 ± 1.7 Mg CH4/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH4/h in the SoCAB.

Chamber Size Effects on Methane Emissions from Rice Production

Quantifying methane (CH4) emissions from cultivated rice (Oryza sativa L.) production in the field has received increased attention recently due to methane’s importance as a greenhouse gas. The enclosed-headspace chamber technique is the standard methodology for field assessments of trace gas emissions. However, to our knowledge, no direct comparisons of measured CH4 fluxes and emissions from field-grown rice among differing chamber sizes have been reported. Therefore, the objective of this study was to evaluate the effect of chamber size [15.2- and 30.4-cm inside diameter (id)] on CH4 fluxes and season-long emissions from rice grown on a clay soil in Arkansas. Chamber size did not affect (P > 0.05) CH4 fluxes on 10 sampling dates during the flooded portion of the rice growing season and only affected fluxes on one of four sampling dates after flood release. Total season-long CH4 emissions from optimally N-fertilized rice were 32.6 and 35.6 kg CH4-C ha&#451&#183season&#451, which did not differ, and from bare clay soil were 0.74 and 1.75 kg CH4-C ha&#451&#183season&#451, which also did not differ, from the 15.2- and 30.4-cm chambers, respectively. Chamber size (i.e., 15.2- or 30.4-cm id) did not result in differences in cumulative CH4 emissions from this flooded-rice study that was conducted on a Sharkey clay soil in northeast Arkansas. Results indicate that both 15.2- and 30.4-cm diameter chambers were similarly adequate for measuring CH4 fluxes and emissions from the clay soil investigated. The similarity in emissions results between chamber sizes also indicates that the 15.2-cm diameter chambers adequately facilitated the quantification of CH4 emissions in this study.

Mobile measurements of climate forcing agents: Application to methane emissions from landfill and natural gas compression

Measuring greenhouse gas (GHG) source emissions provides data for validation of GHG inventories, which provide the foundation for climate change mitigation. Two Toyota RAV4 electric vehicles were outfitted with high-precision instrumentation to determine spatial and temporal resolution of GHGs (e.g., nitrous oxide, methane [CH4], and carbon dioxide [CO2]), and other gaseous species and particulate metrics found near emission sources. Mobile measurement platform (MMP) analytical performance was determined over relevant measurement time scales. Pollutant residence times through the sampling configuration were measured, ranging from 3 to 11 sec, enabling proper time alignment for spatial measurement of each respective analyte. Linear response range for GHG analytes was assessed across expected mixing ratio ranges, showing minimal regression and standard error differences between 5, 10, 30, and 60 sec sampling intervals and negligible differences between the two MMPs. GHG instrument drift shows deviation of less than 0.8% over a 24-hr measurement period. These MMPs were utilized in tracer-dilution experiments at a California landfill and natural gas compressor station (NGCS) to quantify CH4 emissions. Replicate landfill measurements during October 2009 yielded annual CH4 emissions estimates of 0.10 ± 0.01, 0.11 ± 0.01, and 0.12 ± 0.02 million tonnes of CO2 equivalent (MTCO2E). These values compare favorably to California GHG Emissions Inventory figures for 2007, 2008, and 2009 of 0.123, 0.125, and 0.126 MTCO2E/yr, respectively, for this facility. Measurements to quantify NGCS boosting facility-wide emissions, during June 2010 yielded an equivalent of 5400 ± 100 TCO2E/yr under steady-state operation. However, measurements during condensate transfer without operational vapor recovery yield an instantaneous emission rate of 2–4 times greater, but was estimated to only add 12 TCO2E/yr overall. This work displays the utility for mobile GHG measurements to validate existing measurement and modeling approaches, so emission inventory values can be confirmed and associated uncertainties reduced.Implications: Measuring greenhouse gas (GHG) source emissions provides data and validation for GHG inventories, the foundation for climate change mitigation. Mobile measurement platforms with robust analytical instrumentation completed tracer-dilution experiments in California at a landfill and natural gas compressor station (NGCS) to quantify CH4 emissions. Data collected for landfill CH4 agree with the current California emissions inventory, while NGCS data show the possible variability from this type of facility. This work displays the utility of mobile GHG measurements to validate existing measurement and modeling approaches, such that emission inventory values can be confirmed, associated uncertainties reduced, and mitigation efforts quantified.

Spatial variability of methane emissions from Swiss alpine fens

Wetland ecosystems are a major natural source of the important greenhouse gas methane (CH4). Among these ecosystems, fens have been shown to release high quantities of CH4. Data on CH4 emissions from alpine fens are scarce and mainly limited to the United States and China. Therefore, static chambers were used to quantify CH4 emissions from 14 fens located in the Swiss Alps. The aims of this study were to determine the spatial variability of the emissions and to identify potential key factors which influence CH4 turnover. The fens were located at altitudes between 1,800 and 2,600 m a.s.l., the pore water varied from acidic to slightly acidic (pH 4.5–6.4) and the vegetation was dominated by plants of the genus Carex. In addition, the underlying bedrock was either siliceous or calcareous. Methane emissions ranged from 74 ± 43 to 711 ± 212 mg CH4 m−2 day−1. The type of bedrock, the plant biomass above the water table and the CH4 pore water concentrations at depths from 0 to 20 cm were the main factors influencing CH4 emissions. Detailed measurements in three selected fens suggested that more than 98 % of the total CH4 emissions are due to plant-mediated transport.

Questioning the Accuracy of Greenhouse Gas Accounting from Agricultural Waste: A Case Study

The New Zealand Greenhouse Gas Inventory (the NZ Inventory) uses country-specific data to quantify CH emissions from anaerobic ponds treating dairy farm effluent (315 Gg CO equivalent [CO-e] in 2009). In this study, we used literature data to: (i) evaluate the accuracy of the NZ Inventory's parameters used to quantify these CH emissions; and (ii) determine whether the NZ Inventory's scope is capturing the full spectrum of sources with bio-CH potential entering anaerobic ponds. The research indicated that the current NZ Inventory methodology is underestimating CH emissions from anaerobic ponds across New Zealand by 264 to 603 Gg CO-e annually. Moreover, the NZ Inventory is currently not accounting for (i) manure from supplementary feed pads and stand-off pads (annual CH emissions = 207-330 Gg CO-e); (ii) waste milk (153-280 Gg CO-e); and (iii) supplementary feed waste (90-216 Gg CO-e). Annual CH emissions from anaerobic ponds on dairy farms across New Zealand are thus more likely to be 1029 to 1744 Gg CO-e, indicating that the NZ Inventory is reporting as little as 18% of actual CH emissions produced by this sector. These additional wastes are not accounted for in the methodology prescribed by the Intergovernmental Panel on Climate Change for estimating CH emissions from dairy manure. Consequently, other significant dairying nations will also probably be underestimating their waste CH emissions. Our research highlights that, if governments attempt to include country-specific emission factors in their greenhouse gas inventories, these factors must be based on an assessment of the full spectrum of sources contributing to greenhouse gas emissions within any given sector.

Comparing methane emissions from different sheep-keeping systems in semiarid regions: A case study of Syria

Sheep husbandry represents a significant source of methane (CH4) in semiarid grassland regions such as Syria. However, the contribution of sheep to CH4 emissions in Syria is still unknown. This study was designed to quantify CH4 emissions and identify possible mitigation strategies for their reduction. Methodology developed by the Intergovernmental Panel on Climate Change (IPCC) was used to estimate CH4 emissions. A survey was conducted on 64 farms from different locations in Syria in 2009. Data were collected concerning sheep-keeping systems (SKSs), body mass, milk and wool yield, farm locations, feed rations, periods of grazing on the Steppe, the duration of pasturing on agricultural residuals and time periods when sheep were kept in stables. Using a linear statistical model, the influence of SKS, geographical region and sheep body mass on emitted CH4 were analysed. The results showed that the geographical region, SKS and sheep body mass had significant effects (P<0.05) on CH4 emissions. According to the model, the mean values of estimated CH4 emissions from extensive, semi-intensive and intensive SKSs were 26±0.9, 22.5±1.3 and 13.5±1.7kg/sheepyear, respectively. In comparing differences between the least square means of CH4 emissions, the extensive and semi-intensive SKSs produced 92% and 66% higher CH4 emissions compared to intensive SKS. The differences in CH4 emissions within the distinct SKSs were attributed to dietary composition. Extensive SKS used a less concentrated feeding regime (98±17day/year) than semi-intensive SKS (114±47day/year), and intensive SKS employed concentrated feeding year round. Furthermore, it was observed that sheep with the same body mass produced higher CH4 emissions in extensive SKS than in semi-intensive and intensive SKSs. Moreover, the semi-intensive SKS occupied more natural pastures than extensive SKS, which caused an overuse of the Steppe. Therefore, an effective mitigation strategy involves the use of more digestible feed, which would be accomplished by increasing the quantity of concentrated feed. Owing to unfavourable farming conditions, low-cost nonconventional feeds such as the residuals of wheat and cotton should be used to improve sheep management practices to reduce Steppe overgrazing in the extensive and semi-intensive SKSs of Syria and other semiarid areas.

Modeling methane emissions from the Alaskan Yukon River basin, 1986–2005, by coupling a large‐scale hydrological model and a process‐based methane model

Much progress has been made in methane modeling for the Arctic. However, there is still large uncertainty in emissions estimates due to the spatial variability in water table depth resulting from complex topographic gradients, and due to variations in methane production and oxidation due to complex freezing and thawing processes. Here we extended an extant methane emission module within a biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to include a large‐scale hydrology model, the variable infiltration capacity (VIC) model. The VIC model provides the required inputs, including freezing and thawing fronts, soil temperature and moisture, to the methane module. The effect of topography on the redistribution of soil moisture and water table depth was explicitly modeled using the TOPMODEL approach. The coupled modeling framework was applied to the Yukon River basin at a spatial resolution of 1 km from 1986 to 2005. The simulations show that the average annual net emissions of CH4 from the region are 4.01 Tg CH4 yr−1. El Niño phenomena usually lead to positive emission anomalies, while decreases in net CH4 emissions may be associated with strong La Niña events. Precipitation was found to be more closely related to CH4 dynamics than to soil temperature and active layer depth during the study period. This study suggests that the effects of soil freezing and thawing processes and the effects of microtopography on hydrology should be considered in the quantification of CH4 emissions.

Non-microbial methane emissions from fresh leaves: Effects of physical wounding and anoxia

Abstract Non-microbial methane (CH4) emissions from plants might be widespread in nature. However, this unexpected source and its global strength still remain controversial. Very recently it has been suggested that CH4 release by plants may be linked to environmental stress. Using fresh leaves of 73 plants, including those from trees, shrubs and herbaceous species, a series of laboratory experiments have been employed to quantify CH4 emissions and to examine the effect of physical wounding and anoxia. Approximately half of the plants investigated emitted CH4 at rates ≥0.2 ng gdw−1h−1. Emissions from detached intact fresh leaves were in the ranges of 0.20–2.25 and 0.38–2.14 ng gdw−1h−1 when incubated under air and anoxic conditions, respectively. Strongly enhanced emissions were monitored when leaves were physically wounded and/or incubated under anoxia. Several experiments were conducted to verify in-situ emissions of CH4 and exclude microbial activity as the source. Average short-lived pulsed CH4 emissions of 53.4 ng gdw−1h−1, with a range of 0–687 ng gdw−1h−1, were observed from ground fresh leaves of the 60 plant species investigated, indicating that pulse emissions from plants immediately following environmental stress such as wounding need consideration to constrain global CH4 emissions from vegetation. This type of emission may also assist with the delineation of the mechanism involved in non-microbial CH4 formation.

Comparison of open-circuit respiration chambers with a micrometeorological method for determining methane emissions from beef cattle grazing a tropical pasture

Emissions of CH4 methane from beef cattle grazing pastures characteristic of northern Australia are yet to be reliably quantified. Poor quality pastures and low animal productivity are typically associated with high CH4 emissions/unit animal product. Our study reports two independent methodologies to quantify CH4 emissions from beef cattle at herd scale and from individual animals. The first method identifies each animal within a herd (n=18) as a point source of CH4. Emissions at the herd scale were estimated with a backward Lagrangian stochastic (bLs) dispersion model. This model used atmospheric turbulence data and line-averaged concentrations of CH4 measured with an open-path laser and inputs (ppm) from 5 paths across 1ha Rhodes grass (Chloris gayana) dominated pastures that were flat and free of obstructions. The second method used open circuit respiration chambers to measure 24h CH4 emissions from 18 steers fed freshly cut forage from the same pasture. The CH4 emissions determined using the dispersion method were 136.1±21.5g/d or 29.7±3.70g/kg dry matter (DM) intake and 114±5.1g/d or 30.1±2.19g/kg DM intake using open circuit respiration chambers. Estimates of CH4 emissions based on predictive algorithms for beef cattle grazing similar pastures range from 82.7±3.98g/d to 112.7±2.57g/d. Additional studies with different tropical pastures and herds are required to obtain estimated CH4 emission values for further comparisons with predictions from the Australian Greenhouse Gas Inventory and those currently reported in the literature for beef cattle.This paper is part of the special issue entitled: Greenhouse Gases in Animal Agriculture – Finding a Balance between Food and Emissions, Guest Edited by T.A. McAllister, Section Guest Editors; K.A. Beauchemin, X. Hao, S. McGinn and Editor for Animal Feed Science and Technology, P.H. Robinson.