Current available strategies to mitigate greenhouse gas emissions in livestock systems: an animal welfare perspective

Livestock production is a major contributor to greenhouse gas (GHG) emissions, so will play a significant role in the mitigation effort. Recent literature highlights different strategies to mitigate GHG emissions in the livestock sector. Animal welfare is a criterion of sustainability and any strategy designed to reduce the carbon footprint of livestock production should consider animal welfare amongst other sustainability metrics. We discuss and tabulate the likely relationships and trade-offs between the GHG mitigation potential of mitigation strategies and their welfare consequences, focusing on ruminant species and on cattle in particular. The major livestock GHG mitigation strategies were classified according to their mitigation approach as reducing total emissions (inhibiting methane production in the rumen), or reducing emissions intensity (Ei; reducing CH₄ per output unit without directly targeting methanogenesis). Strategies classified as antimethanogenic included chemical inhibitors, electron acceptors (i.e. nitrates), ionophores (i.e. Monensin) and dietary lipids. Increasing diet digestibility, intensive housing, improving health and welfare, increasing reproductive efficiency and breeding for higher productivity were categorized as strategies that reduce Ei. Strategies that increase productivity are very promising ways to reduce the livestock carbon footprint, though in intensive systems this is likely to be achieved at the cost of welfare. Other strategies can effectively reduce GHG emissions whilst simultaneously improving animal welfare (e.g. feed supplementation or improving health). These win–win strategies should be strongly supported as they address both environmental and ethical sustainability. In order to identify the most cost-effective measures for improving environmental sustainability of livestock production, the consequences of current and future strategies for animal welfare must be scrutinized and contrasted against their effectiveness in mitigating climate change.     

Methane emission from global livestock sector during 1890–2014: Magnitude,trends and spatiotemporal patterns

Human demand for livestock products has increased rapidly during the past few decades largely due to dietary transition and population growth, with significant impact on climate and the environment. The contribution of ruminant livestock to greenhouse gas (GHG) emissions has been investigated extensively at various scales from regional to global, but the long‐term trend, regional variation and drivers of methane (CH₄) emission remain unclear. In this study, we use Intergovernmental Panel on Climate Change (IPCC) Tier II guidelines to quantify the evolution of CH₄ emissions from ruminant livestock during 1890–2014. We estimate that total CH₄ emissions in 2014 was 97.1 million tonnes (MT) CH₄ or 2.72 Gigatonnes (Gt) CO₂‐eq (1 MT = 10¹² g, 1 Gt = 10¹⁵ g) from ruminant livestock, which accounted for 47%–54% of all non‐CO₂ GHG emissions from the agricultural sector. Our estimate shows that CH₄ emissions from the ruminant livestock had increased by 332% (73.6 MT CH₄ or 2.06 Gt CO₂‐eq) since the 1890s. Our results further indicate that livestock sector in drylands had 36% higher emission intensity (CH₄ emissions/km²) compared to that in nondrylands in 2014, due to the combined effect of higher rate of increase in livestock population and low feed quality. We also find that the contribution of developing regions (Africa, Asia and Latin America) to the total CH₄ emissions had increased from 51.7% in the 1890s to 72.5% in the 2010s. These changes were driven by increases in livestock numbers (LU units) by up to 121% in developing regions, but decreases in livestock numbers and emission intensity (emission/km²) by up to 47% and 32%, respectively, in developed regions. Our results indicate that future increases in livestock production would likely contribute to higher CH₄ emissions, unless effective strategies to mitigate GHG emissions in livestock system are implemented.     

Prediction of enteric methane production,yield, and intensity in dairy cattle using an intercontinental database

Enteric methane (CH₄) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH₄ is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH₄ production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH₄ production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH₄ production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH₄ prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH₄ production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH₄ emission conversion factors for specific regions are required to improve CH₄ production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH₄ yield and intensity prediction, information on milk yield and composition is required for better estimation.     

Evaluation of enteric methane prediction equations for dairy cows used in whole farm models

The importance of evaluating greenhouse gas (GHG) emissions from dairy cows within the whole farm setting is being realized as more important than evaluating these emissions in isolation. Current whole farm models aimed at evaluating GHG emissions make use of simple regression equations to predict enteric methane (CH₄) production. The objective of the current paper is to evaluate the performance of nine CH₄ prediction equations that are currently being used in whole farm GHG models. Data used to evaluate the prediction equations came from a collection of individual (IND) and treatment averaged (TRT) data. Equations were compared based on mean square prediction error (MSPE) and concordance correlation coefficient (CCC) analysis. In general, predictions were poor, with root MSPE (as a percentage of observed mean) values ranging from 20.2 to 52.5 for the IND database and from 24.0 to 38.2 for the TRT database and CCC values ranging from 0.009 to 0.493 for the IND database and from 0.000 to 0.271 for the TRT database. Overall, the equations of Moe & Tyrrell and IPCC Tier II performed best on the IND dataset, and the equations of Moe & Tyrrell and Kirchgeßner et al., performed best on the TRT dataset. Results show that the simple more generalized equations performed worse than those that attempted to represent important aspects of diet composition, but in general significant amounts of bias and deviation of the regression slope from unity existed for all equations. The low prediction accuracy of CH₄ equations in whole farm models may introduce substantial error into inventories of GHG emissions and lead to incorrect mitigation recommendations.     

基于IPCC Tier 1层级的中国反刍家畜胃肠道甲烷排放格局变化分析

依据政府间气候变化委员会(IPCC)2006年公布的反刍家畜胃肠道CH4排放系数(奶牛61 kg CH4头-1a-1,肉役牛47 kg CH4头-1a-1,绵羊和山羊均为5 kg CH4头-1a-1)和IPCC Tier 1计算方法,结合《中国统计年鉴》和《中国畜牧业统计年鉴》,估算了中国以及各个省份1990—2010年CH4的排放总量,绘制出中国反刍家畜胃肠道CH4排放格局及历史变化图。研究结果表明:11990—2010年期间,中国反刍家畜胃肠道CH4排放量(5.90—7.65 Tg)总体呈现先上升(1995年最高)后下降的趋势,其中肉役牛(主要是黄牛和水牛)胃肠道CH4排放量(4.33 Tg)及其所占比例(65%)最大。奶牛胃肠道CH4排放量及其比例呈现逐年增加的趋势,2006年(0.83 Tg,12.7%)超过山羊和绵羊胃肠道CH4排放量及其比例,成为中国反刍家畜胃肠道CH4排放第二大源。但是,奶牛单位产奶量所排放的CH4量逐年降低,表明中国奶牛饲养技术与生产性能不断提高。2中国反刍家畜胃肠道CH4排放格局呈现区域集中特点,主要集中在中西部和北部的各个省份,其中四川、内蒙古、新疆、河南、西藏、山东、河北、黑龙江、云南和甘肃等10个省份的排放量占中国排放总量的50%以上。总之,1990—2010年间,中国反刍家畜胃肠道CH4排放总量为(6.77±0.46)Tg(肉役牛为主要排放源),随时间推移呈现先上升后下降的趋势;中国反刍家畜胃肠道CH4排放的格局呈区域集中分布,中西部和北部的各个省份占60%以上。     

Mitigation of ammonia,nitrous oxide and methane emissions from manure management chains: a meta‐analysis and integrated assessment

Livestock manure contributes considerably to global emissions of ammonia (NH₃) and greenhouse gases (GHG), especially methane (CH₄) and nitrous oxide (N₂O). Various measures have been developed to mitigate these emissions, but most of these focus on one specific gas and/or emission source. Here, we present a meta‐analysis and integrated assessment of the effects of mitigation measures on NH₃, CH₄ and (direct and indirect) N₂O emissions from the whole manure management chain. We analysed the effects of mitigation technologies on NH₃, CH₄ and N₂O emissions from individual sources statistically using results of 126 published studies. Whole‐chain effects on NH₃ and GHG emissions were assessed through scenario analysis. Significant NH₃ reduction efficiencies were observed for (i) housing via lowering the dietary crude protein (CP) content (24–65%, compared to the reference situation), for (ii) external slurry storages via acidification (83%) and covers of straw (78%) or artificial films (98%), for (iii) solid manure storages via compaction and covering (61%, compared to composting), and for (iv) manure application through band spreading (55%, compared to surface application), incorporation (70%) and injection (80%). Acidification decreased CH₄ emissions from stored slurry by 87%. Significant increases in N₂O emissions were found for straw‐covered slurry storages (by two orders of magnitude) and manure injection (by 26–199%). These side‐effects of straw covers and slurry injection on N₂O emission were relatively small when considering the total GHG emissions from the manure chain. Lowering the CP content of feed and acidifying slurry are strategies that consistently reduce NH₃ and GHG emissions in the whole chain. Other strategies may reduce emissions of a specific gas or emissions source, by which there is a risk of unwanted trade‐offs in the manure management chain. Proper farm‐scale combinations of mitigation measures are important to minimize impacts of livestock production on global emissions of NH₃ and GHG.     

Annual emissions of greenhouse gases from sheepfolds in Inner Mongolia

Sheepfolds represent significant hot spot sources of greenhouse gases (GHG) in semi-arid grassland regions, such as Inner Mongolia in China. However, the annual contribution of sheepfolds to regional GHG emissions is still unknown. In order to quantify its annual contribution, we conducted measurements of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) fluxes at two sheepfold sites in the Baiyinxile administrative region of Inner Mongolia for 1 year, using static opaque chamber and gas chromatography methods. Our data show that, at an annual scale, both sheepfolds functioned as net sources of CO₂, CH₄ and N₂O. Temperatures primarily determined the seasonal pattern of CO₂ emission; 60–84% of the CO₂ flux variation could be explained by temperature changes. High rates of net CH₄ emissions from sheepfold soils were only observed when animals (sheep and goats) were present. While nitrous oxide emissions were also stimulated by the presence of animals, pulses of N₂O emissions were also be related to rainfall and spring-thaw events. The total annual cumulative GHG emissions in CO₂ equivalents (CO₂: 1; CH₄: 25; and N₂O: 298) were quantified as 87.4?±?18.4 t ha^?1 for the sheepfold that was used during the non-grazing period (i.e., winter sheepfold) and 136.7?±?15.9 t ha^?1 used during the grazing period (i.e., summer sheepfold). Of the annual total GHG emissions, CH₄ release accounted for approximately 1% of emissions, while CO₂ and N₂O emissions contributed to approximately 59% and 40%, respectively. The total GHG emission factor (CO₂?+?CH₄?+?N₂O) per animal for the sheepfolds investigated in this study was 30.3 kg CO₂ eq yr^?1 head^?1, which translates to 0.3, 18.8 and 11.2 kg CO₂ eq yr^?1 head^?1 for CH₄, CO₂ and N₂O, respectively. Sheepfolds accounted for approximately 34% of overall N₂O emissions in the Baiyinxile administrative region, a typical steppe region within Inner Mongolia. The contribution of sheepfolds to the regional CO₂ or CH₄ exchange is marginal.     

Changes in soil greenhouse gas fluxes by land use change from primary forest

Primary forest conversion is a worldwide serious problem associated with human disturbance and climate change. Land use change from primary forest to plantation, grassland or agricultural land may lead to profound alteration in the emission of soil greenhouse gases (GHG). Here, we conducted a global meta‐analysis concerning the effects of primary forest conversion on soil GHG emissions and explored the potential mechanisms from 101 studies. Our results showed that conversion of primary forest significantly decreased soil CO₂ efflux and increased soil CH₄ efflux, but had no effect on soil N₂O efflux. However, the effect of primary forest conversion on soil GHG emissions was not consistent across different types of land use change. For example, soil CO₂ efflux did not respond to the conversion from primary forest to grassland. Soil N₂O efflux showed a prominent increase within the initial stage after conversion of primary forest and then decreased over time while the responses of soil CO₂ and CH₄ effluxes were consistently negative or positive across different elapsed time intervals. Moreover, either within or across all types of primary forest conversion, the response of soil CO₂ efflux was mainly moderated by changes in soil microbial biomass carbon and root biomass while the responses of soil N₂O and CH₄ effluxes were related to the changes in soil nitrate and soil aeration‐related factors (soil water content and bulk density), respectively. Collectively, our findings highlight the significant effects of primary forest conversion on soil GHG emissions, enhance our knowledge on the potential mechanisms driving these effects and improve future models of soil GHG emissions after land use change from primary forest.     

Effect of improved nitrogen management on greenhouse gas emissions from intensive dairy systems in the Netherlands

Dairy systems in Europe contribute to the emissions of the greenhouse gases (GHGs) nitrous oxide (N₂O), methane (CH₄) and carbon dioxide (CO₂). In this paper, the effects of improved nitrogen (N) management on GHG emissions from Dutch dairy farms are determined. The GHG emissions are calculated using the panel on climate change (IPCC) methodology for the Netherlands, an updated and refined IPCC methodology, and a full accounting approach. The changes in dairy farming over the last 20 years, and the consequences for N management are described using detailed farm‐level data, collected in 1985, 1997 and 2002. The selected years represent distinct stages in the implementation of N policies. The changes in N management have reduced the GHG emissions. A reduction of the N surplus per kilogram milk with 1 g N reduced the GHG emissions per kilogram milk with approximately 29 g CO₂‐equivalents. The reduction of the N surpluses was mainly brought about by reduced fertilizer use and reduced grazing time. The use of updated and refined emission factors resulted in higher CH₄ emissions and lower N₂O emissions. On average, the overall emission was 36% higher with the refined method. Full accounting, including all direct and indirect emissions of CH₄, N₂O and CO₂, increased the emission with 36% compared with the refined IPCC methodology. We conclude that the N surplus at farm level is a useful indicator of GHG emissions. A full accounting system as presented in this study may effectively enable farmers to address the issue of emissions of GHGs in their operational management decisions. Both approaches serve their own specific objectives: full accounting at the farm level to explore mitigation options, and the IPCC methods to report changes in GHG emissions at the national level.     

Effect of biochar amendment on the soil-atmosphere exchange of greenhouse gases from an intensive subtropical pasture in northern New South Wales, Australia

We assessed the effect of biochar incorporation into the soil on the soil-atmosphere exchange of the greenhouse gases (GHG) from an intensive subtropical pasture. For this, we measured N₂O, CH₄ and CO₂ emissions with high temporal resolution from April to June 2009 in an existing factorial experiment where cattle feedlot biochar had been applied at 10 t ha^?1 in November 2006. Over the whole measurement period, significant emissions of N₂O and CO₂ were observed, whereas a net uptake of CH₄ was measured. N₂O emissions were found to be highly episodic with one major emission pulse (up to 502 ??g N₂O-N m^?2 h^?1) following heavy rainfall. There was no significant difference in the net flux of GHGs from the biochar amended vs. the control plots. Our results demonstrate that intensively managed subtropical pastures on ferrosols in northern New South Wales of Australia can be a significant source of GHG. Our hypothesis that the application of biochar would lead to a reduction in emissions of GHG from soils was not supported in this field assessment. Additional studies with longer observation periods are needed to clarify the long term effect of biochar amendment on soil microbial processes and the emission of GHGs under field conditions.     

Implementing an appropriate metric for the assessment of greenhouse gas emissions from livestock production: A national case study

Livestock farming is of major economic relevance but also severely contributes to environmental impacts, especially greenhouse gas (GHG) emissions such as methane (CH₄; particularly from ruminant production) and nitrous oxide (N₂O; mainly from manure management and soil cultivated for feed production). In this study, we analyse the impact of GHG emissions from Austrian livestock production, using two metrics: a) the commonly used global warming potential (GWP) over 100 years (GWP₁₀₀ in CO₂-equivalents, CO₂-e), and b) the recently introduced metric GWP*, which describes additional warming as a function of the timeline of short-lived GHG emissions (unit CO₂ warming equivalents, CO₂-we). We first compiled the sectoral (i.e. only direct emissions without upstream processes) GWP₁₀₀ for different livestock categories with a focus on dairy cattle, beef cattle and pigs in Austria between 1990 and 2019. We also estimated product-related (i.e. per kg carcass weight or per litre of milk) GWP₁₀₀ values, including upstream processes. We then calculated the corresponding GWP* metrics, both sectoral and product-related, and compared them with the GWP₁₀₀ values. Decreasing livestock numbers and improved production efficiency were found to result in strong sectoral emission reductions from dairy production (–32 % of GWP₁₀₀ from 1990 to 2019) and from pigs (–32 % CO₂-e). This contrasts with low reductions from other livestock categories and even increases for cattle other than dairy cows (+3 % CO₂-e), mainly due to rising suckler cow numbers. Allocated results per kg milk and kg body mass show quite similar results. Using the GWP* metric, the climate impacts of Austrian livestock production are less severe. When assuming constant management and emission intensity over a period of at least 20 years, the CO₂-we (GWP*) is almost 50 % less than CO₂-e (GWP₁₀₀) per kg Austrian raw milk due to the different impacts of the short-lived CH₄. A similar trend applies to an average cattle carcass (-40 % warming impact). The emission reductions of the shrinking Austrian livestock population represent an important contribution to a climate-neutral agriculture: The CH₄ reductions of livestock production during the past 20 years reduce the current total Austrian CO₂-we by 16 %. Continuous CH₄ reduction, as we show it here for Austrian livestock, is an effective option to tackle the climate crisis in the short term. It shall be stressed that a relatively low GWP* should not be interpreted as a concession for further CH₄ emissions but as an actual reduction of (additional) warming.     

The Greenhouse Gas Balance of a Dairy Farm as Influenced by the Uptake of Biogas Production

The production of energy crops for farm-scale anaerobic digestion (AD) can affect emissions of greenhouse gases (GHG) in a number of ways. Some examples are: fugitive CH₄ emissions from the digester and the storage of the digestate, emissions of N₂O from soil and emissions of CO₂ from farm machinery. Moreover, uptake of AD may be accompanied by changes in the way the farm is operated, which may affect GHG emissions. The scale of these emissions was assessed from published data for the biogas feedstocks cattle slurry and grass silage. Emissions were compared to references representing current farm operation and energy generation by fossil fuels. Feeding the digester with cattle slurry for the entire year did not result in reduced emissions due to relatively high emissions from stored raw slurry in summer. If grass was used for digester feedstock, the level of N₂O emissions from the crop was the most important factor for the GHG balance of farm-scale AD. If N₂O emissions were low, biogas realised substantial savings of GHG in the order of 1 t CO₂ equivalents per hectare per year. At a high level of N₂O emissions, energy cropping might even result in increased GHG emissions compared to fossil fuels.     

Using Common Boundaries to Assess Methane Emissions: A Life Cycle Evaluation of Natural Gas and Coal Power Systems

There is consensus on the importance of upstream methane (CH₄) emissions to the life cycle greenhouse gas (GHG) footprint of natural gas systems, but inconsistencies among recent studies explain why some researchers calculate a CH₄ emission rate of less than 1% whereas others calculate a CH₄ emission rate as high as 10%. These inconsistencies arise from differences in data collection methods, data collection time frames, and system boundaries. This analysis focuses on system boundary inconsistencies. Our results show that the calculated CH₄ emission rate can increase nearly fourfold not by changing the magnitude of any particular emission source, but by merely changing the portions of the supply chain that are included within the system boundary. Our calculated CH₄ emission rate for extraction through pipeline transmission is 1.2% for current practices. Our model allows us to identify GHG contributors in the upstream supply chain, but also allows us to tie upstream findings to complete life cycle scenarios. If applied to the life cycles of power systems and assessed in terms of cumulative radiative forcing, the upstream CH₄ emission rate can be as high as 3.2% before the GHG impacts from natural gas power exceed those from coal power at any point during a 100‐year time frame.     

Urbanization can accelerate climate change by increasing soil N2O emission while reducing CH4 uptake

Urban land-use change has the potential to affect local to global biogeochemical carbon (C) and nitrogen (N) cycles and associated greenhouse gas (GHG) fluxes. We conducted a meta-analysis to (1) assess the effects of urbanization-induced land-use conversion on soil nitrous oxide (N₂O) and methane (CH₄) fluxes, (2) quantify direct N₂O emission factors (EF_d) of fertilized urban soils used, for example, as lawns or forests, and (3) identify the key drivers leading to flux changes associated with urbanization. On average, urbanization increases soil N₂O emissions by 153%, to 3.0 kg N ha⁻¹ year⁻¹, while rates of soil CH₄ uptake are reduced by 50%, to 2.0 kg C ha⁻¹ year⁻¹. The global mean annual N₂O EF_d of fertilized lawns and urban forests is 1.4%, suggesting that urban soils can be regional hotspots of N₂O emissions. On a global basis, conversion of land to urban greenspaces has increased soil N₂O emission by 0.46 Tg N₂O-N year⁻¹ and decreased soil CH₄ uptake by 0.58 Tg CH₄-C year⁻¹. Urbanization driven changes in soil N₂O emission and CH₄ uptake are associated with changes in soil properties (bulk density, pH, total N content, and C/N ratio), increased temperature, and management practices, especially fertilizer use. Overall, our meta-analysis shows that urbanization increases soil N₂O emissions and reduces the role of soils as a sink for atmospheric CH₄. These effects can be mitigated by avoiding soil compaction, reducing fertilization of lawns, and by restoring native ecosystems in urban landscapes.     

Emissions of CH4 and N2O under Different Tillage Systems from Double-Cropped Paddy Fields in Southern China

Understanding greenhouse gases (GHG) emissions is becoming increasingly important with the climate change. Most previous studies have focused on the assessment of soil organic carbon (SOC) sequestration potential and GHG emissions from agriculture. However, specific experiments assessing tillage impacts on GHG emission from double-cropped paddy fields in Southern China are relatively scarce. Therefore, the objective of this study was to assess the effects of tillage systems on methane (CH₄) and nitrous oxide (N₂O) emission in a double rice (Oryza sativa L.) cropping system. The experiment was established in 2005 in Hunan Province, China. Three tillage treatments were laid out in a randomized complete block design: conventional tillage (CT), rotary tillage (RT) and no-till (NT). Fluxes of CH₄ from different tillage treatments followed a similar trend during the two years, with a single peak emission for the early rice season and a double peak emission for the late rice season. Compared with other treatments, NT significantly reduced CH₄ emission among the rice growing seasons (P<0.05). However, much higher variations in N₂O emission were observed across the rice growing seasons due to the vulnerability of N₂O to external influences. The amount of CH₄ emission in paddy fields was much higher relative to N₂O emission. Conversion of CT to NT significantly reduced the cumulative CH₄ emission for both rice seasons compared with other treatments (P<0.05). The mean value of global warming potentials (GWPs) of CH₄ and N₂O emissions over 100 years was in the order of NT<RT<CT, which indicated NT was significantly lower than both CT and RT (P<0.05). This suggests that adoption of NT would be beneficial for GHG mitigation and could be a good option for carbon-smart agriculture in double rice cropped regions.     

Methane emissions from wetlands: biogeochemical,microbial, and modeling perspectives from local to global scales

Understanding the dynamics of methane (CH₄) emissions is of paramount importance because CH₄ has 25 times the global warming potential of carbon dioxide (CO₂) and is currently the second most important anthropogenic greenhouse gas. Wetlands are the single largest natural CH₄ source with median emissions from published studies of 164 Tg yr^?1, which is about a third of total global emissions. We provide a perspective on important new frontiers in obtaining a better understanding of CH₄ dynamics in natural systems, with a focus on wetlands. One of the most exciting recent developments in this field is the attempt to integrate the different methodologies and spatial scales of biogeochemistry, molecular microbiology, and modeling, and thus this is a major focus of this review. Our specific objectives are to provide an up‐to‐date synthesis of estimates of global CH₄ emissions from wetlands and other freshwater aquatic ecosystems, briefly summarize major biogeophysical controls over CH₄ emissions from wetlands, suggest new frontiers in CH₄ biogeochemistry, examine relationships between methanogen community structure and CH₄ dynamics in situ, and to review the current generation of CH₄ models. We highlight throughout some of the most pressing issues concerning global change and feedbacks on CH₄ emissions from natural ecosystems. Major uncertainties in estimating current and future CH₄ emissions from natural ecosystems include the following: (i) A number of important controls over CH₄ production, consumption, and transport have not been, or are inadequately, incorporated into existing CH₄ biogeochemistry models. (ii) Significant errors in regional and global emission estimates are derived from large spatial‐scale extrapolations from highly heterogeneous and often poorly mapped wetland complexes. (iii) The limited number of observations of CH₄ fluxes and their associated environmental variables loosely constrains the parameterization of process‐based biogeochemistry models.     

Herd-scale measurements of methane emissions from cattle grazing extensive sub-tropical grasslands using the open-path laser technique

Methane (CH₄) emissions associated with beef production systems in northern Australia are yet to be quantified. Methodologies are available to measure emissions, but application in extensive grazing environments is challenging. A micrometeorological methodology for estimating herd-scale emissions using an indirect open-path spectroscopic technique and an atmospheric dispersion model is described. The methodology was deployed on five cattle properties across Queensland and Northern Territory, with measurements conducted during two occasions at one site. On each deployment, data were collected every 10 min for up to 7 h a day over 4 to 16 days. To increase the atmospheric concentration of CH₄ to measurable levels, cattle were confined to a known area around water points from ~0800 to 1600 h, during which time measurements of wind statistics and line-averaged CH₄ concentration were taken. Filtering to remove erroneous data accounted for 35% of total observations. For five of the six deployments CH₄ emissions were within the expected range of 0.4 to 0.6 g/kg BW. At one site, emissions were ~2 times expected values. There was small but consistent variation with time of day, although for some deployments measurements taken early in the day tended to be higher than at the other times. There was a weak linear relationship (R²=0.47) between animal BW and CH₄ emission per kg BW. Where it was possible to compare emissions in the early and late dry season at one site, it was speculated that higher emissions at the late dry season may have been attributed to poorer diet quality. It is concluded that the micrometeorological methodology using open-path lasers can be successfully deployed in extensive grazing conditions to directly measure CH₄ emissions from cattle at a herd scale.     

Estimation of greenhouse gas emissions from sewer pipeline system

Purpose

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system.

Methods

The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis.

Results and discussion

The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 10⁴ t CO₂eq year^?1, 64.9%) is the most significant for total GHG emissions (5.65 × 10⁴ t CO₂eq year^?1) because a huge amount of CH₄ (3.51 × 10⁴ t CO₂eq year^?1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH₄ emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions.

Conclusions

This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

     

Opposing seasonal temperature dependencies of CO2 and CH4 emissions from wetlands

Wetlands are critically important to global climate change because of their role in modulating the release of atmospheric greenhouse gases (GHGs) carbon dioxide (CO₂) and methane (CH₄). Temperature plays a crucial role in wetland GHG emissions, while the general pattern for seasonal temperature dependencies of wetland CO₂ and CH₄ emissions is poorly understood. Here we show opposite seasonal temperature dependencies of CO₂ and CH₄ emissions by using 36,663 daily observations of simultaneous measurements of ecosystem-scale CO₂ and CH₄ emissions in 42 widely distributed wetlands from the FLUXNET-CH₄ database. Specifically, the temperature dependence of CO₂ emissions decreased with increasing monthly mean temperature, but the opposite was true for that of CH₄ emissions. Neglecting seasonal temperature dependencies may overestimate wetland CO₂ and CH₄ emissions compared to the use of a year-based static and consistent temperature dependence parameter when only considering temperature effects. Our findings highlight the importance of incorporating the remarkable seasonality in temperature dependence into process-based biogeochemical models to predict feedbacks of wetland GHG emissions to climate warming.     

Comparison of different modeling approaches to better evaluate greenhouse gas emissions from whole wastewater treatment plants

New tools are being developed to estimate greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs). There is a trend to move from empirical factors to simple comprehensive and more complex process‐based models. Thus, the main objective of this study is to demonstrate the importance of using process‐based dynamic models to better evaluate GHG emissions. This is tackled by defining a virtual case study based on the whole plant Benchmark Simulation Model Platform No. 2 (BSM2) and estimating GHG emissions using two approaches: (1) a combination of simple comprehensive models based on empirical assumptions and (2) a more sophisticated approach, which describes the mechanistic production of nitrous oxide (N₂O) in the biological reactor (ASMN) and the generation of carbon dioxide (CO₂) and methane (CH₄) from the Anaerobic Digestion Model 1 (ADM1). Models already presented in literature are used, but modifications compared to the previously published ASMN model have been made. Also model interfaces between the ASMN and the ADM1 models have been developed. The results show that the use of the different approaches leads to significant differences in the N₂O emissions (a factor of 3) but not in the CH₄ emissions (about 4%). Estimations of GHG emissions are also compared for steady‐state and dynamic simulations. Averaged values for GHG emissions obtained with steady‐state and dynamic simulations are rather similar. However, when looking at the dynamics of N₂O emissions, large variability (3–6 ton CO₂e day^?1) is observed due to changes in the influent wastewater C/N ratio and temperature which would not be captured by a steady‐state analysis (4.4 ton CO₂e day^?1). Finally, this study also shows the effect of changing the anaerobic digestion volume on the total GHG emissions. Decreasing the anaerobic digester volume resulted in a slight reduction in CH₄ emissions (about 5%), but significantly decreased N₂O emissions in the water line (by 14%). Biotechnol. Bioeng. 2012; 109: 2854–2863. © 2012 Wiley Periodicals, Inc.