The impact of uncertainties on predicted greenhouse gas emissions of dairy cow production systems

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Life cycle assessment of the energy consumption and GHG emissions of state-of-the-art automotive battery cell production

<p>Evaluating greenhouse gas (GHG) emissions at farm level is an important tool to mitigate climate change. Livestock account for 80% of the total GHG emissions in Uruguay, and beef cow-calf systems are possibly the largest contributors. In cow-calf grazing systems, optimizing forage allowance and grazing intensity may increase pasture productivity, reproductive performance, beef productivity, and possibly reduce GHG emissions. This study estimated GHG emissions per kg of live weight gain (LWG) and per hectare from 20 cow-calf systems in Uruguay, with different management practices. The GHG emissions were on average 20.8 kg CO<sub>2</sub>-e.kg LWG<sup>-1</sup>, ranging from 11.4 to 32.2. Beef productivity and reproductive efficiency were the main determinants of GHG emissions. Five farm clusters were identified with different productive and environmental efficiency by numerical classification of relevant variables. Improving grazing efficiency by optimizing the stocking rate and forage production can increase beef productivity by 22% and reduce GHG emissions per kg LWG by 28% compared to “low performance” management. Further improvements in reproductive efficiency can increase productivity by 41% and reduce GHG emissions per kg LWG by 23%, resulting in a “carbon smart” strategy. However, the most intensified farms with highest stocking rate and beef productivity, did not reduce GHG emissions per kg LWG, while increased GHG emissions per ha compared to the carbon smart. This analysis showed that it is possible to simultaneously reduce carbon footprint per kg and per ha, by optimizing grazing management. This study demonstrated that there is high potential to reduce cow-calf GHG emissions through improved grazing management.</p>

中国氮磷钾肥制造温室气体排放系数的估算

GHG emission factors developed for the collection, transport and landfilling of municipal waste in South African municipalities

Identifying effective agricultural management practices for climate change adaptation and mitigation: A win-win strategy in South-Eastern Australia

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Globally, agriculture is directly responsible for 14% of annual greenhouse gas(GHG) emissions and induces an additional 17% through land use change, mostlyin developing countries (Vermeulen et al 2012). Agricultural intensification andexpansion in these regions is expected to catalyze the most significant relativeincreases in agricultural GHG emissions over the next decade (Smith et al 2008,Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa andAsia are predominately managed by smallholders, with 80% of land holdingssmaller than ten hectares (FAO 2012). One can therefore posit that smallholderfarming significantly impacts the GHG balance of these regions today and willcontinue to do so in the near future.However, our understanding of the effect smallholder farming has on theEarth’s climate system is remarkably limited. Data quantifying existing andreduced GHG emissions and removals of smallholder production systems areavailable for only a handful of crops, livestock, and agroecosystems (Herrero et al2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteenstudies of nitrous oxide emissions from soils have taken place in sub-SaharanAfrica, leaving the rate of emissions virtually undocumented. Due to a scarcity ofdata on GHG sources and sinks, most developing countries currently quantifyagricultural emissions and reductions using IPCC Tier 1 emissions factors.However, current Tier 1 emissions factors are either calibrated to data primarilyderived from developed countries, where agricultural production conditions aredissimilar to that in which the majority of smallholders operate, or from data thatare sparse or of mixed quality in developing countries (IPCC 2006). For the mostpart, there are insufficient emissions data characterizing smallholder agricultureto evaluate the level of accuracy or inaccuracy of current emissions estimates.Consequentially, there is no reliable information on the agricultural GHG budgetsfor developing economies. This dearth of information constrains the capacity totransition to low-carbon agricultural development, opportunities for smallholdersto capitalize on carbon markets, and the negotiating position of developingcountries in global climate policy discourse.Concerns over the poor state of information, in terms of data availability andrepresentation, have fueled appeals for new approaches to quantifying GHGemissions and removals from smallholder agriculture, for both existing conditionsand mitigation interventions (Berry and Ryan 2013, Olander et al 2013).Considering the dependence of quantification approaches on data and the currentdata deficit for smallholder systems, it is clear that in situ measurements must bea core part of initial and future strategies to improve GHG inventories and

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

Improving the accuracy of greenhouse gas accounting for wastewater treatment plants: seasonal differences must not be overlooked.

Does increasing milk yield per cow reduce greenhouse gas emissions? A system approach

The temporal variation of greenhouse gas (GHG) emission in a petrochemical wastewater treatment plant (WWTP) was investigated in this study. Two approaches including an in-situ continuous monitoring and a typical grab sampling methods were also compared. The in-situ continuous monitoring method provided more detailed information regarding the temporal variations of GHG concentrations. A sufficient sampling frequency (e.g., once every 6 hours) for the grab sampling method is required to effectively resolve the diurnal variations of GHG concentrations. This study highlights significant diurnal variations of GHG concentrations in different wastewater treatment units. Only with proper and reliable sampling and analytical methods, it becomes possible to correctly identify the characteristics of GHG emissions and to develop strategies to curtail the GHG emissions from such an important source in response to regulatory measures and international treaties. This study revealed that N2O was the dominant species responsible for GHG emissions in the WWTP and the emission factors of CH4 and N2O were higher in the equalization tank and final sedimentation tank compared to other units. We further compared the GHG emission factors of this study with other literatures, showing that the GHG emission factors were lower than those measured in Netherlands, Australia, and IPCC, but similar to those measured in Japan.

The traditional upscaling approach to greenhouse gas (GHG) emission estimates of inland waters is imprecise, but more precise methods based on environmental drivers are a longstanding challenge. Mexico lacks GHG emission estimates for its inland waters, and only sparse but scientifically validated information is available. This study provides the first GHG emission estimates from Mexican inland waters using 4275 GHG flux measurements from 26 distinctive waterbodies and one local and another global surface area dataset (INEGI and HydroLAKES). GHG emission factors were calculated and subsequently upscaled to estimate total national GHG emissions from the inland waters and compare to other emission measures based on mean global emission factors or size-productivity weighted (SPW) models. Mean (standard error) annual fluxes from all inland waters were 2.2 (5.3) kg CO2 m−2 yr−1, 0.6 (1.14) kg CH4 m−2 yr−1, and 1.0 × 10−3 (6.0 × 10−4) kg N2O m−2 yr−1. Estimates for natural waterbodies are annual average release rates between 74 (87) and 139 (163.23) Tg CO2eq while artificial waterbodies reach between 32 (2) and 21 (21) Tg CO2eq according to INEGI and HydroLAKES datasets, respectively. Considerable uncertainty was determined in the calculated mean emission factor, mostly for anthropogenic emissions. Waterbody area and chlorophyll a concentration were used as proxies to model CO2 and CH4 fluxes through regression analysis. According to SPW and IPCC models, computed mean annual CH4 emission factors were close to our estimates and exhibited a strong influence from eutrophication. In a likely scenario of increased eutrophication in Mexico, an increase in total net emissions from inland waters could be expected.

<p><strong>Background</strong>. Feeding cattle in small-scale silage-based dairy production systems can improve their production efficiency while reducing greenhouse gas emissions. <strong>Objective</strong>. To determine the effect of partial replacement of corn silage with sorghum silage on the concentration of secondary metabolites in terms of Total Phenols (TP), Total Tannins (TT), and Condensed Tannins (CT), as well as to estimate methane (CH4) and carbon dioxide (CO2) emissions. <strong>Methodology</strong>. The treatments were analyzed with a split-plot experimental design where the treatments (main plot) were; T1 = 50% sorghum silage cv Top Green + 50% corn silage, T2 = 50% sorghum silage cv Caña Dulce + 50% corn silage, T3 = 100% corn silage cv Cenzontle (control), and the measurement periods were the minor plots. <strong>Results</strong>. Inclusion of sorghum silage decreased enteric methane and carbon dioxide emissions (P<0.05), even though the concentration of phytochemical compounds among cultivars was not variable (P>0.05). <strong>Implications</strong>. Understanding the impact of changing forage chemical composition on reducing greenhouse gas (GHG) emissions in dairy systems is an important issue for mitigating climate change. <strong>Conclusions</strong>. The inclusion of sorghum silage in this study slightly reduced enteric methane and carbon dioxide emissions. Under these conditions, it is suggested that more information be provided on greenhouse gas emission factors and mitigation strategies in small-scale production systems.</p>

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third