Analysis of Carbon Footprint Applied to Conceptual Engineering of Offshore Production Units

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).

Regional inventory of methane and nitrous oxide emission from ruminant livestock in the Basque Country

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

A new protocol similar to EPA method TO-14A was used to quantify and report variations in odorous volatile organic compound (VOC) and greenhouse gas (GHG) emissions from different ground level area sources (GLAS) namely feedlot, compost piles and lagoon in a beef feedyard in Texas Panhandle. The objective of this study was to measure gas concentrations and estimate emission factors (EFs) of phenol, p-cresol, methane (CH4), and carbon dioxide (CO2) from this beef feedyard operation. A week-long sampling was conducted and a total of 46 VOCs and 83 GHGs were sampled simultaneously from different GLAS. Thirteen VOCs were identified during sampling period and the gas chromatograph (GC) was calibrated for phenol and p-cresol, the primary compounds found. The GHG GC was calibrated for CH4, CO2, and nitrous oxide (N2O). In the beef feedyard, average measured concentrations of phenol and p-cresol in four corners of the feedlot ranged from 56 to 300 ppbv and 14 to 76 ppbv, respectively. Measured average concentrations for CH4 and CO2 in four pens ranged from 3.6 to 39.6 ppmv and 561 to 626 ppmv, respectively. Average phenol EFs were 0.131±0.111, 0.005±0.002, and 0.001±0.000 kg hd-1 yr-1 from feedlot, compost piles, and lagoon, respectively. Estimated average p-cresol EFs were 0.045±0.036, 0.002±0.001, and 0.0002±0.00004 kg hd-1 yr-1 from feedlot, compost piles, and lagoon, respectively. The overall estimated EFs for phenol and p-cresol were 0.137±0.113 and 0.047±0.037 kg hd-1 yr-1, respectively, during summer. The feedlot alone contributed about 95% of the overall phenol and p-cresol emissions for this feedyard. The overall estimated CH4 and CO2 EFs were 2.18±2.98 and 386±157 kg hd-1 yr-1, respectively. During summer, the feedlot alone contributed about 73% and 82% of the overall CH4 and CO2 emissions from this feedyard.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Quantifying greenhouse gas (GHG) emissions in the waste sector is important to evaluating measures for reduction of GHG emissions. To forecast GHG emissions and identify potential emission reduction for GHG emissions, scenarios applied with environmental policy such as waste reduction and structural change of waste treatment were developed. Scenario I estimated GHG emissions under the business as usual (BAU) baseline. Scenario II estimated GHG emissions with the application of the waste reduction policy while scenario III was based on the policy of structural change of waste treatment. Scenario IV was based on both the policies of waste reduction and structural change of waste treatment. As for the different scenarios, GHG emissions were highest under scenarios III, followed by scenarios IV, I, and II. In particular, GHG emissions increased under scenario III due to the increased GHG emissions from the enhanced waste incineration due to the structural change of waste treatment. This result indicated that the waste reduction is the primary policy for GHG reduction from waste. GHG emission from landfill was higher compared to those from incineration. However, the contribution of GHG emission from incineration increased under scenario III and IV. This indicated that more attention should be paid to the waste treatment for incineration to reduce GHG emissions.

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

The quantification of greenhouse gas (GHG) emissions is increasingly important in spatial planning for regions, cities, and areas. The combination of territorial and consumption-based accounting (CBA) approaches can currently be considered best practice for calculating GHG emissions at sub-national levels, in terms of informing local decision-making about the different climate impacts of spatial planning policies, both within the boundaries of a given region and for the inhabitants of that region. This study introduces four European case studies that were conducted using the two quantification approaches to assess the climate impacts of locally relevant planning policies. The case studies represent different scales of spatial planning, different European planning systems, and different situations in terms of data availability. Territorial results are not suitable for inter-regional comparison, but rather for internal monitoring, while CBA allows for comparison and provides a comprehensive picture of the global carbon footprint of residents, however, with indications that are more difficult to link to spatial planning decisions. Assessing impacts, and in particular interpreting results, requires both methodological understanding and knowledge of the local context. The results of the case studies show that setting climate targets and monitoring the success of climate action through a single net emissions figure can give false indications. The study shows that the two approaches to quantifying GHG emissions provide complementary perspectives on GHG emissions at the sub-national level and thus provide a more thorough understanding of the GHG emission patterns associated with spatial planning policies. The identification of the regional differences in GHG emission sources and mitigation potentials are the main functions of sub-national GHG inventories and the impact assessment for spatial planning. Harmonization of the data collection for sub-national GHG inventories and the transparency of underlying assumptions would greatly support the coherence of climate action and the implications to spatial planning.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

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.

Oil and gas (O&G) production activities emits greenhouse gases (GHG) which must be well estimated to improve accountability and formulating efficient mitigation. The Indonesia’s GHG emission reported thru Nationally Determined Contribution (NDC) was estimated by Tier-1 Intergovernmental Panel on Climate Change (IPCC) method, while the O&G company adopts different methodology. This leads to asynchronous GHG emission contribution of this industry to national GHG emission. This paper aims to estimate the GHG inventory from O&G offshore production facility by using American Petroleum Institute (API) Compendium Methodology and compare it with Tier-1 IPCC Methodology. It found that GHG emission estimated by API method is significantly lower than IPCC method. Both methods shown fuel combustion sources are the dominant. GHG emission sources from fuel combustion and flaring have been well identified, but emission sources from venting and fugitive need to be improved. Moreover this study identified that to have more accurate national GHG inventory, the GHG calculation method might be different for each industry segment. This evaluation could improve the future national GHG inventory and as reference for the industry. National emission factors database for O&G industry segment is highly suggested to be developed.

With the pressure of energy shortage rising and climate change looming as an imminent disaster, it is up to individual corporate entities to set the pace for climate change action. A good action plan relies heavily on climate knowledge and basis quantification. After the Copenhagen climate summit in 2009, the quantification of greenhouse gases (GHG) emission became the key issue in climate change-mitigation strategy, and was an especially key issue in the negotiations between China and the USA. This report addresses the issue of GHG quantification by demonstrating the potential effectiveness of the Energy and Climate Registry (ECR) that was launched in 2009 in China to help entities input, calculate, analyze, third-party verify and report the energy consumption and GHG emission in China. The ECR is an adaptation of the North American Climate Registry based in Los Angeles, USA. The system will play a pilot role for entities and allow them to measure energy consumption and GHG emissions in an accurate, consistent and verifiable way. This is the first step towards better energy management and the reduction of GHG emissions.

Chapter 10 - Integrating Greenhouse Gas Emissions Management into Capital Projects Planning

In recent years, energy consumption and associated Greenhouse Gas (GHG) emissions and their potential effects on the global climate change have been increasing. Climate change and global warming has been the subject of intensive investigation provincially, nationally, and internationally for a number of years. While the complexity of the global climate change remains difficult to predict, it is important to develop a system to measure the amount of GHG released into the environment. Thus, the purpose of this chapter is to demonstrate how several methods can accurately estimate the true GHG emission reduction potential from renewable technologies and help achieve the goals set out by the Kyoto Protocol reducing fuel consumption and related GHG emissions, promoting decentralization of electricity supply, and encouraging the use of renewable energy technologies. There are several methods in estimating emission factors from facilities: direct measurement, mass balance, and engineering estimates. Direct measurement involves continuous emission monitoring throughout a given period. Mass balance methods involve the application of conservation equations to a facility, process, or piece of equipment. Emissions are determined from input/output differences as well as from the accumulation and depletion of substances. The engineering method involves the use of engineering principles and knowledge of chemical and physical processes (EnvCan, 2006). In Guler (2008) the method used to estimate emission factors considers only the total amount of fuel and electricity produced from power plants. The previous methodology does not take into consideration the offset cyclical relationship, daily and yearly, between electricity generated by renewable technologies. It should be noted that none of the methods mentioned above include seasonal/daily adjustments to annual emission factors. Specifically, the proposed research would include analyzing existing methods in calculating emission factors and attempt to estimate new emission factors based on the hourly electricity demand for the Province of Ontario. In this Chapter, several GHG emission factor methodology was discussed and compared to newly developed monthly emission factors in order to realize the true CO2 reduction potential for small scale renewable energy technologies. The hourly greenhouse gas emission factors based on hour-by-hour demand of electricity in Ontario, and the average Greenhouse Gas Intensity Factor (GHGIFA) are estimated by creating a series of emission factors and their corresponding profiles that can be easily incorporated into simulation

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia