Evaluation of greenhouse gas emission risks from storage of wood residue

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 ...

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).

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Legislation to cap and trade greenhouse gas (GHG) emissions was approved by a 219-212 vote of the United States House of Representatives on June 26, 2009. Cap and trade policy articulated in the American Clean Energy and Security (ACES) act of 2009 regulates GHGs including carbon dioxide, methane, nitrous oxide, sulfur hexafluoride, hydrofluorocarbons, perfluorocarbons and nitrogen trifluoride. Debate over the ACES act focused heavily on economic issues contrasted against concerns about climate change1. However, discussion largely ignored the potential for cap and trade legislation to contribute to reductions in levels of other harmful air pollutants, such as sulfur dioxide, particulate matter, and ozone precursors that share emission sources with GHGs. Under the bill, domestic GHG emissions are to be capped at 2005 annual levels, and reduced to 17% of those marks by 20502. The bill provides for an initial round of pollution permits to be made available, some free, others at auction. Subsequently, these permits can be bought and sold in the open market by organizations such as utility companies and manufacturing firms. A key provision in the ACES act requires the president to impose tariffs on countries that do not implement similar regulations on GHG emissions. While other potentially viable legislation, such as a tax on carbon emissions, has been proposed3, the current cap and trade legislation is the first bill to pass in either the House or Senate. The greenhouse gases regulated under the ACES act do not generally pose serious direct health risks. For example, nitrous oxide is used in dental procedures, and carbon dioxide is an ingredient in carbonated beverages. Other GHGs, like nitrogen trifluoride and sulfur hexafluoride, are not harmful at their current concentration levels, but can be hazardous to persons working with them if safety precautions are not taken. Instead, substantial human health benefits from cap and trade legislation could potentially come from reductions in ambient levels of harmful pollutants, such as particulate matter and ozone, that share emissions sources with GHGs. For example, 94% of CO2 emissions in the US result from combustion of fossil fuels, with electricity generation and transportation alone comprising nearly 70%. These are also the leading source of sulfur dioxide, fine particles having diameter small than 2.5 micrometers (PM2.5), and precursors to ozone such as mono-nitrogen oxides (NOx)4. While the time scale for potential impacts of cap and trade legislation on climate change and related health benefits is likely decades or centuries, ancillary air pollution mitigation could have immediate health benefits. In two nationwide epidemiological studies, daily levels of ambient ozone and PM2.5 have been linked to increased risk of cardiovascular and respiratory mortality5 and to increased risk of emergency hospital admissions, especially for heart failure6, respectively. Estimates of the potential health benefits attributable to reductions in harmful air pollutants resulting from mitigation of GHG emissions, at the city, region and national, have been substantial7. While US cap and trade legislation would likely reduce domestic air pollution levels, two caveats deserve consideration. First, methods for reducing GHG emissions typically reduce air pollution levels, but not always. This problem can be highlighted using airplanes as an example8. Two methods to reduce CO2 emissions from airplanes are to decrease aircraft weight or increase engine combustion temperatures. The former reduces both GHG and air pollution emissions, whereas the later reduces GHG emissions at the cost of increasing precursors to ozone. In the broader context of energy production, it is likely cap and trade legislation would drive a shift away from fossil fuel combustion to sources such as solar technology that produce much less air pollution. However, the exact technology development path is still uncertain. A second problem is the potential for domestic cap and trade legislation to transfer US emissions to newly industrialized nations. Countries facing lower production costs associated with looser regulations on GHG emissions would have an economic advantage over manufacturing industries in the US. However, increased air pollution from new manufacturing could be a key public health issue for developing regions, such as China's Pearl River delta, where air pollution levels are already much higher than standards in the US9. The economic and physical systems that would be affected by cap and trade legislation are extremely complex, and impacts on air pollution will have to be considered in a broad context. For example, while the absence of tariffs would likely push manufacturing, air pollution and related negative health effects to developing regions, those regions might experience health benefits associated with increased per capita income. The discussion is similarly complex in the physical domain. For example, some air pollutants, such as sulfate particulate matter, can contribute to short term climate cooling. Though still somewhat unclear, there is an emerging debate over the possibility that air pollution mitigation could actually exacerbate global warming in the short term10. While it faces potentially significant opposition and alteration in the Senate, the cap and trade bill recently passed in the House has progressed further through Congress than any other similar legislation. There is tremendous potential for legislation regulating GHG emissions, via cap and trade or other strategies, to simultaneously decrease emissions of harmful air pollutants and reduce morbidity and mortality attributable to cardiovascular and respiratory illness. Such improvements in public health have been linked to economic benefits from recovered workforce productivity8, and add important support for progress on cap and trade legislation versus delayed action.

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

Greenhouse gas (GHG) emissions from agricultural production operations are recognized as an important air quality issue. A new technique following the U.S. Environmental Protection Agency Method TO-14A was used to measure GHG emissions from ground-level area sources (GLAS) in a free-stall dairy operation in central Texas. The objective of this study was to quantify and report GHG emission rates (ERs) from the dairy during the summer and winter using this protocol. A weeklong sampling was performed during each season. A total of 75 and 66 chromatograms of air samples were acquired from six delineated GLAS (loafing pen, walkway, barn, silage pile, settling basin, and lagoon) of the same dairy during summer and winter, respectively. Three primary GHGs—methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O)—were identified from the dairy operation during the sampling periods. The estimated overall ERs for CH4, CO2, and N2O during the summer for this dairy were 274, 6005, and 7.96 g head−1day−1, respectively. During the winter, the estimated overall CH4, CO2, and N2O ERs were 52, 7471, and 3.59 g head−1day−1, respectively. The overall CH4 and N2O ERs during the summer were approximately 5.3 and 2.2 times higher than those in the winter for the free-stall dairy. These seasonal variations were likely due to fluctuations in ambient temperature, dairy manure loading rates, and manure microbial activity of GLAS. The annualized ERs for CH4, CO2, and N2O for this dairy were estimated to be 181, 6612, and 6.13 g head−1day−1, respectively. Total GHG emissions calculated for this dairy with 500 cows were 2250 t of carbon dioxide equivalent (CO2e) per year. IMPLICATIONS The agricultural sector, especially concentrated animal feeding operations (CAFOs) contribute a considerable amount of GHGs to the atmosphere. To develop abatement strategies to reduce GHG emissions, it is important to learn to collect, analyze, verify, and report real data on actual emissions. Therefore, there is a need for a robust and accurate technique/protocol to measure GHGs from CAFOs. It is important to obtain direct estimates of GHG emissions from different GLAS in CAFOs to compile emission inventories and to develop GLAS-specific abatement strategies.

Energy consumption and the concomitant Green House Gases (GHG) emissions of network infrastructures are becoming major issues in the Information and Communication Society (ICS). Current optical network infrastructures (routers, switches, line cards, signal regenerators, optical amplifiers, etc.) have reached huge bandwidth capacity but the development has not been compensated adequately as for their energy consumption. Renewable energy sources (e.g. solar, wind, tide, etc.) are emerging as a promising solution both to achieve drastically reduction in GHG emissions and to cope with the growing power requirements of network infrastructures. The main contribution of this paper is the formulation and the comparison of several energy-aware static routing and wavelength assignment (RWA) strategies for wavelength division multiplexed (WDM) networks where optical devices can be powered either by renewable or legacy energy sources. The objectives of such formulations are the minimization of either the GHG emissions or the overall network power consumption. The solutions of all these formulations, based on integer linear programming (ILP), have been observed to obtain a complete perspective and estimate a lower bound for the energy consumption and the GHG emissions attainable through any feasible dynamic energy-aware RWA strategy and hence can be considered as a reference for evaluating optimal energy consumption and GHG emissions within the RWA context. Optimal results of the ILP formulations show remarkable savings both on the overall power consumption and on the GHG emissions with just 25% of green energy sources. © 2011 IEEE.

Total Intravenous Anesthetic Versus Inhaled Anesthetic: Pick Your Poison.

BackgroundPolicies to mitigate climate change by reducing greenhouse gas (GHG) emissions can yield public health benefits by also reducing emissions of hazardous co-pollutants, such as air toxics and particulate matter. Socioeconomically disadvantaged communities are typically disproportionately exposed to air pollutants, and therefore climate policy could also potentially reduce these environmental inequities. We sought to explore potential social disparities in GHG and co-pollutant emissions under an existing carbon trading program—the dominant approach to GHG regulation in the US and globally.Methods and findingsWe examined the relationship between multiple measures of neighborhood disadvantage and the location of GHG and co-pollutant emissions from facilities regulated under California’s cap-and-trade program—the world’s fourth largest operational carbon trading program. We examined temporal patterns in annual average emissions of GHGs, particulate matter (PM2.5), nitrogen oxides, sulfur oxides, volatile organic compounds, and air toxics before (January 1, 2011–December 31, 2012) and after (January 1, 2013–December 31, 2015) the initiation of carbon trading. We found that facilities regulated under California’s cap-and-trade program are disproportionately located in economically disadvantaged neighborhoods with higher proportions of residents of color, and that the quantities of co-pollutant emissions from these facilities were correlated with GHG emissions through time. Moreover, the majority (52%) of regulated facilities reported higher annual average local (in-state) GHG emissions since the initiation of trading. Neighborhoods that experienced increases in annual average GHG and co-pollutant emissions from regulated facilities nearby after trading began had higher proportions of people of color and poor, less educated, and linguistically isolated residents, compared to neighborhoods that experienced decreases in GHGs. These study results reflect preliminary emissions and social equity patterns of the first 3 years of California’s cap-and-trade program for which data are available. Due to data limitations, this analysis did not assess the emissions and equity implications of GHG reductions from transportation-related emission sources. Future emission patterns may shift, due to changes in industrial production decisions and policy initiatives that further incentivize local GHG and co-pollutant reductions in disadvantaged communities.ConclusionsTo our knowledge, this is the first study to examine social disparities in GHG and co-pollutant emissions under an existing carbon trading program. Our results indicate that, thus far, California’s cap-and-trade program has not yielded improvements in environmental equity with respect to health-damaging co-pollutant emissions. This could change, however, as the cap on GHG emissions is gradually lowered in the future. The incorporation of additional policy and regulatory elements that incentivize more local emission reductions in disadvantaged communities could enhance the local air quality and environmental equity benefits of California’s climate change mitigation efforts.

All material supplied via Jukuri is protected by copyright and other intellectual property rights. Duplication or sale, in electronic or print form, of any part of the repository collections is prohibited. Making electronic or print copies of the material is permitted only for your own personal use or for educational purposes. For other purposes, this article may be used in accordance with the publisher's terms. There may be differences between this version and the publisher's version. You are advised to cite the publisher's version. This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail.

The world population is expected to grow to about 10 billion in 2050. To supply the future human population with food while sustaining a liveable planet, food should be produced sustainably. One of the most urgent environmental issues is climate change, induced by greenhouse gas (GHG) emissions. The dairy sector is a large contributor to GHG emissions. Important GHGs related to milk production are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), mainly emitted during feed production, enteric fermentation, and manure management. Diseases in dairy cows can reduce milk production, reproduction performance and longevity, and increase the amount of discarded milk. The objectives of this thesis were to estimate the impact of diseases (subclinical ketosis, clinical mastitis, and foot lesions) on GHG emissions, and to understand the relation between impact of diseases on GHG emissions and economic performance. First, a dynamic stochastic simulation model was developed to simulate the dynamics of the diseases and the associated production losses (reduced milk production, discarded milk, a prolonged calving interval, and removal (culling or dying on the farm)) per cow during one lactation. This model was combined with a life cycle assessment to quantify the impact of diseases on GHG emissions per ton fat-and-protein-corrected milk (kg CO2equivalents/t FPCM) from cradle to farm gate. Processes included were feed production, enteric fermentation, and manure management. The emissions of GHGs of cows with a disease increased on average by 21 (2.3%) kg CO2e/t FPCM per case of subclinical ketosis, by 58 (6.2%) kg CO2e/t FPCM per case of clinical mastitis, by 4 (0.4%) kg CO2e/ t FPCM per case of digital dermatitis, by 39 (4.3%) kg CO2e/ t FPCM per case of white line disease, and by 33 (3.6%) kg CO2e/ t FPCM per case of sole ulcer. An economic analyses was performed to estimate the costs of subclinical ketosis and related diseases. The total costs of subclinical ketosis were €130 per case per year. Comparing the impact of production contributors from a GHG emissions and economic perspective showed that a reduction in milk production had the highest impact on the economic performance, whereas removal and discarded milk had the highest impact on increase in GHG emissions. Prevalence, pathogen type, farm management (e.g. culling, feed, and manure), and prices (e.g. milk and feed) will affect the impact of production contributors on GHG emissions and economic performance. Therefore, specific farm analyses are needed to estimate the impact of diseases for a specific dairy farm. Diseases in dairy cows increase GHG emissions by approximately 0.4 Mton per year, which equals 15% of the Dutch governmental goal of GHG emission reductions in agriculture in 2030. Reducing diseases can decrease GHG emissions, can increase the income of the farmer, and can improve animal welfare. Therefore, reducing diseases can contribute to sustainable development of the dairy sector.

Delaware’s (DE) Climate Action Plan lays out a pathway to reduce greenhouse gas (GHG) emissions by at least 26% by 2025 but does not consider soil-based GHG emissions from land conversions. Consequently, DE’s climate action plan fails to account for the contribution of emissions from ongoing land development economic activity to climate change. Source attribution (SA) is a special field within the science of climate change attribution, which can generate “documentary evidence” (e.g., GHG emissions inventory, etc.). The combination of remote sensing and soil information data analysis can identify the source attribution of GHG emissions from land conversions for DE. Traditional attribution science starts with climate impacts, which are then linked to source attribution of GHG emissions. The most urgent need is not only to detect climate change impacts, but also to detect and attribute sources of climate change impacts. This study used a different approach that quantified past soil GHG emissions which are then available to support impact attribution. Study results provide accurate and quantitative spatio-temporal source attribution for likely GHG emissions, which can be included in the DE’s climate action plan. Including the impact of land conversion on GHG emissions is critical to mitigating climate impacts, because without a more complete source attribution it is not possible to meet overall emission reduction goals. Furthermore, the increased climate change impacts from land conversions are in a feedback loop where climate change can increase the rates of GHG emissions as part of these conversions. This study provides a spatially explicit methodology that could be applied to attribute past, future, or potential GHG emission impacts from land conversions that can be included in DE’s GHGs inventory and climate impact assessment.

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

Imposing versus Enacting Commitments for the Long‐Term Energy Transition: Perspectives from the Firm

During the last decade, developing more sustainable transportation modes has become a primary objective for car manufacturers and governments around the world to mitigate environmental issues, such as climate change, the continuous increase in greenhouse gas (GHG) emissions, and energy depletion. The use of hydrogen fuel cell technology as a source of energy in electric vehicles is considered an emerging and promising technology that could contribute significantly to addressing these environmental issues. In this study, the effects of Hydrogen Fuel Cell Battery Electric Vehicles (HFCBEVs) on global GHG emissions compared to other technologies, such as BEVs, were determined based on different relevant factors, such as predicted sales for 2050 (the result of the developed prediction model), estimated daily traveling distance, estimated future average global electricity emission factors, future average Battery Electric Vehicle (BEV) emission factors, future global hydrogen production emission factors, and future average HFCBEV emission factors. As a result, the annual GHG emissions produced by passenger cars that are expected to be sold in 2050 were determined by considering BEV sales in the first scenario and HFCBEV replacement in the second scenario. The results indicate that the environmental benefits of HFCBEVs are expected to increase over time compared to those of BEVs, due to the eco-friendly methods that are expected to be used in hydrogen production in the future. For instance, in 2021, HFCBEVs could produce more GHG emissions than BEVs by 54.9% per km of travel, whereas in 2050, BEVs could produce more GHG emissions than HFCBEVs by 225% per km of travel.