An Environmental and Economic Evaluation of Pyrolysis for Energy Generation in Taiwan with Endogenous Land Greenhouse Gases Emissions

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).

As traditional petroleum supplies dwindled and prices soared over the past few years, oil companies have shifted their attention to oil sands, a mix of sand, water, and a heavy, viscous hydrocarbon called bitumen that can be converted to oil. With the plunge in oil prices in fall 2008, many producers began canceling or postponing plans to expand oil sands development projects, but this turn of events could yet reverse, as Canada’s vast oil sands deposits are lauded as a secure source of imported oil for the United States. At the same time, however, oil sands present troubling questions in terms of the environmental health effects associated with their development.

Greenhouse gas (GHG) emission inventory has always been considered a crucial first step towards any development of climate change mitigation plans and measures. In this paper, the Bilan Carbone (Carbon Balance) version 6, an easy-to-use Excel-based GHG inventory tool developed by the French Environment and Energy Management Agency, is used to make an inventory of GHG emissions generated within Can Tho City’s territory. The data used for the direct and indirect GHG emissions were collected from Can Tho City’s 2020 Statistical Yearbook, relevant businesses, and administrative units. Ten sectors, namely Energy Industry, Industrial Processes, Tertiary Sector, Residential Sector, Agriculture and Fishing, Transporting Goods, Travel by People, Construction and Highways, End-of-life Waste, and Food, were taken into account for the related analysis. Considering all GHGs cited in the Kyoto Protocol coupled with emission factors updated for Vietnam and the magnitude of emission sources, we found out that the total GHG emission of Can Tho City in 2020 is 4,311,952 tons of CO2 equivalent (CO2e) with an average of approximately 3.5 tons of CO2e per capita. Residential Sector, Industrial Processes, and Travel by People contribute the most to the total GHG footprint of the city, in which Residential Sector accounts for the largest share (743,346 tons of CO2e, making up 17.2% of the total GHG emission). Industrial Processes ranks second with 727,504 tons of CO2e (representing 16.9%), and Travel by People is third with 619,823 tons of CO2e, accounting for 14.4%. Some scientific and realistic interpretations of such sectorial findings are also provided to facilitate the next step of initiating and carrying out associated GHG mitigation measures for the city.

Greenhouse gas (GHG) emissions must be precisely estimated in order to predict climate change and achieve environmental sustainability in a country. GHG emissions are estimated using empirical models, but this is difficult since it requires a wide variety of data and specific national or regional parameters. In contrast, artificial intelligence (AI)-based methods for estimating GHG emissions are gaining popularity. While progress is evident in this field abroad, the application of an AI model to predict greenhouse gas emissions in Saudi Arabia is in its early stages. This study applied decision trees (DT) and their ensembles to model national GHG emissions. Three AI models, namely bagged decision tree, boosted decision tree, and gradient boosted decision tree, were investigated. Results of the DT models were compared with the feed forward neural network model. In this study, population, energy consumption, gross domestic product (GDP), urbanization, per capita income (PCI), foreign direct investment (FDI), and GHG emission information from 1970 to 2021 were used to construct a suitable dataset to train and validate the model. The developed model was used to predict Saudi Arabia’s national GHG emissions up to the year 2040. The results indicated that the bagged decision tree has the highest coefficient of determination (R2) performance on the testing dataset, with a value of 0.90. The same method also has the lowest root mean square error (0.84 GtCO2e) and mean absolute percentage error (0.29 GtCO2e), suggesting that it exhibited the best performance. The model predicted that GHG emissions in 2040 will range between 852 and 867 million tons of CO2 equivalent. In addition, Shapley analysis showed that the importance of input parameters can be ranked as urbanization rate, GDP, PCI, energy consumption, population, and FDI. The findings of this study will aid decision makers in understanding the complex relationships between the numerous drivers and the significance of diverse socioeconomic factors in defining national GHG inventories. The findings will enhance the tracking of national GHG emissions and facilitate the concentration of appropriate activities to mitigate climate change.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms

Sweetness and Power - Public Policies and the ‘Biofuels Frenzy’

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

Effect of greenhouse gas emissions on the life cycle of biomass energy production and conversion under different straw recycling modes

Nowadays, the global climate change has been a worldwide concern and the greenhouse gases (GHG) emissions are considered as the primary cause of that. The United Nations Conference on Environment and Development (UNCED) divided countries into two groups: Annex I Parties and Non-Annex I Parties. Since Iran and all other countries in the Middle East are among Non-Annex I Parties, they are not required to submit annual GHG inventory report. However, the global climate change is a worldwide phenomenon so Middle Eastern countries should be involved and it is necessary to prepare such a report at least unofficially. In this paper the terminology and the methods to calculate GHG emissions will first be explained and then GHG emissions estimates for the Iranian power plants will be presented. Finally the results will be compared with GHG emissions from the Canadian electricity generation sector. The results for the Iranian power plants show that in 2005 greenhouse gas intensity for steam power plants, gas turbines and combined cycle power plants were 617, 773, and 462 g CO2eq/kWh, respectively with the overall intensity of 610 g CO2eq/kWh for all thermal power plants. This GHG intensity is directly depend on efficiency of power plants. Whereas, in 2004 GHG intensity for electricity generation sector in Canada for different fuels were as follows: Coal 1010, refined petroleum products 640, and natural gas 523 g CO2eq/kWh, which are comparable with same data for Iran. For average GHG intensity in the whole electricity generation sector the difference is much higher: Canada 222 vs. Iran 610g CO2eq/kWh. The reason is that in Canada a considerable portion of electricity is generated by hydro-electric and nuclear power plants in which they do not emit significant amount of GHG emissions. The average GHG intensity in electricity generation sector in Iran between 1995 and 2005 experienced 13% reduction. While in Canada at the same period of time there was 21% increase. However, the results demonstrate that still there are great potentials for GHG emissions reduction in Iran’s electricity generation sector.

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 ...

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

Problem statement: In recent years, Greenhouse Gas (GHG) emissions and their potential effects on global climate change have been a worldwide concern. According to International Energy Agency (IEA), power generation contributes more than half of the global GHG emissions. Approach: Purpose of this study is to examine GHG emission reduction potentials in the Canadian electricity generation sector through fuel switching and adoption of advanced power generation systems. To achieve this objective, eight different scenarios were introduced. In the first scenario, existing power stations’ fuel was switched to natural gas. Existing power plants were replaced by Natural Gas Combined Cycle (NGCC), Integrated Gasification Combined Cycle (IGCC), Solid Oxide Fuel Cell (SOFC), hybrid SOFC and SOFC-IGCC hybrid power stations in scenario numbers 2 to 6, respectively. In last two scenarios, CO2 capture systems were installed in the existing power plants and in the second scenario, respectively. Results: The results showed that Canada’s GHG emissions can be reduced by 33, 59, 20, 64, 69, 29, 86 and 94% based on the first to eighth scenarios, respectively. On the other hand, the second scenario is the most practical and its technology has already matured and is available. In this scenario by replacing existing power plants by NGCC power plants, Canada can fulfill more than 25% of its 238,000 kt year-1 commitment of GHG emission reduction to the Kyoto Protocol. In addition, the GHG emission reduction potentials for each province and Canada as a whole were presented and compared. Based on the results, Alberta, Ontario and Saskatchewan are the biggest producers of GHG in Canada by emitting 49, 21 and 14% of Canada’s GHG emissions, respectively. Therefore, they have higher potential to reduce GHG emissions. The comparison of the results for different provinces revealed that based on efficiency of electricity generation and consumed fuel distribution; specific scenario(s) tend to be suitable for each province. Conclusion: The results pointed out that despite of acceptable performance of some provinces, there are still great potentials to reduce GHG emission level in Canada. In addition, the economical analysis showed that some scenarios are economically competitive with current technologies and should be considered when a new power station is to be built.

The agricultural sector is the second most emitting sector globally, contributing about 18% of total global greenhouse gas (GHG) emissions. Multipurpose high in-demand commodities like palm oil contribute significantly to these emissions. The Roundtable on Sustainable Palm Oil (RSPO) with an objective to make the palm oil sector sustainable, developed a new tool to quantify carbon emissions from palm oil mills. The PalmGHG tool has been used in Southeast Asia to measure carbon emissions from palm oil production and for palm oil certification. However, no studies have used the tool to evaluate GHG emissions from palm oil mills in sub-Saharan Africa, which contributes about 24% of global palm oil production and is home to one of the last remaining primary forests in the world. In this study, we quantify GHG emissions along the crude palm oil (CPO) life cycle in a growing palm oil producing region in Cameroon. We use the RSPO PalmGHG accounting tool, to identify sources of CO2 emissions and quantify them in tons of CO2 equivalent. Six mills across the South West and Center regions of Cameroon were sampled. We found that the sources of carbon emissions from our sampled mills in decreasing order of magnitude are land conversion (78%), palm oil mill effluent (21%), fertilizer use (0.9%), mill fuel combustion (0.1%) and grid electricity utilization (0.04%). The average GHG emissions per ton of crude palm oil produced were exceptionally high at 22.3 tCO2e compared to other palm oil producing regions in the world such as Indonesia with only 1.6 tCO2e/ton of CPO. In addition, we found that planting oil palm on previously logged land instead of primary forest conversion could prevent field emissions by up to about 89% and by up to about 69% for replanting old oil palm stands. Intensification measures like improving palm oil mill extraction rates and improving yields would drastically reduce emissions per ton of crude palm oil produced. Although land conversion associated with deforestation remains the major source of palm oil GHG emissions, farm and mill practices such as reduction in fertilizer use, biogas capture and use of clean energy could help reduce emissions in the long run.

Greenhouse gas emissions from extractive industries in a globalized era