Greenhouse Gas Emission from Contrasting Management Scenarios in the Northern Corn Belt

A pilot scale composting plant has been established on-campus in Universiti Teknologi Malaysia (UTM) to achieve the goal as a sustainable campus. Portion of organic wastes were diverted from landfilling by converting it into compost (organic fertiliser) for reducing greenhouse gases (GHG) emission at the landfill and the dependency on inorganic fertiliser. Composting has been reported as a sustainable approach to reduce the footprint of GHG as compared to the waste disposal through landfilling. However, the amount of GHG emitted during composting can vary due to localised condition. The aim of this study was to assess the potential of composting in mitigating GHG emission compared to the current waste management employed in UTM (Landfilling). A business as usual (BAU) scenario represents the current organic waste management practice in UTM was established. Composting was proposed as an alternative scenario. The amount of GHG emitted or reduced from different sources including for transportation, waste processing, waste treatment as well as downstream activities such as carbon sequestration and inorganic fertiliser substitution was estimated based on lifecycle inventory analysis. The result indicated that composting scenario offer a GHG reduction of 66.72 % as compared to the BAU scenario. The fugitive emission from biodegradation of organic waste contributed significantly to the GHG emission for both scenarios whereas the GHG emission from the fossil fuel combustion was considered as not significant. The overall result suggested the potential of composting as a viable technology for sustainable organic waste management in UTM.

This paper presents a novel quantitative methodology for the evaluation and optimisation of the environmental impacts of the whole life cycle of a mega-event project: construction and staging the event and post-event site redevelopment and operation. Within the proposed framework, a mathematical model has been developed that takes into account greenhouse gas (GHG) emissions resulting from use of transportation fuel, energy, water and construction materials used at all stages of the mega-event project.The model is applied to a case study - the London Olympic Park. Three potential post-event site design scenarios of the Park have been developed: Business as Usual (BAU), Commercial World (CW) and High Rise High Density (HRHD). A quantitative summary of results demonstrates that the highest GHG emissions associated with the actual event are almost negligible compared to those associated with the legacy phase. The highest share of emissions in the legacy phase is attributed to embodied emissions from construction materials (almost 50% for the BAU and HRHD scenarios) and emissions resulting from the transportation of residents, visitors and employees to/from the site (almost 60% for the CW scenario). The BAU scenario is the one with the lowest GHG emissions compared to the other scenarios. The results also demonstrate how post-event site design scenarios can be optimised to minimise the GHG emissions. The overall outcomes illustrate how the proposed framework can be used to support decision making process for mega-event projects planning.

With light duty vehicles (LDVs) responsible for 17% of annual US greenhouse gas (GHG) emissions, integrating emerging GHG-reducing technologies into the fleet is essential. However, the slow rate of vehicle turnover presents a significant barrier to the market penetration of new technologies, with adoption delayed by the low number of vehicles needing replacement each year. A strategy of accelerated vehicle turnover through a vehicle lifespan cap could potentially mitigate this limit. While older studies reach differing conclusions on their effectiveness, two newer studies that incorporate life cycle assessment find that accelerated turnover strategies can be effective if coupled with high levels of electric vehicle deployment. We seek to determine whether a vehicle lifespan cap strategy can be an effective and efficient (cost-effective) method for reducing US LDV fleet GHG emissions. We augment the capabilities of the Fleet Life Cycle Assessment and Material Flow Estimation (FLAME) fleet life cycle assessment model, integrating vehicle lifespan caps and comprehensive calculations of cost along with sensitivity analysis for electric vehicle survival curves and battery degradation. The augmented FLAME model is used to analyse the impact of vehicle lifespan caps of varying lengths on a suite of scenarios, including a business as usual (BAU) scenario and eight scenarios modelling different technology improvement assumptions. This work confirms that vehicle lifespan caps have limited effectiveness in reducing GHG emissions under a BAU scenario but show potential to meaningfully reduce GHG emissions in a scenario with accelerated deployment of electric vehicles. However, abatement costs are high, exceeding 2020 USD 1000/tCO2eq under baseline assumptions, but falling within the range of current estimates of the social cost of carbon under more optimistic assumptions. Overall, vehicle lifespan caps must be carefully considered as they accelerate both the benefits and costs of new vehicle technologies, and are best positioned as part of a larger integrated strategy for tackling transportation GHG emissions.

Previous studies have evaluated the economics and ecosystem services of perennial bioenergy crops when replacing grain crops on marginal (environmentally critical and/or underproductive) lands. This study used life‐cycle analysis (LCA) to investigate the greenhouse gas (GHG) emissions of perennial crops when grown in targeted landscape positions and their impact in reducing nitrogen leaching. Specifically, LCA was performed to evaluate the GHG emissions of growing shrub willow on marginal lands in the Indian Creek watershed in Illinois to assess the sustainability of strategically planted willow buffer strips. Willow was grown as a short‐rotation woody crop with a 21‐year rotation under three scenarios including a business‐as‐usual (BAU) field‐scale production with nitrogen fertilizer application and two unfertilized subfield buffer scenarios – landscape single subfield (LSSF) or landscape multiple subfields (LMSF) – grown alongside cornfields to reduce nitrate leaching. Each scenario also considers three field sizes, 2.0, 10.1, and 40.5 ha. The average annual GHG emissions from willow production and depot transportation were 0.32–0.77 Mg‐CO2e ha−1 with the lowest emissions for the LSSF scenario and highest for the BAU. The GHG emissions for the LSSF and BAU scenarios are independent of field size, whereas LMSF emissions increase with increasing field size, 0.41 Mg‐CO2e ha−1 at 2.0 ha and 0.76 Mg‐CO2e ha−1 at 40.5 ha. Emission results were most sensitive to the willow yield, followed by fertilizer application rate (BAU only), harvest fuel consumption, and transportation distance. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd

Abstract. To track progress towards keeping global warming well below 2 ∘C or even 1.5 ∘C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO2 emissions, CH4 emissions, N2O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF6, NF3) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (∼ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO2 eq. consisting of CO2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO2, CO2-LULUCF 5.7 ± 4.0 GtCO2, CH4 10 ± 3.1 GtCO2 eq., N2O 2.6 ± 1.6 GtCO2 eq., and F-gases 1.3 ± 0.40 GtCO2 eq. Initial estimates suggest further growth of 1.3 GtCO2 eq. in GHG emissions to reach 59 ± 6.6 GtCO2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr−1) compared to 2000–2009 (2.4 % yr−1), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

Strategic Analysis of Most Energy and Emissions Intensive Sectors of India: Implications for Public Policy on Greenhouse Gas Emissions

ABSTRACTThis study aims at the development of Thailand’s low-carbon society in 2030 by using the Asia-Pacific Integrated Model/Extended Snap Shot model for analysis of greenhouse gas (GHG) mitigation through renewable energy (RE) utilization. This article presents the potentials of RE in power generation, industrial, and transport sectors in Thailand for GHG mitigation in 2030. The deployment of the RE sources is used in the analyses with potentials of mini-hydro of 390 MW, wind power of 960 MW, solar power of 600 MW, biomass energy of 4,400 MW, biogas power of 144 MW, waste to power of 192 MW, bioenergy of 4,634 ktoe, and RE for thermal of 8,088 ktoe in 2030. According to the proposed development, the amount of GHG emissions is estimated based on business-as-usual (BAU) without mitigation measures and countermeasures with GHG mitigation options of adopted RE technologies available during 2005–2030. Results show that annual GHG emissions in the base year of 2005 are 185,983 kt-CO2. In 2030 the GHG emissions in the BAU scenario will increase to 563,730 kt-CO2 or 3.03 times higher than the base year 2005. The GHG emissions in the 2030 can be decreased dramatically to 443,043 kt-CO2, and accounted for 21.4% of GHG reduction by deployment of RE technologies.

Assessing transition pathways to low-carbon electricity generation in Kenya: A hybrid approach using backcasting, socio-technical scenarios and energy system modelling

Carbon prices and greenhouse gases abatement from agriculture, forestry and land use in Nepal

Reducing greenhouse gas (GHG) emissions is a global concern after Paris Agreement (PA). Identification of GHG emission sources and accurate and precise estimation of the corresponding emissions is the first step to meet reduction targets under PA. Increasing share of agricultural emissions in the global concentration has raised concerns on this sector. Now, reducing agricultural emissions without compromising food security is a real challenge. The present study was aimed to provide the current emission profile of Pakistan’s agriculture, historical emission trends and future projections under agricultural growth scenarios according to prescribed guidelines of Intergovernmental Panel on Climate Change (IPCC) for national GHGs inventory development. In this study, GHG emissions were estimated using United Nations Framework Convention on Climate Change (UNFCCC) Non-Annex-I Inventory Software (NAIIS), version 1.3.2 as per prescribed Revised 1996 IPCC Guidelines. In these emission estimations, tier-1 approach (which employs default emission factors) was used in accordance with national circumstances and data availability in the country. The emissions baseline was projected for 2030 under business as usual (BAU), food security (FS) and enhanced consumption pattern (ECP) scenarios. Agriculture sector emitted 174.6 million tons (Mt) of carbon dioxide equivalent (CO2-equivalent) emissions, of which 89.8 Mt is methane (CH4) and 83.7 Mt is nitrous oxide (N2O). Carbon monoxide (CO) emissions were found to be 1.07 Mt of CO2-equivalent. Emission from agricultural soils constituted 45.5% of the total agricultural emissions followed by 45.1% from enteric fermentation and 6.5% from livestock manure management. The rest of 1.7% of the emissions were from rice cultivation followed by 1.1% from burning of crop residue. Historical emission trends showed that the agricultural emissions grew from 71.6 to 174.6 Mt of CO2-equivalent from 1994 to 2015, a 143.8% increase over the period of 21 years. Emissions baseline projections were found to be 271.9, 314.3 and 362.9 Mt tons of CO2-equivalent under BAU, FS and ECP scenarios, respectively.

This study investigated the scenarios of Greenhouse Gas (GHG) emission for Thailands textile industries between 2010 to 2030. GHG emission for Business as usual (BAU) Scenario is increasing from 5.10 to 11.72 Million tons carbon dioxide equivalent (tCO2eq) (approximately 4.3% per year). The IME scenario that new installation of high efficient equipment showed the GHG mitigate as 6.34% in 2030 compared with BAU scenario that including motor, compressor and boiler have contributed as 62.6, 30.6 and 6.8% of the GHG mitigation potential, respectively. On the other hand, the FS scenario which is switching from fuel oil to natural gas mitigates GHG emission as 0.97%.

Approximately 60 % of Beninese lack access to electricity, relying heavily on traditional energy sources, electricity imports, and low renewable energy integration. This study aims to forecast the energy demand for Benin while reducing greenhouse gas (GHG) emissions and propose alternative solutions to clean energy deployment barriers. The Low Emissions Analysis Platform (LEAP) is used to explore the future energy demand for Benin and associated GHG emissions. Four scenarios have been developed, namely Business as Usual (BAU), High Economic Development (HED), Electrification and Urbanization Growth (EUG), and High Efficient Energy Application (HEEA). In addition, the Fuzzy AHP and TOPSIS techniques have been employed to rank and prioritize alternative solutions to Renewable Energy (RE) deployment barriers in the country. A total of eighteen sub-barriers were identified and classified into five main categories under the four pillars of sustainability (technical, social, economic, and environmental), and nine strategies were identified and proposed to overcome the barriers. The results show that under the BAU scenario, the total energy demand is expected to reach 445 PJ in 2050 from the current demand of around 164 PJ. A total GHG emission of 21 MtCO2e is estimated under the BAU scenario in 2050. However, the HEEA scenario indicates that energy demand would considerably decrease resulting in low GHG emissions from the energy sector. The findings from the Fuzzy AHP ranking show that technical barriers, political and regulatory barriers, and financial and economic barriers, are the top three barriers hindering RE deployment in Benin. Moreover, adequate policy and regulatory framework emerges as the most weighted solution to eliminating barriers to RE deployment in the country. These results encourage the application of effective policy to support sustainable energy transition. The study's approach is applicable to other developing countries outside Benin, offering insights into RE barriers and potential alternative solutions.

Energy consumption and GHG emissions from China's freight transport sector: Scenarios through 2050

In 2014, Indonesia is reported as the world’s tenth largest economy in the world. With stable economic growth rate above 5 % per annum in the last 10 years, national energy demand is projected to increase from 712 million barrel of oil equivalent (BOE) in 2010 to 1.3 billion BOE in 2019. Indonesia is highly dependent on fossil fuel. The country has become a net importer of oil with 800,000 barrel oil per day imported that year. In order to reduce the burden of national budget for oil import, the government has established the national energy policy that shifts the main energy source from oil to other sources. It has also set up regulation for developing approximately 20,000 MW of coal-fired power plants (Fast Track Program Phases 1 and 2) at the expense of higher greenhouse gas (GHG) emissions. In order to provide an insight for government in developing a strategy for mitigating GHG emission, alternative scenarios of electricity planning are analyzed using the Indonesia Integrated Energy, Economic, and Environmental Modeling (I2E3M) software. The alternative scenarios include higher utilization of renewable energy and demand-side management program. The results confirm that limiting the GHG emission will increase the share of renewable energy in the primary energy mix for electricity generation. By setting GHG emission at 10 % lower than business as usual (BAU) case, the share of renewable energy will be increased to around 15 % in 2020. Moreover, the demand-side management program is another option in reducing GHG emission from electricity generation activities.

This paper assesses long-term energy consumption and greenhouse gas (GHG) emissions in Rayong Province which is one of the three provinces in the Eastern Economic Corridor (EEC) of Thailand. LEAP (the Low Emissions Analysis Platform) is used to project final energy demand for each economic sector by using the 2019 data as a base year. In the model, we defined the energy consumption into two scenarios; a business-as-usual (BAU) scenario and a low carbon scenario (LCS), to see different energy demand and CO2 emissions up to the year 2050. There are different assumptions between BAU and LCS in each sector such as energy efficiency improvement, shift to modern energy, the share of high energy-efficient vehicles, etc. In the BAU scenario, the final energy consumption needed by Rayong Province will increase with an average annual growth rate (AAGR) of 3.49%, while only 1.52% for the LCS. CO2 emissions in the LCS will be reduced by 41.7% by 2050 when compared with the BAU scenario. Most interestingly, even though energy demand in Rayong Province will be increasing up to 2050, CO2 emissions will peak about 2035 and then reduce. The industry and transport sectors are the most final energy consumption and the highest CO2 emissions. This is because EEC is driven by a production-based economy. The solution for this is to transform to alternative energies sourcing, shift all productions to sustainable ones, restructure the industrial estate to become the eco-industrial and GHG emissions management, which will also result in obvious carbon reduction. This kind of information will be beneficial to energy demand conservation and GHG emission mitigation at the provincial level which will depend on the energy policies initiated and implemented in the future.