Energy use and emissions scenarios for transport to gauge progress toward national commitments

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 ...

Solely economic mitigation strategy suggests upward revision of nationally determined contributions

The National Academies of Sciences, Engineering, and Medicine reports that 28 percent of energy used in the United States is for transportation, moving people and goods. Transport vehicles in this context include automobiles, motorcycles, trucks (light, medium, and heavy‐duty), buses, trains, aircraft, and watergoing vessels. Of these vehicles, approximately 58 percent of the related energy use is from cars, light‐duty trucks, and motorcycles, with the remaining shares being other trucks (23 percent), aircraft (8 percent), boats and ships (4 percent), and trains and buses (3 percent). Pipelines account for 4 percent of transportation energy use, transporting liquids and gases across the United States. It is worth noting that greenhouse gas (GHG) emissions reported by the US Environmental Protection Agency (EPA) are greatest in the transportation sector (29 percent), followed by electricity (28 percent), industry (22 percent), commercial and residential (22 percent), and agriculture (9 percent), as illustrated in Figure 1. This suggests, as many know, that any serious effort to reduce GHG emissions—as many states and municipalities and businesses and consumers have pledged—requires reducing energy use and, therefore, GHG emissions in the transportation sector.

Researchers at Argonne National Laboratory expanded the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model and incorporated the fuel economy and electricity use of alternative fuel/vehicle systems simulated by the Powertrain System Analysis Toolkit (PSAT) to conduct a well-to-wheels (WTW) analysis of energy use and greenhouse gas (GHG) emissions of plug-in hybrid electric vehicles (PHEVs). The WTW results were separately calculated for the blended charge-depleting (CD) and charge-sustaining (CS) modes of PHEV operation and then combined by using a weighting factor that represented the CD vehicle-miles-traveled (VMT) share. As indicated by PSAT simulations of the CD operation, grid electricity accounted for a share of the vehicle's total energy use, ranging from 6% for a PHEV 10 to 24% for a PHEV 40, based on CD VMT shares of 23% and 63%, respectively. In addition to the PHEV's fuel economy and type of on-board fuel, the marginal electricity generation mix used to charge the vehicle impacted the WTW results, especially GHG emissions. Three North American Electric Reliability Corporation regions (4, 6, and 13) were selected for this analysis, because they encompassed large metropolitan areas (Illinois, New York, and California, respectively) and provided a significant variation of marginal generation mixes. The WTW results were also reported for the U.S. generation mix and renewable electricity to examine cases of average and clean mixes, respectively. For an all-electric range (AER) between 10 mi and 40 mi, PHEVs that employed petroleum fuels (gasoline and diesel), a blend of 85% ethanol and 15% gasoline (E85), and hydrogen were shown to offer a 40-60%, 70-90%, and more than 90% reduction in petroleum energy use and a 30-60%, 40-80%, and 10-100% reduction in GHG emissions, respectively, relative to an internal combustion engine vehicle that used gasoline. The spread of WTW GHG emissions among the different fuel production technologies and grid generation mixes was wider than the spread of petroleum energy use, mainly due to the diverse fuel production technologies and feedstock sources for the fuels considered in this analysis. The PHEVs offered reductions in petroleum energy use as compared with regular hybrid electric vehicles (HEVs). More petroleum energy savings were realized as the AER increased, except when the marginal grid mix was dominated by oil-fired power generation. Similarly, more GHG emissions reductions were realized at higher AERs, except when the marginal grid generation mix was dominated by oil or coal. Electricity from renewable sources realized the largest reductions in petroleum energy use and GHG emissions for all PHEVs as the AER increased. The PHEVs that employ biomass-based fuels (e.g., biomass-E85 and -hydrogen) may not realize GHG emissions benefits over regular HEVs if the marginal generation mix is dominated by fossil sources. Uncertainties are associated with the adopted PHEV fuel consumption and marginal generation mix simulation results, which impact the WTW results and require further research. More disaggregate marginal generation data within control areas (where the actual dispatching occurs) and an improved dispatch modeling are needed to accurately assess the impact of PHEV electrification. The market penetration of the PHEVs, their total electric load, and their role as complements rather than replacements of regular HEVs are also uncertain. The effects of the number of daily charges, the time of charging, and the charging capacity have not been evaluated in this study. A more robust analysis of the VMT share of the CD operation is also needed.

Since the Paris Agreement in COP21, many countries around the world, including Ghana and Thailand, have established a Nationally Determined Contribution (NDC) to reduce greenhouse gas (GHG) emissions, with first update recently in COP26. With Ghana’s ongoing effort at COP26 to change its baseline to 2019, this study established a detailed Ghana vehicle ownership model with necessary transport parameters to construct an energy demand model to provide insight for reducing GHG emission contributions from road transport through biofuel (both bioethanol and biodiesel) potential by recourse to a Low Emission Analysis Platform (LEAP), with two scenarios of development from Thailand’s best practice for policy recommendation, which are alternative (ALT), with up to E20/B20, and extreme (EXT), with up to E85/B50, for new vehicles. In each case, energy demand and GHG emissions were analyzed from detailed data on Ghana’s transport sector to show potential benefit from biofuel usages. From Ghana’s transport sector contribution to NDC, 8.4% and 11.1% of GHG emission reduction in 2030 can be achieved with a 0.13% and 0.27% additional arable land requirement from ALT and EXT scenarios. Policy recommendation and implication were also discussed.

BackgroundThe Nationally Determined Contribution (NDC) of Thailand intends to reduce greenhouse gas (GHG) emissions by 20 to 25% from the projected business as usual level by 2030 with the deployment of renewable energy technologies and energy efficiency improvement measures in both the supply and demand sectors. However, in order to contribute towards meeting the long-term goal of the Paris Agreement to stay well below 2 °C, ambitious mitigation efforts beyond 2030 are needed. As such, it is necessary to assess the effects of imposing more stringent long-term GHG reduction targets in Thailand beyond the NDC commitment.MethodsThis paper analyses the macroeconomic effects of limiting the GHG emissions by using a computable general equilibrium (CGE) model on Thailand’s economy during 2010 to 2050. Besides the business as usual (BAU) scenario, this study assesses the macroeconomic effects of ten low to medium GHG mitigation scenarios under varying GHG reduction targets of 20 to 50%. In addition, this study also assesses three different peak emission scenarios, each targeting a GHG reduction of up to 90% by 2050, to analyze the feasibility of zero GHG emissions in Thailand to pursue efforts to hold the global temperature rise to 1.5 °C above pre-industrial levels, as considered in the Paris Agreement.ResultsAccording to the BAU scenario, the GHG emissions from the electricity, industry, and transport sectors would remain the most prominent throughout the planning period. The modeling results indicate that the medium to peak emission reduction scenarios could result in a serious GDP loss compared to the BAU scenario, and therefore, the attainment of such mitigation targets could be very challenging for Thailand. Results suggest that the development and deployment of energy-efficient and renewable energy-based technologies would play a significant role not only in minimizing the GHG emissions but also for overcoming the macroeconomic loss and lowering the price of GHG emissions.ConclusionsThe results reveal that without a transformative change in the economic structure and energy system of Thailand, the country would have to face enormous cost in reducing its GHG emissions.

The livestock sector holds a prominent position among Brazilian economic sectors; however, beef production is linked to noteworthy environmental impacts, including deforestation and greenhouse gas (GHGs) emissions. In alignment with the Paris Agreement, Brazil aims to reduce GHG emissions by 43% by 2030 as part of its NDC commitment. This study aims to elucidate the nexus between beef production and emissions from beef cattle, providing an assessment of predictive GHG emission scenarios for 2030, and an economic valuation of these emissions utilizing the social cost of carbon (SCC). Under a business-as-usual (BAU) scenario, GHG emissions from beef production are estimated to range between 0.42-0.63 GtCO2e in 2030. Conversely, meeting the Brazilian Nationally Determined Contributions (NDC) target requires limiting emissions to 0.26 GtCO2e. The SCC analysis unveils a potential cost reductions ranging from US $18.8 to $42.6 billion in 2030, contingent upon achieving the NDC. Furthermore, a strategic assessment considering climate targets and prioritizing beef exports envisions a domestic market availability of 2-10kg of beef per capita in 2030. This study highlight the critical need for transformative adjustments in livestock production methods to reduce GHG emissions per unit of beef yield, with a focus on the economic advantages of emission mitigation.

Thailand commits to achieving Carbon Neutrality by 2050 and net-zero GHG emissions by 2065. Its Nationally Determined Contributions (NDC) also aims to reduce greenhouse gas (GHG) emissions by 30% by 2030 through domestic efforts, termed “Unconditional NDC,” and up to 40% with international support, termed “Conditional NDC,” compared to its 2030 Business-as-Usual (BAU) of 555 MtCO2eq. This study explores the potential for reducing GHG emissions in Thailand's energy sector through international cooperation such as the Joint Credit Mechanism (JCM), in accordance with of the Paris Agreement (PA). It is essential that the results of international transfers are accurately accounted for and reported in the NDC tracking under Article 13 by both Parties to prevent double counting. The investigation utilizes the AIM/EndUse model, created by the National Institute for Environmental Studies in Japan. The results show that under the international cooperation framework, Thailand needs to reduce GHG emissions beyond the target specified in the conditional NDC. Finally, to enable the transfer of Internationally Transferred Mitigation Outcomes (ITMOs) under Article 6.2 of PA, Thailand's share of carbon credits should reasonably be capped at no more than 20%, with an additional emission reduction of 12.34 MtCO2 beyond the conditional Nationally Determined Contribution (NDC) target of 49.34 MtCO2.

The pyrolysis of biomass can help produce liquid transportation fuels with properties similar to those of petroleum gasoline and diesel fuel. Argonne National Laboratory conducted a life-cycle (i.e., well-to-wheels [WTW]) analysis of various pyrolysis pathways by expanding and employing the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The WTW energy use and greenhouse gas (GHG) emissions from the pyrolysis pathways were compared with those from the baseline petroleum gasoline and diesel pathways. Various pyrolysis pathway scenarios with a wide variety of possible hydrogen sources, liquid fuel yields, and co-product application and treatment methods were considered. At one extreme, when hydrogen is produced from natural gas and when bio-char is used for process energy needs, the pyrolysis-based liquid fuel yield is high (32% of the dry mass of biomass input). The reductions in WTW fossil energy use and GHG emissions relative to those that occur when baseline petroleum fuels are used, however, is modest, at 50% and 51%, respectively, on a per unit of fuel energy basis. At the other extreme, when hydrogen is produced internally via reforming of pyrolysis oil and when bio-char is sequestered in soil applications, the pyrolysis-based liquid fuel yield is low (15% of the dry mass of biomass input), but the reductions in WTW fossil energy use and GHG emissions are large, at 79% and 96%, respectively, relative to those that occur when baseline petroleum fuels are used. The petroleum energy use in all scenarios was restricted to biomass collection and transportation activities, which resulted in a reduction in WTW petroleum energy use of 92-95% relative to that found when baseline petroleum fuels are used. Internal hydrogen production (i.e., via reforming of pyrolysis oil) significantly reduces fossil fuel use and GHG emissions because the hydrogen from fuel gas or pyrolysis oil (renewable sources) displaces that from fossil fuel natural gas and the amount of fossil natural gas used for hydrogen production is reduced; however, internal hydrogen production also reduces the potential petroleum energy savings (per unit of biomass input basis) because the fuel yield declines dramatically. Typically, a process that has a greater liquid fuel yield results in larger petroleum savings per unit of biomass input but a smaller reduction in life-cycle GHG emissions. Sequestration of the large amount of bio-char co-product (e.g., in soil applications) provides a significant carbon dioxide credit, while electricity generation from bio-char combustion provides a large energy credit. The WTW energy and GHG emissions benefits observed when a pyrolysis oil refinery was integrated with a pyrolysis reactor were small when compared with those that occur when pyrolysis oil is distributed to a distant refinery, since the activities associated with transporting the oil between the pyrolysis reactors and refineries have a smaller energy and emissions footprint than do other activities in the pyrolysis pathway.

Toward a Super-COP? Timing, Temporality, and Rethinking World Climate Governance

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

In order to achieve target greenhouse gas (GHG) emissions, such as those proposed by each country by nationally determined contributions (NDCs), GHG emission projections are receiving attention around the world. Generally, integrated assessment models (IAMs) are used to estimate future GHG emissions considering both economic structure and final energy consumption. However, these models usually do not consider the entire supply chain, because of differences in the aims of application. In contrast, life cycle assessment (LCA) considers the entire supply chain but does not cover future environmental impacts. Therefore, this study aims to evaluate the national carbon footprint projection in Japan based on life cycle thinking and IAMs, using the advantages of each. A future input–output table was developed using the Asia-Pacific integrated model (AIM)/computable general equilibrium (CGE) model (Japan) developed by the National Institute for Environmental Studies (NIES). In this study, we collected the fundamental data using LCA databases and estimated future GHG emissions based on production-based and consumption-based approaches considering supply chains among industrial sectors. We targeted fiscal year (FY) 2030 because the Japanese government set a goal for GHG emissions in 2030 in its NDC report. Accordingly, we set three scenarios: FY2005 (business as usual (BAU)), FY2030 (BAU), and FY2030 (NDC). As a result, the carbon footprint (CFP) in FY2030 will be approximately 1097 megatons of carbon dioxide equivalent (MtCO2eq), which is 28.5% lower than in FY2005. The main driver of this reduction is a shift in energy use, such as the introduction of renewable energy. According to the results, the CFP from the consumption side, fuel combustion in the use stage, transport and postal services, and electricity influence the total CFP, while results of the production side showed the CFP of the energy and material sectors, such as iron and steel and transport, will have an impact on the total CFP. Moreover, carbon productivity will gradually increase and FY2030 (NDC) carbon productivity will be higher than the other two cases.

Greening passenger transport: a review

One of the priorities of the “Europe 2020” strategy is to combat climate change and to reduce greenhouse gases (GHG) emissions. The key elements for the climate policy framework for the European Commission for 2020 are as follows: (1) reducing GHG emissions by 40% in comparison to the level in 1990; (2) increasing the share of renewable energy in the use of final energy to 27%; (3) increasing the energetic efficiency by 27%. Those are ambitious goals which will require the Member States to increase their efforts in all the sectors of the economy. In 2015 the GHG emissions in the EU fell by 23.7% in comparison to the level in 1990. All the sectors, apart from the transport sector contributed to the emission reduction in the years 1990–2015. The transport emission increased by 13.3% in that period in comparison to the year 1990, which is particularly worrisome. This is important because the fuels use in the transport sector contributed to approximately 20% of all the GHG emissions in the EU in 2015. The article presents the factors and the tools which significantly affect the achievement of the goals set in the Green Paper: a 2030 framework for energy and climate policies, which concern the transport sector and the indicated guidelines and instruments supporting them. The road transport will be extensively analysed as it is the transport mode which shows an extraordinary growth tendency and it is a vital barrier in the achievement of the goals set in the area of “Climate change and GHG emission reduction”. The article presents the results of the research, which show the impact of various identified tools on the achievement of the threepriorities of the climate policy. The multivariate analysis of variance (MANOVA) was used, in which the dependent variables were: the GHG emission levels, the use of renewable energy and the energy intensity of transport. The results were calculated based on the data from 28 Member States and the model was verified.

Nationally Determined Contributions (NDCs), submitted by Parties to the United Nations Framework Convention on Climate Change before and after the 21st Conference of Parties, summarize domestic objectives for greenhouse gas (GHG) emissions reductions for the 2025–2030 time horizon. In the absence, for now, of detailed guidelines for the format of NDCs, ancillary data are needed to interpret some NDCs and project GHG emissions in 2030. Here, we provide an analysis of uncertainty sources and their impacts on 2030 global GHG emissions based on the sole and full achievement of the NDCs. We estimate that NDCs project into 56.8–66.5 Gt CO2eq yr−1 emissions in 2030 (90% confidence interval), which is higher than previous estimates, and with a larger uncertainty range. Despite these uncertainties, NDCs robustly shift GHG emissions towards emerging and developing countries and reduce international inequalities in per capita GHG emissions. Finally, we stress that current NDCs imply larger emissions reduction rates after 2030 than during the 2010–2030 period if long-term temperature goals are to be fulfilled. Our results highlight four requirements for the forthcoming ‘climate regime’: a clearer framework regarding future NDCs’ design, an increasing participation of emerging and developing countries in the global mitigation effort, an ambitious update mechanism in order to avoid hardly feasible decarbonization rates after 2030 and an anticipation of steep decreases in global emissions after 2030.