Greenhouse Gas Emission Pathways Research Articles

Hailstone size dichotomy in a warming climate

Hailstorms are analyzed across the United States using explicit hailstone size calculations from convection-permitting regional climate simulations for historical, mid-century, and end of twenty-first-century epochs. Near-surface hailstones <4 cm are found to decrease in frequency by an average of 25%, whereas the largest stones are found to increase by 15–75% depending on the greenhouse gas emissions pathway. Decreases in the frequency of near-surface severe hail days are expected across the U.S. High Plains, with 2–4 fewer days projected—primarily in summer. Column-maximum severe hail days are projected to increase robustly in most locations outside of the southern Plains, a distribution that closely mimics projections of thunderstorm days. Primary mechanisms for the changes in hailstone size are linked to future environments supportive of greater instability opposed by thicker melting layers. This results in a future hailstone size dichotomy, whereby stronger updrafts promote more of the largest hailstones, but significant decreases occur for a majority of smaller diameters due to increased melting.

Enhancing human resilience against climate change: Assessment of hydroclimatic extremes and sea level rise impacts on the Eastern Shore of Virginia, United States

Coastal regions face climate-induced threats that have likely increased over the past four decades. In this work, we quantify the future climate impacts on hydroclimatic extremes in the risk-prone, 15-m-above-sea-level Eastern Shore of Virginia (ESVA) region, utilizing the Sixth International Coupled Model Intercomparison Project (CMIP6) Assessment Report 6 (AR6) and General Circulation Models (GCMs). We incorporate historical data on demographics and disasters, land use land cover (LULC), Landsat imagery, and sea level rise (SLR) to better understand and highlight the correlation between hydroclimatic extremes and societal components in this region. The hydrological model Soil and Water Assessment Tool (SWAT), Standardized Precipitation Index (SPI), Normalized Difference Water Index (NDWI), and Interquartile Range (IQR) method have been used to evaluate the intensity and frequency of projected climate extremes, in which SLR projections under different greenhouse gas emission pathways are temporally and spatially quantified. Our findings include (1) a trend towards wetter conditions is found with an increase in the number of flood events and up to an 8.9 % rise in the severity of flood peaks compared to the 2003–2020 period; (2) current coastal high-risk regions, identified using historical data of natural disasters, demographics, and LULC, are projected to be more susceptible to future climate impacts; and (3) low-lying coastal towns and regions are identified as currently vulnerable to coastal and SLR-induced flooding and are projected to become even more susceptible by 2100. This is the first effort that provides a valuable scientific basis for anticipated shifts in future climate patterns, essential for natural hazard prevention in ESVA. It highlights the need for authorities and decision-makers to plan and implement adaptive strategies and sustainable policies for the ESVA region and other coastal areas across the United States.

Modeling a hot, dry future: Substantial range reductions in suitable environment projected under climate change for a semiarid riparian predator guild.

An understanding of species-environmental relationships is invaluable for effective conservation and management under anthropogenic climate change, especially for biodiversity hotspots such as riparian habitats. Species distribution models (SDMs) assess present species-environmental relationships which can project potential suitable environments through space and time. An understanding of environmental factors associated with distributions can guide conservation management strategies under a changing climate. We generated 260 ensemble SDMs for five species of Thamnophis gartersnakes (n = 347)-an important riparian predator guild-in a semiarid and biogeographically diverse region under impact from climate change (Arizona, United States). We modeled present species-environmental relationships and projected changes to suitable environment under 12 future climate scenarios per species, including the most and least optimistic greenhouse gas emission pathways, through 2100. We found that Thamnophis likely advanced northward since the turn of the 20th century and overwinter temperature and seasonal precipitation best explained present distributions. Future ranges of suitable environment for Thamnophis are projected to decrease by ca. -37.1% on average. We found that species already threatened with extinction or those with warm trailing-edge populations likely face the greatest loss of suitable environment, including near or complete loss of suitable environment. Future climate scenarios suggest an upward advance of suitable environment around montane areas for some low to mid-elevation species, which may create pressures to ascend. The most suitable environmental areas projected here can be used to identify potential safe zones to prioritize conservation refuges, including applicable critical habitat designations. By bounding the climate pathway extremes to, we reduce SDM uncertainties and provide valuable information to help conservation practitioners mitigate climate-induced threats to species. Implementing informed conservation actions is paramount for sustaining biodiversity in important aridland riparian systems as the climate warms and dries.

Differences of East Asian Summer Monsoon Precipitation Responses between Transient and Stabilization Simulations

The differences between the two global warming targets of the Paris Agreement, 1.5 °C and 2 °C above pre-industrial levels, have drawn much attention from the scientific community. However, there is a remaining gap to distinguish regional climate responses in these two most typical pathways, i.e., transient and stabilization simulations, toward specific warming levels. In this study, we discern the East Asia summer monsoon (EASM) responses between these two types of simulations at low-warming targets, based on the fully coupled community Earth system model (CESM). The two types of responses display a similar increase pattern in the EASM precipitation. However, the quantitative differences between these two types of responses are as large as those between the 1.5 °C and 2 °C warming scenarios. The moist budget analysis reveals that the EASM precipitation differences are mainly caused by the thermodynamic, dynamic, and transient eddy effects. Specifically, the thermodynamic effect contributes to the precipitation increment in the coastal area of East Asia in both types of responses, with the enhanced low-level specific humidity. The dynamic contribution shows tripolar and bipolar patterns in East Asia in the transient and stabilization responses, respectively. Remarkably, the transient eddy effect contribution emerges only in the stabilization responses. Further, we reveal the dominant role of the East Asian subtropical jet (EASJ) in determining the contributions from dynamic and transient eddy effects. The changes in the EASJ’s position and intensity are greatly regulated by the temperature change patterns at the mid-high levels in response to different greenhouse gas emission pathways. Our study highlights the differences between transient and stabilization climate states on a regional scale.

Decarbonization in the Automotive Sector: A Holistic Status Quo Analysis of Original Equipment Manufacturer Strategies and Carbon Management Activities

The automotive sector is a significant contributor to global carbon emissions and, as such, to climate change. However, there is currently no publicly available sector-wide insight into the extent to which Original Equipment Manufacturers (OEMs) in the automotive sector have implemented decarbonization strategies and carbon management activities. This paper addresses this issue by collecting and analyzing the implementation status of all OEMs with annual sales of more than 500,000 light-duty vehicles. For this purpose, a structured set of criteria is developed that allows conclusions to be drawn for several areas of corporate carbon management. The analysis shows a sector-wide implementation of decarbonization strategies and carbon management activities. However, significant regional differences in external communication, data transparency and methodological inconsistencies emerge. This study provides both academics and practitioners in the automotive industry with valuable insights into current reporting practices, target setting and communicated mitigation actions. On this basis, scientists can project possible greenhouse gas (GHG) emission pathways, align their research with the focus of practitioners to provide them with science-based data, and work on the methodological inconsistencies. Furthermore, the developed criteria provide a useful toolbox for the holistic analysis of other industries.

Emergent constraints on future extreme precipitation intensification: from global to continental scales

Extreme precipitation intensification due to global warming has received significant attention; however, large uncertainties remain regarding how much it will change in the future, even under a given greenhouse gas emissions pathway. Our constraining analysis provides smaller future extreme precipitation intensification with reduced uncertainties than raw/unconstrained model simulation projections from the global to continental scales and also several sub-continental areas. Historical warming trends in climate model simulations present strong positive inter-model correlations with future annual maximum daily precipitation intensification from the global to continental scales. This emergent relationship is employed for constraining analysis. The proposed emergent constraints are mostly associated with thermodynamics (atmospheric moisture changes), with limited contribution from dynamics (atmospheric circulation variations). This constraining framework has various advantages, including lower observation uncertainty, and more robust theoretical interpretation than previously suggested constraints for extreme precipitation frequency projections. CMIP6 models generally overestimate historically observed warming, which resultantly generates weaker extreme precipitation intensification following constraining analysis than unconstrained model simulation projections from the global to individual continents, and even several mid- and high-latitude sub-continental areas. Additionally, constrained projections exhibit narrower uncertainty ranges in future extreme precipitation projections. During the late 21st century (2070–2099), under the high-emission scenario (Shared Socioeconomic Pathway 5–8.5, characterized by fossil fueled development and a radiative forcing of 8.5 W m−2 in 2100), our results present reduced global average intensity and uncertainty for future annual maximum daily precipitation intensification by 25% and 27%, respectively.

Neglected implications of land-use and land-cover changes on the climate-health nexus

Climate change can substantially affect temperature-related mortality and morbidity, especially under high greenhouse gas emission pathways. Achieving the Paris Agreement goals require not only drastic reductions in fossil fuel-based emissions but also land-use and land-cover changes (LULCC), such as reforestation and afforestation. LULCC has been mainly analysed in the context of land-based mitigation and food security. However, growing scientific evidence shows that LULCC can also substantially alter climate through biogeophysical effects. Little is known about the consequential impacts on human health. LULCC-related impact research should broaden its scope by including the human health impacts. LULCC are relevant to several global agendas (i.e. Sustainable Development Goals). Thus, collaboration across research communities and stronger stakeholder engagement are required to address this knowledge gap.

The sea level simulator v1.0: a model for integration of mean sea level change and sea level extremes into a joint probabilistic framework

Abstract. A statistical model called the sea level simulator v1.0 is introduced. The model integrates mean sea level change and sea level extremes into a joint probabilistic framework that is useful for coastal spatial planning. Given a user-defined planning period, the model can estimate the flood risk as a function of height above the current mean sea level. These flood risk estimates are derived through Monte Carlo simulations of a very large number of planning periods. The derived flood risk is contingent on user-assigned probabilities for future greenhouse gas emission pathways, and the model is thus also useful for quantifying the dependence of flood risk on such pathways and their probabilities. Moreover, the simulator can quantify whether flood risk is dominated by sea level extremes or mean sea level rise and how this depends on the length of the planning period. The code, written in MATLAB, is parallelized and lightweight enough that it can be run on an ordinary PC. The code is easily adaptable to include new locations, new mean sea level projections and similar model developments. The flood risk estimates derived from the simulator are well suited to tackle adaptation and decision problems. Applications for construction of coastal protection and land development in coastal areas have been demonstrated in the past. The paper gives an in-depth technical description of the model. Example simulations from a Swedish nuclear site are also given, and the capabilities of the simulator are discussed. The main aim of the paper is to work as a technical reference for the first public release of the sea level simulator.

Impacts on water quality in the peatland dominated catchment due to foreseen changes in Nordic Bioeconomy Pathways

The Nordic Bioeconomy Pathways (NBPs), conceptualized subsets of Shared Socioeconomic Pathways varying from environmentally friendly to open-market competition scenarios, can lead to plausible stressors in future for using bioresources. This study analysed the impacts of NBPs on hydrology and water quality based on two different land system management attributes: management strategy and a combination of reduced stand management and biomass removal at a catchment-scale projection. To understand the potential impacts of NBPs, the Simojoki catchment in northern Finland was chosen, as the catchment mainly covered peatland forestry. The analysis integrated a stakeholder-driven questionnaire, the Finnish Forest dynamics model, and Soil and Water Assessment Tool to build NBP scenarios, including Greenhouse gas emission pathways, for multiple management attributes to simulate flows, nutrients, and suspended solids (SS). For the catchment management strategy, an annual decrease in nutrients was observed for sustainability and business-as-usual scenarios. Reduced stand management and biomass removal also led to decreased export of nutrients and SS for the same scenarios, whereas, in other NBPs, the export of nutrients and SS increased with decreased evapotranspiration. Although the study was investigated at a local scale, based on the current political and socioeconomic situation, the approach used in this study can be outscaled to assess the use of forest and other bioresources in similar catchments.

Built for net-zero: analysis of long-term greenhouse gas emission pathways for the Nigerian cement sector

Nigeria is Africa's top cement producer and could be on course to be one of the top producers globally. The goal of this study is to identify and critically examine the pathways available to Nigeria to meet its decarbonisation goals in the cement sector. Based on a literature review, the study assesses demand drivers and decarbonisation potentials for the sector. It then presents two different quantitative pathways for growth in production of cement by 2050, and three different pathways for decarbonisation of the sector. Using published data and a scenario analysis tool, the study calculates how the sector's emissions might evolve under each of these pathways. The results indicate that, in the most ambitious scenario, emissions from the sector can plateau by the late 2030s, resulting in an overall increase of 21% by 2050 (compared to 2015 levels). Achieving this scenario is necessary in order to put the sector on a path to net zero emissions beyond 2050. The scenario is driven by reductions in both energy-related and process emissions, as well as a small share of carbon capture and storage and demand management. A moderately ambitious scenario that relies mostly on savings on energy-related emissions results in an 84% increase in emissions by 2050. Finally, the Business-as-Usual scenario results in an almost tripling of emissions by 2050. The results indicate a strong potential for policies to drive improvements in energy efficiency and clinker-to-cement ratio. Critical areas of uncertainty within the assumptions include the production rates (including the evolution of the export market) and the fuel mix.

Towards net zero: making baselines for international carbon markets dynamic by applying ‘ambition coefficients’

ABSTRACT This paper discusses options to increase mitigation ambition in crediting mechanisms that serve the Paris Agreement (PA), such as the Article 6.4 mechanism. Under the Clean Development Mechanism and other crediting mechanisms, baselines have been specified in the form of greenhouse gas (GHG) intensity factors and linked to business-as-usual developments. This means that with increasing production of goods and services through carbon market activities, absolute emissions may increase or fall only slowly. At a global level, such an approach widens the ‘emissions gap’. To enable continued use of emissions intensity baselines in crediting mechanisms while being in line with the PA’s goal to pursue efforts to limit temperature rise to 1.5°C, we propose to apply an ‘ambition coefficient’ to emissions intensities of technologies when establishing the baseline. This coefficient would decrease to reflect increasing ambition over time, and reach zero when a country needs to reach net zero emissions. Due to the principle of common but differentiated responsibilities and respective capabilities, the coefficient would fall more quickly for developed than for developing countries. The latter would be able to generate emission reduction credits well beyond 2050, while for the former, crediting would stop around 2035 or before. An ambition coefficient approach would generate certainty for carbon market investors and preserve trust in international carbon markets that operate in line with the agreed, long-term ambition of the international climate regime. Key policy insights An ambition coefficient can help to align carbon market activities with net zero GHG emission pathways at country level, and ensure that carbon markets will not lead to a lock-in of emissions in participating countries. The ambition coefficient approach can serve as a ‘bridging proposal’ for the operationalization of PA carbon markets. It may resolve negotiation gridlock between those who want to increase stringency in carbon market instruments and those who think mitigation ambition should be generated through more stringent NDCs, facilitated by cost savings and increased financial resources generated by international carbon markets. The use of an ambition coefficient can enable the alignment of existing methodologies with necessary ambition levels to implement the PA, while also keeping transaction costs low.

Shallow lakes under alternative states differ in the dominant greenhouse gas emission pathways

AbstractOver the past decades, shallow lakes of the Pampean Plain, Argentina, have been shifting from clear vegetated to turbid phytoplanktonic states due to anthropic pressures. It is not clear, though, if this change in state also involves a change in the overall CO2 and CH4 balance of these lakes. Therefore, the main objective of this work was to assess potential differences in the C gas (CH4 and CO2) balance of shallow lakes under contrasting states—clear vegetated and turbid phytoplanktonic. We sampled two clear and two turbid shallow lakes in the Pampean region along an annual cycle and we measured all of the major C gas emission pathways: diffusive and ebullitive fluxes and also emissions from emergent vegetated habitats. CO2 and CH4 diffusive, ebullitive and vegetated habitat fluxes were comparable between states, but they differed in their relative contribution to the C gas balance because of differences in the coverage of the habitats associated to these pathways. Mean annual, area‐weighted CO2 and CH4 fluxes of clear lakes were 41.9 ± 19.0 and 15.4 ± 18.5 mmol m−2 d−1, respectively, and 7.7 ± 7.3 and 17.9 ± 19.8 mmol m−2 d−1 for CO2 and CH4 fluxes, respectively, for turbid lakes. Despite major differences in the relative contribution of the emission pathways between states, there was a remarkable convergence between states in total greenhouse gas emissions when expressed in terms of mean annual CO2 equivalent greenhouse gas flux.

Deep learning-based neural networks for day-ahead power load probability density forecasting.

Energy efficiency is crucial to greenhouse gas (GHG) emission pathways reported by the Intergovernmental Panel on Climate Change. Electrical overload frequently occurs and causes unwanted outages in distribution networks, which reduces energy utilization efficiency and raises environmental risks endangering public safety. Electrical load, however, has a dynamically fluctuating behavior with notoriously nonlinear hourly, daily, and seasonal patterns. Accurate and reliable load forecasting plays an important role in scheduling power generation processes and preventing electrical systems from overloading; nevertheless, such forecasting is fundamentally challenging, especially under highly variable power load and climate conditions. This study proposed a deep learning-based monotone composite quantile regression neural network (D-MCQRNN) model to extract the multiple non-crossing and nonlinear quantile functions while conquering the drawbacks of error propagation and accumulation encountered in multi-step-ahead probability density forecasting. The constructed models were assessed by an hourly power load series collected at the electric grid center of Henan Province in China in two recent years, along with the corresponding meteorological data collected at 16 monitoring stations. The results demonstrated that the proposed D-MCQRNN model could significantly alleviate the time-lag and biased-prediction phenomena and noticeably improve the accuracy and reliability of multi-step-ahead probability density forecasts on power load. Consequently, the proposed model can significantly reduce the risk and impact of overload faults and effectively promote energy utilization efficiency, thereby mitigating GHG emissions and moving toward cleaner energy production.

Quantification of greenhouse gas emission from wastewater treatment plants

AbstractIn this study, a new quantitative approach of greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) is established. It is developed based on three categories of WWPTs: (1) energy and chemical consumption; (2) final disposal of biosolids; and direct GHG emission from treatment processes, which is helpful to better estimate the GHG emission pathways. The developed approach can provide actual results of GHG emission in terms of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) from wastewater treatment process. Then, this method is applied to a municipal WWPT, where the GHG emission from the processes of final treatment, biological treatment, and anaerobic digestion, at the southside of Guelph city in Canada. The results show that there are 6743.8 CO2 eq.kg/day of CO2 and 1924.48 CO2 eq.kg/day of N2O emissions from aeration tank/activated sludge system. The biological treatment and anaerobic digestion release 74177.58 CO 2eq.kg/day of CH4, 7258.5 CO2 eq.kg/day of CO2, and 59022.6 CO2 eq.kg/day of CH4, 3493.24 CO2eq.kg/day of CO2. If the methane, which discharged from biological treatment and anaerobic digestion, is captured and burned for energy regeneration, then it can produce 12937.9 CO2 eq.kg/day of CO2. The total amount of GHG indicates that about 80% GHG is emitted from the final disposal field while 9% and 11% GHG is emitted from biological treatment and anaerobic digestion, respectively. Therefore, based on the calculated results, engineers can put forward suggestions to optimize operation conditions to reduce greenhouse gas emissions. © 2022 Society of Chemical Industry and John Wiley &amp; Sons, Ltd.

Thailand’s mid-century greenhouse gas emission pathways to achieve the 2 degrees Celsius target

BackgroundThe Paris Agreement aims at minimizing threats of climate change by keeping global temperature rise well below 2 degrees Celsius above the pre-industrial level and to pursue efforts to limit the rise to 1.5 degrees Celsius. The Representative Concentration Pathways (RCPs) are developed to investigate GHG emission pathways. RCP2.6 focuses on limiting the global temperature rise to less than 2 degrees Celsius. This paper assesses the impacts of carbon price and CCS on energy and GHG emissions in Thailand. The no carbon price (T0) and the carbon price pathways are compared. In addition, the net-zero emissions and year are discussed.ResultsThe decarbonized energy system with low-carbon power generation and increased electricity usage in the final energy consumption is the main pillar of GHG mitigation. Imposing carbon prices; increasing solar, wind, and biomass electricity generation; energy efficiency improvements in power generation; and energy savings in the industry and the building sectors, will be the key options for clean power generation in the carbon prices (CT) scenarios. Renewable electricity, coal and natural gas, coupled with CCS and bio-energy with CCS (BECCS) will be utilized significantly to curb GHG emissions. The increase of renewable energy and the electrification of end-use plays a key role in reducing GHG emissions. Fuel switching from diesel to biodiesel, energy efficiency improvement and electric pick-ups and trucks will help reducing GHG emissions in the transport sector.ConclusionsThere are three major policy implications to meet Thailand’s 2 degrees Celsius target. First, carbon prices will be the mechanism to accelerate the transformation in the energy sector. Wind and solar electricity will be key pillars of clean electricity in 2050. Policy-makers should update the renewable electricity plans to meet Thailand’s 2 degrees Celsius target in 2050. Second, coal- and gas-fired plants, and BECCS will become important options in reducing CO2 emissions. The policy-makers should investigate the application of CCS in the power sector and the storage location. Third, a major transformation in the transport sector is critically needed. Liquid biofuel and electrification in pick-ups, sedans, and trucks will help reduce GHG emissions.

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

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

Uniting the Global Gastroenterology Community to Meet the Challenge of Climate Change and Non-Recyclable Waste

Uniting the Global Gastroenterology Community to Meet the Challenge of Climate Change and Non-Recyclable Waste

Modelled response of debris-covered and lake-calving glaciers to climate change, Kā Tiritiri o te Moana/Southern Alps, New Zealand

Glaciers will lose mass during the next decades as the climate warms. While the largest uncertainty in this mass loss is the global greenhouse gas emissions pathway, on a local or regional scale there are large uncertainties in some processes that influence glacier response. We explore the competing processes of reduced ablation under debris cover and increased ablation from calving by applying a coupled mass-balance/ice-flow model in the central Southern Alps/Kā Tiritiri o te Moana of New Zealand. Glacier volume loss is assessed over the period from AD 1880 to AD 2099, driven by observed climate data before 2005, and perturbing the modern climate state and imposing representative concentration pathway (RCP) scenarios 2.6–8.5 as expressed by six global circulation models (GCMs) which leads to a regional warming of between 1–4 °C (2006–2099). Key findings are (1) modelled ice volume reduced from 47 km3 to 29 km3 between AD 1880 and 2005; (2) over the period 2006–2099 further volume loss to 24 km3 (19% reduction) is committed under present-day climate; (3) modelled ice volume at AD 2099 is estimated at 2 km3 ± 6 km3 (RCP8.5) to 15 km3 ± 6 km3 (RCP2.6), a reduction of 50–92% relative to present day. The wide range of projected ice volumes reflects the large range of temperature projections between RCP2.6 and RCP8.5. The mode and timing of ice loss provides insight into processes that will drive future glacier behavior. Under RCP2.6 at 2099, the glaciers retain a similar configuration to present, although clean-ice glaciers will retreat significantly, and some debris-covered tongues will disconnect from their accumulation areas. For RCP4.5, RCP6.0 and RCP8.5 the clean-ice glaciers will retreat to become small remnants in the high mountains. Experiments where the debris cover is removed shows a much faster loss of ice, whereas experiments with no lake calving slows ice loss. However, under all but the most moderate warming scenarios, by 2099 the strong climatic forcing overwhelms these processes as there is little ice left at low elevations where debris cover and lake calving occur.

Phasing out the blast furnace to meet global climate targets

Phasing out the blast furnace to meet global climate targets

Equity and justice as central components of climate change adaptation

Equity and justice as central components of climate change adaptation