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At least 865 records · Page 48

Building Envelope Characteristics in Cold Climates

Prescriptive guidelines for thermal insulation in the design of buildings in cold climates have traditionally been derived by a holistic consideration of climatic factors, energy policy, environmental policy, and economics. The differences in thermal barrier requirements in buildings across the arctic and subarctic regions of the world are influenced as much by the differing priorities of the governing bodies that set these requirements as by actual physical demands and conditions. Usually, national requirements for building envelope characteristics such as thermal insulation values, building envelope airtightness, vapor permeability, building mass, and detailing are based on economics, durability, and environmental considerations. Consideration of thermal energy system resilience provides a new paradigm through which to view the optimization of these parameters. The paper describes specifics of construction in cold climates; summarizes best practice requirements for the building envelope characteristics for buildings located in cold and arctic climate of the United States, Canada, and Scandinavian countries; provides some details illustrating how to implement these requirements; and compares the effects of different levels of building envelope efficiency and building mass on indoor air temperature decay when heat supply is interrupted. The paper also presents results from experts' discussions during the consultation forum "Thermal Energy Systems Resilience in Cold/Arctic Climates" (ERDC 2020) and research conducted under the IEA EBC Annex 73, the Environmental Security Technology Certification Program (ESTCP) Project "Technologies Integration to Achieve Resilient, Low-Energy Military Installations," and U.S. Army Program project 633734T1500 under Military Engineering Technology Demonstration. The paper complements the Cold-Climate Design Guide (ASHRAE 2015) with a focus on the resilience of thermal energy systems.

Arctic↗

It's All About the Envelope: Prioritizing Envelope Upgrades for Electrification of Cold Climate Homes

Building decarbonization via electrification on a clean grid is the most promising climate solution proposed to date for the building sector. In cold climate zones, building electrification will be driven in large part by moving from natural gas space heating to cold climate heat pumps (CCHPs). CCHPs are commercially available today, including economical cold climate air source heat pumps (ccASHPs). But there's one big problem - wide-scale adoption of ccASHPs will dramatically increase winter peak electricity demand, even with the highest efficiency ccASHP products. Furthermore, cold climate space heating loads will drive unprecedented electric system peaks during the lowest periods of renewable generation and are likely to overwhelm existing distribution systems. This scenario is avoidable by coupling electrification with building envelope upgrades to reduce peak heating loads. This paper presents a model, built from home energy audit and research data sets, that quantifies the above challenges. Results demonstrate how weatherization efforts coupled with additional high-performance envelope upgrade measures can prepare the building stock for electrification and show the benefit these measures can bring to future utility operations. Much of this envelope upgrade work is cost-effective, according to conservative cost-benefit testing and program successes to date, and is coupled with substantial non-energy benefits. However, persistent market barriers have made scaling of envelope retrofit work challenging for decades, suggesting additional policy support is required. Lessons learned from previous policy experience, combined with new technology and administrative support, create exciting potential for this decarbonization climate solution.

air sealing↗

Climate Challenges and Nonproliferation: Addressing the Issue through Technical Cooperation

Climate change is an urgent global challenge that is already severely impacting many regions of the world. The 2015 Paris Agreement was a landmark achievement, while the 2023 UN COP 28 Climate Conference in Dubai recognized nuclear energy and its applications as a proven and sustainable means to help societies adapt to climate change and take measures to mitigate and, possibly, reverse its effects. Twenty-two countries, supported by over 120 companies, pledged to triple the share of global nuclear energy generation by 2050. The global interest in nuclear applications for peaceful uses has never been higher. The deployment of advanced reactors around the globe – focused primarily on lowering the carbon footprint and allowing for socio-economic development – must be addressed responsibly through setting priorities for its implementation. Tackling the challenges that new technologies, such as advanced reactors, bring to the nonproliferation regime is at the top of the list. The regime stands on the three pillars of the Nuclear Nonproliferation Treaty (NPT): nonproliferation, peaceful uses of nuclear energy, and disarmament. Recognizing the inherent risks of expanding applications of nuclear materials and technologies for peaceful uses, all such efforts must concurrently strengthen the nonproliferation norm enshrined in the NPT. The challenges of adapting to and mitigating climate change with the use of advanced reactors is already impacting the discussions and expectations about the future of the NPT. The dialog with non-traditional domestic, and international partners on a strategic technical cooperation approach is key to proposing and implementing scientific and technical solutions for urgent climate issues, while framing the discussion within nonproliferation requirements and commitments, and demonstrating the underlying value of the NPT in support of peaceful nuclear applications. This paper addresses adaptation to climate challenges and mitigation of them through advanced reactors and establishes nonproliferation linkages that derive from the deployment of this technology. This paper presents an assessment of the benefits of mechanisms for technical cooperation and peaceful uses of nuclear technology in the framework of Article IV of the NPT.

Prah, Christina↗

ClimGen: Learning the Forcing-Response Relationship in Climate System

Solar Radiation Management (SRM) is emerging as a potential geoengineering strategy to address the anthropogenic impact on climate, but its effective implementation requires an iterative and large ensemble of highly accurate and efficient climate projections. Traditional climate projections rely on executing computationally demanding and time-consuming numerical climate models. Recent advances in machine learning (ML) aim to enhance these approaches by emulating traditional methods. In this work, we propose a novel framework for directly learning the relationship between solar radiation flux at the top of the atmosphere and the corresponding surface temperature response. To evaluate the feasibility of this direct ML-based projection, we developed a dataset using an intermediate complexity model, incorporating a comprehensive suite of different forcing patterns and evaluation metrics to rigorously assess the ML model’s performance. We introduce a Conditional Denoising Diffusion Probabilistic Model (cDDPM) for this task, which demonstrates encouraging skill in representing climate statistics under previously unseen forcing patterns. This approach provides a promising pathway for direct climate projections by accurately learning the forcing-response relationship, with a wide range of applications in impact mitigation, emissions policy design, and SRM strategies.

Chen, Tse-Chun [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

Decline in malaria incidence in a typical county of China: Role of climate variance and anti-malaria intervention measures

Highlights: • Malaria incidence shows a steeply interannual decline and an obvious seasonality. • Malaria incidence highly correlates to temperature, precipitation and humidity. • Two favorable climate conditions are determined for high incidence of malaria. • There is good agreement between a decreasing malaria incidence and slightly declined climate variance in epidemic months. • Malaria incidence is declined rapidly because of the persistent progress of anti-malaria interventions. Malaria is an important vector-borne disease which is widespread in tropical and subtropical areas worldwide as well as in south China. Previous research has separately focused on the association between malaria incidence and meteorological variables or between malaria incidence and anti-malaria intervention measures in China, especially in Yunnan Province. Therefore, a typical county, Tengchong County, in Yunnan Province with high malaria incidence was selected as the study area to investigate the integrated influence of climate variance and anti-malaria intervention measures. Malaria incidence and meteorological variables were analyzed with a 2-month lag. The variables include average monthly temperature, minimum temperature, maximum temperature, cumulative precipitation, wind speed, maximum wind speed, relative humidity and minimum relative humidity. First, the principal component analysis was introduced to investigate the relationship between malaria incidence and meteorological variables; classification and regression trees were used to clarify contributions of key meteorological variables to malaria incidence afterwards. Second, based on existing anti-malaria intervention measures and above results, the integrated impact of climate variance and anti-malaria interventions on interannual trends of malaria incidence was analyzed. High malaria incidence occurred under one of the two meteorological conditions: 1) high minimum temperature combined with high minimum relative humidity or both precipitation and minimum relative humidity above middle level; 2) middle minimum temperature combined with both precipitation and minimum relative humidity below middle levels. Moreover, the steep interannual decline of malaria incidence in Tengchong was determined by slight climate variance and persistent anti-malaria intervention measures during malaria epidemics, predominantly by the latter. These findings will provide evidence data for developing malaria surveillance strategies in China.

54 ENVIRONMENTAL SCIENCES↗

A review of the potential impacts of climate change on bulk power system planning and operations in the United States

In this paper, climate change might impact various components of the bulk electric power system, including electricity demand; transmission; and thermal, hydropower, wind, and solar generators. Most research in this area quantifies impacts on one or a few components and does not link these impacts to effects on power system planning and operations. Here, we advance the understanding of how climate change might impact the bulk U.S. power system in three ways. First, we synthesize recent research to capture likely component-level impacts of climate change in the United States. Second, given the interconnected nature of the electric power system, we assess how aggregated component-level impacts might affect power system planning and operations. Third, we outline an agenda for future research on climate change impacts on power system planning and operations. Although component-level impacts vary in their magnitude, collectively they might significantly affect planning and operations. Most notably, increased demand plus reduced firm capacity across generation types might require systems to procure significant additional capacity to maintain planning reserve margins, and regional declines in renewable resources might need to be offset by increasing zero-carbon investment to meet decarbonization targets. Aggregated impacts might also affect operations, e.g., through shifts in dispatching and increased operational reserve requirements. Future research should aggregate component-level impacts at operational timescales, quantify impacts on wind and solar variability, and contextualize climate change impacts within ongoing shifts in the electric power system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Estimating the Impacts of Increasing Temperatures and the Efficacy of Climate Adaptation Strategies in Urban Microclimates with Deep Learning

As urbanization and climate change progress, understanding and addressing urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in the urban core can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, modeling the urban microclimate is an ongoing field of research typically burdened by an imprecise description of the built environment, incomplete observational records, significant computational cost, and a lack of high-resolution estimates of the impacts of increasing temperatures. Here, we present computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to a neighborhood in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50 %. The corresponding increase in winter gas heating offsets the summer cooling benefit in the current climate, but total annual energy use from combined heating and cooling with electric heat pumps benefits from the engineered heat mitigation strategies under both current and future climates.

54 ENVIRONMENTAL SCIENCES↗

ENSO's Changing Influence on Temperature, Precipitation, and Wildfire in a Warming Climate

On interannual to decadal time scales, the climate mode with many of the strongest societal impacts is the El Niño–Southern Oscillation (ENSO). However, quantifying ENSO's changes in a warming climate remains a formidable challenge, due to both the noise arising from internal variability and the complexity of air-sea feedbacks in the tropical Pacific Ocean. In this paper, we use large (≥30-member) ensembles of climate simulations to show that anthropogenic climate change can produce systematic increases in ENSO teleconnection strength over many land regions, driving increased interannual variability in regional temperature extremes and wildfire frequency. As the spatial character of this intensification exhibits strong land-ocean contrasts, a causal role for land-atmosphere feedbacks is suggested. The identified increase in variance occurs in multiple model ensembles, independent of changes in sea surface temperature variance. In conclusion, this suggests that in addition to changes in the overall likelihoods of heat and wildfire extremes, the variability in these events may also be a robust feature of future climate.

54 ENVIRONMENTAL SCIENCES↗

Thunderstorm Activity Under Intermediate and Extreme Climate Change Scenarios

Assessing how increasing greenhouse gas concentrations may modify regional climates is an ongoing challenge. Relatively little work has examined how climate change may influence processes related to regional thunderstorm activity. This is important to consider in areas where thunderstorms are important for maintaining regional hydroclimates. Here, this study focuses on three convection-allowing climate simulations—namely, a retrospective simulation (1990–2005) and two possible climate change scenarios (2085–2100)—with domains encompassing the conterminous United States. Regional and seasonal variability is noted in the response of thunderstorm activity as measured by thresholds in simulated radar reflectivity factor in the two climate change scenarios. A decrease in thunderstorm activity is projected for the Southern Plains, whereas the Southeast and Midwest experience an increase in thunderstorm activity. An examination of environmental parameters related to thunderstorm activity reveals an overall increase in convective instability but spatially varying changes in convective inhibition.

54 ENVIRONMENTAL SCIENCES↗

Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.

54 ENVIRONMENTAL SCIENCES↗

Pushing the frontiers in climate modelling and analysis with machine learning

Climate modelling and analysis are facing new demands to enhance projections and climate information. Here, in this study, we argue that now is the time to push the frontiers of machine learning beyond state-of-the-art approaches, not only by developing machine-learning-based Earth system models with greater fidelity, but also by providing new capabilities through emulators for extreme event projections with large ensembles, enhanced detection and attribution methods for extreme events, and advanced climate model analysis and benchmarking. Utilizing this potential requires key machine learning challenges to be addressed, in particular generalization, uncertainty quantification, explainable artificial intelligence and causality. This interdisciplinary effort requires bringing together machine learning and climate scientists, while also leveraging the private sector, to accelerate progress towards actionable climate science.

54 ENVIRONMENTAL SCIENCES↗

Economic losses from extreme weather in the U.S. Gulf Coast region: spatially differential contributions of climate hazard and socioeconomic exposure and vulnerability

Worldwide economic losses from extreme weather events (EWE) have increased over recent decades, with significant geographic heterogeneity in damages. The IPCC defines the risk from EWE as a function of the climate hazard, socioeconomic exposure, and vulnerability. Although these three drivers vary at fine spatial scales, spatial variability largely has been overlooked in assessments of the drivers of economic loss from EWE. Using cluster analysis, we developed a novel socio-climate hazard typology (SCT) that integrates locally defined climate hazard and socioeconomic exposure and social vulnerability typologies. The results identified 838 unique SCT types impacted by EWE across the Gulf Coastal United States during 1981–2010. We regressed the SCT types and their constituent hazard and socioeconomic components against the cumulative economic loss (1981–2010) from EWE for each SCT type. Across the landscape, economic damages of SCT types were determined by unique, spatially explicit combinations of different risk factors, even in explaining the same level of economic loss. For example, multi-billion-dollar damages in the central Gulf Coast and peninsular Florida were explained by different drivers of risk, with damages in the former explained by additive interaction between climate hazard and multiplicative interaction between climate hazard and socioeconomic exposure and vulnerability, and in the latter explained by socioeconomic exposure and vulnerability. These results highlight the need to diagnose additive and multiplicative interactions among drivers of EWE risk in a spatially explicit context.

54 ENVIRONMENTAL SCIENCES↗

Climate change, malaria and neglected tropical diseases: a scoping review

Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

60 APPLIED LIFE SCIENCES↗

The Engineering of Climate Engineering

While reducing anthropogenic greenhouse gas emissions remains the most essential element of any strategy to manage climate change risk, it is also in principle possible to directly cool the climate by reflecting some sunlight back to space. Possible such \climate engineering" approaches include adding aerosols to the stratosphere or marine cloud brightening. Assessing whether these ideas could reduce risk requires a broad multidisciplinary research eort spanning climate science, social sciences, and governance. However, if such strategies were ever used, the effort would also constitute one of the most critical engineering design and control challenges ever considered: making real-time decisions for a highly uncertain and nonlinear dynamic system with many input variables, many measurements, and vastly more internal degrees of freedom whose dynamics span a wide range of timescales. We provide a review of the engineering and design aspects of climate engineering, discussing both progress to date and remaining challenges that will need to be addressed.

climate engineering, climate modeling, geoengineer↗

Dryland feedbacks to future climate change: how species mortality and replacement will affect coupled biogeochemical cycles and energy balance (Final Technical Report)

The overall goal of the dryland climate manipulation experiment is to improve our understanding and ability to forecast dryland responses to increasing temperatures and altered precipitation regimes. Drylands cover over 40% of Earth’s terrestrial surface and are predicted to increase in size 11-23% by 2100. Yet our understanding of this vast biome, which exchanges enormous amounts of CO 2 and energy with the atmosphere, is exceedingly poor. This project aims to transform and improve that understanding in order to reduce uncertainty and increase the confidence with which we can make global predictions of future climate. We focus on both above- and belowground processes, and explore temperature controls over critical aspects of carbon and nutrient cycling for dryland plants, soil, and microbes. We have 60 climate manipulation plots where plants (from above the canopy) and soils are warmed using infrared lamps and where precipitation has been altered using targeted watering regimes. We have measured myriad aspects of plant physiology, morphology, carbon exchange, energy exchange, and phenology, as well as analogous climate-induced changes to biological soil crusts and soil microbial communities. Our goals are to investigate temperature responses and acclimation potential of dryland plant and soil processes. Concurrent soil incubation experiments complement the in-situ soil warming component and enable more controlled mechanistic investigations of temperature response on microbial function. Automated soil CO 2 efflux chambers within the plots provide phenomenal opportunity to improve our understanding of dryland CO 2 exchange with the atmosphere and are coupled with plant CO 2 exchange measurements. The project has been exceptionally successful, with 35 peer-reviewed publications (and more in review), including in high-profile journals such as Nature Climate Change and PNAS. We have given over fifty presentations on the work and it has been featured in many high-profile media outlets, such as Discover Magazine and on NPR.

54 ENVIRONMENTAL SCIENCES↗

Performance assessment for climate intervention (PACI): preliminary application to a stratospheric aerosol injection scenario

As the prospect of exceeding global temperature targets set forth in the Paris Agreement becomes more likely, methods of climate intervention are increasingly being explored. With this increased interest there is a need for an assessment process to understand the range of impacts across different scenarios against a set of performance goals in order to support policy decisions. The methodology and tools developed for Performance Assessment (PA) for nuclear waste repositories shares many similarities with the needs and requirements for a framework for climate intervention. Using PA, we outline and test an evaluation framework for climate intervention, called Performance Assessment for Climate Intervention (PACI) with a focus on Stratospheric Aerosol Injection (SAI). We define a set of key technical components for the example PACI framework which include identifying performance goals, the extent of the system, and identifying which features, events, and processes are relevant and impactful to calculating model output for the system given the performance goals. Having identified a set of performance goals, the performance of the system, including uncertainty, can then be evaluated against these goals. Using the Geoengineering Large Ensemble (GLENS) scenario, we develop a set of performance goals for monthly temperature, precipitation, drought index, soil water, solar flux, and surface runoff. The assessment assumes that targets may be framed in the context of risk-risk via a risk ratio, or the ratio of the risk of exceeding the performance goal for the SAI scenario against the risk of exceeding the performance goal for the emissions scenario. From regional responses, across multiple climate variables, it is then possible to assess which pathway carries lower risk relative to the goals. The assessment is not comprehensive but rather a demonstration of the evaluation of an SAI scenario. Future work is needed to develop a more complete assessment that would provide additional simulations to cover parametric and aleatory uncertainty and enable a deeper understanding of impacts, informed scenario selection, and allow further refinements to the approach.

climate intervention↗

Impacts of Climate Change on the Generation Potential of Solar and Wind Energy Systems in India

Low-carbon energy sources like wind and solar are essential for decarbonizing the electricity sector. In addition, the cost of electricity generated from these sources has plummeted over the last decade. Therefore, these energy sources are poised to take a significant share of the total installed capacity soon. However, they are susceptible to the impacts of climate change as their generation potential depends on the weather conditions. Estimating the installed capacity requirements of solar and wind energy to decarbonize the power sector without accounting for these possible changes in generation potential could lead to missing out on the set climate goals and meeting future electricity demand. This study evaluates the effect of climate change on the generation potential of wind and solar energy systems in India for two future periods, 2050 and 2070, under two climate scenarios or Shared Socioeconomic Pathway (SSP): SSP245 and SSP585. Almost all regions show a decrease, and most regions show a significant decline (>5%) in the generation potential of solar Photovoltaic (PV) as compared to 2010 levels under both climate scenarios and future periods. The changes in the generation potential of wind energy are more significant (>10%), and the majority of regions show a decline in generation potential. Southwestern and central regions show an increase in wind generation potential for 2070 as compared to 2050 levels under the SSP245 scenario and the SSP585 scenario, respectively.

climate change↗

An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment

The Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water–carbon–climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO 2 -emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the “Assessment Fast Track”, drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding.

Environmental sciences↗