Estimation of fuelwood-induced carbon emission from the use of improved cook stoves by selected households in Kwara State, Nigeria Abstract This study estimates the fuelwood-induced carbon emission of a 4-year national project called National Assembly Intervention on Clean Cooking Initiative (NAICCI), which involved the distribution of improved wood-saving stoves and Liquefied Petroleum Gas (LPG) and burners to poor households in Kwara State of Nigeria between 2014 and 2018. Questionnaires were used to collect primary data from a sample of 161 households out of 1000 covering variables such as average dry weight of fuel wood used per household, average dry weight of fuel wood used in the production of charcoal, and area logged per year. A randomized experimental design was deployed across the study area covering Asa, Ilorin West, Ilorin East, and Ilorin South Local Government Areas. NAICCI was aimed at reducing carbon emission from the use of fuelwood for cooking, which was estimated using Reducing Emission from Deforestation and Forest Degradation Decision Support Tool (REDD+ DST) to arrive at an estimate of 8.6 tonnes of carbon emission (CO2e) per capita for the period under review translating to 2.2 tCO2e/year. For fuelwood-induced carbon emissions to be sustainably reduced, we recommend enforcement of prevention of illegal logging to prevent indiscriminate deforestation, use of satellite technology in improving carbon reduction estimates, use of bioethanol from biowaste and nonfood crops, and use of Vulnerability Scoping Diagrams (VSDs) for targeted selection of beneficiaries. We conclude that the use of improved cook stoves and fuels for cooking could help in forest conservation and reduce CO2e emissions in Nigeria.

Quantifying student engagement in learning about climate change using galvanic hand sensors in a controlled educational setting Abstract Teaching climate change is complex because it requires a system-level understanding of many science disciplines and also because students may have preconceptions about climate change. Previous work shows students learn and retain science content better when they are engaged in the learning process. Active learning strategies engage students in learning science, but the engagement impact of active learning has not yet been assessed in a controlled environment using both biometric and self-reporting tools. Here, we analyze 52 university students’ engagement during several common active learning strategies in a controlled research setting. We collected biometric data from all participants with hand sensors that measured changes in skin conductance as a proxy for engagement. Participants self-reported their engagement as a control. The combined biometric and self-reported data show that skin conductance data matched self-reported engagement, confirming that skin conductance is a robust proxy for engagement. Overall, dialog was the most engaging activity, with engagement levels about 165% above baseline. Non-science majors had higher average engagement than science majors (137% vs. 53% above baseline, respectively). Notably, skin conductance data showed no statistically significant differences based on participants’ political or religious affiliations. In summary, our results demonstrate biometric sensors’ potential to measure and monitor engagement in a learning environment. Relevant for climate education, in-class dialog increases student engagement in learning climate science and is especially effective for non-science majors.

Long-run trend in agricultural yield and climatic factors in Europe Abstract Reliable projections of crop production are an essential tool for the design of feasible policy plans to tackle food security and land allocation, and an accurate characterization of the long-run trend in crop yield is the key ingredient in such projections. We provide several contributions adding to our current understanding of the impact of climatic factors on crop yield. First of all, reflecting the complexity of agricultural systems and the time required for any change to diffuse, we show that crop yield in Europe has historically been characterized by a stochastic trend rather than the deterministic specifications normally used in the literature. Secondly, we found that, contrary to previous studies, the trend in crop yield has slowly changed across time rather than being affected by a single abrupt permanent change. Thirdly, we provide strong evidence that climatic factors have played a major role in shaping the long-run trajectory of crop yield over the decades, by influencing both the size and the statistical nature of the trend. In other words, climatic factors are important not only for the year-to-year fluctuations in crop yield but also for its path in the long-run. Finally, we find that, for most countries in this study, the trend in temperature is responsible for a reduction in the long-run growth rate of yield in wheat, whereas a small gain is produced in maize, except for Southern European countries.

Changing yields in the Central United States under climate and technological change Abstract This paper projects the race between technologically driven increases in crop yields and changing climatic conditions in the central USA, one of the world’s most productive agricultural regions. Using the highest, average, and lowest decadal rates of technologically driven increases in crop yields over the 1980 to 2017 period, we develop spatially explicit yield scenarios to the end of the twenty-first century under RCP4.5 and RCP8.5. We find that with static technological innovation, severe climate change will decrease yields by an average of 22.4% (26.1 bu. ac−1) for maize, 27.9% (8.83 bu. ac−1) for soybeans, and 20% (7.14 bu. ac−1) for winter wheat in the central USA; however, with even the lowest rates of technological yield growth, yields increase by an average of 25.0% (40.5 bu. ac−1) for maize and 30.2% (14.2 bu. ac−1) for soybeans. We conclude that technology has the potential to overcome the negative impacts of climate change on the yields of maize, soybeans, and winter wheat in the central USA, but if these increases are to be environmentally sustainable, technological developments must be information-intensive rather than input-intensive.

Climate change beliefs shape the interpretation of forest fire events Abstract Using a naturalistic quasi-experimental design and growth curve modeling techniques, a recently proposed climate change risk perception model was replicated and extended to investigate changes in climate change risk perception and climate policy support in relation to exposure to forest fires. At the start of the study, above-average indirect exposure to forest fires (e.g., through media and conversations) was associated with stronger climate change risk perception, but direct exposure to forest fires (e.g., seeing smoke) and other types of extreme weather events was not. Over time, changes in climate change risk perception were positively associated with changes in climate policy support. However, individual differences in growth trajectories occurred. For example, in this naturalistic setting without any intervention, the climate change risk perceptions of individuals with weaker perceptions of scientific agreement on climate change were less likely to be positively influenced by fire exposure than those of individuals with stronger perceptions of scientific agreement. These findings highlight the importance of tailoring climate change communication.

Thermodynamic Model of CO 2 Deposition in Cold Climates Abstract A thermodynamic model, borrowing ideas from psychrometric principles, of a cryogenic direct-air CO2-capture system utilizing a precooler is used to estimate the optimal CO2 removal fraction to minimize energy input per tonne of CO2. Energy costs to operate the system scale almost linearly with the temperature drop between the ingested air and the cryogenic desublimation temperature of CO2, driving siting to the coldest accessible locations. System performance in three Arctic/Antarctic regions where the proposed system can potentially be located is analyzed. Colder ambient temperatures provide colder system input air temperature yielding lower CO2 removal energy requirements. A case is also presented using direct-sky radiative cooling to feed colder-than-ambient air into the system. Removing greater fractions of the ingested CO2 lowers the CO2 desublimation temperature, thereby demanding greater energy input for air cooling. It therefore is disadvantageous to remove all CO2 from the processed air, and the optimal mass fraction of CO2 desublimated under this scheme is found to be ~0.8-0.9. In addition, a variety of precooler effectiveness (ε ) values are evaluated. Increasing effectiveness reduces the required system power input. However, beyond ε = 0.7, at certain higher values of desublimated CO2 mass fraction, the CO2 begins to solidify inside the precooler before reaching the cryocooler. This phenomenon fouls the precooler, negating its effectiveness. Further system efficiencies can be realized via a precooler designed to capture solidified CO2 and eliminate fouling.

Probable maximum precipitation in a warming climate over North America in CanRCM4 and CRCM5 Abstract In the context of climate change and projected increase in global temperature, the atmosphere’s water holding capacity is expected to increase at the Clausius-Clapeyron (C-C) rate by about 7% per 1 °C warming. Such an increase may lead to more intense extreme precipitation events and thus directly affect the probable maximum precipitation (PMP), a parameter that is often used for dam safety and civil engineering purposes. We therefore use a statistically motivated approach that quantifies uncertainty and accounts for nonstationarity, which allows us to determine the rate of change of PMP per 1 °C warming. This approach, which is based on a bivariate extreme value model of precipitable water (PW) and precipitation efficiency (PE), provides interpretation of how PW and PE may evolve in a warming climate. Nonstationarity is accounted for in this approach by including temperature as a covariate in the bivariate extreme value model. The approach is demonstrated by evaluating and comparing projected changes to 6-hourly PMP from two Canadian regional climate models (RCMs), CanRCM4 and CRCM5, over North America. The main results suggest that, on the continental scale, PMP increases in these models at a rate of approximately 4% per 1 °C warming, which is somewhat lower than the C-C rate. At the continental scale, PW extremes increase on average at the rate of 5% per 1 °C near surface warming for both RCMs. Most of the PMP increase is caused by the increase in PW extremes with only a minor contribution from changes in PE extremes. Nevertheless, substantial deviations from the average rate of change in PMP rates occur in some areas, and these are mostly caused by sensitivity of PE extremes to near surface warming in these regions.

Twenty-five years of adaptation finance through a climate justice lens Abstract How much finance should be provided to support climate change adaptation and by whom? How should it be allocated, and on what basis? Over the years, various actors have expressed different normative expectations on climate finance. Which of these expectations are being met and which are not; why, and with what consequences? Have new norms and rules emerged, which remain contested? This article takes stock of the first 25+ years of adaptation finance under the United Nations Framework Convention on Climate Change (UNFCCC) and seeks to understand whether adaptation finance has become more justly governed and delivered over the past quarter century. We distinguish among three “eras” of adaptation finance: (1) the early years under the UNFCCC (1992–2008); (2) the Copenhagen shift (2009–2015); and (3) the post-Paris era (2016–2018). For each era, we systematically review the justice issues raised by evolving expectations and rules over the provision, distribution, and governance of adaptation finance. We conclude by outlining future perspectives for adaptation finance and their implications for climate justice.

Communication of IPCC visuals: IPCC authors’ views and assessments of visual complexity Abstract Scientific figures, i.e. visuals such as graphs and diagrams, are an important component of Intergovernmental Panel on Climate Change (IPCC) reports that support communication and policy-making. It is therefore imperative that figures are robust representations of the science and are accessible to target audiences. We interviewed IPCC authors (n = 18) to understand the development of figures in the IPCC Fifth Assessment Report (AR5) Working Group 1 (WG1) Summary for Policy-Makers (SPM). Authors expressed the view that the need to maintain scientific accuracy constrained making figures more accessible, with the consequence that figures retained complexity and often required specialists to explain the figures to others. Using sort tasks with IPCC authors and with a group of non-specialists (undergraduate students; n = 38), we found that IPCC authors generally had good awareness of which figures non-specialists perceived as being most difficult to understand. Further, by evaluating the visual complexity of the AR5 WG1 SPM figures using a computational measure, we found that greater visual complexity (i.e. high quantity of information, use of multiple colours and densely packed visual elements) is associated with greater perceived comprehension difficulty. Developing and integrating computational approaches to assess figures alongside user testing could help inform how to overcome visual complexity while maintaining scientific rigour and so enhance communication of IPCC figures and scientific visuals.

Countrywide climate features during recorded climate-related disasters Abstract Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.