Unlocking the potential of forage fish to reduce the global burden of disease.

Red meat consumption is associated with an elevated risk of mortality from non-communicable diseases (NCDs). In contrast, forage fish, as highly nutritious, environmentally friendly, affordable, and the most abundant fish species in the ocean, are receiving increasing interest from a global food system perspective. However, little research has examined the impact of replacing red meat with forage fish in the global diet on diet-related NCDs. METHODS: We based our study on datasets of red meat projections in 2050 for 137 countries and forage fish catches. We replaced the red meat consumption in each country with forage fish (from marine habitats), without exceeding the potential supply of forage fish. We used a comparative risk assessment framework to investigate how such substitutions could reduce the global burden of diet-related NCDs in adults. RESULTS: The results of our study show that forage fish may replace only a fraction (approximately 8%) of the world's red meat due to its limited supply, but it may increase global daily per capita fish consumption close to the recommended level. Such a substitution could avoid 0.5-0.75 million deaths and 8-15 million disability-adjusted life years, concentrated in low- and middle-income countries. Forage fish as an alternative to red meat could double (or more) the number of deaths that could be avoided by simply reducing red meat consumption. CONCLUSIONS: Our analysis suggests that forage fish is a promising alternative to red meat. Policies targeting the allocation of forage fish to regions where they are needed, such as the Global South, could be more effective in maximising the potential of forage fish to reduce the global burden of disease.

Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050.

Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

How climate change may shift power demand in Japan: Insights from data-driven analysis.

The impact of climate change on power demand in Japan and its related CO2 emissions is a matter of concern for the Japanese authorities and power companies as it may have consequences on the power grid, but is also of global importance as Japan is a significant contributor to global greenhouse gas emissions. In this study, we trained random forest models against daily power data in ten Japanese regions and for different types of power generation to project changes in future power production and its carbon intensity. We used climate variables, heat stress indices, and one variable for the level of human activities. We then used the models trained from the present-day period to estimate the future power demand, carbon intensity, and pertaining CO2 emissions over the period 2020-2100 under three Shared Socioeconomic Pathways (SSPs) scenarios (SSP126, SSP370, and SSP585). The impact of climate change on CO2 emissions via power generation shows seasonal and regional disparities. In cold regions, a decrease in power demand during winter under future warming leads to an overall decrease in power demand over the year. In contrast, the decrease in winter power demand in hot regions can be overcompensated by an increase in summer power demand due to more frequent hot days, resulting in an overall annual increase. From our regional models, power demand is projected to increase the most in most Japanese regions in May, June, September, and October rather than in the middle of summer, as found in previous studies. This increase could result in regular power outages during those months as the power grid could become particularly tense. Overall, we observed that power demand in regions with extreme climates is more sensitive to global warming than in temperate regions. The impact of climate change on power demand induces a net annual decrease in CO2 emissions in all regions except for Okinawa, in which power demand strongly increases during the summer, resulting in a net annual increase in CO2 emissions. However, climate change's impact on carbon intensity may reverse the trend in some regions (Shikoku, Tohoku). Additionally, we assessed the relative impacts of socioeconomic factors such as population, GDP, and environmental policies on CO2 emissions. When combined with these factors, we found that the climate change effect is more important than when considered individually and significantly impacts total CO2 emissions under SSP585. The contrasting results observed in the warm and cold regions of Japan can offer valuable insight into the potential future variations in energy demand and resulting CO2 emissions on a global scale.

Japanese Pharmacists' Perceptions of Self-Development Skills and Continuing Professional Development.

BACKGROUND: The role of healthcare professionals, including pharmacists, is changing. Lifelong learning and continuing professional development (CPD) are more critical than ever for both current and future pharmacists in the face of global health challenges and new technologies, services and therapies that are continually and rapidly introduced into their daily practice. Currently, Japanese pharmacists' licences are not renewable, although most developed countries have a renewal system. Therefore, understanding Japanese pharmacists' perceptions of CPD is the first step in reviewing undergraduate and postgraduate education. METHODS: The target population was Japanese pharmacists, i.e., community pharmacy pharmacists and hospital pharmacists. The participants were administered a questionnaire with 18 items related to continuing professional development. RESULTS: Our study found that regarding item "Q16 Do you think you need further education in your undergraduate education to continue your professional development?", (a) the ability to identify one's own problems and issues, (b) the ability to make plans to solve problems and issues, (c) the ability to carry out plans to solve problems and issues and (d) the ability to repeat steps of self-development, approximately 60% of pharmacists answered that these aspects were "necessary" or "quite necessary". CONCLUSION: As part of universities' responsibility for the lifelong education of pharmacists, it is necessary to systematically conduct teaching seminars or undergraduate education or postgraduate education on self-development while training pharmacists to meet the needs of citizens.

Effects of heatwave features on machine-learning-based heat-related ambulance calls prediction models in Japan.

Researchers agree that there is substantial evidence of an increasing trend in both the frequency and duration of extreme temperature events. Increasing extreme temperature events will place more pressure on public health and emergency medical resources, and societies will need to find effective and reliable solutions to adapt to hotter summers. This study developed an effective method to predict the number of daily heat-related ambulance calls. Both national- and regional-level models were developed to evaluate the performance of machine-learning-based methods on heat-related ambulance call prediction. The national model showed a high prediction accuracy and can be applied over most regions, while the regional model showed extremely high prediction accuracy in each corresponding region and reliable accuracy in special cases. We found that the introduction of heatwave features, including accumulated heat stress, heat acclimatization, and optimal temperature, significantly improved prediction accuracy. The adjusted coefficient of determination (adjusted R2) of the national model improved from 0.9061 to 0.9659 by including these features, and the adjusted R2 of the regional model also improved from 0.9102 to 0.9860. Furthermore, we used five bias-corrected global climate models (GCMs) to forecast the total number of summer heat-related ambulance calls under three different future climate scenarios nationally and regionally. Our analysis demonstrated that, at the end of the 21st century, the total number of heat-related ambulance calls in Japan will reach approximately 250,000 per year (nearly four times the current amount) under SSP-5.85. Our results suggest that disaster management agencies can use this highly accurate model to forecast potential high emergency medical resource burden caused by extreme heat events, allowing them to raise and improve public awareness and prepare countermeasures in advance. The method proposed in Japan in this paper can be applied to other countries that have relevant data and weather information systems.

Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces.

Estimates of future climate change impacts using numerical impact models are commonly based on a limited selection of projections of climate and other key drivers. However, the availability of large ensembles of such projections offers an opportunity to estimate impact responses probabilistically. This study demonstrates an approach that combines model-based impact response surfaces (IRSs) with probabilistic projections of climate change and population to estimate the likelihood of exceeding pre-specified thresholds of impact. The changing likelihood of exceeding impact thresholds during the 21st century was estimated for selected indicators in three European case study regions (Iberian Peninsula, Scotland and Hungary), comparing simulations that incorporate adaptation to those without adaptation. The results showed high likelihoods of increases in heat-related human mortality and of yield decreases for some crops, whereas a decrease of NPP was estimated to be exceptionally unlikely. For a water reservoir in a Portuguese catchment, increased likelihoods of severe water scarce conditions were estimated for the current rice cultivation. Switching from rice to other crops with lower irrigation demand changes production risks, allowing for expansion of the irrigated areas but introducing a stronger sensitivity to changes in rainfall. The IRS-based risk assessment shown in this paper is of relevance for policy making by addressing the relative sensitivity of impacts to key climate and socio-economic drivers, and the urgency for action expressed as a time series of the likelihood of crossing critical impact thresholds. It also examines options to respond by incorporating alternative adaptation actions in the analysis framework, which may be useful for exploring the types, choice and timing of adaptation responses.

Hourly future climate scenario datasets for impact assessment of climate change considering simultaneous interactions among multiple meteorological factors.

Assessing the impacts of climate change in multiple fields, such as energy, land and water resources, and human health and welfare is important to find effective strategies to adapt to a changing climate and to reduce greenhouse gases. Many phenomena influenced by climate change have diurnal fluctuations and are affected by simultaneous interactions among multiple meteorological factors. However, climate scenarios with detailed (at least hourly) resolutions are usually not available. To assess the impact of climate change on such phenomena while considering simultaneous interactions (e.g., synergies), climate scenarios with hourly fluctuations are indispensable. However, because meteorological indicators are not independent, the value of one indicator varies as a function of other indicators. Therefore, it is almost impossible to determine the functions that show all relationships among meteorological elements considering the geographical and temporal (both seasonal and time of a day) characteristics. Therefore, generating hourly scenarios that include possible combinations of meteorological indicators for each hourly observation unit is a challenging problem. In this study, we provide secondary future climate scenario datasets that have hourly fluctuations with reasonable combinations of meteorological indicator values that are likely to occur simultaneously, without losing the long-term climate change trend in the existing daily climate scenarios based on global climate models. Historical hourly weather datasets observed from 2017 to 2019 (the reference years) are used to retrieve short-term fluctuations. Bias-corrected daily future climate scenario datasets generated using four global climate models (GFDL CM3, HadGEM2-ES, MIROC5, and MRI-CGCM3) and two Representative Concentration Pathways (RCP8.5 and 2.6) are used to model long-term climate change. A total of 48 different types of hourly future scenario datasets for five meteorological indicators (temperature, solar radiation, humidity, rainfall, and wind speed) were acquired, targeting a projection period from 2020 to 2080, for 10 weather stations in Japan. The generated hourly climate scenario datasets can be used to project the quantitative impacts of climate change on targeted phenomena considering simultaneous interactions among multiple meteorological factors.

Land-based climate change mitigation measures can affect agricultural markets and food security.

Earlier studies have noted potential adverse impacts of land-related emissions mitigation strategies on food security, particularly due to food price increases-but without distinguishing these strategies' individual effects under different conditions. Using six global agroeconomic models, we show the extent to which three factors-non-CO2 emissions reduction, bioenergy production and afforestation-may change food security and agricultural market conditions under 2 °C climate-stabilization scenarios. Results show that afforestation (often simulated in the models by imposing carbon prices on land carbon stocks) could have a large impact on food security relative to non-CO2 emissions policies (generally implemented as emissions taxes). Respectively, these measures put an additional 41.9 million and 26.7 million people at risk of hunger in 2050 compared with the current trend scenario baseline. This highlights the need for better coordination in emissions reduction and agricultural market management policies as well as better representation of land use and associated greenhouse gas emissions in modelling.

Long-term projections of economic growth in the 47 prefectures of Japan: An application of Japan shared socioeconomic pathways.

Assessing climate change impacts on local communities is an urgent task for national and subnational governments. The impact assessment requires socioeconomic scenarios, including a long-term outlook for demographic and economic indices. In Japan, the National Institute for Environmental Studies developed the Japan Shared Socioeconomic Pathways (JPNSSPs) and presented regional population scenarios corresponding to five different storylines. However, there exists no quantitative information about changes in local economies under the population scenarios. This study examines the economic activities in Japan's 47 prefectures using statistical models and calculates changes in the major economic indices (e.g., production, capital stock, and labor population) until 2100. The economic projection is based on ten socioeconomic scenarios generated from the JPNSSP population scenarios and original productivity scenarios. The economic projection results clearly show that Japan's population aging and decline have catastrophic impacts on national and subnational economies. Even in the most optimistic scenario, assuming a massive influx of immigrants and fast productivity growth, the GDP growth rate becomes negative in the 2090s. In the most pessimistic scenario, the GDP growth rate becomes negative in 2028 and continues to decline. As a result, Japan's GDP decreases to the level of the 1970s by 2100. The improvement of productivity cannot offset the GDP shrink caused by demographic changes. Furthermore, the population aging and decline accelerate the wealth concentration in urban areas. The Theil index, calculated using the economic projection results, shows increasing trends in all the scenarios. Tokyo's presence in Japan's economy will continue to increase throughout this century. Meanwhile, Kanagawa and Saitama, which belong to the top five prefectures in terms of economic production, may lose their positions. The Tohoku region, already suffering from population decline, will face severe economic stagnation. Our findings suggest that the depressing future is inevitable unless Japan overcomes the population aging and decline.

Extreme climate events increase risk of global food insecurity and adaptation needs.

Climate change is expected to increase the frequency, intensity and spatial extent of extreme climate events, and thus is a key concern for food production. However, food insecurity is usually analysed under a mean climate change state. Here we combine crop modelling and climate scenarios to estimate the effects of extreme climate events on future food insecurity. Relative to median-level climate change, we find that an additional 20-36% and 11-33% population may face hunger by 2050 under a once-per-100-yr extreme climate event under high and low emission scenarios, respectively. In some affected regions, such as South Asia, the amount of food required to offset such an effect is triple the region's current food reserves. Better-targeted food reserves and other adaptation measures could help fill the consumption gap in the face of extreme climate variability.

Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators.

More than half of the world's population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country's total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific.

Integrated Climate-Change Assessment Scenarios and Carbon Dioxide Removal.

To halt climate change this century, we must reduce carbon dioxide (CO2) emissions from human activities to net zero. Any emission sources, such as in the energy or land-use sectors, must be balanced by natural or technological carbon sinks that facilitate CO2 removal (CDR) from the atmosphere. Projections of demand for large-scale CDR are based on an integrated scenario framework for emission scenarios composed of emission profiles as well as alternative socio-economic development trends and social values consistent with them. The framework, however, was developed years before systematic reviews of CDR entered the literature. This primer provides an overview of the purposes of scenarios in climate-change research and how they are used. It also introduces the integrated scenario framework and why it came about. CDR studies using the scenario framework, as well as its limitations, are discussed. Possible future developments for the scenario framework are highlighted, especially in relation to CDR.

Biodiversity can benefit from climate stabilization despite adverse side effects of land-based mitigation.

Limiting the magnitude of climate change via stringent greenhouse gas (GHG) mitigation is necessary to prevent further biodiversity loss. However, some strategies to mitigate GHG emission involve greater land-based mitigation efforts, which may cause biodiversity loss from land-use changes. Here we estimate how climate and land-based mitigation efforts interact with global biodiversity by using an integrated assessment model framework to project potential habitat for five major taxonomic groups. We find that stringent GHG mitigation can generally bring a net benefit to global biodiversity even if land-based mitigation is adopted. This trend is strengthened in the latter half of this century. In contrast, some regions projected to experience much growth in land-based mitigation efforts (i.e., Europe and Oceania) are expected to suffer biodiversity loss. Our results support the enactment of stringent GHG mitigation policies in terms of biodiversity. To conserve local biodiversity, however, these policies must be carefully designed in conjunction with land-use regulations and societal transformation in order to minimize the conversion of natural habitats.

Site-specific hourly resolution wet bulb globe temperature reconstruction from gridded daily resolution climate variables for planning climate change adaptation measures.

Changes in the environmental heat stress need to be properly evaluated to manage the risk of heat-related illnesses, particularly in the context of climate change. The wet bulb globe temperature (WBGT) is a useful index for evaluating heat stress and anticipating conditions related to heat-related illness in the present climate, but projecting the WBGT with a sufficiently high temporal and spatial resolution remains challenging for future climate conditions. In this study, we developed a methodological framework for estimating the site-specific hourly resolution WBGT based on the output of general circulation models using only simple calculations. The method was applied to six sites in Japan and its performance was evaluated. The proposed method could reproduce the site-specific hourly resolution WBGT with a high accuracy. Based on the developed framework, we constructed future (2090s) projections under two different greenhouse gas emission pathways. These projections showed a consistent rise in the WBGT and thus the capacity to perform physically demanding activities is expected to decrease. To demonstrate the usefulness of the projected WBGT in planning adaptation measures, we identified the optimal working schedules which would minimize outdoor workers' exposure to heat at a specific site. The results show that a substantial shift in the working time is required in the future if outdoor workers are to compensate the effect of increased heat exposure only by changing their working hours. This methodological framework and the projections will provide local practitioners with useful information to manage the increased risk of heat stress under climate change.

Gridded emissions and land-use data for 2005-2100 under diverse socioeconomic and climate mitigation scenarios.

Information on global future gridded emissions and land-use scenarios is critical for many climate and global environmental modelling studies. Here, we generated such data using an integrated assessment model (IAM) and have made the data publicly available. Although the Coupled Model Inter-comparison Project Phase 6 (CMIP6) offers similar data, our dataset has two advantages. First, the data cover a full range and combinations of socioeconomic and climate mitigation levels, which are considered as a range of plausible futures in the climate research community. Second, we provide this dataset based on a single integrated assessment modelling framework that enables a focus on purely socioeconomic factors or climate mitigation levels, which is unavailable in CMIP6 data, since it incorporates the outcomes of each IAM scenario. We compared our data with existing gridded data to identify the characteristics of the dataset and found both agreements and disagreements. This dataset can contribute to global environmental modelling efforts, in particular for researchers who want to investigate socioeconomic and climate factors independently.

Risk implications of long-term global climate goals: overall conclusions of the ICA-RUS project.

We have assessed the risks associated with setting 1.5, 2.0, or 2.5 °C temperature goals and ways to manage them in a systematic manner and discussed their implications. The results suggest that, given the uncertainties in climate sensitivity, "net zero emissions of anthropogenic greenhouse gases in the second half of this century" is a more actionable goal for society than the 2 or 1.5 °C temperature goals themselves. If the climate sensitivity is proven to be relatively high and the temperature goals are not met even when the net zero emission goal is achieved, the options left are: (A) accepting/adapting to a warmer world, (B) boosting mitigation, and (C) climate geoengineering, or any combination of these. This decision should be made based on a deeper discussion of risks associated with each option. We also suggest the need to consider a wider range of policies: not only climate policies, but also broader "sustainability policies", and to envisage more innovative solutions than what integrated assessment models can currently illustrate. Finally, based on a consideration of social aspects of risk decisions, we recommend the establishment of a panel of "intermediate layer" experts, who support decision-making by citizens as well as social and ethical thinking by policy makers.

How do climate-related uncertainties influence 2 and 1.5 °C pathways?

We investigate how uncertainties in key parameters in the carbon cycle and climate system propagate to the costs of climate change mitigation and adaptation needed to achieve the 2 and 1.5 °C targets by 2100 using a stochastic version of the simple climate model for optimization (SCM4OPT), an integrated assessment model. For the 2 °C target, we find a difference in 2100 CO2 emission levels of 20.5 GtCO2 (- 1.2 GtCO2 to 19.4 GtCO2), whereas this difference is 12.0 GtCO2 (- 6.9 GtCO2 to 5.1 GtCO2) for the 1.5 °C target (17-83% range). Total radiative forcing in 2100 is estimated to be 3.3 (2.7-3.9) Wm-2 for the 2 °C case and 2.5 (2.0-3.0) Wm-2 for the 1.5 °C case. Carbon prices in 2100 are 482 (181-732) USD(2005)/tCO2 and 713 (498-1014) USD(2005)/tCO2 for the 2 and 1.5 °C targets, respectively. We estimate GDP losses in 2100 that correspond to 1.9 (1.2-2.5)% of total gross output for the 2 °C target and 2.0 (1.5-2.7)% for the 1.5 °C target.

Anatomical and Radiological Analyses of L-shaped Kidney with Vascular Anomalies.

L-shaped kidney is a congenital anomaly. The disorder results in the kidney appearing very similar in shape to horseshoe kidney (also a congenital anomaly), but either the right or left kidney is located at a position lower than the other kidney. In this report, we describe a woman with L-shaped kidney, identified during anatomical dissection, and compare the findings with clinical data obtained before her death. We discuss the embryology of L-shaped kidney based on detailed anatomical data on the kidney and its vascular system obtained by means of gross anatomical, radiological, and histological examinations. Our findings indicate the importance of detailed anatomical information when planning surgical procedures in patients with fused kidneys, as well as kidney transplantation, resection of renal carcinoma, or surgical treatment of abdominal aortic aneurysm.

Influence on Learning of a Collaborative Learning Method Comprising the Jigsaw Method and Problem-based Learning (PBL).

Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.