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Abstract The observed global mean surface temperature increase from 1998 to 2012 was slower than that since 1951. The relative contributions of all relevant factors including climate forcers, however, have not been comprehensively analyzed. Using a reduced-complexity climate model and an observationally constrained statistical model, here we find that La Niña cooling and a descending solar cycle contributed approximately 50% and 26% of the total warming slowdown during 1998-2012 compared to 1951-2012. Furthermore, reduced ozone-depleting substances and methane accounted for roughly a quarter of the total warming slowdown, which can be explained by changes in atmospheric concentrations. We identify that non-CO2 greenhouse gases played an important role in slowing global warming during 1998-2012.

Abstract Climate mitigation is reported to benefit biodiversity globally. However, the impacts of mitigation measures based on large-scale land-use modifications can be concentrated in the regions where they are introduced, resulting in regional mismatches between mitigation efforts and biodiversity benefits. Here, we evaluated the impacts of large-scale deployment of bioenergy with carbon capture and storage and afforestation to attain the climate stabilization target stated by the Paris Agreement on global and regional biodiversity by using an integrated model framework. Our results highlight that climate mitigation efforts can benefit global biodiversity regardless of large-scale implementation of land-based mitigation measures. However, the negative impacts of mitigation measures on biodiversity are concentrated in regions with a higher contribution to land-use change and carbon sequestration. The results imply the need to consider the unequal regional distribution of benefits from climate mitigation, as well as mitigation options that avoid regional biodiversity loss by minimizing land-use change.

Abstract Afforestation is a major carbon dioxide removal technology but can negatively affect food and land systems. Here, we used an integrated assessment model to quantitatively demonstrate how the selection of forest type to use in afforestation could increase global carbon sequestration without compromising global food and land sustainability. Our findings indicate that if a carbon-intensive forest type is selected, afforestation would increase carbon sequestration by 25% compared to the level assuming the native forest type. At the same time, if implemented inappropriately at a large scale, afforestation would worsen the economy, food, and land systems due to decreased land efficiency in carbon removal compared to bioenergy with carbon capture and storage, leading to increased land expansion for carbon removal, higher food prices, and increased risk of hunger. These results suggest the need to implement carbon-intensive forest types with complementary measures to reduce the adverse impacts on food and land sustainability.

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.

Fire emits hazardous air pollutants, the most dominant of which is fine particulate matter of diameter ⩽2.5 μ m (PM _2.5 ). PM _2.5 is a great concern due to its adverse effects on public health. Previous studies have examined the health burden from fire-related PM _2.5 for the historical period; however, future global mortality associated with fire-PM _2.5 , particularly under the coexisting impacts of climate and socioeconomic changes, is yet to be projected. Here, we estimated the mortality associated to fire-PM _2.5 (fire-PM _2.5 mortality) for the present period (2010s) and then projected the mortality for the 2050s and 2090s under 10 scenarios created by combining two Representative Concentration Pathways (RCP2.6 or 6.0) with five Shared Socioeconomic Pathways (SSP1–5). We used the Li-Park fire model in combination with a chemical transport model and health risk assessment to calculate fire-PM _2.5 mortality. For the present period, the estimated fire-PM _2.5 mortality was 135 180 (105 403–163 738), which is 1.7 deaths per 100 000 population globally. When countries were grouped by income, the fire-PM _2.5 mortality rate was the highest in the high-income country group and lowest in the lowest-income country group. For the 2050s and 2090s, the fire-PM _2.5 mortality rate was projected to decrease under most scenarios because of decreases in fire emissions and baseline mortality rate. However, a scenario of high population growth and low technical development (SSP3) together with severe global warming (RCP6.0) would lead to an increase in the fire-PM _2.5 mortality rate in the 2090s, particularly in the highest-income countries, due to increased fire under drier and warmer weather conditions. Stratification of countries by gross domestic product indicated the need for adaptation efforts in the highest-income countries to avoid future increases of mortality associated with fire-PM _2.5 .

Abstract Climate scenario data set are indispensable for assessing future climate impacts. In this study, we developed statistically downscaled climate scenarios in Japan using modified bias correction method based on five general circulation models selected from the Coupled Model Intercomparison Project (CMIP) Phase 6 to facilitate impact assessments and adaptation strategies. Modification of time window of the original correction method results in successful agreement with the observed seasonal change of variables in each grid. The original CMIP6 models have a relatively small bias compared to CMIP5 models. The advantage of CMIP6‐based bias‐corrected scenarios is its availability for multiple global circulation models, which covered wide uncertainty in CMIP6 ensembles, with various emissions scenarios for representative concentration pathway (RCP) including RCP4.5, RCP2.6, and RCP8.5. Several temperature‐related indices derived from the CMIP6‐based climate scenarios agreed well with observations. The number of extremely hot days and nights increased nonlinearly in the future with additional global warming. An increase in the global warming level from 1 to 2°C above the early 1900s would increase the probability of the number of extremely hot days per year exceeding the 2018 case by 4.1 times. The development of bias‐corrected climate scenarios facilitates the study of various climate impacts on a CMIP6 basis.

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.

Assessing the impacts of future climate change on electricity demand is critical to managing electricity systems efficiently and identifying reliable adaptation measures to mitigate the adverse effects of climate change. This study assessed the impacts of future climate change on electricity demand while considering simultaneous interactions among multiple factors and the expected diurnal and seasonal variations of meteorological conditions. The study targeted regions across the wide climate zones of Japan and the period from 2020 to 2080. Models were developed using multiple meteorological and human behavioral indicators to explain the hourly demand for electricity. Multivariate adaptive regression splines were used for model construction to capture the simultaneous interaction effects of multiple meteorological variables. Hourly future climate scenarios were then generated based on the daily scenarios that were developed with four global climate models for representative concentration pathways (RCPs) 8.5 and 2.6. These scenarios were applied to the models of electricity demand to project future electricity demand at an hourly temporal resolution. The regional and temporal variations of the impacts of future climate change on electricity consumption were illustrated by examining the projected hourly electricity demand for ten regions in Japan. Nationwide total annual impacts on consumption were not large. Consumption was projected to increase by approximately 1.8% (0.3–3.0%) from 2020 to 2080 in Japan for RCP8.5. However, the increases of nationwide consumption during the hot seasons were significant, as much as 14.2% (10.7–18.0%). Less frequent but high-intensity spikes of demand were projected to increase in frequency and intensity during the summer as the years progressed from 2020 to 2080. The net impact was determined by the balance between the increase of electricity demand for cooling and the decrease of electricity demand for heating. The contrast between the increased demand for cooling and decreased demand for heating increased as the years progressed. In addition to the progressively larger magnitude of the impacts, climate change was predicted to gradually enlarge regions of greater consumption for electricity, the duration of the seasons of greater demand, and the hours per day when cooling was required. The impacts based on RCP8.5 could be reduced if the RCP2.6 scenario were followed.

Evaluating the heat risk among city dwellers is important. Here, the authors assessed the heat risk in Philippine cities using remote sensing data and social-ecological indicators and found that the cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high.

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.

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.

What will be the aggregated cost of climate change in achieving the Paris Agreement, including mitigation, adaptation, and residual impacts? Several studies estimated the aggregated cost but did not always consider the critical issues. Some do not address non-market values such as biodiversity and human health, and most do not address differentiating discount rates. In this study, we estimate the aggregated cost of climate change using an integrated assessment model linked with detailed-process-based climate impact models and different discount rates for market and non-market values. The analysis reveals that a climate policy with minimal aggregated cost is sensitive to socioeconomic scenarios and the way discount rates are applied. The results elucidate that a lower discount rate to non-market value—that is, a higher estimate of future value—makes the aggregated cost of achieving the Paris Agreement economically reasonable.

Greenhouse gas mitigation can involve land-use changes that alter the habitat available for wildlife. Here, Ohashi et al. perform an integrated assessment showing that climate mitigation can be beneficial for global biodiversity but may entail local biodiversity losses where land-based mitigation is implemented.

Abstract Bioenergy plays an important role in low greenhouse gas stabilization scenarios. Among various possible sources of bioenergy, dedicated bio‐crops could contribute to most of the potential. However, large scale bio‐crop deployment raises sustainability concerns. Policies to alleviate the pressure of bio‐crops on the terrestrial environment can affect bioenergy potential and production costs. Here, we estimated the maximum bioenergy potential under environmental protection policies (biodiversity and soil protection) and societal transformation measures from demand and supply side (demand‐side policy includes sustainable diet; supply‐side policy includes advanced technology and trade openness for food) by using an integrated assessment modelling framework, which consists of a general equilibrium model (Asian‐Pacific Integrated Model/Computable General Equilibrium) and a spatial land use allocation model (Asian‐Pacific Integrated Model/Platform for Land‐Use and Environmental Model). We found that the global advanced bioenergy potential under no policy was 245 EJ/year and that 192 EJ/year could be produced under US$5/GJ. These figures were 149 EJ/year and 110 EJ/year, respectively, under a full environmental policy. Biodiversity protection has a greater impact than soil protection due to its larger coverage and stronger implementation. Societal transformation measures effectively increase them to 186 EJ/year and 143 EJ/year, respectively, even under full environmental policies. These results imply that the large‐scale bioenergy deployment possibly needed for the climate target to limit the global mean temperature increase well below 2°C compared to the preindustrial level might face a trade‐off with environmental protection targets and that possible mitigation pathways in harmony with other environmental issues need to be explored.

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.

The Paris Agreement has confirmed that the ultimate climate policy goal is to hold the increase in the global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the increase to 1.5 °C. Moving the goal from 2 °C to 1.5 °C calls for much more concerted effort, and presents greater challenges and costs. This study uses an Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) to evaluate the role of socioeconomic factors (e.g. technological cost and energy demand assumptions) in changing mitigation costs and achieving the 1.5 °C and 2 °C goals, and to identify the channels through which socioeconomic factors affect mitigation costs. Four families of socioeconomic factors were examined, namely low-carbon energy-supply technologies, end-use energy-efficiency improvements, lifestyle changes and biomass-technology promotion (technology cost reduction and social acceptance promotion). The results show that technological improvement in low-carbon energy-supply technologies is the most important factor in reducing mitigation costs. Moreover, under the constraints of the 1.5 °C goal, the relative effectiveness of other socioeconomic factors, such as energy efficiency improvement, lifestyle changes and biomass-related technology promotion, becomes more important in decreasing mitigation cost in the 1.5 °C scenarios than in the 2 °C scenarios.

Since many new generation Earth system models (ESMs) have been suggested to overestimate future global warming, the latest report of the Intergovernmental Panel on Climate Change used the constrained range of global warming instead of that in the raw ensemble. However, it is not clear how the constraints of climate change projections potentially reduce the uncertainty of impact assessments. Here, we show that the climate-related uncertainty of the economic impact of climate change in the world can be constrained. By applying an impact emulator, we estimate the economic impacts in nine sectors based on 67 ESMs’ future climate change projections and find that the impacts in eight sectors are closely related to the recent past trend of global mean temperature, which is the metric used for the constraint of global warming projections. Observational constraints lower the upper bound of the aggregate economic impact simulated by the single emulator from 2.9% to 2.5% of the world gross domestic product (the relative reduction of variance is 31%) under the medium greenhouse gas concentration scenarios. Our results demonstrate how advances in climate science can contribute to reducing climate-related uncertainties in impact assessments, while we do not examine uncertainties of emulators and impact models.

Objective: To describe the need to create indicators or to use the competency framework of the Japanese six-year initial pharmacy education programme for the assessment of the programme from various viewpoints. Methods: A web-based survey of pharmacists who graduated from the previous four-year pharmacy education programme (experienced 4-YP pharmacists) and pharmacists who graduated from the six-year initial pharmacy education programme (6-YP pharmacists) was conducted, targeting 350 pharmacists (200 experienced 4-YP pharmacists and 150 6-YP pharmacists). Based on their perceptions, experienced 4-YP pharmacists and 6-YP pharmacists evaluated whether 6-YP pharmacists possessed the “Professional Competencies for Pharmacists”. The authors compared the 6-YP pharmacists’ self-perceived competency evaluations with the experienced 4-YP pharmacists’ perceived competency evaluations. Results: Regarding overarching competency as pharmacists (total competencies including competency 1–10 as pharmacists), the 6-YP pharmacists’ perceived competency self-evaluations were significantly higher overall than the experienced 4-YP pharmacists’ perceived competency evaluations (p ​

In this paper, we present a Deep Learning-based system for the support of information triaging on Twitter during emergency situations, such as disasters, or other influential events, such as political elections. The system is based on the assumption that a different type of information is required right after the event and some time after the event occurs. In a preliminary study, we analyze the language behavior of Twitter users during two kinds of influential events, namely, natural disasters and political elections. In the study, we analyze the credibility of information included by users in tweets in the above-mentioned situations, by classifying the information into two kinds: Primary Information (first-hand reports) and Secondary Information (second-hand reports, retweets, etc.). We also perform sentiment analysis of the data to check user attitudes toward the occurring events. Next, we present the structure of the system and compare a number of classifiers, including the proposed one based on Convolutional Neural Networks. Finally, we validate the system by performing an in-depth analysis of information obtained after a number of additional events, including an eruption of a Japanese volcano Ontake on 27 September 2014, as well as heavy rains and typhoons that occurred in 2020. We confirm that the methods works sufficiently well even when trained on data from nearly 10 years ago, which strongly suggests that the model is well-generalized and sufficiently grasps important aspects of each type of classified information.

Effects of carbon impurities and oxygen vacancies in Al2O3 film on the characteristics of Al2O3/GaN MOS capacitors were studied using the different atomic layer deposition (ALD) precursor and high-pressure water vapor annealing (HPWVA). Trimethyl aluminum (TMA: Al(CH3)3) and dimethyl aluminum hydride (DMAH: Al(CH3)2H) were used as ALD precursors to control the carbon impurities. On the other hand, oxygen vacancies in Al2O3 film were suppressed using the HPWVA. The DMAH precursor reduced the concentration of carbon impurities in the ALD Al2O3 film. It was found that the interface trap density (Dit) was mainly affected by the carbon impurities rather than the oxygen vacancies at the Al2O3/GaN interface. On the other hand, voltage stress induced flat band voltage (VFB) shift was attributed to both the carbon impurities and the oxygen vacancies.

Actions tackling with climate change can cause co-benefits and trade-offs with Sustainable Development Goals (SDGs) concerned with air pollution, water scarcity, food security, land use, and sustainable energy. Such interactions can be greatly influenced by socioeconomic conditions. The impacts of socioeconomic conditions on multiple SDGs have not been evaluated separately from climate policies. This paper employs a Representative Concentration Pathways–Shared Socio-economic Pathways (RCP-SSP) framework and the Asia-Pacific Integrated Model/computable general equilibrium (AIM/CGE) integrated assessment model to identify the global multi-sectoral consequences of socioeconomic conditions through 2050 under future SSP scenarios. Results show that changes of socioeconomic conditions consistent with the SSP1 pathway could always improve SDG indicators, with or without climate policies. In many respects, socioeconomic conditions are more important than climate policies in achieving SDGs, particularly SDGs concerned with food security and energy affordability, as well as in simultaneously achieving multiple SDGs. We conclude that the advantages of a joint effort to implement climate policies and promulgate socioeconomic changes should be recognized by policy makers.

Synergies and trade-offs exist between climate mitigation actions and target indicators of the Sustainable Development Goals (SDGs). Some studies have assessed such relationships, but the degree of such interaction remains poorly understood. Here, we show the SDG implications associated with CO _2 emissions reductions. We developed ‘marginal SDG-emissions-reduction values (MSVs)’, which represent the marginal impacts on SDG indicators caused by a unit CO _2 emissions reduction. This metric is applicable to national assessments and was applied to Asia. We found clear relationships between CO _2 emissions reduction rates and many SDG targets. For instance, 1% reduction of CO _2 can avoid 0.57% of air pollution-related premature deaths (SDG3), whereas the mean species richness (SDG15) is decreased by 0.026% with the same reduction (not including climate change impacts). Our findings are useful for assessing the SDG implications associated with CO _2 emissions reduction targets, which will help inform national climate policies.

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10-30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods.

Clarifying characteristics of hazards and risks of climate change at 2 °C and 1.5 °C global warming is important for understanding the implications of the Paris Agreement. We perform and analyze large ensembles of 2 °C and 1.5 °C warming simulations. In the 2 °C runs, we find substantial increases in extreme hot days, heavy rainfalls, high streamflow and labor capacity reduction related to heat stress. For example, about half of the world’s population is projected to experience a present day 1-in-10 year hot day event every other year at 2 °C warming. The regions with relatively large increases of these four hazard indicators coincide with countries characterized by small CO _2 emissions, low-income and high vulnerability. Limiting global warming to 1.5 °C, compared to 2 °C, is projected to lower increases in the four hazard indicators especially in those regions.

The Paris Agreement set long-term global climate goals to pursue stabilization of the global mean temperature increase at below 2 °C (the so-called 2 °C goal). Individual countries submitted their own short-term targets, mostly for the year 2030. Meanwhile, the UN’s sustainable development goals (SDGs) were designed to help set multiple societal goals with respect to socioeconomic development, the environment, and other issues. Climate policies can lead to intended or unintended consequences in various sectors, but these types of side effects rarely have been studied in China, where climate policies will play an important role in global greenhouse gas emissions and sustainable development is a major goal. This study identified the extent to which climate policies in line with the 2 °C goal could have multi-sectoral consequences in China. Carbon constraints in China in the 2Deg scenario are set to align with the global 2 °C target based on the emissions per capita convergence principle. Carbon policies for NDC pledges as well as policies in China regarding renewables, air pollution control, and land management were also simulated. The results show that energy security and air quality have co-benefits related to climate policies, whereas food security and land resources experienced negative side effects (trade-offs). Near-term climate actions were shown to help reduce these trade-offs in the mid-term. A policy package that included food and land subsidies also helped achieve climate targets while avoiding the adverse side effects caused by the mitigation policies. The findings should help policymakers in China develop win–win policies that do not negatively affect some sectors, which could potentially enhance their ability to take climate actions to realize the global 2 °C goal within the context of sustainable development.

Adult bronchial asthma (hereinafter, asthma) is characterized by chronic airway inflammation, reversible airway narrowing, and airway hyperresponsiveness. Long-standing asthma induces airway remodeling to cause an intractable asthma. The number of patients with asthma has increased, while the number of patients who die from asthma has decreased (1.7 per 100,000 patients in 2009). The aim of asthma treatment is to enable patients with asthma to lead a healthy life without any symptoms. A partnership between physicians and patients is indispensable for appropriate treatment. Long-term management with agents and elimination of causes and risk factors are fundamental to asthma treatment. Four steps in pharmacotherapy differentiate mild to intensive treatments; each step includes an appropriate daily dose of an inhaled corticosteroid (ICS), varying from low to high doses. Long-acting β2 agonists (LABA), leukotriene receptor antagonists, and theophylline sustained-release preparation are recommended as concomitant drugs, while anti-IgE antibody therapy is a new choice for the most severe and persistent asthma. Inhaled β2 agonists, aminophylline, corticosteroids, adrenaline, oxygen therapy, etc., are used as needed against acute exacerbations. Allergic rhinitis, chronic obstructive pulmonary disease (COPD), aspirin induced asthma, pregnancy, and cough variant asthma are also important factors that need to be considered.

Background: Rat trachea display a differential topographical distribution of connective tissue mast cells (CTMC) and mucosal mast cells (MMC) that may imply regional differences in the release of allergic mediators such as tumor necrosis factor-α (TNF-α) and eicosanoids.

Energy demand associated with space heating and cooling is expected to be affected by climate change. There are several global projections of space heating and cooling use that take into consideration climate change, but a comprehensive uncertainty of socioeconomic and climate conditions, including a 1.5 °C global mean temperature change, has never been assessed. This paper shows the economic impact of changes in energy demand for space heating and cooling under multiple socioeconomic and climatic conditions. We use three shared socioeconomic pathways as socioeconomic conditions. For climate conditions, we use two representative concentration pathways that correspond to 4.0 °C and 2.0 °C scenarios, and a 1.5 °C scenario driven from the 2.0 °C scenario with assumption in conjunction with five general circulation models. We find that the economic impacts of climate change are largely affected by socioeconomic assumptions, and global GDP change rates range from +0.21% to −2.01% in 2100 under the 4.0 °C scenario, depending on the socioeconomic condition. Sensitivity analysis that differentiates the thresholds of heating and cooling degree days clarifies that the threshold is a strong factor that generates these differences. Meanwhile, the impact of the 1.5 °C is small regardless of socioeconomic assumptions (−0.02% to −0.06%). The economic loss caused by differences in socioeconomic assumption under the 1.5 °C scenario is much smaller than that under the 2 °C scenario, which implies that stringent climate mitigation can work as a risk hedge to socioeconomic development diversity.

Climate change mitigation to limit warming to 1.5 °C or well below 2 °C, as suggested by the Paris Agreement, can rely on large-scale deployment of land-related measures (e.g. afforestation, or bioenergy production). This can increase food prices, and hence raises food security concerns. Here we show how an inclusive policy design can avoid these adverse side-effects. Food-security support through international aid, bioenergy tax, or domestic reallocation of income can shield impoverished and vulnerable people from the additional risk of hunger that would be caused by the economic effects of policies narrowly focussing on climate objectives only. In the absence of such support, 35% more people might be at risk of hunger by 2050 (i.e. 84 million additional people) in a 2 °C-consistent scenario. The additional global welfare changes due to inclusive climate policies are small (

The expired nitric oxide (NO) concentration is known to be higher in asthmatic subjects than in normal subjects. To elucidate the role of NO in asthma, we examined the expired NO concentrations in relation to the type (atopic, mixed, non- atopic), and severity (mild, moderate, severe) of asthmatics, as well as the influence of steroid treatment. Twenty-seven normal subjects, 48 asthmatics, 8 subjects with allergic rhinitis, and 13 subjects with pulmonary emphysema participated in the study. The expired NO concentration was significantly higher in asthmatics and patients with allergic rhinitis than in normal subjects (P

We performed an intercomparison of river discharge regulated by dams under four meteorological forcings among five global hydrological models for a historical period by simulation. This is the first global multimodel intercomparison study on dam-regulated river flow. Although the simulations were conducted globally, the Missouri–Mississippi and Green–Colorado Rivers were chosen as case-study sites in this study. The hydrological models incorporate generic schemes of dam operation, not specific to a certain dam. We examined river discharge on a longitudinal section of river channels to investigate the effects of dams on simulated discharge, especially at the seasonal time scale. We found that the magnitude of dam regulation differed considerably among the hydrological models. The difference was attributable not only to dam operation schemes but also to the magnitude of simulated river discharge flowing into dams. That is, although a similar algorithm of dam operation schemes was incorporated in different hydrological models, the magnitude of dam regulation substantially differed among the models. Intermodel discrepancies tended to decrease toward the lower reaches of these river basins, which means model dependence is less significant toward lower reaches. These case-study results imply that, intermodel comparisons of river discharge should be made at different locations along the river's course to critically examine the performance of hydrological models because the performance can vary with the locations.

The exposure of workers to hot environments is expected to increase as a result of climate change. In order to prevent heat-related illness, it is recommended that workers take breaks during working hours. However, this would lead to reductions in worktime and labor productivity. In this study, we estimate the economic cost of heat-related illness prevention through worker breaks associated with climate change under a wide range of climatic and socioeconomic conditions. We calculate the worktime reduction based on the recommendation of work/rest ratio and the estimated future wet bulb glove temperature, which is an index of heat stresses. Corresponding GDP losses (cost of heat-related illness prevention through worker breaks) are estimated using a computable general equilibrium model throughout this century. Under the highest emission scenario, GDP losses in 2100 will range from 2.6 to 4.0% compared to the current climate conditions. On the other hand, GDP losses will be less than 0.5% if the 2.0 °C goal is achieved. The benefit of climate-change mitigation for avoiding worktime loss is comparable to the cost of mitigation (cost of the greenhouse gas emission reduction) under the 2.0 °C goal. The relationship between the cost of heat-related illness prevention through worker breaks and global average temperature rise is approximately linear, and the difference in economic loss between the 1.5 °C goal and the 2.0 °C goal is expected to be approximately 0.3% of global GDP in 2100. Although climate mitigation and socioeconomic development can limit the vulnerable regions and sectors, particularly in developing countries, outdoor work is still expected to be affected. The effectiveness of some adaptation measures such as additional installation of air conditioning devices or shifting the time of day for working are also suggested. In order to reduce the economic impacts, adaptation measures should also be implemented as well as pursing ambitious climate change mitigation targets.

Climate change is one of the greatest long-term challenges faced by humanity. In the projection of climate change impacts, scenarios based on assumptions regarding future conditions are commonly used. Shared socio-economic pathways (SSPs) are widely employed as socio-economic scenarios for global-scale predictions. The SSPs provide future projections of population and gross domestic products. However, SSPs are not suitable for detailed assessments for a country such as Japan, as they include only global regional data. The S-18 project aims at a nationally unified projection of climate change impacts across multiple sectors in Japan. In contribution to this, based on the previous study for Japan SSPs, we established common socio-economic scenarios designated as Japan SSP1, Japan SSP5, and status quo. Japan SSP1 and Japan SSP5 are based on qualitative links to global SSPs. Japan SSP1 foresees sustainable society with low-carbon emission, while Japan SSP5 envisions a society dependent on fossil fuels, emitting large amounts of greenhouse gases. The status-quo scenario assumes no future change based on the current conditions in Japan. Moreover, we provided a common dataset of population and land-use under these scenarios. Population data were obtained from existing population projections, and land-use data were estimated according to population changes and current land-use classifications. Here, the dataset prepared for the S-18 project is detailed and possibilities for its improvement discussed. [ABSTRACT FROM AUTHOR]

Under the Paris Agreement, parties set and implement their own emissions targets as nationally determined contributions (NDCs) to tackle climate change. International carbon emissions trading is expected to reduce global mitigation costs. Here, we show the benefit of emissions trading under both NDCs and a more ambitious reduction scenario consistent with the 2 °C goal. The results show that the global welfare loss, which was measured based on estimated household consumption change in 2030, decreased by 75% (from 0.47% to 0.16%), as a consequence of achieving NDCs through emissions trading. Furthermore, achieving the 2 °C targets without emissions trading led to a global welfare loss of 1.4%–3.4%, depending on the burden-sharing scheme used, whereas emissions trading reduced the loss to around 1.5% (from 1.4% to 1.7%). These results indicate that emissions trading is a valuable option for the international system, enabling NDCs and more ambitious targets to be achieved in a cost-effective manner.