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.

Regional trends and drivers of the global methane budget.

The ongoing development of the Global Carbon Project (GCP) global methane (CH4 ) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions-China, Southeast Asia, USA, South Asia, and Brazil-account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH4  yr-1 in 2008-2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.

Intergenerational inequities in exposure to climate extremes.

Young generations are severely threatened by climate change.

Nitrogen budgets in Japan from 2000 to 2015: Decreasing trend of nitrogen loss to the environment and the challenge to further reduce nitrogen waste.

The benefits of the artificial fixation of reactive nitrogen (Nr, nitrogen [N] compounds other than dinitrogen), in the form of N fertilizers and materials are huge, while at the same time posing substantial threats to human and ecosystem health by the release of Nr to the environment. To achieve sustainable N use, Nr loss to the environment must be reduced. An N-budget approach at the national level would allow us to fully grasp the whole picture of Nr loss to the environment through the quantification of important N flows in the country. In this study, the N budgets in Japan were estimated from 2000 to 2015 using available statistics, datasets, and literature. The net N inflow to Japanese human sectors in 2010 was 6180 Gg N yr-1 in total. With 420 Gg N yr-1 accumulating in human settlements, 5760 Gg N yr-1 was released from the human sector, of which 1960 Gg N yr-1 was lost to the environment as Nr (64% to air and 36% to waters), and the remainder assumed as dinitrogen. Nr loss decreased in both atmospheric emissions and loss to terrestrial water over time. The distinct reduction in the atmospheric emissions of nitrogen oxides from transportation, at -4.3% yr-1, was attributed to both emission controls and a decrease in energy consumption. Reductions in runoff and leaching from land as well as the discharge of treated water were found, at -1.0% yr-1 for both. The aging of Japan's population coincided with the reductions in the per capita supply and consumption of food and energy. Future challenges for Japan lie in further reducing N waste and adapting its N flows in international trade to adopt more sustainable options considering the reduced demand due to the aging population.

Methane budget of East Asia, 1990-2015: A bottom-up evaluation.

The regional budget of methane (CH4) emissions for East Asia, a crucial region in the global greenhouse gas budget, was quantified for 1990-2015 with a bottom-up method based on inventories and emission model simulations. Anthropogenic emissions associated with fossil fuel extraction, industrial activities, waste management, and agricultural activities were derived from the Emission Database for Global Atmospheric Research version 4.3.2 and compared with other inventories. Emissions from natural wetlands and CH4 uptake by upland soil oxidation were estimated using the Vegetation Integrative SImulator for Trace gases (VISIT), a biogeochemical model that considers historical land use and climatic conditions. Emissions from biomass burning and termites were calculated using satellite and land-use data combined with empirical emission factors. The resulting average annual estimated CH4 budget for 2000-2012 indicated that East Asia was a net source of 67.3 Tg CH4 yr-1, of which 88.8% was associated with anthropogenic emissions. The uncertainty (±standard deviation) of this estimate, ±14 Tg CH4 yr-1, stemmed from data and model inconsistencies. The increase of the net flux from 60.2 Tg CH4 yr-1 in 1990 to 78.0 Tg CH4 yr-1 in 2012 was due mainly to increased emissions by the fossil fuel extraction and livestock sectors. Our results showed that CH4 was a crucial component of the regional greenhouse gas budget. A spatial analysis using 0.25°â€¯× 0.25° grid cells revealed emission hotspots in urban areas, agricultural areas, and wetlands. These hotspots were surrounded by weak sinks in upland areas. The estimated natural and anthropogenic emissions fell within the range of independent estimates, including top-down estimates from atmospheric inversion models. Such a regional accounting is an effective way to elucidate climatic forcings and to develop mitigation policies. Further studies, however, are required to reduce the uncertainties in the budget.

Global soil nitrous oxide emissions since the preindustrial era estimated by an ensemble of terrestrial biosphere models: Magnitude, attribution, and uncertainty.

Our understanding and quantification of global soil nitrous oxide (N2 O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO2 concentration, on global soil N2 O emissions for the period 1861-2016 using a standard simulation protocol with seven process-based terrestrial biosphere models. Results suggest global soil N2 O emissions have increased from 6.3 ± 1.1 Tg N2 O-N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N2 O-N/year in the recent decade (2007-2016). Cropland soil emissions increased from 0.3 Tg N2 O-N/year to 3.3 Tg N2 O-N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N2 O emissions since the 1970s. However, US cropland N2 O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N2 O emissions appear to have decreased by 14%. Soil N2 O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N2 O-N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO2 concentration reduced soil N2 O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N2 O emissions, this study recommends several critical strategies for improving the process-based simulations.

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.

Global land-use allocation model linked to an integrated assessment model.

We developed a global land-use allocation model that can be linked to integrated assessment models (IAMs) with a coarser spatial resolution. Using the model, we performed a downscaling of the IAMs' regional aggregated land-use projections to obtain a spatial land-use distribution, which could subsequently be used by Earth system models for global environmental assessments of ecosystem services, food security, and climate policies. Here we describe the land-use allocation model, discuss the verification of the downscaling technique, and explain the influences of the downscaling on estimates of land-use carbon emissions. A comparison of the emissions estimated with and without downscaling suggested that the land-use downscaling would help capture the spatial distribution of carbon stock density and regional heterogeneity of carbon emissions caused by cropland and pasture land expansion.

Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model.

Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO2) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO2. In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

Changing ecophysiological processes and carbon budget in East Asian ecosystems under near-future changes in climate: implications for long-term monitoring from a process-based model.

Using a process-based model, I assessed how ecophysiological processes would respond to near-future global changes predicted by coupled atmosphere-ocean climate models. An ecosystem model, Vegetation Integrative SImulator for Trace gases (VISIT), was applied to four sites in East Asia (different types of forest in Takayama, Tomakomai, and Fujiyoshida, Japan, and an Alpine grassland in Qinghai, China) where observational flux data are available for model calibration. The climate models predicted +1-3 degrees C warming and slight change in annual precipitation by 2050 as a result of an increase in atmospheric CO2. Gross primary production (GPP) was estimated to increase substantially at each site because of improved efficiency in the use of water and radiation. Although increased respiration partly offset the GPP increase, the simulation showed that these ecosystems would act as net carbon sinks independent of disturbance-induced uptake for recovery. However, the carbon budget response relied strongly on nitrogen availability, such that photosynthetic down-regulation resulting from leaf nitrogen dilution largely decreased GPP. In relation to long-term monitoring, these results indicate that the impacts of global warming may be more evident in gross fluxes (e.g., photosynthesis and respiration) than in the net CO2 budget, because changes in these fluxes offset each other.

[Relation between comprehensive-geriatric assessment and the ability of self-administration in elderly diabetic patients].

Intellectual ability of self-administration plays a crucial role in a diabetes regimen. However, in many cases, self-administration is considered difficult, because of the impairment of activities of the individual's daily living (ADL), instrumental ADL and cognitive function. To assess comprehensive-geriatric-assessment (CGA) in elderly diabetic sufferers, 62 elderly inpatients and outpatients aged over 70 years were investigated. CGA includes Barthel index (BI), Mini-mental-state-examination (MMSE) and the Tokyo Metropolitan Institute of Gerontology index of competence (TMIGIC). The relation of ability to self-administer and CGA was examined. In oral therapy, there was significant difference between self-administration and non-self-administration in MMSE (p=0.0065), BI (p=0.0219) and TMIGIC (p=0.0053). Among these indexes, TMIGIC was the most sensitive index in oral therapy. In insulin therapy, there was also significant difference between self-administration and non-self-administration: MMSE (p=0.00042), BI (p=0.000019) and TMIGIC (p=0.0019). Among these indexes, BI was the most sensitive index in insulin therapy. It was suggested that CGA was useful to assess the ability of self-administration in elderly diabetic patients.