# National Institute for Environmental Studies

• Tsukuba, Japan
Recent publications
Background The oogamous green algal genus Volvox exhibits extensive diversity in mating systems, including heterothallism and homothallism with unisexual (male and/or female) and/or bisexual spheroids. Although four mating systems have been recognized worldwide in strains identified as “ Volvox africanus ”, most of these strains are extinct. However, we previously rediscovered two types of the four mating systems (heterothallic, and homothallic with male and bisexual spheroids within a clone) from an ancient Japanese lake, Lake Biwa. Results Here, we obtained strains exhibiting the third mating system (homothallic with unisexual male and female spheroids within a clone) from a freshwater area of Kalasin Province, Thailand. When sexual reproduction was induced in the present Thai strains, both male and female unisexual spheroids developed to form smooth-walled zygotes within a clonal culture. Phylogenetic analyses of the internal transcribed spacer region-2 of nuclear ribosomal DNA sequences from all four mating systems, including the extinct strains, resolved the third mating system is basal or paraphyletic within the homothallic clade. Conclusions The present morphological and molecular data of the Thai strains indicate that they belong to the homothallic species V. africanus . The phylogenetic results suggested that third mating system (homothallic with separate male and female sexual spheroids) may represent an initial evolutionary stage of transition from heterothallism to homothallism within Volvox africanus . Further field collections in geologically stable intracontinental regions may be fruitful for studying diversity and taxonomy of the freshwater green algal genus Volvox .
Abstract We developed lookup tables for the correlated k-distribution (CKD) method in the 940 nm water vapor absorption region (WV-CKD), with the aim of rapid and accurate computation of narrow-band radiation around 940 nm (10,000–10,900 $${\mathrm{cm}}^{-1}$$ cm - 1 ) for ground-based angular-scanning radiometer data analysis. Tables were constructed at three spectral resolutions (2, 5, and 10 $${\mathrm{cm}}^{-1}$$ cm - 1 ) with quadrature values (point and weight) and numbers optimized using simulated sky radiances at ground level, which had accuracies of ≤ 0.5% for sub-bands of $$10 {\mathrm{cm}}^{-1}$$ 10 cm - 1 . Although high-resolution WV-CKD requires numerous quadrature points, the number of executions of the radiative transfer model is reduced to approximately 1/46 of the number used in the line-by-line approach by our WV-CKD with a resolution of 2 $${\mathrm{cm}}^{-1}$$ cm - 1 . Furthermore, we confirmed through several simulations that WV-CKD could be used to compute radiances with various vertical profiles. The accuracy of convolved direct solar irradiance and diffuse radiance at a full width at half maximum (FWHM) of 10 nm, computed with the WV-CKD, is
The Great East Japan Earthquake (GEJE) in March 2011 greatly changed the spatial pattern of energy use in Fukushima Prefecture. The previously nuclear-reliant energy policy has transformed, with energy now generated mainly by fossil fuels and renewable sources. The spatio-temporal variation of fossil fuel use and the major causes of these changes have not previously been fully clarified. This study quantified the annual fossil fuel use in eight user sectors at high spatial resolution using a bottom-up approach. The total fossil fuel use in Fukushima is estimated to have increased by about 91,233 TJ from 2010 to 2015, despite decreases in most socioeconomic indicators. The increase was mainly attributed to changes in electricity generation (104,521 TJ). The three sectors with the greatest decrease in energy use were road transportation (-7159 TJ), industrial and commercial (-3608 TJ), and residential (-2334 TJ). Spatial analysis using high-resolution maps identified areas of increased energy use mainly in central, southeastern, and northeastern Fukushima and confirmed some local variations in energy use by sector. It showed that decreasing energy use in the area within 20 km of the Fukushima Daiichi Nuclear Power Station resulted in increased use in areas located >20 km from the power station. Sensitivity analysis clarified the relations among factors underlying each sector’s changing energy use before and after the GEJE. For instance, consider the electricity generation sector: reduced energy use was caused by decreased energy use intensity (-23,299 TJ) and the increased use of biomass (-4848 TJ), whereas increases were caused by rising utilization efficiency (102,410 TJ) and increased electricity generation capacity (35,988 TJ), which led to a large overall increase for this sector (104,521 TJ). However, road transportation’s negative energy use change (-7159 TJ) arose owing to decreased traffic volumes (-7573 TJ) and decreased energy use intensity (-7177 TJ), despite some positive energy use changes caused by the increased proportion of large vehicles (3684 TJ) and changes in mean travel speed (1381 TJ). The approach used in this study will be helpful for policy makers to evaluate spatio-temporal variations and develop policies to reduce energy use in response to unusual local events.
This study tried to assess the impact of the food loss reduction on Indonesia's economy and environment. The simulation utilises the Computable General Equilibrium (CGE) model, which simulates the effect of food loss technologies adoption in food crops and livestock sectors. The simulation results indicate that the food loss reduction potentially has a positive impact economically and environmentally. From an economic perspective, applying technology to reduce food loss is estimated to increase Indonesia's GDP by 0.37% (around 88 trillion IDR) by 2030 compared to the BAU level. This economic improvement is mostly driven by the increase in household consumption, which can be increased by around 0.47% by 2030. This result follows that around 40% of household incomes in Indonesia are spent on food expenditure. Food loss reduction holds an important key to increasing food availability and household consumption of foods. Our simulation also indicated some positive effects of food loss reduction on the environment. By reducing the food loss, around 14.19 Mt CO2eq of GHG can also be reduced by 2030, while the cropland needed for food crop cultivation can also be reduced by 3.37% by 2030. Finally, this result highlights the importance of food loss reduction for Indonesia's economy and environment. It is recommended that the government pay serious attention to applying food loss reduction technologies to all food crops in the country.
Tracking decarbonization effects requires a model for the identification of spatial energy demands on city facilities. However, most developing countries lack detailed discrete time and device-specific energy demand data. In this study, we installed multiple energy demand monitoring systems that could observe electricity demands at the device level in some residences in Bogor, Indonesia. The study aimed to estimate the time-series and equipment ratio of electricity consumption by households in the entire city based on the monitoring data. However, the number of households monitored was small, and therefore unlikely to be regarded as having a representative system. Therefore, we used questionnaire data to create monitored mimic data and increased the number of samples to estimate the energy demand characteristics of the entire city via spatial interpolation. In addition, we developed a reinforcement learning system for discrete time–electricity demand estimation systems for unmonitored households using a 5-step procedure; 1) Analyzing energy demand and its patterns from monitoring data, 2) Questionnaire-based surveying of households, 3) Estimation of energy demand and its patterns based on questionnaire responses in monitored households, 4) Development of a deep learning model that extends the results from (3) to unmonitored households using data fusion, and 5) Spatial interpolation of energy demand characteristics for all households in Bogor using a spatial statistics method. The spatial electricity demand of households was interpolated from GIS and high-resolution satellite data matching procedures. Based on this analysis, we developed an hourly energy demand prediction system that could be automatically improved by adding new data from the reinforced learning framework.
Climate change is expected to exacerbate drought conditions over many global regions. However, the future risk posed by droughts depends not only on the climate-induced changes but also on the changes in societal exposure and vulnerability to droughts. Here we illustrate how the consideration of human vulnerability alters global drought risk associated with runoff (hydrological) and soil moisture (agriculture) droughts during the 21st-century. We combine the changes in drought frequency, population growth, and human development as a proxy of vulnerability to project global drought risk under plausible climate and socioeconomic development pathways. Results indicate that the shift toward a pathway of high greenhouse gas emissions and socioeconomic inequality leads to i) increased population exposure to runoff and soil moisture droughts by 81% and seven folds, respectively, and ii) a stagnation of human development. These consequences are more pronounced for populations living in low than in very high human development countries. In particular, Sub-Saharan Africa and South Asia, where the majority of the world's less developed countries are located, fare the worst in terms of future drought risk. The disparity in risk between low and very high human development countries can be substantially reduced in the presence of a shift toward a world of rapid and sustainable development that actively reduces social inequality and emissions. Our results underscore the importance of rapid human development in hotspots of drought risk where effective adaptation is most needed to reduce future drought impacts.
We have determined the hourly atmospheric concentrations of ¹²⁹I in aerosols dispersed into the atmosphere by the nuclear accident at the Fukushima Daiichi Nuclear Power Plant (FD1NPP) on March 11, 2011. Data were obtained by measuring the quantity of ¹²⁹I in suspended particulate matter (SPM) collected on filter tapes at 41 SPM monitoring stations in Fukushima and other prefectures in eastern Japan, including the metropolitan area of Tokyo and the surrounding area. After scrutiny, 500 out of 920 hourly SPM samples were determined to be reliable (i.e., devoid of cross-contamination), and these were subjected to further analysis and discussion. Based on the data from these samples, especially data from the four SPM sampling sites located close to the FD1NPP (Futaba, Naraha, Haramachi and Nihonmatsu), the time-series variations in the atmospheric concentration of ¹²⁹I and the activity ratio of ¹²⁹I/¹³⁷Cs were reconstructed by using ¹³⁷Cs concentration data in the literature. ¹²⁹I and ¹³⁷Cs were observed to be continuously and sometimes explosively dispersed into the atmosphere in aerosols transported by radioactive plumes from the FD1NPP. The highest activity concentrations of ¹²⁹I and ¹³⁷Cs were observed in the SPM sample at the Futaba SPM station (3.2 km west-northwest of the FD1NPP) at 14:00–15:00 on March 12 after the venting of Unit 1. Systematically high ¹²⁹I/¹³⁷Cs activity ratios were observed at the Futaba and Haramachi stations from March 12 to 14, suggesting that radioactive masses released from the FD1NPP during the first few days after the nuclear accident were relatively enriched in radioiodine. High activity ratios of ¹²⁹I/¹³⁷Cs were also measured starting on March 21 at Naraha (17.5 km south of FD1NPP) and from March 22–23 in the metropolitan area which must have been caused by a different type of emission event(s) on those days at the FD1NPP, as previously reported. The ¹²⁹I data from this study are highly effective in the validation and elaboration of the modelling of the atmospheric dispersion of radioiodine. They further contribute to assessing the internal exposure due to inhalation of ¹³¹I estimated by means of such elaborate atmospheric diffusion models.
An improved understanding of the global carbon cycle is important to the success of efforts to mitigate climate change, such as agreed in the Paris meeting of the UN Conference of the Parties in 2016. Climate change mitigation and adaptation requires action by individual countries, municipalities, cities, and their citizens. These actions require a diverse range of information. Current efforts responding to the need for these carbon observations are, however, fragmented. There is a need to coordinate observations on carbon, GHG measurements, and ecosystem processes related to carbon cycle dynamics. The GEO Carbon and Greenhouse Gas Initiative (GEO‐C) was launched to further support continuity and coherence of the ongoing efforts and facilitate their cooperation and interoperability. The GEO‐C Initiative (1) supports the development of a holistic cross‐domain, global carbon cycle and GHG monitoring system that provides long‐term, high quality, and open access; (2) engages with users and policy makers and ensures the fitness for purpose of the observation and reporting system; and (3) aims to establish a common terminology (including scientists and decision makers) involved in addressing GHG emissions. This chapter describes the background of the GEO‐GHG initiative and describes the main aims of the initiative and first steps toward implementation.
Time perspectives may change as people age and become more aware of their limited time remaining in life. A research question is whether awareness of one’s limited time remaining associates with pet ownership among older adults. Although owning pets in old age involves both benefits and risks, the association between pet ownership and subjective remaining time in life remains understudied. The present study examines the associations between pet ownership and the subjective perception of time remaining in life among older adults. We assessed the experience of pet ownership (dog or cat) and age-related future time perspectives of 329 community-dwelling older adults in Japan. By adopting three constructs of the Future Time Perspective scale, we found that current dog ownership was associated with more limited future opportunities but not with limited time left or future constraints. Older dog owners may focus on the present rather than new future opportunities, yet they may see the future of their dogs that require care. Yet no such association was observed among current cat owners. The present findings extend the previous research of age-related future time perspectives by suggesting that pet ownership in late adulthood may be another contributing factor that needs to be better understood.
Solar radiation received at the Earth's surface (Rs) is comprised of two components, the direct radiation (Rd) and the diffuse radiation (Rf). Rd, the direct beam from the sun, is essential for concentrated solar power generation. Rf, scattered by atmospheric molecules, aerosols, or cloud droplets, has a fertilization effect on plant photosynthesis. But how Rd and Rf change diurnally is largely unknown owing to the lack of long‐term measurements. Taking advantage of 22 years of homogeneous hourly surface observations over China, this study documents the climatological means and evolutions in the diurnal cycles of Rd and Rf since 1993, with an emphasis on their implications for solar power and agricultural production. Over the solar energy resource region, we observe a loss of Rd which is relatively large near sunrise and sunset at low solar elevation angles when the sunrays pass through the atmosphere on a longer pathway. However, the concentrated Rd energy covering an average 10‐hr period around noon during a day is relatively unaffected. Over the agricultural crop resource region, the large amounts of clouds and aerosols scattering more of the incoming light result in Rf taking the main proportion of Rs during the whole day. Rf resources and their fertilization effect in the main crop region of China further enhances since 1993 over almost all hours of the day.
Knowledge of the effects of local‐ and landscape‐scale environmental factors is indispensable for the conservation of wetland biodiversity. We surveyed the distribution and abundance of two spring‐dependent invertebrates, the Japanese freshwater crab Geothelphusa dehaani and larvae of dragonfly Anotogaster sieboldii, at 37 spring‐fed wetlands in the Lake Inba watershed, Japan. The relationships among local factors (water temperature, channel‐water velocity, substrate type, and abundance of the red swamp crayfish Procambarus clarkii), a landscape‐scale factor (the percentage of permeable surface in catchment; PPSC), and catch per unit effort (CPUE) of each species were analyzed using path analyses. PPSC indirectly affected the CPUE of both G. dehaani and A. sieboldii via different processes. For G. dehaani, PPSC affected the CPUE via a positive effect on channel‐water velocity and substrate composition in the wetland. On the other hand, PPSC positively affected the CPUE of A. sieboldii by decreasing the summer water temperature. Red swamp crayfish had no significant direct effects on either species, although we found a significant negative effect of channel‐water velocity on the distribution of red swamp crayfish. For conservation of these spring‐dependent species, we suggest preserving the area of permeable surface in the watershed in order to maintain flow velocity and low water temperature in wetlands. The distribution and abundance of two spring‐dependent invertebrates, Geothelphusa dehaani, and larval of Anotogaster sieboldii, were surveyed, and the effects of local‐ and landscape‐scale environmental factors were analyzed in the Lake Inbanuma watershed. The results suggested that preserving the area of the permeable surface in the watershed can contribute to conserving these species through the maintenance of flow velocity or water temperature in wetlands.
Monoethanolamine (MEA), a toxic organic chemical, is widely used in industries and is found in their wastewater. Anaerobic MEA degradation is an appropriate strategy to reduce energy and cost for treatment. Industry wastewaters also contain sulfate, but information on the effects of sulfate on MEA degradation is limited. Here, an up-flow anaerobic sludge blanket (UASB) for MEA-containing wastewater treatment was operated under psychrophilic conditions (18–20ºC) to investigate the effects of sulfate on the microbial characteristics of the retained sludge. To acclimatize the sludge, the proportion of MEA in the influent (containing sucrose, acetate, and propionate) was increased from 15% to 100% of total COD (1,500 mg L–1); sulfate was then added to the influent. The COD removal efficiency remained above 95% despite the increase in MEA and sulfate. However, granular sludge disintegration was observed when sulfate was increased from 20 to 330 mg L–1. Batch tests revealed that propionate and acetate were produced as the metabolites of MEA degradation. In response to sulfate acclimation, methane-producing activities for propionate and hydrogen declined, while sulfate-reducing activities for MEA, propionate, and hydrogen increased. Accordingly, acclimation and changes in dominant microbial groups promoted the acetogenic reaction of propionate by sulfate reduction.
Understanding the changes in the temporal and spatial concentrations of chemical substances in sediment toxicity tests facilitates interpretation of their toxicity and accumulation in benthic organisms, because benthic organisms are affected by chemicals via multiple exposure pathways. However, such investigations using chronic sediment toxicity tests have rarely been performed. To examine the concentration profiles of a hydrophobic organic chemical using chronic spiked‐sediment toxicity tests, we performed 28‐day sediment toxicity tests of fluoranthene with a freshwater amphipod Hyalella azteca using a semi flow‐through system and compared the results with those of 10‐day tests. In these experiments, we measured various types of fluoranthene concentrations over the test periods: total dissolved (Cdiss) and freely dissolved concentrations (Cfree) in overlying and pore water as well as sediment concentrations. We also examined which concentration correlated with the amphipod bioconcentration factor (BCF). We found that both overlying and pore water Cfree did not differ significantly on days 10 and 28. Sediment concentrations remained almost stable for 28 days, whereas Cdiss in overlying water varied temporally. These results suggest that the 28‐day test provides almost constant concentrations of fluoranthene, particularly in pore water, even in a semi flow‐through system. Additionally, the comparison of BCF of fluoranthene on day 10 in the present study with that obtained from water‐only tests reported in the literature suggested that Cfree in pore water was the most representative indicator of bioaccumulation in H. azteca. Our findings support the possible use of a water‐exchange system in chronic spiked‐sediment toxicity tests of hydrophobic organic chemicals. However, further studies using sediments and chemicals with different properties are warranted to generalize the findings of this study. This article is protected by copyright. All rights reserved.
Environmental conditions critically affect the expansion behaviour of concrete due to alkali–silica reaction (ASR) and therefore must be modelled to predict the ASR-induced expansion behaviour. In addition, laboratory tests are important for the provision of useful data for numerical models, since these models often require the calibration of some unknown parameters according to the materials tested. To address this, the authors have developed a testing method for concrete expansion, called the alkali-wrapped concrete prism test (AW-CPT). Predictions using the results of the AW-CPT would be beneficial for the assessment of potential expansion of concrete when exposed to the outdoor environment. In this study, the effects of environmental conditions on ASR-induced expansion behaviours is determined through exposure and laboratory tests. The environmental conditions are modelled and implemented in numerical simulations. The results indicate that the solar insolation and rainfall are critical parameters for modelling the environmental conditions as well as ambient temperature and relative humidity.
Accurate estimates of the carbon dioxide (CO 2 ) fluxes at the earth’s surface are imperative for comprehending the carbon cycle mechanisms and providing reliable global warming predictions. Furthermore, they can also provide valuable science-based information that will be helpful in reducing human-induced CO 2 emissions. Inverse analysis is a prominent method of quantitatively estimating spatiotemporal variations in CO 2 fluxes; however, it involves a certain level of uncertainty and requires technical refinement, specifically to improve the horizontal resolution so that local fluxes can be compared with other estimates made at the regional or national level. In this study, a novel set of inversion schemes was incorporated into a state-of-the-art inverse analysis system named NISMON-CO 2 . The introduced schemes include a grid conversion, observational weighting, and anisotropic prior error covariance, the details of which are described. Moreover, pseudo-observation experiments were performed to examine the effect of the new schemes and to assess the reliability of NISMON-CO 2 for long-term analysis with practical inhomogeneous observations. The experiment results evidently demonstrate the advantages of the grid conversion scheme for high-resolution flux estimates (1° × 1°), with notable improvements being achieved through the observational weighting and anisotropic prior error covariance. Furthermore, the estimated seasonal and interannual variations in regional CO 2 fluxes were confirmed to be reliable, although some potential bias in terms of global land–ocean partitioning was observed. Thus, these results are useful for interpreting the flux variations that result from real-observation inverse analysis by NISMON-CO 2 ver. 2021.1.
Water, energy, and food are all essential components of human societies. Collectively, their respective resource systems are interconnected in what is called the “nexus”. There is growing consensus that a holistic understanding of the interdependencies and trade-offs between these sectors and other related systems is critical to solving many of the global challenges they present. While nexus research has grown exponentially since 2011, there is no unified, overarching approach, and the implementation of concepts remains hampered by the lack of clear case studies. Here, we present the results of a collaborative thought exercise involving 75 scientists and summarize them into 10 key recommendations covering: the most critical nexus issues of today, emerging themes, and where future efforts should be directed. We conclude that a nexus community of practice to promote open communication among researchers, to maintain and share standardized datasets, and to develop applied case studies will facilitate transparent comparisons of models and encourage the adoption of nexus approaches in practice.
Global warming mitigation requires worldwide action in a wide range of fields, including waste treatment and management. In Japan, demands to transform waste into energy as a greenhouse gas emissions reduction strategy are increasing. The use of steam generated from waste treatment plants as a source of energy in industries is a promising energy recovery method. In recent years, the feasibility and economic potential of conversion of waste into energy have been evaluated; however, economic efficiency is not always achieved. Therefore, it is necessary to classify steam supply targets based on profitability. Herein, we selected appropriate industries from different types and scales of industries for steam supply based on analyses carried out in Aichi Prefecture. Therefore, industries were classified based on their production shipment value. We also calculated the maximum profit potential from steam supply from waste treatment plants and the steam demand potential of each mesh. We applied data envelopment analysis (DEA) to evaluate energy efficiency and regression analysis to evaluate the potential effects on growth. The appropriate industry was estimated through decision tree analysis based on DEA scores for the mixed industries cluster. We extracted four appropriate industries: pulp, textiles, ceramics, and steel. For each industry, we calculated the number of firms required in the mesh for economic benefit. We also selected industries that could be used to explore the potential of adopting the developed methodology for other regions and industries and for identification of waste treatment plants that could participate in steam supply.
Estimating abundance or biomass using eDNA metabarcoding is a powerful emerging tool that may provide an alternative to conventional laborious methods for biological monitoring. However, inferring aquatic macroorganism abundance or biomass using eDNA concentrations remains challenging, especially in lotic environments, because of several potential confounding factors. In this study, we tested whether quantitative eDNA metabarcoding that uses internal standard DNA can be used to estimate the abundance of four fish species. We collected eDNA samples and concurrently estimated fish densities using the conventional removal method in small tributaries in four seasons during a year. The effects of potential confounding factors, including the body mass of the individuals, water temperature, and discharge volume, were assessed using an allometric scaling model. We found an increasing trend of eDNA concentration against the increase in abundance across all species. In the most abundant species, a significant increase in the precision of predicted abundance was achieved by considering confounding factors, such as season and discharge. Although this study successfully determined the relationships between eDNA concentration and fish abundance under lotic field conditions, it also identified several limitations of quantitative eDNA metabarcoding. The relationship between eDNA concentration and fish abundance in rare species showed significant variances in the regression. More sequencing depth may be necessary to detect rare species sufficiently. The eDNA concentration estimation error effect was significant, particularly among the samples that showed the same abundance figures by direct capture estimation. The utilization of quantitative eDNA metabarcoding may be suitable for organisms that are expected to have a substantial variation in their population density. More comparative studies with various conventional methods would be informative, especially in lotic field environments, to overcome these limitations and achieve wider applications of eDNA metabarcoding in future research and monitoring. Relationship between eDNA concentration obtained from the metabarcoding method and the abundance obtained from the removal method. Lines and shaded areas represent the median and 95% confidence interval of predicted values, respectively, obtained from the allometric scaling model of abundance on eDNA concentration in different mean body mass (g) conditions.