Objective To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases,and to develop deep learning-based models for daily hospital admission pre...Objective To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases,and to develop deep learning-based models for daily hospital admission prediction.Methods A multi-city study was conducted in Tokyo’s 23 wards,Osaka City,and Nagoya City.Random forest models were employed to assess the synergistic short-term lag effects(lag0,lag3,and lag7)of climate and air pollutants on hospitalization for five cardiovascular diseases(CVDs)and two respiratory diseases(RDs).Furthermore,we developed hybrid deep learning models that integrated an autoencoder(AE)with a Long Short-Term Memory network(AE+LSTM)to predict daily hospital admissions.Results On the day of exposure(lag0),air pollutants,particularly nitrogen oxides(NOx),exhibited the strongest influence on hospital admissions for CVD and RD,with pronounced effects observed for hypertension(I10–I15),ischemic heart disease(I20),arterial and capillary diseases(I70–I79),and lower respiratory infections(J20–J22 and J40–J47).At longer lags(lag3 and lag7),temperature and precipitation were more influential predictors.The AE+LSTM model outperformed the standard LSTM,improving the prediction accuracy by 32.4%for RD in Osaka and 20.94%for CVD in Nagoya.Conclusion Our findings reveal the dynamic,time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions.This framework can inform early warning systems,enhance healthcare resource allocation,and support climate-adaptive public health strategies.展开更多
This study investigated the effects of temperature,as well as extreme temperature events and air pollution on cardiovascular and respiratory morbidity and mortality in Tokyo's 23 wards,Osaka city,and Nagoya city f...This study investigated the effects of temperature,as well as extreme temperature events and air pollution on cardiovascular and respiratory morbidity and mortality in Tokyo's 23 wards,Osaka city,and Nagoya city from 2017 to 2019.We utilized a two-stage time-series analysis to explore daily average temperature,extreme temperature events with different percentile and air pollutant concentrations(NOx,CO,SO2,PM2.5,suspended particulate matter[SPM]),and health outcomes.Results showed that low temperatures significantly increased cardiovascular and respiratory disease risks,with effects more pronounced than those of high temperatures.The minimum mortality temperature was approximately 12-15℃for mortality of respiratory and cardiovascular disease.Extreme cold event(at 2.5th and fifth percentiles)consistently increased morbidity and mortality risks of respiratory disease and mortality of cardiovascular disease,while Extreme heat event effects were less pronounced and occasionally increased the risk of mortality from cardiovascular and respiratory diseases(at the 95th and 97th percentiles).All air pollutants demonstrated immediate effects(lag0-1 days)on cardiovascular and respiratory disease morbidity.PM2.5 and SPM exhibited more prolonged impacts on cardiovascular morbidity.This study provides insights into the distinct health impacts of temperature,extreme temperature events,and air pollution in Japan's urban areas,highlighting the need for targeted public health interventions considering both environmental stressors.展开更多
The Great East Japan Earthquake in March 2011 devastated the eastern region of Japan.Due to the resulting nuclear accident,Japanese Cabinet decided to revise its energy policies.The Energy and Environment Council in N...The Great East Japan Earthquake in March 2011 devastated the eastern region of Japan.Due to the resulting nuclear accident,Japanese Cabinet decided to revise its energy policies.The Energy and Environment Council in National Policy Unit published options on the nation's scenarios for energy and economy in 2030.We estimated the economic impacts of the options to national economy and households in 2030.Finally,we clarified significant factors to establish a secure,affluent and low-carbon society based on the energy scenarios.展开更多
Waste management is becoming a crucial issue in modem society owing to rapid urbanization and the increasing generation of municipal solid waste （MSW）. This paper evaluates the carbon footprint of the waste manageme...Waste management is becoming a crucial issue in modem society owing to rapid urbanization and the increasing generation of municipal solid waste （MSW）. This paper evaluates the carbon footprint of the waste management sector to identify direct and indirect carbon emissions, waste recycling carbon emission using a hybrid life cycle assessment and input-output analysis. China and Japan was selected as case study areas to highlight the effects of different industries on waste management. The results show that the life cycle carbon footprints for waste treatment are 59.01 million tons in China and 7.01 million tons in Japan. The gap between these footprints is caused by the different waste management systems and treatment processes used in the two countries. For indirect carbon footprints, China＇s material carbon footprint and deprecia- tion carbon footprint are much higher than those of Japan, whereas the purchased electricity and heat carbon footprint in China is half that of Japan. China and Japan have similar direct energy consumption carbon footprints. However, CO2 emissions from MSW treatment processes in China （46.46 million tons） is significantly higher than that in Japan （2.72 million tons）. The corresponding effects of waste recycling on CO2 emission reductions are consider- able, up to 181.37 million tons for China and 96.76 million tons for Japan. Besides, measures were further proposed for optimizing waste management systems in the two countries. In addition, it is argued that the advanced experience that developed countries have in waste management issues can provide scientific support for waste treatment in developing countries such as China.展开更多
A review of our recent work on ultrahigh resolution optical fiber sensors in the quasi-static region is presented, and their applications in crustal deformation measurement are introduced. Geophysical research such as...A review of our recent work on ultrahigh resolution optical fiber sensors in the quasi-static region is presented, and their applications in crustal deformation measurement are introduced. Geophysical research such as studies on earthquake and volcano requires monitoring the earth＇s crustal deformation continuously with a strain resolution on the order of nano-strains （ne） in static to low frequency region. Optical fiber sensors are very attractive due to their unique advantages such as low cost, small size, and easy deployment. However, the resolution of conventional optical fiber strain sensors is far from satisfactory in the quasi-static domain. In this paper, several types of recently developed fiber-optic sensors with ultrahigh resolution in the quasi-static domain are introduced, including a fiber Bragg grating （FBG） sensor interrogated with a narrow linewidth tunable laser, an FBG based fiber Fabry-Perot interferometer （FFPI） sensor by using a phase modulation technique, and an FFPI sensor with a sideband interrogation technique. Quantificational analyses and field experimental results demonstrated that the FBG sensor can provide nano-order strain resolution. The sub-nano strain resolution was also achieved by the FFPI sensors in laboratory. Above achievements provide the basis to develop powerful fiber-optic tools for geophysical research on crustal deformation monitoring.展开更多
基金supported by the Japan Science and Technology Agency SPRING Program(JST SPRING),Grant Number JPMJSP2108,which was partially funded by the Japan Society for the Promotion of Science(JSPS)Grant Numbers 20H03949,23K22919,23K28289the Environmental Restoration and Conservation Agency of Japan,and the Environment Research and Technology Development Fund(S-24).
文摘Objective To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases,and to develop deep learning-based models for daily hospital admission prediction.Methods A multi-city study was conducted in Tokyo’s 23 wards,Osaka City,and Nagoya City.Random forest models were employed to assess the synergistic short-term lag effects(lag0,lag3,and lag7)of climate and air pollutants on hospitalization for five cardiovascular diseases(CVDs)and two respiratory diseases(RDs).Furthermore,we developed hybrid deep learning models that integrated an autoencoder(AE)with a Long Short-Term Memory network(AE+LSTM)to predict daily hospital admissions.Results On the day of exposure(lag0),air pollutants,particularly nitrogen oxides(NOx),exhibited the strongest influence on hospital admissions for CVD and RD,with pronounced effects observed for hypertension(I10–I15),ischemic heart disease(I20),arterial and capillary diseases(I70–I79),and lower respiratory infections(J20–J22 and J40–J47).At longer lags(lag3 and lag7),temperature and precipitation were more influential predictors.The AE+LSTM model outperformed the standard LSTM,improving the prediction accuracy by 32.4%for RD in Osaka and 20.94%for CVD in Nagoya.Conclusion Our findings reveal the dynamic,time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions.This framework can inform early warning systems,enhance healthcare resource allocation,and support climate-adaptive public health strategies.
基金supported by the Japan Science and Technology Agency SPRING Program(JST SPRING),Grant Number JPMJSP2108this work was partially funded by Japan Society for the Promotion of Science(JSPS),Grant Number:20H03949,23K22919,and 23K28289 and the Environmental Restoration and Conservation Agency of Japan,the Environment Research and Technology Development Fund(JPMEERF25S12433).
文摘This study investigated the effects of temperature,as well as extreme temperature events and air pollution on cardiovascular and respiratory morbidity and mortality in Tokyo's 23 wards,Osaka city,and Nagoya city from 2017 to 2019.We utilized a two-stage time-series analysis to explore daily average temperature,extreme temperature events with different percentile and air pollutant concentrations(NOx,CO,SO2,PM2.5,suspended particulate matter[SPM]),and health outcomes.Results showed that low temperatures significantly increased cardiovascular and respiratory disease risks,with effects more pronounced than those of high temperatures.The minimum mortality temperature was approximately 12-15℃for mortality of respiratory and cardiovascular disease.Extreme cold event(at 2.5th and fifth percentiles)consistently increased morbidity and mortality risks of respiratory disease and mortality of cardiovascular disease,while Extreme heat event effects were less pronounced and occasionally increased the risk of mortality from cardiovascular and respiratory diseases(at the 95th and 97th percentiles).All air pollutants demonstrated immediate effects(lag0-1 days)on cardiovascular and respiratory disease morbidity.PM2.5 and SPM exhibited more prolonged impacts on cardiovascular morbidity.This study provides insights into the distinct health impacts of temperature,extreme temperature events,and air pollution in Japan's urban areas,highlighting the need for targeted public health interventions considering both environmental stressors.
文摘The Great East Japan Earthquake in March 2011 devastated the eastern region of Japan.Due to the resulting nuclear accident,Japanese Cabinet decided to revise its energy policies.The Energy and Environment Council in National Policy Unit published options on the nation's scenarios for energy and economy in 2030.We estimated the economic impacts of the options to national economy and households in 2030.Finally,we clarified significant factors to establish a secure,affluent and low-carbon society based on the energy scenarios.
文摘Waste management is becoming a crucial issue in modem society owing to rapid urbanization and the increasing generation of municipal solid waste （MSW）. This paper evaluates the carbon footprint of the waste management sector to identify direct and indirect carbon emissions, waste recycling carbon emission using a hybrid life cycle assessment and input-output analysis. China and Japan was selected as case study areas to highlight the effects of different industries on waste management. The results show that the life cycle carbon footprints for waste treatment are 59.01 million tons in China and 7.01 million tons in Japan. The gap between these footprints is caused by the different waste management systems and treatment processes used in the two countries. For indirect carbon footprints, China＇s material carbon footprint and deprecia- tion carbon footprint are much higher than those of Japan, whereas the purchased electricity and heat carbon footprint in China is half that of Japan. China and Japan have similar direct energy consumption carbon footprints. However, CO2 emissions from MSW treatment processes in China （46.46 million tons） is significantly higher than that in Japan （2.72 million tons）. The corresponding effects of waste recycling on CO2 emission reductions are consider- able, up to 181.37 million tons for China and 96.76 million tons for Japan. Besides, measures were further proposed for optimizing waste management systems in the two countries. In addition, it is argued that the advanced experience that developed countries have in waste management issues can provide scientific support for waste treatment in developing countries such as China.
文摘A review of our recent work on ultrahigh resolution optical fiber sensors in the quasi-static region is presented, and their applications in crustal deformation measurement are introduced. Geophysical research such as studies on earthquake and volcano requires monitoring the earth＇s crustal deformation continuously with a strain resolution on the order of nano-strains （ne） in static to low frequency region. Optical fiber sensors are very attractive due to their unique advantages such as low cost, small size, and easy deployment. However, the resolution of conventional optical fiber strain sensors is far from satisfactory in the quasi-static domain. In this paper, several types of recently developed fiber-optic sensors with ultrahigh resolution in the quasi-static domain are introduced, including a fiber Bragg grating （FBG） sensor interrogated with a narrow linewidth tunable laser, an FBG based fiber Fabry-Perot interferometer （FFPI） sensor by using a phase modulation technique, and an FFPI sensor with a sideband interrogation technique. Quantificational analyses and field experimental results demonstrated that the FBG sensor can provide nano-order strain resolution. The sub-nano strain resolution was also achieved by the FFPI sensors in laboratory. Above achievements provide the basis to develop powerful fiber-optic tools for geophysical research on crustal deformation monitoring.
