Fugacity model incorporating computational fluid dynamics for analyzing the behavior of an insecticide sprayed indoors.

Fugacity models are used widely to predict the time-dependent behaviors of chemicals in environments containing several media (e.g., air, sediment, soil, and water). However, these fugacity models work on the assumption that the concentration of a chemical in each medium is uniform, so they cannot describe the spatial distribution of the chemical. We developed a new fugacity model, termed InPestCFD, incorporating computational fluid dynamics to describe both the time-dependent distribution and the spatial distribution of a chemical in a medium. InPestCFD was used to calculate the behavior of an insecticide released from an aerosol canister in a room. Indoor airflow and aerosol particle behavior were calculated via computational fluid dynamics and using a Lagrangian dispersion model. Transport of the insecticide among media (aerosol particles, air, ceiling, floor, and walls) was calculated using the fugacity model. The time-dependent distributions and spatial distributions of the insecticide in the media agreed well with real measurements.

Machine learning analysis and risk prediction of weather-sensitive mortality related to cardiovascular disease during summer in Tokyo, Japan.

Climate-sensitive diseases developing from heat or cold stress threaten human health. Therefore, the future health risk induced by climate change and the aging of society need to be assessed. We developed a prediction model for mortality due to cardiovascular diseases such as myocardial infarction and cerebral infarction, which are weather or climate sensitive, using machine learning (ML) techniques. We evaluated the daily mortality of ischaemic heart disease (IHD) and cerebrovascular disease (CEV) in Tokyo and Osaka City, Japan, during summer. The significance of delayed effects of daily maximum temperature and other weather elements on mortality was previously demonstrated using a distributed lag nonlinear model. We conducted ML by a LightGBM algorithm that included specified lag days, with several temperature- and air pressure-related elements, to assess the respective mortality risks for IHD and CEV, based on training and test data for summer 2010-2019. These models were used to evaluate the effect of climate change on the risk for IHD mortality in Tokyo by applying transfer learning (TL). ML with TL predicted that the daily IHD mortality risk in Tokyo would averagely increase by 29% and 35% at the 95th and 99th percentiles, respectively, using a high-level warming-climate scenario in 2045-2055, compared to the risk simulated using ML in 2009-2019.

Estimating the carbon footprint of household activities in Japan from the time-use perspective.

The household sector is a major driver of energy consumption and greenhouse gas (GHG) emissions. However, most existing studies have only estimated households' carbon footprint from their expenditures. Households' daily activity time, a scarce resource that limits and determines their consumption behavior, has rarely been integrated into the estimation. Incorporating the daily time-use patterns should thus provide a more practical perspective for mitigation policies aiming at promoting sustainable household lifestyles. In this study, by linking household time-use data and expenditure data of Japan, the carbon footprint and the GHG intensity of time of 85 daily household activities constituting the 24 hours in a day are estimated. Compared to the maximal 20-activity disaggregation in existing studies, our detailed 85-category disaggregation of daily time enables unprecedented details on the discrepancies between the carbon footprint from daily activities, many of which have previous been treated as one activity. Results indicate significant carbon mitigation potential in activities with a high GHG intensity of time, such as cooking, bathing, and mobility-related and activities. Average daily GHG emissions were also found to be higher on weekends as time-use patterns shift from paid work to free-time activities, highlighting the need for mitigation strategies on a weekly scale.

Loss of disability-adjusted life years due to heat-related sleep disturbance in the Japanese.

The purpose of this study was to quantify the sleep disturbances caused by climate change using disability-adjusted life years (DALY). The revised sleep quality index for daily sleep (SQIDS2), a self-administered questionnaire for daily sleep quality, was developed to assess daily sleep disturbances. This questionnaire referenced and simplified the Pittsburgh Sleep Quality Index (PSQI). This study was conducted in Nagoya City in August 2011 and 2012. Sleep quality was measured using SQIDS2 and PSQI. A total of 574 participants in 2011 and 710 in 2012 responded to the survey. The sleep disturbance prevalence calculated from the SQIDS2 score was correlated with the daily minimum temperature (p = 0.0067). This score increased when the daily minimum temperature was above 24.8 °C. When correcting for the PSQI score, DALY loss due to heat-related sleep disturbances in Nagoya City (population: 2,266,851) was estimated to be 81.8 years in 2012. This value was comparable to the DALY loss due to heatstroke. Sleep disturbance due to climate change was quantified using the DALY based on the PSQI. Legislators must recognize the critical impact of the damage caused by sleep disturbances due to high temperatures at night. Additionally, a daily minimum temperature of 25 °C should be the starting point when establishing a goal or guideline for nighttime temperature.

Future increase in elderly heat-related mortality of a rapidly growing Asian megacity.

Urban dwellers are at risk of heat-related mortality in the onset of climate change. In this study, future changes in heat-related mortality of elderly citizens were estimated while considering the combined effects of spatially-varying megacity's population growth, urbanization, and climate change. The target area is the Jakarta metropolitan area of Indonesia, a rapidly developing tropical country. 1.2 × 1.2 km2 daily maximum temperatures were acquired from weather model outputs for the August months from 2006 to 2015 (present 2010s) and 2046 to 2055 (future 2050s considering pseudo-global warming of RCP2.6 and RCP8.5). The weather model considers population-induced spatial changes in urban morphology and anthropogenic heating distribution. Present and future heat-related mortality was mapped out based on the simulated daily maximum temperatures. The August total number of heat-related elderly deaths in Jakarta will drastically increase by 12~15 times in the 2050s compared to 2010s because of population aging and rising daytime temperatures under "compact city" and "business-as-usual" scenarios. Meanwhile, mitigating climate change (RCP 2.6) could reduce the August elderly mortality count by up to 17.34%. The downwind areas of the densest city core and the coastal areas of Jakarta should be avoided by elderly citizens during the daytime.

Fatigue and sleep under large summer temperature differences.

BACKGROUND: It has been recognized that an increase in outdoor ambient temperatures has a negative impact on health, particularly fatigue and sleep quality; however, the relationship among fatigue, sleep quality, and air temperature has yet to be sufficiently elucidated. OBJECTIVES: To examine whether fatigue and sleep quality in a healthy Japanese population were affected by rising air temperature at three time points in summer and to investigate the confounding factors for fatigue. METHODS: A total of 602 healthy volunteers in Osaka, Japan, participated in a survey that was conducted at the end of July, August, and September in 2010. The questionnaire consisted of four sections; demographic variables, accommodation status, fatigue, and sleep quality. We used the Chalder fatigue scale for assessment of fatigue, and the Japanese version of the Pittsburgh Sleep Quality Index (PSQI) for assessment of sleep quality. RESULTS: The fatigue score was positively correlated with the sleep quality score in the total cohort. All the questionnaires at the three time points were completed by 162 participants. There were significant differences in fatigue scores among the surveys. We stratified the subjects into two groups of good and poor sleepers using a cutoff value of the PSQI. The good sleepers did not show differences in fatigue score regardless of the change in air temperature. However, the fatigue score of poor sleepers was greater at higher air temperatures. The use of air conditioners, accommodation type, and subject's age were confounding factors for fatigue. CONCLUSIONS: High air temperatures in summer increased fatigue in healthy volunteers, especially those with poor sleep patterns, depending on the use of air conditioners, accommodation status, and subject's age.

Association between sleep and residential environments in the summertime in Japan.

OBJECTIVES: We aimed to identify the effect of environmental factors on sleep in the summertime in Japan. METHODS: A self-reported questionnaire survey was conducted in Japan. Age of participants ranged from 20 to 70 years. RESULTS: The mean Pittsburgh Sleep Quality Index (PSQI) score was 4.9 (±2.7), and 123 (35.0%) participants had scores of >5. According to the results of multivariate logistic regression analysis, the adjusted odds ratio (aOR) for PSQI scores of >5 without installation of air conditioner was 1.8 (95% confidence interval [CI], 1.0-3.3; P<.05), use of a light bulb was 3.7 (95% CI, 1.1-12.6; P<.05), and noise was 2.1 (95% CI, 1.1-4.1; P<.05) after controlling for several confounding variables. Difficulty initiating sleep (DIS) was associated with installation of an air conditioner (1 [reference] to 3 [aOR, 2.5 {95% CI, 1.2-5.1}] and 4 [aOR, 2.8 {95% CI, 1.1-7.1}]) and noise (1 [reference] to 3 [aOR, 2.4 {95% CI, 1.0-5.9}] and 4 [aOR, 8.8 {95% CI, 3.1-25.0}]). Difficulty maintaining sleep (DMS) was associated with installation of a fan (1 [reference] to 2 [aOR, 0.4 {95% CI, 0.2-0.8}] and noise (1 [reference] to 3 [aOR, 2.3 {95% CI, 1.0-5.3}]) after controlling for several confounding variables. CONCLUSIONS: Our finding using analysis of the association between residential environments and subjective sleep statuses, which determined that the installation of an air conditioner and lighting equipment might affect sleep, may be useful to discuss sleep environments and improve sleep quality.

Life cycle assessment of integrated municipal solid waste management systems, taking account of climate change and landfill shortage trade-off problems.

Steps taken to counter the climate change problem have a significant impact on the municipal solid waste management (MSW) sector, which must tackle regional environmental problems such as the shortage of sanitary landfills, especially in Japan. Moreover, greenhouse gas emissions and final disposal have a trade-off relationship. Therefore, alleviation of both these environmental problems is difficult, and Japanese local municipalities are anxious for action to solve these problems and reduce treatment costs. Although ambitious waste management measures have been enacted in many countries, they appear to lack a holistic view and do not adopt a life cycle approach. Therefore, it is important to reconstruct the MSW management system, taking into account environmental and economic aspects. In the present study, life cycle assessment and mathematical modelling were used to seek ways of redesigning the MSW management system in order to minimize environmental impacts and/or reduce treatment costs. One economic block was selected as the study area (Iwate Prefecture in Japan). The life cycle inventory and costs data for every MSW transportation and treatment process in this region were collected and processed. Then, taking account of geographic information, an optimal solution for the minimization of environmental impact or treatment costs was derived. To solve the trade-off problem, a sensitivity analysis was conducted to find optimal reduction targets for climate change and final disposal.