Average Sunshine Duration Research Articles

Influence of climate and landscape structure on soil erosion in China's Loess Plateau: Key factor identification and spatiotemporal variability.

Climate and landscape structure are widely recognized as the primary drivers of soil erosion; however, the spatiotemporal variability of their effects remains insufficiently understood, limiting our comprehension of the dynamic processes of soil erosion. To address this gap, this study analyzed soil erosion trends on the Loess Plateau from 2000 to 2018. extreme Gradient Boosting was used to identify key climatic and landscape structural factors, while a geographically and temporally weighted regression model was applied to assess the spatiotemporal variability of these influences. The results indicate a decreasing trend in soil erosion from 2000 to 2008, followed by a sharp increase from 2008 to 2018. Grassland edge density emerged as the most important factor, followed closely by grassland percentage and annual precipitation. Temporally, the positive effect of annual precipitation has been intensifying since 2010, contributing to increased erosion, while landscape structural factors progressively enhanced their hydrological regulatory roles, reflecting dynamic interactions with climate. Spatially, the direction of climatic influences remained generally stable, consistently promoting erosion, although by 2018, the effects of average annual temperature and annual sunshine duration reversed to suppress erosion in specific areas. In contrast, landscape structural influences exhibited greater spatial variability, often fluctuating or reversing depending on topography, human activity, and land use. This variability applied specifically and differentially to each metric of fragmentation and diversity, highlighting the critical importance of trade-offs in landscape management. The findings emphasize the complexity and dynamics of soil erosion in response to climate and landscape structure, suggesting implications for the development of spatially targeted soil erosion control strategies that accommodate the phases of temporal variation.

Spatiotemporal Distribution of Human Rabies and Identification of Predominant Risk Factors in China from 2004 to 2020.

Human rabies is a prevalent issue in China, posing a significant public health concern in the country. This study fitted the Bayesian model of separable in spatial and temporal variation and inseparable spatiotemporal variation in disease risk respectively based on Integrated Nested Laplace Approximation (INLA) to investigate the spatiotemporal characteristics of human rabies across 31 provinces in China from 2004 to 2020. It also investigated the influence of natural and socio-environmental factors on the incidence of the disease. Within the study period, a total of 26,807 cases of human rabies were reported, with the highest risk of incidence occurring in 2007, followed by a steady annual decline to the lowest risk in 2020. Guangxi Province exhibited the highest risk, while Jilin Province had the lowest, with the southern, central, and eastern regions reporting higher risks than the northern and western areas. By 2020, most provinces such as Guangxi and Guizhou had significantly reduced their relative risk (RR) of human rabies from historical highs. However, some provinces like Hunan, Henan, and Jiangsu experienced an increase in RR compared to previous years. As the annual average temperature increases, the risk of human rabies incidence in China correspondingly rises. Conversely, with increases in the annual average daily sunshine duration, per capita disposable income of urban residents, and local government healthcare expenditures, the risk of human rabies incidence declines. We conclude that the risk of human rabies in China initially increased and then decreased annually from 2004 to 2020. Future efforts should continuously increase financial investments in rabies prevention and control, focusing particularly on Hunan, Henan, Jiangsu, and provinces characterized by higher temperatures, shorter sunshine durations, and lower economic levels.

Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014–2021

BackgroundTuberculosis (TB) remains a pressing public health issue, posing a significant threat to individuals' well-being and lives. This study delves into the TB incidence in Chinese mainland during 2014–2021, aiming to gain deeper insights into their epidemiological characteristics and explore macro-level factors to enhance control and prevention.MethodsTB incidence data in Chinese mainland from 2014 to 2021 were sourced from the National Notifiable Disease Reporting System (NNDRS). A two-stage distributed lag nonlinear model (DLNM) was constructed to evaluate the lag and non-linearity of daily average temperature (℃, Atemp), average relative humidity (%, ARH), average wind speed (m/s, AWS), sunshine duration (h, SD) and precipitation (mm, PRE) on the TB incidence. A spatial panel data model was used to assess the impact of demographic, medical and health resource, and economic factors on TB incidence.ResultsA total of 6,587,439 TB cases were reported in Chinese mainland during 2014–2021, with an average annual incidence rate of 59.17/100,000. The TB incidence decreased from 67.05/100,000 in 2014 to 46.40/100,000 in 2021, notably declining from 2018 to 2021 (APC = -8.87%, 95% CI: -11.97, -6.85%). TB incidence rates were higher among males, farmers, and individuals aged 65 years and older. Spatiotemporal analysis revealed a significant cluster in Xinjiang, Qinghai, and Xizang from March 2017 to June 2019 (RR = 3.94, P < 0.001). From 2014 to 2021, the proportion of etiologically confirmed cases increased from 31.31% to 56.98%, and the time interval from TB onset to diagnosis shortened from 26 days (IQR: 10–56 days) to 19 days (IQR: 7–44 days). Specific meteorological conditions, including low temperature (< 16.69℃), high relative humidity (> 71.73%), low sunshine duration (< 6.18 h) increased the risk of TB incidence, while extreme low wind speed (< 2.79 m/s) decreased the risk. The spatial Durbin model showed positive associations between TB incidence rates and sex ratio (β = 1.98), number of beds in medical and health institutions per 10,000 population (β = 0.90), and total health expenses (β = 0.55). There were negative associations between TB incidence rates and population (β = -1.14), population density (β = -0.19), urbanization rate (β = -0.62), number of medical and health institutions (β = -0.23), and number of health technicians per 10,000 population (β = -0.70).ConclusionsSignificant progress has been made in TB control and prevention in China, but challenges persist among some populations and areas. Varied relationships were observed between TB incidence and factors from meteorological, demographic, medical and health resource, and economic aspects. These findings underscore the importance of ongoing efforts to strengthen TB control and implement digital/intelligent surveillance for early risk detection and comprehensive interventions.Graphical

Plant diversity in the understory of Eucalyptus plantations on Hainan Island and its response to environmental factors

Research on understory plant diversity and its response to environmental factors helps in the sustainable development of plantation forests. We investigated the characteristics of understory plant diversity in Eucalyptus plantation forests located in Dongfang, Ding'an, Tunchang, and Lingao on Hainan Island by leveraging the plot survey method, and analyzing how the understory plant diversity in these Eucalyptus plantation forests responds to environmental factors. The results showed that a total of 124 plant species belonging to 62 families and 112 genera were recorded in the sampled plots of the Dongfang, Ding’an, Tunchang, and Lingao regional sites on Hainan Island, among which species of Fabaceae and Poaceae comprised the largest number of plants. The number of species and plant diversity indices of the shrub layer and herb layer in Eucalyptus plantation forests varied at different sites, The richest understory vegetation in Tunchang, located in the center of Hainan Island, and the highest α-diversity whether gauged by species or phylogenetically. The similarity of the understory plant community species was greatest between Ding’an and Tunchang, whereas the difference in composition was largest between Dongfang and the other three sites. Phylogenetically, the understory plant community at Ding’an had the most distant affinities among species, whereas that at Tunchang had the closest affinities among species. The results of the Mantel test and redundancy analysis revealed differing correlations between plant diversity in the shrub layer versus herb layer and various environmental factors. In particular, elevation and annual average temperature are the two main factors influencing plant diversity in the shrub layer, and soil available nitrogen and annual average sunshine duration are the two main factors influencing plant diversity in the herb layer. Variance decomposition showed that the combined effect of soil, climate, and topography factors is the main driver shaping plant diversity in the shrub layer of the understory in Eucalyptus plantation forests, while the combined effect of climate and soil factors is the main one determining plant diversity in their herb layer.

Dynamics of Puccinia striiformis f. sp. tritici Urediniospores and Its Relationship with Meteorological Factors in Mianyang, China.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the main diseases of wheat worldwide. Mianyang of Sichuan province in Southwest China is one of main regions for winter Pst inoculum production and spring epidemic and provides urediniospores for infecting wheat in the surrounding regions. Understanding the urediniospore dynamics is important to predict and manage stripe rust. In this study, spore trapping coupled with a TaqMan real-time quantitative PCR method was used to monitor airborne Pst urediniospores from December 2019 to December 2022 in Mianyang. Weather conditions (temperature, relative humidity, daily sunshine duration, and precipitation) were collected for the same period. These data were used to study the relationship of airborne urediniospore density with climatic conditions. The results showed that Pst urediniospores were captured all year round, and the annual peak of urediniospore densities occurred in the period from March to April in which the urediniospores accounted for the largest proportion of the annual total urediniospores. The density of urediniospores in the period of March to April was linearly related to the average sunshine duration of 20 days and average temperature of 15 days prior to the final day of a 7-day trapping period. This relationship needs to be tested in other regions where Pst can sporulate during the winter before it can be integrated with Pst infection conditions to predict rust development.

Exploring the effects and interactions of meteorological factors on the incidence of scrub typhus in Ganzhou City, 2008-2021.

Scrub typhus poses a substantial risk to human life and wellbeing as it is transmitted by vectors. Although the correlation between climate and vector-borne diseases has been investigated, the impact of climate on scrub typhus remains inadequately comprehended. The objective of this study is to investigate the influence of meteorological conditions on the occurrence of scrub typhus in Ganzhou City, Jiangxi Province. METHODS: From January 1, 2008 to December 31, 2021, we gathered weekly records of scrub typhus prevalence alongside meteorological data in Ganzhou city. In order to investigate the correlation between meteorological factors and scrub typhus incidence, we utilized distributional lag nonlinear models and generalized additive models for our analysis. Between 2008 and 2021, a total of 5942 cases of scrub typhus were recorded in Ganzhou City. The number of females affected exceeded that of males, with a male-to-female ratio of 1:1.86. Based on the median values of these meteorological factors, the highest relative risk for scrub typhus occurrence was observed when the weekly average temperature reached 26°C, the weekly average relative humidity was 75%, the weekly average sunshine duration lasted for 2h, and the weekly mean wind speed measured 2m/s. The respective relative risks for these factors were calculated as 3.816 (95% CI: 1.395-10.438), 1.107 (95% CI: 1.008-1.217), 2.063 (95% CI: 1.022-4.165), and 1.284 (95% CI: 1.01-1.632). Interaction analyses showed that the risk of scrub typhus infection in Ganzhou city escalates with higher weekly average temperature and sunshine duration. The findings of our investigation provide evidence of a correlation between environmental factors and the occurrence of scrub typhus. As a suggestion, utilizing environmental factors as early indicators could be recommended for initiating control measures and response strategies.

Temporal Variation of Sunshine Duration and Its Potential Affecting Factors with Emphasis on Saudi Arabia for the Period 1983-2022

The rising trend in fossil fuel prices and the depletion of natural resource reserves in the future force the authority of any country to find a more sustainable option for energy sources, so that future energy demand can be ensured for sustainable development. Assessing the trend and availability of sunshine duration (SD) at a spatiotemporal scale and the effect of different metrological parameters on the SD change is crucial to ensure the efficient utilization of solar energy, support the growth of renewable energy systems, and contribute to a sustainable future. In Saudi Arabia, The average monthly SD is 283 ± 18 hm-1, and there was a rising trend of SD that increased at a rate of 1.48 hy-1 with a 95% confidence level. Most of the regions experienced an annual mean of SD between 3375 and 3754 hy-1, except for the southwest and the middle-eastern part where SD was between 3072 and 3375 hours in a year. The highest mean monthly SD was 318 ± 39 hm-1 during the summer season, but the trend of SD changes over the years was downward ( -0.21 hy-1). The mean monthly SD was lowest (244 ± 38 hm-1) in the winter season, and the changing pattern of SD was on the rise at a rate of 0.26 hy-1 with a 95% confidence level. There was a decline in SD across the country between 1983 and 1998, whereas from 2000 onward the country experienced an upward trend in SD. Relative humidity (R = -0.53, p &lt; 0.01) and cloud cover (R = -0.42, p &lt; 0.05) as potential factors have a strong negative correlation with SD, whereas wind speed (R = 0.06, p &gt; 0.1) and temperature (R = 0.12, p &gt; 0.1) have a positive correlation with SD in the region.

Impact of meteorological factors on the incidence of hand-foot-mouth disease in Yangzhou from 2017 to 2022: a time series study.

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China, and numerous studies have indicated a close association between HFMD incidence and meteorological factors. This study aims to investigate the relationship between meteorological factors and HFMD in Yangzhou City, Jiangsu Province, China. HFMD case reports and meteorological data from Yangzhou City between 2017 and 2022 were extracted from the National Notifiable Infectious Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. A generalized additive model (GAM) was employed to assess the exposure-response relationship between meteorological factors and HFMD. Subsequently, a distributed lag nonlinear model (DLNM) was used to explore the exposure-lag-effect of meteorological factors on HFMD. HFMD in Yangzhou City exhibits obvious seasonality and periodicity. There is an inverted "U" shaped relationship between average temperature and the risk of HFMD, with the maximum lag effect observed at a temperature of 25°C with lag 0 day (RR = 2.07, 95% CI: 1.74-2.47). As the duration of sunshine and relative humidity increase, the risk of HFMD continuously rises, with the maximum lag effect observed at a sunshine duration of 12.4 h with a lag of 14 days (RR = 2.10, 95% CI: 1.17-3.77), and a relative humidity of 28% with a lag of 14 days (RR = 1.21, 95% CI: 1.01-1.64). There is a "U" shaped relationship between average atmospheric pressure and the risk of HFMD, with the maximum effect observed at an atmospheric pressure of 989 hPa with no lag (RR = 1.45, 95% CI: 1.25-1.69). As precipitation increases, the risk of HFMD decreases, with the maximum effect observed at a precipitation of 151 mm with a lag of 14 days (RR = 1.45, 95% CI: 1.19-2.53). Meteorological factors including average temperature, average atmospheric pressure, relative humidity, precipitation, and sunshine duration significantly influenced the risk of HFMD in Yangzhou City. Effective prevention measures for HFMD should be implemented, taking into account the local climate conditions.

Habitat Suitability of Pine Wilt Disease in Northeast China under Climate Change Scenario

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus, is one of the most severe forest diseases worldwide. PWD causes devastating disasters to Chinese pine trees, seriously threatening forestry production and the forest ecological environment, and causes economic losses of over ten billion yuan per year to China. Previous studies have shown that the spread of PWD is closely related to climate factors. Today, PWD is spreading rapidly owing to abnormal climate changes. In order to provide a reference for controlling the spread of PWD in China, in this study, we accurately assessed the risk of the continued spread of PWD in Northeast China; a correlative species distribution model (MaxEnt) (RM = 1, AUC = 0.9904) was used to evaluate China’s climate suitability for PWD. The effects of climate factors on the spread of PWD in Northeast China were studied using Liaoning Province as an example by analyzing the relationship between the changes in average precipitation, average temperature, average relative humidity, average vapor pressure deficit, average wind speed, average sunshine duration and the area of the PWD epidemic over the past five years. These results suggest that with the change in climate, the areas suitable for PWD have expanded, and certain previously unsuitable areas for its distribution have become suitable. Temperature and precipitation were found to play key roles in the occurrence and damage of PWD, and hot and arid conditions favored the spread of PWD. It is recommended that for areas within the suitable range of PWD but not yet epidemic areas, quarantine should be strengthened to prevent the further spread of PWD. In addition, special attention should be paid to epidemic areas with high temperatures and arid while the monitoring of PWD should be strengthened to achieve the early detection and timely treatment of infected epidemic trees. Our results indicate that PWD undoubtedly poses a major threat to Northeast Chinese pine species if climate change proceeds as projected. In the future, more attention should be paid to monitoring the northward spread of PWD, and further studies should consider meteorological data forecasts, which could facilitate timely control measures.

Impact of Climate on the Carbon Sink Capacity of Ecological Spaces: A Case Study from the Beijing–Tianjin–Hebei Urban Agglomeration

Climate plays a significant role in shaping ecosystem-level carbon sinks. Research on the mechanisms of climate impacts on carbon sinks can contribute to the achievement of carbon neutrality. Investigating the mechanisms by which climate impact on carbon sinks in ecological spaces in the Beijing–Tianjin–Hebei region, one of the most important urban clusters in China, is of great significance. This study employed spatial autocorrelation and econometric models to explore how various climatic factors impact net primary productivity (which is used to represent carbon sink capacity) on a spatial scale. We found an increasing trend in NPP across the Beijing–Tianjin–Hebei urban agglomeration from 2000 to 2020, with marked spatial clustering. Climatic factors exhibited the best fit with the spatial Durbin model, except for average annual precipitation. The remaining factors had significant effects on NPP, showing spatial spillover effects. Results also showed that the average annual temperature, evaporation, and relative humidity had positive impacts on NPP at a local scale but adverse effects at a regional scale. Average annual sunshine duration and the ground temperature had negative effects on NPP locally but promoted effects regionally. Furthermore, the average annual wind speed negatively impacted both local- and regional-scale NPP. This research provides insights into how climate affects carbon sinks on a small spatial scale, offering important references for making policy decisions and improving the accuracy of carbon cycling simulations.

Environmental factors differentially affect epistaxis among preschool and school-aged children.

Environmental factors are closely associated with pediatric epistaxis. Whether this association differs according to age has not been previously reported. Therefore, we tried to evaluate the differences in associations between environmental factors and epistaxis in children of different ages. A total of 20,234 patients with epistaxis who visited the hospital between January 1, 2002, and December 31, 2015, were enrolled in this study. The patients were divided into two groups according to their ages: preschool-aged (<6 years) and school-aged children (6-18 years). Daily, monthly, and yearly data on environmental factors were collected. We performed a stepwise logistic regression to identify the potential environmental risk factors for epistaxis in each age group. The mean number of epistaxis cases per month in both groups was highest in September. The cases were lowest in February in preschool-aged children and in November in school-aged children. Temperature, humidity, maximum wind speed, and sunshine duration were associated with epistaxis in preschool-aged children. Average wind speed, particulate matter (>10 μm diameter), temperature, humidity, sunshine duration, and sulfur dioxide concentration were associated with epistaxis in school-aged children. This study indicates that the differences in environmental risk factors for epistaxis are associated with the patient's age.

Quantifying the effects of urban development intensity on the surface urban heat island across building climate zones

Urban heat island (UHI) has gradually been a critical issue in the context of global environmental change and regional sustainability. The urban development intensity (UDI) increases with rapid urbanization and exacerbates the UHI problem, but the effects and contributions of UDI on UHI remain unclear. Based on Landsat 8 satellite images, this study quantified the effects of UDI on surface UHI intensity (SUHII) in 20 important cities across 5 building climate zones of China by using regression analysis, correlation analysis and boosted regression tree (BRT), and analyzed their potential influence mechanisms. Results indicated that there was apparent spatial heterogeneity of SUHII in different building climate zones (ranging from 3.26 °C to 4.43 °C) and cities (ranging from 1.44 °C to 6.61 °C). The effect of UDI on SHUII in cities of north was stronger than that in south, the average R2 values of the UDI-SUHII relationship in severe cold zone and cold zone were higher than the other climate zones. Building density, as the most critical predictor of SUHII among UDI metrics in all cities, was significantly positively correlated with SUHII. The R2 values showed significant positive correlation with annual average sunshine duration and aridity, and significant negative correlation with annual average precipitation, humidity and soil clay content. Our findings can offer new insights and decision-support in climate-adapted urban planning and heat-related risk management across different building climate zones.

Climate Variations in the Low-Latitude Plateau Contribute to Different Sugarcane (Saccharum spp.) Yields and Sugar Contents in China.

In China, the main sugarcane (Saccharum spp.) planting areas can be found in the low-latitude plateau (21° N-25° N, 97° E-106° E), which has most of the natural ecological types. However, there is limited information on the climate conditions of this region and their influence on sugarcane yield and sucrose content. Monthly variations in the main climate factors, namely, average air temperature (AAT), average relative humidity (ARH), average rainfall amount (ARA), and average sunshine duration (ASD), from 2000 to 2019 and sugarcane yield and sucrose content of 26 major sugarcane-producing areas from 2001/2002 to 2018/2019 were collected from the low-latitude plateau in Yunnan for studying the impact of climate variations on sugarcane yield and sucrose content. The results showed that AAT in the mid-growth season had a significant positive correlation with sucrose content (p < 0.05), and AAT in the late-growth season had a very significant positive correlation with sucrose content (p < 0.01). ARH in the mid-growth season had a significant positive correlation with sugarcane yield (p < 0.05). ARA in the early-growth season showed a significant positive correlation with sugarcane yield (p < 0.05). ASD in the late-growth season had a significant positive correlation with sugarcane yield (p < 0.05) and sucrose content (p < 0.01). The rainy and humid sugarcane areas were characterized by high ARA and ARH during the entire growth period, low AAT and ASD in the mid-growth season, and low AAT in the late-growth season, contributing to a high sugarcane yield, but not a high sucrose content. The low temperature and sunshine semi-humid sugarcane areas were characterized by the lowest AAT in the early and middle stages of sugarcane growth, less ASD in the early and middle stages, and less ARA in the early and late stages, which are unfavorable for sugarcane yield and sucrose content. The high temperature and humidity sugarcane areas were characterized by higher AAT and ARA, and moderate ASD during the entire growth period, resulting in good sugarcane growth potential and contributing to the sugarcane yield and sucrose content. The semi-humid and multi-sunshine sugarcane areas were characterized by the lowest ARH in the entire growth period, the lowest ARA in the middle and late seasons, and the longest ASD, contributing to an increase in sucrose content. The humid and sunny areas were characterized by the longest ASD and high ARH in the early and late seasons of sugarcane growth and moderate AAT and ARA during the entire growth season, which are beneficial for high sugarcane yield and sucrose content. Overall, these findings suggest that the sugarcane variety layout should be based on the climate type (of which there are five in the plateau), and corresponding cultivation practices should be used to compensate for the climatic conditions in various growth stages.

The dynamic linkages among crude oil price, climate change and carbon price in China

Crude oil prices, weather changes, and carbon prices are closely related, but little research investigates their dynamic relationship. Studying how crude oil prices and weather changes dynamically affect carbon prices is significant to investors and producers. Taking carbon prices in Hubei and Guangdong as examples, we use the time-varying parameter vector autoregressive (TVP-VAR) model to investigate the time-varying influence of WTI and weather changes (average temperature, sunshine duration, and precipitation) on China's carbon prices. Our empirical results show that: firstly, the impact of crude oil prices and weather changes on carbon prices is obviously time-varying and lagging. Secondly, the short-term impact of crude oil prices and weather changes on carbon prices is higher than the long-term impact. And crude oil price mainly positively affects carbon prices in the short term. Finally, due to the differences in industrial development and weather conditions between Hubei and Guangdong, there are certain regional differences in the impact of crude oil prices and weather changes on carbon prices. Based on these research results, some suggestions are provided for global sustainable development and green transformation of enterprises.

Investigation of the effect of climate change on reference evapotranspiration in Tekirdag, Turkiye

It is important to determine the impact of global climate change on water resources. In the effective use of water resources, the amount of water required for agricultural irrigation should be planned under these conditions. In this study, the trend analysis of the climate data required for the calculation of reference evapotranspiration (ET0) between 2011 and 2020 for the meteorology station of Tekirdag, Turkey was carried out. Analysis of change in the study was carried out according to the methods of Linear Regression Test, Mann-Kendall Test and Sen T Test. As a result of the change analysis, it was determined that the reference evapotranspiration (ET0) values had a decreasing trend in June and July and this decrease was statistically significant. As a result of the analysis of the changes in the climate parameters used in the calculation of reference evapotranspiration (ET0), it was determined that the values of maximum temperature, average relative humidity and average sunshine duration were in a decreasing trend, while minimum temperature and wind speed values were in an increasing trend. In the study, the change in monthly precipitation amounts during the measurement periods was also examined. As a result of the analysis of the changes, it was determined that the monthly precipitation amounts have a decreasing trend and the changes especially in April, September, October and December are statistically significant. It is thought that the results obtained will contribute to the future agricultural production planning in the regional conditions.

Association between provincial sunshine duration and mortality rates in China: Panel data study

Backgroundmortality rates are usually influenced by the variations of environmental factors. However, there are few studies on the impact of sunlight duration induced mortality. In this study, we examine provincial level associations between the sunshine duration and crude mortality rates. Methodswe use China mortality data from the National Bureau of Statistics of China combined with China census data and data from the China Meteorological Data Service Centre. Annual mortality rates for 31 provinces, autonomous regions, and municipalities in China from 2005 to 19. Data are analyzed at the provincial level by using panel regression methods. The main outcome measures are the mortality rates associated with average daily sunshine duration. Then we perform a series of sentimental analyses. Resultsthe average daily sunshine duration ratio cubed is positively associated with provincial level mortality rates (β = 11.509, 95% confidence interval 1.869 to 21.148). According to this estimate, increasing 2.895 h of additional daily sunshine is associated with an estimated 1.15% increase in the crude mortality rates. A series of sensitivity analyses show a consistent pattern of associations between average daily sunshine duration ratio cubed and mortality rates. Conclusionsmore sunshine duration is associated with increased mortality rates. While the associations documented cannot be assumed to be causal, they suggest a potential association between increased sunshine duration and increased mortality rates.

Machine Learning Prediction Model of Tuberculosis Incidence Based on Meteorological Factors and Air Pollutants.

Tuberculosis (TB) is a public health problem worldwide, and the influence of meteorological and air pollutants on the incidence of tuberculosis have been attracting interest from researchers. It is of great importance to use machine learning to build a prediction model of tuberculosis incidence influenced by meteorological and air pollutants for timely and applicable measures of both prevention and control. The data of daily TB notifications, meteorological factors and air pollutants in Changde City, Hunan Province ranging from 2010 to 2021 were collected. Spearman rank correlation analysis was conducted to analyze the correlation between the daily TB notifications and the meteorological factors or air pollutants. Based on the correlation analysis results, machine learning methods, including support vector regression, random forest regression and a BP neural network model, were utilized to construct the incidence prediction model of tuberculosis. RMSE, MAE and MAPE were performed to evaluate the constructed model for selecting the best prediction model. (1) From the year 2010 to 2021, the overall incidence of tuberculosis in Changde City showed a downward trend. (2) The daily TB notifications was positively correlated with average temperature (r = 0.231), maximum temperature (r = 0.194), minimum temperature (r = 0.165), sunshine duration (r = 0.329), PM2.5 (r = 0.097), PM10 (r = 0.215) and O3 (r = 0.084) (p < 0.05). However, there was a significant negative correlation between the daily TB notifications and mean air pressure (r = -0.119), precipitation (r = -0.063), relative humidity (r = -0.084), CO (r = -0.038) and SO2 (r = -0.034) (p < 0.05). (3) The random forest regression model had the best fitting effect, while the BP neural network model exhibited the best prediction. (4) The validation set of the BP neural network model, including average daily temperature, sunshine hours and PM10, showed the lowest root mean square error, mean absolute error and mean absolute percentage error, followed by support vector regression. The prediction trend of the BP neural network model, including average daily temperature, sunshine hours and PM10, successfully mimics the actual incidence, and the peak incidence highly coincides with the actual aggregation time, with a high accuracy and a minimum error. Taken together, these data suggest that the BP neural network model can predict the incidence trend of tuberculosis in Changde City.

Relationship between Satsuma mandarin yield and meteorological factors in Shizuoka and distribution of alternative flowering indices in Mikkabi production area, Japan.

Biennial bearing, the biggest factor destabilizing citrus fruit production, is primarily attributed to unfavorable weather changes. However, the relationship between the yield of Satsuma mandarin for more than 50 years and the weather remains poorly understood. Therefore, the present study investigated the effect of meteorological factors, such as average temperature, precipitation, and sunshine duration, on the yield of Satsuma mandarin in Shizuoka Prefecture, Japan. We analyzed fruit production statistics and meteorological observation data from 1961 to 2018. Furthermore, we investigated the alternative indices of flowering and sprouting in each of the 20 districts of Mikkabi Town, Hamamatsu City, Shizuoka Prefecture. We detected a positive correlation between the average temperatures in March and February and yields in Shizuoka and Hamamatsu Cities. All alternative indices, except flowering in the early-maturing cultivar, were significantly lower in the southern than in the northern districts (P < 0.01 or 0.05). Particularly, the alternative index of flowering in the late-maturing cultivar was significantly different between the northern and southern districts (P < 0.01). Furthermore, we found a negative correlation between the mean annual temperature or average temperature from January to April and alternative indices of flowering and sprouting. The findings of our field survey in Mikkabi production area suggest that mean annual temperature may affect the biennial bearing of Satsuma mandarin. © 2023 Society of Chemical Industry.

Performance Ratio and Loss Analysis for a Grid-Connected Solar Photovoltaic System: Case of the 7MW Plant in Malbaza, Niger

The use of solar energy in sunny countries is an efficient way to overcome the energy shortage. The interest of this energy is not only economic but also environmental, as it emits few greenhouse gases. Niger, a vast landlocked country in the Sahel, is characterized by an average sunshine duration of 8.5 hours per day and an estimated average level of sunshine of around 5 to 7 kW/m2 per day. However, the rate of access to electricity in Niger remains very low. To address this problem, a 7MW solar photovoltaic power plant has been built by the State of Niger in the town of Malbaza. It is composed of monocrystalline photovoltaic panels and injects its energy into the national grid. The objective of this study is to compare the performance ratio determined by measurements with that obtained by simulation under PVsyst in order to evaluate its efficiency. The study is based on annual energy production data, recorded at the site, from 1 January 2021 to 31 December 2021. The annual average values of the global irradiation of the site, the energy produced by the system and the energy injected into the grid are respectively 249.86kWh/m², 1225.25MWh and 972.62MWh; those of the ambient temperature and the performance ratio (PR) are respectively 29.78°C and 0.795. The global losses caused by meteorological phenomena and those linked to the technologies of the various components of the system are evaluated at 20.10%.

Analysis of Bioclimatic Comfort Conditions with Tourism Comfort Index in Aydın Province

Geçtiğimiz birkaç on yılda turizm birçok ülkede en önemli ekonomik faaliyetlerden biri haline geldi. Son yıllarda Dünya genelinde hem salgın hem de savaş nedeniyle turizm faaliyetlerinde düşüş görülmektedir. Özellikle soğuk ülkelerden yaz aylarında Türkiye’ye turistler gelmektedir. Salgın ve savaşların yanı sıra küresel iklim değişikliğine bağlı olarak artan sıcaklık turizm aktivitelerini de etkilemektedir. İnsanlar bu artan sıcaklık karşısında kendilerini en rahat hissettiği ortamlarda turizm faaliyetlerini sürdürmek istemektedir. İnsan faaliyetlerine etki eden en önemli faktör biyoklimatik konfor koşullarıdır. Bu koşulların belirlenmesi önemlidir. Biyokonfor koşulları için çeşitli indeksler geliştirilmiştir. Bu çalışmada Aydın İli 2021 yılı haziran, temmuz ve ağustos aylarına ait sıcaklık, aylık ortalama ve maksimum bağıl nem (%), aylık ortalama rüzgâr şiddeti (km/saat), aylık ortalama yağış (mm) ve aylık ortalama güneşlenme süresi (saat) verileri temin edilmiştir. Veriler excel ortamında düzenlenmiştir. Veriler düzenlendikten sonra turizm iklim konforunun hesaplanmasında en yaygın olarak turizm konfor indeksi (TCI) formülü ile çalışma alanında yer alan meteorolojik gözlem istasyonlarına ait TCI değeri hesaplanmıştır. Açık kaynak koldu QGIS yazılımı içerisine meteorolojik gözlem istasyonları ve TCI değerleri atılmıştır. Ters mesafe ağırlıklı enterpolasyon yöntemi kullanılarak haziran, temmuz ve ağustos aylarına ait TCI haritası üretilmiştir. Bu haritalar üzerinde Aydın İli turizm iklim konforu değerlendirilmiştir.