Comparative Analysis of Meteorological versus In Situ Variables in Ship Thermal Simulations

Thermal simulations have become increasingly popular in assessing energy efficiency and predicting thermal behaviors in various structures. Calibration of these simulations is essential for accurate predictions. A crucial aspect of this calibration involves investigating the influence of meteorological variables. This study aims to explore the impact of meteorological variables on thermal simulations, particularly focusing on ships. Using TRNSYS (TRaNsient System Simulation) software (v17), renowned for its capability to model complex energy systems within buildings, the significance of incorporating meteorological data into thermal simulations was analyzed. The investigation centered on a patrol vessel stationed in a port in Galicia, northwest Spain. To ensure accuracy, we not only utilized the vessel's dimensions but also conducted in situ temperature measurements onboard. Furthermore, a dedicated weather station was installed to capture real-time meteorological data. Data from multiple sources, including Meteonorm and MeteoGalicia, were collected for comparative analysis. By juxtaposing simulations based on meteorological variables against those relying solely on in situ measurements, we sought to discern the relative merits of each approach in enhancing the fidelity of thermal simulations.

Effects of Ambient Temperature, Relative Humidity, and Precipitation on Diarrhea Incidence in Surabaya

BACKGROUND

Diarrhea remains a common infectious disease caused by various risk factors in developing countries. This study investigated the incidence rate and temporal associations between diarrhea and meteorological determinants in five regions of Surabaya, Indonesia.

METHOD

Monthly diarrhea records from local governmental health facilities in Surabaya and monthly means of weather variables, including average temperature, precipitation, and relative humidity from Meteorology, Climatology, and Geophysical Agency were collected from January 2018 to September 2020. The generalized additive model was employed to quantify the time lag association between diarrhea risk and extremely low (5th percentile) and high (95th percentile) monthly weather variations in the north, central, west, south, and east regions of Surabaya (lag of 0-2 months).

RESULT

The average incidence rate for diarrhea was 11.4 per 100,000 during the study period, with a higher incidence during rainy season (November to March) and in East Surabaya. This study showed that the weather condition with the lowest diarrhea risks varied with the region. The diarrhea risks were associated with extremely low and high temperatures, with the highest RR of 5.39 (95% CI 4.61, 6.17) in the east region, with 1 month of lag time following the extreme temperatures. Extremely low relative humidity increased the diarrhea risks in some regions of Surabaya, with the highest risk in the west region at lag 0 (RR = 2.13 (95% CI 1.79, 2.47)). Extremely high precipitation significantly affects the risk of diarrhea in the central region, at 0 months of lag time, with an RR of 3.05 (95% CI 2.09, 4.01).

CONCLUSION

This study identified a high incidence of diarrhea in the rainy season and in the deficient developed regions of Surabaya, providing evidence that weather magnifies the adverse effects of inadequate environmental sanitation. This study suggests the local environmental and health sectors codevelop a weather-based early warning system and improve local sanitation practices as prevention measures in response to increasing risks of infectious diseases.

Web-Based Data to Quantify Meteorological and Geographical Effects on Heat Stroke: Case Study in China

Heat stroke is a serious heat-related health outcome that can eventually lead to death. Due to the poor accessibility of heat stroke data, the large-scale relationship between heat stroke and meteorological factors is still unclear. This work aims to clarify the potential relationship between meteorological variables and heat stroke, and quantify the meteorological threshold that affected the severity of heat stroke. We collected daily heat stroke search index (HSSI) and meteorological data for the period 2013-2020 in 333 Chinese cities to analyze the relationship between meteorological variables and HSSI using correlation analysis and Random forest (RF) model. Temperature and relative humidity (RH) accounted for 62% and 9% of the changes of HSSI, respectively. In China, cases of heat stroke may start to occur when temperature exceeds 36°C and RH exceeds 58%. This threshold was 34.5°C and 79% in the north of China, and 36°C and 48% in the south of China. Compared to RH, the threshold of temperature showed a more evident difference affected by altitude and distance from the ocean, which was 35.5°C in inland cities and 36.5°C in coastal cities; 35.5°C in high-altitude cities and 36°C in low-altitude cities. Our findings provide a possible way to analyze the interaction effect of meteorological variables on heat-related illnesses, and emphasizes the effects of geographical environment. The meteorological threshold quantified in this research can also support policymaker to establish a better meteorological warning system for public health.

To tolerate weather and to tolerate pain: two sides of the same coin? The Tromsø Study 7

ABSTRACT

It is a common belief that weather affects pain. Therefore, we hypothesized that weather can affect pain tolerance. This study used data from over 18,000 subjects aged 40 years or older from the general population, who participated in the Tromsø Study 7. They underwent a one-time assessment of cuff algometry pressure pain tolerance (PPT) and cold pain tolerance (CPT), tested with a cold pressor test. The results showed a clear seasonal variation in CPT. The rate of withdrawal in the cold pressor test was up to 75% higher in months in the warmer parts of the year compared with January 2016. There was no seasonal variation in PPT. The study not only found a nonrandom short-term variation in PPT but also indications of such a variation in CPT. The intrinsic timescale of this short-term variation in PPT was 5.1 days (95% % confidence interval 4.0-7.2), which is similar to the observed timescales of meteorological variables. Pressure pain tolerance and CPT correlated with meteorological variables, and these correlations changed over time. Finally, temperature and barometric pressure predicted future values of PPT. These findings suggest that weather has a causal and dynamic effect on pain tolerance, which supports the common belief that weather affects pain.

Assessment of Meteorological Variables and Air Pollution Affecting COVID-19 Cases in Urban Agglomerations: Evidence from China

The 2019 novel coronavirus disease (COVID-19) has become a severe public health and social problem worldwide. A limitation of the existing literature is that multiple environmental variables have not been frequently elaborated, which is why the overall effect of the environment on COVID-19 has not been conclusive. In this study, we used generalized additive model (GAM) to detect the relationship between meteorological and air pollution variables and COVID-19 in four urban agglomerations in China and made comparisons among the urban agglomerations. The four urban agglomerations are Beijing-Tianjin-Hebei (BTH), middle reaches of the Yangtze River (MYR), Yangtze River Delta (YRD), and the Pearl River Delta (PRD). The daily rates of average precipitation, temperature, relative humidity, sunshine duration, and atmospheric pressure were selected as meteorological variables. The PM_2.5, PM₁₀, sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO) contents were selected as air pollution variables. The results indicated that meteorological and air pollution variables tended to be significantly correlated. Moreover, the nature of the relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and meteorological and air pollution variables (i.e., linear or nonlinear) varied with urban agglomerations. Among the variance explained by GAMs, BTH had the highest value (75.4%), while MYR had the lowest value (35.2%). The values of the YRD and PRD were between the above two, namely 45.6% and 62.2%, respectively. The findings showed that the association between SARS-CoV-2 and meteorological and air pollution variables varied in regions, making it difficult to obtain a relationship that is applicable to every region. Moreover, this study enriches our understanding of SARS-CoV-2. It is required to create awareness within the government that anti-COVID-19 measures should be adapted to the local meteorological and air pollution conditions.

Assessment of temporal shifting of PM2.5, lockdown effect, and influences of seasonal meteorological factors over the fastest-growing megacity, Dhaka

Dhaka is subjected to high pollution levels throughout the year, holding some relatively high amounts of pollution readings, making its air unhealthy to breathe. The study examined hourly, shifting, seasonal fluctuations in particulate matter (PM_2.5), the effects of seasonal meteorological variables, and the lockdown effect over the megacity of Dhaka from 2019 to 2021 using data from AirNow. The results indicate the daily average PM_2.5 concentration between 2019 and 2021 was 112.49 µg/m³, about four times higher than the WHO limit and two times higher than the Bangladesh standard. Daily PM_2.5 concentrations was high during morning and evening pick-up hours, reaching a maximum hourly concentration of 472.9 µg/m³ in February 2020. The maximum average PM_2.5 concentration was 211.23 µg/m³ in March 2021 (winter season), and the lowest average was 27.58 µg/m³ in August 2020 (rainy season). The Pearson correlation coefficient (r) between the PM_2.5 and meteorological variables were inverse with rainfall (− 0.62), temperature (− 0.73), humidity (− 0.82), but positive with wind (0.09). Daily average Air Quality Index (AQI) concentrations improved from 108.53 to 67.99 µg/m³ during the lockdown period. Finally, the study recommended many mitigation strategies that might assist accountable authorities in lowering the number of life-threatening components in the air.

Time-Varying Effects of Meteorological Variables on Malaria Epidemiology in the Context of Interrupted Control Efforts in the Amazon Rainforest, 2000-2017

Successful malaria control interventions, mostly based on the training of health workers, distribution of insecticide-treated nets, and spraying, decrease malaria incidence; however, when these interventions are interrupted, a resurgence may occur. In the Peruvian Amazon, after discontinuing the control activities implemented by the PAMAFRO project (2006–2010)-a Global Fund-sponsored project for the strengthening of malaria control and surveillance in multiple countries in Latin America– malaria cases re-emerged dramatically. In parallel, meteorological factors determine the conditions suitable for the development, reproduction, and survival of mosquito vectors and parasites. This study hypothesized that interruption of malaria interventions may have modified the meteorological-malaria relationships over time (i.e., temporal changes in the dose-response between meteorological variables and malaria incidence). In this panel data analysis, we assessed the extent that relationships between meteorological variables and malaria changed temporally using data of monthly malaria incidence due to Plasmodium vivax or P. falciparum in Loreto, Peru (2000–2017). Generalized additive models were used to explore how the effects of meteorological variables changed in magnitude before, during, and after the PAMAFRO intervention. We found that once the PAMAFRO intervention had been interrupted, the estimated effects (dose-response) of meteorological variables on incidence rates decreased for both malaria parasite species. However, these fitted effect estimates did not reach their baseline levels (before the PAMAFRO period); variations of time-varying slopes between 0.45 and 2.07 times were observed after the PAMAFRO intervention. We also reported significant heterogeneity in the geographical distributions of malaria, parasite species, and meteorological variables. High malaria transmission occurred consistently in the northwestern provinces of Loreto Department. Since the end of the PAMAFRO period, a higher effect of precipitation and actual evapotranspiration was described on P. falciparum compared to P. vivax. The effect of temperature on malaria was greater over a shorter time (1-month lag or less), compared with precipitation and actual evapotranspiration (12-month lag). These findings demonstrate the importance of sustained malaria control efforts since interruption may enhance the links between meteorological factors and malaria. Our results also emphasize the importance of considering the time-varying effect of meteorological factors on malaria incidence to tailor control interventions, especially to better manage the current and future climate change crisis.

Global patterns and drivers of rainfall partitioning by trees and shrubs

Spatiotemporal redistribution of incident rainfall in vegetated ecosystems results from the partitioning by plants into intercepted, stemflow, and throughfall fractions. However, variation in patterns and drivers of rainfall partitioning across global biomes remains poorly understood, which limited the ability of climate models to improve the predictions of biome hydrological cycle under global climate change scenario. Here, we synthesized and analyzed the partitioning of incident rainfall into interception, stemflow, and throughfall by trees and shrubs at the global scale using 2430 observations from 236 independent publications. We found that (1) globally, median levels of relative interception, stemflow, and throughfall accounted for 21.8%, 3.2%, and 73.0% of total incident rainfall, respectively; (2) rainfall partitioning varied among different biomes, due to variation in plant composition, canopy structure, and macroclimate; (3) relative stemflow tended to be driven by plant traits, such as crown height:width ratio, basal area, and height, while relative interception and throughfall tended to be driven by plant traits as well as meteorological variables. Our global assessment of patterns and drivers of rainfall partitioning underpins the role of meteorological factors and plant traits in biome-specific ecohydrological cycles. We suggest to include these factors in climate models to improve the predictions of local hydrological cycles and associated biodiversity and function responses to changing climate conditions.

The Association of Meteorological Factors with Cognitive Function in Older Adults

Individual and meteorological factors are associated with cognitive function in older adults. However, how these two factors interact with each other to affect cognitive function in older adults is still unclear. We used mixed effects models to assess the association of individual and meteorological factors with cognitive function among older adults. Individual data in this study were from the database of China Family Panel Studies. A total of 3448 older adults from 25 provinces were included in our analysis. Cognitive functions were measured using a memory test and a logical sequence test. We used the meteorological data in the daily climate dataset of China’s surface international exchange stations, and two meteorological factors (i.e., average temperature and relative humidity) were assessed. The empty model showed significant differences in the cognitive scores of the older adults across different provinces. The results showed a main impact of residence (i.e., urban or rural) and a significant humidity–residence interaction on memory performance in older adults. Specifically, the negative association between humidity and memory performance was more pronounced in urban areas. This study suggested that meteorological factors may, in concert with individual factors, be associated with differences in memory function in older adults.

The Need for Collective Awareness of Attempted Suicide Rates in a Warming Climate

Background: Climate factors may offer a stronger explanation of the variations in suicide rates compared with economic variables, even in the case of patients admitted involuntarily. Aims: We assessed the role of temperature as a determinant of the increased prevalence of suicide attempts (SA). Method: The sample comprised all cases of hospitalization for SA at the Psychiatric Clinic of the IRCCS Ospedale Policlinico San Martino between August 2013 and July 2018. For ambient temperature, data were provided by the Meteorological Observatory of the University of Genoa. Results: We noted a peak in suicides that was typically found in late spring and early summer due to global warming. Limitations: Other environmental/psychological factors contributing to the onset of an acute clinical event were not considered. The cross-sectional design of the study is another limitation. Conclusion: Further studies are needed to clarify the impact of climatic factors on suicide behavior and implement early intervention and preventive strategies for mental health.

Meteorological Variables and Synoptic Patterns Associated with Air Pollutions in Eastern China during 2013-2018

Steady meteorological conditions are important external factors affecting air pollution. In order to analyze how adverse meteorological variables affect air pollution, surface synoptic situation patterns and meteorological conditions during heavy pollution episodes are discussed. The results showed that there were 78 RPHPDs (regional PM_2.5 pollution days) in Jiangsu, with a decreasing trend year by year. Winter had the most stable meteorological conditions, thus most RPHPDs appeared in winter, followed by autumn and summer, with the least days in spring. RPHPDs were classified into three patterns, respectively, as equalized pressure (EQP), advancing edge of a cold front (ACF) and inverted trough of low pressure (INT) according to the SLP (sea level pressure). RPHPDs under EQP were the most (51%), followed by ACF (37%); INT was the minimum (12%). Using statistical methods and meteorological condition data on RPHPDs from 2013 to 2017 to deduce the thresholds and 2018 as an independent dataset to validate the proposed thresholds, the threshold values of meteorological elements are summarized as follows. The probability of RPHPDs without rain was above 92% with the daily and hourly precipitation of all RPHPDs below 2.1 mm and 0.8 mm. Wind speed, RHs, inversion intensity(ITI), height difference in the temperature inversion(ITK), the lower height of temperature inversion (LHTI) and mixed-layer height (MLH) in terms of 25%–75% high probability range were respectively within 0.5–3.6 m s⁻¹, 55%–92%, 0.7–4.0 °C 100 m ⁻¹, 42–576 m, 3–570 m, 200–1200 m. Two conditions should be considered: whether the pattern was EQP, ACF or INT and whether the eight meteorological elements are within the thresholds. If both criteria are met, PM_2.5 particles tend to accumulate and air pollution diffusion conditions are poor. Unfavorable meteorological conditions are the necessary, but not sufficient condition for RPHPDs.

Maximum Temperature and Solar Radiation as Predictors of Bipolar Patient Admission in an Emergency Psychiatric Ward

Environmental variables can regulate behavior in healthy subjects. Recently, some authors investigated the role of meteorological variables in bipolar patients with an impact on both the onset and course of bipolar disorder (BD). The aim of this study was to investigate the impact of meteorological variables and other indexes in bipolar hospitalized patients. We examined all patients admitted to the Psychiatric Inpatient Unit of San Luigi Gonzaga Hospital, Orbassano (Turin, Italy) from September 2013 to August 2015, collecting several socio-demographic and clinical characteristics. Seven hundred and thirty patients were included. Compared to the day of admission of control individuals, patients with BD were admitted on a day that presented higher minimum, medium, and maximum temperature, higher maximum humidity, higher solar radiation, and higher hours of sunshine. After logistic regression analysis, admissions to the emergency psychiatric ward due to a primary diagnosis of BD were associated with maximum temperature and solar radiation. The current study provides a novel perspective on the question surrounding seasonal mood patterns in patients with BD. A greater awareness of all possible precipitating factors is needed to inform self-management and psycho-educational programs as well as to improve resilience regarding affective recurrences in the clinical practice.

How Socio-Environmental Factors Are Associated with Japanese Encephalitis in Shaanxi, China-A Bayesian Spatial Analysis

Evidence indicated that socio-environmental factors were associated with occurrence of Japanese encephalitis (JE). This study explored the association of climate and socioeconomic factors with JE (2006–2014) in Shaanxi, China. JE data at the county level in Shaanxi were supplied by Shaanxi Center for Disease Control and Prevention. Population and socioeconomic data were obtained from the China Population Census in 2010 and statistical yearbooks. Meteorological data were acquired from the China Meteorological Administration. A Bayesian conditional autoregressive model was used to examine the association of meteorological and socioeconomic factors with JE. A total of 1197 JE cases were included in this study. Urbanization rate was inversely associated with JE incidence during the whole study period. Meteorological variables were significantly associated with JE incidence between 2012 and 2014. The excessive precipitation at lag of 1–2 months in the north of Shaanxi in June 2013 had an impact on the increase of local JE incidence. The spatial residual variations indicated that the whole study area had more stable risk (0.80–1.19 across all the counties) between 2012 and 2014 than earlier years. Public health interventions need to be implemented to reduce JE incidence, especially in rural areas and after extreme weather.

Effects of meteorological factors on the incidence of meningococcal meningitis

BACKGROUND AND OBJECTIVES

Substantial climate changes have led to the emergence and re-emergence of various infectious diseases worldwide, presenting an imperative need to explore the effects of meteorological factors on serious contagious disease incidences such as that of meningococcal meningitis (MCM).

METHODS

The incidences of MCM and meteorology data between 1981 and 2010 were obtained from Chaoyang city. Structure Equation Modeling was used to analyze the relationships between meteorological factors and the incidence of MCM, using the LISREL software.

RESULTS

The SEM results showed that Adjusted Goodness of Fit Index (AGFI) = 0.30, Goodness of Fit Index (GFI) = 0.63, and Root Mean Square Error of Approximation (RMSEA) = 0.31. Humidity and temperature both had negative correlations with MCM incidence, with factor loads of -0.32 and -0.43, while sunshine was positively correlated with a factor load of 0.42. For specific observable variables, average air pressure, average evaporation, average air temperature, and average ground temperature exerted stronger influence, with item loads between observable variables and MCM incidence being -0.42, 0.34, -0.32, and -0.32 respectively.

CONCLUSION

Public health institutions should pay more attention to the meteorological variables of humidity, sunshine, and temperature in prospective MCM control and prevention.

Effects of Meteorological Conditions on PM2.5 Concentrations in Nagasaki, Japan

The fine particulate matter (PM_2.5) problem has attracted much scientific and public attention, due to its effects on visibility, human health, and global climate. There are three factors that have important effect on PM_2.5 mass concentration: domestic pollutant emission sources, external sources outside of the country, and the meteorological conditions. Nagasaki is a coastal prefecture located at the westernmost part of Japan, which is an ideal location to study pollutants from long range transport and correlation between PM_2.5 and meteorological conditions. In this paper, PM_2.5 concentration data and meteorological data were obtained during 1 January 2013~31 December 2013. The spatial distribution depicts that the western part of the study area has the most serious PM_2.5 pollution. The correlation analysis results between PM_2.5 concentration and meteorological data showed that temperature had a negative, and precipitation had a positive, correlation with PM_2.5. There was a threshold in the correlations between humidity and wind speed and PM_2.5. The correlation was positive or negative depending on the meteorological variable values, if these were lower or higher than the threshold. From the relationship with wind direction, it can be depicted that the west wind might bring the most pollutants to Nagasaki.

Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea

Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN) model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered.

Density of Aedes aegypti and Aedes albopictus and its association with number of residents and meteorological variables in the home environment of dengue endemic area, São Paulo, Brazil

BACKGROUND

Measure the populations of Ae. aegypti and Ae. albopictus adults according to sex and location inside or outside the residence, estimate Ae. aegypti female density per house and per resident, and test the association with abiotic factors.

METHODS

Adult mosquitoes were collected monthly with a hand net and portable electric catcher in the peridomiciliary and intradomiciliary premises of residences in an urban area with ongoing dengue transmission in the municipality of São Sebastião, Brazil, from February 2011 to February 2012.

RESULTS

Of the 1,320 specimens collected, 1,311 were Ae. aegypti, and nine were Ae. albopictus. A total of 653 male and 658 female of Ae. aegypti were recorded, of which 80% were intradomiciliary. The mean density of Ae. aegypti adult females was 1.60 females/house and 0.42 females/resident. There was an association between the number of females and the number of residents in both intradomiciliary and peridomiciliary premises (r(2) = 0.92; p < 0.001 and r(2) = 0.68; p < 0.001, respectively). There was an association between the number of females and the mean and total rainfall; the correlation was better in peridomiciliary premises (p = 0.00; r(2) = 77%) than intradomiciliary premises in both cases (p = 0.01; r(2) = 48%). Minimum temperature was associated in both environments, exhibiting the same coefficient of determination (p = 0.02; r(2) = 40%). The low frequency of Ae. albopictus (seven females and two males) did not allow for detailed evaluation.

CONCLUSIONS

Ae. aegypti is well established within the urban area studied, and the frequency of isolation is higher inside the houses. Female density was directly proportional to the number of residents in the houses. Our data show that human population density positively affects the number of Ae. aegypti females within the residence. Meteorological variables also affected mosquito populations. These data indicate a high probability of human-vector contact, increasing the possible transmission and spread of the DEN virus. Entomological indicators of adult females revealed important information complimenting what was obtained with traditional Stegomyia indices. This information should be a part of an interconnected data set for evaluating and controlling the vector.

Association of Meteorological Variables and Coronary Blood Flow

We aimed to assess the impact of meteorological variables on coronary blood flow (CBF). Coronary blood flow was evaluated using the thrombolysis in myocardial infarction frame count (TFC). The association of CBF with meteorological parameters such as temperature, relative humidity, total solar radiation, atmospheric pressure, wind velocity, and total sunshine duration were investigated as well as demographic, clinical, and laboratory characteristics. Assessment of 1206 patients (median age = 53 years, 723 females) revealed the presence of slow coronary flow (SCF) in 196 patients. Daily maximum temperature [odds ratio = 0.951, 95% confidence interval = 0.916-0.986, P = .007] was the only independent predictor of the presence of SCF, whereas systolic blood pressure (β = -0.139, P = .026), hematocrit level (β = 0.128, P = .044), and daily maximum temperature (β = -1.479, P = .049) were independent predictors of log10 (mean TFC). Findings of the present study suggest a role of meteorological parameters in CBF regulation.

Meteorological factors and risk of scrub typhus in Guangzhou, southern China, 2006-2012

BACKGROUND

Scrub typhus is becoming the most common vector born disease in Guangzhou, southern China. In this study, we aimed to examine the effect of weather patterns on the incidence of Scrub typhus in the subtropical city of Guangzhou for the period 2006-2012, and assist public health prevention and control measures.

METHODS

Scrub typhus reported cases during the period of 2006-2012 in Guangzhou were obtained from National Notifiable Disease Report System (NNDRS). Simultaneous meteorological data including temperature, relative humidity, atmospheric pressure, sunshine, and rainfall were obtained from the documentation of the Guangzhou Meteorological Bureau. A negative binomial regression was used to identify the relationship between meteorological variables and scrub typhus.

RESULTS

Annual incidence rates of scrub typhus from 2006 to 2012 were 3.25, 2.67, 3.81, 4.22, 4.41, 5.12, and 9.75 (per 100 000) respectively. Each 1°C rise in temperature corresponded to an increase of 14.98% (95% CI 13.65% to 16.33%) in the monthly number of scrub typhus cases, while a 1 hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 8.03% (95% CI -8.75% to -7.31%). Similarly, a 1 hour rise in sunshine corresponded to an increase of 0.17% or 0.54%, and a 1 millimeter rise in rainfall corresponded to an increase of 0.05% or 0.10%, in the monthly number of scrub typhus cases, depending on the variables considered in the model.

CONCLUSION

Our study provided evidence that climatic factors were associated with occurrence of scrub typhus in Guangzhou city, China. Temperature, duration of sunshine, and rainfall were positively associated with scrub typhus incidence, while atmospheric pressure was inversely associated with scrub typhus incidence. These findings should be considered in the prediction of future patterns of scrub typhus transmission.

Comparison of UTCI to selected thermal indices

Over the past century more than 100 indices have been developed and used to assess bioclimatic conditions for human beings. The majority of these indices are used sporadically or for specific purposes. Some are based on generalized results of measurements (wind chill, cooling power, wet bulb temperature) and some on the empirically observed reactions of the human body to thermal stress (physiological strain, effective temperature). Those indices that are based on human heat balance considerations are referred to as "rational indices". Several simple human heat balance models are known and are used in research and practice. This paper presents a comparative analysis of the newly developed Universal Thermal Climate Index (UTCI), and some of the more prevalent thermal indices. The analysis is based on three groups of data: global data-set, synoptic datasets from Europe, and local scale data from special measurement campaigns of COST Action 730. We found the present indices to express bioclimatic conditions reasonably only under specific meteorological situations, while the UTCI represents specific climates, weather, and locations much better. Furthermore, similar to the human body, the UTCI is very sensitive to changes in ambient stimuli: temperature, solar radiation, wind and humidity. UTCI depicts temporal variability of thermal conditions better than other indices. The UTCI scale is able to express even slight differences in the intensity of meteorological stimuli.

Threat of allergenic airborne grass pollen in Szczecin, NW Poland: the dynamics of pollen seasons, effect of meteorological variables and air pollution

The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004-2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM(10) and SO(2) was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy.