apparent temperature
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Due to global warming, increase in air temperature is a growing concern at present. This rise in temperature may cause mild to severe thermal discomfort and heat related hazards mostly for the people who are engaged in outside activities throughout the day. The present study shows the inter-spatial monthly distribution of thermal patches over major stations of Madhya Pradesh, viz., Bhopal, Gwalior, Indore, Jabalpur, Hoshangabad, Rewa, Ratlam, Ujjain, Dhar etc. In this study, various Heat Indices applicable for tropical climate including Wet Bulb Globe Temperature (WBGT) are used to estimate the thermal stress by analyzing the meteorological data of Summer-2018 in Madhya Pradesh. Study was carried out for computing indoor, shady and outdoor heat stress separately and heat transfer rates to identify the places vulnerable to severe heat stroke in the month of March, April and May in 2018.It is observed that declaration of heat wave alone at any station is not sufficient for the administration and health organizations to take precautionary actions; also, discomfort indices should be referred for impact based monitoring and making work schedules. It is found that March and April fall in the partial discomfort category for at least half of the districts in Madhya Pradesh. It is interesting to note that several districts fall in discomfort category in outdoor conditions but not in indoor or shady conditions in May month. Severe stresses are observed mainly in the West and Central Madhya Pradesh during April and May months. Comparison of various Heat Indices is too performed along with computing Tropical Summer Index (TSI) and Apparent Temperature (AT) to indicate real feel-like temperatures in Madhya Pradesh during extreme temperature events.

Increasing air temperature coupled with high humidity due to ongoing climate change across most parts of South Africa is likely to induce and intensify heat exposure, particularly in densely populated areas. The adverse health implications, including heatstroke, are expected to be common and more severe during extreme heat and heat wave events. The present study was carried out to examine heat stress conditions and long-term trends in South Africa. The study aimed to identify geographical locations exposed to elevated heat stress based on over two decades of hourly ground-based data. Selected heat stress indicators were calculated based on Steadman’s apparent temperature (AT in °C). The trends in AT were assessed based on the non-parametric Mann–Kendall (MK) trend test at 5% significance level. Positive trends were detected in 88% of the selected weather stations except in Welkom-FS, Ficksburg-FS, Langebaanweg-WC, Lambertsbaai Nortier-WC, Skukuza-MP, and Thabazimbi-LP. Approximately 47% of the detected positive trends are statistically significant at 5% significant level. Overall, high climatological annual median (ATmed) values (>32 °C) were observed at 42 stations, most of which are in low altitude regions, predominately along the coastlines. The hottest towns with ATmed values in the danger category (i.e., 39–50 °C) were found to be Patensie-EC (41 °C), Pietermaritzburg-KZN (39 °C), Pongola-KZN (39 °C), Knysna-WC (39 °C), Hoedspruit-LP (39 °C), Skukuza-MP (45 °C), and Komatidraai-MP (44 °C). The results provide insight into heat stress characteristics and pinpoint geographical locations vulnerable to heat stress conditions at the community level in South Africa. Such information can be useful in monitoring hotspots of heat stress and contribute to the development of local heat–health adaptation plans.

Background: Temperature and air pollution are often treated as separate risk factors and very few studies have investigated effect modification by temperature on air pollution, and the impact of this interaction on human health in Africa. This study therefore investigated the modifying effects of temperature on the association between air pollution and Respiratory disease (RD) hospital admission in South Africa.  Methods: RD admission data (ICD10 J00-J99) were obtained from two hospitals located in Secunda, South Africa beween 1 January 2011 to 31 October 2016. NO2, SO2, PM10, PM2.5, temperature and relative humidity data were obtained from the South African Weather Services. A case-crossover epidemiological study design was applied and lag0-1 was used. Models were adjusted for public holidays and  Apparent Temperature (Tapp). Tapp was classified as warm (Tapp>75th percentile), cold (Tapp<25th percentile) and normal (Tapp  25th-75th  percentile). Results: Of the 14 568 RD admissions, approximately equal number of females and males were admitted. The average daily NO2, SO2, PM2.5 and PM10 levels were 12.4 μm/m3, 8.5 μm/m3, 32.3 μm/m3 and 68.6 μm/m3, respectively. Overall, a 10 μm/m3 increase in SO2 on warm days was associated with an increase in RD hospital admissions among the patients by 8.5% (95% Conf. Int: 0.4%, 17.2%) and 8.4% (95% Conf. Int: 0.3%, 17.1%) after adjustment for PM2.5 and PM10 respectively. However, increasing PM2.5 or PM10 by 10 μm/m3 was associated with an increase in RD hospital admissions when the temperature was normal after adjusting for SO2.  On cold days there were significant associations between the SO2 and RD admissions among the 0-14 year age group after adjusting for either PM2.5 (6.5%; 95% Conf.Int: 0.9%, 12.4%) or PM10 (5.5%; 95% Conf.Int: 0.3%, 11.1%). Conclusions: SO2 was affected by extremes of temperature while the particulate matters had effect on RD admission during normal temperature in Secunda.

Children spend a significant proportion of their time at school and in school buildings. A healthy learning environment that supports children should be thermally conducive for learning and working. Here, we aimed to study the relations between indoor classroom temperatures and learner absenteeism as a proxy for children’s health and well-being. This one-year prospective study that spanned two calendar years (from June 2017 to May 2018) entailed measurement of indoor classroom temperature and relative humidity, calculated as apparent temperature (Tapp) and collection of daily absenteeism records for each classroom in schools in and around King Williams Town, Eastern Cape province, South Africa. Classroom characteristics were collected using a standardized observation checklist. Mean indoor classroom temperature ranged from 11 to 30 °C, while mean outdoor temperature ranged from 6 °C to 31 °C during the sample period. Indoor classroom temperatures typically exceeded outdoor temperatures by 5 °C for 90% of the study period. While multiple factors may influence absenteeism, we found absenteeism was highest at low indoor classroom Tapp (i.e., below 15 °C). Absenteeism decreased as indoor Tapp increased to about 25 °C before showing another increase in absenteeism. Classroom characteristics differed among schools. Analyses of indoor classroom temperature and absenteeism in relation to classroom characteristics showed few statistically significant relations—although not exceptionally strong ones—likely because of the multiple factors that influence absenteeism. However, given the possible relationship between indoor temperature and absenteeism, there is a learning imperative to consider thermal comfort as a fundamental element of school planning and design. Furthermore, additional research on factors besides temperature that affect learner absenteeism is needed, especially in rural areas.

Abstract Heat waves are increasing in frequency and also exhibit high spatial variability in its distribution over India. There are limited studies focused on the weather related human thermal comfort over India due to non-availability of high resolution (HR) climate data. Here we develop dynamically downscaled HR (4x4 km) daily climate information for the months of April to June during 2001-2016 using a regional climate model called Weather Research and Forecasting (WRF) Model, which are validated with station observations. The thermal comfort and its spatio-temporal variability over India are quantified in terms of indices like Excessive Heat Factor (EHF), Heat Index (HI), Humidex, Apparent Temperature (AT) and Wet Bulb Globe Temperature (WBGT). The daily surface air temperature and thermal comfort indices of HR WRF model simulations are in good agreement with station observations. The results show that there is an increasing trend in annual heat waves coverage (22240km2/year), annual frequency (0.07 days/year) and average intensity (0.04 °C/year) during 2001-2016. The distributions of indices have spatial and temporal variability. The days with severe discomfort are significantly increasing (99% significance level) over north India and it is quantified with increase of extreme category of indices at the rate of EHF (15.9%), HI (14.9%), Humidex (15.9%), AT (13.4%) and WBGT (13.8%). During heat waves, prolonged exposure or physical activity under sun will led to adverse health impacts and it is mostly observed over northwest and south eastern states. These findings stress the need for developing suitable mitigation strategies for a sustainable ecosystem

The ecological state of the environment, climatic conditions with pronounced seasonality, variability, anomaly summer heat and regional manifestations of climate change, have a certain negative impact onwell-being, health and comfort of life of the population. To assess climatic comfort of a person, a bioclimatic index (equivalent-effective temperature) was used, which allows to evaluate thermal sensation of a person under a certain combination of meteorological parameters. In this study we used daily observation data (surface temperature, air humidity and wind velocity) at 34 meteorological stations in Ukraine for the period 1990—2020. Analysis and ranging of data, which characterize the thermal bioclimatic conditions, were done. It was found that the weather conditions with apparent temperature of very cold—cold—cool—slightly cool compose about 268 ± 9 (73 %) days per year. Thus, the population of Ukraine experience conditions of physiologically cold stress during the prevalent time of the year. Weather conditions that fall into gradations very cold –(30 ... 23) and cold –(23 ... 12) represent 6 ± 5 (~2 %) and 42 ± 17 (~12 %) days per year respectively. They can consequently cause extreme cold and strong cold stress and have a tendency towards decreasing repeatability. The largest number of days on average across the country have such gradations as slightly cool 0 ... 12 and cool –(12 ... 0), 113 ± 10 (31 %) and 107 ± 8 (29 %) days per year respectively. Slightly cool weather conditions are typical for the warm period of the year, mainly autumn and spring, and partially winter, while cool –(12 ... 0) is more prevalent in winter, autumn and spring seasons. Comfortable and subcomfortable thermal conditions for human with apparent temperature of slightly warm and warm compose on average 96 ± 8 (~26 %) days per year. Comfortable thermal conditions for human on the territory of Ukraine represent about 47 ± 13 (13 %) days per year and are typical for the warm period from April to October, with maximal values in summer: June 10 ± 3, July 17 ± 4 and August 15 ± 4 days per month. A number of days with subcomfortable thermal conditions for human on the territory of Ukraine compose also 48 ± 3 (13 %) days per year. Moreover, for May—September it has almost an equal number of days per month from 7 to 12 with minimal values in April, October and November, about 1—2 days. There is a tendency to increase in the number of days with comfortable thermal conditions for human in summer by 0.2—0.3 days per month for the period 1991—2020. The trend is 0.83 days per year (on average 25—30 days were added each year) for the period 1991—2020. Thus, comfortable climatic conditions for the local population in Ukraine increase during the warm season. However, the frequency of hot apparent temperatures (23 ... 30) has increased, especially during summer period, which can subsequently cause strong and extreme heat stress for humans. In particular years, it was recorded up to 5—19 days per year. For that reason, the climatic conditions of Ukraine have a certain potentially comfortable climatic resource(in June—August): Western region has a minimal climatic resource (23—40 %); Northern region has a sufficient climatic resource (36—53 %); Central region has an optimal climatic resource (40—60 %); Southern region has an optimal climatic resource (40—67 %).

The epidemiological evidence on relationships between air pollution, temperature, and stroke remains inconclusive. Limited evidence is available for the effect modification by apparent temperature, an indicator reflecting reactions to the thermal environment, on short-term associations between air pollution and hospital admissions for stroke. We used a generalized additive model with Poisson regression to estimate the relative risk (RR) of stroke admissions in Shanghai, China, between 2014 and 2016 associated with air pollutants, with subgroup analyses by age, sex, apparent temperature, and season. During the study period, changes in the daily number of stroke admissions per 10 μg/m3 increase in nitrogen dioxide (at lags 0, 1, 0–1, and 0–2) ranged from 1.05 (95% CI: 0.82%, 2.88%) to 2.24% (95% CI: 0.84%, 3.65%). For each 10 μg/m3 increase in sulfur dioxide concentrations at lags 1, 2, 0–1, and 0–2, the RR of daily stroke admissions increased by 3.34 (95% CI: 0.955%, 5.79%), 0.32 (95% CI: −1.97%, 2.67%), 3.33 (95% CI: 0.38%, 6.37%), and 2.86% (95% CI: −0.45%, 6.28%), respectively. The associations of same-day exposure to nitrogen dioxide with stroke admissions remained significant after adjustment for ozone levels. These associations were not modified by sex, age, apparent temperature, or season. More research is warranted to determine whether apparent temperature modifies the associations between air pollution and stroke admissions.