Urban heat island and bioclimatological conditions in a hot-humid tropical city: the example of Akure, Nigeria

The impact of weather on human health has become an issue of increased significance in recent times, considering the increasing rate of urbanisation and the much associated heat island phenomenon. This study examines the urbanisation influence on human bioclimatic conditions in Akure, a medium sized hot-humid tropical city in Nigeria, utilising data from measurements at urban and rural sites in the city. Differences in the diurnal, monthly and seasonal variation of human bioclimatic characteristics between both environments were evaluated and tested for statistical significance. Higher frequencies of high temperatures observed in the city centre suggest a significant heat stress and health risk in this hot-humid city

Observed urban heat island characteristics in Akure, Nigeria

A climatological analysis of the differences in air temperature between rural and urban areas (Tu-r) corroborates the existence of an urban heat island (UHI) in Akure (7º 25’ N, 5º 20’ E), a tropical city in the south western part of Nigeria. The investigations which have been conducted out of a year-long experiment from fixed point observations focuses on the description of the climatology of urban canopy heat island in the Akure and the analysis of the results were presented. The results show that the nocturnal heat island was more frequent than the daytime heat island as it exists from less intense to higher intensity categories throughout the study period. Nocturnal heat Island intensity was observed to be stronger during the dry season. Although of lower intensity, daytime heat Island exists throughout the day except for few hours in the months of November and December that exhibits a reverse thermal contrast. The daytime heat island is observed to be intense in the wet months than the dry months, which may be caused by the evaporative cooling of wet surfaces. On the average, the urban/ rural thermal differences are positive, varying from 4°C at nocturnal hours during dry months to an approximate of 2°C around noon during wet months. This paper explain the aspects of heat islands and their relation to other causative agents such as the sky view factor (SVF) and also discusses its potential impact on energy demand.Key words: Urban heat island, sky view factor, energy demand

Assessment of Projected Temperature Over West Africa Using CORDEX Regional Climate Models

This study assessed the projections of temperature over West Africa using the simulated daily temperatures which were output of two (2) Coordinated Regional Climate Downscaling Experiment (CORDEX) models, include historical runs (1951-2005) and two (2) concentration pathways scenarios (RCP 4.5 from 2006-2100 and RCP 8.5 from 2006-2070) obtained from Earth System Grid Federation (ESGF) and Copernicus Climate Change Service (C3S-Climate Data Store) with spatial resolution of 0.220. Results show that over West Africa under the Representation Concentration Pathways (RCP 4.5) scenario, there is a strong agreement between the distribution of model and observed PDF for the maximum temperature as the probability density functions ( PDF) increases between 0.1 to 0.2 within the range of maximum temperature of 32.5°C to 36.0°C, the observed and MPI-CCLM5 revealed an agreement while the CCCma-CanRCM4 overestimated the PDF with a spike of 0.45 in March, April and May from 1979-2018. The validation of the PDF yielded skill score for the maximum temperature revealed at 0.86 and 0.81 for CCCma-CanRCM4 and MPI-CCLM5 models respectively under RCP 4.5 scenario in March, April and May from 1979-2018 over West Africa. In June, July, August and September from 1979 to 2018 under the RCP 4.5 scenario, there is a fair agreement between the distribution of model and observed PDF for the maximum temperature as the PDF increases from 0.1 to 0.15 with the MPI-CCLM5 model in fair agreement with the observed while the CCCma-CanRCM4 model overestimated the observed with a spike PDF value of 0.47.The validation of the PDF yielded skill score for the maximum temperature revealed at 0.89 and 0.86 for CCCma-CanRCM4 and MPI-CCLM5 models respectively under RCP 4.5 scenario in June, July, August and September from 1979-2018 over West Africa. The findings revealed a warming trend in the possible future climate of West Africa and the temperature increase could pose a serious threat on socioeconomic activities, which necessitates a call to action for possible climate adaption and mitigation pathways for planners and policymakers. Keywords:Temperature, RCP, PDF DOI: 10.7176/JEES/11-10-01 Publication date:October 31st 202

Comparisons of urban and rural heat stress conditions in a hot–humid tropical city

Background: In recent years the developing world, much of which is located in the tropical countries, has seen dramatic growth of its urban population associated with serious degradation of environmental quality. Climate change is producing major impacts including increasing temperatures in these countries that are considered to be most vulnerable to the impact of climate change due to inadequate public health infrastructure and low income status. However, relevant information and data for informed decision making on human health and comfort are lacking in these countries. Objective: The aim of this paper is to study and compare heat stress conditions in an urban (city centre) and rural (airport) environments in Akure, a medium-sized tropical city in south-western Nigeria during the dry harmattan season (January–March) of 2009. Materials and methods: We analysed heat stress conditions in terms of the mean hourly values of the thermohygrometric index (THI), defined by simultaneous in situ air temperature and relative humidity measurements at both sites. Results: The urban heat island (UHI) exists in Akure as the city centre is warmer than the rural airport throughout the day. However, the maximum UHI intensity occurs at night between 1900 and 2200 hours local time. Hot conditions were predominant at both sites, comfortable conditions were only experienced in the morning and evenings of January at both sites, but the rural area has more pleasant morning and evenings and less of very hot and torrid conditions. January has the lowest frequency of hot and torrid conditions at both sites, while March and February has the highest at the city centre and the airport, respectively. The higher frequencies of high temperatures in the city centre suggest a significant heat stress and health risk in this hot humid environment of Akure. Conclusions: More research is needed to achieve better understanding of the seasonal variation of indoor and outdoor heat stress and factors interacting with it in order to improve the health, safety, and productivity of Akure city dwellers

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Les pathologies de la liberté (ou la liberté des pathologies)

Peer reviewe

Assessment of WRF Land Surface Model Performance over West Africa

Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundEstimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.Methods22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsGlobal all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.InterpretationGlobal adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic