➢ Lime can be considered a cost-effective alternative to KOH in hydrothermal humification. ➢ Lime... more ➢ Lime can be considered a cost-effective alternative to KOH in hydrothermal humification. ➢ Lime could significantly reduce aromatics while increasing sugars and acids. ➢ Wet biomass outperformed dry biomass in the process, reducing the need for pre-drying. ➢ A 0.01% addition of hydrothermal humification products notably enhanced plant growth. ➢ Hydrothermal liquid products showed no toxicity in Daphnia magna bioassays.
Occupational Diseases and Environmental Medicine, 2018
Background: External causes include accidents, injuries or health problems that arise immediately... more Background: External causes include accidents, injuries or health problems that arise immediately after accidents or other external factors. The purpose of this review was to collect information about the relation between temperature and mortality due to external causes. Methods: A systematic search of articles was conducted in PubMed, Scopus, Science Direct, Embase, and Web of Science until January 2017, with no restriction. Broad searches were conducted in all fields, using key words related to ambient temperature exposure and deaths due to external causes. Results: Nine articles were included in the study. Except two articles, one of which had been designed in a cross-sectional way and the other that was retrospective, the rest of the articles were ecological. The outcomes reported were heterogeneous and different metrics had been used in the results; therefore conducting of meta-analysis was not possible. Five articles had found direct and significant relations between high temperature and deaths due to external causes. Only one study found no relation. In the case of cold, one study showed that the proportion of death due to external causes was low during cold waves. Another study showed that there was no relation between cold waves and mortality due to external causes. But one article showed that death due to external causes increased on cold days, significantly. Conclusion: The results of this systematic review showed that high temperatures (heat) were more likely to cause mortality due to external causes than low temperatures (cold). Due to the small number of studies in this field, especially in the context of cold and death due to external causes, it is difficult to make robust conclusions.
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Background The SARS-CoV-2 virus pandemic is primarily transmitted by direct contact between infec... more Background The SARS-CoV-2 virus pandemic is primarily transmitted by direct contact between infected and uninfected people, though, there are still many unknown factors influencing the survival and transmission of the virus. Air temperature is one of the main susceptible factors. This study aimed to explore the impact of air and land surface temperatures on Covid-19 transmission in a region of Iran. Method Daily Land Surface Temperature (LST) measured by satellite and Air Temperature measured by weather station were used as the predictors of Covid-19 transmission. The data were obtained from February 2020 to April 2021. Spatio-temporal kriging was used in order to predict LST in some days in which no image was recorded by the satellite. The validity of the predicted values was assessed by Bland-Altman technique. The impact of the predictors was analyzed by Distributed Lag Non-linear Model (DLNM). In addition to main effect of temperature, its linear as well as non-linear interaction effect with relative humidity were considered using Generalized Additive Model (GAM) and a bivariate response surface model. Sensitivity analyses were done to select models’ parameters, autocorrelation model and function of associations. Results The dose-response curve revealed that the impact of both predictors was not obvious, though, the risk of transmission tended to be positive due to low values of temperatures. Although the linear interaction effect was not statistically significant, but joint patterns showed that the impact of both LST and AT tended to be different when humidity values were changed. Conclusion However the findings suggested that both LST and AT were not statistically important predictors, but they tended to predict the Covid-19 transmission in some lags. Because of local based evidence, the wide confidence intervals and then non-significant values should be cautiously interpreted.
Environmental Science and Pollution Research, 2021
Background: This study aimed to estimate hospitalization risk/number attributed to air extreme te... more Background: This study aimed to estimate hospitalization risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. Methods: A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using one-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. Results: The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. Conclusion: This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.
Introduction: The present study was conducted to compare the added effect of heat waves on mortal... more Introduction: The present study was conducted to compare the added effect of heat waves on mortality and years of life lost in Kerman, Iran during the years 2005-2016.Methods: Daily mean temperatur...
This study provides evidence, showing the effect of climate change on mortality while taking acco... more This study provides evidence, showing the effect of climate change on mortality while taking account of adaptation. • The models showed that mean temperature will rise up to 1°C by 2050 in all scenarios in Kerman. • Heat-related mortality will rise in the future, while cold related mortality might slightly decrease. • There was a big uncertainty in coldrelated deaths.
The association between heat or heat waves and mortality should often be reported in a way that m... more The association between heat or heat waves and mortality should often be reported in a way that makes it sensible by health policymakers. In this study we aimed to assess the effect of heat and heat waves on mortality using attributable risks during 2005-2017. Nine heat waves were defined using a combination of severity and duration of mean daily temperature. Heat wave effects were assessed using added and main effects. Added effects were assessed as a binary variable and main effects were assessed by comparing the median temperature (in heat wave days) to Minimum Mortality Temperature (MMT). The effects of heat, mild heat and extreme heat on mortality were also assessed. Distributed Lag Nonlinear Models were used to assess the relations in a bi-dimensional perspective in which the quadratic b-spline was chosen as the basis function for the dimension of the exposure and the natural cubic b-spline was chosen for lag dimension. The backward perspective was used to estimate the attributable risks. The total mortality attributed to non-optimal temperatures for all days was 1.91% (CI 95%:-6.36, 8.47). The attributable risks (AR) were 2.23%, 2.02% and 0.25% for heat, mild heat and extreme heat days, respectively. AR was more for females and the above 65 years old groups than other groups in heat, mild heat and extreme heat days. While the stronger heat waves defined based on temperature above the 95 and 98 th percentile had a significant attributable risk for total mortality in the added effects; the weaker heat waves (defined based on temperature above of the 90 th percentile (HW1, HW2, HW3) had higher attributable risks, significant for HW1 and HW2,in the main effects. Apparently weaker heat waves show more immediate effects, while stronger heat waves increase mortality over several days.
The present study was conducted to compare the impact of heat waves on mortality and years of lif... more The present study was conducted to compare the impact of heat waves on mortality and years of life lost (YLL) in Kerman, Iran during the years 2005-2017. Daily mean temperature in a combination of intensity and duration were used in order to define heat waves (90, 95, and 98th percentile and ≥ 2, 3, and 4 consecutive days). YLL was calculated according to Iran's life table and by considering the discount rate. In order to investigate the impact of heat waves in different lags and its cumulative effect on mortality and YLL, Poisson and linear models within distributed lag nonlinear models were used respectively. A maximum lag of 14 days was considered. The best model was selected based on AIC (Akaike Information Criteria). The model was adjusted for air pollutants, public holidays, days of the week, and humidity. The average daily mortality and YLL were 10.54 ± 4.31 deaths and 175.58 ± 91.39 years respectively. They were higher in men and in heat waves matching a definition of above the 98th temperature percentile and ≥ 3 days, than others. Except heat waves defined as the 98th percentile and ≥ 4 days, the impact of heat waves on mortality and YLL were the highest at lag 0. The cumulative relative risk of total mortality was significantly higher in heat waves above the 95 and 98th percentiles. The cumulative effect of heat waves on total YLL was significantly higher only above the 98th percentile. Men over 65 years old were the most vulnerable and had the highest mortality and YLL. Heat waves with temperatures above the 98th percentile that lasted at least 2 or 3 consecutive days had a significant effect in increasing both total YLL and mortality in Kerman, Iran.
Background: This study aimed to estimate hospitalization risk/number attributed to air extreme te... more Background: This study aimed to estimate hospitalization risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019.Methods: A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using one-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity.Results: The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cum...
➢ Lime can be considered a cost-effective alternative to KOH in hydrothermal humification. ➢ Lime... more ➢ Lime can be considered a cost-effective alternative to KOH in hydrothermal humification. ➢ Lime could significantly reduce aromatics while increasing sugars and acids. ➢ Wet biomass outperformed dry biomass in the process, reducing the need for pre-drying. ➢ A 0.01% addition of hydrothermal humification products notably enhanced plant growth. ➢ Hydrothermal liquid products showed no toxicity in Daphnia magna bioassays.
Occupational Diseases and Environmental Medicine, 2018
Background: External causes include accidents, injuries or health problems that arise immediately... more Background: External causes include accidents, injuries or health problems that arise immediately after accidents or other external factors. The purpose of this review was to collect information about the relation between temperature and mortality due to external causes. Methods: A systematic search of articles was conducted in PubMed, Scopus, Science Direct, Embase, and Web of Science until January 2017, with no restriction. Broad searches were conducted in all fields, using key words related to ambient temperature exposure and deaths due to external causes. Results: Nine articles were included in the study. Except two articles, one of which had been designed in a cross-sectional way and the other that was retrospective, the rest of the articles were ecological. The outcomes reported were heterogeneous and different metrics had been used in the results; therefore conducting of meta-analysis was not possible. Five articles had found direct and significant relations between high temperature and deaths due to external causes. Only one study found no relation. In the case of cold, one study showed that the proportion of death due to external causes was low during cold waves. Another study showed that there was no relation between cold waves and mortality due to external causes. But one article showed that death due to external causes increased on cold days, significantly. Conclusion: The results of this systematic review showed that high temperatures (heat) were more likely to cause mortality due to external causes than low temperatures (cold). Due to the small number of studies in this field, especially in the context of cold and death due to external causes, it is difficult to make robust conclusions.
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Background The SARS-CoV-2 virus pandemic is primarily transmitted by direct contact between infec... more Background The SARS-CoV-2 virus pandemic is primarily transmitted by direct contact between infected and uninfected people, though, there are still many unknown factors influencing the survival and transmission of the virus. Air temperature is one of the main susceptible factors. This study aimed to explore the impact of air and land surface temperatures on Covid-19 transmission in a region of Iran. Method Daily Land Surface Temperature (LST) measured by satellite and Air Temperature measured by weather station were used as the predictors of Covid-19 transmission. The data were obtained from February 2020 to April 2021. Spatio-temporal kriging was used in order to predict LST in some days in which no image was recorded by the satellite. The validity of the predicted values was assessed by Bland-Altman technique. The impact of the predictors was analyzed by Distributed Lag Non-linear Model (DLNM). In addition to main effect of temperature, its linear as well as non-linear interaction effect with relative humidity were considered using Generalized Additive Model (GAM) and a bivariate response surface model. Sensitivity analyses were done to select models’ parameters, autocorrelation model and function of associations. Results The dose-response curve revealed that the impact of both predictors was not obvious, though, the risk of transmission tended to be positive due to low values of temperatures. Although the linear interaction effect was not statistically significant, but joint patterns showed that the impact of both LST and AT tended to be different when humidity values were changed. Conclusion However the findings suggested that both LST and AT were not statistically important predictors, but they tended to predict the Covid-19 transmission in some lags. Because of local based evidence, the wide confidence intervals and then non-significant values should be cautiously interpreted.
Environmental Science and Pollution Research, 2021
Background: This study aimed to estimate hospitalization risk/number attributed to air extreme te... more Background: This study aimed to estimate hospitalization risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. Methods: A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using one-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. Results: The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. Conclusion: This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.
Introduction: The present study was conducted to compare the added effect of heat waves on mortal... more Introduction: The present study was conducted to compare the added effect of heat waves on mortality and years of life lost in Kerman, Iran during the years 2005-2016.Methods: Daily mean temperatur...
This study provides evidence, showing the effect of climate change on mortality while taking acco... more This study provides evidence, showing the effect of climate change on mortality while taking account of adaptation. • The models showed that mean temperature will rise up to 1°C by 2050 in all scenarios in Kerman. • Heat-related mortality will rise in the future, while cold related mortality might slightly decrease. • There was a big uncertainty in coldrelated deaths.
The association between heat or heat waves and mortality should often be reported in a way that m... more The association between heat or heat waves and mortality should often be reported in a way that makes it sensible by health policymakers. In this study we aimed to assess the effect of heat and heat waves on mortality using attributable risks during 2005-2017. Nine heat waves were defined using a combination of severity and duration of mean daily temperature. Heat wave effects were assessed using added and main effects. Added effects were assessed as a binary variable and main effects were assessed by comparing the median temperature (in heat wave days) to Minimum Mortality Temperature (MMT). The effects of heat, mild heat and extreme heat on mortality were also assessed. Distributed Lag Nonlinear Models were used to assess the relations in a bi-dimensional perspective in which the quadratic b-spline was chosen as the basis function for the dimension of the exposure and the natural cubic b-spline was chosen for lag dimension. The backward perspective was used to estimate the attributable risks. The total mortality attributed to non-optimal temperatures for all days was 1.91% (CI 95%:-6.36, 8.47). The attributable risks (AR) were 2.23%, 2.02% and 0.25% for heat, mild heat and extreme heat days, respectively. AR was more for females and the above 65 years old groups than other groups in heat, mild heat and extreme heat days. While the stronger heat waves defined based on temperature above the 95 and 98 th percentile had a significant attributable risk for total mortality in the added effects; the weaker heat waves (defined based on temperature above of the 90 th percentile (HW1, HW2, HW3) had higher attributable risks, significant for HW1 and HW2,in the main effects. Apparently weaker heat waves show more immediate effects, while stronger heat waves increase mortality over several days.
The present study was conducted to compare the impact of heat waves on mortality and years of lif... more The present study was conducted to compare the impact of heat waves on mortality and years of life lost (YLL) in Kerman, Iran during the years 2005-2017. Daily mean temperature in a combination of intensity and duration were used in order to define heat waves (90, 95, and 98th percentile and ≥ 2, 3, and 4 consecutive days). YLL was calculated according to Iran's life table and by considering the discount rate. In order to investigate the impact of heat waves in different lags and its cumulative effect on mortality and YLL, Poisson and linear models within distributed lag nonlinear models were used respectively. A maximum lag of 14 days was considered. The best model was selected based on AIC (Akaike Information Criteria). The model was adjusted for air pollutants, public holidays, days of the week, and humidity. The average daily mortality and YLL were 10.54 ± 4.31 deaths and 175.58 ± 91.39 years respectively. They were higher in men and in heat waves matching a definition of above the 98th temperature percentile and ≥ 3 days, than others. Except heat waves defined as the 98th percentile and ≥ 4 days, the impact of heat waves on mortality and YLL were the highest at lag 0. The cumulative relative risk of total mortality was significantly higher in heat waves above the 95 and 98th percentiles. The cumulative effect of heat waves on total YLL was significantly higher only above the 98th percentile. Men over 65 years old were the most vulnerable and had the highest mortality and YLL. Heat waves with temperatures above the 98th percentile that lasted at least 2 or 3 consecutive days had a significant effect in increasing both total YLL and mortality in Kerman, Iran.
Background: This study aimed to estimate hospitalization risk/number attributed to air extreme te... more Background: This study aimed to estimate hospitalization risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019.Methods: A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using one-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity.Results: The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cum...
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