6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
Dan Miller, an engineer and venture capitalist focused on non-polluting energy technologies, blogs on climate at ClimatePlace.org and helped NASA climate scientist James E. Hansen prepare his recent New York Times Op-Ed article, “Game Over for the Climate.” Miller complained about the Dot Earth post in which the climate scientists Martin Hoerling and Kerry Emanuel separately criticized aspects of Hansen’s piece and was offered a chance to write the following “Your Dot” post.
The document summarizes Martin P. Hoerling's response to criticisms of claims made in a New York Times Op-Ed by James E. Hansen regarding the impacts of climate change. Hoerling takes issue with several specific assertions made by Hansen, arguing they are contrary to peer-reviewed literature and climate change assessments. He provides analysis and references to studies to support his counterarguments. The overall summary is that the certainty expressed in Hansen's claims is not supported by the current scientific understanding of regional climate change projections and uncertainties.
- The document analyzes the extremist view on climate change and finds little scientific basis for its key claims, such as a temperature increase greater than 3°C by 2100, a significant chance of large sea level rise from melting ice sheets, and an already increased occurrence of extreme weather events due to global warming.
- Most evidence supports only modest global warming around 1°C over the past century from human greenhouse gas emissions, lower than the projections of climate models. Natural factors like ocean cycles and solar activity have also influenced temperatures.
Bruinede bruinetal floodrisk_25feb2014_submitted_revised_30july2014_inpresssuzi smith
The IPCC reports that climate change will pose increased risks of heatwaves and flooding. Although survey-based studies have examined links between public perceptions of hot weather and climate change beliefs, relatively little is known about people’s perceptions of changes in flood risks, the extent to which climate change is perceived to contribute to changes in flood risks, or how such perceptions vary by political affiliation. We discuss findings from a survey of long-time residents of Pittsburgh, Pennsylvania (US), a region that has experienced regular flooding. Our participants perceived local flood risks as having increased and expected further increase in the future; expected higher future flood risks if they believed more in the contribution of climate change; interpreted projections of future increases in flooding as evidence for climate change; and perceived similar increases in flood risks independent of their political affiliation despite disagreeing about climate change. Overall, these findings suggest that communications about climate change adaptation will be more effective if they focus more on protection against local flood risks, especially when targeting audiences of potential climate sceptics.
This document discusses climate and the potential impacts of climate change on human health and agriculture. It defines climate and differentiates it from weather. It then describes the various natural and human-caused factors that can influence climate on both short and long timescales. The document outlines several ways climate change may negatively impact human health, such as through increased heat waves, extreme weather events, changes in air quality, and shifting patterns of climate-sensitive diseases. It also discusses some of the uncertainties around how climate change will precisely affect agriculture and considers various climate factors that could influence crop yields.
Climate Change: Addressing the Major Skeptic ArgumentsAlexander Ainslie
This document addresses major claims made by climate change skeptics in three categories: that Earth is not warming, that human activity is not responsible for warming, and that action is not needed even if warming is occurring. It summarizes the response to key skeptic arguments, finding that the evidence supports conclusions that Earth is warming due to human greenhouse gas emissions and impacts will be serious without emission reductions. Periods of stable temperatures do not disprove warming, and research has found no evidence of conspiracies among scientists. While imperfect, climate models provide reliable guidance when considered alongside observations and theory. The document provides a balanced and thorough examination of issues in the climate change debate.
Factors of climate extremes hyperactivity: a study on MENAPremier Publishers
It is hard to say that all climate events are entirely related to global warming. In this regard, models usually used for global warming predictions are not appropriate for some of climate trends. For instance, prolonged drought in MENA region could not be analyses by global warming predictions. It seems the climate condition in this region is better understood by using the new concept “climate hyperactivity” rather than using the usual global warming predictions. Drought in MENA region is different with other precipitation and temperature rates throughout the world. On one hand, MENA drought is not nonlinear and is not a sudden climate change. On the other hand, there is no sign of reversibility or temporality of climate change in MENA; therefore it is not a macro-climate change either. In fact, MENA drought is a type of hyperactivity of normal behavior of climate factors which leads to a new normal climate in the region. According to Paleo-climate studies, in previous millennia, some kinds of similar climate hyperactivity has led the region to a drier and hotter climate. Rather than focusing on epistemology of climate change, this article compares MENA’s drought with the dominant paradigm of climate change which is concentrated on global warming and greenhouse effect. According to climate factors, the region’s climate change is more effected by natural and climate factors than greenhouse effects.
Dan Miller, an engineer and venture capitalist focused on non-polluting energy technologies, blogs on climate at ClimatePlace.org and helped NASA climate scientist James E. Hansen prepare his recent New York Times Op-Ed article, “Game Over for the Climate.” Miller complained about the Dot Earth post in which the climate scientists Martin Hoerling and Kerry Emanuel separately criticized aspects of Hansen’s piece and was offered a chance to write the following “Your Dot” post.
The document summarizes Martin P. Hoerling's response to criticisms of claims made in a New York Times Op-Ed by James E. Hansen regarding the impacts of climate change. Hoerling takes issue with several specific assertions made by Hansen, arguing they are contrary to peer-reviewed literature and climate change assessments. He provides analysis and references to studies to support his counterarguments. The overall summary is that the certainty expressed in Hansen's claims is not supported by the current scientific understanding of regional climate change projections and uncertainties.
- The document analyzes the extremist view on climate change and finds little scientific basis for its key claims, such as a temperature increase greater than 3°C by 2100, a significant chance of large sea level rise from melting ice sheets, and an already increased occurrence of extreme weather events due to global warming.
- Most evidence supports only modest global warming around 1°C over the past century from human greenhouse gas emissions, lower than the projections of climate models. Natural factors like ocean cycles and solar activity have also influenced temperatures.
Bruinede bruinetal floodrisk_25feb2014_submitted_revised_30july2014_inpresssuzi smith
The IPCC reports that climate change will pose increased risks of heatwaves and flooding. Although survey-based studies have examined links between public perceptions of hot weather and climate change beliefs, relatively little is known about people’s perceptions of changes in flood risks, the extent to which climate change is perceived to contribute to changes in flood risks, or how such perceptions vary by political affiliation. We discuss findings from a survey of long-time residents of Pittsburgh, Pennsylvania (US), a region that has experienced regular flooding. Our participants perceived local flood risks as having increased and expected further increase in the future; expected higher future flood risks if they believed more in the contribution of climate change; interpreted projections of future increases in flooding as evidence for climate change; and perceived similar increases in flood risks independent of their political affiliation despite disagreeing about climate change. Overall, these findings suggest that communications about climate change adaptation will be more effective if they focus more on protection against local flood risks, especially when targeting audiences of potential climate sceptics.
This document discusses climate and the potential impacts of climate change on human health and agriculture. It defines climate and differentiates it from weather. It then describes the various natural and human-caused factors that can influence climate on both short and long timescales. The document outlines several ways climate change may negatively impact human health, such as through increased heat waves, extreme weather events, changes in air quality, and shifting patterns of climate-sensitive diseases. It also discusses some of the uncertainties around how climate change will precisely affect agriculture and considers various climate factors that could influence crop yields.
Climate Change: Addressing the Major Skeptic ArgumentsAlexander Ainslie
This document addresses major claims made by climate change skeptics in three categories: that Earth is not warming, that human activity is not responsible for warming, and that action is not needed even if warming is occurring. It summarizes the response to key skeptic arguments, finding that the evidence supports conclusions that Earth is warming due to human greenhouse gas emissions and impacts will be serious without emission reductions. Periods of stable temperatures do not disprove warming, and research has found no evidence of conspiracies among scientists. While imperfect, climate models provide reliable guidance when considered alongside observations and theory. The document provides a balanced and thorough examination of issues in the climate change debate.
Factors of climate extremes hyperactivity: a study on MENAPremier Publishers
It is hard to say that all climate events are entirely related to global warming. In this regard, models usually used for global warming predictions are not appropriate for some of climate trends. For instance, prolonged drought in MENA region could not be analyses by global warming predictions. It seems the climate condition in this region is better understood by using the new concept “climate hyperactivity” rather than using the usual global warming predictions. Drought in MENA region is different with other precipitation and temperature rates throughout the world. On one hand, MENA drought is not nonlinear and is not a sudden climate change. On the other hand, there is no sign of reversibility or temporality of climate change in MENA; therefore it is not a macro-climate change either. In fact, MENA drought is a type of hyperactivity of normal behavior of climate factors which leads to a new normal climate in the region. According to Paleo-climate studies, in previous millennia, some kinds of similar climate hyperactivity has led the region to a drier and hotter climate. Rather than focusing on epistemology of climate change, this article compares MENA’s drought with the dominant paradigm of climate change which is concentrated on global warming and greenhouse effect. According to climate factors, the region’s climate change is more effected by natural and climate factors than greenhouse effects.
This policy brief examines temperature-related health impacts in the United States. It discusses how temperature variations can cause health issues like heat-related illnesses and mortality. Certain populations, like those in urban areas, are more vulnerable. The brief recommends a holistic approach to address this issue through disaster management planning that integrates health systems. It also emphasizes stakeholder involvement, infrastructure improvements, and public preparedness. Temperature changes significantly impact health care delivery systems by increasing heat-related sickness and healthcare costs. Preventive actions are needed year-round to reduce burdens on public health.
Temperature Changes of Niğde Province in Turkey: Trend analysis of 50 years dataPremier Publishers
This research was carried out in center of Niğde province and Ulukışla district in Turkey. In the study, monthly minimum, maximum and average temperature data between 1970-2019 were evaluated. In the research, Sperman’s Rho and Mann-Kendall correlation tests and Sen’s slope method were applied to temperature data. According to the results of the research, it has been observed that the average minimum temperature for many years was -1,2 °C in center of Niğde province and -2,9 °C in Ulukışla district. Average temperature values were found as 12,8 °C in Center of Niğde and 9,8 °C in Ulukışla district. The average of maximum temperature was found to be 24,5 °C in Niğde Center and 23,1 °C in Ulukışla district. A significant increase was observed in the spring, summer and autumn seasons in center of Niğde and Ulukışla district at minimum temperature values. When the average temperature trends were analyzed, it was determined that there was a significant increase in center of Niğde for every season. A significant increase in summer, autumn and winter seasons was observed in Ulukışla district. It had been determined that there was a significant increase in the maximum temperatures in each district in every season.
This is the fifth lesson taught under the course - Climate Change and Global Environment at the Faculty of Social Sciences and Humanities, Rajarata University of Sri Lanka
Global climate change has far-reaching effects on natural ecosystem and socio-economic system, and it is a hot issue that the governments and the scientific community as well as the general public pay attention to today. Meanwhile, climate change has strong regional characteristics. In the global context of climate warming, the climate change trends and intensity is not entirely consistent. Therefore, strengthening small regional climate change research plays an extremely important role on local agricultural production, livelihood and disaster prevention. On the basis of the monthly average temperature series in Guyuan meteorological station from 1957 to 2011, the temperature trends were analyzed with Mann-Kendall test and Pettitt jump test. The result with linear regression analysis showed that the annual average temperature in Guyuan City is in an increasing trend, and the average increase rate is 0.3071℃/10a. The annual highest temperature, the annual lowest temperature, and the annual average temperature in Guyuan City showed an upward trend with Mann-Kendall test. The biggest change is the annual lowest temperature, and the change rate is 0.60 ℃/10a, and then is the annual average temperature and annual highest temperature. Pettitt jump test results showed that the annual lowest temperature in Guyuan City changed in the earliest year before 1984. The annual average temperature and annual highest temperature changed nearly the year of 1993. Multiple regression analysis showed that changes of temperature in Guyuan City mainly occurred after the 1980s, and there is a significant upward trend into the 21st, which is in accordance with Pettitt jump test results.
Global warming &climate changesGlobal temperature measurements remote from human habitation and activity show no evidence of a warming during the last century. Such sites include “proxy” measurements such as tree rings, marine sediments and ice cores, weather balloons and satellite measurements in the lower atmosphere, and many surface sites where human influence is minimal.
Heat-Related Illness in the US - A Socioeconomic AnalysisJimmyJohn46
As effects of climate-change become more tangible, it is apparent that environmental issues were never divorced from socioeconomic issues. We attempted to understand any socioeconomic disparities in distribution of heat-related illnesses (HRI) in the US by looking at CDC data at the county level across the US for HRI deaths and looking at correlations across a diverse array of potential variables spanning economic, demographic, environmental, land-use and regional/geographical profile categories (data retrieved from US Census Bureau and CDC’s NEPHT databases). SQL and Python were utilized for data ingestion, processing, analysis, and visualization.
This document contains 6 abstracts from epidemiology conferences that discuss various topics related to climate change and environmental health. The abstracts report on research related to heat-related mortality and heat warning systems in the US, mortality related to temperature extremes, the impact of diurnal temperature range on cardiovascular hospital admissions, defining temperature thresholds for heat warning systems in France, the effects of heatwaves on health outcomes in Adelaide, Australia, and projecting temperature-related mortality impacts in New York City under climate change.
Spatial and temporal distribution of urban heat islandsShrabantiDutta
This study examines urban heat islands in Vila Velha, Brazil using Landsat 5 Thematic Mapper imagery from 2008-2011. The methodology uses a mono-window algorithm to calculate land surface temperature and determine its spatial and temporal distribution. Results show higher temperatures in densely urbanized areas of the city, with extreme heat occurring in different seasons annually. A correlation analysis finds higher temperatures correlated with increased built surfaces and lower temperatures correlated with vegetation. An urban thermal field variance index is used to assess ecological impacts, finding urban areas indicate worse conditions while green spaces show excellent conditions. The methods aim to better distribute urban and green spaces to mitigate urban heat island effects.
This presentation discusses the relationship between extreme weather events and human health in a changing climate. It summarizes research analyzing heat wave events and their relationship to mortality rates in the United States. The presentation finds that the number of heat waves has increased in recent decades, especially in the Southeast, and that the duration and intensity of events has also risen. It explores using climate and health data to better understand how changes in extreme temperatures relate to changes in mortality rates. The goal is to publish results and provide information to public health organizations to help prepare for health impacts of climate change.
Impact of three decades of energy efficiency interventions in public housing ...sophieproject
Impact of three decades of energy efficiency interventions in public housing buildings on cold-related mortality: a case-crossover analysis, by Andrés Peralta, Lluís Camprubí, Maica Rodríguez-Sanz, Xavier Basagaña, Carme Borrell, Marc Marí-Dell’Olmo. Communication presented at the 4th International City Health Conference 2015, in Barcelona. 6th November 2015.
This is the last circulated draft of the "Summary for Policy Makers" of the Physical Science section of the fifth report from the Intergovernmental Panel on Climate Change. It's useful to have on hand to compare and contrast with what emerges in Stockholm on 27 September. The IPCC site is http://ipcc.ch
Here's a Dot Earth reader on IPCC history and new steps: http://j.mp/ipcchist
Here's the full text of my (short and simple) 1992 book on global warming, which describes the early days of the panel:
Views of Global Warming in 1992 and Now http://nyti.ms/TZH98r
health can be affected by many factors.These may be in terms of environment and also internal body changes depending on climate.It is discussed in details on these slides the main factors that attribute to the health problems.Countries vary differently in terms of number of people contracting diseases due to different physical,social and psychological effects.
An introduction to Biometeorology and its application in regards to asthma. It includes also, future ideas to be implemented along this line. Three consecutive years of asthma information and weather information are correlated together in order to find possible indicators to define an asthma index.
Analysis of Trend and Variability of Temperature in Ebonyi State, South-easte...Agriculture Journal IJOEAR
— Temperature being one of the indicators of climate change has become one of the most important discussions of recent times. Changes in temperature influence a variety of processes directly or indirectly which cut across every aspect of man existences. This paper therefore examined the trend in temperature as tools of climate change over Ebonyi State, SouthEastern Nigeria, which is an area well known for crop agriculture. Temperature data covering a period of 31 years (1984-2015) were collected and analyzed using mean, moving average, standard deviation coefficient of variation and linear regression. Result revealed that there is a positive trend in temperature over the study period and that the area is getting warmer by 0.0037 o c annually, which is an Indication that Ebonyi State is experiencing a rise in air surface temperature. Since most of the inhabitants are dependent on economic activities that are temperature sensitive like farming, the study therefore recommends that measures should be taken by all stakeholders including the government, individuals and cooperate bodies to take the issue of climate variability serious in the study area in order to mitigate its impact in the long run.
The document summarizes research on the impacts of climate change on human health. It finds that climate change has already contributed to increased deaths from heatwaves, cardiovascular disease and respiratory illness. Infectious diseases are also strongly influenced by climate fluctuations, as changes in temperature can alter transmission of diseases like malaria, dengue fever, and hantavirus. Future projections suggest vulnerable regions may experience disproportionate warming and increased health risks from climate change impacts like flooding, drought and extreme weather events.
There is scientific consensus that rising greenhouse gas emissions from human activity will cause global warming and other climate changes. The IPCC projects an increase in average global temperatures by 2100 of 1.4-5.8°C. Climate change will affect human health in many ways, both beneficial and adverse. Research has focused on impacts of extreme heat, infectious diseases, and food security, but climate change may also disrupt societies and economies in ways that indirectly impact health. While some effects are already apparent, such as heat waves increasing mortality, estimating future health impacts involves uncertainty. Evidence of health risks will strengthen arguments for policies to reduce emissions and adapt to climate change impacts.
Workshop held on 1st of April in Vientnane, Laos. Participants from national institurions (agriculture, education, planning) where joining presentations on the overview of climate variability in the Greater Mekong Sub-Region, using crop modeling and land use change analysis.
Effects of Air Pollution on Infant and Children Respiratory Mortality in Four...Kinza Irshad
This study examined the effects of air pollution on infant and child respiratory mortality in four large Latin American cities: Mexico City, Santiago, Chile, Sao Paulo, and Rio de Janeiro, Brazil. Daily counts of respiratory deaths among infants and children were analyzed in relation to particulate matter (PM10) and ozone (O3) levels using statistical models. The results found small increases in risk of respiratory mortality among infants and children associated with higher PM10 and O3 levels, with the strongest effects seen for lower respiratory infections among infants. The study adds to evidence that air pollution exposure can negatively impact children's respiratory health.
This presentation created and addressed by Omar Bellprat (IC3 Barcelona) in the intensive three day course from the BC3, Basque Centre for Climate Change and UPV/EHU (University of the Basque Country) on Climate Change in the Uda Ikastaroak Framework.
The objective of the BC3 Summer School is to offer an updated and multidisciplinary view of the ongoing trends in climate change research. The BC3 Summer School is organized in collaboration with the University of the Basque Country and is a high quality and excellent summer course gathering leading experts in the field and students from top universities and research centres worldwide.
Most methods of ‘climate’ attribution based on analysis of weather-health associations: episode analysis, time-series, seasonality, inter-annual variations
Relevance to climate change limited by uncertainties over multiple effect-modifiers – changes in vulnerability of population & health
Modelling intrinsic to assessment of likely future burdens & the effect of adaptation options, but entails many uncertainties
This policy brief examines temperature-related health impacts in the United States. It discusses how temperature variations can cause health issues like heat-related illnesses and mortality. Certain populations, like those in urban areas, are more vulnerable. The brief recommends a holistic approach to address this issue through disaster management planning that integrates health systems. It also emphasizes stakeholder involvement, infrastructure improvements, and public preparedness. Temperature changes significantly impact health care delivery systems by increasing heat-related sickness and healthcare costs. Preventive actions are needed year-round to reduce burdens on public health.
Temperature Changes of Niğde Province in Turkey: Trend analysis of 50 years dataPremier Publishers
This research was carried out in center of Niğde province and Ulukışla district in Turkey. In the study, monthly minimum, maximum and average temperature data between 1970-2019 were evaluated. In the research, Sperman’s Rho and Mann-Kendall correlation tests and Sen’s slope method were applied to temperature data. According to the results of the research, it has been observed that the average minimum temperature for many years was -1,2 °C in center of Niğde province and -2,9 °C in Ulukışla district. Average temperature values were found as 12,8 °C in Center of Niğde and 9,8 °C in Ulukışla district. The average of maximum temperature was found to be 24,5 °C in Niğde Center and 23,1 °C in Ulukışla district. A significant increase was observed in the spring, summer and autumn seasons in center of Niğde and Ulukışla district at minimum temperature values. When the average temperature trends were analyzed, it was determined that there was a significant increase in center of Niğde for every season. A significant increase in summer, autumn and winter seasons was observed in Ulukışla district. It had been determined that there was a significant increase in the maximum temperatures in each district in every season.
This is the fifth lesson taught under the course - Climate Change and Global Environment at the Faculty of Social Sciences and Humanities, Rajarata University of Sri Lanka
Global climate change has far-reaching effects on natural ecosystem and socio-economic system, and it is a hot issue that the governments and the scientific community as well as the general public pay attention to today. Meanwhile, climate change has strong regional characteristics. In the global context of climate warming, the climate change trends and intensity is not entirely consistent. Therefore, strengthening small regional climate change research plays an extremely important role on local agricultural production, livelihood and disaster prevention. On the basis of the monthly average temperature series in Guyuan meteorological station from 1957 to 2011, the temperature trends were analyzed with Mann-Kendall test and Pettitt jump test. The result with linear regression analysis showed that the annual average temperature in Guyuan City is in an increasing trend, and the average increase rate is 0.3071℃/10a. The annual highest temperature, the annual lowest temperature, and the annual average temperature in Guyuan City showed an upward trend with Mann-Kendall test. The biggest change is the annual lowest temperature, and the change rate is 0.60 ℃/10a, and then is the annual average temperature and annual highest temperature. Pettitt jump test results showed that the annual lowest temperature in Guyuan City changed in the earliest year before 1984. The annual average temperature and annual highest temperature changed nearly the year of 1993. Multiple regression analysis showed that changes of temperature in Guyuan City mainly occurred after the 1980s, and there is a significant upward trend into the 21st, which is in accordance with Pettitt jump test results.
Global warming &climate changesGlobal temperature measurements remote from human habitation and activity show no evidence of a warming during the last century. Such sites include “proxy” measurements such as tree rings, marine sediments and ice cores, weather balloons and satellite measurements in the lower atmosphere, and many surface sites where human influence is minimal.
Heat-Related Illness in the US - A Socioeconomic AnalysisJimmyJohn46
As effects of climate-change become more tangible, it is apparent that environmental issues were never divorced from socioeconomic issues. We attempted to understand any socioeconomic disparities in distribution of heat-related illnesses (HRI) in the US by looking at CDC data at the county level across the US for HRI deaths and looking at correlations across a diverse array of potential variables spanning economic, demographic, environmental, land-use and regional/geographical profile categories (data retrieved from US Census Bureau and CDC’s NEPHT databases). SQL and Python were utilized for data ingestion, processing, analysis, and visualization.
This document contains 6 abstracts from epidemiology conferences that discuss various topics related to climate change and environmental health. The abstracts report on research related to heat-related mortality and heat warning systems in the US, mortality related to temperature extremes, the impact of diurnal temperature range on cardiovascular hospital admissions, defining temperature thresholds for heat warning systems in France, the effects of heatwaves on health outcomes in Adelaide, Australia, and projecting temperature-related mortality impacts in New York City under climate change.
Spatial and temporal distribution of urban heat islandsShrabantiDutta
This study examines urban heat islands in Vila Velha, Brazil using Landsat 5 Thematic Mapper imagery from 2008-2011. The methodology uses a mono-window algorithm to calculate land surface temperature and determine its spatial and temporal distribution. Results show higher temperatures in densely urbanized areas of the city, with extreme heat occurring in different seasons annually. A correlation analysis finds higher temperatures correlated with increased built surfaces and lower temperatures correlated with vegetation. An urban thermal field variance index is used to assess ecological impacts, finding urban areas indicate worse conditions while green spaces show excellent conditions. The methods aim to better distribute urban and green spaces to mitigate urban heat island effects.
This presentation discusses the relationship between extreme weather events and human health in a changing climate. It summarizes research analyzing heat wave events and their relationship to mortality rates in the United States. The presentation finds that the number of heat waves has increased in recent decades, especially in the Southeast, and that the duration and intensity of events has also risen. It explores using climate and health data to better understand how changes in extreme temperatures relate to changes in mortality rates. The goal is to publish results and provide information to public health organizations to help prepare for health impacts of climate change.
Impact of three decades of energy efficiency interventions in public housing ...sophieproject
Impact of three decades of energy efficiency interventions in public housing buildings on cold-related mortality: a case-crossover analysis, by Andrés Peralta, Lluís Camprubí, Maica Rodríguez-Sanz, Xavier Basagaña, Carme Borrell, Marc Marí-Dell’Olmo. Communication presented at the 4th International City Health Conference 2015, in Barcelona. 6th November 2015.
This is the last circulated draft of the "Summary for Policy Makers" of the Physical Science section of the fifth report from the Intergovernmental Panel on Climate Change. It's useful to have on hand to compare and contrast with what emerges in Stockholm on 27 September. The IPCC site is http://ipcc.ch
Here's a Dot Earth reader on IPCC history and new steps: http://j.mp/ipcchist
Here's the full text of my (short and simple) 1992 book on global warming, which describes the early days of the panel:
Views of Global Warming in 1992 and Now http://nyti.ms/TZH98r
health can be affected by many factors.These may be in terms of environment and also internal body changes depending on climate.It is discussed in details on these slides the main factors that attribute to the health problems.Countries vary differently in terms of number of people contracting diseases due to different physical,social and psychological effects.
An introduction to Biometeorology and its application in regards to asthma. It includes also, future ideas to be implemented along this line. Three consecutive years of asthma information and weather information are correlated together in order to find possible indicators to define an asthma index.
Analysis of Trend and Variability of Temperature in Ebonyi State, South-easte...Agriculture Journal IJOEAR
— Temperature being one of the indicators of climate change has become one of the most important discussions of recent times. Changes in temperature influence a variety of processes directly or indirectly which cut across every aspect of man existences. This paper therefore examined the trend in temperature as tools of climate change over Ebonyi State, SouthEastern Nigeria, which is an area well known for crop agriculture. Temperature data covering a period of 31 years (1984-2015) were collected and analyzed using mean, moving average, standard deviation coefficient of variation and linear regression. Result revealed that there is a positive trend in temperature over the study period and that the area is getting warmer by 0.0037 o c annually, which is an Indication that Ebonyi State is experiencing a rise in air surface temperature. Since most of the inhabitants are dependent on economic activities that are temperature sensitive like farming, the study therefore recommends that measures should be taken by all stakeholders including the government, individuals and cooperate bodies to take the issue of climate variability serious in the study area in order to mitigate its impact in the long run.
The document summarizes research on the impacts of climate change on human health. It finds that climate change has already contributed to increased deaths from heatwaves, cardiovascular disease and respiratory illness. Infectious diseases are also strongly influenced by climate fluctuations, as changes in temperature can alter transmission of diseases like malaria, dengue fever, and hantavirus. Future projections suggest vulnerable regions may experience disproportionate warming and increased health risks from climate change impacts like flooding, drought and extreme weather events.
There is scientific consensus that rising greenhouse gas emissions from human activity will cause global warming and other climate changes. The IPCC projects an increase in average global temperatures by 2100 of 1.4-5.8°C. Climate change will affect human health in many ways, both beneficial and adverse. Research has focused on impacts of extreme heat, infectious diseases, and food security, but climate change may also disrupt societies and economies in ways that indirectly impact health. While some effects are already apparent, such as heat waves increasing mortality, estimating future health impacts involves uncertainty. Evidence of health risks will strengthen arguments for policies to reduce emissions and adapt to climate change impacts.
Workshop held on 1st of April in Vientnane, Laos. Participants from national institurions (agriculture, education, planning) where joining presentations on the overview of climate variability in the Greater Mekong Sub-Region, using crop modeling and land use change analysis.
Effects of Air Pollution on Infant and Children Respiratory Mortality in Four...Kinza Irshad
This study examined the effects of air pollution on infant and child respiratory mortality in four large Latin American cities: Mexico City, Santiago, Chile, Sao Paulo, and Rio de Janeiro, Brazil. Daily counts of respiratory deaths among infants and children were analyzed in relation to particulate matter (PM10) and ozone (O3) levels using statistical models. The results found small increases in risk of respiratory mortality among infants and children associated with higher PM10 and O3 levels, with the strongest effects seen for lower respiratory infections among infants. The study adds to evidence that air pollution exposure can negatively impact children's respiratory health.
This presentation created and addressed by Omar Bellprat (IC3 Barcelona) in the intensive three day course from the BC3, Basque Centre for Climate Change and UPV/EHU (University of the Basque Country) on Climate Change in the Uda Ikastaroak Framework.
The objective of the BC3 Summer School is to offer an updated and multidisciplinary view of the ongoing trends in climate change research. The BC3 Summer School is organized in collaboration with the University of the Basque Country and is a high quality and excellent summer course gathering leading experts in the field and students from top universities and research centres worldwide.
Most methods of ‘climate’ attribution based on analysis of weather-health associations: episode analysis, time-series, seasonality, inter-annual variations
Relevance to climate change limited by uncertainties over multiple effect-modifiers – changes in vulnerability of population & health
Modelling intrinsic to assessment of likely future burdens & the effect of adaptation options, but entails many uncertainties
Finding - Climate extremes and their impactsipcc-media
Climate extremes and their impacts were discussed. It was noted that a changing climate leads to changes in extreme weather events, both in terms of frequency and intensity. Extreme events interacting with vulnerable systems can lead to disasters. Various climate indices were presented to quantify extremes such as temperature and precipitation. Projections indicate increases in hot days and heavy precipitation. Managing risks requires understanding vulnerability and exposure as well as implementing measures like early warning systems, infrastructure improvements, and development policies. Adaptation requires addressing local conditions and involves both short-term risk reduction and long-term sustainable solutions.
Jason Thompson helped Dr. Oliver Hemmers communicate why climate models fail.
Biography
Dr. Oliver Hemmers received his Ph.D. in physics in 1993 from the Technical University in Berlin, Germany, with specialization in x-ray atomic and molecular spectroscopy. Recent research focuses on developments of biofuels and new materials for hydrogen fuel storage. He currently manages a multiyear, multimillion-dollar biodiesel project funded by the U.S. Department of Energy. Over the past 10 years, he has been a principal investigator or co-PI on several research projects at UNLV totaling more than $6 million. Hemmers has made approximately 200 presentations at national and international meetings, published approximately 90 research articles, written one book, and holds one patent. He is a member of the American Physical Society and a reviewer for the American Institute of Physics and the Institute of Physics.
Jason Thompson is an alternative energy photojournalist who wrote more than 300 articles in Diesel Power which around 2010 was the #1 selling automotive magazine at Walmart. He now studies the visual framing of climate control from 1824 to the present.
PROJECT OF THE TITLE PROPOSAL FINL FOR COFFEterefa1234
This document summarizes a study assessing the impact of climate change on crop yields in Bako Tibe Woreda, Ethiopia. Historical climate and crop yield data from 1989-2018 were analyzed. Temperature trends significantly increased while precipitation trends decreased insignificantly. Agricultural drought was analyzed using SPEI and occurred 4 times in the last 3 decades, covering 36% of the district. Crop yields of teff, wheat, barley and maize were significantly correlated with drought indices. The study shows increased temperature and precipitation variability have enhanced drought frequency and intensity, impacting selected crop yields. Improved agricultural technologies and short season crop varieties are needed to enhance farmer capacity.
This document provides an overview of basic epidemiological concepts including:
- Epidemiology is defined as the study of disease distribution and determinants in populations.
- Key measurements include incidence, prevalence, and rates. Incidence refers to new cases, prevalence refers to existing cases at a point in time, and rates provide a measure of frequency adjusted for population size.
- Direct standardization can be used to remove biases from age differences between populations when comparing mortality rates.
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A Comparative Study of the Mortality Risk of Extreme Temperature in Urban and Rural Areas of China An Analysis Based..., Chenzhi WANG
1. Chenzhi Wang
Nonlinear relationship
between extreme
temperature and
mortality across
mainland in China
----- A comprehensive study
based on 127 communities
Beijing Normal University
4. PART ONE Background
With the intensification of extreme weather
events, the impact of global climate change
has been ubiquitous
Climate change
1stthreat
Climate change was considered to be the
most serve global health threat in the 21st
century
Specialists concern on investigating public
exposure-response relation under global
warming
5. Research summary
PART ONE Background
First research Second research
2types
Extreme
temperature
influence
Ambient
temperature
relationship
4problems
Few study
focus on
China
Communities
not Enough
Lack thought on
impact of
temperature
zones
Seldom
compare
the rural
and urban
8. PART TWO Data
• Mortality data: The daily non-accidental
mortality data of each community we
obtained from DSP (Death Surveillance
Points System) is continuous and ranges from
1 January 2007 to 31 December 2012
Dataset
• Meteorological data: We selected the
daily meteorological variables from the
dataset including daily mean temperature
(Tm), maximum temperature (Tmax),
minimum temperature (Tmin) and relative
humidity (Rh)
• Social-economic data: Community level
data is also indispensable and we obtained
these data from the statistical yearbook,
including population size, per capita GDP and
medical data
9. Model and describe the temperature-
mortality relationship at community
level
01
Investigate the spatial autocorrelation
of temperature-mortality association
02
Analyze the different temperature-
mortality relationship at various
temperature zones
04
Analyze temperature-mortality relationship
through a meta-analysis method at national
or regional level03
Compare the difference between
rural and urban with the geostatistics
05
Utilize the statistics to analyze the
driven factors
06
PART TWO Methods
10. PART TWO Method
DLNM Model
• A quasi-Poisson regression
with Distributed Lag Non-
linear Model (DLNM) was
applied to estimate the
relationship between daily
mean temperature and
mortality in each
community .
• During this analysis, we
used the ‘cross-basis’
function to describe the
daily mean temperature-
mortality relationship and
lag days.
( ) ( , ) ( , 3) ( , 9)mean t t t ttLogE Y cb T lag ns Rh df ns Time df Dow Hoilday
Core Model
Yt represents the number of deaths on day t; α is intercept; cb means “cross-
basis” function defined by a B-spline with 5 degree of freedom (df) for the
space of temperature and 4 df for lag spaces.
To ensure that the model can cover the tails of the distribution, we placed 3
knots at 10th percentile, 50th percentile and 90th percentile of mean
temperature distribution of each community.
11. Model and describe the temperature-
mortality relationship at community
level
01 Investigate the spatial autocorrelation
of temperature-mortality association
02
Analyze the different temperature-
mortality relationship at various
temperature zones
04
Analyze temperature-mortality relationship
through a meta-analysis method at national
or regional level03
Compare the difference between
rural and urban with the geostatistics
05
Utilize the statistics to analyze the
driven factors
06
PART TWO Methods
13. PART Three Result
Modeling temperature-mortality
curves at the community level
Community level
Meta-analysis on
temperature-mortality
curves in different
temperature zones
Regional level
A comparison of extreme
temperature effected risk
between rural and urban
areas
Rural vs. Urban area
Find the potential factor and
analyze the coefficient
between those factors and
risk
Influence factor
14. PART THREE Result
• The curves which reflect the temperature-morality
relationship, are typically U-, J-, V-, and W-shaped as
many previous studies have pointed out.
• Different shapes of the temperature-mortality
curves represent different risk characteristics of the
temperature.
• It is obvious that both low and high temperatures
are likely to increase the mortality risk.
Temperature-mortality relationship
Community level
15. PART THREE Result
• Temperature–mortality curves at the community level
showed huge differences, the pooled curves were
generally U- or J- shaped in these five zones.
• The temperature–mortality curves in three zones were
all U-shaped, indicating both low and high temperatures
could increase significantly mortality risk.
• The curves appeared J-shaped in other two zones (the
middle subtropical region and south subtropical region),
implying more mortality risk from cold temperature than
those from hot stress
Pooled result across
Regional level
16. PART THREE Result
• Temperature–mortality curves at the community level
showed huge differences, the pooled curves were
generally U- or J- shaped in these five zones.
• The temperature–mortality curves in three zones were
all U-shaped, indicating both low and high temperatures
could increase significantly mortality risk.
• The curves appeared J-shaped in other two zones (the
middle subtropical region and south subtropical region),
implying more mortality risk from cold temperature than
those from hot stress
Extreme temperature risk
Regional level
Region Relative Risk
Cold Effect Heat Effect
Sub-temperate (29communities) 1.61(0.82,3.36) 1.24(0.70,2.47)
Warm temperate(34 communities) 1.78(0.97,3.53) 1.37(0.72,2.83)
North subtropical(28 communities) 1.27(0.94,1.72) 1.16(0.89,1.53)
Middle subtropical(21 communities) 1.93(1.08,3.60) 1.04(0.65,1.83)
South subtropical(14 communities) 1.56(1.09,2.24) 1.05(0.74,1.51)
17. PART THREE Result
• For cold effect in rural reflected in central area from
West to East the risk is higher than two edges ;the
trend of latitude-effected risk rise first and fall later
• For hot effect in rural area from West to East the risk
is especially higher in central than two edges ;the
trend from the North to South appeared a declining
pattern
Compare urban to rural
Rural area
Cold
Hot
18. PART THREE Result
• For cold effect in urban appeared a U-shaped curve
from West to East; the trend of latitude-effected risk
fall quickly
• For hot effect in urban area, the longitude-effect is
not so significant while the latitude-effect seems a
obvious inverse U-shaped curve
Compare urban to rural
Urban area
Cold
Hot
19. PART THREE Result
• Many study thought the social-economic factor
influence the temperature-mortality relationship,
we pick the per GDP as well as health workers per
thousand people own as two main factors
• For economical factor, we found that the highest
per capita GDP was in the north subtropical zone,
while the related lower per capita GDP was in the
middle subtropical zone
• For the warm zone, it is seem that the social-
economic factors have important impact on the
cold risk
Influence factor
Social & medical factor
20. PART THREE Result
• Temperature–mortality curves at the community level
showed huge differences, the pooled curves were
generally U- or J- shaped in these five zones.
• The temperature–mortality curves in three zones were
all U-shaped, indicating both low and high temperatures
could increase significantly mortality risk.
• The curves appeared J-shaped in other two zones (the
middle subtropical region and south subtropical region),
implying more mortality risk from cold temperature than
those from hot stress
Extreme temperature risk
Regional level
Region Relative Risk
Cold Effect Hot Effect
Sub-temperate (29communities) 1.61(0.82,3.36) 1.24(0.70,2.47)
Warm temperate(34 communities) 1.78(0.97,3.53) 1.37(0.72,2.83)
North subtropical(28 communities) 1.27(0.94,1.72) 1.16(0.89,1.53)
Middle subtropical(21 communities) 1.93(1.08,3.60) 1.04(0.65,1.83)
South subtropical(14 communities) 1.56(1.09,2.24) 1.05(0.74,1.51)
21. PART THREE Result
• Many study thought the social-economic factor
influence the temperature-mortality relationship,
we pick the per GDP as well as health workers per
thousand people own as two main factors
• For economical factor, we found that the highest
per capita GDP was in the north subtropical zone,
while the related lower per capita GDP was in the
middle subtropical zone
• For the warm zone, it is seem that the social-
economic factors have important impact on the
cold risk
Influence factor
Social & medical factor
22. PART THREE Result
• Many study thought the social-economic
factor influence the temperature-mortality
relationship, we pick the per GDP as well as
health workers per thousand people own as
two main factors
• For medical factor ,we found a obvious
correlation between the cold risk and the
urban medical
• However, when we consider the rural cold risk
we found the relationship with the medical
factor is not so significant
Influence factor
Social & medical factor
Urban cold
risk
Urban medical
factor
Rural cold
risk
Rural medical
factor
24. PART FOUR Conclusion
The different characteristics of mortality responding to cold and
hot stress highlighted that not only circumstance temperature but
also social-economic condition can be a main factor controlling
health risk
Multi-factors effect
Nonlinear relationship
Difference between urban and rural
The temperature-mortality relationship showed a distinct spatial
heterogeneity along temperature zones across Chinese mainland.
A systematic research
A comprehensive research on the temperature-mortality relationship
and extreme temperature effect about China.
A obvious difference for both cold and hot risk between urban and
rural areas in China
25. PART Four Innovation
Study based on the most
communities of China
Multi-scales research
A new method to combine
the tiny scale result
New relationship between
temperature
and cold risk
First research compare
the rural and urban
Title of my research is nonlinear relationship between extreme temperature and mortality across mainland in China a comprehensive study based on 127 communities
I will introduce my research from the following five parts.
The previous studies can be classified into two types: First study focus on exploring the relationship between ambient temperature and mortality; The other category investigate the adverse impact of extreme temperature on public health. However, four problems can be summarized from these studies: At first, fewer studies focus on China. Secondly, even though there are some studies focusing on China in recent years, the number of communities they used were not large enough to have an effective representative of China. Furthermore, few studies pay attention to the effect of temperature zones. The last but not least point is, lots of studies pointed out for those developing countries, like China, rapid urbanization have important impact on public health, however, few studies compare the difference between urban and rural areas.
Considering all of above problems, our research included the following four goals: first, we tried to explore the temperature-mortality relationship of plentiful communities and analyze the mortality risk of extreme temperature at community level;
based on this, we pooled these result at community level to get the regional result and identify those hotspot suffering from extreme temperature. Thirdly, we compared the temperature-mortality relationship between urban and rural areas and find their difference. Lastly, we tried to make out how other factors such as social factors can influence this difference.
Here is the second part: data and methods
Our research data contains three components: mortality data, meteorological data and social economy data. We collected non-accidental mortality data of each community from Death Surveillance Points System of China. The continuous data ranges from 1 January 2007 to 31 December 2012.Here is spatial distribution of communities, different colors represents different temperature zones.
Meteorological data is a daily interpolation dataset of the same period. Here we selected daily mean temperature (Tm) and relative humidity (Rh) to build our model and max/ min temperature to describe the characteristics of the community.
Previous studies reported that social economy factors have impact on the temperature-mortality relationship. In our study we used the per capita GDP and the number of medical staff per thousand people possess as indicators
Here is our technical route. And the key part of our method is how to model and describe the temperature-mortality relationship at community level. The core model is the distributed lag non-linear model. This model becomes popular in the environment health assessment field recently.
Here is our technical route. And the key part of our method is how to model and describe the temperature-mortality relationship at community level. The core model is the distributed lag non-linear model. This model becomes popular in the environment health assessment field recently.
So, based on the model at community level, we calculated the mortality risk of extreme temperature. Then we analyze whether there is a spatial autocorrelation of the cold-related risk or heat-related risk. The result shows no spatial autocorrelation. So we can investigate the regional temperature-mortality relationship with the meta-analysis method. Then we compare the difference of this relationship at different temperature zones. The next step is comparing the difference of the mortality risk between urban and rural areas. Here we used some geo-statistical method. At the last period, we tried to analyze what factors can lead to the difference of the characteristics among different areas.
第三部分我们将分享我们的研究结果
Research results included following four aspects: temperature-mortality relationship at community level; temperature-mortality relationship at regional level; a comparison about mortality risk of extreme temperature between rural and urban areas and the analysis on how social economy factors modify the relationship.
Temperature-mortality curves of community level were listed in this table. Roman numerals I to V represent the mid-temperature zones, the warm temperature zones, north subtropics, middle subtropics and south subtropics. However, for lack of space, only some results were listed. Actually, all of the 127 communities had the curves. For each curve, the x-coordinate represents local temperature, the y-coordinate represents the risk. From the table, we can find even though there were difference among this curves, they are typically U-, J-, V-, and W-shaped. This means both low temperature and high temperature can increase the mortality risk.
The result at regional levels seems a lot different. Here we dived the regions from the temperature zones and do the meta-analysis. We can find the temperature-mortality relationship among those five temperature zones are usually U- shaped or J-shaped, which shows a more obvious characteristic: for the mid-temperature zone, warm-temperature zone and north subtropics, their curves are U-shaped which means in this areas both high and low temperature can increase risk; while in the mid-subtropics and south subtropics the curves are J-shaped. This means only low temperature can increase mortality risk. This reflects the acclimatization of human to local environment.
To calculate the risk of extreme temperature, we defined the risk of 1st percentile of the local mean temperature distribution as the cold effect risk while defined the risk of 99th percentile as the heat effect risk. This table shows the result of cold and heat effect of the five temperature zones. From the box plot, we can find with the temperature increasing from the north to south, the heat effect appears a declining trend while the cold effect looks like an M-shaped curve. This is very interesting, and I will give my explanation in the following parts.
This part is about the comparison of the temperature-mortality relationship between rural and urban areas. We used the spatial trend method to analyze the spatial difference. In the picture x-coordinate represents the longitude and y-coordinate represents the latitude, the z-coordinate represent the cold or heat effect risk. We can see in rural areas, for the cold effect, with the longitude increases, there seems no obvious change while with the latitude decrease, it increases at first then decline in the later. For the heat effect, with the longitude increase, risk in north and south areas is low while in central area is high. With latitude decreases, the risk is obviously declining.
Compared with rural areas, the cold and heat effect in urban areas shows a different spatial characteristics. For the cold effect, with the longitude increases, the risk drop at first then rise in the later but it appears a declining trend with the latitude decreases. For the heat effect, longitude have no significant impact but with the latitude decreases and temperature increase, the change is obvious. It rise at first then decline.
The last part is the influence factors. When we look back to the characteristics of temperature-mortality relationship at regional level, we found with the regional temperature raised, the heat related risk shows a declining trend while the cold related risk presents an M-shaped curve. We think environment factors affect the heat-related risk while the social-economy factors can influence the cold-related risk. Look at the picture, bar graph is the per capita GDP of each temperature zone while the plot represent the cold effect. There seems a negative correlation between the cold effect and the economy. We gave this explanation to this phenomenon: In those cold or hot regions, such as the mid-temperature zones and south subtropics, temperature occupy the leading position influence human health; while in those warm areas, such as the warm-temperature zones and north subtropics, social and economy factors have a significant impact on human health. The lowest cold-related risk area, north subtopics, contains the most developed regions in China: the Yangtze River Delta and the Yangtze River Basin.
1.区域差异的规律是,随着温度升高,高温致死风险下降,而低温影响的死亡风险呈现M型
The last part is the influence factors. When we look back to the characteristics of temperature-mortality relationship at regional level, we found with the regional temperature raised, the heat related risk shows a declining trend while the cold related risk presents an M-shaped curve. We think environment factors affect the heat-related risk while the social-economy factors can influence the cold-related risk. Look at the picture, bar graph is the per capita GDP of each temperature zone while the plot represent the cold effect. There seems a negative correlation between the cold effect and the economy. We gave this explanation to this phenomenon: In those cold or hot regions, such as the mid-temperature zones and south subtropics, temperature occupy the leading position influence human health; while in those warm areas, such as the warm-temperature zones and north subtropics, social and economy factors have a significant impact on human health. The lowest cold-related risk area, north subtopics, contains the most developed regions in China: the Yangtze River Delta and the Yangtze River Basin.
To explain the difference of cold related risk between rural and urban areas, we used the medical indicator: medical staff per thousand people possess to get a continuous trend surface. We can find for urban areas, where the medical indicator is higher, the cold risk is lower. However, for rural areas, this spatial pattern only appears in the south areas.
我们的结论包含以下四个方面
Our conclusion include the following four aspects: our research is a systematic research about the temperature-mortality relationship of China. And this relationship shows a distinct spatial heterogeneity along temperature zones across Chinese mainland. Meanwhile, there is an obvious difference of this relationship and mortality risk between urban and rural areas. Moreover, all of this difference is a multi-factors result, economy and medical factors have important impact on these difference.
There are five innovations in our research: First, Compared to previous studies on temperature-mortality relationships in China, the number of communities involved in our study was the largest. Secondly, we studied the influence of temperature on human health from multi-scales. Moreover, compared with previous study, our study combine the result of community scale to get the regional result from the perspective of temperature zones. Based on this, we found an interesting M-shaped curve of the cold-related risk across different temperature zones. The last but least point is we firstly compare the urban and rural areas of the temperature-mortality relationship.