Climate Change Impacts, Exposure and Vulnerability

A changing climate has profound implications for human health, with more frequent heatwaves and extreme weather events, changing patterns of infectious disease, and the exacerbation of existing health challenges around the world. Indicators in this section track how these impact on human health.

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1.1 Health and Heat

A changing climate has profound implications for human health, with more frequent heatwaves and extreme weather events, changing patterns of infectious disease, and the exacerbation of existing health challenges around the world. Indicators in this section track how these impact on human health.

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1.1.1 Vulnerability to Extremes of Heat

People over 65 years of age, particularly those with chronic medical conditions (such as diabetes and heart, lung and kidney disease), are among the most vulnerable to the health effects of heatwaves. In a world that is increasingly warming due to climate change, this indicator measures the vulnerability to heat of populations around the world.

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Key findings

Vulnerability to the extremes of heat continues to increase in every region of the world, led by populations in Europe, with the Western Pacific region, South-East Asia region, and the African region all seeing an increase of more than 10% since 1990.

Data sources

– Global Burden of Disease Study, 2017. Institute for Health Metrics and Evaluation

Caveats

This indicator does not capture the existence or absence of effective adaptation measures, such as heat early warning systems, cooling devices, and green areas in cities.

 

This indicator was last updated in July 2020.

Indicator description

This indicator tracks a population’s vulnerability to heat using a composite index ranging from 0 to 100, which takes into account the proportion of the population over 65, prevalence of chronic disease, and the proportion of the population living in urban areas, which combines data on the proportion of the population older than 65 years; the prevalence of chronic respiratory disease, cardiovascular disease, and diabetes in this population, and the proportion of the total population living in urban areas.

 

1.1.2 Exposure of Vulnerable Populations to Heatwaves

Exposure to extremes of heat results in a range of health consequences, including heat stress and heat stroke, worsening heart disease, and acute kidney injury. Populations over 65 are particularly vulnerable to these effects, and are being exposed to heatwaves in increasing numbers. This indicator tracks the change in the number of heatwaves experienced by vulnerable populations around the world.

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Headline findings

A record 475 million additional exposures to heatwaves affecting vulnerable populations were observed in 2019, representing some 2·9 billion additional days of heatwaves experienced.

 

Data Sources

ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts – Gridded Population of the World. 4 ed (GPWv4), 2020. NASA – Histsoc dataset, 2020. Inter-Sectoral Impact Model Intercomparison Project – 2019 Revision of World Population Prospects, 2020. United Nations DESA/Population Division.

Caveats

As two distinct sources were used for population data there may be some inconsistencies between the pre and post 2000 values.

 

This indicator was last updated in July 2020.

Indicator description

This indicator tracks the change in the number of heatwave exposure events (with one exposure event being one heatwave experienced by one person aged over 65) and days of heatwave exposure in this population compared with the average number of events in the reference period (1986–2005). A heatwave was defined as a period more than 3 days at a given location where the minimum daily temperature was greater than the 99th percentile of the distribution of minimum daily temperature at that location over the 1986-2005 reference period for the entire year.

1.1.3 Heat-Related Mortality

Exposure to extremes of heat results in a range of health consequences, including heat stress and heat stroke, worsening heart disease, and acute kidney injury and leads to an increase in all-cause mortality. Populations over 65 are particularly vulnerable to these effects, and are being exposed to increasing temperatures around the world. This indicator heat-related mortality in over 65 populations around the world.

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Headline finding

From 2000 to 2018, heat-related mortality in people older than 65 years increased by 53·7% and, in 2018, reached 296,000 deaths, the majority of which occurred in Japan, eastern China, northern India, and central Europe.

Data Sources

ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts – Gridded Population of the World. 4 ed (GPWv4), 2020. NASA – Histsoc dataset, 2020. Inter-Sectoral Impact Model Intercomparison Project – 2019 Revision of World Population Prospects, 2020. United Nations DESA/Population Division – Global Burden of Disease, 2020. Institute for Health Metrics and Evaluation

Caveats

One exposure-response relation parameter from one Japanese study was used for the whole world. It may not be suitable for other countries and regions worldwide. It also assumes a constant exposure-response function, whereas there is emerging evidence for declining exposure-response functions over time.

 

This indicator was last updated in July 2020.

Indicator description

This indicator tracks global heat-related mortality in populations older than 65 years. It applies the exposure-response function and optimum temperature described by Honda and colleagues to the daily maximum temperature exposure of the population older than 65 years to estimate the attributable fraction and thus the deaths attributable to heat exposure.

1.1.4 Change in Labour Capacity

Our capacity to work is affected by temperature and humidity, particularly in highly active jobs in agriculture, industry, and manufacturing. Reduced work productivity can also result in flow on health and economic impacts for individuals and communities. As the world continues to warm, this indicator tracks the change in potential work hours lost due to high temperatures and sun exposure.

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Headline findings

Rising temperatures were responsible for an excess of 100 billion potential work hours lost globally in 2019 compared with those lost in 2000, with India’s agricultural sector among the worst affected.

Data Sources

ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts – Gridded Population of the World. 4 ed (GPWv4), 2020. NASA – ILOSTAT, 2020. ILO

Caveats

The distribution of agricultural, construction manufacturing and service sector workers used are country averages, applied evenly to each grid cell.

 

This indicator was last updated in July 2020

Indicator description

This indicator calculates hours of work lost by linking Wet Bulb Globe Temperature (including temperature, humidity, and solar radiation) with the amount of energy typically expended by workers in four sectors: agriculture, construction, service, and industry. It then combines this calculation with the proportion of people working in each of these four sectors within each country to estimate the potential work hours lost per year.

1.2 Health and Extreme Weather Events

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1.2.1 Wildfires

Wildfires cause a range of health impacts, ranging from direct thermal injuries through to exacerbation of acute and chronic lung disease from smoke and pollution. They will often cause substantial economic impacts, affecting vital infrastructure and emergency services. Climate change is creating hotter, drier conditions in many parts of the world, increasing the risk of wildfires. This indicator monitors the change in risk of wildfire and the number of people exposed to wildfires globally.

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Headline findings

In 114 countries, there was an increase in the number of days people were exposed to very high or extremely high risk of danger from fire in 2016–19 compared with 2001–04. This increased risk translated into an increase in population exposure to wildfires in 128 countries.

Data sources

Collection 6 active fire product, the Moderate Resolution Imaging Spectroradiometer, 2020. NASA EarthData – Fire danger indices historical data from the Copernicus Emergency Management Service, 2020. Copernicus Climate Change Service – Gridded Population of the World. 4 ed (GPWv4), 2020. NASA

Caveats

The fire danger index represents a potential fire risk calculated on meteorological parameters. The actual fire events can be also influenced by anthropogenic factors, such as human-induced land use and land cover changes, industrial-scale fire suppression, and human induced ignition. The satellite data does not account for cloud cover or smoke and data is not collected at night. It also assumes that those affected by a wildfire are the population limited to a 10km radius of the fire grid point and does not track exposure to wildfire smoke.

 

This indicator was last updated in July 2020

Indicator description

This indicator uses both model-based risk to wildfires and satellite-observed exposure. Climatological wildfire risk was estimated by combining daily very high or extremely high wildfire risk (a fire danger index score of 5 or 6) with climate and population data. Human exposure to wildfires, in person-days (with one person-day being one person exposed to a wildfire in one day, a number obtained by multiplying the population exposed by the number of days of exposure) was traced using satellite data and population data.

1.2.2 Flood and Drought

Climate change alters hydrological cycles, tending to make dry areas drier and wet areas wetter. Drought poses multiple risks for health, threatening drinking water supplies and sanitation, and crop and livestock productivity, enhancing the risk of wildfires, and potentially leading to forced migration. As climate change alters rainfall patterns and increases temperatures, this indicator tracks the change in months of drought around the world.

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Headline findings

In 2018, the global land surface area affected by excess drought was more than twice that of a historical baseline.

Data sources

ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts

 

Caveats

This indicator only captures the impacts of climate change on meteorological drought, but does not capture the impacts of climate change on hydrological or agricultural drought. It also does not measure the direct relation between a drought and the population living in drought-affected areas.

 

This indicator was last updated in July 2020

Indicator description

This index measures significant increases in the number of months of meteorological drought, using the standardised precipitation evapotranspiration index, compared with an extended historical baseline (1950–2005) to account for periodic variations such as those generated by the El Niño Southern Oscillation

1.3 Climate-Sensitive Infectious Diseases

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1.3.1 Climate Suitability for Infectious Disease Transmission

The suitability for transmission of many infectious diseases is influenced by shifts in temperature and precipitation. Dengue is a mosquito-borne disease that can cause febrile illnesses and, in severe cases, organ failure and death, with children under five particularly at risk. Vibrio bacteria are found in brackish marine waters and cause a range of human infections, including gastroenteritis, wound infections, sepsis and cholera. With temperatures changing across the globe, this indicator tracks how this is affecting the climate suitability for these infections.

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Headline findings

Changing climatic conditions are increasingly suitable for the transmission of numerous infectious diseases. From 1950 to 2018, the global climate suitability for the transmission of dengue increased by 8·9% for Aedes aegypti and 15·0% for Aedes albopictus.

Data Sources

CRU TS4.03, 2020. University of East Anglia Climatic Research Unit – Optimum Interpolation 1/4 Degree Daily Sea Surface Temperature Analysis version 2, 2020. NOAA Earth System Research Laboratory – Mercator Ocean Reanalysis, 2020. Copernicus Marine Environment Monitoring Service

Caveats

These results are not based on case data. Control efforts, such as water, sanitation and hygiene programs, and vector control efforts, may help to mitigate these effects. National presented for vectorial capacity for the transmission of dengue only takes into account the most common aedes species in each country. Data is not presented for countries for which information on vector presence was not available.

 

This indicator was last updated in July 2020

Additional information

1.3.2 Vulnerability to Mosquito-Borne Diseases

Vulnerability to dengue infections is affected by physiological, social, financial, and geographical factors, as well as a community’s capacity to adapt. Improvements in public health have seen a global reduction in vulnerability. As both the climate suitability for dengue, and populations’ adaptive capacity are changing, this indicator tracks both of these to gain an overall picture of population vulnerability to dengue fever.

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Headline findings

Following a sharp decline from 2010 to 2016, 2016–18 saw small up-ticks in national vulnerability to dengue outbreaks in four of six WHO regions; further data are required to establish a trend.

Data sources

-CRU TS4.03, 2020. University of East Anglia Climatic Research Unit

-IHR core capacities data, 2018. WHO

Caveats

The abundance models generate predictions and not observed frequencies in relation to climate conditions, and so should be considered a potential abundance estimate.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks vulnerability to mosquito-borne disease by combining data from indicator 1.3.1 on vectorial capacity for the transmission of dengue with the core capacities of countries’ health-care systems, as outlined by WHO’s International Health Regulations, which have been shown to be effective predictors of protection against disease outbreak.

1.4 Food Security and Undernutrition

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1.4.1 Terrestrial Food Security and Undernutrition

The global number of undernourished people worldwide has been steadily increasing worldwide since 2014. Undernutrition overwhelmingly affects children under five years old, being responsible for more than half of the deaths globally for this age group. This indicator uses changes in climate to track declines in crop yield potential for the world’s major crops: maize, wheat, rice, and soybean.

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Headline findings

From 1981 to 2019, crop yield potential for maize, winter wheat, soybean, and rice has followed a consistently downward trend, with reductions relative to baseline of 5·6% for maize, 2·1% for winter wheat, 4·8% for soybean, and 1·8% for rice.

Data sources

ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts – Portmann FT, Siebert S, Döll P. MIRCA2000—Global monthly irrigated and rainfed crop areas around the year 2000: A new high‐resolution data set for agricultural and hydrological modeling. Global biogeochemical cycles 2010; 24(1). – Sacks WJ, Deryng D, Foley JA, Ramankutty N. Crop planting dates: an analysis of global patterns. Global Ecology and Biogeography 2010; 19(5): 607-20.

Caveats

The temperature-driven change in crop duration is one of many factors affecting crop yield and does not reflect actual crop production. Different ways of calculating the agri-climate index using different data sets would produce slightly different time series, as would the use of different agri-climate proxies.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks the change in crop growth duration (the time taken to reach a target sum of accumulated temperatures and a proxy for crop yield potential) for maize wheat, rice and soybean, using a 1981-2010 reference period. If this sum is reached early, then the crop matures too quickly, and yields are lower than average.

1.5 Migration, Displacement and Sea-Level Rise

Changes in water and soil quality and supply, livelihood security, flooding, and saltwater intrusion are just some of the health impacts of sea-level rise. The health consequences of these effects will depend on various factors, including the options of both in situ and migration adaptation. In a world where sea levels are rising and populations are growing in areas at risk, this indicator tracks current population exposure to future rising sea levels.

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Headline findings

Without intervention, between 145 million and 565 million people living in coastal areas today will be exposed to, and affected by, rising sea levels in the future. Based on the population distributions of 2017, 145 million of the world’s population could be exposed to an average global sea level rise of 1m, a value rising to 565 million people with an average sea level rise of 5m.

Data sources

Kopp RE, DeConto RM, Bader DA, et al. Evolving Understanding of Antarctic Ice-Sheet Physics and Ambiguity in Probabilistic Sea-Level Projections. Earth’s Future 2017; 5(12): 1217-33. – Kulp SA, Strauss BH. CoastalDEM: a global coastal digital elevation model improved from SRTM using a neural network. Remote sensing of environment 2018; 206: 231-9 – LandScan 2017, 2018. Oak Ridge National Lab

Caveats

Estimates of population exposure to global mean sea level rise vary according to the input datasets, timeframes and geographic scales, the parameters that are set for about emissions and socioeconomic scenarios, and methods of analysis. Many factors, including adaptive strategies, influence population displacement due to sea level rise and some populations may not move due to lack of necessary resource to escape sites of risk or may remain in location due to social, cultural or political reasons. Additionally, other climate impacts and demographic factors contribute to migration into low-lying coastal sites. Finally, this indicator only considers current population exposed to 1 metre or 5 metres of sea level rise, which are within the lowest and highest estimates projected by the end of the century.

 

This indicator was last updated in July 2020

Indicator description

This indicator uses a bathtub model, overlaying global mean sea level rise with coastal elevation and then uses 2017 gridded population data to estimate the current population at risk of exposure to 1m and 5m global mean sea level rise.

Adaptation, Planning, and Resilience for Health

Indicators in this section track how communities, health systems, and governments are understanding the health risks of climate change, the strategies and resources they are deploying, and how adaptation and resilience measures are being implemented globally.

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2.1 Adaptation Planning and Assessment

Adaptation Planning and Assessment

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2.1.1 National Adaptation Plans for Health/2.1.2 National Assessments of Climate Change Impacts, Vulnerability and Adaptation for Health

The health impacts of climate change vary by location and population need, with vulnerability and adaptation assessments forming an essential first step in building local resilience. This indicator tracks the number of countries that have conducted national assessments of climate change impacts, vulnerability, and adaptation, as well as the number of countries that have developed national adaptation plans for health.

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Headline findings

Countries are beginning to prepare for the health risks of climate change: 50% of the 101 respondents report having a national health and climate change plan in place. Nonetheless, only 9% report having the budget to implement these plans. Additionally, 48 % of respondents had completed a national assessment of health vulnerability to climate change, but only 40% of these assessments have influenced the allocation of resources.

Data sources

-Health and Climate Country Survey, 2018. WHO

Caveats

The survey sample is not a representative sample of all countries as this survey was voluntary, which might also lead to selection bias. Additionally, there is overrepresentation of Small Island Developing States within the respondents.

 

This indicator was last updated in July 2020

Indicator description

This indicator draws on the WHO 2018 Health and Climate Country Survey, which was completed by 101 WHO Member States. It tracks the countries that have a national health and climate change plan or strategy, current levels of their implementation and the commitment of national health funds towards their implementation. It also tracks countries that have conducted national assessments of vulnerability, impacts and adaptation for health and whether the results from these assessments have influenced policy prioritisation or financial resources.

2.1.3 City-Level Climate Change Risk Assessments

Cities and local communities are at the forefront of the health impacts of climate change, and must be central to any adaptation response. This indicator tracks the proportion of global cities who have conducted climate change risk assessments.

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Headline findings

In 2019, 77% of 789 global cities that responded to the survey had either already completed or were actively undertaking climate change risk assessments, a substantial increase both in number of responding cities as well as in their undertaking of risk assessments from 2018.

Data sources

-Cities Data, 2019. CDP

Caveats

This data is from the voluntary CDP data of annual global survey of cities, and as such may suffer from selection bias. The majority of responding cities are from High Income Countries (48.9%).

 

This indicator was last updated in July 2020

Indicator description

This indicator draws on data from the CDP annual Cities Questionnaire, assessing the number of global cities that have undertaken a city-wide climate change risk or vulnerability assessment.

2.2 Climate Information Services for Health

Climate information from meteorological services is essential in monitoring disease outbreaks, extreme weather events, and other environmental hazards. They can also provide early warning systems, triggering responses in communication to the public and preparedness of health services and human resources. This indicator tracks the number of national meteorological and hydrological services that are providing services to the health sector.

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Headline findings

The number of countries reporting that their meteorological services provide climate information to the health sector has continued to grow, increasing from 70 in 2019 to 86 countries in 2020.

Data sources

– Country Profile data base. WMO

Caveats

This indicator only considers climate services provided by national member states, and not by academic, private, regional, or other providers. The data is self-reported by countries and may therefore include reporting bias.

 

This indicator was last updated in July 2020

Indicator description

This indicator takes data from the World Meteorological Organization Country Profile Database integrated questionnaire, which asks for information regarding the to which communities and sectors the National Member States provide products and information and the extent to which these products are used to improve decisions.

2.3 Adaptation Delivery and Implementation

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2.3.1 Detection, Preparedness and Response to Health Emergencies

Health sector preparedness and response to acute public health emergencies related to climate change is an essential component of any adaptation response. This indicator tracks countries’ emergency preparedness through their implementation of a national health emergency framework.

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Headline findings

In preparation for a multi-hazard public health emergency, 66% of the 166 responding countries have reported medium-to-high implementation of a national health emergency framework in 2019.

Data sources

– International Health Regulations monitoring framework, SPAR, 2019. WHO

Caveats

IHR monitoring questionnaires responses are self-reported, and the responding countries differ from year to year. The core capacities tracked by this indicator are not specific to climate driven risk changes, and they capture potential capacity – not action. Finally, it does not measure the quality of surveillance nor the effectiveness of emergency response plans.

 

This indicator was last updated in July 2020

Indicator description

This indicator monitors implementation of capacity “C8” (the existence of a national health emergency framework), as tracked by the International Health Regulations of the WHO. Due to changes in the reporting format, data is disaggregated in “preparedness” and “response” for 2005 to 2017, but reported as a single value for 2018 and 2019.

2.3.2 Air Conditioning Benefits and Harms

Heatwaves are among the most immediate and severe of the health impacts of climate change. A variety of adaptation strategies exist, from effective ventilation and building regulations through to air conditioning for selected populations. Access to household air conditioning is highly protective against heatwave-related mortality. However, its use also contributes to air pollution, greenhouse gas emissions, and increased urban heat island effect. This indicator tracks the coverage and greenhouse gas emissions of air conditioning use.

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Headline findings

While conferring protection against heat-related illness, the world’s air conditioning stock continued to rise from 2016, reaching 8.5% of total global electricity consumption in 2018, and further contributing to climate change, air pollution, peak electricity demand, and urban heat islands.

Data sources

– International Energy Agency data on household air conditioning use.

Caveats

Data is only available for a limited number of countries or country groups and the rest of the data is estimated as “rest of world”. In addition, the presence of air conditioning in a household does not guarantee the use of air conditioning in that household.

 

This indicator was last updated in July 2020

Indicator description

Using data from the International Energy Agency, this indicator calculates the global proportion of households using air conditioning. It also uses this IEA data to estimate the PM2.5 attributable premature mortality due to air conditioning use.

2.3.3 Urban Green Space

Access to urban green space provides benefits to human health by reducing exposure to air and noise pollution, relieving stress, providing a setting for social interaction and physical activity, and reducing all-cause mortality. In addition, green space sequesters carbon and provides local cooling that disrupts urban heat islands, benefiting both climate change mitigation and heat adaptation. This indicator tracks the availability of greenspace in urban areas around the world.

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Headline findings

Urban green space is an important measure to reduce population exposure to heat; 9% of global urban centres had a very high or exceptionally high degree of greenness in 2019, and more than 156 million people were living in urban centres with concerningly low levels of urban green space.

Data sources

– Global Human Settlement program, European Commission – Urban Centre Database GHS-UCDB R2019A. 2020 – Gridded Population of the World. 4 ed (GPWv4), 2019. NASA – Terra Vegetation Indices, Moderate Resolution Imaging Spectroradiometer (MODIS) from NASA’s Terra satellite. NASA 2020

Caveats

This indicator does not provide information on quality or type of green space, nor on its accessibility. In tracking urban areas as defined by the Global Human Settlement Program, this indicator does not fous on administrative city boundaries, but rather on effective urban developments.

 

This indicator was last updated in July 2020

Indicator description

This indicator quantifies exposure to urban green space for 2019 in the 468 urban centres of more than 1 million inhabitants identified by the Global Human Settlement programme of the European Commission. Green space is detected through remote sensing of green vegetation, making use of the satellite-based Normalised Difference Vegetation Index (NDVI)

2.4 Spending on Adaptation for Health and Health-Related Activities

Health is consistently identified as a key priority area for climate change adaptation, with countries increasingly allocating financial resources to deliver this. This indicator tracks total spending in the health sector.

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Headline findings

In 2019, global spending on health adaptation has increased to $18·4 billion, reaching 5·3% of total spending on adaptation.

Data sources

– Adaptation and Resilience to Climate Change dataset, 2019. kMatrix Ltd

– World Economic and Financial Surveys: World Economic Outlook Database, 2019. International Monetary Fund

Caveats

This indicator only tracks economic transactions for which there is transactional/financial data available.

 

This indicator was last updated in 2020

Indicator description

This indicator uses the “Adaptation and Resilience to Climate Change” dataset from kMatrix to track global spending on adaptation in the health sector.

THE HEALTH BENEFITS OF THE RESPONSE TO CLIMATE CHANGE

Tackling climate change could be the greatest global health opportunity of the 21st century. Many of the interventions required to mitigate and adapt bring enormous benefits for human health and wellbeing in the form of cleaner air, healthier diets, and more liveable cities. Indicators in this section track the world’s efforts to mitigate climate change, and the health benefits of this response.

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3.1 Energy System and Health

Tackling climate change could be the greatest global health opportunity of the 21st century. Many of the interventions required to mitigate and adapt bring enormous benefits for human health and wellbeing in the form of cleaner air, healthier diets, and more liveable cities. Indicators in this section track the world’s efforts to mitigate climate change, and the health benefits of this response.

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3.1.1 Carbon Intensity of the Energy System

The power generation sector is the largest contributor to global greenhouse gas emissions. Burning fossil fuels contributes to the majority of these emissions, and to toxic air pollution. This indicator monitors the carbon intensity of the energy system and greenhouse gas emissions from power generation.

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Headline findings

The carbon intensity of the global primary energy supply has remained flat for the past three decades. Although in 2017 carbon intensity was at its lowest since 2006, it was still 0·4% higher than the levels in 1990.

Data sources

– CO2 Emissions from Fuel Combustion Statistics, 2020. IEA

Caveats

The indicator does not provide information on the share of different fossil fuels, their use in different sectors, and the absolute levels of usage.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks the carbon intensity of the energy system, both at global and regional scales, expressed as the CO2 emitted per terajoule of the total primary energy supply.

3.1.2 Coal Phase-Out

Coal combustion continues to be the largest contributor to emissions from the energy sector and is a major contributor to premature mortality due to air pollution. The phase-out of coal-fired power is therefore an important first step in the mitigation of climate change. This indicator tracks progress towards coal phase-out.

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Headline findings

In 2018, global energy supply from coal was 1·2% higher than in 2017 and 74% higher than in 1990.

Data sources

– World Extended Energy Balances, 2019. IEA

Caveats

This indicator is unavailable for select countries.

 

This indicator was last updated in July 2020

Indicator description

This indicator reports on progress towards a global phase-out of coal, tracking the total primary energy supply from coal and coal’s share of total electricity generation.

3.1.3 Zero-Carbon Emission Electricity

Continued growth in renewable energy, particularly wind and solar sources, is key to replacing fossil fuels. This indicator tracks electricity generation and the share of total electricity generation from all low-carbon sources.

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Headline findings

The average annual growth rate in power generation from wind and solar sources was 21% globally and 38% in China between 2010 and 2017, with all forms of low-carbon energy responsible for 33% of total electricity generation worldwide in 2017.

Data sources

– World Extended Energy Balances, 2019. IEA

Caveats

This indicator set does not provide information on the air pollutant emissions displaced due to the increasing share of renewable energy generation.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks electricity generation and the share of total electricity generation from all low-carbon sources (nuclear and all renewables, including hydro) and renewables (wind and solar, excluding hydro and biomass).

3.2 Clean Household Energy

The use of unhealthy and unsustainable fuels and technologies for cooking, heating, and lighting in the home contributes both to greenhouse gas emissions and to dangerous concentrations of household air pollution. This indicator tracks the proportion of the population who use clean fuels and technologies for cooking, and tracks the usage of zero-emission energy in the residential sector.

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Headline findings

Primary reliance on healthy fuels and technology for household cooking has continued to rise, reaching 63% of the global population in 2018. However, total consumption of zero-emission energy for all household needs remained low at 26%.

Data sources

– World Energy Balances, 2020. IEA

– Household Energy Database, 2020. WHO – World Population Prospects: 2017 Revision. United Nations DESA/Population Division – 2013 Global Burden of Disease Study

Caveats

The data from the IEA on residential energy flows and energy access provide an indication of both the access to electricity and the proportion of the different types of energy used within the residential sector, providing a suggested picture on how access and use might be interacting.

 

This indicator was last updated in July 2020

Indicator description

This indicator draws on national surveys collected by WHO across 194 countries and tracks the proportion of the population who use clean fuels and technologies for cooking, defined as those that have emission rate targets meeting WHO guidelines for air quality. This indicator also tracks the usage of zero-emission energy in the residential sector, measured as fuels with both zero greenhouse gas and zero particulate emissions at the point of use (mainly electricity and renewable heating) with data from the IEA.

3.3 Premature Mortality from Ambient Air Pollution by Sector

Air pollution is responsible for over several million premature deaths every year, with some 91% of deaths from ambient air pollution occurring in low-income and middle-income countries. The majority of this pollution originates from sectors which also produce greenhouse gas emissions, presenting an opportunity for win-win interventions. This indicator tracks global PM2.5 attributable premature mortality by sector.

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Headline findings

Premature deaths from ambient PM2·5 attributed to coal use are rapidly declining, falling from 440,000 deaths in 2015 to 390,000 deaths in 2018. However, total deaths from ambient PM2·5 have increased slightly during this time period, from 2·95 million deaths in 2015 to 3·01 million deaths in 2018, highlighting the need for accelerated intervention.

Data sources

– World Energy Statistics (for 2015) and the World Energy Outlook 2019. IEA – REVIHAAP assessment, 2013. WHO European Centre for Environment and Health – World Population Prospects: 2017 Revision. United Nations DESA/Population Division – 2013 Global Burden of Disease Study

Caveats

This indicator uses both country data and regional aggregated data. There are three deviations in the aggregation of countries as compared to the WHO regions: Sudan and Somalia are included in the ‘African Region’, and Algeria is included in the ‘Eastern Mediterranean’. Different dose-response relationships are used for Europe (REVIHAAP, recommended by WHO-Europe) and the rest of the world (Integrated Exposure-Response functions from the 2013 GBD Study). The non-linearity of the IERs means that in highly polluted environments, the health benefits of a marginal reduction of emissions would be disproportionately smaller than the relative change in concentrations.

 

This indicator was last updated in July 2020

Indicator description

This indicator models the premature deaths caused by air pollution from individual economic sectors, combining bottom-up emission calculations with atmospheric chemistry and dispersion coefficients and then applying this to population data and PM2.5 exposure-response relationships. It also highlights the contribution to premature deaths from coal and biomass burning across all sectors.

3.4 Sustainable and Healthy Transport

Building cities and transport systems which encourage cycling and physical activity will help respond to climate change and improve public health. Transitioning to cleaner fuels for road transport will work alongside this to reduce the health impacts of air pollution. This indicator tracks fuel use for road transportation on a per capita basis, by fuel type.

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Headline findings

Although fossil fuels continue to dominate the transport sector, the use of electricity for road transport rose by 18·1% from 2016 to 2017, and the global electric vehicle fleet increased to more than 5·1 million vehicles in 2018 (a rise of 2 million vehicles in only 12 months).

Data sources

Global Electric Vehicle Outlook, 2019. IEA

Caveats

This indicator does not capture shifts in modes of transport used. In particular, it does not capture walking and cycling for short trips, which can yield substantial health benefits through increased physical activity.

 

This indicator was last updated in July 2020.

Indicator description

This indicator captures change in total fuel use and type of fuel use for transport on a per capita basis.

3.5 Food, Agriculture and Health

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Headline Finding

Total emissions from livestock and crop production have increased by 14% and 10%, respectively, from 2000 to 2016, with 93% of livestock emissions attributed to ruminants.

Indicator Description

This indicator tracks emissions from livestock and crop production, providing the tonnes of CO2 equivalents emitted by animal or crop type, and by emission source.

Caveats

Data limitations – for example on grazing emissions from small island states – have been overcome with modelled outputs.

This indicator was last updated in July 2019

Data Sources

– Herrero M, Havlík P, Valin H, et al. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences 2013; 110(52): 20888-93.

– FAOSTAT, 2019. FAO

– Chang J, Ciais P, Herrero M, et al. Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management. Biogeosciences 2016; 13(12): 3757-76.

– Carlson KM, Gerber JS, Mueller ND, et al. Greenhouse gas emissions intensity of global croplands. Nature Climate Change 2017; 7(1): 63

3.5.1 Emissions from Agricultural Production and Consumption

The food system is responsible for 20–30% of global greenhouse gas emissions, most of which originate from meat and dairy livestock. Although countries’ emissions are typically measured on a production basis, it is their consumption that generates the demand and results in diet-related health outcomes. This indicator tracks agricultural emissions from countries’ production and consumption.

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Headline findings

Ruminant livestock continue to dominate agriculture’s contribution to climate change and are responsible for 56% of total agricultural emissions and 93% of all livestock emissions globally. This proportion represents a 5·5% increase in the per capita emissions from beef consumption between 2000 and 2017, which is particularly concerning given the sharp rise in population during this time period and the health impacts of excess red meat consumption.

Data sources

– Herrero M, Havlík P, Valin H, et al. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences 2013; 110(52): 20888-93.

– FAOSTAT, 2020. FAO

– Carlson KM, Gerber JS, Mueller ND, et al. Greenhouse gas emissions intensity of global croplands. Nature Climate Change 2017; 7(1): 63

Caveats

For livestock, some data is missing for some years, most notably Somalia (2000-2011) for non-dairy cattle, as well as data on grazing emissions from small islands is also missing. The emission factors differ from FAO numbers for livestock and for crops, due to methodology used.

 

This indicator was last updated in July 2020

Indicator description

Agricultural emissions from countries’ production and consumption (adjusting for international trade) were tracked by use of data from the Food and Agriculture Organization of the United Nations.

3.5.2 Diet and Health Co-Benefits

Globally, diet and weight-related risk factors have barely changed since 1990, accounting for 8·8 million deaths in 2017, representing 19% of total mortality. Combined with a range of food system-wide interventions, achieving dietary change consistent with the Paris Agreement and the sustainable development goals is possible by reducing reliance on red meat consumption and prioritising healthier alternatives, with various diets and choices available depending on the region, individual, and cultural context. This indicator presents the change in deaths attributable to dietary risks by focusing on one particular area—the consumption of excess red meat.

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Headline findings

The global number of deaths due to excess red meat consumption rose to 990 000 deaths in 2017, a 72% increase since 1990.

Data sources

– Food Balance Sheets, 2020. FAO

– 2013 Global Burden of Disease Study – Gustavsson J, Cederberg C, Sonesson U, Van Otterdijk R, Meybeck A. Global food losses and food waste: extent, causes and prevention. Rome, Italy: Food and Agriculture Organization of the United Nations, 2011.

– NCD Risk Factor Collaboration. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19· 2 million participants. The Lancet 2016; 387(10026): 1377-96.

– Bechthold A, Boeing H, Schwedhelm C, et al. Food groups and risk of coronary heart disease, stroke and heart failure: A systematic review and dose-response meta-analysis of prospective studies. Critical Reviews in Food Science and Nutrition 2019; 59(7): 1071-90.

– Schwingshackl L, Schwedhelm C, Hoffmann G, et al. Food groups and risk of colorectal cancer. International Journal of Cancer 2018; 142(9): 1748-58.

–Schwingshackl L, Hoffmann G, Lampousi AM, et al. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. European Journal of Epidemiology 2017; 32(5): 363-75.

Caveats

The relative risks used are all supported by statistically significant dose-response relationships in meta-analyses (graded with NutriGrade as moderate or high quality evidence) and the existence of plausible biological pathways, however there are caveats related to nutritional epidemiological studies, such as potential measurement error of dietary exposure.

 

This indicator was last updated in July 2020

Indicator description

This indicator involves a comparative risk assessment, linking food consumption data (adjusted for food waste to estimate exposure) from the food balance sheets of the Food and Agriculture Organization of the United Nations with dietary and weight-related risk factors.

3.6 Mitigation in the Healthcare Sector

Health care is among the most important sectors in managing the effects of climate change and, simultaneously, has an important role in reducing its own carbon emissions. This indicator measures healthcare emissions that come directly from the sector and indirectly through purchased goods and services.

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Headline findings

The health-care sector was responsible for approximately 4·6% of global greenhouse gas emissions in 2017.

Data sources

– World Input-Output Database with environmental accounts, 2013

– EXIOBASE version 2.2

– Global Health Expenditure Database: Indicators and data, 2020. World Health Organization

– Basic Data Selection, 2019. United Nations Statistics Division

– Consumer price index, 2020. World Bank Group

– 2015 Global Burden of Disease Study

Caveats

The EXIOBASE model provides country-specific data for 42 countries, and the remaining data is aggregated into world regions. For the remaining countries, their healthcare sector emissions are estimated based on regional averages.

 

This indicator was last updated in July 2020

Indicator description

This indicator models emissions from the global healthcare sector by use of environmentally extended multi-region input-output (EE MRIO) models combined with data on healthcare expenditure from WHO. It also matches per-capita greenhouse gas emissions data with the Healthcare Access and Quality Index, which is a linear interpolation for years in which HAQ data is not available.

Economics and Finance

The data here works to track the financial and economic dimensions of the effects of climate change, and of mitigation efforts required to respond to these changes. Indicators here monitor the economic costs of climate change and its drivers, as well as the investments and economic tools being deployed to transition to a low-carbon economy.

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4.1 The Economic Impact of Climate Change and its Mitigation

The data here works to track the financial and economic dimensions of the effects of climate change, and of mitigation efforts required to respond to these changes. Indicators here monitor the economic costs of climate change and its drivers, as well as the investments and economic tools being deployed to transition to a low-carbon economy.

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Headline Finding

In 2018, 831 climate-related extreme events resulted in US$166 billion in economic losses and no measurable losses in low-income countries were covered by insurance.

Indicator Description

This indicator tracks the total measurable annual economic losses (insured and uninsured) relative to GDP, resulting from climate-related extreme events.

Caveats

Where these are available, data is taken from official institutions, but where not, estimates are calculated. In cases where only low-quality information is available, such as a description of the number of homes damaged or destroyed, assumptions on value and costs are made.

This indicator was last updated in July 2019

Data Sources

– NatCatSERVICE, 2019. Munch Re

4.1.1 Economic Losses due to Climate-Related Extreme Events

Climate-related extreme events result in direct deaths and injury, the spread of water-borne illness, and the destruction of habitats and infrastructure. Compounding this, these events often result in large economic costs, exacerbating the direct health impacts they produce. This indicator tracks the insured and uninsured economic losses from extreme events.

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Headline findings

In 2019, economic losses from climate-related extreme events were nearly five times greater in low-income economies than in high-income economies.

Data sources

– Sigma catastrophe database, 2020. Swiss Re Institute

Caveats

Only events with measurable economic losses above the threshold levels are included. Where these are available, data is taken from official institutions, but where not, estimates are calculated. In cases where only low-quality information is available, such as a description of the number of homes damaged or destroyed, assumptions on value and costs are made.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks the total annual economic losses (insured and uninsured) relative to GDP, that result from climate-related extreme events.

4.1.2 Economics of Heat-Related Mortality

Exposure to extremes of heat results an increase in all-cause mortality, particularly in the over 65 population. As exposures to extremes of heat and the resulting health outcomes continue to rise, this indicator places a monetary value on heat heat-related mortality.

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Headline findings

The monetised value of global heat-related mortality increased from 0·23% of gross world product in 2000 to 0·37% in 2018. Europe was the worst affected in 2018, with costs equal to the average income of 11 million of its citizens and 1.2% of regional gross national income.

Data sources

ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts

– Gridded Population of the World. 4 ed (GPWv4), 2020. NASA

– Histsoc dataset, 2020. Inter-Sectoral Impact Model Intercomparison Project

– 2019 Revision of World Population Prospects, 2020. United Nations DESA/Population Division

– Global Burden of Disease, 2020. Institute for Health Metrics and Evaluation

– Mortality Risk Valuation in Environment, Health and Transport Policies, 2012. OECD

– Population and GINI (current $US), 2020. World Bank Group

Caveats

VSL values rely on estimates of ‘willingness to pay’ by individuals, which are influenced by the survey design and characteristics of individuals surveyed. As VSL estimates are not available for all countries and regions, the calculation method employed assumes that the average individual’s willingness to pay to reduce the risk of death is linked to the GNI per capita of the country in which they find themselves.

 

This indicator was last updated in July 2020.

Indicator description

This indicator combines estimates on heat-related mortality from Indicator 1.1.3 and the value of a statistical life (VSL) estimated for the member countries of the Organisation for Economic Co-operation and Development (OECD), using a fixed ratio of the value of a statistical life to gross national income for non-OECD countries. The value of mortality is presented as a proportion of total gross national income and as number of people’s incomes this loss would be equivalent to in a given country and region.

4.1.3 Loss of Earnings from Heat-Related Labour Capacity Loss

Higher temperatures, driven by climate change, are affecting people’s ability to work. This indicator considers the loss of earnings that could result from such reduced capacity, compounding the initial cause of ill health and impacting on wellbeing.

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Headline findings

By 2015, heat-related reduction in labour capacity resulted in earnings losses equivalent to an estimated 3·9–5·9% of GDP in the lower-middle-income countries tracked.

Data sources

– ERA5 reanalysis, 2020. European Centre for Medium-Range Weather Forecasts

– Gridded Population of the World. 4 ed (GPWv4), 2020. NASA

– ILOSTAT, 2020. ILO

– World Development Indicators, 2020. World Bank Group

Caveats

There are data gaps in the ILO Earnings and Labour Income dataset for the years studied for each country and thus several assumptions were incorporated in order to fill these data gaps. This indicator covers 25 countries, selected by the impact their workers experience and for geographical coverage.

 

This indicator was last updated in July 2020

Indicator description

The indicator combines heat-related potential work hours lost in agriculture, construction, service, and industry as estimated in Indicator 1.1.4 with data on average earnings by country and sectors.

4.1.4 Economics of the Health Impacts of Air Pollution

Air pollution is responsible for over seven million deaths each year, resulting in profound economic costs. Efforts to mitigate climate change often reduce air pollution, resulting in significant cost-savings and a cost-effective intervention. This indicator tracks the costs of life lost due to air pollution, and the cost-savings of improvements in air quality for Europe.

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Headline findings

Across Europe, ambient PM2·5 pollution from human activity reduced between 2015 and 2018. If held constant, this improvement alone would lead to an annual average reduction in years of life lost to the current population worth $8·8 billion.

Data sources

– World Energy Statistics (for 2015) and the World Energy Outlook 2019. IEA – REVIHAAP assessment, 2013. WHO European Centre for Environment and Health – World Population Prospects: 2017 Revision. United Nations DESA/Population Division – European Commission Impact Assessment Guidelines, 2009. European Commission

Caveats

Data is only available for EU countries and will be expanded in subsequent years. A Value of a Life Year of €50,000 is the lower bound estimate as suggested by the EC Impact Assessment Guidelines. This value does not take into account the health economic costs of healthcare delivery or societal economic costs such as workforce losses, thus representing an underestimation of real economic losses.

 

This indicator was last updated in July 2020

Indicator description

This indicator estimates the change in Years of Life Lost due to PM2.5 in European Union countries from 2015 to 2018, applied across 100 years to the 2015 population, assuming constant levels of emissions and subsequent exposure. A Value of a Life Year (€50,000) is then assigned to the Years of Life Lost to give an estimation of the annual average economic reduction of this change in PM2.5.

4.2 The Economics of the Transition to Zero-Carbon Economies

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Headline Finding

In Europe, improvements in particulate air pollution from human activity were seen from 2015 to 2016. If the levels of pollution for these two years remained the same over a person’s lifetime, this would lead to an annual average reduction in Years of Life Lost worth €5.2 billion.

Indicator Description

This indicator estimates the change in Years of Life Lost due to PM2.5 in European Union countries from 2015 to 2016, applied across 100 years to the 2015 population. A Value of a Life Year (€50,000) is then assigned to the Years of Life Lost to give an estimation of the annual average economic reduction of this change in PM2.5.

Caveats

Data is only available for EU countries and will be expanded in subsequent years. A Value of a Life Year of €50,000 is the lower bound estimate as suggested by the EU Impact Assessment Guidelines. This value does not take into account the health economic costs of healthcare delivery or societal economic costs such as workforce losses, thus representing an underestimation of real economic losses.

This indicator was last updated in July 2019

Data Sources

– Amann M, Bertok I, Borken-Kleefeld J, et al. Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications. Environmental Modelling & Software 2011; 26(12): 1489-501

– World Energy Outlook, 2017. IEA

4.2.1 Investment in New Coal Capacity

Coal phase-out is both an essential first step in the response to climate change, and an important intervention to reduce morbidity and mortality from air pollution. This indicator monitors the future of coal-fired power generation by tracking investments in new coal-fired capacity.

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Headline findings

Largely driven by China, investment in new coal capacity has been declining since 2011 and decreased by 6%between 2018 and 2019. Despite this reduction, global coal capacity continues to increase, with fewer retirements than there were additions of coal plants for every year tracked.

Data sources

– World Energy Investment, 2020. IEA

Caveats

Investment estimates are derived from IEA data for energy demand, supply and trade, and estimates of unit capacity costs. Other areas of expenditure, including operation and maintenance, research and development, financing costs, mergers and acquisitions or public markets transactions, are not included.

 

This indicator was last updated in July 2020

Indicator description

This indicator draws on data from the annual International Energy Agency World Energy Investment to track global coal investment, as a percentage of a 2006 baseline.

4.2.2 Investments in Zero-Carbon Energy and Energy Efficiency

Investment in zero-carbon energy and energy efficiency must continue to displace investment in fossil fuels if the world is to meet its commitments under the Paris Agreement. This indicator looks at the future of energy production, by monitoring global investment in zero-carbon energy, energy efficiency, fossil fuels, and electricity networks.

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Headline findings

Progress towards zero-carbon energy has stalled; investments in zero-carbon energy and energy efficiency have not increased since 2016 and are a long way from doubling by 2030, which is required to be consistent with the Paris Agreement.

Data sources

– World Energy Investment, 2020. IEA

Caveats

Investment estimates are derived from IEA data for energy demand, supply and trade, and estimates of unit capacity costs. Other areas of expenditure, including operation and maintenance, research and development, financing costs, mergers and acquisitions or public markets transactions, are not included.

 

This indicator was last updated in July 2020

Indicator description

This indicator draws on data from the International Energy Agency to assess four categories of investment: renewables and nuclear; energy efficiency; electricity networks; and fossil fuels.

4.2.3 Employment in Low-Carbon and High-Carbon Industries

Investment in zero-carbon energy and energy efficiency must continue to displace investment in fossil fuels if the world is to meet its commitments under the Paris Agreement. This indicator looks at the future of energy production, by monitoring global investment in zero-carbon energy, energy efficiency, fossil fuels, and electricity networks.

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Headline findings

Progress towards zero-carbon energy has stalled; investments in zero-carbon energy and energy efficiency have not increased since 2016 and are a long way from doubling by 2030, which is required to be consistent with the Paris Agreement.

Data sources

– World Energy Investment, 2020. IEA

Caveats

Investment estimates are derived from IEA data for energy demand, supply and trade, and estimates of unit capacity costs. Other areas of expenditure, including operation and maintenance, research and development, financing costs, mergers and acquisitions or public markets transactions, are not included.

 

This indicator was last updated in July 2020

Indicator description

This indicator draws on data from the International Energy Agency to assess four categories of investment: renewables and nuclear; energy efficiency; electricity networks; and fossil fuels.

4.2.4 Funds Divested from Fossil Fuels

Public health institutions have a long history of divesting from products which harm the health of their patients – whether they be tobacco, alcohol, or arms. Increasingly, they are choosing not to invest in the fossil fuel industry because of its impact on public health and on climate change. This indicator tracks fossil fuel divestment from health and medical institutions.

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Headline findings

The global value of new funds committed to fossil fuel divestment in 2019 was $4·01 trillion, of which health institutions accounted for around $19 million. From 2008 to 2019, there was a cumulative sum of $11·51 trillion divested from fossil fuels, with health institutions accounting for $42 billion.

Data sources

– 350.org.

Caveats

Due to confidentiality issues, the value of funds divested by each organization is not available. The year of divestment reflects the year when the commitment was recorded in 350.org.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks the total global value of funds divested from fossil fuels, and the value of divested funds coming from health institutions, using self-reported data from 350.org. The following organisations classified as non-health institutions by 350.org have been considered as health institutions for the purpose of this indicator: HESTA Super Fund; Doctors for the Environment Australia; London School of Hygiene & Tropical Medicine; Berliner Ärzteversorgung / Berlin Doctor’s Pensionfund; HCF; The Royal College of General Practitioners; New Zealand Nurses Organisation.

4.2.5 Net Value of Fossil Fuel Subsidies and Carbon Prices

Placing a price on greenhouse gas emissions provides an incentive to drive the transition towards a low-carbon economy. This strategy also allows for a close reflection of the true cost of emissions-intensive practices, particularly fossil fuel use, capturing some of the negative externalities resulting from their impact on health. However, not all countries explicitly set carbon prices, and, in some cases, the strength of any carbon price might be undermined by the opposing influence of subsidies on fossil fuel production and consumption. As the world works to move away from fossil fuel use, this indicator tracks both carbon pricing mechanisms and fossil fuel subsidies to estimate a net carbon price.

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Headline Finding

58 of the 75 countries reviewed were operating with a net negative carbon price in 2017. The resulting net loss of revenue was, in many cases, equivalent to substantial proportions of the national health budget.

Headline Finding

– Energy Subsidies, 2019. IEA – OECD inventory of support measures for fossil fuels, 2019. OECD. – IBISWorld Industry Report: Global Oil & Gas Exploration & Production, 2020. IBISWorld – Carbon Pricing Dashboard, 2019. World Bank Group

Caveats

The economy-wide net carbon price was derived by dividing fossil fuel subsidies and carbon pricing revenues by total CO2 emissions. This fits well with the subsidies, as these are for fossil fuels, the principal source of CO2. However, some of the carbon pricing instruments from which the revenue was assessed are not only for fossil fuel combustion but apply to other sectors and non-CO2 gases.

 

This indicator was last updated in July 2020

Indicator description

This indicator calculates net, economy-wide average carbon prices and associated net carbon revenue to government. The calculations are based on the value of overall fossil fuel subsidies, the revenue from carbon pricing mechanisms, and the total CO2 emissions of the economy.

Public and Political Engagement

Public and political engagement underpins the foundations of the world’s collective response to climate change, with reductions in global emissions at the speed required by the Paris Agreement depending on engagement from all sectors of society. The indicators in this section track the links between health and climate change in the media, national governments, the corporate sector, and the broader public.

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5.1 Media Coverage of Health and Climate Change

Public and political engagement underpins the foundations of the world’s collective response to climate change, with reductions in global emissions at the speed required by the Paris Agreement depending on engagement from all sectors of society. The indicators in this section track the links between health and climate change in the media, national governments, the corporate sector, and the broader public.

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Headline findings

Although total coverage of climate change increased substantially from 2018 to 2019, the rise was even greater for coverage of health and climate change, which increased by 96% during this period and has considerably increased from 2007 to 2019.

Data sources

– People’s Daily Mandarin edition

– Nexis Uni® database

– Factiva© database

– ProQuest LLC database

Caveats

The selected newspapers cannot be taken to be representative of all media reporting in their countries, and the content analysis does not reflect the ways in which climate change and/or health is reported in the media nor the general messaging. Also, the search terms used are likely to have influenced the types of articles obtained, and databases might return hits of duplicate articles.

 

This indicator was last updated in July 2020.

Indicator description

This indicator has both a quantitative and qualitative component to its tracking of health and climate change in the media. Articles from 2007 to 2019 in 61 newspapers across 36, written in English, German, Portuguese and Spanish were analysed using key word searches within three databases. Additionally, articles in Chinese in China’s People’s Daily were assessed through a process of first trawling through all articles and then searching for keywords in article text. For the qualitative content analysis, this indicator assesses the content of health and climate change in elite press in the USA and India across two key periods in 2019.

5.2 Individual Engagement in Health and Climate Change

Online activity is increasingly being used to understand and drive public and individual engagement, transforming individual access to global knowledge and debates. This indicator tracks individuals’ information-seeking behaviour on Wikipedia in relation to the link between climate change and health.

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Headline findings

Individual information seeking about health and climate change increased by 24% from 2018 to 2019, driven mainly by initial interest in health.

Data sources

Wikimedia Dumps https://dumps.wikimedia.org/other/clickstream/

Caveats

The data the data is not geo-referenced, so it is not possible to infer the location page visits came from. Only English Wikipedia pages were considered in the analysis (approximately 50% of total Wikipedia pages), and while they are accessed globally, it is somewhat biased towards English-speaking countries.

 

This indicator was last updated in July 2020

Indicator description

This indicator measures the number of clicks from health-related Wikipedia articles that lead to visits to climate change-related Wikipedia articles, and the number of visits to climate change-related articles that result in clicks to health-related pages in 2018 and 2019. This “clickstream data” is used as a proxy for the degree to which individuals engage with health and climate change as related issues.

5.3 Coverage of Health and Climate Change in Scientific Journals

Peer-reviewed scientific journals are the premier source of high-quality research that provides evidence used by the media, the government, and the public. This indicator tracks scientific engagement with health and climate change in peer-reviewed journals.

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Headline findings

Between 2007 and 2019, original research on health and climate change increased by a factor of nine, a trend driven by research led by scientists in high-income countries.

Data sources

OVID MEDLINE OVID Embase

Caveats

The methodology provided here enables a quantitative appraisal of the research question. The quality of the data and the specifics of its content are not assessed. However, with the outputs all published in peer-reviewed journals, there is a de facto quality check. For this reason, the indicator does not cover grey literature.

 

This indicator was last updated in July 2020.

Indicator description

This indicator identifies original research articles and research-related articles published from 2007 to 2019 that cover health and climate change topics, using keyword searches for health and climate change in OVID MEDLINE and OVID Embase. It used the comprehensive indexing systems and thesaurus of Medical Subject Headings for MEDLINE and Emtree for Embase and the search strategy was refined for a >90% sensitivity and >50% precision for each database. Articles were geographically organised based on the institution of the first author.

5.4 Government Engagement in Health and Climate Change

Meeting the commitments under the Paris Agreement require accelerated and ambitious interventions from governments across the world. Ensuring these efforts maximise human health and wellbeing begins with these issues being recognised as important areas of concern, and as reasons for change. This indicator tracks references to health and climate change in countries’ Nationally Determined Contributions to the Paris Agreement and in the speeches of global leaders at the United Nations General Debate, the key event for Member States to speak about their nations’ priorities and concerns.

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Headline findings

National governments are increasingly paying attention to health and climate change. Small island developing states are leading this trend at the UN General Debate, and poorer and more climate-vulnerable countries were more likely to reference health in their NDCs, with 95% of least developed countries making these references.

Data sources

– UNFCCC NDC Registry (interim)

– UN General Debate statements (official English versions)

Caveats

There may be cases where governments refer to health and climate change but not the direct linkages between the two. The analyses are based on a narrow range of search terms, which excludes reference to many of indirect links between climate change and health. There also may be rare cases within the NDCs and UNGD statements where the discussion of health and climate change is split over two or more sentences, and where key identifiers for either the health-related category or exposure category are only implied.

 

This indicator was last updated in July 2020

Indicator description

This indicator tracks government engagement in health and climate change in two key forums. It assesses reference to health and climate change as well as their prominence in the text of all available (up until 31st March 2020) first Nationally Determined Contributions by Parties to the Paris Agreement. It also tracks mentions of climate change and health in statements made by national leaders at the UN General Debate, which is part of the annual UN General Assembly, as proxy of high-level political engagement on these two topics as separate and related issues.

5.5 Corporate Sector Engagement in Health and Climate Change

The corporate sector is central to the transition to a low-carbon economy, both through its own behaviour and greenhouse gas emissions and its wider political influence. This indicator tracks engagement with health and climate change in healthcare companies within the UN Global Compact, the world’s biggest corporate sustainability framework.

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Headline findings

In 2019, engagement in health and climate change increased to 24% among health-care companies in the UN Global Compact, although this engagement continues to lag behind that of other sectors.

Data sources

UN Global Compact Communication on Progress reports

Caveats

Only reports that were submitted in English have been considered. This means a little under half of all available reports have been analysed. This analysis is based on a narrow range of search terms, which excludes reference to many of indirect links between climate change and health. Reports may also discuss indirect connections, such as the effect of climate change on agriculture, however, these are not included here.

 

This indicator was last updated in July 2020

Indicator description

UN Global Compact Communication on Progress reports from health and healthcare companies from 2011 to 2019, written in English and publicly available, were assessed for references to health and climate change using key search terms.