How to Measure Climate Impacts
Models are used to estimate aviation’s impacts on climate change. One type of model calculates how greenhouse gas emissions change the energy balance in the atmosphere. Another type of model goes one step further and calculates the temperature change that will be caused by the change in energy balance. The next types of models are even more complex and estimate how the predicted temperature change will cause changes in physical and biological systems (e.g. rainfall patterns or biodiversity) and how much these changes will cost human society (e.g. effects on GDP).
The results of the latter models have much higher uncertainty and depend to a much larger degree on assumptions and value-related decisions than the results of models that calculate physical changes, such as energy balance or temperature difference. Yet such impact models are often more policy-relevant than purely physical models. In other words, knowing the impacts on an ecosystem and its societal costs is more relevant and more important for risk assessment and policy actions than just understanding the radiative forcing of GHG emissions. But because we have to make many more assumptions when determining climate costs than when calculating radiative forcing, the results are more uncertain, and are shaped by underlying political or ethical decisions (e.g. discount rate or damage function). This trade-off between accuracy and relevance is also reflected in the many different approaches that have been used to account for climate impacts from aviation (see Metrics for Aviation Climate Impacts).
These different modeling approaches have all been used in calculating the contribution of aviation to climate change. In order to better understand the advantages and drawbacks of each of these approaches it is useful to break down the process of modeling climate change into the following consecutive steps (Figure 1):
Figure 1: Measuring Climate Impacts
This figure is a simplified illustration of how climate impacts are modeled and estimated. The arrows on the left indicate the fields of expertise required to calculate the climate change parameters (blue boxes in the middle). The arrow to the right indicates theincrease in assumptions to calculate or model these parameters as we progress down the list. Results therefore become more uncertain. Yet relevance for policy making decisions increases as we move down the chain of climate change parameters. (A similar graph can be found in Fuglestvedt et al., 2003.)
Step 1: Calculating Greenhouse Gas Emissions from Human Activities
Humans emit greenhouse gases (GHGs) and other warming agents into the atmosphere through burning of fossil fuels, industrial and agricultural processes, and deforestation. These anthropogenic (human-induced) emissions raise the concentrations of these gases in the atmosphere, contributing to climate change. To calculate emissions from transportation, we need to know the type of fuel burned (e.g. gasoline), the greenhouse gas content of the fuel (e.g. 21 pounds of CO2 per gallon of gasoline) and the amount of fuel burned (e.g. number of gallons).
Step 2: Calculating Atmospheric Greenhouse Gas Concentrations
To ascertain the atmospheric concentration of a particular GHG, we can either directly measure it by taking air samples, or calculate concentrations using models. In order to calculate the concentration of a greenhouse gas in the atmosphere, we need to know how much was emitted, how long the gas remains in the atmosphere, how much of it is absorbed by water and land, and how strong a greenhouse gas it is. Atmospheric concentrations are usually expressed in parts per million (ppm) or parts per billion (ppb); for example, the global atmospheric CO2 concentration has risen from approximately 280ppm to 385ppm in the last approximately 250 years.
Step 3: Determining Radiative Forcing (RF)
Once we know the atmospheric concentration of GHGs, we can calculate their impact on the global energy balance. Greenhouse gases trap solar energy (i.e. heat) in the atmosphere. The term ‘Radiative Forcing’ expresses the capacity of greenhouse gases to alter the temperature (energy balance) of the atmosphere (see Radiative Forcing). To calculate radiative forcing, we need to know the physical properties of the gas (i.e. how much energy a molecule can absorb) and its atmospheric concentration. Radiative forcing is expressed in watts per square meter (W/m2).
Step 4: Modeling Climate Response
Once we have calculated the radiative forcing of GHGs, we can model how the Earth will react to the additional energy the gases trap in the atmosphere. The term ‘Climate Response’ refers to Earth’s physical and chemical responses to changes in the atmospheric energy balance, such as changes in average global temperature and the resultant changes in precipitation patterns.. To calculate climate responses, we need to know not only the radiative forcing of greenhouse gases but also how natural systems respond to these changes in the energy balance. This requires in-depth knowledge of highly complex systems. In order to model such systems, we also need to understand the following:
The term ‘climate feedback’ refers to an initial climate response that triggers a second process that in turn intensifies or reduces the initial response. A positive feedback intensifies the original process, and a negative feedback reduces it. An example of a positive feedback is the albedo effect in the Arctic: if Arctic ice melts due to warmer temperatures, the white snow surface is replaced by a much darker ocean surface. The dark ocean absorbs much more heat than white ice and snow surfaces. The newly-exposed dark surfaces will therefore lead to additional warming. Including climate feedbacks in climate calculations increases the accuracy of climate models because it better describes how much warming or cooling a GHG will cause. To express the potential of GHG emissions to cause climate feedbacks, the term ‘climate efficacy’ is used:
Two greenhouse gases with the same radiative forcing do not necessarily lead to the same temperature increase. The term ‘climate efficacy’ is defined as “the global temperature response per unit forcing relative to the response to CO2 forcing” (Hansen et al., 2005). Climate efficacy expresses the difference in effectiveness of different GHGs in causing warming or cooling. In other words, climate efficacy expresses the initial climate response to a GHG emission as well as the secondary climate feedbacks that the GHG causes. As we will demonstrate, many of the current models used for aviation climate calculations do not take climate efficacy into account.
The term ‘climate sensitivity’ expresses how responsive the climate is to added forcing from GHG emissions. In other words, if there are strong positive climate feedbacks to GHG emissions, the climate sensitivity is higher than if there are no such feedbacks. Or, expressed in terms of climate efficacy: if GHG emissions have a high climate efficacy, they will lead to more warming, which in turn translates into higher climate sensitivity. More technically, it refers to the change in surface air temperature following a change in radiative forcing. The higher the climate sensitivity, the more the climate changes in response to GHG emissions. Climate sensitivity is expressed in degrees Celsius per watts per square meter (°C/Wm2).
Step 5: Modeling Climate Impacts
The term ‘climate impact’ refers to ecosystem changes due to climate responses. Examples include: change in species composition and extinction, increase in vector-borne diseases, and impacts on agricultural crops. These effects can be quantified in many ways; for example, number of species threatened with extinction or number of people displaced by sea level rise.
Step 6: Modeling Climate Damages or Costs
The term ‘climate damages or costs’ refers to climate impacts expressed in economic terms. Climate damages are usually expressed in monetary units, such as property lost to sea-level rise or flooding, medical costs of heat waves and disease, etc. Many assumptions are required to calculate such costs, and to discount them to present economic values; many important climate damages, such as loss of human life, cannot easily be expressed in monetary terms . Simple economic models frequently express all climate damages through a damage function, assuming a mathematically simple relationship between climate changes (measured by temperature increase) and the total value of associated damages. The choice of damage function relies on scientific and non-scientific assumptions and therefore leads to results that are to a large extent value-based. (For more, see Ackerman, 2009.)