**2.2 Results and discussion**

From Eq. (2), two factors cause air density fluctuations: temperature changes and mixing in tracers of different molecular weight to the average molecular weight of the air. Earth atmosphere is dominated by the "dry" inactive components (N2, O2, CO2, etc.). With heat intake, the primary response is expanding in volume and, subsequently, an increased mass center. During the past half century, on average, there is a 30 m lift of the mass center, indicating that the mass is now distributed in a thicker (larger depth) layer (thus reduced density at lower levels). Heating caused expansion is just one effective means that decreases air density throughout the entire tropospheric atmosphere. In-taking of lighter molecules

#### **Figure 1.**

*Changes in near-surface air density for the period 1900–2100 as simulated by 24 climate models over six selected world airports. Near-surface air density estimated from NCEP/NCAR reanalyses is shown as red bold lines. The upper and lower bounds among the 24 climate models are shown as brown lines. The analyses were performed on monthly data and averaged to annual values (actual plotted). As with all land-ocean-ice sheet fully coupled climate model outputs, the exact timing is hard to pinpoint. Only the statistical properties and long-term averages would resemble reality.*

#### *Climate Warming and Effects on Aviation DOI: http://dx.doi.org/10.5772/intechopen.86871*

Klimarechenzentrum (DKRZ) Data Distribution Centre (http://www.ipcc-data.org/ sim/gcm\_monthly/AR5/Reference-Archive.html). For models providing multiple perturbation runs, only *r*1*i*1*p*1 runs are used. To examine whether the historical runs from the climate models are close to reality in their simulated air density, NCEP/NCAR reanalyses are used as observations. The monthly NCEP/NCAR reanalysis [12] data are obtained from the Earth System Research Laboratory website: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.pressure. html. Specific humidity provided by reanalyses can be converted into specific

From Eq. (2), two factors cause air density fluctuations: temperature changes and mixing in tracers of different molecular weight to the average molecular weight of the air. Earth atmosphere is dominated by the "dry" inactive components

(N2, O2, CO2, etc.). With heat intake, the primary response is expanding in volume and, subsequently, an increased mass center. During the past half century, on average, there is a 30 m lift of the mass center, indicating that the mass is now distributed in a thicker (larger depth) layer (thus reduced density at lower levels). Heating caused expansion is just one effective means that decreases air density throughout the entire tropospheric atmosphere. In-taking of lighter molecules

*Changes in near-surface air density for the period 1900–2100 as simulated by 24 climate models over six selected world airports. Near-surface air density estimated from NCEP/NCAR reanalyses is shown as red bold lines. The upper and lower bounds among the 24 climate models are shown as brown lines. The analyses were performed on monthly data and averaged to annual values (actual plotted). As with all land-ocean-ice sheet fully coupled climate model outputs, the exact timing is hard to pinpoint. Only the statistical properties and*

humidity before applying Eq. (2).

*Environmental Impact of Aviation and Sustainable Solutions*

**2.2 Results and discussion**

**Figure 1.**

**178**

*long-term averages would resemble reality.*

(H2O has smaller molar mass than N2 and O2, the dominant constituents of dry air) is another effective way of reducing air density. Although from Clausius-Clapeyron equation [13] warm air has more capacity of holding moisture, it still is debatable whether earth atmosphere actually gains mass, because the hydrological cycle also tends to intensify [14–16], through facilitating interhemispherical moisture exchange [17] and destabilizing local stratification profile [15, 16]. If precipitation increases more than evaporation, there still is a net mass loss for atmosphere. Interestingly, all existing reanalysis datasets show no statistically significant changes in global total air mass during their respective reanalyses period. This implies that the net water vapor input into atmosphere is globally delicately balanced between geographic regions.

Applying the formula as in Eq. (2) to climate model-simulated (under RCP 8.5, a strong emission scenario) near-surface pressure, temperature, and humidity, near-surface air density is estimated over the globe. The same formula also is used on the NCEP/NCAR reanalysis data. Density variations over 1900–2100 for six global airports are shown in **Figure 1**, as representatives. All 27 climate models unanimously indicate that all six locations experienced salient density decreases. Significant inter-model spread exists but started well before the year 1900 and should be ascribed to model systematic biases/drifts. For each climate model, the amount of density decrease easily exceeds the natural interannual variability magnitude. Geographically, high-latitude regions (e.g., Moscow) have larger

#### **Figure 2.**

*GFDL-CM3-simulated near-surface air density (kg/m<sup>3</sup> ) averaged over two periods: (2005–2025) (a) and (2081–2100) (b), under RCP 8.5 scenario assumption. The density differences between these two periods are shown in (c), with corresponding percentage changes shown in (d).*

interannual density variability but also generally experiences larger density decreases over the simulated 200 years. The linear trends of decrease estimated based on the reanalyses are close to model simulation. All 27 climate models show high degree of consensus in the simulated air density changes (e.g., **Figure 2** for GFDL-CM3).

did not pass the *t*-test can be disregarded, because a very limited number of airports are marine-based. Unlike the percentage changes, the tropical region, especially the intertropical convergence zone (ITCZ, an area of low pressure and convergence of trade winds), had the lowest *P*-value, meaning that the changes over the region are most likely to be statistically significant. From Eq. (2), air density is co-controlled by temperature change and vapor content change. The temperature changes over tropical regions are smaller than over the high-latitude regions. What make the changes over tropical regions statistically more significant are the relatively small

Although air density values simulated by the 27 climate models, when compared with those derived from the NCEP/NCAR reanalysis data, have systematic biases, the linear trends derived from models agree very well with the reanalyses. This indicates that for estimating payload decreases as the climate warms, the density time series can be normalized by their average value over a control period, say 1900–1920. For a specific model, differences in the values of the normalized density time series from unity are the percentage reductions of NSAD and MTOW. If one further assumes an invariant unavoidable load (weight of an empty airplane), the decrease of MTOW also is the decrease of maximum payload. Air density changes estimated from all climate models were interpolated to the same spatial resolution as MRI-CGCM3. **Figure 4** shows the MTOW changes between the two 20-year periods (2005–2025 and 2080–2100). Globally, the changes can reach 5% reduction for some high-latitude and high-elevation airports. For the busy North Atlantic Corridor (NAC), the reduction generally is greater than 1%. This has important economic significance. For the Boeing 747-400, this means a net load reduction of about 3969 kg (**Table 2**), approximately the passenger and luggage weight of 25 passengers, or a 6% reduction in its full passenger carrying capacity. Actual payload equivalence of a 1% reduction in MTOW for other types of aircraft is listed in **Table 2**. Because the ratio of unavoidable load to its maximum effective payload varies for different aircraft, the general reduction in net payload over NAC varies from 5 to 8.3% for all the aircraft types considered. Some Northern Hemisphere

*The estimated ensemble mean decrease in aircraft maximum takeoff total weight (MTOW), as a percentage, based on air density changes simulated by 27 climate models under the RCP 8.5 scenario. The near-surface density from each climate model was normalized by its mean value over 2005–2025 (the control period). Then a bilinear interpolation scheme was used to interpolate on to MRI-CGCM3's horizontal resolution. An ensemble average was taken over the climate models. The reduction can reach 5% over Northern Europe. For the North*

*Atlantic Corridor (NAC), a 1% reduction in MTOW was reached during the 75-year span.*

changes in air density, for all time scales.

*Climate Warming and Effects on Aviation DOI: http://dx.doi.org/10.5772/intechopen.86871*

**Figure 4.**

**181**

Air density changes are a gradual process over the years. To quantitatively examine if the density changes were statistically significant, a *t*-test was performed over the two 20-year annual density time series (2005–2025 and 2081–2100). In **Figure 3**, the *t*-value (right panels) and corresponding *P*-values (left panels, for a DoF of 38) are presented (six climate models are shown to demonstrate this). Under the RCP 8.5 scenario, most global regions pass the 95% confidence interval. The signal-to-noise ratio is low only for very limited oceanic regions off the southern tip of Greenland and some sectors of the Southern Ocean. The oceanic region off southern Greenland collocates with the deep-water formation region of the North Atlantic meridional overturning circulation (MOC). Further investigation indicates that the lack of a decrease in density is due to a weakened MOC that places less moisture into the atmosphere. Regionally, the air becomes drier and heavier. On the other hand, warming reduces the air density. These two canceling factors make the net reduction in density statistically insignificant or, when the moistening effect wins out, may even increase the air density. For this study, the oceanic regions that

#### **Figure 3.**

*A t-test was performed for near-surface air density (simulated under RCP 8.5 scenario) annual time series over two periods (2005–2025) and (2080–2100). Sophisticated modern climate models show consensus on the geographical patterns of the P-value (left panels) and t-values (right panels). Except for some oceanic regions off the southern tip of Greenland and some portions of the Southern Oceans, most global regions passed the 95% confidence interval, for a DoF of 38. Tropical regions, especially over the intertropical convergence zone (ITCZ), experienced the most significant density decreases. The oceanic region off southern Greenland collocates with the region of deep-water formation of the North Atlantic meridional overturning circulation (MOC).*

#### *Climate Warming and Effects on Aviation DOI: http://dx.doi.org/10.5772/intechopen.86871*

interannual density variability but also generally experiences larger density decreases over the simulated 200 years. The linear trends of decrease estimated based on the reanalyses are close to model simulation. All 27 climate models show high degree of consensus in the simulated air density changes (e.g., **Figure 2** for

*Environmental Impact of Aviation and Sustainable Solutions*

Air density changes are a gradual process over the years. To quantitatively examine if the density changes were statistically significant, a *t*-test was performed over the two 20-year annual density time series (2005–2025 and 2081–2100). In **Figure 3**, the *t*-value (right panels) and corresponding *P*-values (left panels, for a DoF of 38) are presented (six climate models are shown to demonstrate this). Under the RCP 8.5 scenario, most global regions pass the 95% confidence interval. The signal-to-noise ratio is low only for very limited oceanic regions off the southern tip of Greenland and some sectors of the Southern Ocean. The oceanic region off southern Greenland collocates with the deep-water formation region of the North Atlantic meridional overturning circulation (MOC). Further investigation indicates that the lack of a decrease in density is due to a weakened MOC that places less moisture into the atmosphere. Regionally, the air becomes drier and heavier. On the other hand, warming reduces the air density. These two canceling factors make the net reduction in density statistically insignificant or, when the moistening effect wins out, may even increase the air density. For this study, the oceanic regions that

*A t-test was performed for near-surface air density (simulated under RCP 8.5 scenario) annual time series over two periods (2005–2025) and (2080–2100). Sophisticated modern climate models show consensus on the geographical patterns of the P-value (left panels) and t-values (right panels). Except for some oceanic regions off the southern tip of Greenland and some portions of the Southern Oceans, most global regions passed the 95% confidence interval, for a DoF of 38. Tropical regions, especially over the intertropical convergence zone (ITCZ), experienced the most significant density decreases. The oceanic region off southern Greenland collocates with the region of deep-water formation of the North Atlantic meridional overturning circulation (MOC).*

GFDL-CM3).

**Figure 3.**

**180**

did not pass the *t*-test can be disregarded, because a very limited number of airports are marine-based. Unlike the percentage changes, the tropical region, especially the intertropical convergence zone (ITCZ, an area of low pressure and convergence of trade winds), had the lowest *P*-value, meaning that the changes over the region are most likely to be statistically significant. From Eq. (2), air density is co-controlled by temperature change and vapor content change. The temperature changes over tropical regions are smaller than over the high-latitude regions. What make the changes over tropical regions statistically more significant are the relatively small changes in air density, for all time scales.

Although air density values simulated by the 27 climate models, when compared with those derived from the NCEP/NCAR reanalysis data, have systematic biases, the linear trends derived from models agree very well with the reanalyses. This indicates that for estimating payload decreases as the climate warms, the density time series can be normalized by their average value over a control period, say 1900–1920. For a specific model, differences in the values of the normalized density time series from unity are the percentage reductions of NSAD and MTOW. If one further assumes an invariant unavoidable load (weight of an empty airplane), the decrease of MTOW also is the decrease of maximum payload. Air density changes estimated from all climate models were interpolated to the same spatial resolution as MRI-CGCM3. **Figure 4** shows the MTOW changes between the two 20-year periods (2005–2025 and 2080–2100). Globally, the changes can reach 5% reduction for some high-latitude and high-elevation airports. For the busy North Atlantic Corridor (NAC), the reduction generally is greater than 1%. This has important economic significance. For the Boeing 747-400, this means a net load reduction of about 3969 kg (**Table 2**), approximately the passenger and luggage weight of 25 passengers, or a 6% reduction in its full passenger carrying capacity. Actual payload equivalence of a 1% reduction in MTOW for other types of aircraft is listed in **Table 2**. Because the ratio of unavoidable load to its maximum effective payload varies for different aircraft, the general reduction in net payload over NAC varies from 5 to 8.3% for all the aircraft types considered. Some Northern Hemisphere

#### **Figure 4.**

*The estimated ensemble mean decrease in aircraft maximum takeoff total weight (MTOW), as a percentage, based on air density changes simulated by 27 climate models under the RCP 8.5 scenario. The near-surface density from each climate model was normalized by its mean value over 2005–2025 (the control period). Then a bilinear interpolation scheme was used to interpolate on to MRI-CGCM3's horizontal resolution. An ensemble average was taken over the climate models. The reduction can reach 5% over Northern Europe. For the North Atlantic Corridor (NAC), a 1% reduction in MTOW was reached during the 75-year span.*


work persistently year-round and there is no easy way to circumvent or ameliorate them. We, however, agree with Ref. [19] that aviation industry still has technical room to cope with the detrimental effects from climate warming, perhaps at the extra costs of maintenance, passenger comfort, and may even require relaxation of

Aviation fuel efficiency is underpinning recent contest between aviation engine makers—using higher bypass engines and improving higher fuel-burning temperature. Aside from technical challenges, further improvements in fuel-burning efficiency may also have safety consequences. In the following discussion, a normal seven-stage flight profile (these are A, start and taxi to runway; B, takeoff and initial climbing; C, climbing to cruising altitude; D, en route cruising; E, descent; F, approach (includes 8-minute holding at 1500 ft. approach and landing); and G, taxi to docking) is considered (**Figure 5**). **Figure 5** also shows the typical fuel-burning rates at different stages of a commercial airplane engine.

In this subsection, we start from the theoretical expression of the total work an aircraft needs to perform from the origin airport to the destination airport. Another aspect of the fuel efficiency issue is related to the second law of thermodynamics. All airplane engines are thermal engine. Increased environmental temperature always is detrimental for thermal efficiency. This is directly related to the fuel costs

of civil aviation. With changed atmospheric thermal structure, the aircraft's mechanical efficiency may also vary; suppose the same FAA regulation is in position. All components that are sensitive to climate change are investigated and quantitatively from climate model simulations under the RCP 4.5 emission

During different stages of flying, the force balance situation on an aircraft is different. At the takeoff and climbing stages, there are vertical and forward accelerations. The vertical component of thrust aids the lift in overwhelming gravity. Similarly, the horizontal component of thrust also overwhelms drag. At cruising

*Typical flight profile of an aircraft and the fuel-burning rate in each stage. Except the cruising stage, other six*

*stages last from 10 to 40 minutes only. In all, cruising stage is the most fuel-consuming stage.*

**3. Adverse effects on civil fuel efficiency from a warmer climate**

aviation code.

*Climate Warming and Effects on Aviation DOI: http://dx.doi.org/10.5772/intechopen.86871*

scenario—a more likely scenario.

**3.1 Methods and data**

**Figure 5.**

**183**

#### **Table 2.**

*Actual payload equivalence of a 1% reduction in near-surface air density (NSAD). Percentages of maximum payload equivalence are shown in parenthesis.*

high latitudes have a 5% decrease in NSAD or MTOW. Considering that a 1% reduction in MTOW corresponds to a 2% (for larger aircraft such as a Boeing 747-800 or an An-24) to 3.6% (for small aircrafts such as an Embraer ERJ-145) reduction in effective payload, the 5% reduction in MTOW means a 8.5–19% reduction in effective payload year-round. As we stated earlier, at the costs of extra maintenance, aircraft still can operate with the manufacturer-labeled MTOW, which is lower than MTOW, under the unfavorable condition of warming. There may be no apparent passenger or cargo reduction. However, there will be hidden extra costs from a warming atmosphere.

#### **2.3 Discussion**

Based on the diagnosis of stresses (and forces) exerted on aircraft, a suitable invariant entity was identified for investigating climate change effects on aviation payload. Assuming no changes in technical aspects of aircraft and no changes to FAA regulations on takeoff performance, near-surface air density is the single most significant atmospheric parameter. Reanalyses data indicated clearly that the Earth's atmosphere had expanded in volume in the past half century.

Consequently, the near-surface air density experienced significant decreases globally. The 27 climate models showed a high level of consensus in simulated nearsurface air density variations. The ensemble mean of their twenty-first century simulations in NSAD trends was used to examine future reduction to effective payload. In line with Ref. [18], our study aimed to illustrate the potential for rising temperatures to influence weight restriction at takeoff stage. All technical aspects as commented on by Ref. [19] were assumed to be invariants during the analyses period. The simple fact that during extreme hot weather in summertime cargo airplanes have to reduce the effective payload indicates the validity of such analyses. The difference found with seasonal cycle is that these superimposed effects

#### *Climate Warming and Effects on Aviation DOI: http://dx.doi.org/10.5772/intechopen.86871*

work persistently year-round and there is no easy way to circumvent or ameliorate them. We, however, agree with Ref. [19] that aviation industry still has technical room to cope with the detrimental effects from climate warming, perhaps at the extra costs of maintenance, passenger comfort, and may even require relaxation of aviation code.
