An Evaluation of the Impact of Emissions from Airports in Egypt ^†

Abstract

Aircraft emissions are a growing environmental concern due to their contribution to local air pollution and potential health risks, particularly around rapidly expanding airports. In Egypt, rapid urban growth and tourism have driven the construction of new airports, underscoring the need to assess their environmental impacts, particularly those related to aircraft emissions in the surrounding areas. Few studies have assessed aircraft emissions across multiple Egyptian airports, particularly under future capacity and climate scenarios, using dispersion models. This study evaluates the environmental impact of aircraft emissions at four Egyptian airports using the Graz Lagrangian Dispersion Model (GRAL). The analysis accounts for projected increases in airport capacity through 2030 and 2035 and examines how climate change may influence pollutant dispersion. Emissions from 2021 served as a baseline, while future meteorological conditions were simulated with the RegCM4 regional climate model under the RCP4.5 scenario. Results show that maximum daily average carbon monoxide concentrations at Administrative Capital Airport increased from ~24.5 µg/m³ in 2021 to ~100.3 µg/m³ in 2035, while nitrogen dioxide concentrations at El-Meliz Airport rose from ~20.3 to ~47.6 µg/m³. Similar upward trends were observed for sulfur dioxide and particulate matter (PM₁₀), although all simulated values remained below the thresholds established by Egyptian Environmental Law. These findings highlight that continued growth in aviation activity, even without breaching national standards, may contribute to long-term health risks for nearby communities.

1. Introduction

Egypt has witnessed rapid urbanization, tourism expansion, and increased investment in air transport infrastructure, leading to the construction of new airports and the development of existing ones across the country [1], contributing to increased job opportunities, GDP growth, and regional connectivity [2]. However, with the expansion of aviation activity, the environmental impacts of aircraft emissions require careful assessment, particularly on surrounding communities. Assessing how these emissions are dispersed is essential for sustainable airport planning.

Airports are pivotal to economic growth and regional connectivity, but they are also major contributors to local and regional air pollution. Aircraft engines, ground-based service vehicles, fuel handling, and associated infrastructure release a range of pollutants, including nitrogen oxides (NO_x), carbon monoxide (CO), volatile organic compounds (VOCs), sulfur oxides (SO_x), fine particulate matter (PM), and ozone precursors. Many of these pollutants are associated with negative impacts that can extend miles downwind, impacting air quality, human health, and climate [3,4].

Aircraft operations during landing and takeoff cycles have been shown to have a significant impact on local air quality in areas surrounding airports. Several studies at international airports have investigated the contributions of aviation activities to ambient pollution. For example, annual aircraft emissions of nitrogen oxides (NO_x) at Heathrow International Airport were estimated at approximately 15,000 tons [5]. Measurements near Los Angeles International Airport revealed particulate matter concentrations five times higher than normal, extending up to 10 km downwind [6]. At Madrid–Barajas Airport, elevated levels of NO_x, SO₂, CO, and particulate matter were detected near runways, reflecting noticeable impacts from aircraft operations [7], and analyses at Ercan International Airport in Cyprus [8] indicated elevated concentrations of nitrogen oxides and very fine particulate matter near the runways, with measurable health impacts on surrounding communities. This illustrates that the impacts of emissions related to airports are not limited to the runways but can extend to surrounding communities on a regional scale. Exposure to these pollutants remains a health concern, even when measured concentrations fall below legal limits. Long-term exposure to NO₂, PM_2.5, and ozone has been consistently linked to respiratory and cardiovascular diseases [9]. Recent research continues to highlight the importance of airport emissions on local air quality. Ref. [10] demonstrated that at Beijing Daxing International Airport, airport-related NO_x impacts are concentrated near the airport, highlighting increasing concern for surrounding communities as flight operations expand. Ref. [11] showed that aircraft emissions can significantly contribute to urban nitrogen oxide levels near major hubs in China. Ref. [12] emphasized the importance of incorporating atmospheric variability into dispersion models to capture near-surface pollution.

Moreover, climate change adds further complexity, as changes in wind, temperature, and atmospheric stability directly affect the dispersion and accumulation of pollutants. Several modeling studies have shown that shifts in atmospheric regimes can alter near-surface pollutant concentrations in the vicinity of airports [13,14]. For this reason, aviation emissions analyses should consider not only the current climate but also projected future conditions.

In Egypt, a few studies have begun to address the environmental impacts of airports. For example, a recent assessment at Sphinx International Airport combined monitoring, aircraft emission estimates, and dispersion modeling, showing that pollutant levels generally remained within national limits [15]. Similarly, an analysis of Borg El Arab Airport highlighted the importance of carbon reduction strategies in future airport planning [16]. However, studies covering multiple Egyptian airports and projecting the effects of future capacity growth remain limited. To address this gap, the present study evaluates aircraft emissions at four Egyptian airports using the Graz Lagrangian (GRAL) dispersion model. Baseline emissions were determined for 2021 and then projected for 2030 and 2035 to reflect expected capacity growth. Meteorological inputs were extracted from the International Centre for Theoretical Physics (ICTP) RegCM4 model under the RCP4.5 climate scenario.

Unlike previous studies that focused on individual Egyptian airports, this work presents the first integrated assessment of aircraft emissions at four airports using the GRAL dispersion model. It also enhances existing research by incorporating projected capacity growth under a climate change scenario (RCP4.5) to assess future impacts on air quality.

2. Materials and Methods

Dispersion Model: To simulate pollutant dispersion from aircraft operations, we used the Graz Lagrangian Dispersion Model (GRAL, version 20.01; https://gral.tugraz.at, (accessed on 18 December 2019); [17]). GRAL is used in regulatory assessments and scientific studies due to its high spatial resolution (on a few meters) and its capability to accurately represent complex emission sources in urban areas [18,19].

Study Area and Emission Source Description: The analysis focused on a 10 km radius around the center of each airport runway, to capture the impacts not only near the runway but also the surrounding community, which is consistent with previous airport air quality assessments [5,13]. Aircraft emissions were modeled as the primary source, represented at 5 m above ground level, 17 m wide, and extending along the full length of the runway as listed in

Table 1. The four studied airports, their latitudes and longitudes, and the runway length used in GRAL dispersion model.

Airport Name	Latitude (N)	Longitude (E)	Runway Length Used in Model (Meters)
New Administrative Capital	30.07	31.84	3076
Sphinx	30.10	30.88	4103
El-Meliz (Bardawil)	30.40	33.15	4793
Bernice	23.91	35.46	3483

. Since this study focuses on the impact of aircraft on areas surrounding airports, only the landing and takeoff (LTO) cycle was considered in the simulations, during which engines operate close to the ground and produce the highest emission rates. The assumed release height here (5 m above ground) is consistent with the adopted heights in previous airport dispersion studies [5,20].

Meteorological Data: Meteorological data used by GRAL were simulated by running the ICTP regional climate model (RegCM, version 4.7; [21]), driven by the MPI-ESM-MR global climate model under the RCP4.5 scenario. The RegCM outputs of wind speed and direction, and surface net radiation (which affected by clouds and other meteorological parameters) were used to calculate the stability classes required by GRAL besides the wind data. Simulations were performed for the years 2021, 2030, and 2035. In addition, annual wind roses were plotted for each airport to illustrate the dominant wind patterns applied in the dispersion modeling.

Emission Estimation Approach: Aircraft emissions were estimated based on operational data from several aircraft types in 2021, which was taken as the reference year. These baseline emissions were assumed from an internal dataset provided by the airports’ authority. A similar approach, relying on operational data and modeled emissions, has been adopted in previous airport studies (e.g., [15]). For 2030 and 2035, emissions were scaled proportionally to anticipated increases in airport capacity relative to the 2021 baseline. In the absence of detailed hourly flight movement data, the calculated emissions were assumed to be uniformly distributed across the 24-h period throughout the year, an assumption consistent with other dispersion studies of airport sources (e.g., [5,20]). The estimated emission rates for each pollutant are illustrated in

Table 2. The calculated emission rate of each pollutant entered into the dispersion model each year.

Pollutant	2021 (kg/h)	2030 (kg/h)	2035 (kg/h)
Nitrogen Oxides (NO2)	4.59	13.77	18.36
Carbon Monoxide (CO)	3.63	10.89	14.52
Sulfur Dioxide (SO2)	0.80	2.39	3.19
Particulate Matter (PM10)	0.05	0.14	0.19

.

As shown in

Table 3. Comparison of used pollutant emissions in the current study with international airports (kg/h).

Pollutant	The Studied Emissions (2021)	Dubai International (2021)	Heathrow (London) (2021)
Nitrogen Oxides (NO2)	4.59	9.0	7.8
Carbon Monoxide (CO)	3.63	8.5	6.2
Sulfur Dioxide (SO2)	0.80	1.2	1.0
Particulate Matter (PM10)	0.05	0.3	0.2

, the current study’s calculated emissions for the four new Egyptian airports in 2021 are lower than those reported for major international airports such as Dubai [22] and Heathrow [23], due to the significant differences in annual passenger volumes and aircraft movements between the study airports and these international airports. Among the pollutants, nitrogen oxides and carbon monoxide exhibit the highest emission rates, consistent with combustion-related processes during takeoff and landing. The relatively low PM₁₀ and SO₂ values indicate the limited sulfur content of jet fuel and the actual fuel combustion efficiency. This comparison demonstrates that although the study airports currently emit less pollution than major global hubs, continued air traffic growth may narrow this gap in the future. This highlights the importance of proactive monitoring and emissions management strategies as traffic levels increase in the future.

Regulatory Benchmarks: To evaluate the significance of predicted concentrations, modeled results were compared against the Egyptian ambient air quality limits [24] and the World Health Organization (WHO) guideline values [9].

Table 4. Egyptian ambient air quality standards, as defined by Environmental Protection Law No. 4 of 1994 (amended by Law No. 9 of 2009), compared with WHO guidelines (values expressed in µg/m³).

Pollutant	Averaging Time	Egyptian Limit (µg/m3)	WHO Guideline Value (µg/m3)
Nitrogen Dioxide (NO2)	1 h 24 h	300 150	200 40
Carbon Monoxide (CO)	1 h 8 h	30,000 10,000	10,000 4000
Sulfur Dioxide (SO2)	1 h 24 h	300–350 125–150	500 125
Particulate Matter (PM10)	24 h	150	45

summarizes the reference standards used in this study. The WHO guidelines are generally more stringent than the Egyptian standards, particularly for nitrogen oxides and fine particulate matter. Including both sets of standards ensures that the assessment reflects national regulatory requirements while being consistent with international health recommendations. This approach allows for a balanced interpretation of the predicted concentrations and supports comparison with future regional and global studies.

3. Results

3.1. Administrative Capital Airport

Figure 1 (left panel) shows the wind roses for 2021, 2030, and 2035, respectively, based on the wind data from RegCM4.7 simulations. The prevailing wind direction at the airport is predominantly northeasterly, with higher wind speeds extending into northwesterly and southwesterly directions in 2030 and 2035. The right panels present the GRAL dispersion model simulations of the highest daily average concentrations of carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and particulate matter (PM₁₀), respectively. In 2021, maximum daily averages near the runway are ~24.5 µg/m³ for CO, ~17.9 µg/m³ for NO₂, ~4.3 µg/m³ for SO₂, and ~0.28 µg/m³ for PM₁₀, decreasing rapidly with distance. With increased air traffic, concentrations rise steadily across the study period, reaching ~100.3 µg/m³ for CO, ~48.0 µg/m³ for NO₂, ~18.0 µg/m³ for SO₂, and ~1.0 µg/m³ for PM₁₀ by 2035. In all cases, pollutant concentrations are highest along the runway and decline gradually outward.

3.2. Sphinx Airport

At Sphinx Airport, as shown in the left panel of Figure 2, the wind during 2021–2035 is dominated by northeasterly to northwesterly flows. The dispersion simulations indicate that pollutant concentrations are consistently highest along the runway, with values decreasing gradually outward into the surrounding area, as shown in the columns 2–5 of Figure 2. For CO, daily averages rise from ~21.6 µg/m³ in 2021 to ~141 µg/m³ in 2035, while minimum values increase from ~0.1 to ~1 µg/m³. NO₂ shows a similar trend, increasing from ~16.8 µg/m³ in 2021 to ~100 µg/m³ in 2035, with background levels ranging from 0.07 to 0.5 µg/m³ in the remote regions from the runway. SO₂ concentrations grow from ~3.9 µg/m³ in 2021 to ~20 µg/m³ in 2035, with minima around 0.02–0.1 µg/m³. PM₁₀ remains comparatively lower, but still increases from ~0.32 µg/m³ in 2021 to ~1.5 µg/m³ in 2035, with minimum values near 0.01 µg/m³.

3.3. El-Meliz Airport

Figure 3 shows the results at El-Meliz Airport, where the prevailing winds during 2021–2035 are mainly northerly to northeasterly, with occasional southwesterly flows. CO levels start with a maximum daily average of ~31.8 µg/m³ in 2021, dropping to ~0.12 µg/m³ further away, whereas by 2035 CO concentrations increase with projected traffic growth, reaching ~123.6 µg/m³ near the runway, while minimum values rise slightly to ~0.48 µg/m³. NO₂ follows the same trend, with peak concentrations rising from ~20.3 µg/m³ in 2021 to ~47.6 µg/m³ in 2035, while the lowest levels range between ~0.08 and 0.19 µg/m³. SO₂ shows relatively high values, with maxima of ~29.0 µg/m³ in 2021 and decreased to ~25.8 µg/m³ in 2035, and background or the lowest values remaining close to 0.1 µg/m³. PM₁₀ is much lower in magnitude but still increases with time, from ~0.28 µg/m³ in 2021 to ~1.1 µg/m³ in 2035, while the lowest values remain around 0.01 µg/m³.

3.4. Bernice Airport

At Bernice Airport, as shown in Figure 4, winds between 2021 and 2035 are predominantly northwesterly. Pollutant dispersion patterns follow this wind regime, spreading mainly southeast of the runway. CO shows the highest daily average concentrations near the runway, around 30.2 µg/m³ in 2021, decreasing to 0.12 µg/m³ farther away. With increased traffic, levels rise to about 117.7 µg/m³ by 2035, with minimum values near 0.46 µg/m³. NO₂ displays a similar pattern, reaching ~20.2 µg/m³ in 2021 and up to 49.1 µg/m³ in 2035, while minimum concentrations increase from 0.08 to 0.19 µg/m³. SO₂ concentrations peak at ~4.8 µg/m³ in 2021 and ~20 µg/m³ by 2035, with minima between 0.02 and 0.08 µg/m³. PM₁₀ is more dispersed, with concentrations of ~0.27 µg/m³ in 2021 rising to ~1.1 µg/m³ in 2035, while minimum levels remain near 0.01 µg/m³.

4. Conclusions

This study examined the dispersion of aircraft-related emissions at four Egyptian airports (Administrative Capital, Sphinx, El-Meliz, and Bernice) using the GRAL dispersion model, with baseline emissions for 2021 and projected scenarios for 2030 and 2035 based on the RCP4.5 pathway. The results show that average daily concentrations of carbon monoxide, nitrogen dioxide, sulfur dioxide, and fine particulate matter (PM₁₀) are expected to rise steadily with increasing traffic demand. By 2035, modeled peak concentrations of carbon monoxide (Sphinx) reached approximately 141 µg/m³, nitrogen dioxide (Sphinx) reached approximately 100 µg/m³, sulfur dioxide (El-Meliz) reached approximately 26 µg/m³, and PM₁₀ reached approximately 1.5 µg/m³ at all studied airports. Despite these increases, all concentrations remain below the limits permitted by Egyptian environmental law and below the World Health Organization guideline values, indicating that under the scenario studied, the expansion of airport operational capacity with increased aircraft numbers is not expected to lead to regulatory exceedances in the surrounding areas.

However, the continued upward trend highlights the need for proactive mitigation measures. Even pollutant levels below legal limits may pose health risks with long-term exposure, particularly for communities living near airports. Measures such as improving fuel efficiency, promoting cleaner technologies, and strengthening monitoring of airport-related air quality are recommended to minimize potential future impacts. In future planning, adopting low-sulfur or alternative aviation fuels can help reduce sulfur dioxide and fine particulate matter emissions. Operational strategies, such as optimizing taxi time and reducing engine idle time, can further reduce CO and NO₂ emissions near the runways. Additionally, establishing local air quality monitoring stations around airports will provide continuous data to support regulatory compliance. These combined measures will help maintain air quality within safe limits as air traffic continues to grow.