Post-War Air Quality Index in Mosul City, Iraq: Does War Still Have an Impact on Air Quality Today?

Abstract

The air quality in Mosul was adversely affected both directly and indirectly during and after the conflict phase, spanning from the occupation to the liberation of the city from ISIS (2014–2017). Direct impacts included the ignition of oil fields and sulphur deposits, as well as the use of military weapons and their propellants. Indirectly, the air quality was also compromised by various other factors negatively affecting the quality due to excessive emission levels of air pollutants, such as particulate matter (PM), sulphur dioxide (SO₂), nitrogen dioxide (NO₂) and other toxic gases. Six important locations in the city of Mosul were selected, and the concentrations of the parameters PM2.5, PM10, formaldehyde (HCHO), total volatile organic compounds (TVOC), NO₂ and SO₂ were determined at monthly intervals during the year 2022. The sites were selected both according to their proximity and their specific distance from the direct conflict zone. The aim was to assess the present pollutant levels based on WHO guidelines and to compare the results with previous pre-war studies to understand the long-term war impact on air quality. The results showed that the annual average values of PM2.5, PM10 and NO₂ were above the WHO limits at all locations throughout the year. In contrast, the annual average values of TVOC, HCHO and SO₂ were within the limits in the hot months but exceeded them in the cold months (December to March), which can be attributed to the use of heating material in winter. Two sites revealed higher pollution levels than the others, which can be attributed to their proximity to the devastated areas (conflict zones), high traffic density and a high density of power generators. These factors were further exacerbated by post-war migration from the destroyed and unsafe areas. Thus, in addition to the short-term effects of burning oil fields and sulphur deposits, as well as airborne weapon emissions, the increase in traffic, the use of decentralized power generators, and the higher demand for heating oil, progressive desertification due to deforestation and the destruction of extensive green areas, as well as increasing and unaddressed environmental violations in general, can be held responsible for declining air quality in the urban area. This work should be considered as preliminary work to emphasise the urgent need for conventional air quality monitoring to consolidate air quality data and monitor the effectiveness of different approaches to mitigate war-related air quality deterioration. Possible approaches include the implementation of air purification technologies, the preservation of existing ecosystems, the replacement of fossil energy sources with renewable energy options, proactive and sustainable urban planning and enforcing strict air quality regulations and policies to control and reduce pollution levels.

1. Introduction

1.1. Air Pollution During the War (Direct Impact)

During armed conflicts, direct pollution of the environment is mainly used by the conflict parties to weaken the enemy quickly, particularly in the case of air pollution [1]. Direct air pollution includes dust emissions from destroyed buildings, fires and emissions of air pollutants caused by ammunition explosions [2]. However, most direct war-related impacts on air quality are usually temporary in nature. Air pollution is usually transferred to other media, especially soil, water and eventually the biosphere as the progressive deposition of atmospheric pollutants increases the load of the compartments beyond the normal levels or ecotoxic substances are introduced into the compartments [3]. These direct impacts not only affect emissions of heavy metals, combustion gases and unconverted hydrocarbons, but also have a significant impact on greenhouse gas emissions, which contribute to anthropogenic climate change [4].

In detail, the burning of the oil wells in the Qayyarah area, as well as the sulphur fields in the Mishraq area during the occupation and liberation of the city of Mosul from ISIS [3], led to a directly war-related environmental disaster for the city, as ISIS rigged 25 oil wells with explosives and blew up 18 of them in June 2016. As a result, these oil wells caught fire, creating huge plumes of exhaust that stretched for dozens of kilometres, blocking out the sun and containing highly toxic combustion intermediates. The intensity of the smoke was so strong that the darkened sky was dubbed “Daesh Winter”. The extinguishing of the last burning oil well lasted nine months and took place in March 2017, as remaining ISIS fighters hindered or prevented the extinguishing work by firing mortar grenades [5]. A similar time frame was also observed during the oil well fires in Kuwait in 1991 during the Second Gulf War. A further 16 oil wells were damaged and did not catch fire, but crude oil escaped uncontrollably [5]. It is estimated that a total of 1.4–2.0 million barrels of oil were lost. Due to the fires, many house interiors are covered in soot [5,6,7,8,9] and are therefore actually uninhabitable. As these soot deposits are respirable in terms of their particle size distribution and contain polycyclic aromatic hydrocarbons (PAHs) and heavy metals (lead), which pose a significant health risk to the residents of these indoor spaces, indoor air is of poor quality. In addition to the aforementioned oil wells, ISIS also set fire to a stockpile of around 50,000 tonnes of refined sulphur in the Al-Mishra company in October 2016. An estimated 30,000–35,000 metric tons of this were reportedly burned, creating a thick white cloud of toxic sulphur dioxide and sulphur trioxide that reached Baghdad and neighbouring countries [5,9]. The sulphuric acid processing plant, where sulphur is melted using the Frash process with superheated steam and extracted from the sulphur store as liquid sulphur using compressed air, was also set on fire by ISIS, causing the expelled liquid sulphur to flow into a large ditch that drains into the Tigris. Although the sulphur hardened there, a gradual release into the Tigris can be assumed during precipitation events.

However, the greatest medium- and long-term environmental risks come from a stockpile of around 2 million tonnes of sulphur waste, which consists of around 80% bitumen and 20% sulphur content [5,10].

Health and environmental risks from oil and sulphur fires result from the atmospheric release of pollutants such as sulphur dioxide, nitrogen dioxide, carbon monoxide, polycyclic aromatic hydrocarbons, particulate matter and heavy metals such as nickel, vanadium and lead [8,11]. As adulterated fuels with high ammonia content are mainly used in the transport sector, the reaction of ammonia with the mentioned acidic gases even forms secondary particulate matter (PM2.5) [12]. As these reactions require water as a reaction partner, the formation of secondary PM2.5 and PM10 particularly takes place in the wetter wintertime [12,13,14]. The complex combat environment with the attack and fire at the Al-Mishraq sulphur plant in conjunction with oil fires and the suspected use of chemical weapons led to an intensification of the already existing humanitarian crises in the region [15], as oxides of nitrogen and sulphur are associated with acid rain and its negative impact on vegetation and soils and cause severe health impacts, especially for people with pre-existing respiratory problems [9].

Furthermore, nitrogen oxides, released from fossil fuel use and other combustion processes, affect air quality and climate. From the mid-1990s onward, nitrogen dioxide (NO₂) has been monitored from space, and since 2004, with relatively high spatial resolution, by the Ozone Monitoring Instrument. Strong upward NO₂ trends have been observed in the southern and eastern regions of Asia and the Middle East, in particular in major cities [16], even though economic activities are responsible for 12% of depersonalized emissions [17]. Despite this complex parameter structure, increased NO₂ emissions due to armed conflicts can be observed in the Middle East in particular [18] and were also recently confirmed in the Ukraine conflict [16].

1.2. Post-War Air Pollution (Indirect Impact)

While direct impacts last for a short time, indirect effects on air quality, however, can last much longer. For example, significantly increased emissions can be observed due to the 11 million tons of debris lying around within Mosul, equivalent to four times the Eiffel Tower or nearly 1.1 million truck loads [5], and demolition work on severely damaged buildings, as well as damage to the transport infrastructure and, therefore, very low speeds on the affected traffic routes. Optimistically estimating, clearing work would last for years. Further adverse effects on air quality result from wildfires [6] and looting due to anarchic conditions directly after the war, as well as from the search for alternative fuels to cover the energy needs of the civilian population and industries associated with the construction sector, e.g., the cement industry [5].

As the city faced electricity shortages during the occupation, residents were forced to resort to rudimentary energy sources, such as the combustion of trees for heat and electricity or the utilization of household generators fuelled by gasoline or diesel. These local small-scale emission sources reveal significantly poorer emission qualities than large power plants, worsening the overall emission situation due to their number and location in the urban area. The dependency on decentralized energy sources, which was still a post-war effect of the Gulf Wars, has increased considerably following the recent conflict-based power cuts. As a consequence, the number of decentralized generators increased from 1347 from pre-war level to 3147 in 2014 [14] and even higher after the war. Besides a lack of safe power grid supply, large numbers of refugees doubling the city’s population enhanced power demands and caused an increase in the pre-war vehicle level from 316,734 to more than 800,000 vehicles recently, as the main consumers of the city’s 385 million litres of pre-war demand for heating oil and fuels [19]. While precise quantitative data on the city’s annual fuel oil consumption are not readily available, it is evident that this consumption has also significantly increased in line with the growing population.

Conclusively, air pollution has emerged as a formidable challenge for Mosul in the aftermath of its liberation, and air quality tends to deteriorate. As a consequence of progressive pollution and the depletion of natural resources in conjunction with long-term war damage, social upheaval and restrictions on the lives of the affected inhabitants and consequences for the bioclimatic environment are pre-programmed. Hence, a shift in the niches of species and thereby increased species migration is stimulated [1], which will not improve citizens’ situation.

1.3. Previous Studies on Air Pollutants in Mosul City

There are only a few existing studies that reliably reflect the air pollution in the city of Mosul (see Table 1). One category of studies particularly focused on the area-related dust deposition in the urban area of Mosul, which was estimated at 9.94–185 g/(m²∗month) [20,21,22,23], while a second category of studies focussed on dust concentrations in residential areas and exceedances of the permissible annual WHO limit value (for example, 230.8 ± 210 µg/m³ [11] and 240.5 ± 50.4 µg/m³) [24]. For both approaches, the occurring dust concentrations strongly depend on geomorphological parameters such as vegetation density, topography (location of mountain ranges and corresponding large-scale wind profiles) and meteorological parameters (wind speed, precipitation, and temperature). According to these parameters, dust levels increased with decreasing vegetation density and, thus, increasing temperature in the summer, with corresponding wind channelling through mountain ranges and decreasing precipitation and humidity [12,14,20,25]. In the case of wind velocity, an inverse proportionality is even postulated, which must be critically criticized due to rare measurement data according to wind velocities above 1.1 m/s (four data sets at high velocity vs. approx. forty data sets at low velocity). A follow-up study, where high dust loads were observed during the storm period in spring, therefore, negates this statement. The topographical location of Mosul, in combination with the higher vegetation density due to the high water input from the Tigris, causes five times lower air dust loads compared to cities with proximity to the desert or wind-channelling mountains (i.e., Sinjar, Al-Hatra, Al-Jazari) at approx. 65 g/(m²∗month) [20]. However, it was observed that traffic is particularly responsible for present dust loads (about 60% of man-made dust) compared to industry and power generation (both about 20% of man-made dust) [12,24,26,27] and natural dust emissions by sand and dust storms (about 28% of total dust loads) [28].

A subsequent extended study [29] on inner-city concentrations of NO_x (NO + NO₂) and ozone (O₃), which were obtained using a stationary measuring station supplying 210–252 data sets per month, it was determined that the ozone concentration in summer increased by a factor of six compared to the winter period, with concentrations of 44 ppb in summer versus 7 ppb in winter. At the same time, the lowest concentration of NO occurred in summer at 45 ppb, while the concentration of this combustion gas reached its highest value in winter at 128 ppb on average and 376 ppb at maximum. As NO can react with ozone to form NO₂, the negative correlation between the two gases is understandable. In contrast, the NO₂ concentration of 33–48 ppb over the course of the year was not significantly influenced by the concentrations of the accompanying gases or accompanying parameters such as temperature, air pressure, UV dose or similar. In contrast, ozone correlated positively with temperature and UV dose and negatively with relative humidity as a reactant and atmospheric pressure. The pre-war concentrations of ozone and nitrogen oxides measured here in the urban area of Mosul did not exceed the globally permissible limits [29].

Air quality analyses at six fixed locations on both the left and right banks of the Tigris within the urban region of Mosul for the parameters TVOC, NMHC, CO₂, CO, SO₂, NO_x, NO₂, NO, O₃ and PM10 in the last pre-war years showed that significant differences in pollutant levels occurred between the different locations. While levels of NO₂, SO₂ and O₃ each exceeded the global limit values once at one measurement site, the PM10 limit value was exceeded at all sites in a total of seven analytical campaigns [30]. Despite the already mentioned positive conditions for dust emissions in the case of the city of Mosul, the pre-war situation thus showed that dust limit values were repeatedly exceeded and that NO₂ and SO₂, as indicators of decentralized combustion processes, occurred in concentrations close to the limit values due to the ongoing burdens in the energy and heat supply from the previous Gulf wars. Further studies with similar experimental time frames even showed exceedances of the WHO limits for NO₂ and SO₂, thus emphasising the present problems [12,26]. Similar results were also shown in two post-war studies [25,31]. In summer, ozone is a secondary reaction product of existing NO₂ emissions.

Table 1. Overview of literature data on air quality in Mosul.

Reference			Shihab 2021 [14]		Shihab & Taha 2014 [24]		Shihab & Al-Jarrah 2015 [29]		Shihab 2022 [26]	Asmel et al. 2023 [12]	Hammoud 2021 [25]		Plumelab 2024 [31]		This Study
Parameter	Unit	Season	Winter	Sommer	Winter	Sommer	Winter	Sommer	Win./Som.	Win./Som.	Winter	Somme	Winter	Sommer	Winter	Sommer
PM2.5	µg/m3	Mean								86.28			33.6	22.65	13.5	58.2
		MAX								198			114	54	15.1	88.8
		MIN								10.7			6	8	12.3	35.8
		STD								39.21			17.8	9.07	1.48	27.4
PM10	µg/m3	Mean							145.05		0.534	0.783	81.1	78.92	36.1	296.7
		Max							348		1.572	1.289	506	202	51	347
		Min							2.33		0.11	0.108	10	23	19	248
		STD							69.25		0.489	0.331	90.0	35.6	16.1	49.7
PM50	µg/m3	Mean			53	240
		Max			62.5	345
		Min			45	130
		STD			6.5	50.4
TVOC	ppm	Mean							2.420	1.265					1.57	0.19
		Max							4.040	2.314					2.10	0.274
		Min							0.040	0.053					0.92	0.15
		STD							0.840	0.376					0.60	0.065
HCHO	ppm	Mean													0.54	0.028
		Max													0.58	0.056
		Min													0.50	0.37
		STD													0.04	0.028
CH4	ppm	Mean							1.680	1.807
		Max							2.260	5.208
		Min							0.020	0.119
		STD							0.530	0.848
CO	ppm	Mean							1.240	0.716	0.365	9.235
		Max							3.560	2.344	0.700	18.100
		MIN							0.390	0.138	0.000	0.000
		STD							0.730	0.423	0.246	5.267
NO	ppm	Mean					0.12	0.04	0.036	0.008
		Max					0.37	0.15	0.184	0.026
		MIN					0.004	0.000	0.004	0.000
		STD					0.137	0.058	0.035	0.006
NO2		Mean					0.04	0.03	0.026	0.033	0.290	0.330	0.014	0.005	0.04	0.015
		MAX					0.20	0.07	0.055	0.091	0.600	0.800	0.027	0.010	0.05	0.018
		MIN					0.002	0.005	0.009	0.000	0.000	0.000	0.001	0.002	0.034	0.015
		STD					0.063	0.028	0.041	0.019	0.197	0.260	0.007	0.002	0.009	0.001
NOx	ppm	Mean					0.176	0.078	0.062	0.041
		Max					0.487	0.235	0.217	0.107
		MIN					0.009	0.005	0.014	0.001
		STD					0.188	0.086	0.041	0.021
SO2	ppm	Mean							0.016		0.230	0.435			0.011	0.006
		MAX							0.042		0.900	1.000			0.013	0.007
		MIN							0.003		0.000	0.000			0.007	0.005
		STD							0.008		0.287	0.325			0.002	0.002
H2S	ppm	Mean							0.016		0.030	1.210
		MAX							0.042		0.000	0.000
		MIN							0.003		0.300	5.000
		STD							0.008		0.092	1.607
O3	ppm	Mean					0.007	0.044	0.028	0.058	0.185	0.247	0.014	0.046
		MAX					0.010	0.046	0.069	0.094	0.800	2.000	0.039	0.050
		MIN					0.005	0.043	0.001	0.007	0.000	0.000	0.001	0.040
		STD					0.003	0.001	0.016	0.025	0.230	0.484	0.012	0.002
AQI	-	Mean	86.3	116.8									111.4	89.8	40	330
		MAX	157.2	448.5									283	176	49	386
		MIN	30.8	37.6									31	39	32	276
		STD	41.89	90.44									49.9	29.7	8	55
Year			02/2013–01/2014		01/2010–09/2010		05/2013–04/2014		02/2013–01/2014	12/2013–03/2014			12/24–01/2025	Jul-24	01/22–12/22
Before/After war			before war		before war		before war		before war		After war		after war		after war

Table 1. Overview of literature data on air quality in Mosul.

Reference			Shihab 2021 [14]		Shihab & Taha 2014 [24]		Shihab & Al-Jarrah 2015 [29]		Shihab 2022 [26]	Asmel et al. 2023 [12]	Hammoud 2021 [25]		Plumelab 2024 [31]		This Study
Parameter	Unit	Season	Winter	Sommer	Winter	Sommer	Winter	Sommer	Win./Som.	Win./Som.	Winter	Somme	Winter	Sommer	Winter	Sommer
PM2.5	µg/m3	Mean								86.28			33.6	22.65	13.5	58.2
		MAX								198			114	54	15.1	88.8
		MIN								10.7			6	8	12.3	35.8
		STD								39.21			17.8	9.07	1.48	27.4
PM10	µg/m3	Mean							145.05		0.534	0.783	81.1	78.92	36.1	296.7
		Max							348		1.572	1.289	506	202	51	347
		Min							2.33		0.11	0.108	10	23	19	248
		STD							69.25		0.489	0.331	90.0	35.6	16.1	49.7
PM50	µg/m3	Mean			53	240
		Max			62.5	345
		Min			45	130
		STD			6.5	50.4
TVOC	ppm	Mean							2.420	1.265					1.57	0.19
		Max							4.040	2.314					2.10	0.274
		Min							0.040	0.053					0.92	0.15
		STD							0.840	0.376					0.60	0.065
HCHO	ppm	Mean													0.54	0.028
		Max													0.58	0.056
		Min													0.50	0.37
		STD													0.04	0.028
CH4	ppm	Mean							1.680	1.807
		Max							2.260	5.208
		Min							0.020	0.119
		STD							0.530	0.848
CO	ppm	Mean							1.240	0.716	0.365	9.235
		Max							3.560	2.344	0.700	18.100
		MIN							0.390	0.138	0.000	0.000
		STD							0.730	0.423	0.246	5.267
NO	ppm	Mean					0.12	0.04	0.036	0.008
		Max					0.37	0.15	0.184	0.026
		MIN					0.004	0.000	0.004	0.000
		STD					0.137	0.058	0.035	0.006
NO2		Mean					0.04	0.03	0.026	0.033	0.290	0.330	0.014	0.005	0.04	0.015
		MAX					0.20	0.07	0.055	0.091	0.600	0.800	0.027	0.010	0.05	0.018
		MIN					0.002	0.005	0.009	0.000	0.000	0.000	0.001	0.002	0.034	0.015
		STD					0.063	0.028	0.041	0.019	0.197	0.260	0.007	0.002	0.009	0.001
NOx	ppm	Mean					0.176	0.078	0.062	0.041
		Max					0.487	0.235	0.217	0.107
		MIN					0.009	0.005	0.014	0.001
		STD					0.188	0.086	0.041	0.021
SO2	ppm	Mean							0.016		0.230	0.435			0.011	0.006
		MAX							0.042		0.900	1.000			0.013	0.007
		MIN							0.003		0.000	0.000			0.007	0.005
		STD							0.008		0.287	0.325			0.002	0.002
H2S	ppm	Mean							0.016		0.030	1.210
		MAX							0.042		0.000	0.000
		MIN							0.003		0.300	5.000
		STD							0.008		0.092	1.607
O3	ppm	Mean					0.007	0.044	0.028	0.058	0.185	0.247	0.014	0.046
		MAX					0.010	0.046	0.069	0.094	0.800	2.000	0.039	0.050
		MIN					0.005	0.043	0.001	0.007	0.000	0.000	0.001	0.040
		STD					0.003	0.001	0.016	0.025	0.230	0.484	0.012	0.002
AQI	-	Mean	86.3	116.8									111.4	89.8	40	330
		MAX	157.2	448.5									283	176	49	386
		MIN	30.8	37.6									31	39	32	276
		STD	41.89	90.44									49.9	29.7	8	55
Year			02/2013–01/2014		01/2010–09/2010		05/2013–04/2014		02/2013–01/2014	12/2013–03/2014			12/24–01/2025	Jul-24	01/22–12/22
Before/After war			before war		before war		before war		before war		After war		after war		after war

In addition to the local situation in the city, the overall regional trend in air contaminants must also be taken into account to critically evaluate the present study’s data. Lelieveld et al. [18] showed an existing strong upward trend in NO₂ emissions and thus rising atmospheric NO₂ concentrations in the world regions of South and East Asia and the Middle East, especially in the area of large cities.

This increase in NO₂ concentrations derived by the authors from increasing industrial production volumes and rising local consumption, and thus creatable with economic indicators in predictive models, was drastically altered by political factors such as the armed conflict in Iraq. Here, large changes, including trend reversals, have occurred since about 2010 that could not have been predicted and, therefore, are at odds with emission scenarios used in projections of air pollution and climate change in the early 21st century.

Measurement data from NASA’s Ozone Measurement Instrument for the period of 2005–2021 in Mosul showed a very significant increase in atmospheric NO₂ levels as early as the beginning of the civil war at the end of 2011, where concentrations rose by 25% within one year. This trend continued, despite the collapse in economic output, during the civil war (2011–2013), the war with ISIS (2014–2017) and, as a consequence, in the post-war years, which are still characterized by armed attacks in rural regions [32]. Overall, emissions increased by 81.6% (+/−14.1%) in the period of 2005–2021. It is necessary to take into consideration that satellite measurements can be affected by cloud cover, as mentioned in the introduction. The dense cloud of dust resulting from explosions and burning oil depots over the city indeed had the potential to influence the accuracy of satellite-based NO₂ and ozone readings.

Since the space-based measurements indicate a significant deterioration in air quality, but studies on the systematic assessment of pollutant parameters in the urban area during the post-war phase are lacking, the aim of the current study was to provide early evidence of a potential issue that requires further investigation by evaluating the long-term effects of the war on air pollution by assessing post-war air pollution in Mosul City. The assessment was performed via measurement of air pollutant parameters (PM2.5, PM10, formaldehyde, TVOC, NO₂ and SO₂) in the present post-war phase at various locations in Mosul in the proximity of the former conflict zones, to assess compliance with global limit values on the basis of daily and annual average values and to derive the impact of military operations by comparison with pre-war studies. Present data were correlated with meteorological factors, and the T-test approach was used to evaluate the seasonal and annual variation during the study period in order to determine the long-term effects of the war on air quality in the Mosul urban area against the background of strong population growth due to refugee movements, the presence of debris and the long-lasting damage to the surrounding vegetation.

2. Methodology

2.1. Air Quality Monitoring Sites

The study includes six monitoring sites in Mosul City, as shown in

Table 2. Location of sample sites.

No.	Location	Latitude N	Longitude E	Area Type	Description
S1	Nineveh Environment Directorate	36°375474″ N	33°144447″ E	Residential area	Located on the left coast in a main street; close to a busy traffic intersection.
S2	Public Library	36°352716″ N	33°225501″ E	Commercial area	Located on the left coast in a main street; close to a busy traffic intersection; close to debris area.
S3	Fever Hospital	36°326370″ N	33°184714″ E	Residential area	Located on left coast; close to an electrical generator.
S4	Mosul Municipality	36°336212″ N	33°140137″ E	Commercial area	On right coast; close to a busy traffic intersection; close to the debris area.
S5	Health Center	36°294598″ N	33°150632″ E	Residential and commercial area	Located on right coast; located in a main street; close to the debris area.
S6	Alshabab Sport center	36°273241″ N	33°163325″ E	Service area	Located on right coast; close to a busy traffic intersection and an electrical generator.

and Figure 1. Three sites were chosen on the left bank of the city and three sites on the right side of the city. Sites S2 and S4 were directly located within the conflict zone (S4) or close to it (S2). Besides spatial extension of the conflict zone, data availability at previous sites was taken into account for the selection of present sites.

2.2. Analytical Methods

Only portable measuring devices were used for the on-site determination of the air quality parameters; in detail, a Dräger X-am 8000 for the measurement of NO₂ and SO₂, an AQI AX-8016 multifunctional air detector for PM2.5, PM10, formaldehyde and TVOC, as well as a GT8907 mobile weather station with an anemometer and data logger (Shenzhen Jumaoyuan Science and Technology Co., Ltd., Shenzhen, China), and the BENETCH software, version 3.4.0.3, for reading out the measurement data on a PC to determine the meteorological parameters of wind speed, wind direction, temperature and humidity. All equipment was freshly calibrated in the fab before the measurement campaigns, and signal output was cross-checked with common lab devices. The measurement data at all locations were recorded at 10-min intervals, with three individual data sets being summarized as half-hourly averages, i.e., 9 data sets per site and test day. The measurements took place over 8 h (10 a.m.–6 p.m.) between January and December 2022, with three test days per month being carried out as only daytime measurements. In total, 324 data sets per site were collected.

2.3. Air Quality Index (AQI)

The air quality was assessed according to the US EPA’s AQI. This is a six-graded scale to categorise air quality from Good to Dangerous and where each air pollutant is assigned a conversion factor according to its human toxicity. Hence, conversion of concentration levels to AQI values is possible (µg/m³ for PM2.5 and PM10, ppm for CO and ppb for O₃, NO₂ and SO₂). The final index value results from the respective maximum value of these six individual parameters. The calculation is carried out according to the following formula, with the breakpoints according to [33]:

$$AQI={\displaystyle \frac{I_{high}-I_{low}}{C_{high}-C_{low}}}\left(C-C_{low}\right)+I_{low}$$

(1)

where

C 

concentration level of pollutant

C_low 

low breakpoint of the concentration in the present concentration interval

C_high 

high breakpoint of the concentration in the present concentration interval

I_low 

lowest index value in the present concentration interval

I_high 

highest index value in the present concentration interval

2.4. Limitations in Methodology

One of the most significant obstacles faced during the study period was the destruction of standard measurement devices in the urban area of Mosul City due to the war. The lack of equivalent technology in the post-war phase, driven by the administration’s urgent priorities and concerns over theft, meant that all air pollutant analyses in this study were conducted using portable devices and as only daytime measurements. Consequently, this work is considered preliminary and underscores the strong need for conventional air quality monitoring methods to consolidate the presented air quality data. Therefore, it is recommended that conventional large-scale air quality monitoring be implemented in these areas to underline the present data and conclusions.

Additionally, this analysis was primarily conducted in 2022, five years after the war. As a result, observed impacts on air quality were mainly limited to indirect factors, i.e., secondary emissions. The five-year period is particularly long for troposphere-based observations of conflict-related air quality impacts. Direct effects (=primary emissions) of the war appeared during the war and the first post-war years. However, in this time period, the city experienced significant chaos, not only from air pollution caused by burning oil and sulphur but also from the settlement of immigrants and a large increase in the population, random burning and both the absence of strict laws and executive staff, prohibiting safe installation and operation of the devices by scientific staff. This tremendous boost in population caused a severe increase in vehicles, fuel consumption, and the number of generators used to produce energy, i.e., impact analysis is mainly driven by secondary emissions of secondary factors.

3. Result and Discussion

3.1. Variation of Daily Average Values of All Parameters According to the Sites

3.1.1. Particles Matter (PM2.5, PM10)

PM10 particles are small enough to pass through the nose and throat to reach the upper respiratory tract, which has a strong impact on the development of chronic obstructive pulmonary disease (COPD), asthma [34] and cardiovascular diseases, and thus increased morbidity [35]. Even more critical, PM2.5, with a diameter less than 2.5 µm, can penetrate the airway and cross the blood barrier, causing severe health damage and increased mortality [36,37]. Anthropogenic emissions of dust particles occur in particular during combustion processes for the provision of heat and energy for private households, companies and institutions [38], but also from agricultural land [39] (so-called primary aerosols). Main sources of anthropogenic fugitive, combustion, and industrial dust are fly ash from coal combustion, mineral iron particle emissions from steel production, lime dust from the cement industry, resuspension from paved and unpaved roads, mining, quarrying, road-residential-commercial construction and agricultural operations like ploughing, harrowing or harvesting, especially in the case of dry soils or soils with low undergrowth [39].

In addition to the primary aerosols mentioned above, combustion gases are the main source of secondary PM2.5 aerosols. Here, a reaction of the acidic combustion gases (CO₂, sulphate, nitrate, HCl, etc.) with ammonia occurs in the presence of atmospheric moisture, which is particularly prevalent with adulterated fuels as well as in agricultural regions. Reaction products are the corresponding ammonium salts, which belong to the PM2.5 category. Higher PM2.5 formation due to higher atmospheric concentrations occurs in the winter months. Although high relative humidity is favourable for the reactions, condensing conditions enveloping PM2.5 particles by a hydrolayer lead to increased deposition [40]. Hence, either an increase or decrease in PM2.5 concentrations may occur during winter compared to summertime, depending on the humidity. It is therefore not surprising that the seasonal comparison of PM2.5 concentrations provides an indifferent result.

In contrast, a significant increase in the PM10 fraction is expected in the period from spring to autumn as these seasons are characterised by an enhanced presence of dust and sandstorms [27].

However, the firing of rockets and projectiles also represents a significant source of emissions. For example, dust emissions of 3.42 mg/m³ at an 8 m distance to the left of the muzzle and 4.62 mg/m³ at a distance of 22 m in the projectile corridor were detected during the operation of an M777 155 mm howitzer, with 63% of the dust concentration being accounted for by PM10 and approx. 30% by particles smaller than 3.5 µm [41]. The chemical analysis of particulate matter (PM) after a war can reveal a variety of pollutants and toxic substances.

Heavy metals, which include lead, mercury, cadmium and arsenic, can originate from the destruction of buildings, vehicles and industrial sites [41], while radioactive particles may be present in cases involving nuclear weapons or facilities, but also by the use of depleted uranium munitions as armour-penetrating ammunition [42]. Hence, radioactive isotopes like cesium-137 and iodine-131 may be detected [43].

Besides volatile organic compounds (VOCs) as accompanying emissions, particulate organic compounds like polycyclic aromatic hydrocarbons (PAHs) are often present due to the incomplete combustion of fuels and heating materials. Inorganic ions like sulphates, nitrates, and ammonium can also be found as common residues of projectile explosions and fires.

During the analytical period, the daily average PM2.5 values at all sampling sites were between 6–160 µg/m³, and for PM10 at 8–661 µg/m³. The highest mean value for PM2.5, as well as for PM10, was reached at site S4 with 45 µg/m³ (PM2.5) and 193.3 µg/m³ (PM10), due to the very high volume of debris, which corresponds to a WHO guideline limit value (see

Table 3. Recommended WHO 2021 AQG levels for air quality guidelines.

Pollution	Avg. Time	AQG Level
PM2.5 (µg/m3)	Annual	5
	24 h	15
PM10 (µg/m3)	Annual	15
	24 h	45
NO2 (µg/m3)	Annual	10
	24 h	25
SO2 (µg/m3)	Annual	-
	24 h	40
TVOC (mg/m3)	Annual	-
	24 h	0.3–0.5
HCHO (mg/m3)	Annual	-
	24 h	0.1

), the exceedance by a factor of 3.0 (PM2.5) and 4.28 (PM10) [11], as shown in Figure 2 and

Table 4. Min, max and mean daily values of air pollutants in all sites during the year 2022.

Parameter		PM2.5	PM10	TVOC	HCHO	NO2	SO2
WHO 2021		15 μg/m3	45 μg/m3	0.5 mg/m3	0.1 mg/m3	25 μg/m3	40 μg/m3
S1	Mean	30.54	138.62	1.30	0.154	24.44	16.98
	MAX	86.00	442.00	4.00	0.515	51.00	40.00
	MIN	10.00	12.00	0.13	0.049	6.00	14.00
	STD	30.87	178.34	1.56	0.055	11.8	9.9
S2	Mean	40.64	187.83	1.58	0.402	38.33	24.77
	Max	160.00	560.00	4.50	1.545	96.00	48.00
	Min	12.00	18.00	0.34	0.017	14.00	17.44
	STD	57.06	256.06	1.88	0.055	36.9	12.0
S3	Mean	34.92	109.58	1.06	0.179	21.33	20.92
	Max	89.00	445.00	3.00	0.295	51.00	40.0
	Min	8.00	8.00	0.12	0.01	12.00	20.35
	STD	38.83	168.81	1.29	0.055	6.5	10.5
S4	Mean	45.17	193.33	1.98	0.442	44.14	25.09
	Max	110.00	661.00	4.00	1.145	87.00	48.00
	Min	16.00	20.00	0.28	0.025	12.00	13.57
	STD	42.94	216.37	1.65	0.055	9.3	13.4
S5	Mean	30.33	117.08	0.78	0.092	21.57	22.56
	Max	88.00	442.00	2.04	0.745	33.00	35.85
	MIN	6.00	12.00	0.12	0.013	9.00	17.44
	STD	37.94	174.02	0.85	0.244	9.83	7.27
S6	Mean	44.10	165.70	1.40	0.245	32.30	35.90
	MAX	112	576	3	0.955	62.00	46.82
	MIN	16.00	21.00	0.31	0.015	12.00	17.44
	STD	45.2	228.4	1.293	0.154	21.81	15

. The primary fine dust released by projectiles and ammunition in the conflict area itself is of less relevance, as dust levels in the non-conflict areas S1 and S6 were a factor of 1.4 (S1) or 1.2 (S6) higher than at sites next to the conflict zone with comparable traffic densities or utilization, due to the high mobility of this dust fraction in the air. Hence, the results are in agreement with previous literature data.

3.1.2. Total Volatile Organic Carbons (TVOC)

TVOC emissions mainly arise from the anthropogenic release of fuels during their production, storage, refuelling or incomplete combustion [43], and to a lesser extent from the use of solvents. As some of the volatile organic compounds (VOCs), both native and secondary, the latter formed by incomplete combustion, show carcinogenic potential, very low limit values of 0.5 mg C/m³ (as emissions) and 5 µg/m³ (as emissions) [44,45] are set. Furthermore, VOC inhalation may cause eye, nose, and throat irritation, breathing difficulties and organ damage [46].

The literature comparison shows that no long-term impact of the war can be determined for TVOCs as well. However, there is a clear seasonal variation in concentration between highly polluted winter and low-polluted summer. The higher winter air pollution is primarily due to the higher heating and energy demand of the residents and the resulting VOC slip. It can therefore be assumed that VOC emissions will become more severe as the degree of destruction increases, i.e., comparatively high VOC emissions are expected in the vicinity of the combat zone.

This assumption can be confirmed by the 2022 analytical data of this study, where average daily values of TVOCs at all locations in Mosul City were between 0.1 and 4.5 mg/m³, with the highest daily average values of 1.98 mg/m³ at sampling site S4. The values thus exceeded the daily limit values proposed by the WHO by a factor of 2.8 [11] (see Table 3). Elevated TVOC concentrations of 1.58 mg/m³ were also detected at sampling site S2, which can be explained by the proximity of the site to the conflict area and the associated proximity to the debris, as well as the proximity to important main traffic routes. The composition of the TVOC spectrum was not monitored, but Chen et al. [47] were able to determine dominant emission proportions of BTEX (85.9%, with a relative share of 14.5% of benzene), alkanes (9.1%) and butyl acetate (5.0%) for passenger compartment interior air, with the latter component originating mainly from manufacturing as a solvent for adhesives (see Figure 2 and Table 4).

3.1.3. Formaldehyde HCHO

Combustion gases from fuels, but also tobacco, are a common source of formaldehyde in the environment, with negative effects on indoor air quality in residential buildings [48]. Other sources of formaldehyde, which is the most common outdoor air carcinogen among the 187 hazardous air pollutants (HAPs) listed by the US EPA, include construction materials and home items. According to the EPA [49], up to 13 out of every million persons may develop lung and nasopharyngeal cancer in their lifetime due to exposure to an average HCHO concentration of 1 μg/m³, or approximately 0.7 ppb at standard conditions.

During the test phase, the average daily values of HCHO were between 0.01 and 1.54 mg/m³, with the highest mean value of 0.442 mg/m³ being reached at site S4, thus exceeding the average WHO daily limit value by a factor of 5.08. Due to its proximity to the conflict zone, site S2 also revealed a similar emission level of 0.402 mg/m³. All other sites, with the exception of S6, showed at least 2.5 times lower concentrations. As sites S1 and S6 are also located in the immediate vicinity of main traffic axes, the effect of high traffic density on the formaldehyde concentrations can be recognized but does not explain them alone (see Figure 2 and Table 4).

Formaldehyde, which has also been proven to be produced by the incomplete combustion of propellants such as nitrocellulose [50], in the line of fire with 3.6 µg/m³ or at the side of the projectile corridor of a firing M777 howitzer with 7.1 µg/m³ [41], for the Carl Gustav anti-tank 84 mm weapon (5.8–8.2 µg/m³) [51] or the reaction of explosives during the explosion (e.g., RDX) [52], may therefore be caused by military operations.

As formaldehyde has a high atmospheric elimination rate due to its good water solubility and low UV resistance [53], current formaldehyde pollution is therefore attributable to the traffic situation and stationary combustion processes. The high elimination efficiency of formaldehyde is particularly evident when comparing the high winter concentrations with the summer concentrations, which are a factor of 24 lower.

Even though no pre-war analyses for formaldehyde are available, significant emissions levels at the highly devastated site S4 let suggest war-based increases in secondary emission levels.

3.1.4. Nitrogen Dioxide NO₂

NO₂ from the combustion of fossil fuels and fuels in power plants and generators, vehicles, off-road sources and industrial production [38] can irritate the eyes, nose and throat, as well as cause lung irritation. High nitrogen dioxide levels increase asthma cases and respiratory disease hospitalisations [49].

As a combustion gas, higher concentrations were detected during the wintertime than in the summer, which was confirmed by almost all studies in Table 1. Furthermore, all studies showed similar NO₂ levels before and after the war, i.e., there is no long-term impact from primary emissions. As the electrical grid is unstable due to war devastations and the requirement for decentralized energy supply increases, an increase in secondary emissions may be assumed. However, due to the easy atmospheric removal of this compound, enhanced concentration levels might not be detectable, particularly during the wet wintertime.

Within the urban area, it was present with average daily values of 6–96 µg/m³ over the year 2022. The highest mean value was again measured at site S4 with 44.14 µg/m³, thus a factor of 1.76 above the limit values of the WHO guideline (see Table 3). Sites S2 and S6 followed with 38.33 µg/m³ (S2) and 32.30 µg/m³ (S6) and exceeded the limit value by a factor of 1.53 and 1.29, respectively. All three sites were characterized by high traffic densities and/or the high density of decentralized, installed electrical generators, which meant that correspondingly high NO₂ concentrations were to be expected [24,29,30].

Besides secondary emissions, the burnout of explosives is characterized by primary NO_x emissions of 5 kg per tonne of explosives [54], but these are no longer detectable in the atmosphere due to the time lag. However, evidence of increased nitrate concentrations in the water and soil phases has been provided in previous studies [55,56], underlining the previous presence of enhanced NO_x emissions.

3.1.5. Sulphur Dioxide SO₂

SO₂ is a combustion product of sulphur-containing fuels and combustibles, which is why diesel-powered vehicles and generators, in particular, are the main source of SO₂ emissions in the urban area of Mosul, in addition to industrial production processes. It contributes significantly to particulate matter pollution in many countries, particularly oil-producing ones, as SO₂ undergoes ozonolytic transformation into H₂SO₄ aerosols [57]. It impairs the respiratory system, increases the risk of respiratory infections, and exacerbates conditions like asthma and chronic bronchitis [49]. Additionally, as a combustion gas, enhanced atmospheric concentrations are expected during wintertime due to increased demand for electricity and heat. However, this specific increase in emissions was very moderate in the previous studies in Table 1, but more substantial in the present study. Here, the daily values of SO₂ in 2022 were between 10.5 and 48 μg/m³, while the highest average values were detected at site S6 with 35.9 μg/m³. Compared to other air pollutants detected, the WHO limit values for SO₂ were complied with on an annual average at all sampling sites, although isolated exceedances occurred on a few days in winter at sites S2–S4 and S6 (see Table 4 and Figure 2). Like NO₂, SO₂ also occurs when weapons are fired and can be detected at up to 40 ppm at the muffler of weapons with a calibre of 9–155 mm [41] as a primary emission. Due to the time gap, primary emissions can only be detected indirectly as the accumulation of sulphate in the water and solid phases. Corresponding results have already been presented previously [55,56].

3.2. Annually Average Values and Seasonal Variation of All Parameters According to the Sites

The average values of all air pollutants over the entire analytical campaign of the year 2022, differentiated by location, show that the annual average values of PM2.5 were between 12.3–107.5 μg/m³ depending on the site, while the overall average value across all sites was 38.76 μg/m³, which exceeded the annual WHO guideline values by a factor of 7.7 [11]. The highest individual value was measured in May at 107.5 μg/m³ and the lowest in January at 12.33 μg/m³, which can be explained by the storm phase in spring and the high deposition of dust in the wet winter phase due to wet deposition. The results of all parameters are shown in

Table 5. Monthly average pollutant values and corresponding meteorological conditions by site.

Parameter	PM2.5	PM10	TVOC	HCHO	NO2	SO2	Temperature °C	Wind km/h	Humidity %	Rainfall mm
WHO 2011	5 μg/m3	15 μg/m3	0.5 mg/m3	0.1 mg/m3	10 μg/m3	40 μg/m3
January	12.33	19.00	3.38	0.785	106	35.55	1.2	3 NW	70	62.5
February	13.00	51.00	2.71	0.725	84.67	32.36	9.1	8 SW	80	62.7
March	17.67	95.33	3.03	0.425	66.67	23.58	13.05	6 SW	66	63.2
April	62.00	231.33	1.04	0.065	39.33	22.04	18.2	10 SW	56	44.1
May	107.50	521.00	0.31	0.005	29.33	21.82	24.45	12 NW	30	15.2
June	88.83	347.50	0.25	0.005	29.67	20.86	30.25	18 SW	12	1.1
July	50.17	294.83	0.27	0.015	31.00	13.12	33.95	15 NW	6	0
August	35.83	248.00	0.44	0.075	30.00	12.88	33.4	13 SW	5	0
September	30.67	233.33	0.84	0.235	36.67	14.04	28.65	12 SW	8	0.3
October	15.50	178.67	0.98	0.395	37.33	17.44	22.05	5 NW	23	11.8
November	16.50	46.50	1.20	0.575	49.67	15.37	14.15	4 SW	38	45
December	15.17	38.50	1.48	0.675	69.33	21.38	8.95	6 SW	63	58
Mean	38.76	192.08	1.33	0.325	50.81	21.87	19.78333	14	38	30.3
MAX	107.50	521.00	3.38	0.775	105.80	35.55	33.95	18	80	63.2
MIN	12.33	19.00	0.25	0.005	29.33	12.88	1.2	3	5	0

.

The average PM10 values at all sites were in the range of 19–521 μg/m³, with an annual average value across all locations of 192.08 μg/m³, which exceeded the annual WHO guideline values by a factor of 12.8 [11]. The highest individual PM10 value was reached in May with 521 μg/m³, and the lowest value in January with 19 μg/m³, and thus follows the argumentation for PM2.5.

In detail, the low particle concentrations in winter can be explained by existing precipitation and the associated wet deposition of aerosols, as well as the strong increase in vegetation due to the excess water and the low temperatures, which prevent the vegetation from drying out and stunting. With an increasingly warm and arid climate in spring, supported by the onset of the storm season, particle concentrations rise sharply in spring and reach their maximum concentrations [24,58,59].

The average TVOC values at all sites in 2022 were between 0.25–3.38 mg/m³, while the annual average value across all sites levelled off at 1.33 mg/m³, but still exceeded the annual WHO limits by a factor of 2.6. As domestic heat and energy generation are the main sources of TVOC emissions, the highest emissions exceeding the limit values occur in the winter period or rainy season, while air concentrations fell with increasing outside temperatures in the period from May to August and also fell below the WHO limit values. Accordingly, the highest annual average TVOC values were reached in January at 3.38 mg/m³ and the lowest value in June at 0.25 mg/m³, where the 24-h WHO limit value was only exceeded on individual days.

The average values for formaldehyde (HCHO) considered over the whole of 2022 were between 0.05–0.83 mg/m³ for all sites. The overall average value was 0.325 mg/m³ (see Table 5), but still exceeded the WHO limit values by a factor of 3.8. Interestingly, the limit values were exceeded throughout the entire rainy season, i.e., the months of September to March, although formaldehyde has a high water solubility and wet deposition is to be expected. Contrary to this, in the hot summer months from April to August, there were no exceedances due to photooxidation of formaldehyde [53], but rather very low emission values, although formaldehyde emissions rose again in the months of September and October, which were very hot during the day but characterized by cool nights. September, for example, is also characterized by days that are already one hour shorter than in August, which increases the demand for electricity for lighting purposes. The formaldehyde concentrations are therefore very strongly influenced by the heating behaviour and electricity requirements of the population, and war-related emissions must be extracted from the comparison of the individual sites in relation to the conflict area.

The values of TVOC and HCHO thus increased dramatically in winter, which can be attributed to the increasing use of domestic heating and electricity generators and weather-related increases in vehicle traffic; all three issues lead to a significant increase in the consumption of crude oil products [30,60].

The generally high traffic density in Mosul, characterized by a doubling of the vehicle fleet due to war refugee movements, leads to significant exceedances of the WHO limit value for NO₂ throughout the year, which is exceeded by a factor of 5.1 in the case of the mean value across all sampling sites (50.58 µg/m³) [11]. Broken down by month, the highest concentration as a combustion product is found, as expected, in January at 105.8 µg/m³, while, as expected, the minimum is observed in the hot month of July at 29.3 µg/m³ (see Table 5). However, there has been a clear upward trend in NO₂ levels in recent years during the war and the subsequent post-war period, resulting, on the one hand, from the need for increasing decentralized electricity and heat supplies and the doubling of road traffic volumes, and, on the other hand, from the consequences of military operations (fires at oil and sulphur wells and sulphur depots, use of weapons and explosives) and have already been confirmed in many studies [16,18,32]. Similar environmental effects have also recently been described in the Ukraine conflict [16] and confirm the amplifying impact of direct and indirect combat effects.

In 2022, the annual average values of SO₂ at all sites were in the range of 12–35.55 µg/m³ or 21.8 μg/m³ as an overall annual average value across all sites, and thus is within the annual WHO limit values [11]. As a combustion product, the highest value was reached, as expected, in January at 35.55 μg/m³, while the lowest annual average value was measured in August at 12 μg/m³. As the cool or cold season set in, the SO₂ values rose again accordingly, reflecting similar study results worldwide [61,62].

3.3. Air Quality Index (AQI) and Its Study-Based Variation

Based on previous studies, data from two studies each enable the calculation of the AQI in Mosul from the pre-war period and the post-war period. Average AQI values of 98.8 (winter period, [14]) and 95.6 (annual average, [26]) as pre-war levels, and 89.8 (summer period) or 111 (winter period, [31]) as well as 54–239 (range, summer only, [63]) were shown. Additionally, an average AQI value of 40 (winter period) and 330 (summer period) was calculated in the present study. The dataset from Hammoud 2021 [25] was not taken into account, as a lapsus in metric units seems to be probable. Comparison of these data, however, reveals significant variations in the range of a factor of 2.8–3.7, both in terms of the ratio between summer vs. winter and in terms of the total level. As additional minimum and maximum values exceed or fall short of the average value by a factor of up to 2.5, the analysis of an average value for the AQI is therefore only of very limited significance, and a more detailed analysis of the course of the index in the investigation phases is advantageous. This comparison was carried out using the measurement data for PM2.5, PM10, NO₂, and O₃ and the derived specific and final AQI value, which were published online by Plumelabs. These data are based on information from the Copernicus Atmosphere Monitoring Service of the European Centre for Medium-Range Weather Forecasts, which is supported by 35 countries with their national specific observation programs. Exemplary periods from 29 June 2024–2 August 2024 (summer period) and 22 December 2024–2 January 2025 (winter period) are presented in Figure 3 and Figure 4.

Even within these limited periods, the AQI value fluctuated between 39 and 176 with an average value of 89.8 in summer, and between 31 and 283 with an average value of 111.4 in winter. In particular, the winter values for maximum and thus also average were driven by an extreme weather event in the period 27 December 2024 12 a.m. to 28 December 2024 3 p.m., which significantly increased them. In addition, a pronounced daily cycle in the winter period and a pronounced weekly cycle in the summer period can be observed, although the latter cannot be correlated with rest days. However, these variations in the AQI value should not be over-interpreted, as the AQI value, as a global parameter, was originally conceived by the US EPA as a simple parameter for communication with the public to communicate the ambient air quality and to derive recommendations for outdoor activities and sports. Its use as a scientific parameter is very limited due to its global parameterization.

Nevertheless, while these index curves of Figure 3 and Figure 4 illustrate the limited significance of the AQI, the two figures clearly show that the AQI is determined by the PM10 curve in summer (with individual exceptions for O₃) and by the PM2.5 curve in winter. While the PM10 fraction is influenced in particular by dust and sandstorms, the PM2.5 fraction is strongly impacted by combustion processes, i.e., the increased demand for energy and heat in the winter period is also evident from this. The dominance of the PM fractions in the AQI, with a share of 93.8%, was already previously postulated [14]. The difficult interpretation of the measurement data, therefore, requires a statistical analysis, as described in the following chapters.

As shown above, the PM concentrations do not represent direct war-related primary emissions but are predominantly secondary emissions in addition to natural emissions, as the aforementioned energy grid was severely impaired, especially during the war and the years that followed, and the green belt around the city was heavily cleared. With decreasing vegetation and progressive desertification, dust and sandstorm events are also becoming increasingly important for Mosul, as they have already been documented several times for the Baghdad administrative district [63,64,65].

3.4. T-Test Values of Seasonal Variation of All Parameters

An adequate approach for statistical analysis of deviations in analytical data and their significance is the T-test. The values were compared between the dry season (April to October) and the wet season (November to March) in 2022. The results of PM2.5, PM10, TVOC, HCHO and NO₂, as well as SO₂, were below the critical value (p < 0.05), which is considered as statistically significant differences during the analytical campaign for all parameters, assuming the null hypothesis that the sample mean (p < 0.05) and the population mean are statistically different at the 0.05 significance level. This is due to the increasing fuel consumption during the winter for heating purposes. Corresponding T-test parameters are summarized in

Table 6. T-test values between wet and dry weather during 2022.

Parameter	T	p	Df	Status
PM2.5	3.833896	0.001648901	10	1
PM10	4.700504	0.000420462	10	1
TVOC	−3.62857	0.002311747	10	1
HCHO	−7.11706	1.61448 × 10−5	10	1
NO2	−3.5763	0.002521302	10	1
SO2	−1.80277	0.04019654	10	1

.

3.5. Comparison of the Annual Average Values of Air Pollutants Parameters Before and After the War

A comparative analysis of the annual average concentrations of particulate matter (PM10), total volatile organic compounds (TVOC), nitrogen dioxide (NO₂) and sulphur dioxide (SO₂) reveals a significant increase in these pollutants compared to the pre-war study by Al-Jaraah as a reference study [30]. Only with TVOC levels as an exception, similar contamination levels were shown by Asmel et al. (2023) [12]. Hence, the application of Al-Jaraah data as a reference is a reliable approach. In detail, there was an increase to 157 µg/m³ or by a factor of 1.2 for PM10, by a factor of 40 for TVOCs, by a factor of 2.09 for NO₂ and by a factor of 1.16 for SO₂ (see

Table 7. Comparison of the average annual values of all air pollutant parameters in Mosul City before and after the war (previous data based on Al-Jarrah [30]).

Parameter	Previous Study (2014)	Current Study (2022)	Factor
PM2.5 μg/m3	ND	39	ND
PM10 μg/m3	157	192	1.2
TVOC mg/m3	0.033	1.33	40.3
HCHO mg/m3	ND	0.38	ND
NO2 μg/m3	24.3	50.8	2
SO2 μg/m3	18	21	1.16

).

This increase in pollutant levels is caused in particular by the sharp rise in the city’s population due to refugee movements and the resulting almost tripling of traffic volumes, as the demand and thus the requirement for the provision of heating energy and electrical energy have increased immensely, especially due to decentralized supply structures. The high level of emissions from decentralized supply structures is due to the lack of central supply security caused by war damage from the last three wars and the civil war, as well as a strong dominance of crude oil and natural gas as an energy source (97.7% of the total energy mix) [66]. In addition to the refugees’ arrival, the situation was also exacerbated by the devastation caused by the fighting in the urban area and the resulting loss of living space for the existing population, which meant that settlements had to be made in the surrounding rural area dominated by agricultural use with a loss of green spaces and vegetation density.

The implications of these findings are significant, underscoring the need for targeted environmental policies and interventions to mitigate air pollution and safeguard public health.

3.6. Correlation of All Parameters Within the Study Period

Spearman Correlation Coefficient

The Spearman correlation matrix and heatmap provide insights into the monotonic relationships between variables, helping identify strong positive or negative associations. The detailed analysis of the Spearman correlation shows the following:

• Strong positive correlations:
  • PM2.5 and PM10 (0.94): This indicates a very strong monotonic relationship between PM2.5 and PM10, which is expected as PM2.5 is a subset of PM10. This finding aligns with previous research [67,68].
  • TVOC and NO₂ (0.99): This near-perfect positive correlation suggests that these two pollutants are highly related, likely due to shared sources or similar environmental behaviours.
  • TVOC and HCHO (0.90): A strong positive correlation indicates that as TVOC levels increase, HCHO levels also tend to increase, possibly due to overlapping sources or chemical interactions.
• Strong negative correlations:
  • PM2.5 and HCHO (−0.97): This strong negative correlation suggests that higher PM2.5 levels are associated with lower HCHO concentrations, which could reflect differing sources or removal mechanisms.
  • PM10 and TVOC (−0.92): A strong negative correlation indicates that as PM10 levels increase, TVOC levels tend to decrease, highlighting potential trade-offs in pollutant dynamics.
• Moderate correlation between NO₂ and SO₂ (0.70): A moderate positive correlation suggests some degree of association between these pollutants, possibly due to overlapping sources like combustion processes.
• Weak correlation between PM2.5 and SO₂ (−0.37): A weak negative correlation indicates little to no monotonic relationship between these variables, suggesting they may be influenced by different factors. This indicates that these pollutants likely originate from different sources [69,70] (see Figure 5).

3.7. Meteorological Impact Parameters

3.7.1. Meteorological Conditions

Mosul’s climate is characterized by hot, dry summers, brief shoulder seasons, and relatively cool winters. The city’s semi-arid surroundings create severe temperature contrasts throughout the year. Summers are extremely hot and dry, with average high temperatures hovering between 32.8 °C and 35 °C. Spring and fall are brief and mild, with average high temperatures ranging from 20 °C to 28 °C. Winters are cool but not extremely cold, with average high temperatures ranging between 14.1 °C and 14.8 °C [71,72].

During the study period, meteorological parameters varied as follows: average daily temperature: 1.2–33.95 °C; wind speed: 3–18 km/h; humidity: 5–80%; rainfall: 0–63.2 mm. These parameters describe arid weather conditions, underlining the present and higher demand for irrigation water in the next few years [73]. As shown in Figure 6, the climate prediction model commonly expects less rainfall and an increase in temperature and reference evapotranspiration in 2022 and the following years. In particular, the results showed that monthly evapotranspiration ranged from 43 to 56 mm per month for the summer months (June, July, August and September) of 2022 [73]. As the drought is accompanied by a further decrease in vegetation density, increased particulate pollutant concentrations are to be expected in the summer phase, even outside the storm phase in spring, which will continue into autumn due to the damage to vegetation. This means that an increase in all pollution indicators is expected for the next few years [73].

3.7.2. Correlation Between Pollution Parameters and Meteorological Factors

The empirical analysis delineates a direct correlation between particulate matter concentrations (PM2.5 and PM10) and meteorological variables such as temperature and wind speed. Specifically, an escalation in particulate matter is observed when temperatures surpass 23 °C as water balance turns to arid conditions and wind velocities exceed 5–10 km/h [74,75] under continental climatic conditions Conversely, an inverse relationship is noted with relative humidity and atmospheric pressure, where heightened levels of these factors during the colder months contribute to a diminution in particulate matter concentrations [74] both by condensation and wash-out. This phenomenon is attributed to the confluence of increased atmospheric moisture, pressure, and precipitation, which are prevalent during this season. Additionally, the advent of seasonal vegetation in Mosul city plays a pivotal role in mitigating dust dispersion by the wind. Similar interactions were previously addressed [24,30,76].

Furthermore, the study elucidates an indirect correlation between volatile organic compounds (VOCs), formaldehyde (HCHO), nitrogen dioxide (NO₂) and sulphur dioxide (SO₂) with temperature and wind speed, while a direct correlation is established with humidity and pressure. The augmentation of these pollutants during colder periods is ascribed to the elevated use of heating fuels, which are compounded by other fuel sources utilized for warmth. The indirect association of these parameters with atmospheric pressure and relative humidity is likely due to their propensity to increase on colder days.

These findings are consistent with previous research by Gupta [77] and Mackiewicz-Walec [62], which showed an inverse relationship between NO₂ and SO₂ and temperature and wind (see Figure 6).

4. Conclusions

During the war, the air in the city of Mosul was exposed to direct effects, such as burning oil and sulphate fields, and contamination from weapons of war. Furthermore, significant parts of the city were destroyed by fighting. These primary emissions caused by fighting, destruction and devastation were of short-term duration and are therefore of little relevance today.

However, the secondary emissions caused by post-war consequences reveal a contradictory picture for the city. In detail, the mountains of rubble, their removal, a considerable arrival of refugees and the need to accommodate them as well as the existing population have led to an expansion of the settlement area in the surrounding countryside close to the city, with a loss of green spaces and vegetation density, combined with the risk of increased desertification and a severe increase in traffic, leading to increased urban air pollution. The heat and electricity supply is dominated by decentralised installations, as the security of supply through the central grids is low. Complemented by violations of existing environmental regulations by the population (uncontrolled refuelling of vehicles, incineration of waste), the war-induced situation led to a considerable deterioration in air quality in the urban area. In addition to the risk of further devastation, the forced conversion of agricultural land and green spaces in the surrounding area due to the increase in population will, in particular, worsen the food supply for the urban population.

The results already show that the annual average values of PM2.5, PM10 and NO₂ exceed the WHO limit values at all locations throughout the year, while the annual average values of TVOC, HCHO and SO₂ are still within the limit values in the hot months and only exceed the limit values in the cold months (December to March), which is due to the use of heating materials in winter.

The study identified the direct impact of the war on air pollution through the increase in PM10, TVOC, NO₂ and SO₂ levels during the study period compared to a pre-war study. PM10, NO₂, SO₂ and TVOC increased by a factor of 1.2, 2.09, 1.16 and 40.2, respectively, compared to the pre-war year. This increase can be attributed to the parameters listed above. In winter, TVOC, HCHO, NO₂ and SO₂ levels increased due to increased fuel consumption. For all parameters, there was a significant difference between the wet season and the dry season, which is due to increased fuel consumption for heating purposes in winter.

The relationship between the pollution factors and the meteorological factors indicates that PM2.5 and PM10 have a positive correlation with temperature and wind, while TVOC, HCHO, NO₂ and SO₂ have a direct positive correlation with humidity and hence the cool weather period. The study also showed a significant indirect correlation between PM2.5, PM10 and other parameters. A statistically significant seasonal variation was found for all parameters during the study period. The air analysis data confirmed preliminary studies on war-related pollution of soils, wells and the Tigris River.

Based on the current data, we strongly recommend that conventional large-scale air quality monitoring be considered in these areas; the study recommends implementing environmental measures to control and mitigate the environmental impacts of war, such as developing air purification technologies and preserving ecosystems, replacing energy sources with renewable energy options and urban planning and reducing migration to the city, which in turn will reduce fuel consumption, decrease traffic emissions and also reduce pollution from power generators. Additionally, we recommend increasing green spaces in the city and enforcing strict air quality regulations and policies to control and reduce pollution levels.