In-Depth Analysis of Physicochemical Properties of Particulate Matter (PM10, PM2.5 and PM1) and Its Characterization through FTIR, XRD and SEM–EDX Techniques in the Foothills of the Hindu Kush Region of Northern Pakistan

The current study investigates the variation and physicochemical properties of ambient particulate matter (PM) in the very important location which lies in the foothills of the Hindu Kush ranges in northern Pakistan. This work investigates the mass concentration, mineral content, elemental composition and morphology of PM in three size fractions, i.e., PM1, PM2.5 and PM10, during the year of 2019. The collected samples were characterized by microscopic and spectroscopic techniques like Fourier transform infrared spectroscopy, X-ray diffraction spectroscopy and scanning electron microscopy (SEM) coupled with energy-dispersive X-ray (EDX) spectroscopy. During the study period, the average temperature, relative humidity, rainfall and wind speed were found to be 17.9 °C, 65.83%, 73.75 mm and 0.23 m/s, respectively. The results showed that the 24 h average mass concentration of PM10, PM2.5 and PM1 were 64 µgm−3, 43.9 µgm−3 and 22.4 µgm−3, respectively. The 24 h concentration of both PM10 and PM2.5 were 1.42 and 2.92 times greater, respectively, than the WHO limits. This study confirms the presence of minerals such as wollastonite, ammonium sulphate, wustite, illite, kaolinite, augite, crocidolite, calcite, calcium aluminosilicate, hematite, copper sulphate, dolomite, quartz, vaterite, calcium iron oxide, muscovite, gypsum and vermiculite. On the basis of FESEM-EDX analysis, 14 elements (O, C, Al, Si, Mg, Na, K, Ca, Fe, N, Mo, B, S and Cl) and six groups of PM (carbonaceous (45%), sulfate (13%), bioaerosols (8%), aluminosilicates (19%), quartz (10%) and nitrate (3%)) were identified.


Introduction
Atmospheric pollution caused by particulate matter (PM) is a potential threat to ecosystems and human life as well as a contributor to climatic changes; it is recognized as a worldwide concern [1,2]. Air pollution mortality is high, with approximately 7 million deaths per annum around the world being reported (WHO, 2016). More than 90% of the cities in poor countries and nearly 50% of the cities in the wealthy countries with populations greater than one hundred thousand are not living according to the World Health Organization air quality guidelines [3].
PM samples were collected during the year 2019. The objectives of the present work were to investigate and gain information about the morphology and elemental composition by field emission electron microscope (FE-SEM) in combination with energy-dispersive X-ray (EDX); to report about minerals through Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD); to understand the frequency of types of particles based on the classification into different categories depending on their morphology and chemical composition.

Site Descriptions of the Sampling Locations
Mingora is the capital city of the Swat district and is located in the north of Pakistan (34.77 • N, 72.36 • E) with an altitude of 984 m above sea level (masl), as shown in Figure 1. The population of Mingora city is over 331 thousand. It is the largest city in the northern part of Khyber Pakhtunkhwa (Pakistan) and the epicenter of the surrounding areas. Located on the northern side of the Mingora city is the Swat River, which is approximately 240 km in length. The eastern and southern parts of the city are surrounded by mountains. These mountains are the part of the famous Hindu Kush range. The minerals in rocks found in the mountains of Swat are kaolinite, clinochlore, calcian albite, epidote, calcite, quartz, paragonite, halloysite and montmorillonite [32]. Being the major city, it has many restaurants, hotels and hospitals (public and private) and better health facilities. Moreover, this city is also the center for different crafts such as woodwork, the mining of gemstone, marbles, and many small-scale industries such as plastic, steel, marble and cosmetics. The climate of the city is moderate, generally warm and humid subtropical. June and January are the hottest and coldest months of the year with mean a temperature of 29.2 • C and 7.6 • C, respectively. There is plenty of precipitation in this site; the recorded annual mean precipitation is 897 mm. Sampling was carried out in the Higher Secondary School building. The building is located on roadside 15 feet above the ground.

Meteorological Conditions of the Sampling Locations
The monthly variation in metrological conditions of Mingora city is depicted in Figure 2. The temperature ranged from 6.5 • C (January) to 29.3 • C (July) with an average value of 17.9 • C. The minimum value of Relative Humidity (RH) varied from a minimum value of 52% during the month of June to a maximum value of 79.67% during the month of January with an average of 65.83%. The maximum Rain Fall (RF) was found to be 141.5 mm during the month of February while the minimum RF was found to be 6 mm in the month of September with an average of 73.75 mm during the study period. The wind speed in the months of January, September, November and December was found to be zero, whereas the maximum wind speed (1.5 m/s) was recorded in the month of June with an average of 0.23 m/s. The wind direction/wind speed figure is added as Figure S1 in the Supplementary Material. The prevailing winds were almost calm during the study period. However, some of the winds at the site arrived from the south, north-west, south-west and south-east directions (see Figure S1).

Sample Collection
Low Volume Sampler (LVS) (Leckel, Germany) was used for the collection of PM in three size fractions, i.e., PM 1 , PM 2.5 and PM 10 . Sampling was carried out for 24 h on a daily basis from 7 am to 7 am during the study period. A total of 120 samples from each fraction were collected on each alternate third day, i.e., 10 samples per month. A constant flow rate of the sampler was kept at 16 liters per minute (LPM). Quartz fiber filter (Tissuquartz, Pall Life Sciences) substrates were used for the collection of PM. The filters were preweighted and conditioned before placing properly in the filter holders of the sampler for operation. When the sampling was conducted the filters were delicately handled using forceps. Filters were properly weighted, conditioned and kept in the Petri-dish and then stored in a refrigerator at 4 • C in order to avoid the evaporation of components that are Atmosphere 2022, 13, 124 4 of 21 volatile due to thermal degradation until further analysis was needed. The gravimetric mass of PM was calculated by subtracting average unloaded filter mass from the average loaded filter mass. Every filter substrate was measured at least three times before and after sampling and afterward the average value was calculated.

Meteorological Conditions of the Sampling Locations
The monthly variation in metrological conditions of Mingora city is depicted in Figure 2. The temperature ranged from 6.5 °C (January) to 29.3 °C (July) with an average value of 17.9 °C. The minimum value of Relative Humidity (RH) varied from a minimum value of 52% during the month of June to a maximum value of 79.67% during the month of January with an average of 65.83%. The maximum Rain Fall (RF) was found to be 141.5 mm during the month of February while the minimum RF was found to be 6 mm in the month of September with an average of 73.75 mm during the study period. The wind speed in the months of January, September, November and December was found to be zero, whereas the maximum wind speed (1.5 m/s) was recorded in the month of June with an average of 0.23 m/s. The wind direction/wind speed figure is added as Figure S1 in the Supplementary Material. The prevailing winds were almost calm during the study period. However, some of the winds at the site arrived from the south, north-west, south-west and south-east directions (see Figure S1).  Identifying the functional groups of the collected PM were carried out using Fourier transform infrared (FT-IR) spectroscopy, which is considered one of the best techniques. This technique can be used for minerals and the determination of functional groups [33][34][35]. The Spectrum two (PerkinElmer, UK) was used to collect FT-IR spectra in UATR (Universal Attenuated Total Reflectance) mode. FT-IR spectra in transmission mode were recorded for all filters. A background scan was performed prior to collecting data for every sample. On average, 200 absorbance scans of wavenumbers between 500 and 3700 cm −1 with 4 cm −1 resolution was performed. Prior to air sampling, the spectra of each quartz filter were measured to use as background reference spectra. Following air sampling, the filter spectra were measured once more. During FT-IR analysis, the ratio was calculated between spectra to open beam spectra, kept as absorbance data files. There was no need to prepare the sample for analysis; therefore, FT-IR samples could be directly characterized. Before usage, every unloaded quartz filter was scanned and the obtained spectra were then subtracted from the spectra received from the scanning of the loaded filters.

Sample Collection
Low Volume Sampler (LVS) (Leckel, Germany) was used for the collection of PM in three size fractions, i.e., PM1, PM 2.5 and PM10. Sampling was carried out for 24 h on a daily basis from 7 am to 7 am during the study period. A total of 120 samples from each fraction were collected on each alternate third day, i.e., 10 samples per month. A constant flow rate of the sampler was kept at 16 liters per minute (LPM). Quartz fiber filter (Tissuquartz, Pall Life Sciences) substrates were used for the collection of PM. The filters were pre-weighted and conditioned before placing properly in the filter holders of the sampler for operation. When the sampling was conducted the filters were delicately handled using forceps. Filters were properly weighted, conditioned and kept in the Petri-dish and then stored in a refrigerator at 4 °C in order to avoid the evaporation of components that are volatile due to thermal degradation until further analysis was needed. The gravimetric mass of PM was calculated by subtracting average unloaded filter mass from the average loaded filter mass. Every filter substrate was measured at least three times before and after sampling and afterward the average value was calculated.

X-ray Diffraction
X-ray diffraction (XRD) is a nondestructive analytical technique which is used for the identification of various types of minerals present in PM. An X-ray diffractometer (XRD: EQUINOX 3000, Thermo Scientific, Waltham, MA, USA) was utilized with a Cu-Kα source (λ = 0.15406 nm). The 2θ values against intensity were recorded from 10 • to 50 • . A piece of 1 cm 2 loaded filter was cut and placed in an aluminum (Al) sample holder for the qualitative analysis using XRD.

Particle Morphology and Its Chemical Nature
Particle composition and morphology are interrelated by the widely used methods as employed by others [36]. The characterized particles were grouped into three, which were anthropogenic, geogenic and biogenic. The majority of anthropogenic particles produced from combustion activities are normally spherical and rounded, having smooth surfaces. Biological particles and particles from the soil dust (minerals) typically constitute natural particles. Soil particles have rough surfaces and irregular shapes and form aggregates with irregular sizes and shapes. Particles of biological basis and origin (plant fragments, spores and pollen) reveal high levels of oxygen and carbon atoms; however, minor contributions from other elements such as Mg, P, Na, Ca and K also exist. These particles have regular and symmetrical morphology such as elliptical and spherical [36].

Element Weight in Percentage
To gain insight into the weight percentage of an individual element, Pipal et al. [36] used EDX analysis for the calculation of the percentage of weight of different elements in PM. The EDX spectra of a blank filter was obtained and then subtracted manually from the EDX spectra of each ambient particle. The percentage of weight of each element was calculated from the EDX spectra of each individual particle. The mean percentage of weight of every element present in PM 10 , PM 2.5 and PM 1 was also calculated. The number of particles present in each group was found afterward and the percentage calculation for every group was determined.

Scanning Electron Microscopy
The samples were characterized with the help of the field emission scanning electron microscope (FE-SEM) TESCAN MAIA3 (Czech Republic). The microscope was equipped with an Octane Elite EDX detector. SEM surface characterization was performed in a high vacuum at suitable accelerating voltages while EDX analyses were performed at 20 kV accelerating voltage. FESEM-EDX provides detailed information about particle size, chemical (elemental) composition and the surface morphology of aerosols particles. Morphology and elemental ingredients of ambient aerosols are key indicators to identify the sources of PM. SEM-EDX methodology has also been used by other researchers in order to investigate the morphology, chemical ingredients, density and origin of the particles [37][38][39][40]. A 1 mm 2 portion was cut from selected filters using scissors and this portion was then raised to an aluminum SEM stub for probing. To deposit a very thin gold layer on each sample, a vacuum coating unit, also known as a gold sputter coater (SPI-MODULE, USA), was used. This was carried out to reduce the electronic charge and achieve better conductivity. The sputter coater had the capability to get six samples ready at one time. The samples were kept at the corner of the chamber of the SEM-EDX and afterward two images of every sample were recorded. The coarse particles were probed with a magnification of 550, producing a field of 60 × 150 µm. In a similar way, the smaller particles were examined by keeping the magnification at 2000, and a field of 60 × 50 µm was produced. We used the back-scattering-electron mode to analyze the morphology and location of the particle. Every installed detector responds to a corresponding signal and ignores the other. In this way undesired and background signals were stopped. The instrument was operated as follows: the probe current was from 50 µA to 100 µA and accelerating voltage was from 0.5 to 30 kV; the samples for analysis were kept at a 20 mm distance from the (Si) detector; X-ray detection was approximately limited to 0.1%; acquisition time for the X-ray was 60 s. The morphological parameters, such as particle shape and physical diameter, were manually measured using the entire images obtained for each field and particle. For every filter-substrate under examination, the results obtained from the three fields were selected randomly. For the elemental characterization of PM particles, each individual particle was scanned by electron beam and EDX spectra were obtained. From the obtained spectra, the identification of different peaks was made and peak intensities were obtained using a computer program, and afterward the percentage of weight was determined [41][42][43]. The PM sample was gold-coated and the gold data of EDX was of no use, so it was manually subtracted at the assessment of EDX spectra.

Mass Concentration
The quantification of the mass concentration of particulate matter is one of the key criterions for the assessment of air quality. Low volume sampler was used to collect PM in three fractions PM 10 [44]. The mass concentration of both PM 10 and PM 2.5 are 1.42 and 2.93 times greater than the WHO levels for 24 h PM concentration. Thus, the overall air quality in the region is not unacceptable. The role of the meteorological condition cannot be avoided in the variation of ambient mass concentration. High PM mass concentration is attributed to high RH, low temperature and low wind speed. Figure 3 indicates that during the winter months (January, February and December) and autumn months (September, October and November), the PM concentration is high in comparison to the other months. The high PM concentration during the winter and autumn seasons is due to the stagnant meteorological condition such as low RH, low wind speed and low temperature inversion. Due to low temperature inversion, the particle concentration is trapped near the ground surface, as a result high PM concentrations were observed. However, during the spring and summer months, the low PM concentrations were due to high temperature and high wind speed. Temperature inversion is high during the spring and summer months, consequently the particles are dispersed and lifted high into the atmosphere, thus, low PM concentrations were observed. The anthropogenic reasons for high PM mass concentration include residential combustion, vehicular emissions and the re-suspension of dust, poor drainage systems and road shoulders that are not cemented. The high mass concentration of PM was noted in the months of January, May and December whereas low concentration was noted in the months of March, April, August and September. The high level of mass concentration is attributed to the combined impact of anthropogenic emissions and meteorological conditions in the study site. The coldness, low RF and low wind speed in the months of January and December result in ambient PM not dispersing quickly which leads to the elevation of mass concentrations. The increase in anthropogenic sources (biomass burning, coal, wood burning and waste material incineration) may have increased the level of mass concentrations. An increase of ambient PM in the month of May is noted due to negligible RF, low wind speed, increase in temperature, increase in vehicular usage (transportation of agricultural commodities) and the burning of agricultural residue. The decrease in anthropogenic sources, in addition to meteorological conditions, may be responsible for the low concentration of ambient concentrations. Some other researchers also observed that meteorological parameters are responsible for PM variations [45,46].

FT-IR Measurement
Fourier transform infrared spectroscopy is one of the most commonly utilized techniques for the determination of minerals in ambient particulate matter [51,52]. FT-IR spectra were recorded in transmission mode by averaging two hundred absorbance scans with a resolution of 4 cm −1 at wave numbers ranging from 500 cm −1 to 3700 cm −1 . Six filter samples (two from each fraction) of PM 10 , PM 2.5 and PM 1 were randomly selected for analysis, their spectra are shown in Figure 4. The absorbance peaks at 615 cm −1 represent (SO 4 ) −2 [53,54]. The feldspar peak is located at 646 cm −1 [55]. Crocidolite's silicate ring vibration and chrysotile's outer Mg-OH vibration is represented by the peak at 652 cm −1 [43]. The absorbance of the IR peak at 671 cm −1 stands for CaSO 4 [56]. The IR band of absorbance at 713 cm −1 indicates the occurrence of nitrate ions, i.e., NH 4 NO 3 [56]. The peak at 750 cm −1 indicates the Al-O-Si in-plane vibration of the illite mineral [43]. The stretching mode of the vibration of Si-O, which is the characteristic frequency of silica, occurred at 777 cm −1 [43]. Inorganic nitrate is located at 835 cm −1 [35]. The absorbance peak at 880 cm −1 represents calcite [57]. The peak at 1020 cm −1 is indicative of augite (pyroxene mineral) [58]. Researchers attributed the peaks observed at 1075 cm −1 and 1153 cm −1 to quartz (silica) [55]. One of the most common crystalline silicate minerals is quartz. According to epidemiological studies, inhaling crystalline silica dust can cause Atmosphere 2022, 13, 124 9 of 21 pulmonary tuberculosis, inflammation, lung cancer and silicosis depending on the exposure dose [59]. The absorbance band noted at 1216 cm −1 is indicative of silica's asymmetric stretching to Si-O-Si [33]. The cerussite mineral is also observed in the present study whose peak is located at 1385 cm −1 [51]. The absorbance peak at 1414 cm −1 represents NO 4 + [60]. The inorganic carbonate (C−N (CH 3 ) 2 ) stretch is observed at 1502 cm −1 [33]. The asymmetric CO 2 stretch in carboxylates is located at 1644 cm −1 [33]. The saturated C=O stretch in aldehyde occurred at 1736 cm −1 [33]. The IR absorbance peak at 1772 cm −1 is an indicator of feldspar [51]. Aliphatic C-H stretching is located at 2852 cm −1 and aromatic C-H stretching at 2923 cm −1 [61]. The calcite mineral is indicated by the peak observed at 2957 cm −1 [55]. The absorbance of IR at 3400 cm −1 corresponds to O-H stretching [61]. [43]. Inorganic nitrate is located at 835 cm −1 [35]. The absorbance peak at 880 cm −1 repre sents calcite [57]. The peak at 1020 cm −1 is indicative of augite (pyroxene mineral) [58 Researchers attributed the peaks observed at 1075 cm −1 and 1153 cm −1 to quartz (silica) [55 One of the most common crystalline silicate minerals is quartz. According to epidemio logical studies, inhaling crystalline silica dust can cause pulmonary tuberculosis, inflam mation, lung cancer and silicosis depending on the exposure dose [59]. The absorbanc band noted at 1216 cm −1 is indicative of silica's asymmetric stretching to Si-O-Si [33]. Th cerussite mineral is also observed in the present study whose peak is located at 1385 cm [51]. The absorbance peak at 1414 cm −1 represents NO4 + [60]. The inorganic carbonate (C−N (CH3)2) stretch is observed at 1502 cm −1 [33]. The asymmetric CO2 stretch in carboxylate is located at 1644 cm −1 [33]. The saturated C=O stretch in aldehyde occurred at 1736 cm [33]. The IR absorbance peak at 1772 cm −1 is an indicator of feldspar [51]. Aliphatic C-H stretching is located at 2852 cm −1 and aromatic C-H stretching at 2923 cm −1 [61]. The calcit mineral is indicated by the peak observed at 2957 cm −1 [55]. The absorbance of IR at 340 cm −1 corresponds to O-H stretching [61].

XRD Measurements
In mineralogical research, XRD measurement is the perfect complement to FT-IR measurement, which is used to determine minerals found in complex samples like atmospheric PM and soil samples. In the XRD spectrum, a perfectly crystalline material has more prominent peaks as compared to a less crystalline material. Due to differences in the crystalline properties of materials, all the minerals found in FT-IR may be undetectable in XRD measurement. This finding is in-line with a study published in the literature that found asbestiform minerals in FT-IR but not in XRD investigations [51]. XRD analysis during the studied period are shown in Figure 5. XRD peaks of the mineral wollastonite (CaSiO 3 ) appeared at the 2-theta value of 12.5 • and 21.5 • , ammonium sulphate (NH 4 ) 2 SO 4 was noted at an angle of 14 [63]. Similarly, the mineral crocidolite had a characteristic peak at 28.8 • [64]. during the studied period are shown in Figure 5. XRD peaks of the mineral wollastonite (CaSiO3) appeared at the 2-theta value of 12.5° and 21.5°, ammonium sulphate (NH4)2SO was noted at an angle of 14.1° and 16.8°, wustite was found at an angle of 15.4°, calcium iron oxide, muscovite, gypsum and vermiculite minerals were detected at corresponding peaks of 18.1°, 20.6°, 23.7° and at 23.5°, respectively [62]. The mineral illite appeared at 2θ values of 17.8°, 23.1°, 26.3° and 47.6°, calcite had characteristic peaks at 29.4° and 47.5° minerals like hematite, dolomite and vaterite were detected having corresponding peak at 37.5°, 41.2° and 43.4° [43]. Characteristic peaks for kaolinite, calcium aluminum silicate and gypsum were detected at an angle of 12.30, 35.9° and 23.7°, respectively [55,62]. The mineral augite appeared at an angle of 27.6° and quartz was observed at 40.5°, 40.8°, 42.4 and 44.4° [43,55]. CuSO4 and FeSO4 were detected at 38° and 45°, respectively [63]. Simi larly, the mineral crocidolite had a characteristic peak at 28.8° [64].

Particulate Matter's Major Subgroups Using FE-SEM in Combination with Energy-Dispersive X-ray
On the basis of the FE-SEM coupled with EDX results the particulate matter are classified into anthropogenic, geogenic and biogenic particles.

Anthropogenic Particles
Such types of particles consist of industrial and carbonaceous particles. Local sources (emission) are main contributor of anthropogenic particles.

Carbonaceous Particles
Carbonaceous particles are the major contributor to total suspended particles (TSP). Vehicular emission is the main source of carbonaceous particles in the study area. EDX analysis of the targeted spot indicates the element's sequence in weight-age abundance as C > O > Ca > Al > S > Si > Na. The morphology of such types of particles are aggregated chains or cloudiness dependent on the types of fuels, burning style and atmospheric conditions [65][66][67][68][69][70]. The burning of woods, dung cakes and Kerosene oil for cooking, in addition to congested traffic, old and unmaintained vehicles produce smoke in the city of Mingora. Concentration of carbon in the ambient environment is because of incomplete burning of fuels and biomass [71]. The finding of C along with K and S is the sign of soot particles, its production sources include agricultural burning, wood burning and the burning of organic fuels such as biomass, diesel, coal and oil [72,73]. Carbonaceous particles have diverse morphologies. Aggregated spherical carbonaceous particles noted in our study, in which the (C + O) percentage is greater than 92%, are depicted in Figure 6a. The particle size observed using Image J software was 0.54 µm on average. The percentage of such kinds of particles in our study were 45% as indicated in Figure 7. Previous research confirms that such particles absorb and scatter light, hence efficiently affecting climate [68,74,75]. Other investigators have noted similar findings [40,76].

Sulfate Particles
Sulfur (S)-containing particles can be found in the air. Sulfate soot was identified along with mineral dust particles. The existence of sulfur indicates that they were formed during the combustion process [77]. These particles most likely originated from soil dust, resuspension from the earth crust and road as well as from other anthropogenic activities such as construction and on-road vehicular movement, combustion operations and agricultural fields [63,78]. Figure 6b indicate the sulfur-rich particles along with other elements such as O, Si, Ca, Al and Mg. In the current study, the size of these particles ranged from 2.1 to 7.3 µm. The atomic percentage of weight of these particles were 13% as depicted in Figure 7.

Biogenic Particles
The particles with a biological origin were quantified by the technique used by Matthias-Maser and Jaenicke [79]. Researchers documented that particles with a biological origin (alive or dead) have trace (minor) quantities of Na, Mg, K, P, Si, Fe, Cl, Al and Ca. Biogenic particles are of various shapes and sizes [66,[79][80][81][82]. For the identification and analysis of biological particulate matter, the clustering rules given in the following line was used, as established by Coz et al. [83].
Bioaerosols: [(O + C) > 75% and 1% < K; P; Cl < 10%]. These particles include bacteria, viruses, pollen, spores, animal matter and plant debris. In this study, biological particles were identified as shown in Figure 6c. C + O = 97.24%, while Ca > Al > S > Si were in minimal amounts. This particle was 0.86 µm in length and 0.3 µm in width. The percentage of weight of this type of particle among other analyzed particles was 8%, as depicted in Figure 7. Other research has documented similar particles in the atmosphere [68,[83][84][85]. Atmosphere 2022, 13, x FOR PEER REVIEW 16 of 22

Geogenic Particles
Natural crustal particles are referred to as Geogenic particles. These include aluminosilicate, calcium-rich particles and quartz, etc.

Aluminosilicates
The detection of elements like Al, Ca, C, Fe, Mg, O, K, Si, and Na confirmed the presence of aluminosilicate and quartz. The comparison of the current analysis to previously published research indicates that geogenic particles are generated by the re-suspension of soil/road dust and other anthropogenic particles from fossil fuels and biomass combustion [62,[86][87][88]. Aluminosilicates make up to 72% of all chemical compounds found in the Earth's crust [68]. Our findings indicate that particles of aluminosilicates extracted from the soil are primarily made up of oxides of Al and Si, with varying quantities of K, Na, Ca, Mg and Fe. The size of aluminosilicate particles ranged from 2.3 µm to 30 µm. The particles analyzed in this category are shown in Figure 6d. These particles had a sharp edge-like morphology and were identified as Na-feldspar (albite), in the same way other particles were identified, such as Ca-Mg aluminum silicate, Figure 5e; K-feldspar (K aluminum silicate), Figure 5f; Mg-iron aluminosilicate, not shown in figure. This aluminosilicate category accounts for approximately 19% of the total particles examined, suggesting that minerogenic particles are abundant, as shown in Figure 7. Other researchers have also found similar findings about aluminosilicate [40,62,89].
Quartz Quartz (SiO 2 ) particles (also known as silica) have a high silicon (Si) and oxygen (O) content. These particles are characterized by having almost 50% Si + O by weight. In our environment, pure silica particles are found naturally as well as anthropogenically [46,62,76]. It is the most common chemical constituent of the Earth's crust. The key component of sandstone and granite is silica. Hence, soil is the most common source of silica particles. Furthermore, silica is widely used in the manufacturing of building materials such as cement, glass, bricks, clays and ceramics. As a result, these particles are likely to have come from the construction and demolition of buildings [46]. These particles represent 10% of the total particles analyzed, as shown in Figure 7. The size range of silica is from 0.23 to 0.45 µm. In this group, particles of grossular, biotite and almandine were identified, as shown in Figure 6g-i. Similar kinds of particles have been identified by previous analysis [40,46].

Nitrogen-Rich Particles
From the elemental composition and morphological analysis, we identified a nitraterich particle in our samples, Figure 6j. Typically, such particles exist in irregular shapes [90]. Most of the nitrate in the air is in the form of NaNO 3 , which is generated by the heterogeneous reactions of salt aerosols with gaseous HNO 3 and other nitrous compounds [91]. These particles contribute 3% to the total investigated particles, as shown in Figure 7. The measured size was 0.29 µm. The FT-IR findings matched XRD and SEM-EDX results for the minerals such as crocidolite, chrysotile, CaSO 4 , NH 4 NO 3 , illite, inorganic nitrate, calcite, augite, quartz, feldspar, aldehyde and inorganic carbonate, etc. The EDX data also reveals the sorts of elements required for the formula unit of these minerals, the elemental details are depicted in Figure 8.  and O are greater in percentage. The finding of potassium (K), sulfur (S) and carbon (C) in the atmosphere was due to biomass burning, diesel generators, vehicular emissions, waste incineration, wood burning or agricultural burning in household activities and brick kiln activities in the surrounding areas [72,92,93]. The detection of other elements such as oxygen (O), iron (Fe), silicon (Si), magnesium (Mg), calcium (Ca) and sodium (Na) was due to clay minerals caused by dust re-suspension (wind blowing, vehicular trafficking and building construction) [55,94]. Previous scientific studies confirm that silicon (Si) is the most important constituent of soil minerals [95]. Our study recorded the element nitrogen (N) in the atmosphere of Mingora city. The major source of nitrogen was the waste dumps, decomposition of animal and plants and the use of nitrogen rich fertilizer for crops. Moreover, boron (B) was also detected in our investigations. Cutting and mining in the mountains in the surrounding area contributed boron to the environment. The presence of boron in the urban environment was due to the volatilization of boron during the process of coal combustion [96].  Figure 8 gives a summary of the weight-wise percentage of elements. The total amount of atoms related to the corresponding fraction of PM was computed and then the percentage of weight of each atom in the fraction of PM was calculated. According to EDX spectroscopy, fourteen elements were noted in the samples of the PM1 fraction, which were O, C, Al, Si, Mg, Na, K, Ca, Fe, N, Mo, B, S and Cl. In PM2.5, the recorded elements were O, C, Si, B, Ca, Al, N, Fe, Mg, S, Na, K and Mo, whereas in the samples of PM10, we noted C, O, Si, Na, Cl, Al, K, Fe, Ca and Mg. Our analysis indicates that C and O are greater in percentage. The finding of potassium (K), sulfur (S) and carbon (C) in the atmosphere was due to biomass burning, diesel generators, vehicular emissions, waste incineration, wood burning or agricultural burning in household activities and brick kiln activities in the surrounding areas [72,92,93]. The detection of other elements such as oxygen (O), iron (Fe), silicon (Si), magnesium (Mg), calcium (Ca) and sodium (Na) was due to clay minerals caused by dust re-suspension (wind blowing, vehicular trafficking and building construction) [55,94]. Previous scientific studies confirm that silicon (Si) is the most important constituent of soil minerals [95]. Our study recorded the element nitrogen (N) in the atmosphere of Mingora city. The major source of nitrogen was the waste dumps, decomposition of animal and plants and the use of nitrogen rich fertilizer for crops. Moreover, boron (B) was also detected in our investigations. Cutting and mining in the mountains in the surrounding area contributed boron to the environment. The presence of boron in the urban environment was due to the volatilization of boron during the process of coal combustion [96].

Conclusions
Owing to drastic urbanization, increasing transportation, roads and building construction, mining and industrialization, the mass concentration of particulate matter in different locations of the world had increased. In the urban environment of Swat, the concentration is above the limits set by the WHO. Thus, the air quality is becoming worse

Conclusions
Owing to drastic urbanization, increasing transportation, roads and building construction, mining and industrialization, the mass concentration of particulate matter in different locations of the world had increased. In the urban environment of Swat, the concentration is above the limits set by the WHO. Thus, the air quality is becoming worse every day in the region.