Special issue in honor of Prof. David Y.H. Pui for his “50 Years of Contribution in Aerosol Science and Technology” (V)

Yi-Bo Zhao1,2, Nathalie Hayeck3, Najat A. Saliba4, Claudia Schreiner  2, Markus Zennegg2, Fuze Jiang1,2, Renato Figi2, Davide Bleiner2, Jing Wang   1,2

1 Institute of Environmental Engineering, ETH Zürich, 8093 Zürich, Switzerland
2 Advanced Analytical Technologies, Empa, Ueberlandstrasse 129, 8600 Dübendorf, Switzerland
3 Department of Natural Sciences, Lebanese American University, Chouran, Beirut 1102-2801, Lebanon
4 Department of Chemistry, Faculty of Arts and Sciences, American University of Beirut, Beirut 1107-2020, Lebanon


Received: November 15, 2022
Revised: January 31, 2023
Accepted: February 28, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.220395  


Cite this article:

Zhao, Y.B., Hayeck, N., Saliba, N.A., Schreiner, C., Zennegg, M., Jiang, F., Figi, R., Bleiner, D., Wang, J. (2023). Any Long-term Effect of the Beirut Port Explosion on the Airborne Particulate Matter? Aerosol Air Qual. Res. 23, 220395. https://doi.org/10.4209/aaqr.220395


HIGHLIGHTS

  • No direct effect of explosion pollutants on the PM was found after 1–3 months.
  • Demolition and reconstruction were causing a serious PM level after the explosion.
  • Demolition, traffic, and diesel generators were the main PM emission sources.
  • Cancer risks and ground-level PM were several times higher than the accepted levels.
 

ABSTRACT


The Beirut port explosion in 2020 released a huge amount of chemicals including ammonium nitrate, however, the long-term effects of the explosion on air quality and public health remain unclear. In this study, particulate matter (PM10) samples were collected in Beirut, Lebanon 1 month and 3 months after the explosion. The average concentrations of main anions measured in 2020 (one and three months after the explosion) were compared with those in 2009–2015 by calculating the percentage of difference, and the average concentrations of cations and anions in September (one month after the explosion) and November (three months after the explosion) 2020 were also compared to identify any abnormal values, indicating insignificant effects on the post-explosion PM in terms of component concentrations. That is, PM and gases directly induced by the explosion might be subject to rapid atmospheric transport and deposition. Hence, the results imply that investigations of the chemical contaminations in soil and water are urgently needed. Long-term monitoring is necessary to avoid subsequent air pollution caused by possible particle resuspension. The continuous demolition and reconstruction after the explosion are possibly the main long-term effect of the Beirut port explosion, causing an elevated concentration of PM2.5 at ground level 400% higher than the recommended concentrations (15 µg m–3 for 24-hour mean). Protective measures must be taken to reduce the exposure risks by controlling the PM release from demolition and construction, traffic, and diesel generators. The cancer risk in Beirut based on PAHs measurements in 2021 was also estimated and discussed.


Keywords: Ammonium nitrate, Beirut port explosion, Particulate matter, Air quality, Exposure risks


1 INTRODUCTION


Beirut, a Mediterranean metropolis, has been suffering from severe air pollution events in past years (Waked et al., 2013; Baayoun et al., 2019), which pose serious threats to public health. For example, air pollution induced by PM2.5 and PM10 in Beirut was closely associated with health issues including urticaria especially among people younger than 16 years old (Mrad-Nakhlé et al., 2021), and cardiovascular diseases (Nasser et al., 2015; Hajir et al., 2021). The serious effects of PM on circulatory admissions especially for adults and the elderly were observed in Beirut (Nakhlé et al., 2015). It was found that maternal exposure to PM2.5 in Lebanon was significantly related to the higher risks of birth defects, genitourinary defects, and neural tube defects (Al Noaimi et al., 2021). The cancer risk due to PAHs in Beirut increased from 1.05 × 10–6 in 2015 to 2.25 × 106 in 2017, which was 2.25 times higher than the threshold for acceptable risk set by EPA (10–6) (Jaafar et al., 2021). The insufficient electricity sector induced the further development of decentralized diesel generators (Ahmad et al., 2022), and traffic was the main anthropogenic emission source due to the poor regulation enforcement (Waked and Afif, 2012; Mansour et al., 2018; Abdallah et al., 2020). Diesel generators and traffic were the main emission sources of PAHs, leading to a higher excess cancer risk than the threshold for acceptable risk (10–6). The cumulative cancer risk of non-methane hydrocarbons surpassed the acceptable level (10–6) by 30–40 times, which was mainly attributed to traffic gasoline evaporation and combustion (Dhaini et al., 2017). In a more recent study, the main emission sources of PAHs were traffic, diesel generators, and incineration in 2017, accounting for 48%, 23%, and 29%, respectively, which increased the cancer risk by 35% compared to that in 2015 (Jaafar et al., 2021). Therefore, the understanding and control of air pollution in Beirut are crucial to improving air quality and protecting public health.

The recent explosion in Beirut port, Lebanon on 4 August 2020 could be one of the serious pollution events exacerbating the air quality and public health. It was estimated that the explosive range was 130 to 2000 tons of TNT (trinitrotoluene) possibly due to the explosion of 2750 tons of ammonium nitrate, leading to thousands of casualties (Pasman et al., 2020; Pilger et al., 2021), which was one of the most severe ammonium nitrate explosions in the world. Studies regarding the Beirut port explosion have been recently published mainly focusing on the lessons learned from the incident, such as health and environmental implications (Al-Hajj et al., 2021). The Beirut port explosion could release a large amount of pollutants such as ammonia and nitrous oxide depending on the temperature (Pittman et al., 2014; ur Rehman et al., 2021), and affected the generation and suspension of particulate matter, which stayed in the air for a longer time (Al-Hajj et al., 2021). The release of NOx due to the Beirut port explosion affected a large area with massive atmospheric transport and deposition (Broomandi et al., 2021). A recent study indicated that NO2 concentrations returned to normal level 7 days after the explosion and PM10 levels remained normal after the explosion (Ali et al., 2022). Nonetheless, the long-term effect of ammonium nitrate explosion on the airborne particle phase and its exposure risk is still limited in Beirut, which become a growing academic and public concern. To our knowledge, there were about 40 explosion accidents involving ammonium nitrate globally since 1900 (Yu et al., 2021). The investigation on the airborne particulate matter in Beirut also provides insights into the air quality and protective measures after the explosion accidents of ammonium nitrate around the world.

In this study, for the first time, we performed the analysis of concentration, composition, and exposure risk of airborne PM 1–3 months after the ammonium nitrate explosion in Beirut. The long-term effects of the Beirut port explosion on air quality were evaluated according to analysis of PM chemical compositions. Due to limited information about PM source apportionment in Lebanon (Fakhri et al., 2022), the main emission sources of PM were identified based on available publications and the relationship between PM mass measurements and observed nearby activities. It is also essential to estimate the cancer risks due to the bioaccumulation and carcinogenic properties of PAHs (Sari et al., 2021). The cancer risk calculation was based on the PAH concentrations from the main emission sources. The estimated cancer risks in the scenario with these main emission sources were calculated to perform the cancer risk assessment. It was noted that other pollutants such as heavy metals were not involved in the cancer risk assessment as there was no clear source apportionment for these pollutants. Accordingly, this work could be helpful for the understanding of airborne PM after the explosion and policymaking for PM emission reduction.

 
2 MATERIALS AND METHODS


 
2.1 Sampling Description

PM10 samples were collected on prebaked quartz filters (sampled = Ø 14 cm) using a high-volume sampler at 500 L min1 for 24 hours at two sampling sites (Table S1). The sampling sites included the rooftop of the chemistry department at the American University of Beirut (AUB site, n = 3) and the rooftop of the Geitaoui Hospital facing the port (Geitaoui site, n = 3). Due to the limited operation situations, three samples were collected at the AUB sites 1 month after the explosion, and another three samples were collected at the Geitaoui site 3 months after the explosion. A blank sample was prepared to ensure the measurement quality. A continuous monitoring of PM10 levels in Beirut for a longer time was obtained from PurpleAir Air Quality Database (PurpleAir, 2021). The sampling on the rooftop was to investigate the atmospheric concentrations and avoid the interference from ground-level emissions. The collected filters were analyzed for elemental composition and distribution of PM, inorganic ions, metals, PAHs, and PCBs. The possible explosion chemical was the 2750 tons of ammonium nitrate (Pilger et al., 2021). Therefore, one of the goals was to identify any abnormal concentration of ammonium and nitrate in PM, which could indicate some long-term effects of the explosion. These two sites are shown in Fig. 1 adapted from the map created by Beirut Urban Lab and Lebanon's National Council for Scientific Research (2021). The classification of these two sites is based on the wind direction during the sampling days (Table S1) as well as the prevailing wind directions recorded by the weather station at Beirut Airport (https://www.windfinder.com/windstatistics/beirut) which are W/SW (August and September) and N/NW (October to November). Two sampling sites were chosen to study the impact of the Beirut port explosion on airborne particulate matter. The first one, the AUB site, is a background site located upwind from the port. As a result, the samples collected on this site are not notably affected by the blast and the resulting demolition and construction activities. The second site, Getaoui, is a downwind site from the port and located in the heart of the area affected by the blast. The prevailing wind in the Getaoui area transports pollutants either from the port zone or from one of the highly affected areas.

Fig. 1. Sampling sites (AUB and Geitaoui) in Beirut, Lebanon, and a sampler and sampling filter used in this study.Fig. 1. Sampling sites (AUB and Geitaoui) in Beirut, Lebanon, and a sampler and sampling filter used in this study.

In addition to the ambient 24-hour sampling, a comparison of street pollution between Hamra and Gemmayze in Beirut was performed by measuring the ground-level PM1, PM2.5, and PM10 concentrations using a DustTrak DRX aerosol monitor (model 8533, TSI) in September–December 2020 and April–June 2021. Two researchers walked 4 km on streets simultaneously with the DustTrak DRX aerosol monitors at Hamra and Gemmayze starting at 10 am for 45 min during weekdays. The campaign was conducted 1–3 months (September–December 2020) and 8–9 months (April–June 2021) after the explosion, and a total of 19 ground-level trips for 45 min at each site were recorded. The details of sampling dates and PM2.5 mass concentration are included in the supporting information.

 
2.2 Analytical Methods

The Wavelength Dispersive X-ray fluorescence analysis (WD-XRF) was first performed on the Rigaku Primus IV instrument directly on the surface of the quartz filter samples with a detection limit of approximately 1000 µg g1 (ppm), depending on the sought elements and the sample matrix and mass of loading on the filter (Table S2). The functional groups of PM10 particles on filters were measured using Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR) (Agilent Cary 600 series). environmental scanning electron microscopy (ESEM) (Thermo Fisher Quanta 650) was used to determine the morphology of PM10 particles and an energy-dispersive X-ray spectroscopy detection (EDS) was performed to analyze element compositions and distributions. The quantitative determination of cations, anions, and metals was carried out after two aqueous boiling extractions in the first step with 15 mL boiling water high-purity water (18M Ohm.cm) and in the second step with 10 mL boiling high-purity water (18M Ohm.cm) of the 1/4 filter material. The measurement for the anions was carried out by ion chromatography (IC) (Metrohm IC 882 Compact Plus) and for the cations by inductively coupled plasma mass spectrometry (ICP-MS) (Agilent Triple Quad 8800), after acidified by nitric acid (67% normatom VWR) on pH. Boiling water extraction was considered a proper method for the extraction of inorganic components from sampling filters, which works similarly to ultrasonic extraction and sequential warm solution leach in terms of spike recovery (Jenke, 1983). Certified reference materials were used for quality assurance. The detection limit and recovery ratios were summarized in the supporting information.

For GC-MS analysis, all glassware used for the analysis was treated in a bath with a strong alkaline detergent for 24h (RBS 50) before being washed thoroughly in a laboratory dishwasher. Afterward, all the glassware was heated overnight in a ceramic oven at 450°C. Before use, the glassware was rinsed several times with ultra-pure solvents (dichloromethane and cyclohexane). All solvents used were of pesticide grade (Biosolve, Valkenswaard, The Netherlands). Response factors for all the 16 EPA PAHs between deuterated and native PAHs (Supelco, Bellefonte, USA) were determined just before the sample series were analyzed. One-quarter of the filter (with about 5 mg PM10 on it) was extracted by Soxhlet extraction with cyclohexane for 10 hours. The extract was concentrated using a rotary evaporator at 230 mbar and 50°C down to 1 mL and then was transferred to a 2 mL measuring flask and filled up with cyclohexane. An aliquot of 0.1 mL of the crude extract was spiked with a mixture of 16 deuterated EPA PAHs at a level of 25 ng each. One microliter of the extract was injected into Q-Exactive Orbitrap gas chromatography/high-resolution mass spectrometry (GC-HRMS). The gas chromatographic separation was conducted on a 30 m × 0.25 mm × 0.25 µm TG5-SilMS column (Thermo Scientific) with helium as the carrier gas at a flow rate of 1.5 mL min1. After splitless injection at 260°C, the column was ramped from 100 to 300°C at 10°C min1. The mass spectrometer was operated under electron impact (70 eV) at a resolution of 60000 and mass accuracy of < 1 ppm. The m/z values between 100 and 300 were obtained in full scan mode and the automatic gain control (AGC) was set to 106 ions. The full scan mode was initially used to fully explore the possible organic compounds, and possible detected compounds were listed in the Supporting Information (Tables S5–S11). The signals of the exact masses of the molecular ion of the 16 EPA PAH analytes and the corresponding deuterated analog were used for the quantification. These 16 PAHs included naphthalene (Nap), acenaphthylene (Acy), acenaphthene (Ace), Fluorene (Flu), Phenanthrene (Phe), Anthracene (Ant), Fluoranthene (Flt), Pyrene (Pyr), Benzo-a-anthracene (BaA), Chrysene (Chr), Benzo-b-fluoranthene (BbF), Benzo-k-fluoranthene (BkF), Benzo-a-pyrene (BaP), Indeno-123-cd-pyrene (IP), Dibenz-ah-anthracene (DahA), and Benzo-ghi-perylene (BghiP).

 
2.3 Estimation of Cancer Risk

The estimation of cancer risk was based on PAHs concentrations. PAHs concentrations were converted into the total BaP equivalent concentration (∑BaPeq), which was used to evaluate the carcinogenicity of PAHs (Yu et al., 2022), using the equation:

 

where Ci is the concentration of each PAH in ng m3, and TEFi is the toxicity equivalent factor of each PAH. Excess cancer risk (ECR) was calculated based on the following equation (Hieu and Lee, 2010):

 

where URBaP is the number of people at risk of contracting cancer from inhalation of BaP equivalent concentration of 1 ng m3 over a lifetime of 70 years in population, which is 1.1 × 106 (U.S. EPA, 2011; Reche et al., 2012).


3 RESULTS AND DISCUSSION


 
3.1 Inorganic Components in PM10

FTIR results indicated the presence of aliphatic carbons, organonitrate, ammonium, nitrate, sulfate in PM10 particles (Fig. 2), based on the wavelength ranges identified in a previous study (Shaka’ and Saliba, 2004). Specifically, organonitrate was formed by correlating nitrates with organic matter in fine particles (Jaafar et al., 2014). The comparable average concentration of main inorganic components at AUB and Geitaoui including cations, anions, and metals indicated that most of the inorganic components were distributed homogeneously in the studied area and sampling period (Fig. 3 and Table S12). In particular, the concentrations of NH4+ and NO3 were 1.49 ± 0.33 and 2.29 ± 0.31 µg m3 one month after the explosion (at AUB), respectively, whereas the concentrations were 1.20 ± 0.31 and 2.30 ± 0.83 µg m3 three months after the explosion (at Geitaoui). The major inorganic component was sulfate with an average concentration of 6.73 µg m3, and the major metals were iron (24.2 ng m3), vanadium (13.2 ng m3), and zinc (23.9 ng m3) (Fig. 3 and Table S12). Specifically, the concentration of SO42 was 121% higher one month after the explosion compared with that three months after the explosion, which could be related to SO2 emission involved either a long-range transport (Saliba et al., 2009) or the effects of the explosion and the two fires that took place after the explosion. Another explanation was that the higher concentration of sulfate was induced by demolition activities after the explosion, which was observed to increase by 187.9% in road dust smaller than 38 µm around a demolition site (Brown et al., 2015). A previous study of the PM composition in Beirut has shown that SO42 and NH4+ were more concentrated in PM0.3 (about 90%) compared to PM0.3-2.5 and their gas-to-particle conversion was involved in PM0.3 (Borgie et al., 2016). Therefore, future studies focusing on size-resolved compositions of PM are needed to further investigate the effects of decomposition and combustion gases on air quality. Furthermore, future works could provide more information about secondary formation of nitrate and sulfate based on the sulfur oxidation ratio and nitrogen oxidation ratio (Sun et al., 2006).

Fig. 2. FTIR analysis of PM10 samples collected at AUB and Geitaoui.Fig. 2. FTIR analysis of PM10 samples collected at AUB and Geitaoui.

Fig. 3. Concentrations of (a) main anion, cation and (b) metal ions in PM10 samples collected at AUB and Geitaoui. Grey and red bars indicated the concentrations on AUB and Geitaoui samples, respectively.Fig. 3. Concentrations of (a) main anion, cation and (b) metal ions in PM10 samples collected at AUB and Geitaoui. Grey and red bars indicated the concentrations on AUB and Geitaoui samples, respectively.

The time-serial comparison of the inorganic components including nitrate and metals showed a decreasing trend in recent years, and no exceptional concentration 1–3 months after the explosion was observed, compared with past years (Fig. 4 and Table 1). For instance, the concentration of Cl, NO3, and SO42 were 0.55, 2.29, and 9.26 µg m3 one month after the explosion, which fell into the range of 0–18.4, 1.66–9.15, 1.20–13.8 µg m3 measured in 2009–2015, respectively (Fig. 4(a)). Overall, the concentrations of these chemicals measured in 2020 (one and three months after the explosion) were comparable to those in 2009–2015 (Fig. 4(b)). Besides that, the concentration of most metals such as Fe, Zn, Pb, and Cu was lower than the previous monitoring record in 2012 and 2015 (Table 1). The concentrations of the inorganic components between 2009 and 2015 are monthly averages obtained from several studies conducted in Beirut. PM10 were collected at the same AUB site and other sites in Beirut city. The inorganic ions were determined using ion chromatography (Massoud et al., 2011; Lovett et al., 2018). The percentage difference between NO3 concentrations in 2020 (one and three months after the explosion) and 2009–2015 was calculated, which was 48.3%. The percentage difference between NO3, PO43 and NH4+ concentrations in September (one month after the explosion) and November (three months after the explosion) 2020 was 0.1%, 19.2%, and 21.6%, suggesting no abnormal airborne concentrations and insignificant direct effects of the NH4NO3 explosion. It indicated rapid atmospheric transport and deposition of ammonium and nitrate 1–3 months after the explosion, as major decomposition gases such as NH3, N2O, NO, NO2 and HNO3 were produced based on the thermal decomposition mechanism of ammonium nitrate (Yang et al., 2017), which could be transported by wind and scrubbed by rainfall. As a proof, a recent study based on data from Sentinel-5P program has shown an increase of the NO2 levels in Lebanon after the blast. However, these levels were back to normal 7 days after the explosion. Also, they attributed the increase in the daily average atmospheric pressure to the decomposition of ammonium nitrate (Ali et al., 2022). Therefore, it also implies that investigations of contamination in soil and water are urgently needed due to the huge amount of ammonium nitrate involved in the explosion. For instance, the nitrate concentration at a depth of 5 m was above 30 times higher than the groundwater quality standard after the Tianjin Port 8·12 explosion in China, which could be a health threat to nearby residents (Liu et al., 2019).

Fig. 4. (a) Time-serial average concentrations of Cl–, NO3–, SO42– in Beirut, Lebanon; (b) comparison of PM, Cl–, NO3–, SO42– concentrations in 2020 (one and three months after the explosion) and 2009–2015.Fig. 4. (a) Time-serial average concentrations of Cl, NO3, SO42– in Beirut, Lebanon; (b) comparison of PM, Cl, NO3, SO42– concentrations in 2020 (one and three months after the explosion) and 2009–2015.

Table 1 Average concentration (ng m–3) of metals in PM10 in Beirut, Lebanon (Lovett et al., 2018). The measurements from this study are compared to previous measurements in Beirut (AUB location) by Saliba research group. Some of these data were not previously published.

Mass fraction of airborne components was calculated using the mass measured by instruments mentioned in the method section, divided by total PM10 mass. The soluble inorganic ions contributed to around 32% in PM10 one month and three months after the explosion (Figs. 5(a) and 5(b)), suggesting a possible dust-rich condition due to major construction with a higher fraction of mineral elements, organic and elemental carbon than non-dust days (Saliba and Chamseddine, 2012). PM10 especially large particles with different shapes and sizes were visualized in Fig. 6. We also searched for the possible presence of asbestos (Mg3Si2O5(OH)4) due to its toxicity (Kuroda, 2021), which was common in the shape of fibers. Fiber-liked particles were observed using SEM (Fig. S1). Based on the EDS mapping, the fraction of each element in AUB and Geitaoui samples was acquired (Fig. S1 and Table S13). The fraction of Mg was not significant in all PM10 samples, which accounted for 0.1–0.2% of total elements (Table S13). The fraction of Si and O increased due to the interference from the quartz filter substrate to further lower the fraction of Mg. For asbestos materials, the 3700–3500 cm1 region can be attributed to O-H stretching vibrations, and the bands observed in the 1200–500 cm1 region can be attributed to various lattice vibrations (Zholobenko et al., 2021). There was no obvious peak in the corresponding regions according to the FTIR-ATR result (Fig. S2). Therefore, no clear evidence was found to confirm the presence of asbestos in post-explosion PM10. In addition, to assess the population exposure to asbestos spread out by the demolition and destruction activities, eleven rubble samples were randomly collected from Gemayze, Mar Mikhael and Karantina areas and analyzed for asbestos by Ethos Environmental Ltd using polarized light microscopy (PLM). Details on the sampling sites and location are shared in the supporting information. All eleven samples did not show any asbestos content.

Fig. 5. Proportions of inorganic and organic components in PM10 samples collected at (a) AUB and (b) Geitaoui.Fig. 5. Proportions of inorganic and organic components in PM10 samples collected at (a) AUB and (b) Geitaoui.

Fig. 6. SEM images of airborne PM10 samples on (a) AUB 5, (b) AUB 6, (c) AUB 7, (d) Geitaoui 4, (e) Geitaoui 5, (f) Geitaoui 6.Fig. 6. SEM images of airborne PM10 samples on (a) AUB 5, (b) AUB 6, (c) AUB 7, (d) Geitaoui 4, (e) Geitaoui 5, (f) Geitaoui 6.


3.2 PAHs and PCBs in PM10

As shown in Fig. 7(a), the concentrations of the measured PAHs (< 1 ng m3) fell into the range of concentrations determined between 2013 and 2019 (Jaafar et al., 2021). NaP accounted for the majority of the PAHs in all samples including the blank sample, and Phe, BbF, and BghiP were the main PAHs at the two sites each with a fraction higher than 10% (Fig. 7(b)). The measured BaP concentration was 0.17 ± 0.10 ng m3, which was comparable to that in 2015 (0.49 ± 0.26 ng m3) (Baalbaki et al., 2018) and that in 2017 (0.66 ± 0.05 ng m3) (Jaafar et al., 2021). However, the level of BaP was lower than that determined in the areas greatly affected by power plants and traffic such as Zouk Mikael (1.81 ± 1.09 ng m3) and Dora (2.30 ± 1.00 ng m3). In comparison, the concentrations of PCBs were lower than 2.5 ng per filter sample, which was 3.47 pg m3 (Fig. 7(c)). In particular, PCB 138, PCB153, PCB 180 were the main components in PM10, contributing to the 19.2%, 26.4%, and 20.2% of PCBs, respectively (Fig. 7(d)). The average concentration of the total particle-bound PCBs was 4.78 ± 1.73 pg m3, which was comparable to the typical concentrations in European cities ranging from 1 to 163 pg m3 (Arruti et al., 2012). The source apportionment of PAHs was relatively clear based on a recent study (Jaafar et al., 2021), and the excess cancer risk for every emission source could be estimated based on PAH concentrations. In contrast, PCB concentrations were relatively low, and source apportionment of PCBs was not available, which therefore was not included in the excess cancer risk calculation. It is noted that gaseous carcinogens also contribute to cancer risk, which were not measured in this study.

Fig. 7. Concentrations and fractions of (a) and (b) PAHs and (c) and (d) PCBs in PM10 samples collected at AUB and Geitaoui.Fig. 7. Concentrations and fractions of (a) and (b) PAHs and (c) and (d) PCBs in PM10 samples collected at AUB and Geitaoui.

In 2017, traffic, diesel generator, and incineration were the main emission sources of PAHs, accounting for 48%, 23%, and 29%, respectively (Jaafar et al., 2021). In particular, diesel generators were responsible for 38% of the carcinogen exposure in Hamra, Beirut (Shihadeh et al., 2018). Since the concentrations of individual PAHs measured in this study were comparable to that in 2017 (Table S14), we assumed the same contribution of the three sources. Based on the assumption, ECRs for diesel generators and traffic were calculated to assess the exposure risks in current and predicted scenarios. In 2017, diesel generators in Beirut were operated for 3 hours per day, and the ECR for diesel generators was 5.63 × 107 (25% of the ECR calculated for 2017). The diesel generators were running for longer periods as the electricity shortage was caused by the grid shut down since 2021 (BBC News, 2021). Operations of diesel generators is function of the residential areas and the availability of diesel fuel. Therefore, two scenarios of 15 and 10 hours of operations were assessed. The ECR for the diesel generators were 2.82 × 106 and 1.88 × 106 with 15 hours and 10 hours of operation per day, respectively. It suggested that the ECR for the diesel generation exceeded the acceptable risk (106) (U.S. EPA, 2011) in the hypothetical scenarios, and the ECR would be much higher when taking other emission sources such as traffic into account. Traffic contribution in 2017 was 1.31 × 106, contributing to 58% of total ECR. Therefore, the estimated ECR for the diesel generators (assuming 10 hours of operation) and traffic in 2021 would be 3.19 × 106. The ECR value was higher compared to European cities, such as Grenoble (1.64 × 106) (Tomaz et al., 2016) and Athens (0.47 × 106) (Alves et al., 2017).

 
3.3 Exposure to PM in Beirut at the Ground Level

Fig. 8(a) shows the Hamra and Gemmayze sites where PM2.5 concentrations at the ground level were measured 1–3 and 8–9 months after the explosion in the port of Beirut. During the first month after the Beirut explosion, the average concentrations measured of PM2.5 were 44 µg m3 and 65 µg m3 at Hamra and Gemmayze, respectively (Table S15). The PM2.5 mass concentration at Gemmayze with two spikes was much higher than that at Hamra from September to December 2020 (Fig. 8(b)). The concentrations decreased to 32 µg m3 and 35 µg m3 in Hamra and Gemmayze eight months after the explosion, respectively. It indicated that the PM level went down to the normal condition, as the average PM2.5 concentrations in Beirut was 30 ± 19 µg m3 before the explosion (Mrad-Nakhlé et al., 2021). The measurement of ground-level PM2.5 concentrations at Hamra in 2018 also confirmed that PM2.5 mass concentration was 27 ± 6 µg m3 (Table S16).

Fig. 8. (a) The location of Hamra and Gemmayze in Beirut, Lebanon for PM concentration measurement; (b) comparison of the PM2.5 concentrations (with spline function) 1–5 and 9–11 months after the Beirut port explosion; Fractions of PM1, PM1-2.5, PM2.5-10, and PM>10 at (c) Hamra and (d) Gemmayze.Fig. 8. (a) The location of Hamra and Gemmayze in Beirut, Lebanon for PM concentration measurement; (b) comparison of the PM2.5 concentrations (with spline function) 1–5 and 9–11 months after the Beirut port explosion; Fractions of PM1, PM1-2.5, PM2.5-10, and PM>10 at (c) Hamra and (d) Gemmayze.

Since PM10 and PM2.5 mass concentrations were relatively homogenous in Beirut before the explosion found in a previous study (Massoud et al., 2011), it was reasonable to conclude that the high level of PM2.5 at Gemmayze was induced by some point sources such as construction and traffic activities, which were affected by the Beirut port explosion. The Beirut port explosion destroyed most of the buildings in Gemmayze, Karantina, and Achrafieh (Open Map Lebanon, 2022). At Gemayze, the high level of PM2.5 concentrations was induced by ongoing construction activities (e.g., on November 25, 2020), whereas the relatively low levels at Hamra were due to low traffic density during the COVID-19 partial lockdowns where only vehicles with odd or even numbers depending on the day were allowed to drive (e.g., on May 17 and June 4, 2021) (Figs. S3 and S4). Overall, the significant difference among the three monitoring periods was attributed to local emission sources on the street, including traffic, construction activities, lockdown, and holiday period. As a result of gasoline shortage, cars were forming long queues next to gas stations all over Lebanon. This agglomeration of cars in one location caused an increase in the emissions from these cars. Spikes of PM2.5 concentrations at Hamra were measured next to the long car queues next to gas stations and can be therefore attributed to the concentration of cars.

PM2.5 concentrations measured in average at Gemmayze exceeded by 5 folds the WHO recommendations (15 µg m3 for 24-hour mean) (WHO, 2021) between September 9 and December 4, 2020, while a 50% drop was observed 8 months after the explosion. Average PM2.5 concentrations in Hamra exceeded by 3 folds the WHO recommendations between September 9 and December 4, 2020. Traffic and local diesel generators were two key emission sources of PM in Beirut (Baayoun et al., 2019). Despite the reduced traffic activities due to lockdown scenarios in 2021, the PM2.5 concentrations were still as high as 30 µg m3 due to the emissions from diesel generators.

The average fraction of PM1, PM1-2.5, and PM2.5-10 at Hamra were 73.49%, 2.88%, and 14.03%, respectively (Fig. 8(c)), indicating a low fraction of dust particles. In contrast, the average fraction of PM1, PM1-2.5, and PM2.5-10 at Gemmazye were 59.13%, 3.82%, and 30.02%, respectively (Fig. 8(d)), which suggested a dominant role of PM1 and PM2.5-10 (Daher et al., 2013). The PM2.5/PM10 ratio at Gemmazye was 0.70, which was comparable to that in 2003 (0.57) (Saliba et al., 2010). A previous study suggested that the cancer risk for PM10 was higher than PM2.5 and PM1 by 181.8% and 363.6% in terms of trace metals and PAHs (Reche et al., 2012). It is important to implement strict plans for particle reduction during the destruction and construction activities after the explosion.

 
3.4 Possible Effects of Beirut Port Explosion on Air Quality

According to the IC, ICP-MS, GCMS, and SEM results, no abnormal concentration of inorganic and organic components, and the presence of asbestos were observed, indicating insignificant long-term effects of the explosion in terms of chemical composition. Overall, the chemical composition in the post-explosion PM10 was not changed by chemicals released from the explosion due to the possible rapid transport and deposition. Nonetheless, the chemicals could eventually go into soil and water causing further environmental issues. In addition, resuspension such as on traffic roads (Harrison et al., 2012) also played a role in releasing aged particles. For instance, deposited metals during the 20th century was a persistent source of the metal concentration in London (Resongles et al., 2021). It is worthy to investigate the pollutant remobilization from the soil in Beirut to identify possible long-term exposure pathways.

Based on the PM mass measurements at the ground level, demolition and reconstruction along with other emission sources could increase the PM2.5 level to 8 folds of the WHO air quality standards (15 µg m3 for 24-hour mean), which might exist for a long term. The buildings affected by the explosion are still under repair and reconstruction (Open Map Lebanon, 2022). So far, as shown in the Open Map Lebanon (2022), there are 1% completed repairs and 30.5% ongoing repairs in Beirut. Hence, the exposure to a high level of PM10 and PM2.5 could continue. The continuous high level of PM in the post-explosion period will worsen the air quality, which is higher than the WHO air quality standards for the concentrations of PM10 (45 µg m3 for 24-hour mean) and PM2.5 (15 µg m3 for 24-hour mean).

 
4 CONCLUSIONS


In this work, the chemical composition and concentration of airborne PM 1–3 months after the Beirut port explosion were evaluated. So far, no persistent effect of released chemicals from the explosion was found as no significant difference of inorganic (especially nitrate and ammonium) and organic concentrations were found between PM10 collected 1 month and 3 months after the explosion, likely due to rapid transport and deposition of explosion pollutants. Nonetheless, high levels of PM2.5 concentrations up to 122 µg m3 released from demolition and construction after the explosion, along with diesel generators and traffic, were found based on PM particle size and mass measurements. In addition, the cancer risk was estimated based on PAH measurements, which was higher than the acceptable level by 3.19 times for the diesel generators (assuming 10 hours of operation) and traffic in 2021. Several recommendations regarding future research and policymaking were given based on the available results and analysis. Investigations of soil and water contaminations and size-resolved airborne PM fractions are needed to obtain a comprehensive evaluation of the effects of the explosion. A long-term study (e.g., year-round) is necessary to monitor possible particle resuspension, which could result in long-term air pollution events in Beirut. Demolition and construction activities should be accompanied by a dust reduction plan, and emission reduction plans for diesel generators and vehicles should also be implemented to protect workers and residents of affected areas.

 
ACKNOWLEDGMENTS


Y.-B. Zhao and F. Jiang thank China Scholarship Council (CSC) for the financial support. N.A. Saliba thanks the WHO for providing funding. N. Hayeck and N.A. Saliba thank Ethos Environmental Ltd. for performing the asbestos analysis.


REFERENCES


  1. Abdallah, C., Afif, C., Sauvage, S., Borbon, A., Salameh, T., Kfoury, A., Leonardis, T., Karam, C., Formenti, P., Doussin, J.F., Locoge, N., Sartelet, K. (2020). Determination of gaseous and particulate emission factors from road transport in a middle eastern capital. Transp. Res. Part D Transp. Environ. 83, 102361. https://doi.org/10.1016/j.trd.2020.102361

  2. Ahmad, A., McCulloch, N., Al-Masri, M., Ayoub, M. (2022). From dysfunctional to functional corruption: The politics of decentralized electricity provision in lebanon. Energy Res. Social Sci. 86, 102399. https://doi.org/10.1016/j.erss.2021.102399

  3. Al Noaimi, G., Yunis, K., El Asmar, K., Abu Salem, F.K., Afif, C., Ghandour, L.A., Hamandi, A., Dhaini, H.R. (2021). Prenatal exposure to criteria air pollutants and associations with congenital anomalies: A lebanese national study. Environ. Pollut. 281, 117022. https://doi.org/10.1016/j.​envpol.2021.117022

  4. Al-Hajj, S., Dhaini, H.R., Mondello, S., Kaafarani, H., Kobeissy, F., DePalma, R.G. (2021). Beirut ammonium nitrate blast: Analysis, review, and recommendations. Front. Public Health 9, 661. https://doi.org/10.3389/fpubh.2021.657996

  5. Ali, T., Abouleish, M., Gawai, R., Hamdan, N., Elaksher, A. (2022). Ammonium nitrate explosion at the main port in Beirut (Lebanon) and air pollution: An analysis of the spatiotemporal distribution of nitrogen dioxide. Euro-Mediterr. J. Environ. Integr. 7, 21–27. https://doi.org/​10.1007/s41207-022-00296-5

  6. Alves, C.A., Vicente, A.M., Custódio, D., Cerqueira, M., Nunes, T., Pio, C., Lucarelli, F., Calzolai, G., Nava, S., Diapouli, E., Eleftheriadis, K., Querol, X., Musa Bandowe, B.A. (2017). Polycyclic aromatic hydrocarbons and their derivatives (nitro-PAHs, oxygenated PAHs, and azaarenes) in PM2.5 from Southern European cities. Sci. Total Environ. 595, 494–504. https://doi.org/​10.1016/j.scitotenv.2017.03.256

  7. Arruti, A., Fernández-Olmo, I., Irabien, Á. (2012). Evaluation of the urban/rural particle-bound PAH and PCB levels in the northern Spain (Cantabria region). Environ. Monit. Assess. 184, 6513–6526. https://doi.org/10.1007/s10661-011-2437-4

  8. Baalbaki, R., Nassar, J., Salloum, S., Shihadeh, A.L., Lakkis, I., Saliba, N.A. (2018). Comparison of atmospheric polycyclic aromatic hydrocarbon levels in three urban areas in Lebanon. Atmos. Environ. 179, 260–267. https://doi.org/10.1016/j.atmosenv.2018.02.028

  9. Baayoun, A., Itani, W., El Helou, J., Halabi, L., Medlej, S., El Malki, M., Moukhadder, A., Aboujaoude, L.K., Kabakian, V., Mounajed, H., Mokalled, T., Shihadeh, A., Lakkis, I., Saliba, N.A. (2019). Emission inventory of key sources of air pollution in Lebanon. Atmos. Environ. 215, 116871. https://doi.org/10.1016/j.atmosenv.2019.116871

  10. BBC News (2021). Lebanon Left without Power as Grid Shuts Down (accessed January 2022).

  11. Beirut Urban Lab and Lebanon's National Council for Scientific Research (2021). The Beirut Built Environment Database (accessed 6 January 2022).

  12. Borgie, M., Ledoux, F., Dagher, Z., Verdin, A., Cazier, F., Courcot, L., Shirali, P., Greige-Gerges, H., Courcot, D. (2016). Chemical characteristics of PM2.5–0.3 and PM0.3 and consequence of a dust storm episode at an urban site in Lebanon. Atmos. Res. 180, 274–286. https://doi.org/​10.1016/j.atmosres.2016.06.001

  13. Broomandi, P., Jahanbakhshi, A., Nikfal, A., Kim, J.R., Karaca, F. (2021). Impact assessment of Beirut explosion on local and regional air quality. Air Qual. Atmos. Health 14, 1911–1929. https://doi.org/10.1007/s11869-021-01066-y

  14. Brown, A., Barrett, J.E.S., Robinson, H., Potgieter-Vermaak, S. (2015). Risk assessment of exposure to particulate output of a demolition site. Environ. Geochem. Health 37, 675–687. https://doi.org/10.1007/s10653-015-9747-3

  15. Daher, N., Saliba, N.A., Shihadeh, A.L., Jaafar, M., Baalbaki, R., Sioutas, C. (2013). Chemical composition of size-resolved particulate matter at near-freeway and urban background sites in the greater Beirut area. Atmos. Environ. 80, 96–106. https://doi.org/10.1016/j.atmosenv.​2013.08.004

  16. Dhaini, H.R., Salameh, T., Waked, A., Sauvage, S., Borbon, A., Formenti, P., Doussin, J.F., Locoge, N., Afif, C. (2017). Quantitative cancer risk assessment and local mortality burden for ambient air pollution in an eastern Mediterranean City. Environ. Sci. Pollut. Res. Int. 24, 14151–14162. https://doi.org/10.1007/s11356-017-9000-y

  17. Fakhri, N., Fadel, M., Öztürk, F., Keleş, M., Iakovides, M., Pikridas, M., Abdallah, C., Karam, C., Sciare, J., Hayes, P.L., Afif, C. (2022). Comprehensive chemical characterization of PM2.5 in the large East Mediterranean-Middle East city of Beirut, Lebanon. J. Environ. Sci. 133, 118–137. https://doi.org/10.1016/j.jes.2022.07.010

  18. Hajir, S., Al Aaraj, L., Zgheib, N., Badr, K., Ismaeel, H., Abchee, A., Tamim, H., Saliba, N.A. (2021). The association of urinary metabolites of polycyclic aromatic hydrocarbons with obstructive coronary artery disease: A red alert for action. Environ. Pollut. 272, 115967. https://doi.org/​10.1016/j.envpol.2020.115967

  19. Harrison, R.M., Jones, A.M., Gietl, J., Yin, J., Green, D.C. (2012). Estimation of the contributions of brake dust, tire wear, and resuspension to nonexhaust traffic particles derived from atmospheric measurements. Environ. Sci. Technol. 46, 6523–6529. https://doi.org/10.1021/es300894r

  20. Hieu, N.T., Lee, B.K. (2010). Characteristics of particulate matter and metals in the ambient air from a residential area in the largest industrial city in Korea. Atmos. Res. 98, 526–537. https://doi.org/10.1016/j.atmosres.2010.08.019

  21. Jaafar, M., Baalbaki, R., Mrad, R., Daher, N., Shihadeh, A., Sioutas, C., Saliba, N.A. (2014). Dust episodes in beirut and their effect on the chemical composition of coarse and fine particulate matter. Sci. Total Environ. 496, 75–83. https://doi.org/10.1016/j.scitotenv.2014.07.018

  22. Jaafar, W., Zaherddine, V., Hussein, F., Saliba, N.A., Hayeck, N. (2021). Poor regulation implications in a low and middle income country based on pah source apportionment and cancer risk assessment. Environ. Sci. Process. Impact. 23, 1986–1996. https://doi.org/10.1039/D1EM00285F

  23. Jenke, D.R. (1983). Comparison of three methods for the extraction of selected anions from media used for the collection of airborne particulates. J. Air Waste Manage. Assoc. 33, 765–767. https://doi.org/10.1080/00022470.1983.10465639

  24. Kuroda, A. (2021). Recent progress and perspectives on the mechanisms underlying asbestos toxicity. Genes Environ. 43, 46. https://doi.org/10.1186/s41021-021-00215-0

  25. Liu, L., Liang, S., Liu, H., Zhu, G., Tan, W. (2019). Nitrate contamination in a coastal soil and water system: A case study after the Tianjin Port 8·12 explosion, China. Hum. Ecol. Risk Assess.: Int. J. 25, 2017–2031. https://doi.org/10.1080/10807039.2018.1480352

  26. Lovett, C., Sowlat, M.H., Saliba, N.A., Shihadeh, A.L., Sioutas, C. (2018). Oxidative potential of ambient particulate matter in Beirut during Saharan and Arabian dust events. Atmos. Environ. 188, 345–42. https://doi.org/10.1016/j.atmosenv.2018.06.016

  27. Mansour, C., Haddad, M., Zgheib, E. (2018). Assessing consumption, emissions and costs of electrified vehicles under real driving conditions in a developing country with an inadequate road transport system. Transp. Res. Part D Transp. Environ. 63, 4985–513. https://doi.org/​10.1016/j.trd.2018.06.012

  28. Massoud, R., Shihadeh, A.L., Roumié, M., Youness, M., Gerard, J., Saliba, N., Zaarour, R., Abboud, M., Farah, W., Saliba, N.A. (2011). I Intraurban variability of PM10 and PM2.5 in an Eastern Mediterranean city. Atmos. Res. 101, 8935–901. https://doi.org/10.1016/j.atmosres.2011.05.​019

  29. Mrad-Nakhlé, M., Farah, W., Ziade, N., Abboud, M., Chalhoub, E., Ghabi, E., Dib, N., Annesi-Maesano, I. (2021). Exposure to fine particulate matter and urticaria: An eco-epidemiological time-series analysis in Beirut. Toxicol. Environ. Health Sci. 13, 1755–182. https://doi.org/​10.1007/s13530-021-00078-6

  30. Nakhlé, M.M., Farah, W., Ziadé, N., Abboud, M., Salameh, D., Annesi-Maesano, I. (2015). Short-term relationships between emergency hospital admissions for respiratory and cardiovascular diseases and fine particulate air pollution in Beirut, Lebanon. Environ. Monit. Assess. 187, 196. https://doi.org/10.1007/s10661-015-4409-6

  31. Nasser, Z., Salameh, P., Dakik, H., Elias, E., Abou Abbas, L., Levêque, A. (2015). Outdoor air pollution and cardiovascular diseases in Lebanon: A case-control study. J. Environ. Public Health 2015, 810846. https://doi.org/10.1155/2015/810846

  32. Open Map Lebanon (2022). Beirut Recovery Map (accessed 3 January 2022).

  33. Pasman, H.J., Fouchier, C., Park, S., Quddus, N., Laboureur, D. (2020). Beirut ammonium nitrate explosion: Are not we really learning anything? Process Saf. Prog. 39, e12203. https://doi.org/​10.1002/prs.12203

  34. Pilger, C., Gaebler, P., Hupe, P., Kalia, A.C., Schneider, F.M., Steinberg, A., Sudhaus, H., Ceranna, L. (2021). Yield estimation of the 2020 Beirut explosion using open access waveform and remote sensing data. Sci. Rep. 11, 14144. https://doi.org/10.1038/s41598-021-93690-y

  35. Pittman, W., Han, Z., Harding, B., Rosas, C., Jiang, J., Pineda, A., Mannan, M.S. (2014). Lessons to be learned from an analysis of ammonium nitrate disasters in the last 100 years. J. Hazard. Mater. 280, 472–477. https://doi.org/10.1016/j.jhazmat.2014.08.037

  36. PurpleAir (2021). (accessed February 2021).

  37. Reche, C., Moreno, T., Amato, F., Viana, M., van Drooge, B.L., Chuang, H.C., Bérubé, K., Jones, T., Alastuey, A., Querol, X. (2012). A multidisciplinary approach to characterise exposure risk and toxicological effects of PM10 and PM2.5 samples in urban environments. Ecotoxicol. Environ. Safety 78, 327–335. https://doi.org/10.1016/j.ecoenv.2011.11.043

  38. Resongles, E., Dietze, V., Green, D.C., Harrison, R.M., Ochoa-Gonzalez, R., Tremper, A.H., Weiss, D.J. (2021). Strong evidence for the continued contribution of lead deposited during the 20th century to the atmospheric environment in London of today. Proc. Nat. Acad. Sci. 118, e2102791118. https://doi.org/10.1073/pnas.2102791118

  39. Saliba, N.A., Atallah, M., Al-Kadamany, G. (2009). Levels and indoor–outdoor relationships of PM10 and soluble inorganic ions in Beirut, Lebanon. Atmos. Res. 92, 131–137. https://doi.org/​10.1016/j.atmosres.2008.09.010

  40. Saliba, N.A., El Jam, F., El Tayar, G., Obeid, W., Roumie, M. (2010). Origin and variability of particulate matter (PM10 and PM2.5) mass concentrations over an Eastern Mediterranean city Atmos. Res. 97, 106–114. https://doi.org/10.1016/j.atmosres.2010.03.011

  41. Saliba, N.A., Chamseddine, A. (2012). Uptake of acid pollutants by mineral dust and their effect on aerosol solubility. Atmos. Environ. 46, 256–263. https://doi.org/10.1016/j.atmosenv.2011.​09.074

  42. Sari, M.F., Esen, F., Tasdemir, Y. (2021). Characterization, source apportionment, air/plant partitioning and cancer risk assessment of atmospheric pahs measured with tree components and passive air sampler. Environ. Res. 194, 110508. https://doi.org/10.1016/j.envres.2020.​110508

  43. Shaka’, H., Saliba, N.A. (2004). Concentration measurements and chemical composition of PM10-2.5 and PM2.5 at a coastal site in Beirut, Lebanon. Atmos. Environ. 38, 523–531. https://doi.org/​10.1016/j.atmosenv.2003.10.009

  44. Shihadeh, A., Al Helou, M., Saliba, N., Jaber, S., Alaeddine, N., Ibrahim, E. (2018). Effect of Distributed Electric Power Generation on Household Exposure to Airborne Carcinogens in Beirut. Climate Change and Environment in the Arab World, Issam Fares Institute for Public Policy and International Affairs, American University of Beirut, Beirut.

  45. Sun, Y., Zhuang, G., Tang, A., Wang, Y., An, Z. (2006). Chemical characteristics of PM2.5 and PM10 in haze−fog episodes in Beijing. Environ. Sci. Technol. 40, 3148–3155. https://doi.org/10.1021/​es051533g

  46. Tomaz, S., Shahpoury, P., Jaffrezo, J.L., Lammel, G., Perraudin, E., Villenave, E., Albinet, A. (2016). One-year study of polycyclic aromatic compounds at an urban site in Grenoble (France): Seasonal variations, gas/particle partitioning and cancer risk estimation. Sci. Total Envir. 565, 1071–1083. https://doi.org/10.1016/j.scitotenv.2016.05.137

  47. U.S. Environmental Protection Agency (U.S. EPA) (2011). Exposure Factors Handbook 2011 Edition (Final Report) (accessed November 2022).

  48. ur Rehman, S., Ahmed, R., Ma, K., Xu, S., Aslam, M.A., Bi, H., Liu, J., Wang, J. (2021). Ammonium nitrate is a risk for environment: A case study of Beirut (Lebanon) chemical explosion and the effects on environment. Ecotoxicol. Environ. Saf. 210, 111834. https://doi.org/10.1016/j.​ecoenv.2020.111834

  49. Waked, A., Afif, C. (2012). Emissions of air pollutants from road transport in Lebanon and other countries in the Middle East region. Atmos. Environ. 61, 446–452. https://doi.org/10.1016/j.​atmosenv.2012.07.064

  50. Waked, A., Seigneur, C., Couvidat, F., Kim, Y., Sartelet, K., Afif, C., Borbon, A., Formenti, P., Sauvage, S. (2013). Modeling air pollution in Lebanon: Evaluation at a suburban site in Beirut during summer. Atmos. Chem. Phys. 13, 5873–5886. https://doi.org/10.5194/acp-13-5873-2013

  51. World Health Organization (WHO) (2021). Ambient (Outdoor) Air Pollution (accessed January 2022).

  52. Yang, M., Chen, X., Wang, Y., Yuan, B., Niu, Y., Zhang, Y., Liao, R., Zhang, Z. (2017). Comparative evaluation of thermal decomposition behavior and thermal stability of powdered ammonium nitrate under different atmosphere conditions. J. Hazard. Mater. 337, 10–19. https://doi.org/​10.1016/j.jhazmat.2017.04.063

  53. Yu, G., Wang, Y., Zheng, L., Huang, J., Li, J., Gong, L., Chen, R., Li, W., Huang, J., Duh, Y.S. (2021). Comprehensive study on the catastrophic explosion of ammonium nitrate stored in the warehouse of Beirut port. Process Saf. Environ. Prot. 152, 201–219. https://doi.org/10.1016/​j.psep.2021.05.030

  54. Yu, Z., Wang, H., Zhang, X., Gong, S., Liu, Z., Zhao, N., Zhang, C., Xie, X., Wang, K., Liu, Z., Wang, J.S., Zhao, X., Zhou, J. (2022). Long-term environmental surveillance of PM2.5-bound polycyclic aromatic hydrocarbons in Jinan, China (2014–2020): Health risk assessment. J. Hazard. Mater. 425, 127766. https://doi.org/10.1016/j.jhazmat.2021.127766

  55. Zholobenko, V., Rutten, F., Zholobenko, A., Holmes, A. (2021). In situ spectroscopic identification of the six types of asbestos. J. Hazard. Mater. 403, 123951. https://doi.org/10.1016/j.jhazmat.​2020.123951


Share this article with your colleagues 

 

Subscribe to our Newsletter 

Aerosol and Air Quality Research has published over 2,000 peer-reviewed articles. Enter your email address to receive latest updates and research articles to your inbox every second week.

7.3
2022CiteScore
 
 
77st percentile
Powered by
Scopus
 
   SCImago Journal & Country Rank

2022 Impact Factor: 4.0
5-Year Impact Factor: 3.4

Call for Papers for the special issue on: "Carbonaceous Aerosols in the Atmosphere"

Aerosol and Air Quality Research partners with Publons

CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit
CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit

Aerosol and Air Quality Research (AAQR) is an independently-run non-profit journal that promotes submissions of high-quality research and strives to be one of the leading aerosol and air quality open-access journals in the world. We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.