# Particulate matter and carbonaceous content in aerosols from Haiphong and Hanoi cities, Northern Vietnam

Catherine Guigue, Pauline Martinot, Sandrine Chifflet, Léa Guyomarc'h, Pamela Dominutti, Jean-Luc Jaffrezo, Thanh Ngo-Duc, van Hoi Bui, Cam Tu Vu, Gaëlle Uzu, et al.

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Catherine Guigue, Pauline Martinot, Sandrine Chifflet, Léa Guyomarc'h, Pamela Dominutti, et al. Particulate matter and carbonaceous content in aerosols from Haiphong and Hanoi cities, Northern Vietnam. Atmospheric Pollution Research, 2025, 260 (6), pp.102638. 10.1016/j.apr.2025.102638. hal-05137719

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Particulate matter and carbonaceous content in aerosols from Haiphong and Hanoi cities, Northern Vietnam

Catherine Guigue, Pauline L. Martinot, Sandrine Chifflet, Léa Guyomarc'h, Pamela A. Dominutti, Jean-Luc Jaffrezo, Thanh Ngo-Duc, Van Hoi Bui, Cam Tu Vu, Gaëlle Uzu, Marc Tedetti, Xavier Mari

PII: S1309-1042(25)00240-5

DOI: https://doi.org/10.1016/j.apr.2025.102638

Reference: APR 102638

To appear in: *Atmospheric Pollution Research*

Received Date: 16 December 2024

Revised Date: 16 May 2025

Accepted Date: 24 June 2025

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Please cite this article as: Guigue, C., Martinot, P.L., Chifflet, S., Guyomarc'h, L., Dominutti, P.A., Jaffrezo, J.-L., Ngo-Duc, T., Bui, V.H., Vu, C.T., Uzu, G., Tedetti, M., Mari, X., Particulate matter and carbonaceous content in aerosols from Haiphong and Hanoi cities, *Northern Vietnam, Atmospheric Pollution Research*, https://doi.org/10.1016/j.apr.2025.102638.

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© 2025 Published by Elsevier B.V. on behalf of Turkish National Committee for Air Pollution Research and Control.
1 Particulate matter and carbonaceous content in aerosols from Haiphong and Hanoi

2 cities, Northern Vietnam

3

4 Catherine Guigue<sup>a, b*</sup>, Pauline L. Martinot<sup>a, b</sup>, Sandrine Chifflet<sup>a</sup>, Léa Guyomarc'h<sup>a, b</sup>, Pamela

5 A. Dominutti<sup>c</sup>, Jean-Luc Jaffrezo<sup>c</sup>, Thanh Ngo-Duc<sup>d</sup>, Van Hoi Bui<sup>b</sup>, Cam Tu Vu<sup>b</sup>, Gaëlle

6 Uzu<sup>c</sup>, Marc Tedetti<sup>a, b</sup>, Xavier Mari<sup>a, b</sup>

7

8 <sup>a</sup> Aix-Marseille Univ, Université de Toulon, CNRS, IRD, MIO UM 110, 13288, Marseille,

9 France

10 <sup>b</sup> Water - Environment - Oceanography (WEO) Department, University of Science and

11 Technology of Hanoi (USTH), Vietnam Academy of Science and Technology (VAST),

12 Hanoi, Vietnam

13 <sup>c</sup> Univ. Grenoble Alpes, CNRS, IRD, G-INP, IGE (UMR 5001), 38000 Grenoble, France

14 <sup>d</sup> Space and Applications (SA) Department, University of Science and Technology of Hanoi

15 (USTH), Vietnam Academy of Science and Technology (VAST), Hanoi, Vietnam

16

17 16 May 2025

18 Revised version submitted to Atmospheric Pollution Research

19

20

21

22

23

24

25
26 **Abstract**

27 Airborne particulate matter (PM) and its carbonaceous content (elemental carbon, EC and
28 organic carbon, OC, including polycyclic aromatic hydrocarbons, PAHs) were investigated in
29 Haiphong and Hanoi, two major cities in the Northern Vietnam, aiming at elucidating the
30 relative importance of local and regional atmospheric pollution. The monthly average ranges
31 of PM2.5 were 14-37 µg m-3 in Haiphong, and 35-102 µg m-3 in Hanoi, respectively, during the
32 period 2020-2023. EC, OC and PAH concentrations annually averaged 2.1 ± 1.3 µg m-3, 4.9 ±
33 3.1 µg m-3 and 4.4 ± 2.6 ng m-3 in Haiphong PM10 from Oct. 2012 to Oct. 2013, and 1.3 ± 0.9
34 µg m-3, 9.1 ± 6.2 µg m-3 and 5.9 ± 5.8 ng m-3 in Hanoi PM2.5 from Oct. 2019 to Dec. 2020,
35 respectively. Seasonal variations were observed, with higher values during the dry season
36 (winter) compared to the wet season (summer), as expected according to monsoon
37 meteorological conditions. However, spatial variations and correlations between EC, OC, and
38 PAHs, along with other markers of human activities (such as levoglucosan, secondary
39 inorganic aerosols and metals), emphasized city-specific influence of local emission sources
40 versus those transported from distant locations. Hanoi, highly urbanized, appeared to be
41 yearly dominated by the local emissions while Haiphong, less urbanized and located near the
42 sea, allowed to highlight seasonal variations in emission origin. While PM values exceeded up
43 to 15 times international air quality recommendations, health risk assessment related to
44 inhaled PAHs, in line with previous results relying on metals, remained low to moderate.
45
46 **Key words:** Vietnam, air pollution, airborne particulate matter, carbonaceous content,
47 polycyclic aromatic hydrocarbons.
48
49
50
## 1. Introduction

Vietnam, like its neighboring countries in Southeast Asia, has been facing a growing deterioration of air quality since the early 1990s, caused by rapid economic growth, and strong urbanization and industrialization (Chan and Yao, 2008; Hien et al., 2022; Choomanee et al., 2024). This is particularly pronounced in major cities like Hanoi and Haiphong, the two most densely populated and economically important cities in Northern Vietnam. Hanoi is the capital of the country and Haiphong the largest seaport in Northern Vietnam. These two cities are located in the same highly industrialized area (Nguyen and Diez, 2017; Dang et al., 2020) but differ by their degree of urbanization and geography. For years, Hanoi and Haiphong have experienced highly degraded air quality. Furthermore, the capital frequently ranks among the top ten most air-polluted cities in the world, posing significant risks to citizens' health (Hicks, 2019; Van Khuc et al., 2020; World Air Quality report 2022). As a result, 60,000 premature deaths annually in Vietnam are likely linked to air pollution (Loan, 2018). As a response to poor air quality, additional legislation and national air quality standard (NAQS, QCVN 05:2013/BTNMT) have been implemented by the Vietnam Ministry of Natural Resources and Environment (MONRE, 2019, 2021). However, they are much less restrictive than the international air quality recommendations (AQS, WHO, 2021).

In Northern Vietnam, air pollution originates from both local and regional (i.e., transboundary) emissions but it is also closely linked to seasonal Asian monsoon climatic conditions and geography (coastal or inland location) (Hopke et al., 2008; Ly et al., 2021; Ogino et al., 2022). While most authors suggest that a mix of local and regional sources contributes to air pollution in Northern Vietnam, the relative importance between the two is still under debate (Hien et al., 2020; Nguyen et al., 2022; Vuong et al., 2023). Thus, comparing air quality in Hanoi and Haiphong, two near but contrasting cities, can help
76 decipher the pollution dynamics (emission sources, vectors, aging) and provide crucial
77 information for developing effective strategies to tackle the air quality crisis in the country.

78 PM mass concentration and their chemical composition, such as the carbonaceous
79 content, secondary inorganic aerosols, metals and metalloids, are considered as pollution
80 indicators (Jimenez et al., 2009; Pope et al., 2011; Fuzzi et al., 2015; Xing et al., 2016). The
81 total carbonaceous content, split into elemental and organic carbon (EC and OC,
82 respectively), can represent up to 10-70% of the PM mass in the urban atmosphere (Fuzzi et
83 al., 2006; Rengarajan et al., 2007; Srinivas and Sarin, 2014; Liu et al., 2018; Chen et al.,
84 2019). EC is mainly emitted as primary aerosol from incomplete combustion processes while
85 OC may be emitted into the atmosphere directly from natural and anthropogenic sources
86 (primary organic carbon, POC) either from combustion or non-combustion processes, but also
87 produced from gas to particle conversion (secondary organic carbon, SOC) during aging in
88 the atmosphere (Masiello, 2004; Finlayson-Pitts et al., 2020; Velis and Cook, 2021). The
89 amounts of EC and OC in PM are key parameters for the evaluation of aerosol impacts on
90 radiative forcing at the regional scale (Novakov et al., 2005) and are also associated with
91 increased mortality due to cardio-vascular and respiratory diseases (Chuang et al., 2007; Ostro
92 et al., 2007; Peng et al., 2009; Zhou et al., 2011). Particularly, EC and OC may contain
93 hundreds of organic species, potentially mutagenic and carcinogenic like polycyclic aromatic
94 hydrocarbons (PAHs) (Turpin and Lim, 2001; Brauner et al., 2016; Chen et al., 2016) and
95 derivatives (Albinet et al., 2007; Mardoñez et al., 2023). Indeed, PAHs belong to the most
96 widespread organic contaminants found in the environment. Although PAHs from natural
97 sources (i.e., volcanoes, forest fires) are not negligible (European Community, Position Paper,
98 2001), it is considered that high molecular weight particle-bound PAHs almost exclusively
99 come from the incomplete combustion processes related to anthropogenic activities (Baek et
100 al., 1991). To identify the sources of combustion (mainly fossil fuel versus biomass), many
studies have used the PAH molecular profiles. However, given the high ubiquity of PAHs emitted into the atmosphere, it is necessary to rely on supplementary markers to further assess the sources of pollution/combustion (Srivastava et al., 2018). For instance, levoglucosan can be used as tracer for biomass burning, with potassium ($K^+$) and chloride ($Cl^-$) ions as potential additional indicators (Simoneit et al., 1999, 2004; Simoneit, 2002; Yan et al., 2018). Also, large fractions of secondary inorganic aerosol, mainly composed of ammonium nitrate and ammonium sulfate and identified/quantified by the presence of their corresponding water-soluble ions ($NH_4^+$, $NO_3^-$, $SO_4^{2-}$), as well as metals and metalloids, have already been observed in PM, especially during haze episodes and associated to various anthropogenic activities (Kang et al., 2004; Wang et al., 2006).

Previous studies have already presented results dealing with PM and associated chemical content from Haiphong or Hanoi city ambient air. These works have investigated concentration levels and sources along with meteorological conditions and seasonal variations to help assessing: i) whether local or regional inputs preferentially affect air quality and ii) the health risks based either on metals and metalloids or oxidative potential of PM (Hai and Kim Oanh, 2013; Mari et al., 2017; Chifflet al., 2018, 2024; Hien et al., 2020; Makkonen et al., 2023; Dominutti et al., 2024). Nevertheless, some assessments can be questionable, for example in the Hanoi atmosphere, Dominutti et al. (2024) present secondary inorganic ions as long-range transport (LRT) tracers, while Hien et al. (2020) described them from a local origin. In addition, PAH or metal distribution does not allow for unequivocal identification of their source or origin. Besides, the health risks can greatly differ with regard to the assessment methods (Chifflet al., 2018, 2024; Dominutti et al., 2024).

The studies conducted to date on the local or regional origin of pollution in Northern Vietnam are mainly based on samples collected within Hanoi. Their conclusions may thus be biased by the specific behavior of the city. To further understand the origin of pollution and
126 distinguish between the contribution of local and regional emissions, it seems necessary to
127 compare the concentrations and chemical composition of aerosols collected in Hanoi with
128 those from distant sites subjected to other types of forcing. Furthermore, there is currently no
129 information on the carbon content of aerosols in Haiphong, the second largest city in Northern
130 Vietnam.

131 Therefore, to better understand air quality in Northern Vietnam, we propose here a
132 comparative study of PM mass concentrations and carbonaceous contents between Hanoi and
133 Haiphong. The objectives of this work are i) to compare the annual and seasonal variations in
134 PM, carbonaceous content and PAH-related health risks between Haiphong and Hanoi,
135 considering the climatic conditions prevailing in the Northern Vietnam and the geographical
differences between the two cities, ii) to evaluate the correlations between the PM
136 carbonaceous contents (i.e., EC and OC, including PAHs and levoglucosan) and some
137 secondary inorganic aerosol components and metals, to better understand the main emission
138 sources contributing to PM, and iii) relying on the results from these contrasting sites to better
139 estimate the relative importance of local and regional carbonaceous aerosols on air pollution
140 in the Northern Vietnam.

142

143

## 2. Material and Methods

145

### 2.1. Sampling sites

147 2.1.1. Industrial, agricultural and urban characteristics

148 Hanoi and Haiphong are located in the Red River Delta (Gulf of Tonkin, Northern
149 Vietnam; Fig. 1). Hanoi is the second most populated city in Vietnam, located upstream of the
150 Red River, covering an area of 3359 km² with a population of more than 8 M inhabitants.
Hanoi's urban expansion has been rapid since the 1990s, spreading outward from the urban center through the urban fringe and peri-urban areas to constitute now the “Hanoi Metropolitan Region” with 7 inner and 5 suburban districts. New urban areas, industrial zones and traffic corridors have been constructed on formerly agricultural land. Hanoi hosts number of governmental offices, companies, research institutes, and educational facilities located in the city center, leading to frequent traffic congestion (Hien et al., 2020). Indeed, vehicle traffic increases sharply together with the expansion of urban and industrial activities (Makkonen et al., 2023). In 2019, more than 6.6 M vehicles were registered in Hanoi (0.7 M cars and 5.8 M motorcycles, this latter being the dominant road-traffic pollution source) (GSO, 2020; Ngo et al., 2023). Additionally, the Noi Bai International Airport, with a total capacity of 20 M passengers per year is located 20-25 km from the capital center.

Haiphong is located ~ 100 km Southeast of Hanoi, on the southern bank of the Red River mouth (Fig. 1). With about 2 M inhabitants, Haiphong is the third largest city of Vietnam and the main seaport in Northern Vietnam. It plays a critical economic role in the region due to its strategic location along the East Sea, serving as a major marine distribution center with numerous large-scale manufacturing facilities, industrial complexes, and international free-trade zones.

These two cities are surrounded by many suburban industrial activities (e.g., Thang Long industrial Park in the North, Saidong industrial zone in the East, Ngoc Hoi industrial zone in the South) and several highly industrialized provinces (Thai Nguyen, Quang Ninh, Bac Ninh, and Hung Yen) (Hien et al., 2020). Within 100-200 km, there are located around ten coal-fired power plants (https://globalenergymonitor.org/projects/global-coal-plant-tracker/tracker/), around forty cement plants (Vietnam being the world's largest exporter of cement and the third-largest cement producer with >70% located in the North), and seven steel plants (https://globalenergymonitor.org/projects/global-steel-plant-tracker/tracker-map/).
Vietnam is also the fifth largest rice producer in the world and the first in Southeast Asia, the Red River Delta being the second largest cultivation area in the country, with two main cultivation seasons each year. At the end of harvest periods, rice straw open burning, which is a very popular but uncontrolled practice in Vietnam, is responsible for large emissions of PM and PAHs (Yang et al., 2006; Pham et al., 2019). Moreover, Northern Vietnam is subjected to already polluted air masses, highly impacted by fossil fuel and biomass burning from transboundary origin (Kim Oanh et al., 2018; Du et al., 2020).

### 2.1.2. Southeast Asian monsoon climate

Northern Vietnam is subjected to the Southeast Asia monsoon climate, driven by two prevailing seasons, the Northeast monsoon in the dry season (also called winter or cold season) and the Southeast monsoon in the wet season (also called summer or warm season) (Nguyen and Hieu, 2004). During the dry season (roughly from Nov. to Apr.), atmospheric conditions are affected by Northerly to Northeastern air masses from Siberia and East China Sea. Air from Siberia brings stable atmospheric conditions with low temperatures, while humidity depends on whether air masses have passed through continental or marine areas. In Nov. and Dec., the air, coming from inland China (Northerly) is dry. From Jan. to Apr., air masses shift to East (Northeastern) and travel over the Western Pacific Ocean, picking up moisture, before reaching Northern Vietnam via the Gulf of Tonkin and resulting in smog (haze), low stratus cloudiness, and drizzle. During the dry season, the atmospheric conditions favor a higher potential of LRT in the upper cold air mass, and the subsidence temperature inversion near the ground layer prevents the dispersion of the lower atmospheric content, allowing accumulation of both regional (especially transboundary) and local atmospheric PM, considerably worsening the air quality (Hien et al., 2002; Lawrence and Lelieveld, 2010; Hai and Kim Oanh, 2013).
During the wet season (May-Oct.), the relatively warmer land with lower atmospheric pressure and relatively cooler ocean with higher atmospheric pressure bring wet and warm air masses. These latter have passed through the Indian Ocean and Equatorial Pacific regions, they are characterized by high boundary mixing layer which promote atmospheric particle dispersion, dilution, and washout by rainfall (Bond et al., 2004; Lin and Cheng, 2007; Wu et al., 2019). Although both the dry and wet seasons are characterized by humidity and rainfall, the heaviest rains, associated with unstable conditions over the Inter Tropical Convergence Zone, mainly occur in July and Aug. (Hien et al., 2002).

208

## 2.2. Sampling method

The sampling sites were selected to be representative of the urban atmosphere of the two cities. Two sampling series were conducted, the first one from Oct. 2012 to Oct. 2013 in Haiphong, and the second one from Oct. 2019 to Dec. 2020 in Hanoi (except during the period Mar.-Apr. 2020 due to the COVID-19 pandemic-induced lockdown). In Haiphong, PM₁₀ were collected on the rooftop of the Institute of Marine Environment and Resources (20.86 °N, 106.68 °E) about 15 m above ground level (17 m above sea level). Samples were obtained every two weeks for two consecutive 12-h periods (6:00 pm to 6:00 am and 6:00 am to 6:00 pm), in order to assess the diurnal variability. A total of 56 samples (28 days) were collected at this site, with an average filtered air volume of 1147 ± 126 m³ per sample. In Hanoi, PM₂.₅ samples were collected on the rooftop (30 m above ground level, 45 m above sea level) of the University of Science and Technology of Hanoi (21.05 °N, 105.80 °E), once a week for a 24-h period. A total of 57 filters were collected, with an average filtered air volume of 1803 ± 81 m³ per sample.

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At both sites, samples were collected using a Staplex High Volume Air sampler and Staplex type TFAQ810 quartz fiber filters (20 × 25 cm) that were pre-combusted (500 °C for
225 4-6 h) to remove organic contamination. Field blanks were handled identically to the PM₁₀
226 and PM₂.₅ sampling, but placed on the Staplex sampler for only 1 min (Pekney and Davidson,
227 2005). After collection, filter samples were wrapped in aluminum foil, sealed in zipper plastic
228 bags, and stored frozen until chemical analyzes.

229 Here, we therefore allow ourselves to compare the carbon content between Hanoi PM₂.₅
230 and Haiphong PM₁₀, based on a previous study conducted in this same area which showed
231 that the majority of the carbon content was contained in the PM₂.₅ fraction (Hai and Kim
232 Oanh, 2013), with coarse particles contributing a minor amount. We consider overall that
233 comparing concentrations (expressed per cubic meter) between these two class sizes
234 introduced an acceptable bias.

235

236 **2.3. Meteorological data**

237 Daily ambient air temperature (°C) and rainfall (mm) values were obtained from the
238 Vietnam Meteorological and Hydrological Administration (VMHA). For Hanoi, data from
239 Lang (21.02 °N, 105.80 °E) and Ha Dong sites (20.97 °N, 105.75 °E) while for Haiphong,
240 data from Phu Lien (20.80 °N, 106.63 °E) and Hon Dau sites (20.67 °N, 106.80 °E) were
241 used.

242 Air mass back trajectories for these datasets have already been published in companion
243 papers (Chifflet et al., 2018, 2024). The data of air mass backward trajectories are not
244 presented here but will be discussed in addition to the temperature and rainfall values for the
245 characterization of the meteorological conditions prevailing at the study sites over the
246 sampling periods.

247

248 **2.4. Analysis**

249 2.4.1. PM₂.₅ mass concentrations
Concentration values (µg m⁻³) were taken from https://aqicn.org/station/vietnam-haiphong-aqsea_vn_014/ and https://aqicn.org/city/vietnam/hanoi/us-embassy/ for Haiphong and Hanoi, respectively because these two measuring stations were considered the most reliable and the closest to our two sampling sites. AQICN is the world's largest database of real time air quality monitoring (Rohde and Muller, 2015). The database provides daily averages over several years and can also provide hourly averages over several months.

In Haiphong, PM₂.₅ mass concentrations were recorded with a light scattering low-cost sensor (LCS) managed by the Building Air Quality Monitoring Capacity in Southeast Asia (AQSEA) network. AQSEA network deployed PurpleAir (PA-II, Plantower) and ensured data validation by looking at both the standalone sensor data (when the sensor is producing minute-level data) and the comparative data (when the sensor is co-located with other sensors including government-operated reference stations). In the “standalone” situation, the data quality was ensured regarding the signal to noise ratio (SNR), defined as the coefficient of variation from the hourly readings. Any measurement with SNR constantly higher than 10% could be biased because of incorrect sensor readings (such as defective fan or dust accumulation). In the “comparative” situation, data quality was validated through comparison with the co-located sensor using a "data readings confidence zone" graphic.

In Hanoi, PM₂.₅ mass concentrations were provided by the Northern Center for Environmental Monitoring (NCEM) of the Vietnam Environment Administration (VEA) from the Ministry of Natural Resources and Environment (MONRE; http://cem.gov.vn/). At this site, data were recorded by a reference beta attenuation sensor (BAM 1020, Met One Instruments, Inc, USA) managed by the United States Embassy and calibrated in Sept. 2019.

The current international recommendations (WHO, 2021) for PM₂.₅ are 5 µg m⁻³ on a yearly average, with an acceptance of 3-4 exceedance days (on a 24-h basis) peaking up to more than 15 µg m⁻³. The NAQS in Vietnam (QCVN 05:2013/BTNMT) stipulates higher
annual (25 µg m⁻³) and 24-h (50 µg m⁻³) for average PM₂.₅ limit values. Only PM₂.₅ mass concentrations will be investigated here because PM₁₀ mass concentrations from LCS are mostly considered as unreliable.

### 2.4.2. Total carbon (TC), EC and OC

The total carbon (TC) of the aerosol samples, including EC and OC (TC = EC + OC), was measured on 1 cm²-subsample filters by thermal analysis in PM₁₀ from Haiphong and by thermo-optical method in PM₂.₅ from Hanoi. Details on both methods are provided in Text S1 and Table S1. Intercomparison studies have shown that variability between thermal and thermo-optical methods is acceptable for TC, but can differ significantly for EC according to the fuels and the combustion processes involved (Cachier et al., 1989; Watson et al., 2005). Thus, interpretation of the results should be done with caution.

From EC and OC concentrations, POC and SOC were estimated using the method proposed by Pio et al. (2011). This method is based on the OC/EC ratio minimal value (OC/ECₘₖ) estimated here from the three lowest OC/EC values within the dataset, considering that it represents samples containing exclusively primary carbonaceous aerosols from fossil fuel combustion (Turpin and Huntzicker, 1995; Castro et al., 1999; Viidanoja et al., 2002). In this approach, the concentrations of POC and SOC are estimated from the following equations:

$$ [POC] = OC/EC_{min} \times [EC] \quad (Eq. 1) $$

$$ [SOC] = [OC] - [POC] \quad (Eq. 2) $$

### 2.4.3. δ¹³Cₜₚ signature

The stable isotopic composition of samples (from Haiphong only) was determined using an elemental analyzer (Flash EA 2000, Thermo Scientific®) coupled with a continuous flow isotope ratio mass spectrometer (Delta V Plus, Thermo Scientific®) via a Conflo IV interface. Details are provided in Text S2.

### 2.4.4. PAHs
301 PAHs were measured on 17 cm²-subsample filters. We determined 20 parent PAHs, and
302 15 groups of alkylated PAHs. Individual compounds and alkylated homologues, the
303 respective abbreviations and the number of rings related to the molecular structure further
304 used in the text are listed in Table S2. PAHs were analyzed by gas chromatography (Trace
305 ISQ, Thermo Electron) equipped with mass spectrometry detector. Detailed protocol of PAH
306 extraction, purification, analysis steps are provided in Barhoumi et al. (2018, 2023).

307 2.4.5. Levoglucosan, soluble major inorganic ions and metals

308 Analysis were carried out on 17 cm²-subsample filters. Methods for these compounds
309 have already been detailed in the companion papers (Chifflet et al., 2018, 2024; Dominutti et
310 al., 2024). Briefly, levoglucosan was analyzed by high performance liquid chromatography
311 coupled with pulsed amperometric detection (HPLC-PAD) according to the EU normalized
312 procedure (XP CEN/TS 18044). NH₄⁺, NO₃⁻, SO₄²⁻ and Cl⁻ were determined by dual ion
313 chromatography coupled to a mass spectrometer (IC-MS) according to Glojeck et al. (2024).
314 Levoglucosan and soluble inorganic ions are available for Hanoi only.

315 Metals (K, Al, Fe, Co, Cu, Zn, Cd, Pb, Rb, V, Ni) and one metalloid (As) in Haiphong
316 PM₁₀ and in Hanoi PM₂.₅ were analyzed either with an inductively-coupled plasma optical
317 spectrometer (ICP-OES, Perkin Elmer, Optima 8000DV) or with an inductively-coupled
318 plasma mass spectrometer (Q-ICP-MS NexION 300X, Perkin Elmer).

319 The different parameters and their respective methods for each city, as well as the
320 quality assurance and quality control information are summarized Table S1.

321 2.4.6. Health risk assessment related to PAHs

322 To assess the lifetime excess cancer risk (LECR) by inhalation associated with exposure
323 to environmental PAHs, the WHO unit risk method (8.7 × 10⁻⁵ per ng m⁻³ BaP) was applied
324 according to Aquilina and Harrison (2023). BaP is the only PAH for which a complete
325 quantitative risk assessment has been conducted (Collins et al., 1991, 1998) and it is
considered as representative of the PAH mixture carcinogenicity. An LECR < 10⁻⁶ means that less than 1 person above 1 million presents a significant risk to develop cancer and is classified as very low. LECR between 10⁻⁶ and 10⁻⁴ (1 to 100 people in 1 million) is classified as low, LECR between 10⁻⁴ and 10⁻³ (100 to 1000 people in 1 million) is moderate, whereas an LECR ≥ 10⁻³ (more than 1 people in 1 thousand) denotes a high potential health risk (Caliskan et al., 2020).

## 2.5. Statistical analysis

The Student's t-test (parametric) and Mann Whitney's U-test (non-parametric) were applied to compare means between two groups, depending on whether the number of observations was high and low, respectively. The significance threshold was set at p < 0.05 for all analyzes and tests performed. All statistical analyzes were conducted using XLSTAT 2023.1.3.1407 software. Correlations were considered as strong for r > 0.8 and moderate for 0.6 < r < 0.8 with an adjusted p-value < 0.05.

## 3. Results

To support the comparison between data collected from Haiphong in 2012-2013 and Hanoi in 2019-2020, we examined meteorological conditions and the trend in PM mass concentration over time.

### 3.1. Meteorological conditions

Air mass back trajectories (from wind speed and direction data) corresponding to the two specific sampling periods (Oct. 2012-Oct. 2013 for Haiphong and Oct. 2019-Oct. 2020
for Hanoi) have already been published (Chifflet et al., 2018, 2024). To complete this information, the monitoring of rainfall and ambient T in Haiphong and Hanoi over the past decade (2012-2022) and during the two specific sampling periods is presented Fig. 2.

Over the period 2012-2022, annual trends for rainfall and T were representative of the monsoon climate and were very similar between the two sites (Fig. 2a-b; Table S3). The wet season (May-Oct.) was characterized by higher monthly cumulative rainfall amounts (from 148-155 to 402-426 mm) and higher average ambient T values (from 26 to 30 °C) compared to the dry season (Nov.-Apr.; from 24-32 to 83-94 mm, and from 17 to 25 °C, respectively).
Over this 11-year time period, the mean of annual cumulative rainfall was ~ 1800 mm, 83% of which was during the wet season, i.e., 5 times more than in the dry season (Fig. 2a-b).

In Haiphong, within the specific sampling period (2012-2013), the wet period (Oct. 2012, May-Sept. 2013) displayed monthly cumulative rainfall amounts and ambient T values ranging from 153 to 561 mm and from 26 to 29 °C, respectively, while during the dry period (Nov.-Apr. 2013 and Oct. 2013), they ranged from 16 to 70 mm and from 16 to 25 °C, respectively (Fig. 2c).

In Hanoi, within the specific sampling period (2019-2020), the wet period spread more (Oct. 2019 and Mar.-Oct. 2020) with monthly cumulative rainfall amounts and air T values ranging from 85 to 411 mm and from 22 to 31 °C, respectively, while during the dry period (Nov. 2019-Feb. 2020 and Nov.-Dec. 2020), they were of 5-123 mm and 18-24 °C, respectively (Fig. 2d).

Over these two sampling periods, the rainfall amounts were 7.7 and 6.3 times higher during the wet season compared to the dry one in Haiphong and Hanoi, respectively.

## 3.2. PM mass
PM mass concentrations were available for Hanoi (Oct. 2019-Oct. 2020) but not for Haiphong (Oct. 2012-Oct. 2013). To compensate for this missing data and ensure a robust comparison of PM concentrations between the two cities, we compared data from 2020-2023, a four-year period for which data were available for both cities (Fig. 3).

Over the period 2020-2023, the monthly average concentrations of PM<sub>2.5</sub> in Haiphong ranged from 14 to 37 µg m<sup>-3</sup> (Fig. 3a; Table S4). Average concentrations during the wet season were 20 ± 5 µg m<sup>-3</sup>, while they were 24 ± 8 µg m<sup>-3</sup> during the dry season, indicating an increase by a factor of 1.2 during dry season compared to the wet one (Fig. 3b; Table S4).

In Hanoi, the monthly average concentrations of PM<sub>2.5</sub> ranged from 35 to 102 µg m<sup>-3</sup> (Fig. 3c; Table S4). Average concentrations during the wet season were 42 ± 18 µg m<sup>-3</sup>, while they were 77 ± 22 µg m<sup>-3</sup>, increasing significantly by a factor of 1.8, during the dry season (Fig. 3d; Table S4).

Over the period 2020-2023, the PM<sub>2.5</sub> concentrations were significantly higher in Hanoi than in Haiphong, by a factor 3-4 when considering both wet and dry seasons, a factor of 2 during the wet season and up to 5 during the dry season (t-test, p < 0.05, n = 700-1400) (Fig. 3a-d; Table S4).

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## 3.3. TC, EC, OC, PAH, POC and SOC concentrations

The sampling design in Haiphong aimed to capture annual, seasonal and diurnal variation in EC, OC and PAH concentrations, as well as δ<sup>13</sup>C depletion in PM<sub>10</sub> during the period Oct. 2012-Oct. 2013 (Fig. S1). However, since significant differences between night and day concentrations could not be demonstrated (t-test, p > 0.05, n = 28), likely due to the relatively low sample number, the results are then presented as daily averages in Fig. 4.

At both sites, carbonaceous content displayed large daily variations (Fig. 4a-f). In Haiphong, PM<sub>10</sub> presented annual average concentrations in TC, EC, OC and PAHs of 7.0 ±
400 3.9 µg m⁻³, 2.1 ± 1.3 µg m⁻³, 4.9 ± 3.1 µg m⁻³ and 4.4 ± 2.6 ng m⁻³, respectively (Table 1).

401 During the dry season, TC, EC, OC, PAHs in Haiphong showed higher average values, i.e.,

402 8.0 ± 3.8 µg m⁻³, 2.4 ± 1.2 µg m⁻³, 5.6 ± 3.2 µg m⁻³ and 5.7 ± 2.5 ng m⁻³, respectively,

403 compared to the wet season, i.e., 5.8 ± 3.8 µg m⁻³, 1.8 ± 1.3 µg m⁻³, 4.0 ± 2.8 µg m⁻³ and 3.0 ±

404 1.8 ng m⁻³, respectively, although only PAH concentrations displayed a significant seasonal

405 alternation (U-test, p < 0.05, n = 13-15) (Fig. 4a-c; Table 1). Haiphong PM₁₀ exhibited annual

406 average values of δ¹³C for TC (δ¹³Cₜc) of -24.9 ± 2.3‰. The dry season was marked by

407 significant (U-test, p < 0.05, n = 13-15) higher values (-23.4 ± 1.6‰) compared to the wet

408 season (-26.7 ± 1.7‰). This difference of 3.3‰ indicated a seasonal shift in the PM₁₀

409 carbonaceous content composition (Table 1).

410 In Hanoi, PM₂.₅ presented annual average concentrations in TC, EC, OC and PAHs of

411 10 ± 6.9 µg m⁻³, 1.3 ± 0.9 µg m⁻³, 9.1 ± 6.2 µg m⁻³ and 5.9 ± 5.8 ng m⁻³, respectively, with

412 TC/PM₂.₅ of 20 ± 8.2% over the period Oct. 2019-Dec. 2020 (calculated from PM₂.₅

413 concentrations at the same sampling dates; Table 1). In Hanoi, TC, OC and PAH

414 concentrations were significantly higher (U-test, p < 0.05, n = 26-31) during the dry season

415 (14 ± 7.9 µg m⁻³, 12 ± 7.1 µg m⁻³ and 9.3 ± 6.7 ng m⁻³, respectively) than in the wet season

416 (7.2 ± 3.6 µg m⁻³, 6.1 ± 3.2 µg m⁻³ and 2.8 ± 2.0 ng m⁻³, respectively), whereas EC and

417 TC/PM₂.₅ did not exhibit any seasonal difference: 1.6 ± 1.0 µg m⁻³ and 19 ± 8.8% in dry

418 season, and 1.1 ± 0.8 µg m⁻³ and 21 ± 7.6% in wet season, respectively (Fig. 4d-f; Table 1).

419 When looking at OC/EC ratio, values in Haiphong (2.7 ± 1.6) were very steady

420 throughout the year. Annual average values in Hanoi (7.5 ± 2.6) were much higher (t-test, p <

421 0.05, n = 28-57) compared to Haiphong, and presented seasonal differences (U-test, p < 0.05,

422 n = 13-15), with 8.5 ± 2.5 and 6.6 ± 2.5 during the dry and the wet season, respectively (Table

423 1).
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### 3.4. PAH relative abundance profiles

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In Haiphong and Hanoi, the relative abundance of OC within TC (OC/TC in %) was stable at the yearly scale (69 ± 11% and 87 ± 5.9%, respectively) with significant differences between the two cities. The annual average POC concentrations were of 2.3 ± 1.4 and 2.9 ± 2.1 µg m⁻³, while SOC concentrations were of 2.6 ± 2.7 and 6.2 ± 5.1 µg m⁻³, with OC/ECₘin of 1.1 ± 0.1 and 2.2 ± 0.7, respectively (Table 1). In Haiphong, the annual average of POC and SOC relative abundance within TC (POC/TC and SOC/TC, respectively) was 33 ± 11% and 37 ± 21% while they were of 29 ± 11% and 59 ± 15%, respectively in Hanoi (Table 1). POC concentrations and POC/TC showed no (or weakly) significant differences between cities or seasons. On the other hand, annual SOC concentrations and SOC/TC were significantly higher in Hanoi. Furthermore, SOC concentrations in Hanoi displayed seasonal differences (9.0 ± 5.5 and 3.7 ± 3.0 µg m⁻³ in dry and wet seasons, respectively), contrary to Haiphong (Table 1).

Regarding the differences in analysis methods, comparison of EC, OC and related values between the two cities must be taken with cautions. However, differences in seasonal variations between the cities are considered significant.

The relative abundance profiles for individual and ring-numbered PAHs in Haiphong PM₁₀ and Hanoi PM₂.₅ are presented in Fig. 5. The profiles were dominated by BbF, BeP, IcdP and BghiP, which accounted for 69 ± 8% and 64 ± 6% of total PAHs, in Haiphong PM₁₀ and Hanoi PM₂.₅, respectively (Fig. 5a). The 5-6 ring PAHs were the major compounds (80 ± 9% and 79 ± 7%) followed by 4-ring compounds (13 ± 6% and 15 ± 4%) and finally 2-3 ring compounds (7 ± 3% and 6 ± 5%) in Haiphong PM₁₀ and Hanoi PM₂.₅, respectively. The profiles in both cities were quite stable over the year, showing no significant differences with seasons. The relative distribution between 5- and 6- ring compounds displayed an inverse
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pattern between the two cities: they represented 30 and 50% in Haiphong, and 50 and 30% in Hanoi, respectively (Fig. 5b, c), suggesting differences in PAH dynamics (emission sources, combustion conditions, aging) between the two cities.

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**3.5. Levoglucosan, K⁺, OC/K⁺ and levoglucosan/K⁺**

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The concentrations of levoglucosan (only available for Hanoi) and K⁺, as well as levoglucosan/K⁺ and OC/K⁺ ratios, are presented in Table 1. It is worth noting that K⁺ concentrations from marine origin have been estimated and removed although minor (5.6 ± 5.2% in Haiphong and 2.1 ± 1.7% in Hanoi). In Hanoi, annual average concentrations of levoglucosan and K⁺ were of 0.4 ± 0.4 µg m⁻³ (0.6 ± 0.5 µg m⁻³ for dry season, 0.2 ± 0.1 µg m⁻³ for wet season) and of 0.4 ± 0.3 µg m⁻³ (0.6 ± 0.4 µg m⁻³ for dry season, 0.3 ± 0.2 µg m⁻³ for wet season), respectively, leading to levoglucosan/K⁺ ratio values of 0.8 ± 0.5 (1.1 ± 0.5 and 0.6 ± 0.3 for dry and wet seasons), seasonal differences being significant for these three parameters (t-test, p < 0.05, n = 27-30), while OC/K⁺ ratio values were stable over the year (21 ± 4.9) (Table 1).

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In Haiphong, the annual average K⁺ concentration and OC/K⁺ ratio were 1.2 ± 0.8 µg m⁻³ (1.5 ± 0.8 µg m⁻³ in dry season, 0.8 ± 0.7 µg m⁻³ in wet season) and 4.6 ± 2.2 (3.8 ± 1.2 in dry season, 5.5 ± 2.8 in wet season), respectively. As for Hanoi, seasonal differences were significant for K⁺ concentrations (U-test, p < 0.05, n = 13-15) but not for OC/K⁺ ratio. These higher K⁺ values associated with lower OC values led to OC/K⁺ much lower in Haiphong compared to Hanoi (t-test, p < 0.05, n = 28-57) (Table 1).

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**3.6. Correlations between carbonaceous content, soluble major inorganic ions and**

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**metals**
The correlations between the carbonaceous content, soluble major inorganic ions and metals for both Haiphong and Hanoi datasets are presented in Table 2. In Haiphong, TC was moderately correlated with PAHs (r = 0.74) and with Cu, V, Ni, As and Cd (r = 0.65-0.71), but highly correlated with K⁺, Al, Fe, Co, Pb and Rb (r = 0.77-0.90). When focusing on EC, OC and PAHs, some distinctions were noticeable. On the one hand, EC and OC were very weakly correlated with each other (r < 0.60) and were both quite moderately correlated with PAHs (r = 0.65-0.67). On the other hand, these three parameters correlated quite well with K⁺, Fe and Rb (r = 0.70-0.85), while their behavior appeared decoupled from that of some other metals (Table 2). For instance, Pb correlated well with EC and PAHs but not with OC, whereas Al correlated much better with OC and PAHs than with EC.

In Hanoi, TC (composed of 87% OC) was much more related to OC than to EC (Table 2). OC, PAHs, levoglucosan and K⁺ were remarkably well correlated with each other (r = 0.83-0.95). OC was also highly correlated with NH₄⁺, NO₃⁻ and SO₄²⁻ (r = 0.73-0.83), while PAHs and levoglucosan displayed good correlations (r = 0.69-0.80) with NH₄⁺ (r = 0.69-0.72), NO₃⁻ (r = 0.78-0.80) and Cl⁻ (r = 0.72-0.75), but low correlations with SO₄²⁻ (r < 0.6).
In addition, OC correlated moderately with Al, Fe, Co, As and Cd (r = 0.66-0.70), PAHs and levoglucosan presenting weaker correlations with these elements (r < 0.71). As for EC, it correlated moderately with OC, PAHs, K⁺ and Cl⁻ (r = 0.63-0.74) and weakly (r < 0.6) with levoglucosan, NH₄⁺, NO₃⁻, SO₄²⁻, and most of metals, r being > 0.6 only with Fe and Cu (Table 2).

Interestingly, all the carbonaceous parameters displayed very weak correlations with Zn in Hanoi and Haiphong, and with Pb in Hanoi, although these metals are important markers of anthropogenic activities. Meanwhile, EC was the only carbonaceous parameter showing a significant correlation with Cu.
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## 3.7. Air quality and health risk assessments

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# 4. Discussion

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## 4.1. Comparison of our PM and carbonaceous contents with literature data

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Based on the BaP concentrations and using the WHO unit risk, LECR related to inhaled PAHs in Haiphong ranged from $2.1 \times 10^{-6}$ to $4.6 \times 10^{-5}$ throughout the year and was considered low. In Hanoi, LECR was higher, ranging from $1.3 \times 10^{-6}$ to $1.9 \times 10^{-4}$, and was also considered low during the wet season (up to $4.3 \times 10^{-5}$). However, it increased to a moderate level ($> 10^{-4}$) during the dry season. Additionally, high concentrations of metals (Cd, Mn in Haiphong; Pb, Cd, Cr in Hanoi) and As were found to exceed current WHO guidelines. Despite this, the estimated carcinogenic risk by inhalation was considered low, except for Cr (Bui et al., 2022; Nguyen et al., 2022; Chifflet et al., 2018, 2024).

PM concentrations in Haiphong and Hanoi recorded for the period 2020-2023 (Table 1; Fig. 3a-d; Table S4) were several times higher than those recorded in a rural site (Tam Dao) from Northern Vietnam or remote islands from the region (Rishiri, Japan and Jeju, Korea) (Okuda et al., 2006; Kim et al., 2012; Hoang et al., 2014), pointing out urbanization and industrialization impacts. Also, in Hanoi, PM$_{2.5}$ concentrations in 2020-2023 were higher than those recorded in the city in 1998-1999 ($36.1 \pm 1.3 \mu g m^{-3}$, Hien et al., 2002), but similar to those from 2001-2008 ($54 \pm 33 \mu g m^{-3}$, Cohen et al., 2010), those from the dry season 2006-2007 ($76 \pm 32 \mu g m^{-3}$, Hai and Kim Oanh, 2013), and similar to those from PM$_{2.5}$ mass reconstruction method published by Dominutti et al. (2024). Hence, regarding previous studies, it seems that the PM$_{2.5}$ concentrations in Hanoi have remained fairly constant for more than 20 years (Cohen et al., 2010; Hai and Kim Oanh, 2013).
TC, EC and OC concentrations, and TC/PM<sub>2.5</sub> ratio values determined here in Hanoi (Table 1; Fig. 4d, e) were in line with a study conducted at two other Hanoi sites during almost the same period (12-15 µg m<sup>-3</sup>, 1.8-3.6 µg m<sup>-3</sup>, 10-12 µg m<sup>-3</sup>, 25-28%, respectively; Makkonen et al., 2023). They were also close (25 µg m<sup>-3</sup>, 2.7 ± 1.5 µg m<sup>-3</sup>, 18 ± 12 µg m<sup>-3</sup>, 25%, respectively; Table 1) to a previous study conducted during the dry season (2006-2007) by Hai and Kim Oanh (2013). Furthermore, our EC and OC values were far below those already reported in highly polluted locations in Asia, like Karachi, Pakistan (8.5 ± 4.8 and 39.9 ± 22.8 µg m<sup>-3</sup>, respectively), Kathmandu, Nepal (10.0 ± 5.8 and 34.8 ± 27.1 µg m<sup>-3</sup>, respectively) or Dhaka, Bangladesh (22.0 and 45.7 µg m<sup>-3</sup>, respectively) (Salam et al., 2003; Chen et al., 2019). On the other hand, our EC and OC concentrations were of the same order of magnitude or even higher than those already recorded in megacities from East Asia, such as Seoul, Korea (0.5 and 4.6 µg m<sup>-3</sup>, respectively) and Beijing, China (0.7 and 7.3 µg m<sup>-3</sup>, respectively) (Park et al., 2022). Also, the TC/PM values recorded in Hanoi fitted within the lower range values of ~10-70% typically found for PM in urban atmospheres (Fuzzi et al., 2006; Rengarajan et al., 2007; Srinivas and Sarin, 2014; Liu et al., 2018; Chen et al., 2019).

The PAH concentrations reported for the two sites (Table 1; Fig. 4c, f) were consistent with those reported for Hanoi by Pham et al. (2024) and one order of magnitude lower than those reported for Ho Chi Minh City by Hien et al. (2007). The higher concentrations in Ho Chi Minh City can be explained by the higher level of urbanization and economical activities of this latter over Hanoi and Haiphong. Nonetheless, Nguyen et al. (2021) found PAH concentrations two orders of magnitude higher than those in the present study, these authors underscoring that their concentrations were high and suggesting an increase in PAH concentrations over time in relation to local habits. Because our results did not confirm this assumption, the values from Nguyen et al. (2021) could also be due to the sampling spots
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(near the road at high-traffic sites), considering that concentrations largely increase close to
emissions sources, particularly busy roads.

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On one hand, the PAH profile found in Hanoi PM<sub>2.5</sub> presented similarities with those
observed by Nguyen et al. (2021) at high-traffic sites. On the other hand, the PAH profile in
Haiphong PM<sub>10</sub> was closer to those reported by Pham et al. (2024) in Hanoi, at sites where
biomass burning and vehicular emissions were highlighted as key sources, and to those
reported by Hien et al. (2007) in Ho Chi Minh City, where additional shipping activities using
heavy fuel oil were suspected. This illustrates the ubiquity of PAHs and the difficulty of
ascribing PAH relative abundance profiles to specific emission sources.

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## 4.2. Seasonal and spatial variations

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The meteorological data highlights that the monsoon climatic conditions were stable
over the last decade and prevailed over the two cities during the specific sampling periods,
with marked dry and wet seasons (Fig. 2a-d; Table S3). Airflows from the East and the
Northeast over China dominated during the dry season, and those from the Southeast or the
Southwest over the East Sea prevailed during the wet season (Chifflet et al., 2018, 2024).

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Consistent with these marked climatic conditions, PM and carbonaceous content
(including PAHs and levoglucosan) concentrations and ratios also exhibited seasonal
variations with higher values during the dry (winter) season compared to the wet (summer)
season, especially in Hanoi (Table 1; Fig. 3, 4; Table S4; Fig. S1). Indeed, the monsoon
climatic conditions have already been identified in previous studies on air quality in Northern
Vietnam as one of the main forcing that can exacerbate atmospheric pollution, especially
during dry season, either by trapping local emissions and/or bringing already polluted air
masses from neighboring countries at a regional scale. In addition, the quite high levels of EC
found here might be able to reduce vertical mixing by favoring the heating of some air masses

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leading to stable stratification (Ding et al., 2016; Wilcox et al., 2016; Hu et al., 2020; Duc et al., 2023). This reduction in turbulent kinetic energy in the layers of the atmosphere may promote the ambient air enrichment by local particle emissions, worsening even more the air quality (Petäjä et al., 2016). On the contrary, during the wet season, the marine air masses probably bring air less impacted by anthropogenic inputs and generate heavy rains that wash out the atmosphere (Hien et al., 2002; Yang et al., 2018; Ly et al., 2021), thus decreasing the load in PM and associated compounds (Zheng et al., 2019). The higher values of OC/EC ratios, as well as SOC concentrations that can occur during the dry season, especially in Hanoi, might reflect higher combustion processes, and/or the accumulation of secondary aerosols originating from the transfer of the gas phase to PM during stagnant air conditions in winter compared to higher dispersion and washed out during the wet season.

Although some commonalities were found between Haiphong and Hanoi, such as the annual POC, POC/TC and PAH concentrations (2.3 ± 1.4 and 2.9 ± 2.1 µg m⁻³; 33 ± 11% and 29 ± 11%; 4.4 ± 2.6 and 5.9 ± 5.8 ng m⁻³, respectively) (Table 1), the study highlighted substantial differences. Annual PM₂.₅ mass concentrations, one of the main indicators of air quality monitoring, were significantly higher in Hanoi than in Haiphong over the period 2020-2023 (Table 1; Fig. 3a-e; Table S4). Regarding the carbonaceous content and ratios, OC, OC/EC, SOC, SOC/TC, OC/K⁺ were also annually higher in Hanoi (Table 1; Fig. 4a-f). The marked difference in OC/K⁺ ratios between the two cities may be attributed to both higher OC concentrations in Hanoi and higher K⁺ concentrations in Haiphong. K⁺ can be emitted in large quantities by biomass burning but it is not a specific tracer because K⁺ is also abundant in crustal dust. On one hand, levoglucosan data were not available for Haiphong to support K⁺ biomass burning origin. Also, due to the contribution of the coarse particles (PM₂.₅-10 fraction) in the sampling and based on metal and metalloid enrichment factor method, Chifflet et al. (2018) ascribed to K⁺, natural/crustal sources associated to soil dust and road
597 resuspension/construction activities in the harbor city. Finally, the relative distributions of
598 PAHs differed between Hanoi and Haiphong and remained stable within the two cities
599 throughout the year (Fig. 5a-c) while the seasonal variability was more pronounced and
600 significant in Hanoi (with a dry-to-wet season concentration ratio of 3.3) compared to
601 Haiphong (dry-to-wet season concentration ratio of 1.9). This further supports the evidence of
602 city-specific characteristics in the pollution sources.

603

604 **4.3. Tracers and emission sources**

605 Anthropogenic activities at both sites were important sources of EC, OC and PAHs as
606 residues from incomplete combustion processes, especially biomass and fossil fuel burning.
607 OC/EC and PAH diagnostic ratios have been widely used to assess the relative importance of
608 biomass versus fossil fuel combustion source apportionment (Colombo et al., 1989; Schauer
609 et al., 1999, 2001; Watson et al., 2001; Watson and Chow, 2001; Marchand et al., 2004; Lee
610 et al., 2006; Tao et al., 2012). Nevertheless, the reliability of these ratio methods is weak
611 because of i) the important mixing of various potential sources for each of which EC, OC and
612 PAH emission in primary aerosols depends on the fuel type and the combustion conditions or
613 efficiency (Schauer et al., 2002; Liu et al., 2020), ii) the lack of uniqueness of the PAH
614 molecular fingerprint with regard to the combusted material (Ramdahl et al., 1982; Jenkins et
615 al., 1996), iii) the aging through photochemical reactions occurring either during LRT or from
616 heterogeneous reactions like in clouds which impacts OC values with SOC formation and
617 individual PAH relative abundance (Schauer et al., 1996; Putaud et al., 2004; Katsoyiannis
618 and Breivik, 2014; Däellenbach et al., 2024). Moreover, our OC/EC values (7.5) in Hanoi
619 were higher than those determined by Makkonen et al. (2023) during the same sampling
620 period with the same measurement method, reporting OC/EC ratio of 3.3 at a traffic site and
5.7 in the urban center, pointing out the influence of emission source proximity within the city.

Due to the limitation of ratio methods, investigating the correlations between EC, OC and PAHs with each other and with other anthropogenic activity tracers, such as levoglucosan, secondary major inorganic aerosols and metals, could be an alternative to more relevantly estimate the main carbonaceous compound emission sources (and related potential toxicity) in Haiphong and Hanoi, as demonstrated in Grenoble (France) (Srivastava et al., 2018).

First, it appears that OC and EC emissions were decoupled or weakly associated with each other at both sites. In Hanoi, the remarkable correlation between OC and PAHs with levoglucosan reflects the importance of biomass combustion (all together domestic, open biomass and municipal waste burning, because of the difficulty distinguishing one from another) and coal combustion emissions in the city (Liang et al., 2021). Also, OC's correlation with the secondary major inorganic aerosol confirms the role of SOC formation in the overall OC content. Besides, OC was also well correlated to some metals and As. Previous studies on the concentrations of NO₂ and SO₂, gaseous precursors of the secondary inorganic aerosols production, and metals over Hanoi city revealed the importance of fuel combustion for urban traffic (residential, road) and Noi Bai International Airport activities, coal and gas for cooking (coal briquettes used in households, restaurants, roadside food kiosks) and pottery, solid waste and rice/crop straw open burning, oil and coal combustion from industries (especially the two old the two old industrial hubs of Thanh Tri and Thanh Xuan, power-stations, smelters), soil/dust resuspension from traffic and construction activities (Hien et al., 2004, 2020; Cohen et al., 2010; Bui et al., 2022; Hien et al., 2022; Nguyen et al., 2022; Vuong et al., 2023; Chifflet et al., 2024). EC would be also linked to biomass/coal
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combustion, as well as non-exhaust emissions or industries in urban contexts related to Cu
emission, but in a quite moderate extent (Dominutti, 2023; Makkonen et al., 2023).

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In Haiphong PM₁₀, the good correlations between the carbonaceous parameters (TC, EC, OC and PAHs) and most metals suggest similar sources, such as anthropogenic urban (domestic and traffic), industrial (including harbor) activities relying widely on oil and coal combustion mixed with crustal dust/soil (local road resuspension) (Chifflet et al., 2018).

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However, compared to Hanoi, EC, OC and PAHs were more weakly correlated to each other, which tends to highlight more diffuse, diluted, weathered inputs, which is consistent with lower PM emission levels and reduced urbanization. The differences between Hanoi and Haiphong support the hypothesis of different dominant sources at the city scale.

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Despite the periodic intrusion from rice straw open burning in the two cities atmosphere or harbor activities in that Haiphong, the tracing here did not allow us to unequivocally highlight these types of anthropogenic contributions, as in Pham et al. (2024).

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4.4. Local versus long range transport

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Air quality in Northern Vietnam is related to the overlay of regional LRT and local atmospheric inputs. However, the relative abundance, even the dominance from one to the other, with regard to the great diversity in terms of anthropogenic activities scattered over the area (Fig. 1), might be closely linked to the sampling location. Regional inputs are supposed to homogeneously impact the study area although the geographical positioning of the two cities would also have an effect, while local emissions will provide city-specific variations and signatures.

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In Haiphong, the lower PM and TC concentrations along with the absence of significant diurnal variations (Table 1; Fig. 3, 4; Fig. S1) were consistent with reduced urbanization and higher contributions of regional inputs, especially during the dry season. During the wet

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season, local inputs may contribute more significantly to local atmosphere than marine
organic matter for which reference δ¹³C values would be less negative (Table 1; Fig. S1;
Turekian et al., 2003). Hence, the δ¹³Cₜc enrichment of ~3.3‰ during the dry season could be
due to photochemical aging of aerosols during LRT from transboundary countries. During
aging/oxidation processes in the atmosphere, low vapor pressure compounds, which present
higher δ¹³C values and are precursors of secondary aerosols, tend to condensate and partition
to aerosol during the formation of SOC. These small molecules are either already enriched in
δ¹³C or could become enriched by losing the lighter isotope during photochemical aging
(Wang and Kawamura, 2006; Aggarwal and Kawamura, 2008; Kirillova et al., 2013; Pavuluri
and Kawamura, 2016). Then, in Haiphong, local emissions seem to dominate in the wet
season while additional LRT inputs are suspected during the dry season. This seasonal
variation of local *versus* regional contributions seems in agreement with observations by
Chifflet et al. (2018). The same kind of results depicting the influence of Asian outflows have
also been shown for Sapporo in Japan (Aggarwal and Kawamura, 2008).

The seasonal change in air mass back trajectories is expected to be accompanied by
significant change in PM carbonaceous content. Nonetheless, many parameters (TC/PM,
OC/TC, OC/K⁺, the relative abundance of individual PAHs) were stable throughout the year
at both cities, which is more likely in favor of a larger impact of local sources over the year.
Previous studies on metals/metalloids and organic/inorganic compounds also underscored the
stability of some sources or their relative abundance all year round (Cohen et al., 2010;
Chifflet et al., 2018, 2024) and significant differences for these parameters between Haiphong
and Hanoi also pointed out a city-specific behavior. Compared to Haiphong, the higher PM₂.₅
and carbonaceous content concentrations and ratios in Hanoi, displaying more pronounced
seasonal variability, highlighted intense local emissions with distinct organic content
characteristics. Supporting the strength of local emissions in Hanoi, diurnal variations have
695 been highlighted using hourly variation data available from the US Embassy sensor (Fig. S2).

696 In the dry season, during the day, a significant PM<sub>2.5</sub> emission increase of 20% in the time slot

697 4:00 am-11:00 am, peaking up to 26% in 6:00 am-9:00 am, compared to the night (9:00 pm-4

698 :00 am) was evidenced. Additionally, the inland location of Hanoi may worsen the particle

699 trapping and aging (impacting PM composition) compared to Haiphong, which is located

700 much closer to the sea, and thus more prone to air dispersion/dilution. Hanoi local sources

701 have already been identified as dominating ambient air pollution throughout the year

702 following a decreasing gradient from the center core of the city to its fringe and to the peri-

703 urban districts, LRT air masses representing a minor part (Hien et al., 2002, 2020; Hai and

704 Kim Oanh, 2013).

705

706 **4.5. Health risk assessment**

707 Based on PM<sub>2.5</sub> mass concentrations, air quality in Haiphong was generally within the

708 national guidelines (although often close to the upper limit and sometimes surpassing it), but

709 exceeded the current international ones by around 4 times (WHO, 2021), while the

710 deterioration of air quality in winter was there moderate. Compared to Haiphong, Hanoi air

711 quality was much more degraded, with PM<sub>2.5</sub> concentrations exceeding Vietnamese guidelines

712 by a factor 2 to 3 and international recommendations by a factor 12 (on an annual basis), up to

713 15 times during the dry season. Hien et al. (2020) also showed that both NO<sub>2</sub> and SO<sub>2</sub>

714 concentrations exceeded WHO AQS, while NO<sub>2</sub> also exceeded NAQS in Hanoi. These values

715 made the Vietnam capital a city with extremely detrimental air (World Air Quality report

716 2022). Besides, although PM mass concentrations and their associated pollutants decreased

717 during the wet season, the pollution levels seemed uncoupled with rainfall heights. Despite

718 heavy rains, the concentrations in PM<sub>2.5</sub> remained at high levels, still exceeding guidelines.
719 Focusing on the respective LECR from PAHs, metals and metalloids associated with air inhalation in Haiphong and Hanoi, the cancer risk remains mostly low (except for Cr) with Hanoi occasionally reaching moderate risk during winter. However, recent studies have shown that air pollution in Hanoi has a detrimental effect on the children's respiratory health (Luong et al., 2017; Nhung et al., 2018, 2019, 2024). Moreover, long-term exposure to ambient air pollution, involving a complex mixture of pollutants, has been linked to severe diseases, particularly in Asia (Yang et al., 2022). Thus, it appears that relying on selected (group of) compounds to assess health risk assessment misrepresents the real health risk.

727 To address this major issue, more comprehensive approaches have emerged, such as the promising oxidative potential (OP) methods, which could enable a more thorough health risk assessment related to the full mixture of aerosol-bound pollutants. The development of OP methods has already highlighted the decoupling between the PM mass concentrations and their associated health risks (Däellenbach et al., 2020; Dominutti et al., 2024), raising questions about the validity of current, widely used air quality indices. In addition, the atmospheric gas phase, which may contain much higher concentrations of more soluble or low molecular weight compounds, should not be overlooked, particularly in research on OP (Klein et al., 2006; Stevanovic et al., 2017; Barhoumi et al., 2023). Indeed, the gas phase can be more easily inhaled and transported across the lungs into the bloodstream than large particles (Ramírez et al., 2011) and has been found to contribute more significantly to cancer risk than the particles (Hassan and Khoder, 2012; Tomaz et al., 2016).

739

740

## 4.6. Limitations and strengths of the study

741 The main limitation of the study is that the compared particles came from size classes that differed and from samplings conducted a few years apart. Moreover, PM mass and TC (EC and OC) concentrations were assessed by distinct methods. Although this may affect a

742

743
744 fine comparison of the data, it most likely does not impact the broad trends we describe in our
745 results. In addition, some parameters are lacking for Haiphong, such as PM₁₀ mass,
746 levoglucosan and soluble major inorganic ions. These deficiencies could also interfere with
747 the interpretation and did not allow to process a consistent source apportionment using
748 chemical mass balance or positive matrix factorization.

749 However, this work provides, for the first time, data on the carbonaceous content in
750 Haiphong aerosols. It is therefore essential to make them visible and to propose a first
751 comparative study despite the identified biases, considered here as acceptable. With the
752 support of historical data from various studies in Hanoi, the present results suggest
753 quantitative and qualitative differences in atmospheric content between the two cities. This
754 implies that the relative importance of local and regional contributions in Northern Vietnam
755 cannot be studied from a single site or a single city, and in particular Hanoi, because of the
756 strength of its local emissions. A more representative estimate of the contribution of the
757 various emission sources should incorporate contrasting sites.

758

759

760 **5. Conclusion**

761

762 The PM mass, carbonaceous content concentrations and ratios in aerosols from
763 Haiphong and Hanoi, two major cities in Northern Vietnam, provided insight into how urban
764 ambient air was predominantly impacted by local or regional anthropogenic activity emission
765 sources. Hanoi, in particular, experienced greater impact of local sources due to i) higher
766 emissions driven by greater levels of urban, commercial, industrial and construction activities
767 and ii) its inland location favoring PM trapping/aging compared to Haiphong, located near the
768 sea which favors PM dispersion. Haiphong was rather impacted by local activities in the wet
769 season and by both local and regional inputs during the dry season. Monsoon climatic

770 conditions worsened air quality, especially during the dry season when stable meteorological

771 conditions and particle characteristics can prevent vertical mixing. Our results show that

772 studies on the characterization of atmospheric content and source apportionment in a region

773 cannot be limited to a single city and must integrate several contrasting sites in order to better

774 identify the relative contributions and better represent the complexity of their dynamics.

775 In terms of health risk assessments in Vietnamese cities, it is crucial to adopt integrative

776 methods that consider the full cocktail of pollutants both in particles (even the finest ones) and

777 in the gas phase. As of 2023, Vietnam continues to experience record levels of air pollution.

778 To address this, Vietnamese authorities should promote a comprehensive emission reduction

779 policy in line with MONRE air quality management plan whose aim would be to make

780 national standards tend to international recommendations.

781

782

783 Author contribution statement

784 CG: Analysis of PAHs in Hanoi and Haiphong, writing original draft, editing,

785 PLM: Writing, editing

786 SC: Analyses of metals, reviewing

787 LG: Sampling, analysis of PAHs in Haiphong

788 PAD: Reviewing

789 TND: Meteorological data collection and processing, reviewing

790 VHB: Reviewing

791 CTV: Reviewing

792 GU: Analysis of ions, EC/OC, sugars in Hanoi, reviewing

793 JLJ: Analysis of ions, EC/OC, sugars in Hanoi, reviewing
794 MT: Writing, editing

795 XM: Conceptualization, reviewing.

796

797 Acknowledgements. This study was financially supported by IRD, through the

798 International Research Network on the *Impact of Black Carbon in South East Asia* (IRN

799 SOOT-SEA) and the International Joint Laboratory on *Study center of the land-ocean-*

800 atmosphere regional coupled system (LMI LOTUS), and by the Vietnamese research institute

801 VAST-IMER. We thank VAST-IMER and VAST-USTH for having hosted the PM samplers

802 on their building roof and for their laboratory facilities. We thank the MIO “PACEM”

803 platform for PAH, EC/OC by thermal method, and δ¹³C analyzes, as well as for laboratory

804 facilities. We also thank the CEREGE “LA-ICP-MS” platform for metal and metalloid

805 analysis, as well as the IGE “Air-O-Sol” platform for EC/OC by thermo-optical method,

806 levoglucosan and water-soluble inorganic ions analyzes. We thank Benjamin Guinot and

807 LAERO Laboratory for their support in sample processing. Finally, we acknowledge two

808 anonymous reviewers for their very constructive and helpful comments.

809

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1291
1292 **Figure caption**

1293 **Figure 1.** Map of sampling sites (Hanoi and Haiphong) and context of the study area
1294 (Northern Vietnam).

1295 **Figure 2.** Averages of monthly cumulative rainfall (mm) and ambient temperature (°C) recorded in a) Haiphong and b) Hanoi for the period 2012-2022, in c) Haiphong for the period 1296 Oct. 2012-Oct. 2013, and in d) Hanoi for the period Oct. 2019-Dec. 2020.
1297

1298 **Figure 3.** Monthly and seasonal (wet and dry seasons) averages of particulate matter (PM) concentrations (µg m⁻³) recorded over the period 2020-2023 in a, b) Haiphong and c, d) Hanoi. Red and purple dashed lines represent national air quality standard values for PM₂.₅

1300 Hanoi. Red and purple dashed lines represent national air quality standard values for PM2.5
1301 (NAQS, 25 µg m⁻³) and international air quality recommendation (WHO, 2021, 5 µg m⁻³).

1302 PM₂.₅/PM₁₀ (e) is the ratio of PM₂.₅ over PM₁₀ concentrations over 2020-2023 with blue and
1303 yellow colors representing the wet and the dry season, respectively.

1304 **Figure 4.** Daily concentrations of elemental carbon (EC, ●), organic carbon (OC, ▲) and polycyclic aromatic hydrocarbons (PAHs, ♦) measured in Haiphong PM₁₀ over the period Oct. 2012-Oct. 2013 (a, b, c, respectively) and in Hanoi PM₂.₅ over the period Oct. 2019-Dec. 2020 (d, e, f, respectively). Blue and yellow colors represent the wet and the dry season, respectively.

1309 **Figure 5.** Relative abundance (%) of a) individual polycyclic aromatic hydrocarbons (PAHs) and b, c) ring-numbered PAHs measured in Haiphong (Oct. 2012-Oct. 2013) and Hanoi (Oct. 2019-Dec. 2020).

1312

1313
<table><caption>**Table 1.** Particulate matter and carbonaceous content concentrations and ratios in aerosols from Haiphong and Hanoi cities (Northern Vietnam), and comparison with literature data.</caption><thead><tr><th rowspan="3"></th><th colspan="12">This study</th><th colspan="2">Makkonen et al. (2023)</th><th colspan="2">Hai and Kim Oanh (2013)</th></tr><tr><th colspan="4">Haiphong (Oct. 2012-Oct. 2013)</th><th colspan="4">Hanoi (Oct. 2019-Dec. 2020)</th><th colspan="2">Hanoi</th><th colspan="2">Hanoi</th></tr><tr><th>Annual</th><th colspan="3">PM<sub>10</sub></th><th></th><th>Annual</th><th colspan="3">PM<sub>2.5</sub></th><th>Annual</th><th>PM<sub>2.5</sub></th><th>PM<sub>2.5</sub></th><th>Dry season</th></tr><tr><th></th><th></th><th>Dry season</th><th>Wet season</th><th>Dry/Wet<sup>a</sup></th><th></th><th></th><th>Dry season</th><th>Wet season</th><th>Dry/Wet<sup>a</sup></th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td>PM (µg m<sup>-3</sup>)</td><td></td><td></td><td></td><td></td><td></td><td><b>53 ± 29</b></td><td>73 ± 28</td><td>35 ± 16</td><td>2.1*</td><td>48 – 55</td><td></td><td>76 ± 32</td><td></td></tr><tr><td>EC (µg m<sup>-3</sup>)</td><td><b>2.1 ± 1.3</b></td><td>2.4 ± 1.2</td><td>1.8 ± 1.3</td><td>1.3</td><td><b>1.3 ± 0.9</b></td><td>1.6 ± 1.0</td><td>1.1 ± 0.8</td><td>1.5</td><td></td><td>1.8 – 3.6</td><td></td><td>2.7 ± 1.5</td><td></td></tr><tr><td>OC (µg m<sup>-3</sup>)</td><td><b>4.9 ± 3.1</b></td><td>5.6 ± 3.2</td><td>4.0 ± 2.8</td><td>1.4</td><td><b>9.1 ± 6.2</b></td><td>12 ± 7.1</td><td>6.1 ± 3.2</td><td>2.0*</td><td></td><td>10 – 12</td><td></td><td>18 ± 12</td><td></td></tr><tr><td>TC (µg m<sup>-3</sup>)</td><td><b>7.0 ± 3.9</b></td><td>8.0 ± 3.8</td><td>5.8 ± 3.8</td><td>1.4</td><td><b>10 ± 6.9</b></td><td>14 ± 7.9</td><td>7.2 ± 3.6</td><td>1.9*</td><td></td><td>12 – 15</td><td></td><td>25</td><td></td></tr><tr><td>OC/EC</td><td><b>2.7 ± 1.6</b></td><td>2.7 ± 1.8</td><td>2.7 ± 1.4</td><td>1.0</td><td><b>7.5 ± 2.6</b></td><td>8.5 ± 2.5</td><td>6.6 ± 2.5</td><td>1.3*</td><td></td><td>3.3 – 5.7</td><td></td><td>7.2</td><td></td></tr><tr><td>OC/TC (%)</td><td><b>69 ± 11</b></td><td>69 ± 10</td><td>69 ± 12</td><td>1.0</td><td><b>87 ± 5.9</b></td><td>89 ± 4.1</td><td>85 ± 6.8</td><td>1.0</td><td></td><td>77 – 85</td><td></td><td>88</td><td></td></tr><tr><td>TC/PM</td><td></td><td></td><td></td><td></td><td>20 ± 8.2</td><td>19 ± 8.8</td><td>21 ± 7.6</td><td>0.9</td><td></td><td>25 – 28</td><td></td><td>25</td><td></td></tr><tr><td>δ<sup>13</sup>C<sub>TC</sub> (‰)</td><td>-24.9 ± 2.3</td><td>-23.4 ± 1.6</td><td>-26.7 ± 1.7</td><td>3.3<sup>b*</sup></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>POC (µg m<sup>-3</sup>)</td><td>2.3 ± 1.4</td><td>2.5 ± 1.3</td><td>1.9 ± 1.4</td><td>1.3</td><td>2.9 ± 2.1</td><td>3.4 ± 2.2</td><td>2.4 ± 1.8</td><td>1.5</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>POC/TC (%)</td><td>33 ± 11</td><td>33 ± 11</td><td>33 ± 12</td><td>1.0</td><td>29 ± 11</td><td>25 ± 9</td><td>32 ± 11</td><td>0.8*</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SOC (µg m<sup>-3</sup>)</td><td><b>2.6 ± 2.7</b></td><td>3.1 ± 3.1</td><td>2.1 ± 2.2</td><td>1.5</td><td><b>6.2 ± 5.1</b></td><td>9.0 ± 5.5</td><td>3.7 ± 3.0</td><td>2.4*</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SOC/TC (%)</td><td><b>37 ± 21</b></td><td>36 ± 21</td><td>39 ± 22</td><td>0.9</td><td><b>59 ± 15</b></td><td>64 ± 13</td><td>55 ± 15</td><td>1.2</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PAHs (ng m<sup>-3</sup>)</td><td>4.4 ± 2.6</td><td>5.7 ± 2.5</td><td>3.0 ± 1.8</td><td>1.9*</td><td>5.9 ± 5.8</td><td>9.3 ± 6.7</td><td>2.8 ± 2.0</td><td>3.3*</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Levo (µg m<sup>-3</sup>)</td><td></td><td></td><td></td><td></td><td>0.4 ± 0.4</td><td>0.6 ± 0.5</td><td>0.2 ± 0.1</td><td>3.5*</td><td></td><td>0.38 – 0.43</td><td></td><td></td><td></td></tr><tr><td>K<sup>+</sup> (µg m<sup>-3</sup>)</td><td><b>1.2 ± 0.8</b></td><td>1.5 ± 0.8</td><td>0.8 ± 0.7</td><td>1.9*</td><td><b>0.4 ± 0.3</b></td><td>0.6 ± 0.4</td><td>0.3 ± 0.2</td><td>1.9*</td><td></td><td>0.51 – 0.54</td><td></td><td></td><td></td></tr><tr><td>Levo/K<sup>+</sup></td><td></td><td></td><td></td><td></td><td>0.8 ± 0.5</td><td>1.1 ± 0.5</td><td>0.6 ± 0.3</td><td>1.8*</td><td></td><td>0.70 – 0.83</td><td></td><td></td><td></td></tr><tr><td>OC/K<sup>+</sup></td><td><b>4.6 ± 2.2</b></td><td>3.8 ± 1.2</td><td>5.5 ± 2.8</td><td>0.7</td><td><b>21 ± 4.9</b></td><td>22 ± 4.4</td><td>21 ± 5.4</td><td>1.0</td><td></td><td>19 – 23</td><td></td><td></td><td></td></tr></tbody></table>

PM = particulate matter; EC = elemental carbon; OC = organic carbon; TC = total carbon (EC + OC); OC/EC = OC concentrations over EC concentrations; OC/TC = relative abundance of OC in TC; δ¹³Cₜc = depletion in ¹³C for TC; POC = primary organic carbon; POC/TC = relative abundance of POC in TC; SOC = secondary organic carbon; SOC/TC = relative abundance of SOC in TC; PAHs = polycyclic aromatic hydrocarbons; Levo = levoglucosan; K⁺ = potassium ion (of non-seawater origin); Levo/K⁺ = Levoglucosan concentrations over K⁺ concentrations; OC/K⁺ = OC concentrations over K⁺ concentrations.
Values in bold highlights significant differences in annual concentrations between Haiphong and Hanoi from the present study, (t-test, p < 0.05, n = 28-57).

a Ratio of average concentrations during the dry season over concentrations during the wet season except for δ¹³Cₜc (see b).

b Absolute value of the depletion difference between the two seasons.

* Significant differences between dry and wet seasons (U-test, p < 0.05, n = 13-15 for Haiphong and 27-30 for Hanoi).
1 **Table 2.** Correlation coefficients (r) issued from the linear relationships between
2 concentrations of various elements of carbonaceous content, secondary inorganic aerosols and
3 trace elements determined in PM₁₀ samples collected in Haiphong from Oct. 2012 to Oct.
4 2013 (n = 28), and in PM₂.₅ samples collected in Hanoi from Oct. 2019 to Dec. 2020 (n = 57).

<table><thead><tr><th rowspan="2"></th><th colspan="4">Haiphong</th><th colspan="6">Hanoi</th></tr><tr><th>TC</th><th>EC</th><th>OC</th><th>PAHs</th><th>PM<sub>2.5</sub></th><th>TC</th><th>EC</th><th>OC</th><th>PAHs</th><th>LevoG</th></tr></thead><tbody><tr><td>TC</td><td></td><td>0.72</td><td>0.96</td><td>0.74</td><td>0.72</td><td></td><td>0.74</td><td>0.99</td><td>0.92</td><td>0.92</td></tr><tr><td>EC</td><td>0.72</td><td></td><td>&lt;0.6</td><td>0.67</td><td>&lt;0.6</td><td>0.74</td><td></td><td>0.67</td><td>0.69</td><td>&lt;0.6</td></tr><tr><td>OC</td><td>0.96</td><td>&lt;0.6</td><td></td><td>0.65</td><td>0.74</td><td>0.99</td><td>0.67</td><td></td><td>0.91</td><td>0.93</td></tr><tr><td>PAHs</td><td>0.74</td><td>0.67</td><td>0.65</td><td></td><td>0.65</td><td>0.92</td><td>0.74</td><td>0.91</td><td></td><td>0.93</td></tr><tr><td>LevoG</td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.70</td><td>0.92</td><td>&lt;0.6</td><td>0.93</td><td>0.93</td><td></td></tr><tr><td>K<sup>+</sup></td><td>0.87</td><td>0.74</td><td>0.79</td><td>0.78</td><td>0.68</td><td>0.95</td><td>0.65</td><td>0.95</td><td>0.83</td><td>0.85</td></tr><tr><td>Cl<sup>-</sup></td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.64</td><td>0.71</td><td>0.63</td><td>0.69</td><td>0.75</td><td>0.72</td></tr><tr><td>NH<sub>4</sub><sup>+</sup></td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.80</td><td>0.77</td><td>&lt;0.6</td><td>0.78</td><td>0.69</td><td>0.72</td></tr><tr><td>NO<sub>3</sub><sup>-</sup></td><td>-</td><td>-</td><td>-</td><td>-</td><td>0.84</td><td>0.83</td><td>&lt;0.6</td><td>0.83</td><td>0.78</td><td>0.80</td></tr><tr><td>SO<sub>4</sub><sup>2-</sup></td><td>-</td><td>-</td><td>-</td><td>-</td><td>&lt;0.6</td><td>0.72</td><td>&lt;0.6</td><td>0.73</td><td>&lt;0.6</td><td>&lt;0.6</td></tr><tr><td>Al</td><td>0.84</td><td>0.62</td><td>0.79</td><td>0.70</td><td>&lt;0.6</td><td>0.70</td><td>&lt;0.6</td><td>0.69</td><td>&lt;0.6</td><td>&lt;0.6</td></tr><tr><td>Fe</td><td>0.90</td><td>0.70</td><td>0.85</td><td>0.77</td><td>&lt;0.6</td><td>0.76</td><td>0.61</td><td>0.75</td><td>0.65</td><td>&lt;0.6</td></tr><tr><td>Co</td><td>0.82</td><td>0.68</td><td>0.76</td><td>0.68</td><td>&lt;0.6</td><td>0.68</td><td>&lt;0.6</td><td>0.66</td><td>&lt;0.6</td><td>&lt;0.6</td></tr><tr><td>Cu</td><td>0.65</td><td>0.75</td><td>&lt;0.6</td><td>&lt;0.6</td><td>ns</td><td>ns</td><td>0.64</td><td>ns</td><td>ns</td><td>Ns</td></tr><tr><td>Zn</td><td>&lt;0.6</td><td>0.60</td><td>Ns</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>0.61</td><td>&lt;0.6</td><td>&lt;0.6</td></tr><tr><td>As</td><td>0.69</td><td>0.69</td><td>&lt;0.6</td><td>ns</td><td>&lt;0.6</td><td>0.69</td><td>&lt;0.6</td><td>0.68</td><td>0.60</td><td>&lt;0.6</td></tr><tr><td>Cd</td><td>0.71</td><td>0.77</td><td>&lt;0.6</td><td>0.66</td><td>&lt;0.6</td><td>0.71</td><td>&lt;0.6</td><td>0.70</td><td>0.71</td><td>0.65</td></tr><tr><td>Pb</td><td>0.77</td><td>0.82</td><td>&lt;0.6</td><td>0.73</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td></tr><tr><td>Rb</td><td>0.86</td><td>0.80</td><td>0.75</td><td>0.81</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>V</td><td>0.67</td><td>0.63</td><td>&lt;0.6</td><td>&lt;0.6</td><td>ns</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td><td>&lt;0.6</td></tr><tr><td>Ni</td><td>0.69</td><td>0.72</td><td>&lt;0.6</td><td>&lt;0.6</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td></tr></tbody></table>

ns = not significant (p > 0.05).

Values are presented in bold for significant (p < 0.05) r > 0.6 (highlighting moderate to high correlations), in black for 0.6 ≤ r < 0.7, orange for 0.7 ≤ r < 0.8, and red for r ≥ 0.8.
<figure><img src="image_3.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>Figure 2</figcaption></figure>
Haiphong 2020-2023

<figure><img src="image_8.png" /><figcaption>Figure 3</figcaption></figure>

<figure><img src="image_9.png" /></figure>
<figure><img src="image_10.png" /><figcaption>Figure 4</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>Figure 5</figcaption></figure>
* Differences in carbonaceous content between Haiphong PM₁₀ and Hanoi PM₂.₅

* Hanoi PM₂.₅ was yearly dominated by local biomass and coal burning sources

* Haiphong PM₁₀ showed seasonal variations of local and regional pollution sources

* Asian monsoon climate worsens air quality in Northern Vietnam

* Compound-specific methods do not provide realistic inhalation health risks
**Declaration of interests**

[x] The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

[ ] The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

<figure><img src="image_12.png" /></figure>