Next Article in Journal
Water Resources Evaluation in Arid Areas Based on Agricultural Water Footprint—A Case Study on the Edge of the Taklimakan Desert
Next Article in Special Issue
Statistical PM2.5 Prediction in an Urban Area Using Vertical Meteorological Factors
Previous Article in Journal
Propagation of Perturbations in the Lower and Upper Atmosphere over the Central Mediterranean, Driven by the 15 January 2022 Hunga Tonga-Hunga Ha’apai Volcano Explosion
Correction published on 20 April 2023, see Atmosphere 2023, 14(4), 745.
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Ambient Nanoparticles (PM0.1) Mapping in Thailand

Worradorn Phairuang
Suthida Piriyakarnsakul
Muanfun Inerb
Surapa Hongtieab
Thunyapat Thongyen
Jiraporn Chomanee
Yaowatat Boongla
Phuchiwan Suriyawong
Hisam Samae
Phuvasa Chanonmuang
Panwadee Suwattiga
Thaneeya Chetiyanukornkul
Sirima Panyametheekul
Muhammad Amin
Mitsuhiko Hata
1 and
Masami Furuuchi
Faculty of Geosciences and Civil Engineering, Institute of Science and Engineering, Kanazawa University, Kanazawa 920-1192, Japan
Department of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai 50200, Thailand
Office of National Higher Education Science Research and Innovation Policy Council, Bangkok 10330, Thailand
Faculty of Environmental Management, Prince of Songkla University, Hat Yai 90110, Thailand
Department of Environmental Technology and Management, Faculty of Environment, Kasetsart University, Bangkok 10900, Thailand
Department of Basic Science and Mathematics, Faculty of Science, Thaksin University, Songkhla 90000, Thailand
Department of Sustainable Development Technology, Faculty of Science and Technology, Thammasat University, Rangsit Campus, Pathumtani 12121, Thailand
Research Unit for Energy, Economic, and Ecological Management (3E), Science and Technology Research Institute, Chiang Mai University, Chiang Mai 50200, Thailand
Expert Centre of Innovative Clean Energy and Environment, Thailand Institute of Scientific and Technological Research (TISTR), Klong Luang, Pathumtani 12120, Thailand
Department of Agro-Industrial, Food and Environmental Technology, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand
Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Department of Environmental Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
HAUS IAQ Research Unit, Chulalongkorn University, Bangkok 10330, Thailand
Faculty of Engineering, Maritim University of Raja Ali Haji, Tanjung Pinang, Kepulauan Riau 29115, Indonesia
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(1), 66;
Submission received: 7 December 2022 / Revised: 24 December 2022 / Accepted: 26 December 2022 / Published: 29 December 2022 / Corrected: 20 April 2023
(This article belongs to the Special Issue Atmospheric Particulate Matter Hazard Mapping)


Nanoparticles (NPs), nanoaerosols (NAs), ultrafine particles (UFPs), and PM0.1 (diameters ≤ 0.1 µm or 100 nm) are used interchangeably in the field of atmospheric studies. This review article summarizes recent research on PM0.1 in Thailand. The review involved peer-reviewed papers that appeared in the Scopus and the Web of Science databases and included the most recently published articles in the past 10 years (2013–2022). PM0.1 mainly originate from combustion processes such as in motor vehicles. The highest mass concentration of PM0.1 occurs during the dry season, in which open fires occur in some regions of Thailand. The northern area of the country has higher PM0.1 mass concentrations, followed by the central and southern areas. Carbonaceous nanoaerosols are produced during normal periods, and the proportions of organic to elemental carbon and char to soot suggest that these originate from motor vehicles. However, in haze periods, biomass fires can also produce carbon-containing particles. PM0.1 pollution from local and cross-border countries also needs to be considered. The overall conclusions reached will likely have a beneficial long-term impact on achieving a blue sky over Thailand through the development of coherent policies and managing new air pollution challenges and sharing knowledge with a broader audience.

1. Introduction of Impact of PM0.1

Ambient particulate matters (PMs), which are strongly associated with harmful aspects concerning human health [1,2] and global warming, have recently appeared [3] and have attracted considerable interest regarding environmental pollution in many countries. PMs can be categorized into three modes, which include coarse particles (diameter between 2.5 and 10 µm), fine particles (with a diameter between 0.1 to 2.5 µm), and ultrafine particles (diameters ≤ 0.1 µm or 100 nm) [4,5]. The coarse category is primarily generated from attrition processes, namely, mechanical abrasion, the re-suspension of road and soil dust, volcanic eruptions, and sea spray [6]. On the other hand, fine and ultrafine mode particles evolve mainly from combustion processes, e.g., biomass burning, motor vehicle exhaust, coal combustion, and chemical processes in the atmosphere [7,8].
Nanoparticles (NPs), nanoaerosols (NAs), ultrafine particles (UFPs), and PM0.1 are interchangeably used depending on the subject area [9], but there are slight differences among these particles. The most common nanoparticles are mainly incidentally and unintentionally generated and are suspended in the atmosphere [8,10]. The term nanoaerosols is used to refer to a broader coverage, including environmental and engineered nanoparticles. In addition, toxicologists refer to particle size as ultrafine, fine, and coarse particles to specify their danger to cells and human health [11,12]. The latest definition is PM0.1, which typically refers to solid particles with at least one dimension smaller than 0.1 µm or 100 nm [13] and is always used in atmospheric pollution studies. Therefore, nanoparticles, nanoaerosols, ultrafine particles, and PM0.1 are commonly used in the scientific fields but depend on the subject matter areas.
In the past decade, smaller particles (PM2.5 or, predominantly, PM0.1) are likely to be a human health risk problem [8,14]. Airborne PM is linked to increased mortality and morbidity in humans [15]. There is considerable evidence to show that PMs harm the respiratory, nervous, and cardiovascular systems [16,17,18]. Smaller particles (UFPs) have a large surface area and strong absorption/adsorption capability for various airborne contaminants. UFPs can carry both various hazardous chemical compounds, such as polycyclic aromatic hydrocarbons (PAHs) and heavy metals [19,20,21,22], and airborne pathogens such as bacteria, fungi, and viruses [22,23].
Southeast Asia (SEA) has been a source of PM pollution for the last decades, affecting countries in and countries outside the region [24,25]. The transport plume of Indonesian forest fires affects air quality in Singapore, Malaysia, Brunei, and southern Thailand [25,26,27,28]. Moreover, recent studies suggest that fine particles from open biomass burning plumes are transported from northern Southeast Asia (SEA) to East Asia (EA), including southeastern China, the South China Sea, and southern Taiwan, during the dry season [29,30,31]. In Thailand, the effect of the migration of polluted air masses is vital on a multi-provincial scale (100–200 km) [32].
The particulate matter (PM) pollution observed in Thailand and Southeast Asian countries is related to studies of the PM10 and PM2.5 fractions and, to a slight extent, on the ground monitoring and satellite detection of PM1.0 [33,34,35,36,37]. However, information on the status and characteristics of PM0.1 and emission sources is still ongoing and only limited information is currently available. Only a few studies have appeared concerning the level and sources of airborne NPs between different locations [32,38,39]. This work gathered current papers on all aspects of atmospheric UFPs in Thailand. Over 100 refereed papers in the Web of Sciences and Scopus databases were examined for this study and were used to integrate this knowledge base. The keywords searched included “PM0.1, ultrafine particles, nanoparticles, nanoaerosols, haze pollution, health effects, Thailand”. The work covered publications in this area that have appeared in the past 10 years, from 2013 to 2022, and included the following topics:
  • Introduction to the impact of PM0.1;
  • Recent studies of PM0.1 particles in Thailand;
  • Health concerns regarding PM0.1 particles in Thailand;
  • Challenges to the study of PM0.1 particles in Thailand;
  • Options and recommendations for PM0.1 in Thailand;
  • Conclusions.

2. Recent Studies of PM0.1 in Thailand

2.1. PM0.1 Particle Mass Concentration and Particle Number Concentration

The PM0.1 levels in ambient air are usually extensively measured by particle number concentration (PNC) due to their minuscule size in addition to mass concentration [40]. No standards for airborne PM0.1 have been adopted in Thailand. Thailand’s National Ambient Air Quality Standards recently established parameters for six air pollutants that are deemed the highest priority to protect public health, including PM (TSP, PM10, PM2.5), O3, CO, SO2, NO2, and lead (Pb) (Table 1). The six criteria for pollutants are classified into health risk levels based on criteria defined by Thailand’s Air Quality and Noise Management Bureau, Pollution Control Department, and Ministry of Natural Resources and Environment. This is the current standard as of 2022; particulate pollution is a severe and increasing problem for Thailand. The Pollution Control Department announced in 2022 [41] that it will decrease Thailand’s National Ambient Air Quality of 24 h PM2.5 concentration to 37.5 µg/m3 in 2023. This is because of human health concerns about smaller particles in the recent decade.
Moreover, according to the new guidelines on air quality by the World Health Organization (WHO) (2021) [42], the suggested mean annual concentration for PM10 was 200 µg/m3 in 2005 and the mass concentration for 2021 moved to 150 µg/m3. The 24 h concentration was updated from 50 µg/m3 in 2005 to 45 µg/m3. Furthermore, in 2005, the highest recommended average PM2.5 annual mass concentration was 10 µg/m3; the 2021 revision reduced that number by half, to just 5 µg/m3. The 24 h level changed from 25 µg/m3 in 2005 to 15 µg/m3. The WHO was confident that there was insufficient information to provide guidelines for other types of PM, including elemental and black carbon, sand and dust storm particles, and PM0.1 particles. The WHO does not create a set of best practices for managing those pollutants, even though it recommends further study into their risks and methods for mitigation.
In European countries, the Condensation Particle Counter (CPC) is a standard method for measuring nanoparticles [43]. However, the ambient nanoparticle standard for all emission types is still limited. Only the gasoline and diesel emission standard representing the non-volatile particle of diameter >23 nm has been defined (the Solid Particle Number > 23 nm method (SPN23)) [44]. Surface area and particle number are appropriate for measuring minor mass concentrations of PM0.1 in most atmospheres [16]. NPs are commonly measured as particle number concentration (PNC), representing more than 85% of the total PM2.5 particle number [45]. In contrast, it contributes only slightly (10–20%) to the total PM concentration.
Table 2 shows the PM0.1 mass concentration at each sampling site in Thailand. The first sampling of NPs in Thailand started during 2014–2015 in Bangkok and Chiang Mai. Chiang Mai had the highest PM0.1 level in Thailand based on the sampling period during 2014–2015 up to 25.2 ± 4.7 µg/m3. Bangkok, the capital city of Thailand, is one of the megacities in SEA with high concentrations of residents and traffic congestion. Many studies have concluded that the particulate pollution in the Bangkok metropolitan region (BMR) is mainly from land transportation [46,47,48,49]. The mass concentration of PM0.1 in the BMR ranges from 7.7–18.9 µg/m3, a number that is higher than that in Western countries such as those of Europe and the USA; however, it is in the same range as other Asian megacities such as Shanghai [50]. The levels of PM0.1 particles in southern Thailand are comparatively low compared with other types; cities in Thailand range from 1.9 ± 0.6 (normal)–14.2 ± 10.0 (haze) µg/m3. Interestingly, PM0.1/PM2.5 is the highest in Chiang Mai, Thailand. It is well known that Chiang Mai has been confronted with air pollution in almost every dry season from January to mid-April. PM2.5 concentrations are augmented every dry season (January–April), which starts around mid-January and reaches its peak in March before decreasing by April. The primary source of worsening air pollution during the dry season in these areas was open burning, such as forest fires and crop residue burning [32]. Considering that the ultrafine particles from biomass burning are so high is in general agreement with laboratory experiments, in which nanoparticles account for up to 30% of the total particle mass concentration [51].
In the BMR, the PM0.1/PM2.5 ratio is around 0.23 [32]. Motor vehicles account for smaller particles in this area, and the ratio slightly increases to 0.26 during the dry season, indicating that some biomass burning episodes produce PM0.1 [24]. Hat Yai, Songkhla province, is an economic city in the south of Thailand. A previous study showed that the primary particulate pollutants in Hat Yai are caused by biomass combustion from the rubber industry [56] because southern Thailand is different from the other regions of Thailand. The economic crop in the region is oil palm and para-rubber, which are produced in plantations in the south of Thailand [57,58]. However, PM0.1 in the southern part of Thailand is lower than in other parts due to less frequent open biomass burning fires in the area. The PM0.1/PM2.5 ranges from 0.15 to 0.19 depending on the transboundary particulate effects that increase the mass concentration [26,55].

2.2. Carbonaceous Nanoaerosol

The most significant portion of airborne PM is carbon-containing materials with various physical and chemical characteristics, which account for around 20–50% of the mass concentration of PMs [59,60]. The PM-bound total carbon (TC) can be divided into two types, including organic carbon (OC) and black carbon (BC) or elemental carbon (EC). BC and EC are used interchangeably depending on the analytical method being used [61,62]. Brown carbon (BrC) was recently discovered with light absorption characteristics similar to atmospheric aerosols [63]. BrC is a non-soot organic carbon aerosol that is produced from bioaerosols, tar, and humic-like substances (HULIS) [64,65]. BC is mainly emitted by high-temperature combustion processes (diesel and gasoline exhausts, coal combustion, and biomass burning) [66,67]. BrC is primarily emitted by biomass burning. BC and BrC are the two most crucial light-absorbing substances in atmospheric aerosols [68]. In contrast, OC is a light-scattering material that is mainly generated from biomass fires, coal combustion, motor vehicles, and secondary chemical processes in the atmosphere [69,70]. The Intergovernmental Panel on Climate Change (IPCC) predicted that EC would lead to a direct global radiative forcing of around +0.2 Wm−2 [71]. In contrast, OC was produced at around the same magnitude [72]. Therefore, the primary emissions of BC clearly have global warming potential and can influence the hydrological cycle [73]. Primary pollutants, including BC and OC, include an atmospheric photochemical activity and can produce secondary organic aerosols (SOA) and ozone (O3), creating an even more complicated effect [74].
Information concerning OC and EC is crucial in estimating the impact of PMs and our understanding of the source and strength of these pollutants. EC can be divided into char-EC and soot-EC [75]. Char consists of the residue remaining after burning solid residue. Soot, however, is different from the physical and chemical properties of the source materials after the high-temperature condensation of hot gases during the combustion process [76]. The ratio of Char-EC and Soot-EC varies depending on the main sources and can be used to categorize the origin of this material. Only a small number of studies have reported on the pattern for Thailand’s carbonaceous nanoaerosols (OC and EC) [24,25,32,55]. Brown carbon (BrC) in nanoaerosols, which affects the splitting between OC and EC via a thermal-optical protocol, has not been studied so far in Thailand. A reliable method for detecting BrC plays a vital role in accurately estimating carbonaceous nanoaerosols [77]. The effect on regional and global warming is highly uncertain due to carbonaceous aerosols that are emitted into the atmosphere. This is because the distribution of carbon fractions varies with the time and location, which basically contributes to the chemical, physical, and optical characteristics of carbon components in PMs. Accordingly, information on carbonaceous nanoaerosols is vital in terms of assessing their radiative effects on global warming. Only limited studies of carbon components and spatial and temporal variations in Thailand have appeared, particularly of the nano-scale ambient particles related to carbon components.

2.3. Carbon Characteristics of OC, EC, Char-EC, and Soot-EC

The ratios of OC/EC can be used to classify the exact emission sources of carbonaceous particulate matter. Ratios for diesel exhaust, coal burning, and biomass combustion are different. Biomass burning has a higher ratio, while the OC/EC ratios for fossil burning results are lower [78]. The ratio of OC to EC for biomass combustion is higher (~6–8) [79] and that from fossil fuel is lower (<1) [80]. The characteristics of emission sources of carbon fractions include diesel exhaust (OC/EC ~0.1–0.8) [70], biomass combustion (OC/EC ~4–6) [33,81], and long-range transport/aged aerosol (OC/EC ~12) [82]. On the other hand, OC/EC depends on three factors for appropriately categorizing the source of the emission. The three factors include the primary emission source, the deposition rate, and secondary organic aerosols (SOA) [55,70]. Table 3 shows the average seasonal concentration of OC, EC, Char-EC, Soot-EC (µg/m3), and OC/EC and Char-EC/Soot-EC ratios in different locations in Thailand. A high concentration of carbon species was found in Chiang Mai (2014–2015) [32]; the dry season is longer than the wet season. However, in Songkhla (2019) [55], the wet season is longer than the dry season. The OC/EC ratio in Thailand is typically higher than 2.0, except in the wet season in Pathumtani. The ratios of OC/EC are usually used to diagnose the source of an organic aerosol [32,70]. However, the high OC/EC in many PM0.1 particles suggests that secondary organic carbon is vital in this area. The lower ratio represents the influence of local transportation in Thailand [24,25].
Unlike the OC/EC ratio, the char-EC/soot-EC ratio differs from each source; it is frequently possible to identify the sources [83]. Only two factors can affect the char/soot ratio: the primary emission source and particle deposition by scavenging. A higher proportion of char/soot (generally >1.0) is suggestive of biomass fires; char contributes to the total EC levels. In contrast, char/soot <1.0 suggests that emissions from diesel engines are an essential contributor to the total EC concentrations [32,84]. The Char-EC/Soot-EC ratios in nanoparticles in Thailand are almost constant and less than 1.0 in both the wet and dry seasons, suggesting that motor vehicles are a key source of PM0.1 particles in Thailand. However, only in Chiang Mai during the dry season, the Char-EC content and Char-EC/Soot-EC were increased and higher than 1.0 because of open biomass burning to smaller particles [32,55,70]. Therefore, the PM0.1 particles represent diesel engine emissions, although sensitive to biomass emissions in Thailand, e.g., the Chiang Mai area, which is recognized to have airborne particulate pollution from biomass burning for a long time [85,86]. Moreover, the increased Char-EC content and Char-EC/Soot-EC ratio should be studied in detail in future studies for the accuracy of carbonaceous nanoaerosols in Thailand and elsewhere.

2.4. PM0.1 Derived from Biomass Burning

In SEA, haze has occurred nearly every year during the dry season [85,86]. These haze episodes generated PM that was derived from biomass combustion in the past decade [24,33]. Forest fires and slash and burn in agricultural areas are typical methods for removing biomass residues in SEA [87]. Research reports addressed the high PM concentration that is released from open biomass fires in Thailand [86,88,89]. Hata et al. (2014) [51] reported, based on chamber experiments, that biomass fuel combustion releases around 80% of all sub-micron particles and nanoparticles of approximately 30% of the total particles. Similarly, open biomass fires during a haze episode in northern Thailand revealed that more than 60% of the total PM is smaller than PM1.0 [32]. The size distribution of PM released from open fires depends on fuel type, moisture content, and excess air during combustion [90,91].
Biomass burning is a significant contributor to the production of ambient particles. As reported by Hata et al. (2014) [51], in chamber experiments, biomass solid fuel combustion accounted for more than 30% of the biomass burning and that the particle mass concentration was smaller than <100 nm. However, in the atmospheric environment, PM0.1 particles are contained in the ambient atmosphere due to anthropogenic activities and natural sources or chemical processes. Therefore, determining the actual emission sources under ambient conditions is not an easy task. Phairuang et al. (2021) [53] reported on the source apportionment of PM0.1 particles in Bangkok. They found that around 10% of the ambient nanoparticles in Bangkok during haze episodes came from biomass fires. However, PM0.1 particles, primarily derived from motor vehicle emissions, are also strongly affected by forest fires in the north of Thailand [32]. Hence, this activity has an important influence on the quality of ambient air during the dry season. As a result, the main emission sources of PM0.1 are both natural and anthropogenic. Figure 1 shows the morphology of ambient nanoparticles from Chiang Mai, Thailand, as observed in scanning electron microscope (SEM) analysis [92]. The particles from near emission sources during strong biomass fires represent particles in the ultrafine mode (Dp < 100 nm).

3. Health Concerns of PM0.1 in Thailand

Smaller particles, especially nano-size particles, are recognized as being detrimental to human health due to their small size, chemical makeup, and the fact that they accumulate in ambient conditions [8]. Evidence collected in the past decade makes it clear that PM0.1 affects public health. The Health Effects Institute (HEI) [14] suggests that the PM0.1 data on health risk assessment are still an ongoing study and it cannot conclude or decide on policy making for the control of ambient PM0.1 worldwide. However, health risks, such as oxidative stress and inflammatory damage, may result from human exposure to atmospheric PM0.1 through inhalation [8,10].
In the same manner, studies of PM0.1 in Thailand make it clear that there are health effects from these particles. Only a few studies have appeared on health risk assessment from PM0.1 as related to the chemical composition of these particles. Chomanee et al. (2020) [26] reported on a health risk assessment of nanoparticle-bound PAHs in southern Thailand during a period of transboundary particulate pollution. It is known that the lower SEA suffers from the effects of large peat-land fires during the dry season, around July–September, almost every year. This research suggests that the health effects from carcinogenic PAHs during a strong haze period are higher than normal, by around 2–5 times. Public health concerns in this region should focus on smaller particles in some periods from cross-border pollution that depend on the intensity of emission sources, wind speed, wind direction, and meteorology during those periods.
Similarly, Phairuang et al. (2022) [28] reported on the year-long health effects of PM0.1-bound trace elements in southern Thailand in 2018. They found that the health risk from hazardous components is generally highly recognized during the pre-monsoon season. Toxic elements from peat-land fires that are transported from other sources to southern Thailand depend on the speed and direction of the wind. Cross-border particulate pollution must be investigated in more detail, with emphasis on the origin and health concerns during haze episodes in this region. During the normal period, the primary emission sources of PM0.1 are land transportation [25].
In other parts of Thailand, our knowledge of the health risks from PM0.1 related to the chemical components remains limited. Phairuang et al. (2021) [53] reported that the health risk assessment from PM0.1-bound metals in Bangkok, Thailand, was substantial during a smog haze period. PM0.1-bound elements in Bangkok differ with the season but are generally related to road transport emissions. It is well known that in the Bangkok Metropolitan Region air quality worsens during periods of heavy traffic congestion [32,47,49]. There is general agreement that the production of PM0.1 worldwide is derived from motor vehicles in urban areas [40,50]. Diesel and benzene engines are the primary sources of ambient nanoparticles in mega-cities [93,94]. However, open biomass burning, e.g., forest fires, crop waste, and grass burning, significantly contribute to PM0.1 during intense haze episodes in many countries [5,32]. Most studies have concluded that inhaled airborne PM0.1 has adverse effects on human health. Data of relationships between PM0.1 and sickness are limited. It appears that we are not fully aware of the life-threatening hazards of ambient NPs in air pollution from biomass fires on human health in Thailand.

4. Challenges in Studies of PM0.1 in Thailand

In the past decade, Thailand has been faced with particulate pollution almost yearly. In particular, in the dry season, emissions from open fires and meteorological conditions can temporarily affect the particle concentration [85,95]. Phairuang et al. (2019) [32] examined the influence of biomass fires on air quality in Thailand, i.e., Bangkok and Chiang Mai, in a case study of size-fractionated particulate matter ranging from small to nano-sized. The influence of biomass burning strongly affects ambient PM0.1 in Bangkok, although many reports have suggested that the main contribution of PM2.5 in BMR is from motor vehicles [47,49]. On the other hand, PM0.1 is ubiquitous in the atmospheric environment in the northern part of Thailand during the dry season, as in Chiang Mai, the economic city in the northern part of Thailand. This is a new challenge in the studies of biomass burning, especially crop waste burning and woodland fires in agricultural countries, to understand the production of ambient nanoparticles [5,32,55]. The apportionment of the sources of PM0.1 is very limited in Thailand due to the small amount of mass and chemical composition. Moreover, a recent study of particle size distribution in Bangkok by Panyametheekul et al. (2022) [96] found that the particle number concentration of samples collected from three locations in Bangkok revealed that up to 90% of the PM0.1 was produced in comparison with other sizes. Consequently, in the case of PM0.1, both the number and mass particle concentration are subjects that need to be examined in terms of air quality management in Thailand’s land based on heavy particulate pollution in the past decade.
It is generally assumed that PM0.1 particles are highly toxic substances compared to larger particles because they have a vast surface area per volume that can carry and absorb hazardous chemicals such as heavy metals, carbon components, and carcinogenic PAHs [8]. In the past decade, strong evidence has appeared to suggest that PM2.5 and PM10 induce human illness, including respiratory symptoms, cardiovascular effects, and chronic obstructive pulmonary disease (COPD), which contribute to mortality and morbidity [97,98,99,100]. This is especially true in northern Thailand, which experiences particulate pollution almost yearly. Many reports have revealed that the smoke haze episodes induce more people to visit hospitals in the north of Thailand [101,102]. However, there is no evidence of risks to health from nanoaerosols. Although the northern part of Thailand, during the dry season, has a high mass concentration of PM0.1 particles [32], the relationship and epidemiological survey of ultrafine particles and health effects still underestimate human public health due to insufficient information concerning the source, characteristics, and abundance of such small particles.

5. Option and Recommendations concerning PM0.1 in Thailand

5.1. Evaluation of PM0.1: Present Status and Characteristics, Comparison between Sites

Airborne particles can migrate over long distances and can cross the borders between countries and regions on a global scale. PM2.5 can be transported in the atmosphere for an extended period, change its properties via further chemical reactions [103,104], and can change into fine or coarse particles, known as secondary particles. The effectiveness of the secondary formation of particles suggests that it is more significant than primary formation in that they can contain both hazardous chemicals and are easily carried in the atmosphere [105,106]. For monitoring carbonaceous compounds in suburban areas compared to urban areas in Thailand, it was found that the average concentrations of ambient carbonaceous compounds in a suburban area (Klong Luang, Pathumtani, Thailand) were higher than that in an urban area (Bangkok Metropolitan Region (BMR)) [106,107].
However, information on the long-range transport of ambient nanoparticles continues to be limited. Collecting PM0.1 from cities in Thailand and other countries during a high smoke episode and comparing and examining cross borders among cities and countries are needed if we are to develop a better understanding of the impact of atmospheric PM0.1. Building a monitoring network through monitoring ambient nanoaerosols is a priority in studying PM0.1 in Thailand. Phairuang et al. (2019) [32] reported that the transport of ambient PM0.1 in Thailand can cover a distance of around 100–200 km. Nevertheless, Inerb et al. (2022) [25] reported that during intense forest fire episodes in lower southern Asia, the nanoparticles produced from peat-land fires could be transported around 800 km from Indonesia to the southern part of Thailand. High international collaboration and links between climate and air pollution policies should be compulsory to control small particles’ ambient air quality effects. Therefore, a monitoring network to discuss the contribution of near emission sources and possible transboundary transportation continues to be a challenge. There has only been one monitoring network to study ambient nanoaerosols in East and Southeast Asia, namely, the East Asia Nanoparticle Monitoring Network (EA-Nanonet). The EA-Nanonet was established in 2013 to monitor the emission of nanoparticles and their characteristics, transport, and behavior in many East and Southeast Asian countries, including Japan, China, Thailand, Vietnam, Malaysia, Indonesia, and Cambodia [108].

5.2. Information on PM0.1 Emission Sources

PM0.1 is a small particle that is produced both naturally and by humans, primarily from combustion processes and chemical reactions in the atmosphere [8,10]. In the past decade, nanoparticles were generally produced from diesel engines and contained a high level of carbon and metal. The emission inventory (EI) of PM0.1 particles and chemical relationships has not been extensively studied in Thailand. However, some information on emission factors (EF) from solid biomass burning in Thailand has appeared [90,91]. Interestingly, other emission sources, e.g., coal combustion, motor vehicles, power plants, and non-combustion sources, are still lacking in Thailand. Moreover, particle number concentration (PNC), which usually measures a smaller particle, is still lacking in Thailand. There is a vast gap in emission inventories due to a lack of EFs and other default values that are needed to calculate the accuracy of EI.

5.3. Summary of Facts on PM0.1 for Policy Making

Ambient PM0.1, both number and mass concentration in the ambient air, comes from various sources and influences human health via personal exposure. An inventory of PM0.1 should be seriously addressed. This is scientific information to support policy makers in the near future. It cannot be ignored that the higher the concentration of small particles is, the higher the amount of heavy metal or other toxic materials will be. Developing a standard or even guidelines for a reasonable value for public health is needed. Further, we need to understand the origins, transportation, transformation (new particles), and effects on public health of ambient PM0.1 to identify appropriate procedures to resolve the problem sustainably. The production of new particulate aerosols possibly increases with an increase in the concentration of UFPs under conditions of high relative humidity (RH) above 70%, especially in tropical countries. UFPs should then be an indicator to convince decision makers of the need for policy making. Summarizing ambient nanoparticles will help develop clean air policies in Thailand.

6. Conclusions

The study of ambient PM0.1 particles in Thailand has been ongoing for a decade and is focused on particle mass concentration, the characteristics of the carbon contained by these particles, and the health effects of these particles. The health-related effects of ambient PM0.1 have not resulted in support for air quality management in Thailand and also most of the Asian countries because, unlike coarse and fine particles, of a lack of this type of information. Evaluations of PM0.1, the present status, characteristics, and comparison between sites play an important role in atmospheric systems. Local sources and transboundary ultrafine particulate pollution should be considered for future studies. Other chemical substances in PM0.1 have not been studied extensively in Thailand. They could, however, also be an essential factor in air pollution, which merits future study in a more detailed investigation into the nature and health-related effects. As a result, summarizing factual information concerning PM0.1 for policy making will fill the gap until more in-depth studies of ambient particulate matter can be carried out. This promises to have a long-term impact on achieving a blue sky over Thailand through coherent policies and management.


This work was financially supported by the Office of the Permanent Secretary, Ministry Higher Education, Science, Research and Innovation in Thailand (Grant No. RGNS 63-253). Moreover, this research work was partially supported by JICA-JST SATREPS (Grant No. JPMJSA2102), JSPS KAKENHI 21H03618, and Sumitomo Foundation, Japan.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.


The authors acknowledge the contribution of members of the East Asia Nanoparticle Monitoring Network (EA-Nanonet) for field sampling and laboratory work. Moreover, the authors also wish to thank Milton S. Feather for improving the English in this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Li, Z.; Tang, Y.; Song, X.; Lazar, L.; Li, Z.; Zhao, J. Impact of ambient PM2.5 on adverse birth outcome and potential molecular mechanism. Ecotoxicol. Environ. Saf. 2019, 169, 248–254. [Google Scholar] [CrossRef] [PubMed]
  2. Yang, L.; Zhang, H.; Zhang, X.; Xing, W.; Wang, Y.; Bai, P.; Zhang, L.; Hayakawa, K.; Toriba, A.; Tang, N. Exposure to atmospheric particulate matter-bound polycyclic aromatic hydrocarbons and their health effects: A review. Int. J. Environ. Res. Public Health 2021, 18, 2177. [Google Scholar] [CrossRef] [PubMed]
  3. Lee, D.; Wang, S.Y.S.; Zhao, L.; Kim, H.C.; Kim, K.; Yoon, J.H. Long-term increase in atmospheric stagnant conditions over northeast Asia and the role of greenhouse gases-driven warming. Atmos. Environ. 2020, 241, 117772. [Google Scholar] [CrossRef]
  4. Bulot, F.M.; Johnston, S.J.; Basford, P.J.; Easton, N.H.; Apetroaie-Cristea, M.; Foster, G.L.; Loxham, M. Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment. Sci. Rep. 2019, 9, 7497. [Google Scholar] [CrossRef] [PubMed]
  5. Thuy, N.T.T.; Dung, N.T.; Sekiguchi, K.; Thuy, L.B.; Hien, N.T.T.; Yamaguchi, R. Mass concentrations and carbonaceous compositions of PM0.1, PM2.5, and PM10 at Hanoi, Vietnam urban locations. Aerosol Air Qual. Res. 2018, 18, 1591–1605. [Google Scholar] [CrossRef]
  6. Skuland, T.; Grytting, V.S.; Låg, M.; Jørgensen, R.B.; Snilsberg, B.; Leseman, D.L.A.C.; Kubátová, A.; Emond, J.; Cassee, F.R.; Holme, J.A.; et al. Road tunnel-derived coarse, fine and ultrafine particulate matter: Physical and chemical characterization and pro-inflammatory responses in human bronchial epithelial cells. Part. Fibre Toxicol. 2022, 19, 45. [Google Scholar] [CrossRef]
  7. Deng, L.; Hao, C.; Luo, Y.; Yang, P.; Wu, B. Effect of air and exhaust gas dilutions on ultra-fine particulate emissions in different combustion modes. Sci. Total Environ. 2022, 843, 156865. [Google Scholar] [CrossRef]
  8. Schraufnagel, D.E. The health effects of ultrafine particles. Exp. Mol. Med. 2020, 52, 311–317. [Google Scholar] [CrossRef] [PubMed]
  9. Phairuang, W.; Amin, M.; Hata, M.; Furuuchi, M. Airborne Nanoparticles (PM0.1) in Southeast Asian Cities: A Review. Sustainability 2022, 14, 10074. [Google Scholar] [CrossRef]
  10. Kwon, H.S.; Ryu, M.H.; Carlsten, C. Ultrafine particles: Unique physicochemical properties relevant to health and disease. Exp. Mol. Med. 2020, 52, 318–328. [Google Scholar] [CrossRef]
  11. Oberdörster, G.; Sharp, Z.; Atudorei, V.; Elder, A.; Gelein, R.; Kreyling, W.; Cox, C. Translocation of inhaled ultrafine particles to the brain. Inhal. Toxicol. 2004, 16, 437–445. [Google Scholar] [CrossRef] [PubMed]
  12. Yang, M.; Jalava, P.; Hakkarainen, H.; Roponen, M.; Leskinen, A.; Komppula, M.; Dong, G.-P.; Lao, X.-Q.; Wu, Q.-Z.; Xu, S.-L.; et al. Fine and ultrafine airborne PM influence inflammation response of young adults and toxicological responses in vitro. Sci. Total Environ. 2022, 836, 155618. [Google Scholar] [CrossRef] [PubMed]
  13. Marval, J.; Tronville, P. Ultrafine particles: A review about their health effects, presence, generation, and measurement in indoor environments. Build. Environ. 2022, 2022, 108992. [Google Scholar] [CrossRef]
  14. HEI. Understanding the health effects of ambient ultrafine particles. In HEI Perspectives HEI Review Panel on Ultrafine Particles; Health Effects Institute: Boston, MA, USA, 2013. [Google Scholar]
  15. Vohra, K.; Vodonos, A.; Schwartz, J.; Marais, E.A.; Sulprizio, M.P.; Mickley, L.J. Global mortality from outdoor fine particle pollution generated by fossil fuel combustion: Results from GEOS-Chem. Environ. Res. 2021, 195, 110754. [Google Scholar] [CrossRef]
  16. Chen, Q.; Wang, Q.; Xu, B.; Xu, Y.; Ding, Z.; Sun, H. Air pollution and cardiovascular mortality in Nanjing, China: Evidence highlighting the roles of cumulative exposure and mortality displacement. Chemosphere 2021, 265, 129035. [Google Scholar] [CrossRef]
  17. Nakharutai, N.; Traisathit, P.; Thongsak, N.; Supasri, T.; Srikummoon, P.; Thumronglaohapun, S.; Hemwan, P.; Chitapanarux, I. Impact of Residential Concentration of PM2.5 Analyzed as Time-Varying Covariate on the Survival Rate of Lung Cancer Patients: A 15-Year Hospital-Based Study in Upper Northern Thailand. Int. J. Environ. Res. Public Health 2022, 19, 4521. [Google Scholar] [CrossRef]
  18. Thiankhaw, K.; Chattipakorn, N.; Chattipakorn, S.C. PM2.5 exposure in association with AD-related neuropathology and cognitive outcomes. Environ. Pollut. 2022, 292, 118320. [Google Scholar] [CrossRef]
  19. Arias-Pérez, R.D.; Taborda, N.A.; Gómez, D.M.; Narvaez, J.F.; Porras, J.; Hernandez, J.C. Inflammatory effects of particulate matter air pollution. Environ. Sci. Pollut. Res. 2020, 27, 42390–42404. [Google Scholar] [CrossRef]
  20. Kim, K.H.; Kabir, E.; Kabir, S. A review on the human health impact of airborne particulate matter. Environ. Int. 2015, 74, 136–143. [Google Scholar] [CrossRef]
  21. Schraufnagel, D.E.; Balmes, J.R.; Cowl, C.T.; De Matteis, S.; Jung, S.H.; Mortimer, K.; Perez-Padilla, R.; Rice, M.B.; Riojas-Rodriguez, H.; Sood, A.; et al. Air pollution and noncommunicable diseases: A review by the Forum of International Respiratory Societies’ Environmental Committee, Part 2: Air pollution and organ systems. Chest 2019, 155, 417–426. [Google Scholar] [CrossRef]
  22. Shao, L.Y.; Wang, W.H.; Xing, J.P.; Li, W.J.; Niu, H.Y.; Hou, C.; Tang, S.S. Physicochemical characteristics and effects of airborne particles: Research progress and prospects. Earth Sci. 2018, 43, 1691–1708. [Google Scholar]
  23. Han, Y.P.; Li, L.; Wang, Y.; Ma, J.W.; Li, P.Y.; Han, C.; Liu, J.X. Composition, dispersion, and health risks of bioaerosols in wastewater treatment plants: A review. Front. Environ. Sci. Eng. 2021, 15, 38. [Google Scholar] [CrossRef]
  24. Boongla, Y.; Chanonmuang, P.; Hata, M.; Furuuchi, M.; Phairuang, W. The characteristics of carbonaceous particles down to the nanoparticle range in Rangsit city in the Bangkok Metropolitan Region, Thailand. Environ. Pollut. 2021, 272, 115940. [Google Scholar] [CrossRef] [PubMed]
  25. Inerb, M.; Phairuang, W.; Paluang, P.; Hata, M.; Furuuchi, M.; Wangpakapattanawong, P. Carbon and Trace Element Compositions of Total Suspended Particles (TSP) and Nanoparticles (PM0.1) in Ambient Air of Southern Thailand and Characterization of Their Sources. Atmosphere 2022, 13, 626. [Google Scholar] [CrossRef]
  26. Chomanee, J.; Thongboon, K.; Tekasakul, S.; Furuuchi, M.; Dejchanchaiwong, R.; Tekasakul, P. Physicochemical and toxicological characteristics of nanoparticles in aerosols in southern Thailand during recent haze episodes in lower southeast Asia. J. Environ. Sci. 2020, 94, 72–80. [Google Scholar] [CrossRef] [PubMed]
  27. Cush, K.; Koh, K.; Saikawa, E. Impacts of biomass and garbage burning on air quality in South/Southeast Asia. In Biomass Burning in South and Southeast Asia; CRC Press: Boca Raton, FL, USA, 2021; pp. 3–20. [Google Scholar]
  28. Phairuang, W.; Inerb, M.; Hata, M.; Furuuchi, M. Characteristics of trace elements bound to ambient nanoparticles (PM0.1) and a health risk assessment in southern Thailand. J. Hazard. Mater. 2022, 425, 127986. [Google Scholar] [CrossRef]
  29. Huang, K.; Fu, J.S.; Lin, N.H.; Wang, S.H.; Dong, X.; Wang, G. Superposition of Gobi dust and Southeast Asian biomass burning: The effect of multisource long-range transport on aerosol optical properties and regional meteorology modification. J. Geophys. Res. Atmos. 2019, 124, 9464–9483. [Google Scholar] [CrossRef]
  30. Xing, L.; Bei, N.; Guo, J.; Wang, Q.; Liu, S.; Han, Y.; Pongpiachan, S.; Li, G. Impacts of biomass burning in peninsular Southeast Asia on PM2.5 concentration and ozone formation in Southern China During Springtime—A case study. J. Geophys. Res. Atmos. 2021, 126, e2021JD034908. [Google Scholar] [CrossRef]
  31. Zhang, L.; Ding, S.; Qian, W.; Zhao, A.; Zhao, S.; Yang, Y.; Weng, G.; Tao, M.; Chen, H.; Zhao, S.; et al. The Impact of Long-Range Transport of Biomass Burning Emissions in Southeast Asia on Southern China. Atmosphere 2022, 13, 1029. [Google Scholar] [CrossRef]
  32. Phairuang, W.; Suwattiga, P.; Chetiyanukornkul, T.; Hongtieab, S.; Limpaseni, W.; Ikemori, F.; Hata, M.; Furuuchi, M. The influence of the open burning of agricultural biomass and forest fires in Thailand on the carbonaceous components in size-fractionated particles. Environ. Pollut. 2019, 247, 238–247. [Google Scholar] [CrossRef]
  33. Adam, M.G.; Tran, P.T.; Bolan, N.; Balasubramanian, R. Biomass burning-derived airborne particulate matter in Southeast Asia: A critical review. J. Hazard. Mater. 2021, 407, 124760. [Google Scholar] [CrossRef]
  34. Amnuaylojaroen, T.; Inkom, J.; Janta, R.; Surapipith, V. Long-range transport of southeast asian pm2.5 pollution to northern Thailand during high biomass burning episodes. Sustainability 2020, 12, 10049. [Google Scholar] [CrossRef]
  35. Othman, M.; Latif, M.T.; Hamid, H.H.A.; Uning, R.; Khumsaeng, T.; Phairuang, W.; Lung, S.C.C. Spatial–temporal variability and health impact of particulate matter during a 2019–2020 biomass burning event in Southeast Asia. Sci. Rep. 2022, 12, 7630. [Google Scholar] [CrossRef] [PubMed]
  36. Vejpongsa, I.; Suvachittanont, S.; Klinklan, N.; Thongyen, T.; Veres, M.; Szymanski, W.W. Deliberation between PM1 and PM2.5 as air quality indicators based on comprehensive characterization of urban aerosols in Bangkok, Thailand. Particuology 2017, 35, 1–9. [Google Scholar] [CrossRef]
  37. Nuthammachot, N.; Phairuang, W.; Stratoulias, D. Estimation of carbon emission in the ex-mega rice project, Indonesia based on SAR satellite images. Appl. Ecol. Environ. Res. 2019, 17, 2489–2499. [Google Scholar] [CrossRef]
  38. Amin, M.; Putri, R.M.; Handika, R.A.; Ullah, A.; Goembira, F.; Phairuang, W.; Ikemori, F.; Hata, M.; Tekasakul, P.; Furuuchi, M. Size-Segregated Particulate Matter Down to PM0.1 and Carbon Content during the Rainy and Dry Seasons in Sumatra Island, Indonesia. Atmosphere 2021, 12, 1441. [Google Scholar] [CrossRef]
  39. Putri, R.M.; Amin, M.; Suciari, T.F.; Faisal, M.A.F.; Auliani, R.; Ikemori, F.; Wada, M.; Hata, M.; Tekasakul, P.; Furuuchi, M. Site-specific variation in mass concentration and chemical components in ambient nanoparticles (PM0.1) in North Sumatra Province-Indonesia. Atmos. Pollut. Res. 2021, 12, 101062. [Google Scholar] [CrossRef]
  40. De Jesus, A.L.; Rahman, M.M.; Mazaheri, M.; Thompson, H.; Knibbs, L.D.; Jeong, C.; Evans, G.; Nei, W.; Ding, A.; Qiao, L.; et al. Ultrafine particles and PM2.5 in the air of cities around the world: Are they representative of each other? Environ. Int. 2019, 129, 118–135. [Google Scholar] [CrossRef]
  41. Pollution Control Department. National Thailand Ambient Air Quality Standards. 2022. Available online: (accessed on 1 December 2022).
  42. World Health Organization. WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide. World Health Organization. 2021. Available online: (accessed on 1 December 2022).
  43. CEN/TS 16976:2016; Ambient Air-Determination of the Particle Number Concentration of Atmospheric Aerosol. European Committee for Standardization: Brussels, Belgium, 2016.
  44. Giechaskiel, B.; Lahde, T.; Suarez-Bertoa, R.; Clairotte, M.; Grigoratos, T.; Zardini, A.; Perujo, A.; Martini, G. Particle number measurements in the European legislation and future JRC activities. Combust. Engines 2018, 174, 3–16. [Google Scholar] [CrossRef]
  45. Hinds, W.C.; Zhu, Y. Aerosol Technology: Properties, Behavior, and Measurement of Airborne Particles; John Wiley & Sons: Hoboken, NJ, USA, 2022. [Google Scholar]
  46. Chavanaves, S.; Fantke, P.; Limpaseni, W.; Attavanich, W.; Panyametheekul, S.; Gheewala, S.H.; Prapaspongsa, T. Health impacts and costs of fine particulate matter formation from road transport in Bangkok Metropolitan Region. Atmos. Pollut. Res. 2021, 12, 101191. [Google Scholar] [CrossRef]
  47. ChooChuay, C.; Pongpiachan, S.; Tipmanee, D.; Suttinun, O.; Deelaman, W.; Wang, Q.; Xing, L.; Li, G.; Han, Y.; Palakun, J.; et al. Impacts of PM2.5 sources on variations in particulate chemical compounds in ambient air of Bangkok, Thailand. Atmos. Pollut. Res. 2020, 11, 1657–1667. [Google Scholar] [CrossRef]
  48. Kanjanasiranont, N.; Butburee, T.; Peerakiatkhajohn, P. Characteristics of PM10 Levels Monitored in Bangkok and Its Vicinity Areas, Thailand. Atmosphere 2022, 13, 239. [Google Scholar] [CrossRef]
  49. Narita, D.; Oanh, N.; Sato, K.; Huo, M.; Permadi, D.; Chi, N.; Ratanajaratroj, T.; Pawarmart, I. Pollution characteristics and policy actions on fine particulate matter in a growing Asian economy: The case of Bangkok Metropolitan Region. Atmosphere 2019, 10, 227. [Google Scholar] [CrossRef]
  50. Ding, X.; Kong, L.; Du, C.; Zhanzakova, A.; Wang, L.; Fu, H.; Chen, J.; Yang, X.; Cheng, T. Long-range and regional transported size-resolved atmospheric aerosols during summertime in urban Shanghai. Sci. Total Environ. 2017, 583, 334–343. [Google Scholar] [CrossRef]
  51. Hata, M.; Chomanee, J.; Thongyen, T.; Bao, L.; Tekasakul, S.; Tekasakul, P.; Otani, Y.; Furuuchi, M. Characteristics of nanoparticles emitted from burning of biomass fuels. J. Environ. Sci. 2014, 26, 1913–1920. [Google Scholar] [CrossRef]
  52. Zhao, T.; Hongtieab, S.; Hata, M.; Furuuchi, M.; Dong, S.; Phairuang, W.; Ge, H.; Zhang, T. Characteristics comparison of ambient Nano-particles in Asian cities. In Proceedings of the 33rd Symposium of Japan Association of Aerosol Science and Technology (JAAST) Annual Meeting, Osaka, Japan, 31 August–2 September 2016. [Google Scholar]
  53. Phairuang, W.; Suwattiga, P.; Hongtieab, S.; Inerb, M.; Furuuchi, M.; Hata, M. Characteristics, sources, and health risks of ambient nanoparticles (PM0.1) bound metal in Bangkok, Thailand. Atmos. Environ. X 2021, 12, 100141. [Google Scholar] [CrossRef]
  54. Phairuang, W.; Hongtieab, S.; Suwattiga, P.; Furuuchi, M.; Hata, M. Atmospheric Ultrafine Particulate Matter (PM0.1)-Bound Carbon Composition in Bangkok, Thailand. Atmosphere 2022, 13, 1676. [Google Scholar] [CrossRef]
  55. Phairuang, W.; Inerb, M.; Furuuchi, M.; Hata, M.; Tekasakul, S.; Tekasakul, P. Size-fractionated carbonaceous aerosols down to PM0.1 in southern Thailand: Local and long-range transport effects. Environ. Pollut. 2020, 260, 114031. [Google Scholar] [CrossRef]
  56. Chomanee, J.; Tekasakul, S.; Tekasakul, P.; Furuuchi, M. Effect of irradiation energy and residence time on decomposition efficiency of polycyclic aromatic hydrocarbons (PAHs) from rubber wood combustion emission using soft X-rays. Chemosphere 2018, 210, 417–423. [Google Scholar] [CrossRef]
  57. Office of Agricultural Economics (OAE). Agricultural Statistic in Thailand, 2019; OAE: Bangkok, Thailand, 2020. [Google Scholar]
  58. Phairuang, W.; Tekasakul, P.; Hata, M.; Tekasakul, S.; Chomanee, J.; Otani, Y.; Furuuchi, M. Estimation of air pollution from ribbed smoked sheet rubber in Thailand exports to Japan as a pre-product of tires. Atmos. Pollut. Res. 2019, 10, 642–650. [Google Scholar] [CrossRef]
  59. Samiksha, S.; Kumar, S.; Sunder Raman, R. Two-year record of carbonaceous fraction in ambient PM2.5 over a forested location in central India: Temporal characteristics and estimation of secondary organic carbon. Air Qual. Atmos. Health 2021, 14, 473–480. [Google Scholar] [CrossRef]
  60. Zioła, N.; Banasik, K.; Jabłońska, M.; Janeczek, J.; Błaszczak, B.; Klejnowski, K.; Mathews, B. Seasonality of the Airborne Ambient Soot Predominant Emission Sources Determined by Raman Microspectroscopy and Thermo-Optical Method. Atmosphere 2021, 12, 768. [Google Scholar] [CrossRef]
  61. Rana, A.; Jia, S.; Sarkar, S. Black carbon aerosol in India: A comprehensive review of current status and future prospects. Atmos. Res. 2019, 218, 207–230. [Google Scholar] [CrossRef]
  62. Zhang, Z.W.; Shahpoury, P.; Zhang, W.; Harner, T.; Huang, L. A new method for measuring airborne elemental carbon using PUF disk passive samplers. Chemosphere 2022, 299, 134323. [Google Scholar] [CrossRef]
  63. Pani, S.K.; Lee, C.T.; Griffith, S.M.; Lin, N.H. Humic-like substances (HULIS) in springtime aerosols at a high-altitude background station in the western North Pacific: Source attribution, abundance, and light-absorption. Sci. Total Environ. 2022, 809, 151180. [Google Scholar] [CrossRef]
  64. Tang, J.; Wang, J.; Zhong, G.; Jiang, H.; Mo, Y.; Zhang, B.; Geng, X.; Chen, Y.; Tang, J.; Tian, C.; et al. Measurement report: Long-emission-wavelength chromophores dominate the light absorption of brown carbon in aerosols over Bangkok: Impact from biomass burning. Atmos. Chem. Phys. 2021, 21, 11337–11352. [Google Scholar] [CrossRef]
  65. Wonaschütz, A.; Hitzenberger, R.; Bauer, H.; Pouresmaeil, P.; Klatzer, B.; Caseiro, A.; Buxbaum, H. Application of the integrating sphere method to separate the contributions of brown and black carbon in atmospheric aerosols. Environ. Sci. Technol. 2009, 43, 1141–1146. [Google Scholar]
  66. Cui, M.; Xu, Y.; Yu, B.; Yan, C.; Li, J.; Zheng, M.; Chen, Y. Experimental simulation characterizes carbonaceous matter emitted from residential coal and biomass combustion. Atmos. Environ. 2023, 293, 119447. [Google Scholar] [CrossRef]
  67. Malmborg, V.; Eriksson, A.; Gren, L.; Török, S.; Shamun, S.; Novakovic, M.; Zhang, Y.; Kook, S.; Tunér, M.; Bengtsson, P.-E.; et al. Characteristics of BrC and BC emissions from controlled diffusion flame and diesel engine combustion. Aerosol Sci. Technol. 2021, 55, 769–784. [Google Scholar] [CrossRef]
  68. Runa, F.; Islam, M.; Jeba, F.; Salam, A. Light absorption properties of brown carbon from biomass burning emissions. Environ. Sci. Pollut. Res. 2022, 29, 21012–21022. [Google Scholar] [CrossRef]
  69. Hallquist, M.; Wenger, J.C.; Baltensperger, U.; Rudich, Y.; Simpson, D.; Claeys, M.; Dommen, J.; Donahue, N.M.; George, C.; Goldstein, A.H.; et al. The formation, properties, and impact of secondary organic aerosol: Current and emerging issues. Atmos. Chem. Phys. 2009, 9, 5155–5236. [Google Scholar] [CrossRef]
  70. Amin, M.; Handika, R.A.; Putri, R.M.; Phairuang, W.; Hata, M.; Tekasakul, P.; Furuuchi, M. Size-segregated particulate mass and carbonaceous components in roadside and riverside environments. Appl. Sci. 2021, 11, 10214. [Google Scholar] [CrossRef]
  71. Houghton, J.T.; Ding, Y.D.J.G.; Griggs, D.J.; Noguer, M.; van der Linden, P.J.; Dai, X.; Maskell, K.; Johnson, C.A. (Eds.) Climate Change 2001: The Scientific Basis: Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2001. [Google Scholar]
  72. Kelesidis, G.A.; Bruun, C.A.; Pratsinis, S.E. The impact of organic carbon on soot light absorption. Carbon 2021, 172, 742–749. [Google Scholar] [CrossRef]
  73. Gustafsson, Ö.; Ramanathan, V. Convergence on climate warming by black carbon aerosols. Proc. Natl. Acad. Sci. USA 2016, 113, 4243–4245. [Google Scholar] [CrossRef] [PubMed]
  74. Irei, S.; Takami, A.; Sadanaga, Y.; Nozoe, S.; Yonemura, S.; Bandow, H.; Yokouchi, Y. Photochemical age of air pollutants, ozone, and secondary organic aerosol in transboundary air observed on Fukue Island, Nagasaki, Japan. Atmos. Chem. Phys. 2016, 16, 4555–4568. [Google Scholar] [CrossRef]
  75. Han, Y.; Chen, Y.; Feng, Y.; Shang, Y.; Li, J.; Li, Q.; Chen, J. Existence and formation pathways of high-and low-maturity elemental carbon from solid fuel combustion by a time-resolved study. Environ. Sci. Technol. 2022, 56, 2551–2561. [Google Scholar] [CrossRef]
  76. Falk, J.; Korhonen, K.; Malmborg, V.B.; Gren, L.; Eriksson, A.C.; Karjalainen, P.; Markkula, L.; Bengtsson, P.-E.; Virtanen, A.; Svenningsson, B.; et al. Immersion freezing ability of freshly emitted soot with various physico-chemical characteristics. Atmosphere 2021, 12, 1173. [Google Scholar] [CrossRef]
  77. Zhang, Y.; Peng, Y.; Song, W.; Zhang, Y.L.; Ponsawansong, P.; Prapamontol, T.; Wang, Y. Contribution of brown carbon to the light absorption and radiative effect of carbonaceous aerosols from biomass burning emissions in Chiang Mai, Thailand. Atmos. Environ. 2021, 260, 118544. [Google Scholar] [CrossRef]
  78. Singh, G.K.; Choudhary, V.; Rajeev, P.; Paul, D.; Gupta, T. Understanding the origin of carbonaceous aerosols during periods of extensive biomass burning in northern India. Environ. Pollut. 2021, 270, 116082. [Google Scholar] [CrossRef]
  79. Tao, J.; Zhang, Z.; Zhang, L.; Huang, D.; Wu, Y. Quantifying the relative importance of major tracers for fine particles released from biofuel combustion in households in the rural North China Plain. Environ. Pollut. 2021, 268, 115764. [Google Scholar] [CrossRef]
  80. Yang, H.H.; Dhital, N.B.; Wang, L.C.; Hsieh, Y.S.; Lee, K.T.; Hsu, Y.T.; Huang, S.C. Chemical characterization of fine particulate matter in gasoline and diesel vehicle exhaust. Aerosol Air Qual. Res. 2019, 19, 1349–1449. [Google Scholar] [CrossRef]
  81. Thumanu, K.; Pongpiachan, S.; Ho, K.F.; Lee, S.C.; Sompongchaiyakul, P. Characterization of organic functional groups, water-soluble ionic species and carbonaceous compounds in PM10 from various emission sources in Songkhla Province, Thailand. WIT Trans. Ecol. Environ. 2009, 123, 295–306. [Google Scholar]
  82. Saarikoski, S.; Timonen, H.; Saarnio, K.; Aurela, M.; Järvi, L.; Keronen, P.; Kerminen, V.-M.; Hillamo, R. Sources of organic carbon in fine particulate matter in northern European urban air. Atmos. Chem. Phys. 2008, 8, 6281–6295. [Google Scholar] [CrossRef]
  83. Guo, Y. Carbonaceous aerosol composition over northern China in spring 2012. Environ. Sci. Pollut. Res. 2015, 22, 10839–10849. [Google Scholar] [CrossRef]
  84. Han, Y.M.; Chen, L.W.; Huang, R.J.; Chow, J.C.; Watson, J.G.; Ni, H.Y.; Liu, S.X.; Fung, K.K.; Shen, Z.X.; Wei, C.; et al. Carbonaceous aerosols in megacity Xi’an, China: Implications for comparison of thermal/optical protocols. Atmos. Environ. 2016, 132, 58–68. [Google Scholar] [CrossRef]
  85. Moran, J.; Nasuwan, C.; Poocharoen, O.O. A review of the haze problem in Northern Thailand and policies to combat it. Environ. Sci. Policy 2019, 97, 1–15. [Google Scholar] [CrossRef]
  86. Phairuang, W.; Hata, M.; Furuuchi, M. Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand. J. Environ. Sci. 2017, 52, 85–97. [Google Scholar] [CrossRef]
  87. Janta, R.; Sekiguchi, K.; Yamaguchi, R.; Sopajaree, K.; Plubin, B.; Chetiyanukornkul, T. Spatial and temporal variations of atmospheric PM10 and air pollutants concentration in upper Northern Thailand during 2006–2016. Appl. Sci. Eng. Prog. 2020, 13, 256–267. [Google Scholar] [CrossRef]
  88. Punsompong, P.; Pani, S.K.; Wang, S.H.; Pham, T.T.B. Assessment of biomass-burning types and transport over Thailand and the associated health risks. Atmos. Environ. 2021, 247, 118176. [Google Scholar] [CrossRef]
  89. Vongruang, P.; Pimonsree, S. Biomass burning sources and their contributions to PM10 concentrations over countries in mainland Southeast Asia during a smog episode. Atmos. Environ. 2020, 228, 117414. [Google Scholar] [CrossRef]
  90. Samae, H.; Tekasakul, S.; Tekasakul, P.; Furuuchi, M. Emission factors of ultrafine particulate matter (PM < 0.1 μm) and particle-bound polycyclic aromatic hydrocarbons from biomass combustion for source apportionment. Chemosphere 2021, 262, 127846. [Google Scholar] [PubMed]
  91. Samae, H.; Tekasakul, S.; Tekasakul, P.; Phairuang, W.; Furuuchi, M.; Hongtieab, S. Particle-bound organic and elemental carbons for source identification of PM< 0.1 µm from biomass combustion. J. Environ. Sci. 2022, 113, 385–393. [Google Scholar]
  92. Phairuang, W.; Inerb, M.; Hata, M.; Furuuchi, M. A Review of Ambient Nanoparticles (PM0.1) in South East Asian Cities: Biomass and Fossil Burning Impacts. Available online: (accessed on 1 December 2022).
  93. Kumar, P.; Morawska, L.; Birmili, W.; Paasonen, P.; Hu, M.; Kulmala, M.; Harrison, R.M.; Norford, L.; Britter, R. Ultrafine particles in cities. Environ. Int. 2014, 66, 1–10. [Google Scholar] [CrossRef] [PubMed]
  94. Kumar, P.; Pirjola, L.; Ketzel, M.; Harrison, R.M. Nanoparticle emissions from 11 non-vehicle exhaust sources–a review. Atmos. Environ. 2013, 67, 252–277. [Google Scholar] [CrossRef]
  95. Kliengchuay, W.; Worakhunpiset, S.; Limpanont, Y.; Meeyai, A.C.; Tantrakarnapa, K. Influence of the meteorological conditions and some pollutants on PM10 concentrations in Lamphun, Thailand. J. Environ. Health Sci. Eng. 2021, 19, 237–249. [Google Scholar] [CrossRef]
  96. Panyametheekul, S.; Kangwansupamonkon, W.; Anuchitchanchai, O.; Pongkiatkul, P. Final Report “Research Program on Integrated Technology for Mitigating PM2.5: A Case Study in Bangkok Metropolitan Region (BMR)”. National Research Council Fund. 2022. Available online: (accessed on 1 December 2022).
  97. Ahmad, M.; Manjantrarat, T.; Rattanawongsa, W.; Muensri, P.; Saenmuangchin, R.; Klamchuen, A.; Aueviriyavit, S.; Sukrak, K.; Kangwansupamonkon, W.; Panyametheekul, S. Chemical Composition, Sources, and Health Risk Assessment of PM2.5 and PM10 in Urban Sites of Bangkok, Thailand. Int. J. Environ. Res. Public Health 2022, 19, 14281. [Google Scholar] [CrossRef] [PubMed]
  98. Fold, N.R.; Allison, M.R.; Wood, B.C.; Thao, P.T.; Bonnet, S.; Garivait, S.; Kamens, R.; Pengjan, S. An assessment of annual mortality attributable to ambient PM2.5 in Bangkok, Thailand. Int. J. Environ. Res. Public Health 2020, 17, 7298. [Google Scholar] [CrossRef]
  99. Pothirat, C.; Chaiwong, W.; Liwsrisakun, C.; Bumroongkit, C.; Deesomchok, A.; Theerakittikul, T.; Limsukon, A.; Tajarernmuang, P.; Phetsuk, N. The short-term associations of particular matters on non-accidental mortality and causes of death in Chiang Mai, Thailand: A time series analysis study between 2016–2018. Int. J. Environ. Health Res. 2021, 31, 538–547. [Google Scholar] [CrossRef]
  100. Thao, N.N.L.; Pimonsree, S.; Prueksakorn, K.; Thao, P.T.B.; Vongruang, P. Public health and economic impact assessment of PM2.5 from open biomass burning over countries in mainland Southeast Asia during the smog episode. Atmos. Pollut. Res. 2022, 13, 101418. [Google Scholar] [CrossRef]
  101. Uttajug, A.; Ueda, K.; Oyoshi, K.; Honda, A.; Takano, H. Association between PM10 from vegetation fire events and hospital visits by children in upper northern Thailand. Sci. Total Environ. 2021, 764, 142923. [Google Scholar] [CrossRef]
  102. Uttajug, A.; Ueda, K.; Seposo, X.T.; Honda, A.; Takano, H. Effect of a vegetation fire event ban on hospital visits for respiratory diseases in Upper Northern Thailand. Int. J. Epidemiol. 2022, 51, 514–524. [Google Scholar] [CrossRef] [PubMed]
  103. Dahari, N.; Muda, K.; Latif, M.T.; Hussein, N. Studies of atmospheric PM2.5 and its inorganic water-soluble ions and trace elements around Southeast Asia: A review. Asia-Pac. J. Atmos. Sci. 2021, 57, 361–385. [Google Scholar] [CrossRef]
  104. Tham, J.; Sarkar, S.; Jia, S.; Reid, J.S.; Mishra, S.; Sudiana, I.M.; Swarup, S.; Ong, C.N.; Liya, E.Y. Impacts of peat-forest smoke on urban PM2.5 in the Maritime Continent during 2012–2015: Carbonaceous profiles and indicators. Environ. Pollut. 2019, 248, 496–505. [Google Scholar] [CrossRef] [PubMed]
  105. Feng, X.L.; Sfao, L.Y.; Xi, C.X.; Jones, T.; Zhang, D.Z.; Beru Be, K. Particle-induced oxidative damage by indoor size-segregated particulate matter from coal-burning homes in the Xuanwei lung cancer epidemic area, Yunan Province, China. Chemosphere 2020, 256, 127058. [Google Scholar] [CrossRef] [PubMed]
  106. Huo, M.; Sato, K.; Kim Oanh, N.T.; Mettasithikorn, M.; Leamlaem, M.; Permadi, D.A.; Narita, D.; Garivait, H.; Laogul, W.; Akimoto, H. Chemical characteristics and deposition amounts of carbonaceous species and inorganic ions in precipitation in the Bangkok metropolitan Region. Atmos. Environ. 2022, 291, 119393. [Google Scholar] [CrossRef]
  107. Rao, L.F.; Zhang, L.Y.; Wang, X.Z.; Xie, T.T.; Zhou, S.M.; Lu, S.L.; Liu, X.C.; Lu, H.; Xiao, K.; Wang, W.Q.; et al. Oxidative potential induced by ambient particulate matters with acellular assays: A review. Various Technol. Environ. Pollut. Control 2020, 8, 1410. [Google Scholar] [CrossRef]
  108. Hata, M.; Furuuchi, M.; Dong, S.; Phairuang, W.; Ge, H.; Zhang, T. Ambient nanoparticles characterization by East and Southeast Asia nanoparticle monitoring network. In Proceedings of the 9th Asian Aerosol Conference, Kanazawa, Japan, 24–26 June 2015. [Google Scholar]
Figure 1. SEM images of atmospheric nanoparticles in Chiang Mai, Thailand, in the year 2015 (forest fires dominated as emission sources during the dry season) [92].
Figure 1. SEM images of atmospheric nanoparticles in Chiang Mai, Thailand, in the year 2015 (forest fires dominated as emission sources during the dry season) [92].
Atmosphere 14 00066 g001
Table 1. Thailand’s National Ambient Air Quality Standards.
Table 1. Thailand’s National Ambient Air Quality Standards.
PollutantsTime PeriodConcentration
TSP (PM100)Annual100 µg/m3
24 h330 µg/m3
PM10Annual50 µg/m3
24 h120 µg/m3
PM2.5Annual15 µg/m3
24 h50 µg/m3
O38 h140 µg/m3 (0.07 ppm)
1 h200 µg/m3 (0.10 ppm)
CO8 h10,260 µg/m3 (9 ppm)
1 h3420 µg/m3 (30 ppm)
NO2Annual57 µg/m3 (0.03 ppm)
1 h320 µg/m3 (0.17 ppm)
SO2Annual100 µg/m3 (0.04 ppm)
24 h300 µg/m3 (0.12 ppm)
1 h78,000 µg/m3 (0.3 ppm)
Lead (Pb)Monthly1.50 mcg/m3
Table 2. Ambient PM0.1 concentrations (µg/m3) and PM0.1/PM2.5 ratio at different locations in Thailand.
Table 2. Ambient PM0.1 concentrations (µg/m3) and PM0.1/PM2.5 ratio at different locations in Thailand.
Sampling TimePM0.1PM2.5PM0.1/PM2.5 RatioReferences
Chiang MaiSuburbanSeptember 2014–June 201525.2 ± 4.777.5 ± 23.80.33 ± 0.03[32]
SuburbanMarch–April 201616.5--[52]
PathumtaniSuburbanOctober 2019 (wet)13.5 ± 0.855.1 ± 4.60.25 ± 0.06[24]
January–February 2020 (dry)18.9 ± 4.073.4 ± 16.30.26 ± 0.04
BangkokUrbanJuly 2014–June 201514.5 ± 4.766.4 ± 17.20.23 ± 0.09[32]
UrbanMarch–April 201611.9--[52]
UrbanNovember 2014–October 201515.0 ± 2.4--[53]
UrbanMay 2016–April 201714.8 ± 2.0--[54]
Urban–trafficMarch–April 20167.7--[52]
SongkhlaSuburbanSeptember–October 201514.2 ± 10.073.7 ± 49.80.19[26]
August–October 20171.9 ± 0.612.9 ± 0.80.15
SuburbanMarch–April 201610.9--[52]
SuburbanJanuary–December 201810.2 ± 2.257.8 ± 4.70.18 ± 0.05[55]
SuburbanJanuary–August 201910.4 ± 1.2--[25]
SuburbanJanuary–December 20188.4 ± 1.9--[28]
Table 3. Seasonal average of OC, EC (µg/m3), and OC/EC ratio as well as Char-EC, Soot-EC (µg/m3), and Char-EC/Soot-EC ratio at different locations in Thailand.
Table 3. Seasonal average of OC, EC (µg/m3), and OC/EC ratio as well as Char-EC, Soot-EC (µg/m3), and Char-EC/Soot-EC ratio at different locations in Thailand.
LocationSeasonOC (µg/m3)EC (µg/m3)OC/EC (-)Char-EC (µg/m3)Soot-EC (µg/m3)Char-EC/
Soot-EC (-)
Chiang MaiWet–20142.34 ± 0.820.51 ± 0.145.62 ± 1.220.23 ± 0.110.29 ± 0.070.80 ±
Dry—20154.97 ± 1.461.51 ± 0.663.29 ± 0.670.96 ± 0.580.54 ± 0.131.78 ±
PathumtaniWet—20190.86 ± 0.170.58 ± 0.171.50 ± 0.180.24 ± 0.080.34 ± 0.080.70 ±
Dry—20202.05 ± 0.450.93 ± 0.412.49 ± 0.890.39 ± 0.320.54 ± 0.140.69 ±
BangkokWet—20140.78 ± 0.340.31 ± 0.082.57 ± 1.100.11 ± 0.030.20 ± 0.050.52 ±
Dry—20152.31 ± 0.580.58 ± 0.134.47 ± 1.460.26 ± 0.100.32 ± 0.040.77 ±
BangkokWet—20163.45 ± 0.701.39 ± 0.432.59 ± 0.550.43 ± 0.150.97 ± 0.300.45 ±
Dry—20172.60 ± 0.830.61 ± 0.144.43 ± 1.790.27 ± 0.090.35 ± 0.060.77 ±
SongkhlaWet—20194.90 ± 0.901.85 ± 0.502.70 ± 0.700.43 ± 0.101.40 ± 0.100.30 ±
Dry—20191.60 ± 0.200.66 ± 0.102.42 ± 0.510.15 ± 0.100.50 ± 0.100.33 ±
SongkhlaPre-monsoon—20181.22 ± 1.010.34 ± 0.143.00 ± 1.410.08 ± 0.040.25 ± 0.130.35 ±
Monsoon—20180.42 ± 0.210.14 ± 0.073.15 ± 0.810.04 ± 0.030.12 ± 0.050.34 ±
Dry—20180.44 ± 0.220.18 ± 0.122.75 ± 1.100.05 ± 0.030.14 ± 0.090.37 ±
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Phairuang, W.; Piriyakarnsakul, S.; Inerb, M.; Hongtieab, S.; Thongyen, T.; Chomanee, J.; Boongla, Y.; Suriyawong, P.; Samae, H.; Chanonmuang, P.; et al. Ambient Nanoparticles (PM0.1) Mapping in Thailand. Atmosphere 2023, 14, 66.

AMA Style

Phairuang W, Piriyakarnsakul S, Inerb M, Hongtieab S, Thongyen T, Chomanee J, Boongla Y, Suriyawong P, Samae H, Chanonmuang P, et al. Ambient Nanoparticles (PM0.1) Mapping in Thailand. Atmosphere. 2023; 14(1):66.

Chicago/Turabian Style

Phairuang, Worradorn, Suthida Piriyakarnsakul, Muanfun Inerb, Surapa Hongtieab, Thunyapat Thongyen, Jiraporn Chomanee, Yaowatat Boongla, Phuchiwan Suriyawong, Hisam Samae, Phuvasa Chanonmuang, and et al. 2023. "Ambient Nanoparticles (PM0.1) Mapping in Thailand" Atmosphere 14, no. 1: 66.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop