A review of the sources, distribution sequences, and health risks associated with exposure to atmospheric polycyclic aromatic hydrocarbons

Figures & data

Table 1. Properties of US EPA priority PAHs (B. K. Lee & Vu, 2010; Ghosal et al., 2016; N. Zhang et al., 2022; Patel et al., 2020; Yang et al., 2021)

PAH compounds	MF	MW (g/mol)	MP (^oC)	BP (^oC)	VP at 25 ^oC (KPa)	Number of AR
Naphthalene (Nap)	C10H8	128.17	218	80.26	11.3	2
Acenaphthene (Ace)	C12H10	154.21	93.4	279	0.29	3
Acenapthylene (Acy)	C12H8	152.19	78–82	280	0.64	3
Fluorene (Fl)	C13H10	166.22	295	116–117	0.08	3
Anthracene (Ant)	C14H10	178.23	218	340	0.08	3
Phenanthrene (Phe)	C14H10	178.23	101	332	1.61×10^−2	3
Fluoranthene (Flu)	C16H10	202.25	375	110.8	1.23×10^−3	4
Pyrene (Pyr)	C16H10	202.25	145–148	404	6.00×10^−4	4
Benz[a]anthracene (BaA)	C18H12	228.30	158	438	2.80×10^−4	4
Chrysene (Chr)	C18H12	228.30	254	448	8.31×10^−4	4
Benzo[b]fluoranthene (BbF)	C20H12	252.30	168	-	6.67×10^−5	5
Benzo[a]pyrene (BaP)	C20H12	252.30	179	495	7.32×10^−7	5
Benzo[k] fluoranthene (BkF)	C20H12	252.30	217	228.6	1.29×10^−7	5
Dibenz[a,h]anthracene (DahA)	C22H14	278.34	262	524	1.27×10^−7	5
Indeno[1,2,3-cd]pyrene (IcdP)	C22H12	276.33	162–164	497	1.67×10^−8	6
Benzo[g,h,i]perylene (BghiP)	C22H12	276.34	278	500	1.33×10^−8	6

Note: MF = Molecular formula; MW = Molecular weight; MP = Melting point; BP = Boiling point; VP = Vapour pressure; AR = Aromatic rings

Table 2. Properties of some non-priority PAHs (B. K. Lee & Vu, 2010; Ghosal et al., 2016; N. Zhang et al., 2022; Patel et al., 2020; Yang et al., 2021)

PAH compounds	MF	MW (g/mol)	MP (^oC)	BP (^oC)	VP at 25 ^oC (KPa)	Number of AR
Benzo[a]fluoranthene (BaF)	C20H12	252.30	145	228.6	5.0×10^−7	5
Benzo[ghi]fluoranthene (BghiF)	C18H10	226.30	149	302.8	2.5×10^−5	5
Triphenylene (Tri)	C18H12	228.30	198	438	2.8×10^−6	4
Perylene (Per)	C20H12	252.30	400	276	6.67×10^−8	5
Benzo[j]fluoranthene (BjF)	C20H12	252.30	218	279	3.60×10^−6	5
Benzo[e]pyrene (BeP)	C20H12	252.30	179	495	7.60×10^−7	5
Benzo[g]chrysene (BgC)	C22H14	278.30	254	448	3.07×10^−6	5
Benzo[c]chrysene (BcC)	C22H14	278.30	126.5	356.1	1.20×10^−7	5
Dibenz[a,c]anthracene	C22H14	278.30	205	524	1.33×10^−8	5
Coronene (Cor)	C24H12	300.40	437	525	2.89×10^−10	7
Dibenzo[a,e]fluoranthene (DBaeF)	C24H14	302.40	232	-	9.77×10^−9	6
Dibenzo[a,l]pyrene (DBalP)	C24H14	302.40	162.4	-	6.40×10^−8	6
Dibenzo[a,e]pyrene (DBaeP)	C24H14	302.40	233.5	-	6.93×10^−9	6
Dibenzo[a,i]pyrene (DBaiP)	C24H14	302.40	281.5	-	2.40×10^−9	6
Dibenzo[a,h]pyrene (DBahP)	C24H14	302.40	315	-	8.53×10^−10	6

Note: MF = Molecular formula; MW = Molecular weight; MP = Melting point; BP = Boiling point; VP = Vapour pressure; AR = Aromatic rings

Figure 1. Structures of low-molecular-weight (LMW) PAHs.

Figure 2. Structures of medium-molecular-weight (MMW) PAHs.

Figure 3. Structures of high-molecular0weight (HMW) PAHs.

Table 3. PAH diagnostic ratios utilised as source indicators

PAH ratio	Value Range	Source	References
LMW/HMW	<1 >1	Pyrogenic Petrogenic	D. Liu et al. (2017)
Ant/(Ant+Phe)	<0.1 >0.1	Petrogenic/fossil fuel combustion Pyrogenic/combustion	Tobiszewski and Namie (2012)
Flu/(Flu+Pyr)	0.4–0.5 >0.5 <0.4	Liquid fossil fuel combustion Coal and wood combustion Petrogenic	W. Wang et al. (2021)
BaA/(BaA+Chr)	0.2–0.35 >0.35 <0.2	Petrogenic Coal and wood combustion Liquid fossil fuel combustion	D. Liu et al. (2017) J. Li et al. (2019)
BaP/(BeP+BaP)	<0.5 >0.5	Close sources Distant sources	Tobiszewski and Namie (2012)
IcdP/(IcdP+BghiP)	<0.2 0.2–0.4 >0.5 <0.5	Petrogenic Liquid fossil fuel combustion Coal and wood combustion Combustion of liquid fuel	Dvorská et al. (2011)
BaP/(BghiP)	<0.6 >0.6	Non-traffic emissions Traffic emissions	W. Wang et al. (2021); D. Liu et al. (2017)

Table 4. Distribution of PAHs in ambient air across some cities worldwide

Location	PM	$\sum$ PAHs (ng/m^3)	Dominant PAHs	Distribution pattern of PAHs	References
Bizerte city, Tunisia,	PM10	25.39 (9.38–44.81)	Pyr and Flu	4R (51.7%)>5R (26.7)>6R (11.7%)>3R (9.8%). MMW >HMW>LMW PAHs	Hassine et al. (2014)
Pune, India,	PM2.5 PM10	342.4±14.3 and 446.1±25.6 for PM2.5 and PM10, respectively	Nap	3R>4R>2R>5R>6R for both PM10 and PM2.5. LMW>HMW>MMW PAHs for both PM10 and PM2.5	Roy et al. (2019)
Wuhan, China,	PM2.5		5R PAHs	5R (34.4%)>4R (32.3%)>6R (18.9%)>3R (10.7%)>2R (3.7)	Y. Zhang et al. (2019)
India	PM2.5	Urban (750.80± 19.49) and rural (559.59 ± 17.56)	IcdP	5R (46.2%)>6R (32.4%)>4R (12.4%)>3R (6.9%)>2R (1.9%) for both urban and rural areas. HMW>MMW>LMW PAHs for both urban and rural areas.	A. Kumar et al. (2019)
Thailand	PM2.5	134.7 ± 80.4 and 5.1± 9.7 at haze and non-haze, periods, respectively.	Nap and IcdP	LMW (Nap, Ace) and HMW (IDP, BaP, BgPe) PAHs were dominant in gas and PM2.5 phases respectively	Kongpran et al. (2021)
Giza, Egypt	PG	1,429.74 and 2,912.56 for particulate and gas phases, respectively	BaP and Pyr	5R (38.2%)>4R (29.6%)>6R(23.4%)>3R(7.8%)>2R (1.1%) for particulate and 3R(56.1%)>2R(29.6%)>4R(12.6%)>6R(0.6%) for gas phase	Hassan and Khoder (2012)
Assiut, Egypt	PG	1,590 in both particle and gas phases	Nap and BbF	HMW (80 %) and LMW (90 %) PAHs were dominant in particulate and gas phases, respectively	Abdallah and Atia (2014)
Bangi, Lumpur and Jaya, Malaysia	PM10	Urban (2.03±0.69) and industrial (3.56±1.07)	BbF, BkF, BaP, IcdP	5R (BaP, BbF, BkF) and 6R (IDP, BgPe) contributed over 80 % to the total PAH in PM10	Jamhari et al. (2014)
Poland	TSP	8.66 in atmospheric particulate	Pyr	4R>5R>6R>3R 5R PAHs (BkF, BaP, DahA) exceeded 1 ngm^−3	Siudek and Frankowski (2018)
Rwanda	PM2.5 and PM10	52.4 (PM2.5) and 105.0 (PM10) for urban roadside	Flu, BaP BghiP	PAHs were higher in PM2.5 along the roadside than in urban sites. PAHs were higher in the dry than in the wet season.	Kalisa et al., 2018
Accra, Ghana	PM10	809.8	Pyr	5R>4R>6R>3R>2R. HMW (72.4%) >MMW (21.9) >LMW (5.7%) PAHs. 5R contributed 33% to PAHs	Safo-Adu et al. (2014)
Shinjuku, Japan	PM2.5	0.88 and 1.5 for 7 and 15 PAHs		The average PAHs concentration (0.88 ng/m^3) was lower than that in New York and Paris	Shimada et al. (2022)
Uganda, Kakira and Entebbe	TSP	74.3 (19.3–311) for Kakira and 56.8 (13.3–126) for Entebbe	Nap	3R>2R>4R>5R>6R	Arinaitwe et al. (2012)
Kumasi, Ghana	PM10	2.7±8.7 for the school campus and 29 ±8.9 for the city centre	Phe and BghiP	HMW PAHs were highly distributed in the city centre	Bortey-Sam et al. (2015)
India	PM2.5	Bokaro (797.9±39.1), Ranchi (887.7±38.8), and Gamharia (1015.1±42.7)	6 and 5 ring PAHs	HMW>MMW>LMW PAHs for all the three sites	Ambade et al. (2022)
Lhasa and Tibet, China	TSP	43.9 ± 54.6	Flu	4R and 5R PAHs contributed about 63 to 84 % of total PAHs	Chen et al. (2018)
Europe, South-western	PM10	9.3 (0.68–27.40)	BghiP	BghiP > Chr > IP> BaP > BkF >Ft > Pyr > BaA >Phe > DBahA, Ace > Fl and Ant	Sánchez-Piñero et al. (2021)
Ceske Budejovice, Czech Republic	PM2.5	PAH in PM2.5 ranged from 0.267 to 30.2	Flu and Pyr	BaP level exceeded the European average emission limit (1 ngm^−3) by 1.5 to 6 times	Polachova et al. (2019)
Athens, Greece	PM2.5	Winter (7.0±10.1), spring (2.5±4.1), summer (0.9±0.9), fall (2.2±3.2)	HMW PAHs	BaP (0.26 ngm^−3) <1 (European Union target value) but above the WHO reference level (0.12 ngm^−3)	Tsiodra et al. (2021)
Lahore, Pakistan	TSP	Winter (1.03±0.31) and summer (1.01±0.30)	4 R PAH	HMW>LMW PAHs in both winter and summer. 4R (31%)>3R (26%)>5R (19%)>2R (14%)>6R (10%) for both seasons	Aslam et al. (2022)
Europe	TSP	Varying levels of total PAHs were obtained across European cities	BaP	Regions with the highest individual levels of PAHs within the considered domain were central Europe and the Baltic Sea areas	Garrido et al. (2014)
Nine megacities, China	PM2.5	65±120	Flu	Flu>BbF>Pyr>Chr. 4 to 6 rings contributed 90 % to total PAHs	P. Li et al. (2015)
Brisbane	PM2.5	1.17–38.00	Nap	Nap>Flu>BaA>Chr>BbF> IcdP>DahA	Mishra et al. (2016)
Curacao, Netherland	PM10	2011(1.2–790) 2014 (27–660)	Nap, Ant	LMW PAHs contributed 96% and 84 % to downwind and upwind sites respectively	Pulster et al. (2019)
Urban cities, UK	PM2.5	-	IcdP BghiP	HMW>MMW>LMW PAHs	Jang et al. (2013)
Tehran, Iran	PM10	79.49–137.14	BkF, BbF, Chr	LMW>HMW PAHs	Hoseini et al. (2015)

Note: PM = Particulate matter; UK = United Kingdom; PG= Particle and gas phase

Table 5. Health risk exposure levels to atmospheric PAHs in some cities worldwide

Location	Year	PM	$\sum$PAH	TEQ (ng/m^3)	ILCR level	Comments	References
Ulaanbaatar, Mongolia	2017	TSP	15	>1.00	1.20×10^−5 − 2.10×10^−5	Potential risk	Byambaa et al. (2019)
Urban city, China	2011	PM2.5	16	>1.00	9.08×10^−6	Potential risk	Cheng et al. (2022)
Urban city, Pakistan	2014	PM2.5	16	0.01- 0.24	2.09×10^−5 - 8.28×10^−7	Potential risk	Ishtiaq et al. (2021)
Alexandra, Egypt	2012	TSP	44	>1.00	6.64×10^−3 −4.42×10^−2	Potential high risk	Khairy and Lohmann (2013)
Hamadan, Iran	2019	PM2.5	16	0.35	1.17×10^−5 − 3.50×10^−5	Potential risk	Nadali et al. (2021)
Shangai, China,	2014 – 2017	PM2.5, PM1.1	15	<1.00	>1.00×10^−6	Potential risk	W. Wang et al. (2021)
Kwara State, Nigeria	2011	PM2.5	16	>1.00	1.20×10^−1	Potential high risk	Fakinle et al. (2022)
Tianjin, China	2009	PM2.5	12	>1.00	1.12×10^−5	Potential high risk	Han et al. (2019)
Jeddah, Saudi Arabia	2020	PM2.5	15	>1.00	>1.00×10^−4	Potential high risk	Alamri et al. (2021)
Curitiba, Brazil	2010	PM10	14	0.42 - 1.12	8.16×10^−9 −1.07×10^−8	Low risk	Froehner et al. (2011)
Rural area, China	2020	PM2.5	14	>1.00	4.36×10^−5 −9.28×10^−5	Potential risk	Bai and Li (2022)
Italy	2016–2018	PM10 PM2.5	11	<1.00	2.50×10^−6 − 2.00×10^−6	Potential risk	Pomata et al. (2021)
Vladivostok, Russia	2019	TSP	10	0.06 – 2.90	1.50×10^−5 −1.00×10^−7	Potential risk	Y. Wang et al. (2022)
Ardebil, Iran	2018	PM2.5	16	<1.00	2.00×10^−5 −6.50×10^−4	Potential risk	Rostami et al. (2019)
Lagos, Nigeria	2017	TSP	16	<1.00	1.80×10^−5 − 9.70×10^−5	Potential risk	Alani et al. (2021)
Tehran, Iran	2013 –2014	PM10	16	<1.00	1.68×10^−7	Low risk	Hoseini et al. (2015)
Rwanda	2018	PM2.5 a PM10	15	>1.00	>1.00×10^−6	Potential risk	Kalisa et al., 2019
India	2018	PM2.5	16	134.00- 182.00	1.20×10^−7 − 8.50×10^−7	Low risk	A. Kumar et al. (2019)
South-western Europe	2017	PM10	15	2.70	>1.00×10^−4	Potential high risk	Sánchez-Piñero et al. (2021)
Three urban cities, India	2018 – 2019	PM2.5	16	>1.00	2.60×10^−5 - 7.60×10^−5	Potential risk	Ambade et al. (2022)
Lahore, Pakistan	2017 – 2018	PM10	16	92.50	2.00×10^−2 − 1.40×10^−1	Potential high risk	Alamri et al. (2021)
Thailand	2018	PM2.5	16	>1.00	2.50×10^−5 − 9.30×10^−4	Potential high risk	Kongpran et al. (2021)
Kumasi, Ghana	2011	PM10	15	5.30	2.20×10^−6 − 3.30×10^−6	Potential risk	Bortey-Sam et al. (2015)
Accra, Ghana	2012	PM10	20	58.30	7.10×10^−4	Potential high risk	Safo-Adu et al. (2014)
Bab Ezzouar, Algeria	2018 –2019	PM2.5 PM10 PM1	13	1.23–2.78	8.80×10^−7, 1.00×10^−7, 2.00×10^−6	Potential low risk	Teffahi et al. (2021)
Lhasa and Tibet, China	2013–2014	TSP	15	1.48–24.5	9.08×10^−6	Potential risk	Chen et al. (2018)
Three cities, Malaysia	2010–2011	PM10	16	<1.00	3.40×10^−7	Low risk	Jamhari et al. (2014)
Wuhan, China	2014 –2015	PM2.5	15	>1.00	1.60×10^−4 −3.03×10^−4	Potential high risk	Y. Zhang et al. (2019)
Tarragona, Europe Delhi, India	2008–2009 2021	TSP PG	17 16	0.33–2.07 0.55–38.39	1.20×10^−4 4.53×10^−5 – 6.35×10^−6	Potential high risk Potential risk	Ramírez et al. (2011)B. P. Singh et al. (2023)

Note: PM = Particulate matter; TEQ = Toxic equivalency concentration; ILCR = Incremental lifetime lung Cancer risk; PG = Particulate and gas phase

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