Exposure to Atmospheric Particulate Matter-Bound Polycyclic Aromatic Hydrocarbons and Their Health Effects: A Review
Abstract
:1. Introduction
2. Concentrations of Atmospheric PM-Bound PAHs
2.1. Personal Exposure to PM-Bound PAHs
2.2. Indoor Concentrations of PM-Bound PAHs
2.3. Outdoor Concentrations of PM-Bound PAHs
3. Health Effects and Assessments of PAHs
4. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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Continent | Country | PM2.5 (µg/m3) | PM10 (µg/m3) | References | ||
---|---|---|---|---|---|---|
24-h | Annual | 24-h | Annual | |||
North America | USA | 35 | 12 | 150 | None | [3] |
Mexico | 45 | 12 | 75 | 40 | [31] | |
Canada | 27 | 8.8 | None | None | [32] | |
South America | Brazil | 25 | 10 | 50 | 20 | [33] |
Chile | 50 | 20 | 150 | 50 | [34] | |
Australia | Australia | 25 | 8 | 50 | 25 | [35] |
Africa | South Africa | None | None | 75 | 40 | [39] |
Europe | EU | None | 25 | 50 | 40 | [37] |
Russia | 35 | 25 | 60 | 40 | [38] | |
Asia | China | 75 | 35 | 150 | 70 | [36] |
Japan | 35 | 15 | None | 100 | [36] | |
South Korea | 25 | 25 | 100 | 50 | [36] | |
Mongolia | 50 | 25 | 150 | 50 | [36] | |
India | 60 | 40 | 100 | 60 | [36] |
Species (Abbreviation) | CAS Number | MW a Category | Vapor Pressure b | Structure |
---|---|---|---|---|
US EPA 16 PAHs | ||||
Naphthalene (Nap) | 91-20-3 | 128.17 LMW | 11.3 | |
Acenaphthylene (Acy) | 208-96-8 | 152.19 LMW | 0.64 | |
Acenaphthene (Ace) | 83-32-9 | 154.21 LMW | 0.29 | |
Fluorene (Flu) | 86-73-7 | 166.22 LMW | 0.08 | |
Anthracene (Ant) | 120-12-7 | 178.23 LMW | 0.08 | |
Phenanthrene (Phe) | 85-01-8 | 178.23 LMW | 1.61 × 10−2 | |
Fluoranthene (FR) | 206-44-0 | 202.25 MMW | 1.23 × 10−3 | |
Pyrene (Pyr) | 129-00-0 | 202.25 MMW | 6.00 × 10−4 | |
Benz[a]anthracene (BaA) | 56-55-3 | 228.30 MMW | 2.80 × 10−4 | |
Chrysene (Chr) | 218-01-9 | 228.30 MMW | 8.31 × 10−4 | |
Benzo[b]fluoranthene (BbF) | 205-99-2 | 252.30 HMW | 6.67 × 10−5 | |
Benzo[k]fluoranthene (BkF) | 207-08-9 | 252.30 HMW | 1.29 × 10−7 | |
Benzo[a]pyrene (BaP) | 50-32-8 | 252.30 HMW | 7.32 × 10−7 | |
Dibenz[a,h]anthracene (DBA) | 53-70-3 | 278.30 HMW | 1.27 × 10−7 | |
Indeno[1,2,3-cd]pyrene (IDP) | 193-39-5 | 276.30 HMW | 1.67 × 10−8 | |
Benzo[ghi]perylene (BgPe) | 191-24-2 | 276.30 HMW | 1.33 × 10−8 | |
Non-priority PAHs | ||||
Cyclopenta[def]phenanthrene (CdefP) | 203-64-5 | 190.24 LMW | - c | |
Benzo[c]fluorene (BcF) | 205-12-9 | 216.28 MMW | - c | |
Cyclopenta[c,d]pyrene (CcdP) | 27208-37-3 | 226.30 MMW | - c | |
Benzo[ghi]fluoranthene (BghiF) | 203-12-3 | 226.30, MMW | 2.56 × 10−5 | |
Triphenylene (Tri) | 217-59-4 | 228.30 MMW | 2.8× 10−6 | |
Benzo[c]phenanthrene (BcP) | 195-19-7 | 228.30 MMW | - c | |
Retene (Ret) | 483-65-8 | 234.30, MMW | - c | |
11H-Benz[bc]aceanthrylene (11H-BbcA) | 202-94-8 | 240.30 MMW | - c | |
4H-Cyclopenta[def]chrysene (4H-CdefC) | 202-98-2 | 240.30 MMW | - c | |
Benz[j]aceanthrylene (BjA) | 202-33-5 | 252.30 HMW | - c | |
Benz[e]aceanthrylene (BeA) | 199-54-2 | 252.30 HMW | - c | |
Benz[l]aceanthrylene (BlA) | 211-91-6 | 252.30 HMW | - c | |
Perylene (Per) | 198-55-0 | 252.30 HMW | 6.67 × 10−8 | |
Benzo[a]fluoranthene (BaF) | 203-33-8 | 252.30 HMW | - c | |
Benzo[j]fluoranthene (BjF) | 205-82-3 | 252.30 HMW | 3.60 × 10−6 | |
Benzo[e]pyrene (BeP) | 192-97-2 | 252.30 HMW | 7.60 × 10−7 | |
13H-Dibenzo[a,h]fluorene (13H-DahF) | 239-85-0 | 266.3 HMW | - c | |
Anthanthrene (Anth) | 191-26-4 | 276.30 HMW | - c | |
Indeno[1,2,3-cd]fluoranthene (IDF) | 193-43-1 | 276.30 HMW | - c | |
Benzo[b]chrysene (BbC) | 214-17-5 | 278.30 HMW | - c | |
Benzo[g]chrysene (BgC) | 196-78-1 | 278.30 HMW | 3.07 × 10−6 | |
Benzo[c]chrysene (BcC) | 194-69-4 | 278.30 HMW | 1.20 × 10−7 | |
Dibenz[a,c]anthracene (DBacA) | 215-58-7 | 278.30 HMW | 1.33 × 10−8 | |
Dibenz[a,j]anthracene (DBajA) | 224-41-9 | 278.30 HMW | - c | |
Picene (Pic) | 213-46-7 | 278.30 HMW | - c | |
Coronene (Cor) | 191-07-1 | 300.40 HMW | 2.89 × 10−10 | |
Benzo[b]perylene (BbPer) | 197-70-6 | 302.40 HMW | - c | |
Naphtho[2,3-e]pyrene (NeP) | 193-09-9 | 302.40 HMW | - c | |
Dibenzo[a,e]fluoranthene (DBaeF) | 5385-75-1 | 302.40 HMW | 9.77 × 10−9 | |
Dibenzo[a,l]pyrene (DBalF) | 191-30-0 | 302.40 HMW | 6.40 × 10−8 | |
Dibenzo[a,e]pyrene (DBaeP) | 192-65-4 | 302.40 HMW | 6.93 × 10−9 | |
Dibenzo[a,i]pyrene (DBaiP) | 189-55-9 | 302.40 HMW | 2.40 × 10−9 | |
Dibenzo[a,h]pyrene (DBahP) | 189-64-0 | 302.40 HMW | 8.53 × 10−10 |
Evaluation | Species |
---|---|
Group 1 a | Benzo[a]pyrene |
Group 2A b | Dibenz[a,h]anthracene, Cyclopenta[cd]pyrene, Dibenzo[a,l]pyrene, Dibenzo[c,h]acridine, 1-Nitropyrene, 6-Nitrochrysene, 2-Nitrotoluene, |
Group 2B c | Naphthalene, Benz[a]anthracene, Chrysene, Benzo[b]fluoranthene, Benzo[k]fluoranthene, Benzo[j]fluoranthene, Indeno[1,2,3-cd]pyrene, Benzo[c]phenanthrene, Dibenzo[a,e]pyrene, Dibenzo[a,h]pyrene, Dibenzo[a,i]pyrene, Dibenzo[a,h]acridine, Dibenzo[a,j]acridine, Dibenzo[c,g]carbazole, 5-Methylchrysene, 2-Nitrofluorene, 4-Nitropyrene, 3,7-Dinitrofluoranthene, 3,9-Dinitrofluoranthene, 1,3-Dinitropyrene, 1,6-Dinitropyrene, 1,8-Dinitropyrene, 2,6-Dinitrotoluene, 3-Nitrobenzanthrone, 5-Nitroacenaphthene |
Participants | PM | PAHs | Period | Concentration | Country, City |
---|---|---|---|---|---|
Rural residents | PM | 28 | July | 655 ± 250 | China, Laiyang [71] |
Rural residents | PM2.5 | 10 | 9–12 March 2013 | 4.2–224 | Thailand, Lampang [72] |
Health residents | PM2.5 | 26 | 2014–2016 | 1.7 (0.4–5.2) | China, Hongkong [73] |
Residents | PM2.5 | 16 | 2015–2018 | 8.27 | China, Zhuhai [74] |
Residents | PM2.5 | 16 | 2014–2017 | 11.9 | China, Wuhan [74] |
Children | PM2.5 | 8 | 11 April–9 May 2012 15 July–3 November 2012 | 0.65 0.63 | Italy, Rome [75] |
Children | PM2.5 | 16 | 17 May–23 June 2010 8 November–13 December 2010 | 27.31 58.18 | China, Tianjin [76] |
COPD patients | PM2.5 | 16 | June 2017–October 2018 | 186.85 | China, Harbin [77] |
Drivers | PM4 | 12 | 2015–2018 | 9.97 | Greece, Thessaloniki [15] |
Office workers | PM2 | 13 | 2015 | 4.0 ± 2.3 | Australia, Canberra [16] |
Office workers | PM2.5 | 8 | 6–13 March 2009 10–19 June 2009 | 15.19 ± 15.15 3.04 ± 1.38 | Czech Republic, Ostrava [78] |
Policemen | PM2.5 | 8 | 8–20 February 2009 17–27 May 2009 | 4.27 ± 2.95 1.03 ± 0.61 | Czech Republic, Prague [78] |
Policemen | PM2.5 | 8 | 2–6 March 2009 6–10 June 2009 | 39.08 ± 17.33 4.27 ± 1.99 | Czech Republic, Karvina [78] |
Housewife | PM2.5 | 19 | 4–21 November 2016 | 310 ± 443 | China, Xingping [79] |
Housewife | PM2.5 | 19 | January 2018 | 116 (32–224) | China, Xi’an, [80] |
Highway toll station workers | PM2.5 | 16 | March–May 2014 | 319.90 | China, Tianjin [81] |
Newsagent | PM | 16 | 2013 | 5570 | Iran, Tehran [82] |
Seafarers | PM | 32 | July 2016 | 760–8400 | Sweden [83] |
Chinese kitchen worker | PM | 16 | 4 September–1 November 2014 | 1794–12,108 | China, Taiwan [84] |
Place | Country, City | PM | PAHs | Periods | Concentration |
---|---|---|---|---|---|
Rural households | China, Laiyang [71] | PM | 28 | July | 738 ± 321 |
Households | China, Hongkong [73] | PM2.5 | 26 | 2014–2016 | 3.0 (1.0–7.3) |
China, Xingping [79] | PM2.5 | 19 | 4–21 November 2016 | 211 ± 120 | |
China, Xi’an [80] | PM2.5 | 19 | January 2018 | 92 (15–276) | |
China, Beijing [88] | PM2.5 | 16 | December 2014–February 2016 | 39.8 | |
Saudi Arabia, Jeddah [89] | PM10 | 13 | - | 18.5 ± 11.2 | |
Turkey, Bursa [90] | PM | 16 | July 2014– January 2015 | 22 | |
Spain, Madrid [91] | PM10 | 14 | May 2017–April 2018 | 0.186 | |
Infant room | China, Harbin [92] | PM | 16 | December 2013–March 2014 | 318 ± 314 |
University (dormitory) | China, Beijing [88] | PM2.5 | 16 | December 2014–February 2016 | 34.1 |
China, Wuhan [93] | PM2.5 | 16 | December 2014–June 2015 | 31.3 | |
University (laboratory) | China, Wuhan [93] | PM2.5 | 16 | December 2014–June 2015 | 27.0 |
China, Harbin [94] | PM2.5 | 16 | January 2015 | 115 | |
University (office) | China, Beijing [88] | PM2.5 | 16 | December 2014–February 2016 | 32.1 |
Saudi Arabia, Jeddah [89] | PM10 | 13 | - | 12.7 ± 5.1 | |
China, Wuhan [93] | PM2.5 | 16 | December 2014–June 2015 | 32.4 | |
China, Harbin [94] | PM2.5 | 16 | January 2015 | 96.6 | |
Classroom | China, Beijing [95] | PM2.5 | 12 | October 2016–March 2017 | 29.83 |
Brazil, São Paulo [96] | PM | 15 | 7–11 November 2016 | 0.45 | |
Poland, Warsaw [17] | PM1 | 16 | April–June 2015 | 10.9 | |
Poland, Gliwice [17] | PM1 | 16 | April–June 2015 | 21.6 | |
Portugal, Porto [97] | PM2.5 | 18 | March–May 2014 | 5.03–23.6 | |
Shopping malls | Pakistan, Islamabad [98] | PM2.5 | 16 | February–April 2014 | 2.39 ± 1.45 |
Bakery | Italy, Bari [99] | PM2.5 | 7 | 7–19 April 2013 | 7.4 |
Hotels | Saudi Arabia, Jeddah [89] | PM10 | 13 | - | 6.3 ± 1.3 |
China, Jinan [100] | PM2.5 | 19 | January 2016 | 39.58–115.63 | |
Public bars | Nigeria, Warri [101] | PM | 16 | - | 43.43–155.11 |
Office building | China, Changchun [102] | PM2.5 | 16 | April–October 2018 December 2017–April 2018 | 48.6 67.9 |
Fire station | Poland, North Poland [104] | PM4 | 15 | September 2018 | 1882–5924 |
Ship | Sweden [83] | PM | 32 | July 2016 | 550–39,000 |
Chinese kitchen | China, Taiwan [84] | PM | 16 | 4 September–1 November 2014 | 1648–5342 |
Country, City | PM | PAHs | Periods | Concentration |
---|---|---|---|---|
Oceania | ||||
New Zealand, Auckland [108] | PM2.5 | 15 | 2016–2017 | 0.31 ± 0.19 |
Americas | ||||
Mexico, South Mexico [67] | PM2.5 | 24 | November 2016–March 2017 | 4.82 ± 1.97 |
Peru, Arequipa [109] | PM2.5 PM10 | 14 | January–December 2018 | 7.4 ± 2.3 9.6 ± 3.9 |
Argentina, Cordoba [110] | PM10 | 14 | August 2011–August 2013 | 4.5 ± 4.34 |
Brazil, Belo Horizonte [111] | PM2.5 | 16 | May 2017–April 2018 | 1.68–6.24 |
Canada, Toronto [112] | PM10 | 17 | August 2016–August 2017 | 10.2 ± 2.5 |
US, Washington [113] | PM10 | 19 | April 2016–September 2018 | 0.84 |
Europe | ||||
Spain, Coruña [114] | PM10 | 12 | Januray–December 2017 | 7.56 |
Spain, South Spain [115] | PM2.5 PM10 | 16 | July 2014–June 2015 | 23.0 26.2 |
Italy, Milan [116] | PM2.5 | - | December 2018–February 2019 May–July 2019 | 72.8 ± 16.6 0.40 ± 0.07 |
Poland, Wadowice [117] | PM10 | 9 | March 2017 August 2017 | 80.6 10.5 |
Cyprus, Nicosia [118] | PM2.5 | 50 | January–March 2018 | 1.62 |
Czech Republic, Brno [119] | PM1 | 15 | January–February 2017 | 20.7 |
Croatia, Zagreb [120] | PM10 | 10 | December 2017–February 2018 | 25.4 |
Bosnia and Herzegovina, Sarajevo [120] | PM10 | 10 | December 2017–February 2018 | 64.8 |
Russia, Moscow [121] | PM10 | 9 | June–July 2018 | 1.32–7.68 |
Russia, St. Petersburg [121] | PM10 | 9 | June–July 2018 | 1.71–6.30 |
Russia, Kazan [121] | PM10 | 9 | June–July 2018 | 2.95–9.61 |
Africa | ||||
Algeria, Algiers [122] | PM10 | 22 | June–September 2016 | 7.47 ± 1.21 |
South Africa, Pretoria [123] | PM2.5 | 16 | June–July 2016 | 4.11 |
Rwanda, Kigali [124] | PM2.5 | 15 | May–June 2017 | 52.7 |
Asia | ||||
China, Hongkong [73] | PM2.5 | 26 | 2014–2016 | 3. 9 (1.5–9.6) |
China, Xi’an [127] | PM2.5 PM10 | 16 | December 2016–December 2017 | 63.1 (14.3–266) 66.8 (9.69–349) |
China, Shanghai [18] | PM2.1 | 9 | July 2017 January 2018 | 1.36 ± 0.20 7.72 ± 3.33 |
China, Beijing [128] | PM10 | 15 | January 2017 | 98.1 ± 48.2 |
China, Zhengzhou [128] | PM10 | 15 | January 2017 | 77.9 ± 29.6 |
China, Guangzhou [129] | PM2.5 | 16 | June–July 2016 November–December 2016 | 5.49 10.5 |
China, Taiyuan [129] | PM2.5 | 16 | June–July 2016November–December 2016 | 29.5 197 |
China, Jinan [130] | PM2.5 | 18 | March–December 2016 | 39.8 (8.18–246) |
China, Shanxi [131] | PM10 PM2.1 | 17 | January–February 2017 | 1056 ± 315 937 ± 294 |
China, Urumqi [132] | PM2.5 | 16 | September 2017–September 2018 | 448 |
China, Chengdu [133] | PM10 | 16 | March 2015–February 2016 | 82.0 ± 64.8 |
China, Changchun [134] | PM2.5 | 15 | October–November 2016 | 81.4 ± 46.0 |
China, Harbin [135] | PM2.5 | 16 | June 2017–May 2018 | 86.9 |
China, Lanzhou [136] | PM2.5 | 9 | July 2017–October 2018 | 9.86 |
Japan, Kanazawa [137] | PM2.5 | 9 | April 2017–February 2018 | 0.69 |
Japan, Chiba [138] | PM2.5 | 21 | June 2016–October 2017 | 2.9 |
Japan, Kirishima [139] | PM2.5 | 9 | November–December 2016 | 1.32 (0.36–2.90) |
South Korea, Seoul [140] | PM2.5 | 14 | January–December 2018 | 5.6 ± 7.9 |
South Korea, Gwangju [141] | PM2.5 | 17 | October 2016–April 2017 | 1.04–29.5 |
Vietnam, Hanoi [142] | PM10 | 9 | 2016–2018 | 8.51 |
Singapore, Singapore [143] | PM10 | 16 | May 2015–June 2016 | 0.68–5.97 |
Malaysia, Lumpur [144] | PM2.5 | 16 | June 2015–May 2016 | 2.04 ± 0.28 |
Thailand, Chiang Mai [145] | PM2.5 | 8 | February–April 2016 | 5.88 ± 1.97 |
Qatar, Doha [146] | PM2.5 PM10 | 36 | May–December 2015 | 0.56 0.72 |
Lebanon, Beirut [147] | PM2.5 | 15 | December 2018–October 2019 | 0.95 |
Mongolia, Ulaanbaatar [148] | PM10 | 15 | January 2017 March 2017 September 2017 | 131–773 22.2–531 1.4–54.6 |
Pakistan, Islamabad [149] | PM2.5 PM10 | 16 | January–September 2017 | 25.7 ± 12.0 40.1 ± 16.8 |
India, Jamshedpur [150] | PM2.5 | 16 | December 2016–February 2017 March–May 2017 | 109 ± 18.2 81.1 ± 13.3 |
India, Delhi [151] | PM2.5 | 14 | December 2016–December 2017 | 753 ± 252 |
India, Haryana [151] | PM2.5 | 14 | December 2016–December 2017 | 259 ± 64.6 |
India, Uttar Pradesh [151] | PM2.5 | 14 | December 2016–December 2017 | 535 ± 143 |
India, Pune [152] | PM2.5 PM10 | 16 | March 2015–March 2016 | 342.4 ± 14.3 446.1 ± 25.6 |
Iran, Tehran [153] | PM10 | 16 | February–March 2018 | 213 ± 145 |
Iran, Bushehr [154] | PM2.5 | 16 | December 2016–September 2017 | 0.66–142.3 |
Species a | 1984 b | 1988 c | 1992 d | 1993 e | 1994 f | 1997 g | 1998 h | 1998 i | 2004 j | 2010 k |
---|---|---|---|---|---|---|---|---|---|---|
US EPA 16 PAHs | ||||||||||
Acy | 0.001 | 0.001 | ||||||||
Ace | 0.001 | 0.001 | ||||||||
Flu | 0.001 | 0.001 | ||||||||
Ant | 0.01 | 0.01 | 0.0005 | 0 | ||||||
Phe | 0.001 | 0.00064 | 0.005 | 0 | ||||||
FR | 0.001 | 0.001 | 0.05 | 0.08 | ||||||
Pyr | 0.081 | 0.001 | 0 | 0.001 | 0 | |||||
BaA | 0.013 | 0.145 | 0.1 | 0.1 | 0.1 | 0.014 | 0.005 | 0.1 | 0.2 | |
Chr | 0.001 | 0.0044 | 0.01 | 0.001 | 0.01 | 0.026 | 0.03 | 0.01 | 0.1 | |
BbF | 0.08 | 0.14 | 0.1 | 0.1 | 0.1 | 0.11 | 0.1 | 0.1 | 0.62 | 0.8 |
BkF | 0.004 | 0.066 | 0.1 | 0.01 | 0.1 | 0.037 | 0.05 | 0.1 | 0.17 | 0.03 |
BaP | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
DBA | 0.69 | 1.11 | 5 | 1 | 1 | 0.89 | 1.1 | 10 | ||
IDP | 0.017 | 0.232 | 0.1 | 0.1 | 0.1 | 0.067 | 0.1 | 0.1 | 0.07 | |
BgPe | 0.022 | 0.01 | 0.01 | 0.012 | 0.02 | 0.009 | ||||
Non-priority PAHs | ||||||||||
BcF | 20 | |||||||||
CcdP | 0.023 | 0.1 | 0.012 | 0.02 | 0.4 | |||||
BcP | 0.023 | 0.023 | ||||||||
11H-BbcA | 0.05 | |||||||||
4H-CdefC | 0.3 | |||||||||
BjA | 60 | |||||||||
BeA | 0.8 | |||||||||
BlA | 5 | |||||||||
Per | 0.001 | |||||||||
BjF | 0.061 | 0.1 | 0.045 | 0.05 | 0.1 | 0.52 | 0.3 | |||
BeP | 0.004 | 0.01 | 0 | 0.002 | ||||||
Anth | 0.32 | 0.28 | 0.3 | 0.4 | ||||||
DBacA | 0.1 | 4 | ||||||||
Cor | 0.001 | |||||||||
NeP | 0.3 | |||||||||
DBaeF | 0.9 | |||||||||
DBalP | 1 | 10 | 30 | |||||||
DBaeP | 0.2 | 1 | 0.4 | |||||||
DBaiP | 1.1 | 0.1 | 10 | 12 | 0.6 | |||||
DBahP | 1.2 | 1 | 10 | 11 | 0.9 |
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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. https://doi.org/10.3390/ijerph18042177
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. International Journal of Environmental Research and Public Health. 2021; 18(4):2177. https://doi.org/10.3390/ijerph18042177
Chicago/Turabian StyleYang, Lu, Hao Zhang, Xuan Zhang, Wanli Xing, Yan Wang, Pengchu Bai, Lulu Zhang, Kazuichi Hayakawa, Akira Toriba, and Ning Tang. 2021. "Exposure to Atmospheric Particulate Matter-Bound Polycyclic Aromatic Hydrocarbons and Their Health Effects: A Review" International Journal of Environmental Research and Public Health 18, no. 4: 2177. https://doi.org/10.3390/ijerph18042177