Angelo Rodio This email address is being protected from spambots. You need JavaScript enabled to view it.1, Francesco Misiti1, Alessandro Zagaglia1, Luca Stabile2, Giorgio Buonanno2, Luigi Fattorini3 

1 Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, 03043 Cassino (FR), Italy
2 Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, 03043 Cassino (FR), Italy
3 Department of Physiology and Pharmacology V. Erspamer, University “La Sapienza” of Rome, 00185 Roma (RM), Italy


Received: January 27, 2022
Revised: April 26, 2022
Accepted: May 15, 2022

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


Download Citation: ||https://doi.org/10.4209/aaqr.220029  

  • Download: PDF


Cite this article:

Rodio, A., Misiti, F., Zagaglia, A., Stabile, L., Buonanno, G., Fattorini, L. (2022). Airborne Ultrafine Particle and Acute Physiological Effects during Maximal Aerobic Power Test. Aerosol Air Qual. Res. 22, 220029. https://doi.org/10.4209/aaqr.220029


HIGHLIGHTS

  • UFPs induce adverse efficiency effects during moderate high-intensity exercise.
  • UFPs exposure during outdoor recreational athletes’ training might pose a health risk.
  • UFPs must be considered in assessing the potential adverse effects of exposure to PM.
 

ABSTRACT


BACKGROUND: The practice of physical exercise in polluted areas could lead to adverse health effects that may contribute to the incidence and/or worsening of respiratory and cardiovascular diseases and some types of cancer.

METHODS: Male recreational cyclists performed tests in a manner randomized crossover in two environmental conditions: low (environmental noise exposure) and high ultrafine particle concentration. For each trial, oxygen consumption (V͘O2), carbon dioxide production (VĊO2), respiratory frequency (Rf), tidal volume (Vt), pulmonary ventilation (V͘E), and mechanical workload (WL) were measured. Gross efficiency (GE) was determined using the ratio between mechanical power output and metabolic power input. Repeated-measures ANOVA was applied to evaluate differences (P < 0.05) between physiological and mechanical parameters and compare oxygen consumption trends in the two scenarios. RESULTS: HR, Rf, and VE values do not show any significant difference. On the contrary, V͘O2peak increased (P < 0.05) under high exposure (41.6 ± 4.31 mL kg–1 min–1), during high-intensity exercise, compared to a low exposure (38.4 ± 4.05 mL kg–1 min–1). V͘O2 and GE show differences (p < 0.05) between low and high ultrafine particle concentration conditions during exercise above 80% WLpeak.

CONCLUSIONS: Present data suggest that high airborne UFPs levels impair recreational cyclists' gross efficiency.


Keywords: Particulate matter, Acute exercise, Oxygen consumption, Mechanical Efficiency, oxygen radicals


1 INTRODUCTION


The World Health Organization recommends a physically active lifestyle for reducing the risk of several diseases such as cardiovascular, metabolic disease, hypertension, type-2 diabetes, cancer, and depression (Bull et al., 2020). The recommendations on physical activity suggest, for people between 18–64 years, a weekly 150 minutes of moderate-intensity aerobic activity (Piercy et al., 2018). The most common aerobic activities, such as walking, running, or cycling, are typically practiced outdoors. Outdoor exercise improves mental well-being and is psychologically rewarding (Manferdelli et al., 2019). However, large segments of the population live in highly populated metropolitan areas, and physical activity occurs in urban microenvironments characterized by high airborne particle levels. Regarding particulate matter (PM), the European Union has set two limit values for PM10 to protect human health. PM10 daily mean values should not exceed 50 µg m–3 more than 35 times in a year, while the PM10 annual mean value should not exceed 40 µg m–3 (European Union, 2008). The adverse health effect induced by PM10 is related to the ability to penetrate the deepest areas of the human respiratory tract. Inhalation and consequent deposition of these elements are strictly associated with the size of the carrying particles: higher deposition fractions in the lungs are characteristics of submicron and ultrafine particles (UFPs) (Buonanno et al., 2011). For the UFPs daily concentrations, there are not yet limits. Previous studies establish that exposure to high airborne particle concentrations environments correlates with several adverse health outcomes such as heart diseases, respiratory disorders, asthma, cancer, and increased mortality rate (Giles and Koehle, 2014; Buonanno et al., 2013; Pope et al., 2009). The practice of physical exercise in polluted urban areas increases the number of particles inhaled as a result of the increased pulmonary activity (Carlisle and Sharp, 2021; Niinimaa et al., 1981). Previous studies suggest avoiding physical exercise in polluted areas due to increased pollutants inhalation (Carlisle and Sharp, 2021; Buonanno et al., 2013; Pope et al., 2009). Acute adverse effects of PM10 (particles with a diameter < 10 µm) were evidenced in predicted maximal oxygen consumption (Gao et al., 2013; Yu et al., 2004) and in female marathon performance (Marr et al., 2010). Furthermore, acute exposure to PM during exercise on a cycle-ergometer impairs maximal accumulated work on a 6-min trial (Marr et al., 2010). This study aimed to evaluate physiological and mechanical parameters, under high UFPs exposure with respect to environmental noise exposure, in healthy and physically active subjects during incremental maximal aerobic tests performed on a cycle ergometer in a fully controlled environmental chamber.

 
2 METHODS


 
2.1 Participants

The University of Cassino and Southern Lazio's Institutional Review Board-Biomedical Section approved this study. All participants signed informed written consent, as previously reported (Rodio and Fattorini, 2014). Fifteen (age was 40.7 ± 6.9 years, stature 1.77 ± 0.07 m, body mass 77.1 ± 11.6 kg) males, active, non-smoking recreational cyclists (Araújo and Scharhag, 2016), were involved in this study. Enrolled subjects were researchers and Ph.D. students at the University of Cassino and Southern Lazio, practicing cycling as amateurs, i.e., athletes cycling an amount of 7 hours a week, corresponding to about 400 hours per year. Enrolled subjects presented a valid medical certificate obtained after a medical assessment following the Italian Protocol for Sports Medicine Rating System. No subject with asthma was included. Each subject avoided high-intensity exercise and alcohol 24 hours before testing, consumption of caffeine 6 hours before, and food or non-water beverages the 2 hours before the trial. All participants were also required to have the same meal before all the tests.

 
2.2 Procedures

Acute effects of high indoor airborne ultrafine particle environmental concentration were evaluated during ramp maximal aerobic power tests compared to environmental noise, defined by the authors as low particle condition and without incense. Low ultrafine particle concentration was recorded in standard indoor conditions. High concentration of airborne ultrafine particles was generated by burning incense, as described, and evaluated by Stabile et al. (2012). Specifically, two incense sticks were kept burning for 15 minutes to maintain a steady-state ultrafine particles concentration level. To determine the participant’s exposure, ultrafine particle concentration levels were monitored using a condensation ultrafine particle counter (CPC TSI 3775, Shoreview MN, USA), assessing concentrations up to 1·107 part. cm–3 of ultrafine particles under 4 nm with a 1-s time resolution and a Dust Track™ DRX Aerosol Monitors Model 8534 (TSI Inc., MN, USA) assessing concentrations of different particulate matter fractions (PM1, PM2.5, PM10). The CPC TSI 3775 was calibrated using a TSI 3068B Aerosol Electrometer measuring NaCl particles generated by a TSI 3940 Aerosol Generator. The Dust Track was calibrated for the PM fractions studied before experimental tests. To carry out a risk assessment related to the exposure to incense airborne particles of the fifteen subjects in the experimental campaign, we applied a modified risk assessment scheme for airborne particles, whose details are reported in (Buonanno et al., 2015) and based on an existing risk assessment model (Sze-To et al., 2012).

This scheme used particle surface area as the dosimetry for hazardous chemicals in the form of UFPs and mass as the dosimetry for super-micron particles. The lung cancer risk characterization equation for each pollutant is:

where ELCRi is the excess lifetime cancer risk of the i-th pollutant, SFi is the inhalation slope factor used to describe the cancer potency of the i-th pollutant, BW is the bodyweight of the receptor, mi is the mass concentration of the i-th pollutant present on the PM10 mass, δS (nm2 day−1) and δM (mg day−1) are the daily particle surface area (S) and mass (M) deposited dose. The conversion coefficient (Cf) was obtained based on exposure to heavy-duty vehicle emissions (Sze-To et al., 2012). It represents the equivalent toxicity of the particle surface area metric expressed as particle mass; it is used since the cancer potency data are referred to as particle mass metric (SF). The Cf was defined as a parameter depending on the physical size rather than the chemical constituent of the particulate matter and, therefore, can also be used for different types of particulate matter (Sze-To et al., 2012).

UFPs concentrations, temperature, and humidity rate were constantly monitored during the trials. Each subject performed two-cycle ergometer tests, separated by a gap of seven days, under low and high airborne UFPs conditions. Physiological parameters were measured to investigate metabolic and respiratory modifications induced by high ultrafine particle exposure. For all the subjects, continuous electrocardiogram monitoring has been carried out (data not shown).

 
2.3 Experimental Test

Tests were carried out in a 48 m3 room at the “Marco Marchetti” Sport and Exercise Physiology laboratory of the University of Cassino and Southern Lazio in spring. Although the exercise performance is reproducible in recreational cyclists on the contrary of less trained participants that exhibit greater variability in performance and pacing. All subjects, to reduce variability, have prior performed a familiarization with the exercise protocol, during which was also identified the mechanical peak workload. Each subject carried out in a manner randomized crossover the low and high exposure condition, interspersed each by 7 days; each trial comprised: i) 30 min environmental exposure at rest ii) physical exercise, including warm-up and recovery for about 30 minutes. All physical trials were performed on a cycle ergometer at constant friction (Monark 894E peak Bike, Vansbro, Sweden™), and respiratory and metabolic parameters measurements were carried out by a breath-by-breath metabolimeter (Cosmed K4 b2, Rome, Italy™) (Rodio et al., 2008). According to the legislation, cardiac activity was monitored all along with the trial by using an electrocardiogram, to detect possible signs of health risk in the act (Cosmed Quark 12cpet, Rome, Italy) (Buonanno et al., 2016). Each progressive maximal aerobic power test was structured as follows: 5 minutes of oxygen uptake (V͘O2) measurement in an orthostatic posture before physical exercise; 3 minutes of warm-up executed at 60 RPM with a 1 kg workload (~60 watt); exertion phase conducted at 60 RPM and workload (WL) increase of 0.1 kg every 20 seconds (~18 watts for 1 min) up to exhaustion; recovery phase sitting on the stationary bike for 10 minutes. The workload was increased until to occur two of the following three conditions were considered indicative of exhaustion obtained: i) V͘O2 value not higher than 150 mL1 kg1 min1, ii) respiratory exchange ratio (RER) equal to 1.15 or above, iii) achieving 95% of theoretical maximal heart rate. Peak oxygen consumption values were used to characterize the fitness level of the subjects, as previously reported (Piercy et al., 2018). Each subject performed trial in low ultrafine particle concentration first, then a second trial was carried out in the other condition after one week. Maximum WL value (WLpeak) achieved in Low conditions was set as the WLpeak also for the second one (High conditions), to evaluate physiological differences (i.e., oxygen kinetic) in both conditions at the same values of WLpeak and its fractions (100%, 90%, 80%, 60%, and 30%). Moreover, gross efficiency (GE) was determined through the ratio between mechanical power output (W) and metabolic input (W). To calculate this parameter, V͘O2 was converted to Joule (J) by using caloric equivalents for oxygen, in the function of relative RER, and a conversion factor of 4.184 kJ per kcal.

 
2.4 Statistical Analysis

Metabolic, cardiovascular, respiratory, and mechanical parameters measured throughout the trials were compared to investigate physiological modifications induced by the two different environmental conditions. A repeated-measures ANOVA was used to compare values of physiological and mechanical parameters measured during tests and to compare oxygen consumption (V͘O2) trends in the two different scenarios. Data were previously tested through a Shapiro-Wilk test evaluating their normality and the pertinence of the repeated-measures ANOVA. The results were significant at P < 0.05. Physiological parameters values mean and SD in each different atmosphere were calculated. Statistical analyses were realized using Stat View version 5.01 (Sas Institute, Inc., USA).

 
3 RESULTS AND DISCUSSION


Based on the concentrations of the major pollutants on the incense particles (See et al., 2007; Yang et al., 2013) and of the inhalation slope factors obtained from the Office of Environmental Health Hazard Assessment, a lung cancer risk for each participant for all the tests equal to 108 was estimated. This value is three orders of magnitude less than the accepted threshold value from the Environmental Protection Agency US: therefore, the overall risk of participants can be considered as negligible. In Table 1, UFPs number concentrations and PM10 concentrations obtained during experimental trials were summarized. Ultrafine particles number (expressed in part. cm–3) was 33.2 times higher in high concentration conditions than low (environmental noise). As well as for particle number, PM10 concentrations (mg m–3) were about 92 times higher in the high than low scenario. Respiratory parameters (VE; Vt; Rf) values obtained during tests in low and high UFPs exposure conditions are reported in Table 2. No significant differences in Rf, Vt, and VE have been detected at different percentages of WLpeak in two conditions. Table 3 shows V͘O2, VĊO2, and RER mean values. By splitting exercise into two phases, light-moderate intensity, below 80% of WL peak, and moderate-high intensity, above it, we could observe different physiological responses. In the first phase, from 0% to 80% of WLpeak, no differences between the two environmental conditions were found. In the second phase, while exercise increased in intensity and definitively over the ventilatory threshold, a diverging trend, at 80%, 90%, and 100% of WLpeak, was detected for V͘O2 and RER statistically differences (p < 0.05); the V͘O2 and RER trend values are reported in Table 3 and resulted increasing in high UFPs condition. No differences were found for VĊO2 all over the ramp tests, even during high-intensity exercise. Table 4 summarize slope and intercepts values representing the oxygen consumption kinetics that have been obtained in two experimental conditions. For both, slope and intercept, significant differences (P < 0.05) were found in polluted conditions meaning that high particles concentrations induce an increment in oxygen consumption. Table 5 reports mean values for gross efficiency (GE) at different workloads (%WLpeak). The results obtained show that the GE decreased (P < 0.05) at workloads above 80% of WLpeak in high compared to low ultrafine particle conditions. This result is due to the different behavior of the V͘O2, which significantly increased in high conditions above 80% of WLpeak at the same mechanical output (WL), that was fixed experimentally. We could observe that above 80% of WLpeak, GE reduced about of 7 and 8% at 90 and 100% of WLpeak respectively in the high UFPs condition.

Table 1. Average (sd) ultrafine particle number concentrations.

Table 2. Respiratory indices mean values and sd at different workloads (%WLpeak).

 Table 3. Metabolic indices mean values and sd at different workloads (%WLpeak).

Table 4. Slope and intercepts values representing the oxygen consumption kinetics in high and low experimental conditions.

Table 5. Mean and sd values for gross efficiency (GE) at different workloads (%WLpeak).

The aim of this study was to determine metabolic and respiratory acute effects, in environmental controlled, induced by UFPs concentrations during high-intensity exercise. Subjects were all physically active and healthy; their fitness level, corrected for age, ranged from average to good, following Physical Activity Guidelines for Americans (Piercy et al., 2018). Their average V͘O2max was about 40 mL kg–1 min–1. In this study, UFPs mean concentration in low exposure scenarios was 34 times lower than other conditions. To the best of our knowledge, this is the first time that physiological parameters have been assessed throughout maximal aerobic ramp test, starting from low to reach maximal intensity exercise, fixing the same maximum workload, in a fully controlled environmental chamber and with negligible risk for the subjects’ health. Splitting exercise in two phases, no significant differences for VĊO2 were found, showing that the anaerobic contribution was similar during light-moderate and moderate-high exercise intensity. As for oxygen consumption, a paradoxical situation emerged. Where exercise intensity increased from light to moderate, V͘O2 and mechanical power increased proportionally, the V͘O2 behaviors were comparable for the two scenarios. On the contrary, while exercise intensified, above 80% of WLpeak, a higher oxygen consumption under high UFPs exposure compared to low was observed. A higher V͘O2 in high UFPs conditions indicates better aerobic power and, consequently, a positive effect. But considering the ratio between mechanical and metabolic work (GE), the ultrafine particle-rich environment proved to be detrimental. Higher oxygen consumption at the same workload means a negative effect induced by UFPs on gross efficiency, i.e., on performance. Considering that GE is defined as one of the most important functional abilities of athletes (Coyle, 1995), these results suggest that physical performance is impaired by high ultrafine particles concentration levels, especially if the physical activity is carried out mostly at low particulate environments. As mentioned earlier, a higher oxygen consumption under high ultrafine particle concentrations was assessed, but only during sustained exercise above the ventilatory threshold, the performance suffers a remarkable decrease in efficiency of 5% higher. It is well known that in mitochondria a small quote of electrons escapes from the mitochondrial oxidative chain generating reactive oxidant species (ROS). At rest conditions, 2% of electrons generate ROS (Barja et al., 2004; Powers Jackson, 2008). Furthermore, increasing oxygen consumption at several increasing workloads can result in elevated ROS production and oxidative stress (Allen and Tresini, 2000). Previous studies suggest that physical exercise under airborne UFPs exposure increases ROS production and oxidative stress (Kelly, 2003; Brunekreef and Holgate, 2002). So, the vertiginous/accelerated/extremely rapid increment in V͘O2 emerging under high exposure conditions may be justified by considering the synergy of airborne UFPs exposure and high-intensity exercise (above 80% of WLpeak) could have amplified ROS production. In this study, tests have been performed in a controlled environmental chamber, where concentrations of UFPs were constant. 


4 CONCLUSIONS


Present data suggest that athletes' gross efficiency is impaired in polluted areas and support the notion that results achieved in sports competitions carried out in urban environments (i.e., marathons, cycling, 20- and 50-km walk) could be affected by high airborne UFPs levels (El Helou et al., 2012; Kargarfard et al., 2011; Marr et al., 2010) Furthermore, recreational athletes should train in a low pollution environment since ultrafine particles (mainly UFPs) boost ROS production during high-intensity exercise, which could in turn have an impact on health (Marr and Ely, 2010; Jacobs et al., 2010; Vinzents et al., 2005; Tauler et al., 2002). It should be also noted that the UFPs concentrations level, achieved in this study could be the basis for future studies to identify the safe environmental level for UFPs as for PM10.

 
ACKNOWLEDGMENTS


We thank the amateur athletes involved in this study and the “Marco Marchetti” laboratory’s team for the technical assistance provided.


REFERENCES


  1. Allen, R.G., Tresini, M. (2000). Oxidative stress and gene regulation. Free Radical Biol. Med. 28, 463–499. https://doi.org/10.1016/s0891-5849(99)00242-7

  2. Araújo, C.G.S., Scharhag, J. (2016). Athlete: A working definition for medical and health sciences research. Scand. J. Med. Sci. Sports 26, 4–7. https://doi.org/10.1111/sms.12632

  3. Barja, G. (2004). Free radicals and aging. Trends Neurosci. 257, 1–6. https://doi.org10.1016/j.​tins.2004.07.005

  4. Brunekreef, B., Holgate, S.T. (2002). Air pollution and health. Lancet 360, 1233–1242. https://doi.org/10.1016/S0140-6736(02)11274-8

  5. Bull, F.C., Al-Ansari, S.S., Biddle, S., Borodulin, K., Buman, M.P., Cardon, G., Carty, C., Chaput, J.P., Chastin, S., Chou, R., Dempsey, P.C., DiPietro, L., Ekelund, U., Firth, J., Friedenreich, C.M., Garcia, L., Gichu, M., Jago, R., Katzmarzyk, P.T., Lambert, E., et al. (2020). World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br. J. Sports Med. 54, 1451–1462. https://doi.org/10.1136/bjsports-2020-102955

  6. Buonanno, G., Dell’Isola, M., Stabile, L., Viola, A. (2011). Critical aspects of the uncertainty budget in the gravimetric PM measurements. Measurement 44, 139–147. https://doi.org/10.1016/j.​measurement.2010.09.037

  7. Buonanno, G., Marks, G., Morawska, L. (2013). Health effects of daily airborne particle dose in children: Direct association between personal dose and respiratory health effects. Environ. Pollut. 180, 246–250. https://doi.org/10.1016/j.envpol.2013.05.039

  8. Buonanno, G., Giovinco, G., Morawska, L., Stabile, L. (2015). Lung cancer risk of airborne particles for Italian population. Environ. Res. 142, 443–451. https://doi.org/10.1016/j.envres.2015.07.​019

  9. Buonanno, G., Stabile, L., Lecce, D., Rodio, A., Fuoco, Fernanda, C. (2016). Physiological responses to acute airborne particle exposure during maximal aerobic power. Aerosol air Qual. Res. 16, 1922–1930. https://doi.org/10.4209/aaqr.2015.04.0208

  10. Carlisle, A.J., Sharp, N.C. (2001). Exercise and outdoor ambient air pollution. Br. J. Sports Med. 35, 214–222. https://doi.org/10.1136/bjsm.35.4.214

  11. Coyle, E.F. (1995). Integration of the physiological factors determining endurance performance ability. Exerc. Sport Sci. Rev. 23, 25–64. https://doi.org/10.1249/00003677-199500230-00004

  12. El Helou, N., Tafflet, M., Berthelot, G., Tolaini, J., Marc, A., Guillaume, M., Hausswirth, C., Toussaint, J.F. (2012). Impact of environmental parameters on marathon running performance. PLoS ONE 7, e37407. https://doi.org/10.1371/journal.pone.0037407

  13. European Union (2008). Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe. Official Journal of the European Union L152/I, http://data.europa.eu/eli/dir/2008/50/oj

  14. Gao, Y., Chan, E.Y.Y., Zhu, Y., Wong, T.W. (2013). Adverse effect of outdoor air pollution on cardiorespiratory fitness in Chinese children. Atmos. Environ. 64, 10–17. https://doi.org/​10.1016/j.atmosenv.2012.09.063

  15. Giles, L.V., Koehle, M.S. (2014). The health effects of exercising in air pollution. Sports Med. 44, 223–249. https://doi.org/10.1007/s40279-013-0108-z

  16. Jacobs, L., Nawrot, T.S., de Geus, B., Meeusen, R., Degraeuwe, B., Bernard, A., Sughis, M., Nemery, B., Panis, L.I. (2010). Subclinical responses in healthy cyclists briefly exposed to traffic-related air pollution: An intervention study. Environ. Health 9, 64. https://doi.org/10.1186/​1476-069X-9-64

  17. Kargarfard, M., Poursafa, P., Rezanejad, S., Mousavinasab, F. (2011). Effects of exercise in polluted air on the aerobic power, serum lactate level and cell blood count of active individuals. Int. J. Prev. Med. 2, 145–150.

  18. Kelly, F.J. (2003). Oxidative stress: Its role in air pollution and adverse health effects. Occup. Environ. Med. 60, 612–616. https://doi.org/10.1136/oem.60.8.612

  19. Manferdelli, G., La Torre, A., Codella, R. (2019). Outdoor physical activity bears multiple benefits to health and society. J. Sports Med. Phys. Fitness 59. https://doi.org/10.23736/S0022-4707.18.08771-6

  20. Marr, L.C., Ely, M.R. (2010). Effect of air pollution on marathon running performance. Med. Sci. Sports Exercise 42, 585–591. https://doi.org/10.1249/MSS.0b013e3181b84a85

  21. Niinimaa, V., Cole, P., Mintz, S., Shephard, R.J. (1981). Oronasal distribution of respiratory airflow. Respir. Physiol. 43, 69–75. https://doi.org/10.1016/0034-5687(81)90089-X

  22. Piercy, K.L., Troiano, R.P., Ballard, R.M., Carlson, S.A., Fulton, J.E., Galuska, D.A., George, S.M., Olson, R.D. (2018). The physical activity guidelines for Americans. JAMA 320, 2020. https://doi.org/10.1001/jama.2018.14854

  23. Pope, C.A., Ezzati, M., Dockery, D.W. (2009). Fine-particulate air pollution and life expectancy in the United States. N. Engl. J. Med. 360, 376–386. https://doi.org/10.1056/NEJMsa0805646

  24. Powers, S.K., Jackson, M.J. (2008). Exercise-induced oxidative stress: Cellular mechanisms and impact on muscle force production. Physiol. Rev. 88, 1243–1276. https://doi.org/10.1152/​physrev.00031.2007

  25. Rodio, A., Quattrini, F.M., Fattorini, L., Egidi, F., Faiola, F., Pittiglio, G. (2008). Power output and metabolic response in multiple Wingate tests performed with arms. Med. Sport 61, 21–28.

  26. Rodio, A., Fattorini, L. (2014). Downhill walking to improve lower limb strength in healthy young adults. Eur. J. Sport Sci. 14, 806–812. https://doi.org/10.1080/17461391.2014.908958

  27. See, S.W., Balasubramanian, R., Joshi, U.M. (2007). Physical characteristics of nanoparticles emitted from incense smoke. Sci. Technol. Adv. Mater. 8, 25–32. https://doi.org/10.1016/j.​stam.2006.11.016

  28. Stabile, L., Fuoco, F.C., Buonanno, G. (2012). Characteristics of particles and black carbon emitted by combustion of incenses, candles, and anti-mosquito products. Build. Environ. 56, 184–191. https://doi.org/10.1016/j.buildenv.2012.03.005

  29. Sze-To, G.N., Wu, C.L., Chao, C.Y.H., Wan, M.P., Chan, T.C. (2012). Exposure and cancer risk toward cooking-generated ultrafine and coarse particles in Hong Kong homes. HVAC&R Res. J. 18, 204–216. https://doi.org/10.1080/10789669.2011.598443

  30. Tauler, P., Aguiló, A., Fuentespina, E., Tur, J., Pons, A. (2002). Diet supplementation with vitamin E, vitamin C and β-carotene cocktail enhances basal neutrophil antioxidant enzymes in athletes. Pflug. Arch. Eur. J. Physiol. 443, 791–797. https://doi.org/10.1007/s00424-001-0770-0

  31. Vinzents, P.S., Møller, P., Sørensen, M., Knudsen, L.E., Hertel, O., Jensen, F.P., Schibye, B., Loft, S. (2005). Personal exposure to ultrafine particles and oxidative DNA damage. Environ. Health Perspect. 113, 1485–1490. https://doi.org/10.1289/ehp.7562

  32. Yang, T.T., Lin, S.T., Hung, H.F., Shie, R.H., Wu, J.J. (2013). Effect of relative humidity on polycyclic aromatic hydrocarbon emissions from smoldering incense. Aerosol Air Qual. Res. 13, 662–671. https://doi.org/10.4209/aaqr.2012.07.0182

  33. Yu, I.T., Wong, T.W., Liu, H.J. (2004). Impact of air pollution on cardiopulmonary fitness in schoolchildren. J. Occup. Environ. Med. 46, 946–952. https://doi:00043764-200409000-00008


Share this article with your colleagues 

 

Subscribe to our Newsletter 

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

6.5
2021CiteScore
 
 
77st percentile
Powered by
Scopus
 
   SCImago Journal & Country Rank

2021 Impact Factor: 4.53
5-Year Impact Factor: 3.668

Aerosol and Air Quality Research partners with Publons

Aerosol and Air Quality Research partners with Publons

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

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