The variables of interest are displayed in Table 2. Among the seven sampling points analyzed, the average concentration of PM10 ranged from 1.12 to 55.85 µg.m-3 and the average concentration of PM2.5 ranged from 0.69 to 34.43 µg.m-3; the concentration of CCs ranged from 0.85 to 816.37 µg.m-3; the thermal discomfort index ranged from 25.31 to 27.18; average noise ranged from 59.87 to 66.81 dB; and average microbiological organisms (MOs) ranged from 61 to 735 CFUs.m-3 for fungi and 142 to 2381.5 CFUs.m-3 for bacteria.
Table 2 – Descriptive statistics of results of each indicator
|
PM10 (µg.m-3)
|
PM2.5
(µg.m-3)
|
CCs
(µg.m-3)
|
MOs
(CFUs.m-3)
|
Noise
(dBA)
|
Thermal comfort (DI)
|
Fungi
|
Bacteria
|
Max
|
55.85
|
34.43
|
816.37
|
735
|
2381.5
|
66.81
|
27.18
|
Mean
|
27.87
|
17.18
|
89.08
|
185.6
|
1069.23
|
63.95
|
26.2
|
Min
|
1.12
|
0.69
|
0.85
|
61.0
|
142.0
|
59.87
|
25.31
|
SD
|
14.84
|
9.15
|
152.95
|
170.7
|
526.21
|
1.61
|
0.49
|
The variables varied considerably among the seven sampling points, especially the chemical (PM and CCs) and biological (MOs) variables of air quality. This variation demonstrates considerable differences among the study sites in terms of the characteristics of the surrounding environment, directly altering the environmental quality of each site.
According to Moratto et al. (2005), the quality of the urban environment is one of the most important aspects for the determination of the quality of life of the population. When considering spaces used to improve the health and wellbeing of individuals, such as public squares and walkways, the environmental quality of these areas must be good enough not to cause any harm to visitors.
Fig.3 shows the average concentration of CCs at each sampling point. The highest concentration (464.41 µg.m-3) was found at P6 in the wet period, followed by P5 in the dry period (238.67 µg.m-3). P6 is located next to a hospital, which may have exerted a direct influence on the high concentration of CCs, as there may have been the excessive use of VOCs, especially formaldehyde, or other substances that may have formed it when emitted within the hospital, substantially increasing CC levels in the local atmosphere, as shown in the studies by Bessoneau et al. (2013) and Hyttinen et al. (2021), who evaluated the concentration of these compounds in various hospitals.
P5 also had a high average concentration of CCs, but in the dry period. This point has a high vehicular traffic flow, which exerts a direct influence on CC levels. Moreover, greater concentrations of CCs were found in the dry period in the majority of points studied, which may be explained by the photochemical reactions that form CCs in the atmosphere and predominate in the dry period. Wang et al. (2007) reported that higher levels of CCs found in the dry period compared to the wet period are attributed to high photochemical production. Moreover, relative humidity is higher in the wet period, which contributes to a reduction in CC levels in the atmosphere.
Sources of CCs include motor vehicles, the evaporation of gasoline, the use of solvents, liquefied natural gas leaks, photochemical processes, industrial emissions and biogenic emissions. Direct emissions from vehicles and other fuel sources are generally the main sources of CCs in the ambient air. Other sources, however, such as the photo-oxidation of VOCs, may contribute to the formation of these compounds, especially on hot days. Previous studies reported that vehicle exhaust was the main source of CCs in the winter (Possanzini et al., 1996; Ho et al., 2002). Liu et al. (2008) reported that vehicle exhaust was the major source of VOCs, accounting for more than 50% of environmental VOCs in three urban locations (Guangzhou, Foshan and Zhongshan). Analyzing measurements taken on a road, Kean et al. (2001) demonstrated that CCs represented 30-60% of VOCs were emitted from diesel-powered vehicles and 3-5% were emitted from gasoline-powered vehicles.
Fig.4 displays the average PM10 and PM2.5 concentrations. Higher PM levels were found in the wet period at all sampling points, as wind speed is much lower in this period (2 km.h-1 on the surface) compared to the dry season (3.5 km.h-1 on the surface) in the city of Fortaleza. Winds are effective at maintaining air quality by dispersing PM (Tiwari et al., 2009; 2013; 2014b). Thus, a higher wind speed is associated with a lower concentration of PM in the local atmosphere.
Automobiles are among the most important sources of PM in the atmosphere of urban centers (Wang et al., 2000; Bogo et al, 2003; Tiwari et al., 2014b). In the present study, the lowest PM concentrations were found at P5, which, despite having intense gasoline-powered vehicular traffic, is an open space with few buildings and good air circulation, facilitating the dispersion of particles by the wind.
Fig.5 displays the levels of fungi and bacteria, revealing no clear predominance between the two seasons. Nonetheless, higher peaks were found in the dry period, particularly for fungi at P2 (587.5 CFUs.m-3) as well as bacteria at P1, P3 and P6 (1631.83, 1288.5 and 1526.16 CFUs.m-3 respectively).
Medrela-Kuder (1991; 2003), Fang et al. (2007), Hameed et al. (2009) and Wang et al. (2010) report that higher levels of microorganisms in the air are found predominantly in the dry period due to the higher temperature, lower relative humidity, higher wind speeds and greater solar radiation. A somewhat higher air temperature, intense solar radiation and lower relative humidity are the main characteristics of the city of Fortaleza and contribute to the survival of microorganisms in the air. According to Cox and Wathes (1995), the high moisture content in bioaerosol particles constitutes potential stress for microorganisms in the air, whereas high wind speeds may be allied with higher concentrations of MOs in the air in some cases. In the present study, the more intense wind speed in the dry period could have contributed to the increase in the Mosin this period due to the resuspension of microorganisms present in greater quantity in the soil.
Physical indicators, noise and thermal comfort are presented in Fig.6. No substantial difference in noise levels were found between seasons. The largest differences were found at P7 (only 2 dBA) and P2 (only 1.5 dBA) between the dry and wet periods. For thermal comfort, a clear predominance in the wet period was found, as higher temperatures (less thermal comfort) were found in this period at all sampling points, especially P1 (34.13 °C).
Previous studies reported a strong association between noise and automobile traffic in urban centers. Nijland et al. (2007), Pandian et al. (2009), Souza & Giunta (2011), Ko et al. (2011) and Silva & Mendes (2012) reported that automobiles on roadways are the main source of noise in cities and that urban morphology exerts an influence on noise levels. Greater exposure to noise occurs at buildings with several stories and lower levels are found in residential parks. According to Mazur et al. (2007), due to their closed construction and central location on main streets, large blocks of buildings are more exposed to high levels of noise in an urban center.
Thermal comfort is influenced mainly by air temperature, wind speed and relative humidity. According to Santos et al. (2011), moisture in the atmosphere serves as a thermal regulator, absorbing heat from the sun, conserving it for a certain period of the day and subsequently returning it to the atmosphere in the form of sensitive heat flow. Thus, greater moisture in the air (more humidity) absorbs more heat. The wet period in the city of Fortaleza is characterized by high humidity and weak winds, which increases thermal discomfort at different points of the city.
The difference in thermal comfort between seasons was highest at P1 (nearly 4 °C). This site is on the Fortaleza waterfront, which is the location of the greatest density of high rises in the city. Indeed, the considerable influence of verticalization on thermal comfort was evident at this site, which, along with the building materials, leads to an increase in temperature and low wind circulation in the wet period, causing the most thermal discomfort found in this study due to the formation of a warmer zone on the walkway. Rocha et al. (2016) reported similar findings for the same sampling points. Greater thermal discomfort at P1 was found in the wet period, which was the only site classified as “tolerable discomfort”.
3.1 Risk to human health
The cancer risk estimate for a 5-year exposure time was made only for the compounds formaldehyde and acetaldehyde, as they are the only CCs with carcinogenic potential according to the IRIS system (US-EPA), and for PM2.5.
Fig. 7 shows the estimated cancer risk for each site studied during the morning and afternoon in the two seasonal periods, first for formaldehyde and then for acetaldehyde. Thus, in terms of the estimated cancer risk for formaldehyde, all the points exceeded the maximum limit set by NIOSH (National Institute for Occupational Safety & Health) for there to be no risk to people's health, especially in the dry period, where there is a higher concentration of these two compounds due to greater photochemical production, as explained above. The WHO limit was exceeded only by P1 (dry), P3 (only during the afternoon in dry period) and P6 (wet). The P6, in the wet period, exceeded the other limits set by the US environmental agency, EPA, and the Brazilian NR-15 standard – which regulates the levels of these compounds only for indoor and occupational environments – offering a high risk to the health of its users. As for estimating the risk of cancer from acetaldehyde, all the points studied were below the limits set by environmental and health bodies (for this reason there are no limits expressed in the graph).
Fig. 7 only shows the estimated cancer risk for men, for both formaldehyde and acetaldehyde. Women have, on average, a longer life expectancy and a lower body weight, thus increasing the chance of developing cancer from inhaling these two compounds over a long period of time. In this study, the risk of cancer for women was found to be 9% higher than for men.
The cancer risk of PM2.5 was estimated by multiplying the CDI by the relative risk (RR). Studies conducted in more than 30 countries have recently revealed that each 10 μg m−3 increase in PM2.5 levels in the air has corresponded to a 9 to 36% increase in lung cancer rates in recent years (Raaschou-Nielsen et al. 2013; Hamra et al. 2014). The International Agency for Research on Cancer (IARC) classified external atmospheric particles (particles suspended in the air of outdoor/open environments) as group 1 carcinogens because these particles cause permanent mutagenesis, heart attacks, diseases related to changes in blood pressure and even premature death (Hamra et al. 2014).
In this study, the highest risk of cancer to PM2.5 was found in P2 during the afternoon in the wet period (Fig. 8). The other two points with a high risk were P6 and P7, also during the wet period and in the afternoon. In the dry period, all the points had a higher risk in the afternoon. This result may be associated with the higher levels of vehicle traffic at these points.
3.2 The most suitable days and hours for physical and recreational activities.
Figures 9 and 10 show the ratios of all parameters evaluated at each studied point, between morning and afternoon and week and weekend. It is possible to see, more clearly, which periods had the highest concentrations/levels.
As for the first parameters of atmospheric pollutants (Fig. 9), it can be seen that there was a predominance of the morning period for CCs with ratios greater than 1, that is, the highest concentrations of the measured parameter were found in this period of the day, and for PM there was a total dominance of the afternoon period (ratios less than 1). Regarding the week/weekend ratio, there was a predominance of the week in the highest concentrations of the three parameters.
For microbiological organisms, fungi and bacteria (Fig. 10), the predominance of periods with higher levels was not as clear as that of the other parameters, however it can be said that there was a slight dominance of the afternoon period, for higher levels of fungi and bacteria (ratios less than 1). As for the week/weekend ratio, it was not possible to state which of the two periods would be better (with lower levels of OMs), since the result, among the seven points studied, was well divided.
Still according to Fig. 10, the ratios of the noise parameter indicated a clear predominance of the afternoon and week periods for the highest levels. As for thermal comfort, there was a total dominance of the afternoon period for the highest degrees (lower thermal comfort) and as for the week/weekend ratio, there was no prevalence of a period among the seven evaluated points, it is not possible to state which it would be more comfortable.
3.3 Points classification according to environmental quality
Table 3 shows the environmental quality of the seven sampling points stratified by season. Five points were classified as “excellent” in the dry period; P1 and P5 were the only exceptions. Moreover, five points were classified as poor in the wet period; P3 and P4 were the only exceptions.
Table 3 – Classification of sampling points based on environmental quality.
The environmental quality results reveal that the dry period in the city of Fortaleza is much more favorable to the health and wellbeing of the population, especially individuals who use public squares and walkways, as the most of sampling points had excellent environmental quality in this period. The second semester of the year (dry period) in Fortaleza has high wind speeds and lower relative humidity compared to the first semester, which assists in improving the environmental quality, especially in terms of air quality and thermal comfort.
P1 and P5 were the only sampling points not to have a classification of “excellent” in either season and, therefore, had the worst environmental quality in the present study. In contrast, P3 and P4 were the only sampling points not to have a classification of “poor” in either season and, therefore, had the best environmental quality in the study.
One factor that may have contributed to the excellent/good environmental quality at P3 and P4 was the considerable vegetation found at the locations. Previous studies conducted by Gomes & Soares (2003), Rocha et al. (2004), Lima Neto et al. (2007), Shams et al. (2009), Freitas et al. (2015) and Rocha et al. (2016) demonstrated the effect of vegetation on minimizing air pollution by gases and particles, attenuating noise levels and improving local thermal comfort by the capacity to increase humidity and lower the temperature. However, vegetation is not always associated with an improvement in air quality; depending on the positioning of the plant cover, gases and particles may be trapped, contributing to atmospheric pollution. Thus, a study is needed prior to the placement of plants in an area.