The study was carried out in a region of intense commerce located in the city of Fortaleza/Ceará, Brazil. The region was then divided into three different routes called: 1) greater perimeter; 2) average perimeter; and 3) smaller perimeter. The region of analysis is known for the great commercialization of products and offer of services, besides having the main access roads to the beaches of the east region of Fortaleza, presence of roads with intense flow of vehicles, access roads to noble neighborhoods of Fortaleza and mainly the intense circulation of people and vehicles of public and private transport.

For analysis of atmospheric pollutants in the region, the route of each perimeter was divided into monitoring points with intervals of approximately 500 m between them. Atmospheric analyzes were performed over a period of 5 minutes at each monitoring point. The perimeters were divided into points according to Figure 1.

The larger perimeter, with approximately 10.5 km, was divided into 17 monitoring points; the average perimeter, with approximately 3.7 km, in 9 points; and the smaller perimeter, with approximately 1.4 km, in 4 points, totaling 30 monitoring points. For the transfer during the analyses between the 30 points, a motorcycle was used.

This study was carried out to determine the feasibility of the analysis methodology developed, in addition to verifying whether the environment is harmful in terms of the exposure of people in that region to pollutants. The study was

carried out between November/December 2021 (for O₃ analyses) and April/May 2022 (for other analyses), when the atmospheric pollutant indices were analyzed in the three different perimeters of the center of Fortaleza and in their respective points of contact monitoring.

The collections were carried out during the period of 5 minutes in each of the 30 points of the three perimeters (Major-Middle-Smaller), during three consecutive days (Tuesday, Wednesday and Thursday), considered these for being typical days compared to Monday or Friday. Each perimeter was analyzed at 7:00 am, 12:00 noon and 17:00 pm.

Figure 1 represents the paths covered, where A characterizes the largest perimeter and 17 analysis points, B corresponds to the average perimeter and its 9 points, and C corresponds to the smallest perimeter with its 4 analysis points. This region is marked by the large commerce that operates strongly in the area, including schools, colleges, squares, hospitals, clinics, tram stations, homes and churches, among others. It is evident a large number of people and exposed to the intense flow of vehicles often marked by extensive traffic jams. Not to mention unexpected facts, for example, rain and collisions between vehicles.

For pollutant analysis, a TEMTOP M2000-Elitech meter was used. This consists of a portable device with a high precision electrochemical sensor, laser particle sensor and carbon dioxide sensor based on Non-Dispersive Infrared Analyzers (NDIR). This device detects particles of carbon dioxide and formaldehyde in the air and transforms the concentration of air pollutants into visual data. It is possible to detect the indices of the following particles and factors: PM_2.5, PM₁₀, CO₂, HCHO.

Together for the static analyses, the concentrations of ozone (O₃) were determined using the continuous analyzer model 202 from 2B Technologies in the pilot project. This analyzer uses an absorption cell that absorbs at a wavelength of 254 nm and has a pollutant detection range ranging from low ppb (~1.5 ppb accuracy) to 250,000 ppb (0 - 250 ppm).

The spatial representation of the dispersion of analyzed pollutants was carried out through interpolated assistance. Interpolation is a method for calculating or finding a point between known values, based on experiments or a function. The need for this process arises due to the limitations of the nodal sensors employed in identifying the value of each analyzed pollutant. Various types of interpolation can be applied, such as linear interpolation, quadratic interpolation, and cubic spline interpolation.

In this study, cubic spline interpolation was used, where a point between four points is sought or calculated. The technique maximizes the use of available data, capturing non-linear variations between sampling points with adjustable precision and smoothing, presenting a more subtle appearance when compared to other interpolation techniques (Aràndiga et al., 2022; Tayebi et al., 2022; Roe & Brooks, 2021) .

Building on the static analyses, it is crucial to integrate urban planning and management considerations to address the average concentration levels of pollutants within each perimeter (Major - Medium - Minor) at different times (7:00 am, 12:00 noon, and 5:00 pm) as illustrated in Figures 2-4.

Examining the concentrations of PM_2.5 and PM₁₀ in the larger perimeter at 7:00 am, 12:00 noon, and 17:00 pm (Figure 2), it becomes imperative to align these findings with urban planning initiatives. A comparison with the standards set by the National Council for the Environment (CONAMA) in resolution 491/2018 and the updated World Health Organization (WHO) guidelines for the year 2021 reveals crucial insights into the urban environment’s air quality.

Analyzing variations in PM_2.5 concentrations in the largest perimeter emphasizes the need for spatial planning, especially noting that point 3 exhibits the highest average concentration at 17:00 pm. Similarly, for PM₁₀, concentration increases along the route, albeit within the acceptable limits established by CONAMA and WHO.

In the larger perimeter, point 1 holds strategic importance at the intersection of Avenida de Bezerra de Menezes, marking the exit loop of Parque Araxá and São Gerardo neighborhoods and the commencement of Centro neighborhood. Urban planning should consider this location’s dynamics, which includes large supermarket chains, mechanical workshops, São Sebastião Market, known for its vibrant fruit and vegetable trade, commercial buildings, day care centers, small shops, residences, a bike lane, and an exclusive bus lane.

This perimeter’s characteristics, such as the presence of faculties, a technical school, and residences, underscore the need for thoughtful urban planning to accommodate diverse activities. The flow of people, particularly during the beginning and end of classes, highlights the importance of synchronized transportation planning. Noteworthy establishments like the School for Sailors’ Apprentices, various shops, restaurants, bars, and dental centers further emphasize the diverse urban landscape and necessitate comprehensive spatial management.

In Figure 2, the portrayal of average concentrations of CO₂, HCHO, and O₃ in the larger perimeter at various times emphasizes the importance of integrating

urban planning and spatial management strategies to address these dynamic concentrations. The levels of external CO₂ concentrations were compared with the limit recommended by RN 02/2003 of the Brazilian Association of Refrigeration, Air Conditioning, Ventilation and Heating (ABRAVA), which corresponds to 500 ppm, according to ABRAVA, this is a traffic indicator very intense in urban areas, validating the influence of the large vehicular flow on the levels and concentrations of CO₂.

Regarding O₃ concentrations, the levels were compared with the limits established by the National Council for the Environment (CONAMA), according to resolution 491/2018 and the limit standards updated in 2021 recommended by the World Health Organization (WHO). Regarding the levels of HCHO, the averages of their concentrations were compared with limits determined by the WHO for indoor environments, due to the absence of specific legislation for levels of concentrations in outdoor areas. The highest CO₂ averages in the larger perimeter were evidenced at points 8, 12 and 13 at 7:00 am and at points 3, 10, 12 and 16 at 17:00 pm. Regarding O₃ and HCHO, they maintained their concentrations below the legislated standards that were compared, whereas CO₂ exceeded the limits recommended by ABRAVA.

In the characterization of the points, it is possible to identify elements that cause changes in concentration levels. Point 3 is characterized by a large shopping center with small shopkeepers that attracts a large number of people ranging from small wholesalers and retailers to customers in general, intense movement most of the day, schools, squares and small commercial buildings are also present. Point 8 corresponds to the Central Market of Fortaleza, other elements present are churches, few residential buildings, event houses, most of the local commerce is from street vendors and some wholesale establishments, this space has wide two-way lanes, thus vehicles that transit in this area come from both coastal neighborhoods and neighborhoods further away from the city center, traffic lights and speed cameras control the traffic in the area. Point 10 is located on Avenida Monsenhor Tabosa, an area characterized by the presence of large buildings, hotels, supermarkets, restaurants, bars, beauty centers, churches, schools, the presence of street vendors is not significant, the commerce in general is physical stores and quite miscellaneous.

Characterizing specific points in the larger perimeter reveals elements influencing concentration levels, such as the bustling activity at Point 3, the commercial and traffic dynamics at Point 8, and the diverse urban landscape at Point 10. These characterizations highlight the importance of spatial management and planning to accommodate various activities.

At point 13, the CO₂ level changed at 7:00 am, this point located on a one-way street that also gives access to the main avenues in the surroundings of the center, there are schools, faculties, hospitals, small clinics, residences and commercial buildings, in addition to multi-sports gyms, local commerce is dominated by vehicle workshops, restaurants and snack bars.

As for the time of 12:00 noon in the afternoon on the higher perimeter, the levels of concentrations of CO₂, O₃ and HCHO pollutants remained at the established standards.

Figure 3 shows the average concentrations obtained in the average perimeter at 7:00 am, 12:00 noon and 17:00 pm. Identifying changes in CO₂ concentrations along the route of the average perimeter, particularly at points 18, 19, 20, 22, 24, and 25, reinforces the need for spatial management strategies to address peak concentrations, especially at 7:00 am. The dominance of high concentrations at points 18, 22, and 24 at 12:00 noon and points 20 and 22 at 17:00 pm emphasizes the importance of strategic urban planning interventions. Point 22, in particular, demonstrates consistently high averages across all analysis times, suggesting the necessity for focused urban management.

For HCHO, the concentration variations at points 19 and 23 underscore the importance of targeted planning measures, especially during noon and 7:00 am, to ensure compliance with established standards. Conversely, O₃ did not exceed the limits recommended by CONAMA.

Regarding the variations in PM_2.5 concentrations in the average perimeter,

point 22 presented the highest average concentration at 17:00 pm, exceeding the limit determined by the WHO, however the average concentrations did not exceed the standards defined by CONAMA, regarding PM10 its averages suffered an increase in concentration along the route, however the concentration values did not exceed the limits established by the limit standards required by CONAMA and WHO.

Figure 4 shows the average concentrations obtained in the smaller perimeter

at 7:00 am, 12:00 noon and 17:00 pm. It is possible to identify changes in the levels of CO₂ concentrations, where point 27 had the highest concentration level at 12:00 noon and 15:00 pm and point 29 had the highest concentration at 7:00 am, that is, both points exceeded the limits established by ABRAVA. In relation to the average concentrations of HCHO at 12:00 noon, all points exceeded the established limits when compared to the WHO levels, while at other times all points remained below the established. The mean concentrations of O₃ at the three times did not exceed the limit determined by CONAMA.

Regarding the average concentrations of PM_2.5 and PM₁₀ in the smaller perimeter, no point exceeded the standards established by CONAMA and WHO, at the time of analysis.

Due to the high volatility of HCHO, the most affected are those who handle products that contain it in large quantities. High concentrations cause shortness of breath, breathing difficulties, headaches, eye irritation, pulmonary edema, laryngitis, bronchitis and pneumonia (Mendell et al., 2007) .

Thus, humans exposed to these levels of HCHO can be affected in the eye region and upper airways (nasal cavity, oral cavity, pharynx and larynx). In addition, eye and upper airway irritations are more common features of people who live or work in environments where materials containing formaldehyde compounds are used in large amounts (Sakamoto et al., 1999) .

The Air Pollution Monitoring Project was created in 2014 with the objective of meeting the demands and programming actions of circulation and traffic of urban transport in a city that reduce the influence on local atmospheric conditions, modifying the functional structures in the transport system allowing changes in air quality (PLANMOB, 2015) .

The traffic problem is a reflection of the few adjustments made to Fortaleza’s road network in view of the accelerated growth in the use of private cars. Measures aimed at planning and managing transport in the city were insufficient, aggravating the current situation. The private vehicle fleet increases every year, due to the increase in travel times, the decrease in fluidity, incidents or unexpected events on the road, accidents with victims and even the stress caused by traffic jams (PLANMOB, 2015) .

In this way, changes in concentrations can be potentiated with the increase in traffic jams along the perimeters, as vehicles in congestion consume more fuel, that is, to operate when not in motion, the vehicle’s engine needs fuel that burns and releases polluting gases. Together, there is a constant problem regarding traffic laws in Fortaleza, which results in traffic accidents and troubled relations between transport and drivers (PLANMOB, 2015) .

Even knowing the types of vehicles, it is also necessary to define the pollutants to be analyzed, where it is necessary to identify the behavior and reaction of each pollutant when interacting with other substances present in the atmosphere. For local studies, pollutants that impact the health of the population can be prioritized, as at a global level, concern for the environment as a whole can prioritize the reduction of other types of pollutants (DIAS et al., 2016) .

The mitigation of atmospheric pollution effects in large urban centers represents a complex and critical challenge, requiring an integrated approach to urban planning and management. As highlighted by Hanif et al. (2022) , increasing urbanization and the growth of industrial activities have significantly contributed to the emission of atmospheric pollutants, directly impacting air quality. In this context, effective urban planning strategies become imperative to address this issue, considering the population density and the diversity of emission sources present in urban areas.

Efficient management of urban areas requires the implementation of policies that consider not only pollution sources but also sustainable development, urban mobility, and the promotion of green spaces. The introduction of low-emission zones, the expansion of public transportation networks, and the creation of urban green zones are examples of practices that not only reduce pollutant emissions but also promote a better quality of life for urban inhabitants (Flanagan et al., 2022; Verbeek & Hincks, 2022) . Therefore, it is essential to recognize the interconnection between urban planning and air quality, integrating strategies that address the complex dynamics of modern cities towards more sustainable and healthy urban environments.

Figure 5 shows 2D interpolations of the examined pollutants in the analysis region. Color changes become visible when pollutant data reaches a specific threshold value. Each type of pollutant exhibits a visually distinct map based on the analyzed data results.

Upon evaluation, it is observed that PM_2.5 and PM₁₀ share focal points at 3 and 22, indicating higher concentrations of pollutants at these locations. This suggests that these points generate positive gradients for the dispersion of these pollutants into other areas. This trend is supported by the values presented in figures 2 and 3 for these points, with a notable emphasis on the 17:00 pm period.

Regarding O₃, point 27 appears to be responsible for its dispersion in the region, with concentration values reaching 57 μg/cm³ on the contour plots. Higher O₃ values were observed at points 19 and 22 during morning periods (Figure 2 and Figure 3), suggesting a more intense dispersion gradient during this time.

In the analysis of HCHO, contour plots of 210, 180, 150, and 120 μg/cm³ were found around point 28 at radial distances of less than 0.2 km between these curves, indicating a pronounced positive dispersion gradient. Average values exceeding 150 μg/cm³ of HCHO were found at points along the smaller perimeter during the 12:00 noon period (Figure 3), supporting the trend presented in the 2D interpolations of the region’s points.

Interpolations in 2D of CO₂ unveiled five diffusion points for these pollutants (points 3, 12, 18, 22, and 27), with concentrations exceeding 500 ppm. The spreading dynamics of CO₂ in the region appeared chaotic, as contour plots, although originating from a relatively constant value, were directly influenced by the radial distance from the source. The dispersion gradient was more pronounced at points 27 and 22, being the main vectors for this pollutant in the region.

Although 2D interpolations successfully captured an average dispersal trend of the analyzed pollutants, external factors such as wind speed, diffusion coefficient of each pollutant, and the region’s topology add complexity to predicting this behavior. Nevertheless, cubic spline interpolation modeling proves effective in recording the average concentration of each assessed pollutant in the region.

The temporal tracking of each analysis was crucial for proposing boundary conditions for the two-dimensional mapping.

The analysis of the inhaled dose of MP (MP_2.5 and MP₁₀) was estimated based on: 1) the average concentration of MP in each of the three analyzed perimeters; 2) physiological characteristics; and 3) the exposure time (44 h/month) of an adult working in the environment of the analyzed perimeters.

According to the analysis of the concentrations of MP_2.5 and MP₁₀ (Figure 6), variability of the pulmonary dose received by humans was estimated, generating more realistic deposition results (Li et al., 2016) . The lung structures are composed of subdivisions, which are classified by regions, such as: extrathoracic, tracheobronchial and pulmonary regions (Hussain et al., 2011) , aiming to calculate the deposition of particles in the respiratory system (Upper, tracheobronchial and alveolar) of adults (Koblinger, 1990) .

The highest concentrations of PM_2.5 and PM₁₀ deposited in the respiratory system were obtained in the largest perimeter at 17:00 pm. The lowest concentrations of PM_2.5 and PM₁₀ deposited in the respiratory system were also obtained in the larger perimeter at 12:00 noon.

In addition, we observed that most of the deposition of the inhaled particles (PM_2.5 and PM₁₀) is deposited in the upper region, in relation to the tracheobronchial and alveolar regions, due to the diameter of the PM_2.5 particles where they can be deeply fixed in the respiratory system reaching the lungs. For this reason, they are called thoracic particles PM₁₀, on the other hand, can pass through the nasal and oral cavities and penetrate to the larynx. In the case of ultrafine particles, PM_0.1 can pass from the pulmonary alveoli and reach the circulatory system (Brito et al., 2018) . The particles can come from both biogenic and anthropogenic sources, where anthropogenic sources are generally composed of ultrafine particles, while biogenic sources are commonly composed of coarse particles (Avino et al., 2016) .

Much of the air pollution from human particles is present in urban centers, coming from vehicular combustion (Karagulian et al., 2015) . Diesel vehicles are the most worrisome compared to other automobiles, as their emissions occur mainly in the ultra-thin size range (Kittelson, 1998; Kittelson et al., 2002) . It is worth mentioning that public transport is one of the diesel-powered vehicles and is quite present on the perimeter roads. According to Burtscher (2005) , the particles emitted in the burning of diesel vary between 1 nm and 1 μm, and more than 90% are smaller than 0.050 μm.

The vast majority of these particles are agglomerates consisting mainly of spherical primary particles of about 15 to 40 nm in diameter. Another critical factor of the particles emitted in the burning of diesel is due to the large surface area they have and, for this reason, they can absorb several compounds suspended in the air that can be toxic, mutagenic and carcinogenic (Cohen & Nikula, 1999; Oravisjärvi et al., 2011) .

The risks to human health arising from atmospheric pollutants evaluated, above all, by studies carried out in urban areas, concerned with atmospheric emissions from industrial or vehicular origin. Many studies adopt the conceptual framework of human exposure assessment. Exposure consists of contact between the person and a specific concentration of environmental contaminant, in a certain period of time. Human beings are constantly exposed to pollutants present in the atmosphere, personal exposure is the presence of a pollutant in the breathing zone of an individual (Ribeiro & Assunção, 2002) .

Regarding the calculation of the inhaled dose per body mass, respiratory parameters of men and women aged 20 to 39 years were considered, using the concentrations of PM_2.5 and PM₁₀ measured at each of the perimeters. As the inhaled dose is proportional to the exposure time, considering an individual who works (176 h/month) in the vicinity of each perimeter, where he is daily exposed to pollutants from that environment. The concentration of the inhaled doses is shown in Figure 7. To determine the inhaled dose of MP_2.5 and MP₁₀, it was performed from the average of the three analysis times for each perimeter.

According to the averages calculated in each perimeter, higher concentrations of inhaled dose are observed in the smaller perimeter and for the lowest concentrations of inhaled dose in the medium perimeter. The risk of mortality related to exposure to PM_2.5 (Li et al., 2018) , among these, the increase in cardiovascular causes and diseases (Kim et al., 2020) . Regarding exposure to PM₁₀, evidence was found between exposure to this pollutant and the risk of lung cancer (Consonni et al., 2018) . Aerobic exercise practitioners can lead to a higher inhaled dose, in addition, children also receive potentially greater dose than adults as they have greater ventilation by body mass and are generally more active and spend more time outdoors (Commitee of the Environmental, 1996) .