Ecosystem Services Provided by an Urban Green Space in Timișoara (Romania): Linking Urban Vegetation with Air Quality and Cooling Effects

Abstract

This study was conducted in an urban park in a temperate-continental city of Europe (Timișoara, Romania) and aimed to investigate the contribution of urban vegetation in maintaining air quality and mitigating the heat in the analyzed city. The following air parameters were monitored: fine particulate matter PM_2.5, coarse particulate matter PM₁₀, AQI (Air Quality Index) (resulted from PM_2.5 and PM₁₀), particle number, air temperature, relative air humidity, TVOC (total volatile organic compounds), and HCHO (formaldehyde). The results of this study show that urban vegetation remains a reliable factor in reducing PM_2.5 and PM₁₀ in city air and in keeping the AQI within the limits corresponding to good air quality, but also that relative air humidity counteracts the contribution of vegetation in achieving this goal. Inside the park, the HCHO concentration increased by up to 4–5 times compared to the outside, and this increase was not caused by vehicle traffic but rather by the photochemical reactions generating HCHO. Regarding the cooling effect on air temperature, the studied green space did not exhibit this effect, as the air temperature inside it increased by up to 1–6 °C compared to the outside. Our results contrast with the general perception that urban parks and green spaces are cooler islands within the cities and draw attention to the fact that having a green space in a city does not necessarily mean achieving environmental goals, such as reducing the heat risk of cities. Based on the results, we consider that the main limitations in achieving these objectives were the park’s small size (88 hectares) and its morphology and architecture resulting from the integration of the species that compose it. It follows from these data that it is not enough for an urban green space to be established, but its design must be combined with urban morphology strategies if the heat mitigation effect is to be achieved and the cooling benefits are to be maximized in cities.

1. Introduction

Urban green spaces represent the connection between humans and nature in cities. The way people’s emotional reactions are influenced by accessing green spaces, as well as the social consequences resulting from this connection, has been a topic of interest, especially in recent years. Surveys of the urban population have shown that city dwellers primarily access urban green spaces for reasons related to recreation and spending leisure time in an area with natural elements, but also because of the need to access a cooler area during the summer, as well as because of the belief that urban green spaces are, within cities, islands with clean air, or at least with cleaner air than the surrounding areas [1]. It follows from this that the general perception of city dwellers is that urban green spaces are places for recreation and means for ensuring air quality and thermal comfort in cities in the context of climate change and the urban warming that is so strongly felt in urban environments.

Policies to ensure air quality in areas inhabited by humans are diverse, but the nature-based ones are by far the most implementable and feasible, mainly due to the non-static and continuously dynamic nature of this environmental factor, which is why other remedial solutions are less applicable. It thus becomes evident that, on a global scale, the only truly viable option for ensuring air quality is self-purification, which involves the contribution of biological factors in achieving this result. Most studies on this topic have been conducted in urban environments, as these areas have multiple major sources of air pollution, and because a large part of the human population resides in cities (over 70% in Europe and America), and it is predicted that by 2050, more than 70% of the world’s population will be urban [2]. The use of vegetation as a tool to obtain quality air in cities has been widely studied in many parts of the world [3,4,5]. Most of the studies approach many industrialized urban areas of the world with the aim to highlight the role of urban vegetation in providing ecosystem services that ensure urban air quality. Thus, the results of research in the field to date have shown that urban vegetation, especially woody vegetation, is able to extract and sequester the atmospheric carbon dioxide and to retain and trap the airborne particulate matter or other air pollutants [6]. Also, the urban vegetation can act like a protective barrier between pollutants and their sources and the population [7]. To achieve these goals, numerous factors are decisive. Some of these are vegetation-related, such as canopy size, leaf area and shape [7], stomata characteristics [7], trichome presence [7], intercellular spaces available for gas diffusion in the case of gaseous pollutants [8], evapotranspiration, and leaf architecture and morphology in generating the shading effect. However, other factors pertain to chemical and physical processes occurring both at the plant level and in its surrounding environment. Therefore, some approaches to the role of urban vegetation in ensuring air quality look at the impact on the adjacent microclimate [9] or on the local climate of the site. Thus, it results that the potential of plants in pollution mitigation in urban areas is a species-specific mechanism. Urban studies have shown that plants have the ability to capture atmospheric pollutants based on species-specific physiological and morphological characteristics that differentiate them in terms of efficiency, making them, from this point of view, more or less preferable for inclusion in urban green space planning. For example, some studies [10] have shown that mature trees with large canopies are major contributors in optimizing and regulating the ecosystem services in cities, while large and open urban green spaces with extensive natural vegetation provide multi-functionality in regulating services [11]. Leaf morphology and microstructure influence the retention patterns of the pollutants and also their removal with fallen precipitation or with wind. Therefore, in urban green planning, it is important to select urban vegetation by estimating species contribution to air purification according to the meteorological conditions of the zone. Climatic patterns are also important. Several studies [12] have shown that, in the removal process of the pollutants from plant leaves, the rainfall phase is more influential than other factors, such as particle diameter or particle adherence to the leaf. Meteorological conditions significantly influence the atmospheric pollution levels, affecting the dispersion, transport, and accumulation of pollutants. Essential meteorological factors that intervene in these processes include thermal inversions, wind speed and direction, atmospheric humidity, and precipitation. In the case of thermal inversions, if a warmer air layer is situated above a cooler, denser air layer that contains pollutants, it prevents the dispersion of pollutants and traps them in the lower layer, potentially increasing local pollution. Urban vegetation can mitigate this phenomenon by ensuring more efficient local air circulation through evapotranspiration processes and by shading the ground, but also as an effect of the vertical disposition of individuals of different heights.

Wind speed and direction play an important role in the transport and dispersion of pollutants.

Strong winds help dilute and remove particulate pollutants, reducing their concentrations in a given area. However, strong winds can also cause surface erosion of buildings in cities, increasing levels of pollutants such as airborne particulate matter. Low wind speeds can also impact urban air quality by favoring air stagnation and keeping pollutants in certain areas for longer periods, resulting in a higher local exposure risk.

Besides the effect on pollutant capture and air phytoremediation, the urban vegetation can emit biogenic substances with supporting roles in human health, such as biogenic volatile organic compounds (VOC), strengthening the public’s and authorities’ conviction of the necessity of having a reasonable area of green space per inhabitant in cities. The World Health Organization (WHO) recommends a minimum surface of green space of 9 m² per person and an ideal surface of 50 m² per person [13], whereas it considers the physical accessibility of urban green spaces by residents within a short distance, a 5 min walk, or a distance of up to 300 m to be acceptable. Also, for climatic purposes, the WHO recommends a minimum width of green corridors of 50 m, ideally over 300 m [14].

Another important ecosystem service provided by urban green spaces is their critical role in mitigating the effect of urban heating, thus contributing to urban resilience. The urban resilience could be increased when, for establishing urban parks, the most suitable species [15] are used to reach this goal, such as native or alien species, species resistant to drought stress, or long-life species. The urban vegetation contributes to energy saving in cities by enhancing the thermal performance of the buildings [16] and thus representing an unconventional and sustainable solution for cooling in the densely populated areas.

The intrinsic relationship existing for a long time between humans and nature generated their strong feeling of biophilia [17] towards other living beings in the global ecosystem, which also creates the special need of city dwellers to connect with nature through urban green spaces. Studies have shown the psychological, emotional, and social benefits of urban green parks [18] for those who access them, through sensory experiences and interactions (visual, auditory, olfactory, and even tactile) that benefit human health and well-being.

In light of the above-exposed arguments, the research aimed to investigate the contribution of an urban green space in maintaining air quality and mitigating the warming in a Romanian city, as related to its surrounding environment, in order to reveal the ecosystem services provided by the urban green spaces in urban areas. This study brings data about the importance of green spaces in the urban matrix and about the ecosystem services provided by urban vegetation. The results highlight that urban vegetation is a reliable factor in maintaining air quality but also draw attention to the fact that simply having green spaces in cities does not necessarily mean achieving environmental objectives, such as reducing the urban heat risk; therefore, urban morphology strategies must be implemented to maximize cooling benefits and effectively mitigate heat.

2. Materials and Methods

2.1. Research Site

The research was carried out in the Central Park „Anton von Scudier” in downtown Timișoara (Figure 1), Romania (45°45′05″ N, 21°13′16″ E).

This urban green space has a temperate-continental climate, covers an area of 87,663 m², and is one of the oldest parks in Timișoara, being established in 1880 by order of General Anton von Scudier (an Austro-Hungarian officer of German origin who served as a military governor of Timișoara, known for his military career and contributions to the city’s development, and who lived between 1818 and 1885). This study monitored 9 sample points (SPs) noted as SP1, SP2, SP3, SP4, SP5, SP6, SP7, SP8, and SP9. These sample points were established in relation to the park’s boundary line, as follows: SP1—outside the park, 93 m from the park border; SP2—outside the park, 55 m from the park border; SP3—on the park border; SP4—inside the park, 10 m from the park border; SP5—inside the park, 20 m from the park border; SP6—inside the park, 30 m from the park border; SP7—inside the park, 164 m from the park border; SP8—inside the park, 275 m from the park border; and SP9—outside the park, 583 m from the park border. Sample point SP9 was chosen at a greater distance from the park because it was intended for it to be located both far from vegetation and enclosed by buildings to determine if there are similarities or differences in the monitored parameters between the vegetated environment and the built-up, vegetation-free environment.

2.2. Research Methodology

Air quality monitoring was conducted over four consecutive days at the end of August, 19–22 August 2024 (working days, Monday to Thursday), between 12:00 and 14:00, at nine fixed points (Figure 1). The monitoring days were labeled as Day 1, Day 2, Day 3, and Day 4. The measurements were performed using a Temtop LKC-1000 Series Air Quality Monitor (Elitech Technology Inc., San Jose, CA, USA) [19]. This is an air quality monitoring tool, a low-cost sensor capable of measuring a variety of essential parameters for the assessment of environmental conditions. Low-cost sensors provide real-time air monitoring and highly localized air information that is accurate despite their low cost [20]. Also, low-cost and accessible instruments [21,22,23] that are at the same time portable [23,24] have been shown to be reliable in air quality monitoring. This device used for this research relies on laser scattering technology for measuring air particulate matter (PM_2.5 and PM₁₀) and electrochemical or photoionization sensors for detecting air gases such as formaldehyde (HCHO) and total volatile organic compounds (TVOC). The air temperature and air humidity are measured using integrated digital sensors. This instrument was suitable for the intended purpose of this research because it uses high-precision sensors and has a compact size (177 × 65.5 × 32 mm), which makes it conveniently portable, and regarding the operating conditions, the device functions optimally at temperatures ranging from 0 to 50 °C and at an relative air humidity of 0 to 90%. Additionally, the device is designated to operate at a standard atmospheric pressure (1 atm). The following air parameters were monitored with this device: fine particulate matter PM_2.5 (with aerodynamic diameter < 2.5 μm), coarse particulate matter PM₁₀ (with aerodynamic diameter < 10 μm), air temperature, relative air humidity, TVOC (total volatile organic compounds), and HCHO (formaldehyde). In addition, the Air Quality Index (AQI) and the particle number were monitored, both being indicators derived from the corroboration of the values recorded for PM_2.5 and PM₁₀. The Air Quality Index (AQI) is an indicator used to communicate air quality to the public in a format easily understood by a wide audience. The Temtop LKC-1000 Series Air Quality Monitor measures the particle number as an air indicator different from the sum of particles PM_2.5 and PM₁₀, because it also includes particles of other, smaller sizes. Although the detailed specifications regarding the exact size range of particles detectable by this device are not stated in the supplied specifications, in general, similar laser sensors can detect particles ranging from approximately 0.3 µm to 10 µm [25]. This does not mean that we know the exact size range the device used in this research is capable of measuring, but it suggests that it may measure particles smaller than those in the PM_2.5 and PM₁₀ categories, i.e., very fine particles.

The device was used to measure air parameters at the same height from the ground (approximately 1 m above the ground) on all four days, and samples were taken from the same point on each day. Three samples were taken from each point at equidistant time intervals, every 2 min (the device operated for 2 min, after which it was paused to record the data). The measurements were performed at a height of 1 m from ground level. The monitored parameters and the measurement characteristics of the air quality monitor (measurement range and resolution) are presented in

Table 1. Measurement characteristics of the air quality monitor (measurement range and resolution) [26].

Measurement Characteristics	Air Parameter
	PM2.5	PM10	HCHO	TVOC	Air Temperature	Relative Air Humidity
Measurement range	0–999 μg/m3	0–999 μg/m3	0–5 mg/m3	0–5 mg/m3	0–50 °C	0–90%
Measurement resolution	0.1 μg/m3	0.1 μg/m3	0.01 mg/m3	0.01 mg/m3	0.01 °C	0.01%

.

2.3. Results Interpretation

For the interpretation of the recorded values, there are multiple assessment scales. The device used reports the recorded data with reference to the standards of the United States Environmental Protection Agency (EPA) only for the parameters PM_2.5, PM₁₀, and AQI (

Table 2. Reference levels and air quality ratings for the parameters PM_2.5, PM₁₀, and AQI (Air Quality Index).

Air Quality Parameter
PM2.5 (μg/m3)					PM10 (μg/m3)					AQI
United States Environmental Protection Agency (EPA) Standards [26]		Air Quality Guidelines of the World Health Organization [28]		Romanian Standard (Law no. 104/15 June 2011) [29]	United States Environmental Protection Agency (EPA) Standards [26]		Air Quality Guidelines of the World Health Organization [28]		Romanian Standard (Law no. 104/15 June 2011) [29]	United States Environmental Protection Agency (EPA) Standards [26]
PM2.5 Value (μg/m3)	Air quality level	PM2.5 Value (μg/m3)		20 µg/m3—Annual limit value for human health protection, which must be respected throughout the entire calendar year	PM10 Value (μg/m3)	Air quality level	PM10 Value (μg/m3)		PM10 Value (μg/m3)	AQI Value	Air quality level
≤12	Good	5 (Annual)	15 (24 h)		≤54.9	Good	15 (Annual)	45 (24 h)	50 µg/m3—Daily limit value for human health protection, which must not be exceeded more than 35 days a year 40 µg/m3—Annual limit value for human health protection, this being the value that must be respected throughout the entire calendar year	≤50	Good
12.1–35.4	Moderate				55–154.9	Moderate				51–100	Moderate
35.5–55.4	Unhealthy for Sensitive Groups				155–254.9	Unhealthy for Sensitive Groups				101–150	Unhealthy for Sensitive Groups
55.5–150.4	Unhealthy				255–354.9	Unhealthy				151–200	Unhealthy
150.5–250.4	Very Unhealthy				355–424.9	Very Unhealthy				201–300	Very Unhealthy
≥250.5	Hazardous				≥425					≥301	Hazardous

) [26], while for the parameters TVOC and HCHO, it follows the Air Quality Guidelines of the World Health Organization (WHO) (

Table 3. Reference levels and air quality ratings for formaldehyde (HCHO) and TVOC concentrations [26,27].

Air Quality Parameter
TVOC (mg/m3)				HCHO (mg/m3)
United States Environmental Protection Agency (EPA) Standards [26]		Air Quality Guidelines of the World Health Organization [27]		Air Quality Guidelines of the World Health Organization [27]			Romanian Standard (Law no. 104/15 June 2011; Directive 2004/107/CE) [29]
TVOC Value (mg/m3)	Air quality rating	TVOC Value (mg/m3)		HCHO Value (mg/m3)			HCHO Value (mg/m3)
≤0.5	Healthy	Annual	24 h	Annual	24 h	30 min.	≤0.1
				-	≤0.1	≤0.1
>0.5	Unhealthy	-	0.3–0.5 mg/m3	-	>0.1	>0.1

) [26,27]. However, for interpreting the results obtained in this study, to ensure consistency in interpretation and because WHO standards are more restrictive and therefore more relevant for assessing the impact of the measured values on human health (compared to Romanian standards in Table 2 and Table 3), it was decided that reporting the analyzed parameters to the WHO-recommended standards would be more appropriate (exception: air temperature, relative air humidity, and AQI, this last one being interpreted according to EPA standards—Table 2) [27,28].

For the interpretation of HCHO and TVOC values, some clarifications are necessary. The WHO provides recommendations for maximum permissible limits for HCHO only for indoor air (Table 3) [27], while for TVOC, it recommends a range of 0.3–0.5 mg/m³ [27]. In Romania, there is legislation that regulates permissible limits for HCHO in the air (Law No. 104 of 15 June 2011) [29], which aligns with European Union standards (Directive 2004/107/EC of the European Parliament and of the Council of 15 December 2004) [30]. According to this European directive, the annual concentration limit for HCHO in the air is 0.1 mg/m³ (equivalent to 100 µg/m³), i.e., the same as that recommended by the WHO (Table 3) and the value to which the measured HCHO levels in this study were referenced. This value represents the maximum permissible long-term concentration of HCHO in the air over a period of one year. If this limit is exceeded in the long term, adverse effects on human health may occur, and public health protection measures must be implemented. Regarding TVOC, there is no specific national regulation in Romania that imposes a certain limit in outdoor ambient air, similar to the limits for PM₁₀ and PM_2.5 or for HCHO. However, European regulations (Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008) [31] influence the monitoring and management of TVOC emissions in the air, and these are applicable in Romania under environmental legislation. However, this directive also does not specify a certain concentration threshold for TVOC in the air. However, since VOCs are considered a group of chemical pollutants that can affect human health, they are monitored within the air quality monitoring system, and the interpretation of this parameter’s values is made according to WHO recommendations (Table 3).

Regarding AQI, Romania does not have specific legislation regulating precise values for this air parameter. However, AQI is a concept used to assess air quality, and it is also utilized in Romania to inform the public about pollution levels and associated risks through various platforms. The AQI is an air quality index with multiple calculation methods across different countries. In this study, the AQI measured by the Temtop LKC-1000 device is derived exclusively from the measured PM_2.5 and PM₁₀ values, and its interpretation was made according to WHO standards (Table 2).

As for the total number of particles measured by the Temtop LKC-1000 Series Air Quality Monitor used in this study, there is no standardized maximum allowable limit expressed in particles per liter of air (pcs/L). This is because air quality standards typically focus on the mass of suspended particles (PM_2.5 and PM₁₀), expressed in µg/m³. The limit values for interpreting PM_2.5 and PM₁₀ levels therefore refer to particle mass and not to the total number of particles. Since the number of particles and their mass do not have a simple direct relationship (as particles of different sizes contribute differently to the total mass), there are no regulated standards for the total number of particles per liter of air. Regarding particulate matter, the PM_2.5 and PM₁₀ limit values for ambient air quality in force in Romania (according to Law No. 104 of 15 June 2011) (Table 2) were not considered in this study. This is because they are less stringent than those recommended by the WHO, and we believe they downplay the concern that should be maintained regarding ambient air quality for the protection of human health.

Measurements were conducted over four consecutive weekdays to capture periods of intense human activity at the same time intervals, at the same height, and in the same locations, allowing for the observation of the evolution and modification of the analyzed parameters. Since weather conditions varied on certain days, they were taken into account in the interpretation of results. Pearson correlations (p < 0.05) were analyzed to determine whether the measured factors influenced each other and whether any relationships existed between them. Additionally, statistically significant differences (paired-samples t-test, p < 0.05) were examined between the recorded values at different depths within the park and outside of it. Graphs were created using Microsoft Office Excel (2010), and statistical analysis was performed using IBM SPSS Statistics version 28.0.

3. Results and Discussion

The measured values of the air parameters are presented in

Table A1. Air quality parameters in the monitoring sample points, within the analyzed period.

Monitoring Date	Sample Point (SP)	Air Parameter
		PM2.5 (μg/m3)	PM10 (μg/m3)	Air Temperature (°C)	Relative Air Humidity (%)	AQI	HCHO (mg/m3)	TVOC (mg/m3)	Number of Particles
Day 1	SP1—outside the park 93 m from park border	8.86 ±3.23	14.33 ±4.80	32.90 ±0.26	39.10 ±0.43	36.33 ±12.74	0.013 ±0.005	0.04 ±0.04	1393.66 ±453.18
	SP2—outside the park 55 m from park border	9.66 ±2.71	15.00 ±4.50	34.83 ±0.50	38.60 ±0.40	40.00 ±11.53	0.03 ±0.010	0.13 ±0.03	1473.00 ±359.63
	SP3—on the park border	6.83 ±0.49	11.66 ±0.58	37.50 ±0.62	34.13 ±0.51	28.00 ±1.73	0.02 ±0.01	0.10 ±0.04	1151.66 ±102.92
	SP4—inside the park 10 m from border	7.03 ±0.86	11.13 ±0.46	38.76 ±0.30	34.10 ±0.10	28.66 ±3.51	0.04 ±0.00	0.18 ±0.00	1087.33 ±122.83
	SP5—inside the park 20 m from border	5.53 ±0.40	8.86 ±0.70	38.86 ±0.11	34.13 ±0.55	22.66 ±1.52	0.05 ±0.00	0.21 ±0.01	914.66 ±8.38
	SP6—inside the park 30 m from border	7.33 ±1.05	11.86 ±1.66	38.13 ±0.15	33.86 ±0.95	30.00 ±4.58	0.03 ±0.005	0.17 ±0.02	1203.66 ±172.81
	SP7—inside the park 164 m from border	5.73 ±0.96	9.40 ±1.67	36.90 ±0.10	34.03 ±0.05	23.33 ±4.04	0.03 ±0.01	0.15 ±0.03	894.00 ±164.83
	SP8—inside the park 275 m from border	4.96 ±0.50	8.33 ±1.45	35.06 ±0.20	37.30 ±0.70	20.33 ±2.51	0.04 ±0.005	0.18 ±0.01	859.33 ±116.42
	SP9—outside the park 583 m from border	6.63 ±1.96	11.23 ±3.61	36.56 ±0.92	35.13 ±1.68	27.00 ±7.81	0.01 ±0.005	0.07 ±0.01	1045.66 ±281.03
Day 2	SP1—outside the park 93 m from park border	15.23 ±1.82	26.06 ±3.18	30.63 ±0.50	46.40 ±0.30	57.00 ±3.60	0.01 ±0.00	0.04 ±0.01	2308.66 ±273.63
	SP2—outside the park 55 m from park border	11.66 ±0.50	19.26 ±1.02	32.00 ±0.20	44.70 ±0.45	48.33 ±2.51	0.02 ±0.00	0.08 ±0.01	1816.66 ±101.63
	SP3—on the park border	10.50 ±1.70	16.86 ±1.87	36.50 ±1.17	40.73 ±1.49	43.33 ±7.09	0.02 ±0.005	0.13 ±0.00	1613.66 ±262.8
	SP4—inside the park 10 m from border	10.90 ±0.90	17.66 ±1.70	38.46 ±0.60	37.60 ±0.95	45.00 ±4.00	0.03 ±0.005	0.15 ±0.01	1682.33 ±174.61
	SP5—inside the park 20 m from border	10.33 ±1.61	16.93 ±2.45	37.66 ±1.15	37.30 ±0.79	42.33 ±7.02	0.03 ±0.005	0.15 ±0.01	1654.66 ±204.39
	SP6—inside the park 30 m from border	10.30 ±0.78	16.90 ±0.72	35.00 ±0.30	40.20 ±0.78	43.00 ±1.73	0.03 ±0.005	0.16 ±0.02	1663.33 ±105.64
	SP7—inside the park 164 m from border	7.76 ±1.90	14.40 ±1.30	36.60 ±1.27	38.60 ±1.90	34.66 ±3.78	0.02 ±0.005	0.11 ±0.01	1306.00 ±110.43
	SP8—inside the park 275 m from border	8.13 ±1.15	10.53 ±1.89	32.76 ±0.35	43.10 ±0.70	27.66 ±6.11	0.03 ±0.00	0.13 ±0.01	1039.00 ±208.51
	SP9—outside the park 583 m from border	9.56 ±1.20	16.26 ±1.80	33.56 ±0.80	43.13 ±1.68	39.33 ±5.03	0.01 ±0.005	0.07 ±0.02	1541.00 ±125.03
Day 3	SP1—outside the park 93 m from park border	20.33 ±8.05	33.50 ±14.70	32.26 ±2.02	47.73 ±3.69	70.00 ±19.97	0.01 ±0.00	0.01 ±0.01	3109.00 ±1229.73
	SP2—outside the park 55 m from park border	10.96 ±1.00	18.10 ±2.06	33.46 ±0.25	45.10 ±0.80	45.00 ±4.00	0.01 ±0.00	0.06 ±0.01	1736.33 ±172.63
	SP3—on the park border	9.96 ±0.85	16.96 ±2.05	35.83 ±1.32	41.26 ±3.05	40.66 ±3.21	0.01 ±0.005	0.08 ±0.02	1527.66 ±173.09
	SP4—inside the park 10 m from border	11.16 ±1.95	16.10 ±4,58	37.96 ±0.15	38.16 ±0.72	45.33 ±7.50	0.02 ±0.005	0.11 ±0.01	1736.66 ±305.78
	SP5—inside the park 20 m from border	10.13 ±0.15	16.90 ±0.34	37.20 ±0.17	39.30 ±0.10	41.33 ±0,57	0.02 ±0.005	0.12 ±0.01	1576.33 ±48.8
	SP6—inside the park 30 m from border	10.10 ±0.98	16.36 ±1.75	36.30 ±0.90	40.70 ±1.15	41.33 ±4.16	0.03 ±0.005	0.15 ±0.01	1583.33 ±163.72
	SP7—inside the park 164 m from border	8.56 ±1.07	14.20 ±1.60	37.76 ±2.10	38.00 ±2.23	35.00 ±4.35	0.02 ±0.00	0.10 ±0.01	1315.00 ±186.67
	SP8—inside the park 275 m from border	10.86 ±1.42	18.50 ±2.26	35.03 ±1.05	39.66 ±0.66	45.00 ±6.08	0.03 ±0.00	0.14 ±0.01	1740.00 ±218.86
	SP9—outside the park 583 m from border	12.93 ±0.55	20.70 ±1.37	35.33 ±2.01	38.33 ±2.81	51.66 ±1.15	0.01 ±0.005	0.08 ±0.01	1938.66 ±80.32
Day 4	SP1—outside the park 93 m from park border	23.26 ±0.32	39.63 ±0.98	27.56 ±0.15	61.10 ±0.26	74.00 ±1.00	0.01 ±0.00	0.04 ±0.01	3551.00 ±47.46
	SP2—outside the park 55 m from park border	16.70 ±1.73	28.40 ±3.73	32.23 ±1.71	53.63 ±3.46	60.00 ±3.60	0.01 ±0.00	0.02 ±0.01	2571.66 ±278.5
	SP3—on the park border	17.63 ±4.25	29.83 ±7.57	32.90 ±1.76	50.63 ±1.92	62.00 ±8.71	0.01 ±0.005	0.07 ±0.01	2690.33 ±597.53
	SP4—inside the park 10 m from border	15.80 ±2.83	26.63 ±4.16	32.76 ±0.90	51.03 ±1.00	58.33 ±5.85	0.01 ±0.005	0.04 ±0.01	2400.66 ±433.96
	SP5—inside the park 20 m from border	14.80 ±0.30	24.70 ±1.68	32.03 ±0.80	51.06 ±1.32	56.66 ±0.57	0.02 ±0.00	0.08 ±0.01	2254.33 ±122.78
	SP6—inside the park 30 m from border	13.40 ±1.15	23.06 ±1.97	30.16 ±0.30	54.40 ±0.52	53.00 ±2.00	0.02 ±0.00	0.09 ±0.01	2069.00 ±173.51
	SP7—inside the park 164 m from border	16.76 ±0.05	29.20 ±0.52	33.56 ±1.04	49.06 ±1.68	60.66 ±0.57	0.01 ±0.005	0.05 ±0.01	2620.66 ±26.63
	SP8—inside the park 275 m from border	14.46 ±3.02	25.70 ±5.12	29.60 ±1.15	55.06 ±2.45	56.00 ±6.24	0.02 ±0.00	0.08 ±0.01	2436.00 ±484.90
	SP9—outside the park 583 m from border	18.63 ±5.29	31.83 ±8.94	30.76 ±1.41	51.36 ±3.35	64.33 ±11.37	0.01 ±0.00	0.03 ±0.02	2861.66 ±794.31

, by monitoring days and sample points (SP1–SP9).

3.1. Particulate Matter PM_2.5

It was observed that on the first day of monitoring, for PM_2.5, there is a decreasing trend in its concentration as one moves deeper into the park (Figure 2). Measurement points SP1–SP2 were located outside the park, in areas with high traffic and car congestion, and they served as control points against which the recorded values were compared. Measurement point SP3 was located right at the edge of the park, at the park entrance, and it was the first point where a significant decrease in PM_2.5 was observed on Day 1 compared to points SP1 and SP2, with reductions of 22.92% and 29.3%, respectively (Figure 2).

Entering deeper into the park, oscillations in PM_2.5 values were observed, but the overall trend was a decrease compared to the values measured outside the park. At a distance of 20 m inside the park (SP5), it was found that PM_2.5 values had decreased by 42.76% compared to the more distant exterior point (SP2) located 55 m away from the park boundary. A point of interest was located in the middle of the vegetation, 275 m from the park entrance (SP8), where a significant decrease in PM_2.5 values was observed compared to the park’s exterior (SP2) (

Table A2. Statistically significant differences (paired-samples t-test, p < 0.05) between sample points (SPs) regarding the values of the measured air parameters within the analyzed period.

Crt. No.	Statistically significant differences ([aired-samples t-test, p < 0.05) regarding the air quality parameters between sample points (SPs)—Day 1
	Air Parameter
	PM2.5	PM10	AQI	Particle Number	Relative Air Humidity	Air Temperature	TVOC	HCHO
1	SP2–SP7	SP2–SP7	SP2–SP7	SP2–SP4	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP4
2	SP2–SP8	SP3–SP5	SP2–SP8	SP3–SP5	SP1–SP3	SP1–SP3	SP1–SP4	SP1–SP5
3	SP3–SP5	SP3–SP8	SP3–SP5	SP5–SP6	SP1–SP4	SP1–SP4	SP1–SP5	SP1–SP6
4	SP3–SP8	SP4–SP5	SP3–SP8	-	SP1–SP5	SP1–SP5	SP1–SP6	SP1–SP7
5	SP4–SP7	SP4–SP8	SP4–SP7	-	SP1–SP6	SP1–SP6	SP1–SP7	SP2–SP5
6	SP4–SP8	SP5–SP6	SP4–SP8	-	SP1–SP7	SP1–SP7	SP1–SP8	SP2–SP9
7	SP5–SP6	-	SP5–SP6	-	SP1–SP8	SP1–SP8	SP2–SP5	SP3–SP5
8	SP6–SP8	-	-	-	SP1–SP9	SP1–SP9	SP2–SP8	SP3–SP6
9	-	-	-	-	SP2–SP3	SP2–SP3	SP2–SP9	SP4–SP9
10	-	-	-	-	SP2–SP4	SP2–SP4	SP3–SP4	SP5–SP6
11	-	-	-	-	SP2–SP5	SP2–SP5	SP3–SP5	SP5–SP9
12	-	-	-	-	SP2–SP6	SP2–SP6	SP3–SP6	SP6–SP9
13	-	-	-	-	SP2–SP7	SP2–SP7	SP4–SP5	SP7–SP9
14	-	-	-	-	SP2–SP8	SP2–SP9	SP4–SP9	SP8–SP9
15	-	-	-	-	SP2–SP9	SP3–SP4	SP5–SP6	-
16	-	-	-	-	SP3–SP8	SP3–SP5	SP5–SP9	-
17	-	-	-	-	SP4–SP8	SP3–SP8	SP6–SP9	-
18	-	-	-	-	SP5–SP8	SP3–SP9	SP7–SP9	-
19	-	-	-	-	SP6–SP8	SP4–SP7	SP8–SP9	-
20	-	-	-	-	SP6–SP9	SP4–SP8	-	-
21	-	-	-	-	SP7–SP8	SP4–SP9	-	-
22	-	-	-	-	-	SP5–SP6	-	-
23	-	-	-	-	-	SP5–SP7	-	-
24	-	-	-	-	-	SP5–SP8	-	-
25	-	-	-	-	-	SP5–SP9	-	-
26	-	-	-	-	-	SP6–SP7	-	-
27	-	-	-	-	-	SP6–SP8	-	-
28	-	-	-	-	-	SP7–SP8	-	-
No.	Statistically significant differences (paired-samples t-test, p < 0.05) regarding the air quality parameters between sample points (SPs)—Day 2
	Air parameter
	PM2.5	PM10	AQI	Particle Number	Relative Air Humidity	Air Temperature	TVOC	HCHO
1	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP3
2	SP1–SP3	SP1–SP3	SP1–SP3	SP1–SP3	SP1–SP3	SP1–SP3	SP1–SP3	SP1–SP4
3	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP5
4	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP6
5	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP7
6	SP1–SP7	SP1–SP7	SP1–SP7	SP1–SP7	SP1–SP7	SP1–SP7	SP1–SP7	SP2–SP4
7	SP1–SP8	SP1–SP8	SP1–SP8	SP1–SP8	SP1–SP8	SP1–SP8	SP1–SP8	SP2–SP5
8	SP1–SP9	SP1–SP9	SP1–SP9	SP1–SP9	SP1–SP9	SP1–SP9	SP2–SP3	SP2–SP6
9	SP2–SP7	SP2–SP3	SP2–SP7	SP2–SP7	SP2–SP3	SP2–SP3	SP2–SP4	SP4–SP9
10	SP2–SP8	SP2–SP6	SP2–SP8	SP2–SP8	SP2–SP4	SP2–SP4	SP2–SP5	SP5–SP7
11	SP4–SP7	SP2–SP7	SP3–SP8	SP3–SP8	SP2–SP5	SP2–SP5	SP2–SP6	SP5–SP9
12	SP4–SP8	SP2–SP8	SP4–SP7	SP4–SP7	SP2–SP6	SP2–SP6	SP2–SP7	SP6–SP7
13	SP5–SP8	SP3–SP8	SP4–SP8	SP4–SP8	SP2–SP7	SP2–SP7	SP2–SP8	SP8–SP9
14	SP6–SP7	SP4–SP7	SP5–SP7	SP5–SP7	SP2–SP8	SP2–SP9	SP3–SP4	-
15	SP6–SP8	SP4–SP8	SP6–SP7	SP5–SP8	SP3–SP4	SP3–SP4	SP3–SP7	-
16	-	SP5–SP7	SP6–SP8	SP6–SP7	SP3–SP5	SP3–SP8	SP3–SP9	-
17	-	SP5–SP8	-	SP6–SP8	SP3–SP7	SP3–SP9	SP4–SP7	-
18	-	SP6–SP7	-	SP8–SP9	SP3–SP9	SP4–SP6	SP4–SP9	-
19	-	SP6–SP8	-	-	SP4–SP6	SP4–SP7	SP5–SP7	-
20	-	SP8–SP9	-	-	SP4–SP8	SP4–SP8	SP5–SP9	-
21	-	-	-	-	SP4–SP9	SP4–SP9	SP6–SP7	-
22	-	-	-	-	SP5–SP6	SP5–SP6	SP6–SP8	-
23	-	-	-	-	SP5–SP8	SP5–SP8	SP6–SP9	-
24	-	-	-	-	SP5–SP9	SP5–SP9	SP7–SP8	-
25	-	-	-	-	SP6–SP8	SP6–SP8	SP7–SP9	-
26	-	-	-	-	SP7–SP8	SP7–SP8	SP8–SP9	-
27	-	-	-	-	SP7–SP9	SP7–SP9	-	-
No.	Statistically significant differences (paired-samples t-test, p < 0.05) regarding the air quality parameters between sample points (SPs)—Day 3
	Air parameter
	PM2.5	PM10	AQI	Particle Number	Relative Air Humidity	Air Temperature	TVOC	HCHO
1	SP2–SP3	SP1–SP4	SP1–SP4	SP2–SP3	SP1–SP3	SP1–SP3	SP1–SP2	SP1–SP4
2	SP2–SP7	SP2–SP7	SP1–SP6	SP2–SP7	SP1–SP4	SP1–SP4	SP1–SP3	SP1–SP5
3	SP2–SP9	SP3–SP7	SP1–SP8	SP3–SP9	SP1–SP5	SP1–SP5	SP1–SP4	SP1–SP6
4	SP3–SP9	SP3–SP9	SP2–SP3	SP5–SP9	SP1–SP6	SP1–SP7	SP1–SP5	SP1–SP7
5	SP5–SP9	SP5–SP7	SP2–SP7	SP6–SP9	SP1–SP7	SP1–SP9	SP1–SP6	SP2–SP4
6	SP6–SP9	SP5–SP9	SP2–SP9	SP7–SP9	SP1–SP8	SP2–SP3	SP1–SP7	SP2–SP5
7	SP7–SP9	SP6–SP8	SP3–SP9	-	SP1–SP9	SP2–SP4	SP1–SP8	SP2–SP6
8	SP8–SP9	SP6–SP9	SP5–SP9	-	SP2–SP3	SP2–SP5	SP1–SP9	SP2–SP7
9	-	SP7–SP8	SP6–SP9	-	SP2–SP4	SP2–SP6	SP2–SP4	SP3–SP6
10	-	SP7–SP9	SP7–SP9	-	SP2–SP5	SP2–SP7	SP2–SP5	SP3–SP8
11	-	-	-	-	SP2–SP6	SP3–SP7	SP2–SP6	SP6–SP9
12	-	-	-	-	SP2–SP7	SP4–SP5	SP2–SP7	SP8–SP9
13	-	-	-	-	SP2–SP8	SP4–SP6	SP2–SP8	-
14	-	-	-	-	SP2–SP9	SP4–SP8	SP3–SP6	-
15	-	-	-	-	SP3–SP7	SP5–SP8	SP3–SP8	-
16	-	-	-	-	SP3–SP9	SP6–SP8	SP4–SP6	-
17	-	-	-	-	SP4–SP5	SP7–SP9	SP4–SP8	-
18	-	-	-	-	SP4–SP6	-	SP4–SP9	-
19	-	-	-	-	SP4–SP8	-	SP5–SP9	-
20	-	-	-	-	-	-	SP6–SP7	-
21	-	-	-	-	-	-	SP6–SP9	-
22	-	-	-	-	-	-	SP7–SP8	-
23	-	-	-	-	-	-	SP8–SP9	-
No.	Statistically significant differences (paired-samples t-test, p < 0.05) regarding the air quality parameters between sample points (SPs)—Day 4
	Air parameter
	PM2.5	PM10	AQI	Particle Number	Relative Air Humidity	Air Temperature	TVOC	HCHO
1	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP2	SP1–SP5	-
2	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP4	SP1–SP3	SP1–SP3	SP1–SP6	-
3	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP5	SP1–SP4	SP1–SP4	SP1–SP8	-
4	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP6	SP1–SP5	SP1–SP5	SP2–SP3	-
5	SP1–SP7	SP1–SP7	SP1–SP7	SP1–SP7	SP1–SP6	SP1–SP6	SP2–SP5	-
6	SP1–SP8	SP1–SP8	SP1–SP8	SP1–SP8	SP1–SP7	SP1–SP7	SP2–SP6	-
7	SP2–SP6	SP2–SP4	SP2–SP6	SP2–SP6	SP1–SP8	SP1–SP8	SP2–SP7	-
8	SP5–SP7	SP2–SP6	SP3–SP8	SP5–SP6	SP1–SP9	SP1–SP9	SP2–SP8	-
9	SP6–SP7	SP4–SP6	SP5–SP6	SP5–SP7	SP2–SP7	SP2–SP7	SP3–SP4	-
10	-	SP5–SP7	SP5–SP7	SP6–SP7	SP2–SP9	SP2–SP9	SP3–SP7	-
11	-	SP6–SP7	SP6–SP7	-	SP3–SP6	SP4–SP6	SP4–SP5	-
12	-	-	-	-	SP3–SP8	SP4–SP8	SP4–SP6	-
13	-	-	-	-	SP4–SP6	SP4–SP9	SP4–SP7	-
14	-	-	-	-	SP4–SP7	SP5–SP6	SP4–SP8	-
15	-	-	-	-	SP5–SP6	SP5–SP8	SP6–SP7	-
16	-	-	-	-	SP5–SP8	SP6–SP7	SP6–SP9	-
17	-	-	-	-	SP6–SP7	SP7–SP8	SP7–SP8	-
18	-	-	-	-	-	SP7–SP9	SP8–SP9	-
19	-	-	-	-	-	SP8–SP3	-	-

), specifically a reduction of 48.66% (Figure 2), meaning a substantial decrease, almost half of the concentration outside the park. We consider this effect to be due to the presence of tree vegetation in the park, related to which other studies have shown that higher levels of urban green space are associated with decreased pollution levels [21,32].

Some studies have shown that when aiming to avoid high concentrations of PM_2.5, it is not enough to have urban parks with vegetation; it is essential for these parks to contain trees [33]. However, there are also studies [34,35] indicating that in cities, PM_2.5 reduction has also occurred in built-up areas where the presence of buildings limits air ventilation and, consequently, air currents, suggesting that, at least from a physical perspective, buildings can serve as a physical source of limitation for PM_2.5 concentrations. This is supported by the results of this study, as it was observed that, at monitoring point SP9, located 583 m from the park in a square surrounded by buildings and devoid of vegetation, PM_2.5 concentrations were 31.37% lower compared to the exterior of the park, which is not bordered by buildings and lacks vegetation (SP2). This effect is comparable to the one recorded at the park entrance (SP3). When interpreting this result, we must also consider that the points SP1, SP2, and SP9 share the characteristic of being located outside the studied urban park. However, they differ in that at SP9, access by vehicles is restricted, whereas at SP1 and SP2, vehicle traffic is intense. Other major sources for airborne particulate matter (such as industrial sources) were not considered because the research site was located in the downtown area of the city, without industrial objects. Only plant pollen [36,37] or the aeolian erosion of buildings could be a source, but these were also excluded due to the seasonal moment of the monitoring and local meteorological conditions on the monitoring days. Regarding the presence of the cars, a study conducted in another city in Romania [38] showed that the noise produced by them plays an important role in the propagation of the particulate matter along with the sound, because the vehicle-related noise penetrates the atmosphere and the airborne particulate matter formed at the noise source is ulteriorly lifted into the atmosphere by the sound waves. The same study also showed that vehicles are responsible for raising dust particles into the atmosphere through the rolling of their tires. Therefore, we consider that the higher PM_2.5 values recorded at exterior points SP1 and SP2 compared to exterior point SP9 are also due to this factor (vehicle traffic), not just the absence of a mechanical barrier provided by buildings. However, these results also highlight the importance of urban morphology and architecture in achieving goals related to air quality in cities.

On the second day of monitoring, it was observed that the evolution of PM_2.5 concentrations was similar to that of the first day. On the night between Day 3 and Day 4, it rained, which we consider to be the cause of the significant increase in PM_2.5 concentrations on Day 4 compared to the previous days (Figure 2 and Figure 3). Thus, on Day 4, after the rain during the night, PM_2.5 exceeded the daily maximum limit of 15 μg/m³ recommended by the WHO [28] at almost all monitoring points, including inside the park (except for SP6 and SP8), situation that was not observed for any sample point on Day 1, and on Day 2 and Day 3, it was only observed at the point outside the park (SP1). Therefore, on Day 2, only at point SP1 located outside the park was the limit recommended by the WHO exceeded, and the same occurred on Day 3. The recorded results indicate that atmospheric humidity is a factor that counteracts the contribution of vegetation as a factor for reducing PM_2.5 concentrations in the air. Although no statistically significant correlation was found between PM_2.5 concentration and relative air humidity in the study (Figure 4, Figure 5, Figure 6 and Figure 7), significant statistical differences (Table A2) regarding these parameters confirm what other researchers have found, namely that there is a strong positive correlation between air humidity and the increase in PM_2.5 concentration [39]. This suggests that, depending on the air humidity, both the quantitative variation in these particles and their deposition differ, as some studies have shown that PM_2.5 particles are enveloped with a hydrolayer within the condensing process, which causes increased deposition [24]. This means that the presence of PM_2.5 particles in the atmosphere is influenced by atmospheric humidity and precipitation [22]. However, if we compare the PM_2.5 concentration in the air on Day 4 at SP1 and SP9, i.e., the points farthest from the park and thus from the presence of vegetation, we can see that it increased significantly compared to the other points (Figure 2), which strengthens the idea that vegetation remains a reliable factor for reducing PM_2.5 in the air.

The range of PM_2.5 concentrations measured in the air varied between 4.96 μg/m³ (inside the park, Day 1, SP8—275 m from the border, among trees) and 23.26 μg/m³ (outside the park, Day 4, SP1—93 m from the border, after rain) (Table A1, Figure 3). Although these data show the extremes of the measurements and only punctually exceed the daily limit recommended by the WHO (15 μg/m³), when analyzing Table A1, very high values of this air parameter are observed compared to other values recorded in other cities. For example, a similar study conducted in Dublin (Ireland) showed air values of PM_2.5 by 6–7 μg/m³ [21], lower than those recorded in this study.

The effect of vegetation caused the PM_2.5 values recorded in this study to remain lower inside the park, with significant increases only on Day 4 after precipitation fell, when the relative humidity of the air also increased. The concentrations were more frequently elevated outside the park, even at lower relative humidity levels in the atmosphere.

3.2. Particulate Matter PM₁₀

Regarding the PM₁₀ particles, it was observed that the dynamics of their concentration over the four consecutive monitoring days generally resemble the trend of PM_2.5 concentrations, with a decreasing trend when entering further into the park. As with PM_2.5 particles, the lowest concentration was recorded on all monitoring days at point SP8, located deep within the park and surrounded by vegetation. These findings are similar to others showing an inverse association of urban green space with PM_2.5 and PM₁₀ [40]. For example, compared to SP2, which is located outside the park and 55 m from its border, the PM₁₀ concentration at SP8, located at the heart of the vegetation, was 44.47% lower (Figure 8), a statistically significant difference (Table A2). None of the recorded PM₁₀ concentrations exceeded the daily recommended limit of 45 μg/m³ set by the WHO, nor the 50 μg/m³ limit enforced in Romania. As with PM_2.5 particles, a significant increase (Table A2) in PM₁₀ concentrations was observed on Day 4, following the precipitation that occurred overnight between Day 3 and Day 4.

3.3. Air Quality Index (AQI)

The AQI values measured during the four consecutive monitoring days are presented in Figure 9. The device used in this study calculates the AQI exclusively based on the concentrations of PM_2.5 and PM₁₀, which is why this indicator follows the trends of the two parameters that determine it. According to the EPA’s air quality standards, which specify a maximum AQI value of 50 for good air quality (Table 2) with no negative effects on the human population, it was found that, for this study, the AQI values indicated good air quality inside the park, except for Day 4, when the value was exceeded following the precipitation from the previous night, resulting in moderate air quality. At monitoring point SP1, the farthest from the park and lacking the physical protection of buildings but near vehicle routes, the AQI values for good air quality were exceeded on Days 2–4. Similarly, at SP9, between buildings and without vegetation, AQI values were exceeded on Days 3–4 (Figure 9), suggesting that proximity to an urban park, an area with vegetation, cannot fully compensate for the presence of vehicles that generate PM_2.5 and PM₁₀ particles.

Comparing Figure 2 and Figure 8, it can be seen that the contribution of PM_2.5 particles is more significant in determining AQI values, as the permissible concentrations for PM₁₀ were not exceeded at any measurement point. Throughout the four monitoring days, a decreasing trend in AQI values was observed at the inner points of the park (SP3-SP8) compared to the outer points (SP1, SP9). Point SP8 inside the park showed the lowest AQI values during the first two measurement days. In interpreting the AQI values, the relative humidity of the air at the time of measurement was also taken into account. Thus, it was observed that on days with higher humidity, inside the park, where tree vegetation is much denser, AQI values had an increasing trend, reflecting lower air quality compared to previous days with lower humidity (Figure 9), and similarly in the park’s exterior. Therefore, the increase in AQI values was consistent on Day 4 compared to Day 1 at all sampling points, with the increase exceeding 50% at nearly all measurement points, except SP2 and SP6 (Figure 9). On Day 4, it was also found that AQI positively correlated with the relative humidity of the air in the park’s exterior at SP2 (Figure 7) and negatively at SP8, located deeper within the vegetation (Figure 7). Similar results were found by Zender-Świercz et al., 2024 [22], who observed that AQI positively correlates with air humidity, especially when its values place the air quality in the unhealthy and moderate range. These results highlight the importance of air humidity in increasing the concentration values of several air quality parameters (PM_2.5, PM₁₀, AQI) and in exceeding their admissible or recommendable limits. Statistically significant correlations were found between AQI and the concentrations of PM_2.5 and PM₁₀ (Figure 4, Figure 5, Figure 6 and Figure 7), but these were expected, considering that the AQI measured by the device used in the study is the expression of these two indicators and that similar findings have been made in other studies of the same kind [22]. However, AQI correlated more frequently with the PM_2.5 concentration than with the PM₁₀ concentration (Figure 4, Figure 5, Figure 6 and Figure 7), indicating that the PM_2.5 concentration carries more weight in determining its value.

3.4. Particle Number

The measurement of the particle count (pcs/L) in the air showed that inside the park, the number of particles was lower than outside throughout all four days (Figure 10). Similarly to other monitored indicators, on Day 4, after precipitation, the amount of particles in the air increased considerably compared to the previous days. Thus, at SP8, the point located the deepest within the vegetation, the particle count was the lowest compared to other inner points of the park; however, here, on Day 4, it was 64.73% higher than on Day 1, a significant and noteworthy difference (Table A2). These results highlight both the importance of vegetation and the impact of meteorological conditions, in this case the relative atmospheric humidity resulting from the precipitation that fell the night before, on the amount and dynamics of particles in the air. Atmospheric humidity influences the composition and concentration of particles in the air. In conditions of high humidity, hygroscopic particles absorb water, leading to an increase in their size and changes in their physicochemical properties. This process can have a dual effect: on one hand, it can facilitate the deposition and removal of pollutants from the atmosphere through wet deposition, and on the other hand, in the presence of fog or secondary aerosols, it can lead to the formation of fine liquid particles that contribute to an increase in their atmospheric proportion due to their suspension in the air for varying periods of time.

Among the meteorological variables, it was found that relative air humidity can predict the accumulation of particulate matter [41]. Results supporting the involvement of the same factors in the dynamics of particulate matter in the air have also been found and explained in the literature [42]. The vegetation of the studied park is predominantly represented by trees, which have been found to reduce the number of particles in the air through retention mechanisms at the leaf level [43,44], absorption at the stomata level [44], or dispersion [45]. However, the situation observed on Day 4, when the particle concentration in the air increased significantly after the precipitation compared to previous days, was contradictory to the estimated expectations, as the wet deposition effect of the particles reported by other studies [24] was not confirmed.

3.5. Air Temperature

Temperature monitoring was also conducted on all four days and at all sample points. The hypothesis and expectations underlying the research were that, when entering further into the park, the air temperature would decrease. These expectations were based on studies [46,47,48,49] showing that urban parks act as significant buffers against high temperatures during hot seasons. However, this hypothesis was not confirmed in the present study (Figure 11), as it was found that the air temperature was higher inside the park (SP3–SP8) than outside it (SP1, SP2, SP9) on almost all measurement days. Thus, the temperature differences between the park’s exterior points and interior points ranged from 1 to 6 °C. A decrease in air temperature was observed on Day 4 compared to previous days, correlating with the rainfall the night before and the increase in relative humidity. Inside the park, the lowest air temperature was recorded at the point surrounded by tree vegetation, although this value remained approximately 2–3 °C higher than the exterior of the park.

These results, similar to the variation in PM_2.5 and PM₁₀ particles, support the contribution of urban vegetation to influencing the dynamics of air quality parameters in urban areas. A higher air temperature inside an urban green space than outside it has been reported in other urban studies [33], and it can be explained by several hypotheses. One explanation might be that within the park, air ventilation through air currents is insufficient to reduce the air temperature, as happens outside it, and this fact could be influenced by the morphology of the surrounding environmental characteristics, such as vegetation structure and distribution [50], canopy porosity [51], landscape composition and morphology [49], and the presence and density of buildings [52,53], as well as alley and building albedo [54]. Monitoring point SP8 was surrounded by trees and it is possible that plant evapotranspiration contributed to the increase in air humidity through aerosol formation, as this point had the highest relative humidity. Aerosols and water vapors in the air can absorb solar radiation, resulting in an increase in air temperature [55]. In addition, air humidity can influence the rate of evapotranspiration of vegetation in the park, and if this process is reduced, its cooling effect on the ambient air temperature diminishes or is overtaken by solar radiation absorption [56,57]. Other interior sample points in the park (SP2-SP7) were near concrete alleys, so it is possible that they released accumulated heat, thus increasing the air temperature. SP9 is situated in a square paved with concrete slabs and is lacks vegetation, so it does not benefit from shading effects, as SP1 does, which is near a very tall building. Moreover, the presence of buildings can limit wind speed [58], and buildings and pavements absorb heat and release it, which could explain the additional 2–4 °C observed at this point compared to other exterior points of the park (SP1 and SP2). It results from these data that it is not enough for an urban green space to be established, but its design must be integrated with urban morphology strategies if it is aimed that the heat mitigation effect be achieved and maximized in cities. In addition, besides technical elements of urban design and those that are vegetation-related, attention should be given to the soils of the parks as related to their impact on local temperature increases. Some studies have shown that soil impermeability plays an important role in raising air temperature in urban green spaces [59]. Soils in urban parks, especially in urban arboreta, due to maintenance work, are minimally disturbed technosols and therefore their compaction degree and impermeability may be high. Therefore, attention should be given to other factors involved in maintaining soil permeability in urban parks, such as pedofauna, since its contribution to soil permeability was demonstrated [60,61,62]. No significant and consistent correlations were found in this study between air temperature and other parameters, as some other studies have shown. For instance, some studies have indicated that air pollution amplifies the intensity of the urban heat island effect, especially when the green spaces have small sizes [63], while other studies support this idea, showing a strong correlation between air temperature and PM_2.5 concentration [64] and that PM₁₀ concentration increases when the temperature is low [65]. No significant positive correlation was found between air temperature and its relative humidity, meaning that other factors likely influenced the increase in air temperature inside the park compared to the outside, possibly factors related to shading architecture [66], tree density [58], airflow [67], vegetation cover and layouts [68], or even alley surface materials. It is possible that the small size of the studied park (approximately 88 hectares) was also a factor that caused the increase in the air temperature inside the park compared to the outside, because it was found that larger parks with good vegetation (tree) coverage may be better at enhancing the evapotranspiration rate and pollutant absorption, thus increasing their cooling effect [63]. A study [33] revealed that urban green spaces smaller than 525 hectares have a cooling effect of only approximately 1 °C. Thus, our findings show the importance of the integrated urban green space design in maximizing the cooling benefits of the urban green spaces. This is very important when the urban park attendance is considered, as it may be affected [69] because people are specifically seeking the cooling effects of urban green spaces, and if this is absent, their thermal comfort level is not ensured.

3.6. Relative Air Humidity

The relative humidity of the air decreased entering deeper into the park (Figure 12) compared to exterior points SP1 and SP2. However, when comparing the exterior points of the park, it was observed that the one located between buildings showed a lower relative air humidity than those near the park. It is possible that the proximity to vegetation could be the reason for the higher relative air humidity around it, due to the evapotranspiration effect [66]. Clearly, as a result of the precipitation that occurred during the night from Day 3 to Day 4, the relative humidity of the air increased on Day 4 both inside the park, with values ranging from 30.64% (SP7) to 37.76% (SP6), and outside, with values ranging from 28.03% (SP2) to 36.01% (SP1). It was found that, inside the park, the relative humidity of the air increased the most at the point where the trees become denser (SP8), surrounded by tree vegetation, likely as a result of the evapotranspiration effect exhibited by the plants. However, it still remained lower than the relative air humidity outside the park.

The decrease in relative air humidity when moving towards the interior of an urban park can possibly be explained by the connection between plant evapotranspiration and local warming. Since in the studied urban green space the air temperature increased compared to the exterior, it is possible that the trees in the park release water vapor through transpiration, but this process may also be accompanied by the absorption of solar radiation by the water vapor or aerosols, thus causing the air temperature to rise. If the air temperature increases within the park due to the retention of heat as a result of this mechanism, for which we suspect as the primary cause the inefficient circulation of air masses, then the relative humidity of the air decreases.

Thus, an inverse proportional relationship between air temperature and relative air humidity results. This relationship was not statistically validated in this study, but that does not mean that it does not exist, especially since it has been reported by other studies. For example, it has previously been shown that the urban heat island effect is due to the lack of humidity [70], which determines an increase in air temperature, making cities warmer. Other studies have also found that increased atmospheric humidity was associated with higher air temperature, as well as with soil moisture and soil electrical conductivity in the first 5–7 cm of urban park soil [71]. The evapotranspiration of urban vegetation is a physiological process that influences urban air humidity, which in turn is an indicator of cities’ sustainability, as it has been shown to be strongly influenced by urbanization and directly related to the phenomenon of global warming [72]. However, at the microclimate level, some studies have shown that in urban parks, the shading effect of trees plays nearly three times as large a role as evapotranspiration in cooling the environment [69]. The decrease in relative air humidity in cities has also been reported by other studies, which have shown that cities are, in this regard, urban dry islands [47], especially in the summer season in temperate cities [48,72].

Towards the edge of the park, it was observed that the relative humidity of the air is slightly higher. Some bibliographic sources have shown that at the edges of urban green spaces, air humidity can also be influenced by external sources that are not vegetation-related, such as the proximity of wet surfaces (lakes, fountains, seas) [33] or moisture generating sources, such as the humidity resulting from urban traffic and buildings [73]. The latter situation applies to the studied site and may explain the higher relative air humidity at the marginal sample points, because the park is surrounded by heavily used roads and partially by buildings (Figure 1), and some studies have shown that traffic gas emissions tend to be bound with water particles [74] and remain suspended in the air, thus increasing air humidity. Other factors that could explain the lower relative humidity of the air inside the analyzed green space may include the absorption of moisture by vegetation and soil. The soil and tree foliage can retain moisture from the air, especially in the deeper areas of the park, where the vegetation layer is denser. This effect may lead to a local decrease in relative humidity because water vapor is absorbed by the leaves and soil before it can contribute significantly to the air humidity. Additionally, the effect of moist air consumption through condensation on leaves could be a cause, as, in certain situations, cooler leaves can condense water vapor from the air, reducing the relative humidity of the air [75].

3.7. Volatile Organic Compounds (TVOC) in Air

The concentration of total volatile organic compounds (TVOC) was monitored (Figure 13), and values comparable to those reported by other studies [76] were observed. An increase in TVOC concentrations was noted inside the park compared to its exterior. Although we expected higher concentrations outside the park, specifically at SP1 and SP2, based on the argument that these points are closer to roadways where VOC presence is increased due to incomplete fuel combustion and the fact that VOCs are generally concentrated near their sources [77], the measurements showed the opposite. The increase in TVOC concentration inside the park is considered to have its source in the emissions of biogenic volatile organic compounds by park vegetation [78]. As Bao et al., 2024 [79], have shown, these biogenic VOCs can lead to the formation of secondary pollutants (ozone, organic aerosols) in the urban green areas, but they can also enhance human health (emotional balance, immunity). The same study reported a contribution of approximately 20% of biogenic VOCs to the total VOCs. The recommended limit by the WHO [27,77,80] (0.3–0.5 mg/m³ as emissions) was not exceeded for this parameter.

The daily measured values ranged from 0.01 to 0.21 mg/m³, with the highest value recorded at SP5 inside the park and the lowest at SP1 outside the park. This indicator did not show increases on Day 4, when relative air humidity was high; on the contrary, its concentration decreased on this day. However, the statistically significant correlations observed (Figure 4, Figure 5, Figure 6 and Figure 7) were contradictory. Thus, in our study, TVOC was positively correlated with relative air humidity during the first three monitoring days, both inside and outside the park (Figure 4, Figure 5 and Figure 6), but negatively correlated inside the park on the fourth day (Figure 7), when the relative air humidity was higher after previous precipitation, confirming the inverse proportionality relationship between TVOC and relative humidity on Day 4. In attempting to find out what could cause the increase in TVOC concentration when relative air humidity decreases inside the monitored urban green space, physicochemical and biological mechanisms were frequently invoked. Thus, TVOC may interact with water vapors. Studies have strongly suggested that VOC’s ability to form hydrogen bonds is a key factor of VOC transfer in condensed water when the relative air humidity is high [81]. This could explain our findings, because in conditions of decreasing air humidity, this bond formation may be reduced, and VOC’s remain suspended in the atmosphere. Other studies revealed that an increase in the air temperature can reduce the effect of the relative air humidity on VOC removal [82], which can explain why in our study there was an inverse relationship between air temperature and air humidity simultaneously with an increase in TVOC. Also, it was found that TVOC was negatively correlated with the content of PM_2.5 and with AQI at SP8, inside vegetation. Lopes et al., 2025 [63], showed that air PM_2.5 interacts with gases and influences several chemical reactions involving VOC in the atmosphere.

3.8. Air Formaldehyde (HCHO)

Formaldehyde (HCHO) is a VOC substance. It was decided to monitor the formaldehyde (HCHO) concentration in the studied park (Figure 14) based on the argument that in cities there are both natural sources of formaldehyde (emissions from vegetation due to metabolic processes, decomposition of organic matter, organic photodegradation, and emissions from the soil) and anthropogenic sources (urban pollution from industrial sources, vehicle exhaust gases, urban furniture, and smoking), as well as because of its implications on human health (carcinogenic nature). However, the most significant contributor to formaldehyde emissions in urban areas is incomplete combustion by motor vehicles [83] and heating systems [84]. Urban parks, especially arboretums and those dominated by woody vegetation, are both sources of formaldehyde originating from biotic VOCs, which can be dispersed into the atmosphere and reach areas outside the parks, but they can also act as attenuators of this volatile organic compound’s concentration in the air, as vegetation can absorb and partially degrade formaldehyde through complex chemical and biological processes specific to phytoremediation [85]. A first hypothesis in the research was that formaldehyde levels would not be too high in the studied park, based on the results of many studies that confirmed this fact, as well as on the consideration that the park is located in the central area of the city, where there are no industrial sources likely to emit formaldehyde, although there is still, in the vicinity of the park, the source of the exhaust gasses of the vehicles, which was taken into account for a second hypothesis, namely that, due to this factor, but also because the plants are capable of HCHO phytoremediation, the park would have lower HCHO concentrations than its exterior. The first hypothesis was confirmed, as formaldehyde levels were below the recommended WHO limit (<0.1 mg/m³) at all monitoring points (Figure 14), with concentrations ranging from 0.01 to 0.05 mg/m³. However, the second hypothesis was not confirmed, as it was found that the formaldehyde concentration inside the park was up to 4–5 times higher compared to the exterior.

The highest HCHO concentration was recorded 20 m from the park’s boundary moving towards the interior, specifically at SP5 (Figure 14), which is located in close proximity to the roadway, heavily trafficked during the measurement period (especially because the monitored site is an ultracentral area of the city and the measurements were performed in the first working days of the week). Therefore, we consider that the contribution of exhaust gases plays a determining role in establishing the HCHO concentration at this point. The same as TVOC, HCHO concentrations did not increase on Day 4 following precipitation; on the contrary, they decreased compared to the previous days. This effect is likely due to the fact that HCHO is very water soluble [24] and the wet deposition has occurred.

In contrast, the differences in HCHO concentration are significant between the exterior and interior of the park, being two to five times higher inside than outside (Figure 14, Table A2). Explaining these results is difficult, as other analyses were not included in the current study. However, if we consider the factor of road traffic, it is possible that this is not the cause, since studies have shown high HCHO concentrations even in rural air with low traffic levels due to photochemical reactions [86,87]. Formaldehyde is easily photolyzed and therefore has a short lifetime. As the points inside the park recorded the highest HCHO concentrations and not the points outside it, which were the closest to the source of car traffic, it is possible that, here too, the cause of the increased HCHO concentration is not road traffic, but rather the photochemical reactions [88] of biogenic VOCs. The photolysis and photooxidation of organic compounds can lead to formaldehyde formation in the atmosphere [89]. The biogenic VOCs emitted by vegetation as a response to environmental stressors are major drivers of formaldehyde variability in air [90], because biogenic VOCs are precursors of HCHO. The relationship between biogenic volatile organic compounds and formaldehyde is so tight that it can be used as an indirect tool to determine biogenic VOC levels in the air [91]. Thus, HCHO emissions in the studied park may serve as an indicator of biogenic VOCs released in response to thermal stress, given the elevated air temperatures recorded during the monitoring period. Sporadically, on certain monitoring days and at specific sample points, but always located inside the urban green space (Figure 4, Figure 5, Figure 6 and Figure 7), positive correlations were found between HCHO concentration and relative air humidity, which contradicts previous results that showed an inverse relationship between formaldehyde concentrations and relative humidity [92]. The fact that the dynamics of HCHO concentrations followed the trend of TVOC concentrations in the study area, along with the finding that HCHO and TVOC concentrations were lower outside the urban park than inside, suggests that HCHO concentration inside the green space is the result of the photochemical oxidation of VOCs caused by intense sunlight during the summer monitoring period. However, the phytoremediation ability of vegetation in the urban green space should be considered and supported through several urban planning strategies that can enhance and valuate this ability of urban vegetation in HCHO purification, such as strategies regarding species combination or architectural arrangements that favor the enzymatic apparatus of green plants involved in HCHO phytoremediation, for which they have been referred to as the “green liver” [93] of the planet.

4. Conclusions

The results of this study showed that the studied urban green space confirmed what other studies have also found, namely that urban vegetation and the establishment of green spaces in cities contribute to maintaining air quality, at least in terms of the studied aspects, specifically PM_2.5 and PM₁₀ concentrations and AQI values. The results indicated that urban vegetation remains a reliable factor in reducing PM_2.5 and PM₁₀ levels in cities’ air, but the relative air humidity proved to be a counteracting factor that diminishes the contribution of vegetation in decreasing PM_2.5 and PM₁₀ concentrations and in maintaining an AQI corresponding to good air quality. This study highlights the importance of air humidity in enhancing the values of PM_2.5, PM₁₀, and AQI and in exceeding their admissible or recommended limits for air quality. The effect of wet deposition of airborne particles, as reported by other studies in relation to precipitation, was not confirmed by this study.

Inside the park, HCHO concentrations increased by up to 4–5 times compared to the exterior. Since the highest HCHO concentrations were recorded at points inside the park and not at exterior points closest to the traffic source, it is possible that the increased HCHO concentration is not due to road traffic but rather to the photochemical reactions of biogenic VOCs.

Regarding the air temperature cooling effect, the studied green space showed results contrary to other findings in the field, revealing an increase in air temperature of up to 1–6 °C inside the park compared to the exterior. This means that it did not achieve the goal of providing climatic comfort to citizens during the summer or serving as a cooling spot in the city. Our results contrast with the general perception and conviction that urban parks and green spaces are cooler islands within cities. Our findings draw attention to the fact that simply having a green space in a city does not necessarily mean achieving environmental objectives such as reducing the heat risk of cities or enhancing air quality, as some monitored parameters registered higher values inside the green space than outside.

In this study, based on the results, we consider that the main limitations in achieving these goals were the small size of the park (88 hectares) and its morphology and architecture, which resulted from the integration of the species that compose it. These findings suggest that establishing an urban green space is not sufficient; rather, its design must align with urban morphology strategies if the heat mitigation effect is to be achieved and cooling benefits are to be maximized in cities. This aspect is very important when it comes to urban park attendance by the population, because it could be affected, as people seek exactly the cooling effect of urban green spaces, and if this effect is lacking, their thermal comfort is not ensured. Therefore, in urban planning, environmental strategies should comprise not only esthetic criteria but also scientific criteria in order to reach the ultimate goal of urban green spaces in cities: a sustainable, healthy, and comfortable environment.

5. Research Limitations and Further Recommendations

In applying the conclusions identified in this study, we must consider several limitations that arise from the fact that certain factors were not included in the research. For instance, contextual local meteorological data (such as wind, atmospheric pressure, solar radiation, etc.) were not recorded. Other environmental studies on urban sustainability in the Romanian cities [94,95] showed that these are important. It is known that wind direction and speed can significantly influence the dispersion of pollutants. However, when the decision was made to not associate the study with the wind factor, the structure of the park’s vegetation was taken into account. The park is dominated by trees and woody vegetation, which was assumed, through visual assessment, to act as a mechanical barrier reducing wind speed inside the park by absorbing and deflecting airflow. The wind-shielding effect of woody vegetation in urban parks depends on its spatial arrangement, density, and especially on the presence of large trees with rich canopies, which can help transform the park interior into a protected area with a relatively stationary air mass and thus a moderated microclimate. However, since no such analyses were carried out, a recommendation for future investigations that could complement and strengthen the current study is to examine the morphology, orientation, and layout of the vegetation within the urban park, particularly trees, as well as the impact of vertical stratification of vegetation on its mechanical barrier effect against air currents, the importance of the canopy in shading, and other related aspects. Another factor that was not monitored in this study is road traffic. It was not assessed, based on the assumption that it was the only significant local anthropogenic source of pollution, since the studied park is located in the city center where there are no major industrial pollution sources. However, an evaluation of traffic density around the park would be useful to confirm its contribution to the recorded values of the studied parameters. The short measurement period and the limited time of day during which measurements were taken (only at midday) may also be limitations in interpreting the results. However, the study did not aim to analyze seasonal behavior or intraday variability but rather the differences between the park interior and its surroundings. Other studies [96] have also monitored the air quality for short periods of a few days in cities and demonstrated that such short-term approaches can provide valuable information about the impact of urban vegetation on air quality and can provide a basis for understanding this relationship. These factors untaken in the study could be included in future studies; for example, since the pollution and temperature can vary significantly throughout the day, it would be interesting to see whether the observed differences persist during other time intervals and over the long term. Measuring only at noon excludes values from the morning or evening, when other relevant phenomena may occur (e.g., thermal inversions, ozone decrease, etc.). Furthermore, the types of surfaces (pavement vs. soil, trees vs. grass) were not monitored, even though their contribution was intuitively considered in this study in interpreting variations in air temperature. The most significant limitation of the study is considered to be the lack of vegetation characterization: species, their morphology, and spatial arrangement (density, coverage, and horizontal and vertical structure). All these limitations may serve as subjects for future research that could complete and enrich the present study.