The increasing interest for environmental issues and the attention of the public for the problems connected to conservation have determined a new way of understanding the greening also in relation to people’s well-being . There has been a transformation in the way of living with a greater attention to the quality of the life . Today 57% of the world population lives in cities and it is estimated that 62% of the world population will live in urban areas by the year 2030 . The rapid growth of urban areas has brought social, economic and environmental challenges . Urban greening is a valuable asset for modern cities delivering key functions and benefits that enhance the quality of the life   . Urban green spaces play an important role from a social perspective by promoting physical activity, increasing people interaction    and reducing stress  . Moreover, urban greening increases the attractiveness of communities, as well as neighborhood desirability which has been quantified in a real estate value as a “willingness to pay” . Consequently, due to the range of social and environmental services they afford, urban green spaces are a public good and their availability is a core indicator for a sustainability profile . Thus, the use of plants to ameliorate urban air quality has become a focus of research     . Vegetation that covers various segments of urban areas (i.e. public and private parks, gardens, sport fields, hedges and tree-lined avenues) contributes to air quality amelioration by reducing air pollution    and decreasing CO2 concentration, air temperature and noise level   . During the last decade, there has been considerable research effort to quantify the carbon (C) storage of urban forests worldwide  . The above-ground biomass estimation is a key parameter in accounting for carbon storage by trees . In general, trees of large size have a greater C storage capability than trees of small size   . Although C stored in urban forests is relatively small in scale compare to forest stands and plantation trees, the proximity of urban forests to emission sources means that their potential C storage should not be neglected  . In such context, the main objective of this research was to evaluate the role of tree species growing in the Campus of Sapienza University of Rome to improve environmental quality. In particular, data about C storage, air temperature, CO2 concentration and noise level collected inside the Campus area were compared with those collected in the surrounding streets characterized by a higher traffic level. University areas play an important role as the environment to promote and protect health of the students and staff, to create holistic health-conducive working, learning and living environments with sustainability, and to develop health promotion in teaching and research .
2. Materials and Methods
2.1. The Study Area
The greening of the Sapienza University of Rome Campus (hereafter called Campus) largely maintains the characteristics of the original project carried out in the 1930s. The Campus covers an area of 20.3 ha. A majority of the species are Pinus pinea L., Cedrus deodara (Roxb. Ex D. Don) G. Don, Quercus ilex L., Cupressus sempervirens L., Myrtus communis L., Arbutus unedo L., Olea europaea L., Tilia × europaea L., and Cercis siliquastrum L.
The considered tree species, on average, are 100 years old. Along the Avenue that connects the entrance to the Minerva Fountain, there are Q. ilex trees followed by P. pinea, C. deodara and C. sempervirens. On both sides of the Minerva Fountain, there are Q. ilex trees. The South and North Avenues are characterized by T. × europaea. The Experimental Garden (8354 m2, hereafter called Garden) borders Cesare De Lollis Street in the southern side that is characterized by high traffic level during the day. The northern side is bordered by the University Avenue, characterized by high traffic levels during the day (Figure 1). The study was carried out in the period January 2017-January 2018.
The study area is under a Mediterranean type of climate. The average total annual rainfall was 819 mm, most of it distributed in autumn and winter. The mean maximum air temperature (Tmax) of the hottest months (July and August) was 31.8˚C ± 0.1˚C and the mean minimum air temperature (Tmin) of the coldest month (January) 4.7˚C ± 1.1˚C. The mean yearly air temperature was 16.8˚C ± 6.6˚C (data provided by the Lazio Regional Agency for Development and Agricultural Innovation, Meteorological Station of Rome, Lanciani Street, data for the period 2006-2017).
2.3. CO2 Concentration, Air Temperature and Humidity, Traffic Density and Noise Level
Measurements were carried out in four sites: Cesare De Lollis Street (site A), outside the Campus and bordering the Campus in the southern side, Garden (site B), the central area inside the Campus (site C) and University Avenue (site D), outside the Campus and bordering it in the northern side (Figure 1). CO2 concentration (ppm), air temperature (Ta, ˚C) and humidity (RH, %) were monitored simultaneously by handheld tools (Rotronic, CP11). Noise level (N, dB) was monitored by portable sound level meters (Testo 816, class 2, Italy). Traffic density (i.e. number of vehicles per minute) was monitored simultaneously with microclimate, CO2 concentration and noise level in A and D sites. Measurements were carried out monthly (three sampling days per month with comparable climatic conditions, almost 3 days after the last rainfall) from 8.00 to 11.30 a.m. (traffic density peak hours, Gratani and Varone 2005) during the study period, at 1.50 m from the soil, according to .
2.4. Plant Traits
The number of tree per each species growing in the Campus and in the Garden was counted. Structural traits were measured on representative trees. In particular, tree diameter at breast height (DBH, m) was measured by callipers (Silvanus calliper—65 cm) or by a DBH tape (length = 20 m) when the diameter was larger than 65 cm. Plant height (H, m) was measured by electronic clinometers (Haglöf, Sweden). Trees with a diameter larger than 5 cm were considered . Trees different age classes were selected for P. pinea, based on the ratio between H and crown height (CH, m), according to . CH was defined as the vertical
Figure 1. Map of the Sapienza University of Rome Campus. The Transect from Cesare De Lollis Street (A site), the Experimental Garden (B site), the central area inside the Campus (C site) to the University Avenue (D site) is shown. Image from google.earth.
distance from the lowest branch insertion to the highest point of the trees, according to .
2.5. Aboveground Biomass and Carbon Storage
The aboveground biomass (AB) of the tree species was obtained by allometric equations     using DBH and H for each species. If no allometric equations were found for a species, the mean value of the equations of the same genus was used. If no genus equations were found, the value from broadleaf or conifer general equations was used, according to .
The carbon (C) stored in the aboveground biomass (CA) was calculated by multiplying AB by 0.5 .
2.6. Statistical Analysis
Differences of the means were tested by one-way analysis of variance (ANOVA) and Tukey test for multiple comparisons. All statistical tests were performed using a statistical software package (Statistica, Statsoft, USA). A correlation analysis was carried out between CO2 concentration and traffic density, and between CO2 concentration and Ta.
3.1. CO2 Concentration, Air Temperature and Humidity, Traffic Density and Noise Level
The CO2 concentration trend during the study period is shown in Figure 2. The mean yearly CO2 concentration at 8.30 a.m., when traffic peaked (27 ± 7 vehicles∙min−1, mean value of A and D sites), was 502 ± 47 ppm (mean value of
Figure 2. Carbon dioxide concentration (CO2) monitored at 8.30 a.m. (a) and at 11.30 a.m. (b) during the study period along the transect. A = Cesare De Lollis Street, B = Experimental Garden, C = central area inside the Campus, D = the Avenue of the University. Mean value and standard deviation are shown (n = 9). Differences across the transect are always significant except when indicated (*, ANOVA, p < 0.05).
A-B-C-D) decreasing by 6% at 11.30 a.m. (mean value of A-B-C-D). The highest values were monitored in winter (544 ± 23 ppm) when traffic peaked (31 ± 6 vehicles∙min−1, mean value of A and D) decreasing by 17% and 20% in spring and summer, respectively. The highest CO2 concentration along the transect was monitored in A and in D (523 ± 60 ppm and 505 ± 52 ppm, respectively, mean value at 8.30 a.m. and 11.30 a.m., during the study period) and the lowest in B (448 ± 34, ppm). There was a significant positive correlation between CO2 concentration and traffic density (y = 4.0083x + 409.61, R2 = 0.4025, p < 0.05) showing that 40% of CO2 concentration variations depended on traffic density variations.
The mean yearly Ta was 20.1˚C ± 8.9˚C (mean value of A-B-C-D) at 8.30 a.m. increasing by 27% at 11.30 a.m. (mean value of A-B-C-D). The highest Ta was monitored in summer (31.0˚C ± 1.8˚C, mean value of A-B-C-D) at 8.30 a.m. (Figure 3) decreasing by 47% and 73% in autumn and winter, respectively. Along the transect, the lowest Ta was monitored in B (21.4˚C ± 8.8˚C, mean value at 8.30 a.m. and 11.30 a.m.) increasing by 10% in A, C and D (mean value). There was a significant negative correlation between CO2 and Ta (y = −4.7597x + 595.15, R2 = 0.63, p < 0.05).
The mean yearly RH was 49% ± 14% (mean value of A-B-C-D) at 8.30 a.m. decreasing by 24% (mean value of A-B-C-D) at 11.30 a.m. The lowest RH was monitored in summer (33% ± 6%, mean value of A-B-C-D) at 8.30 a.m., and the highest in autumn (65% ± 7%, mean value of A-B-C-D). Along the transect, the highest RH was measured in B (46.0% ± 10.0%, mean value at 8.30 a.m. and 11.30 a.m.) and the lowest in C (38% ± 4%, mean value at 8.30 a.m. and 11.30 a.m.).
The highest noise level was monitored in A and D (80 ± 2 dB, mean yearly value) decreasing by 44% and 36% in B and C, respectively. During the year, the highest noise level was monitored in winter (84 ± 2 dB, mean value of A and D)
Figure 3. Air temperature (Ta) monitored at 8.30 a.m. (a) and at 11.30 a.m. (b) during the study period along the transect. A = Cesare De Lollis Street, B = Experimental Garden, C = central area inside the Campus, D = the Avenue of the University. Mean value and standard deviation are shown (n = 9).
when traffic peaked, decreasing by 8% and 14%, in spring and summer, respectively, according to the traffic density decreasing (26% and 39%, respectively).
3.2. Plant Traits
Structural traits of the considered tree species growing in the Campus and in the Garden, and the tree numbers for each species are shown in Table 1 and Table 2, respectively. The total number of trees in the Campus was 647 of which Q. ilex, T. × europaea and P. pinea were 33%, 15% and 13%, respectively. H ranged from 2.9 ± 0.3 m (Chamaerops humilis) to 29.0 ± 1.1 m (C. deodara). C. deodara had the highest DBH (96.0 ± 0.8 cm) and Persea americana the lowest (6.4 ± 0.5 cm). H varied from 6.3 ± 1.5 m (15 years), 13.0 ± 2.3 m (45 years) to 24.3 ± 5.4 m (100 years) in P. pinea.
In the Garden there were 85 trees, covering 6040 m2 (72% of the total Garden area) Platanus orientalis and Cinnamoum camphora showing the highest H (26.4 m and 23.2 ± 6.1 m, respectively) and Platanus orientalis the highest DBH (154 cm). Citrus spp. had the lowest H and DBH (3.5 ± 0.3 m and DBH 10 ± 0.6 cm, respectively).
3.3. Carbon Storage
The total C stored by all the trees growing in the Campus was 372 Mg of C to which those growing in the Garden contributed by 9% (Table 3 and Table 4). P. pinea, C. deodara, Q. ilex and T. × europaea had the highest C storage (30%, 20%, 18% and 13%, respectively, of the total C storage in the Campus), while Bauhinia aculeata C storage was lower than 0.01%. P. orientalis and C. camphora growing in the Garden contribute by 13% and 11%, respectively to the total C storage in the Garden while Nolina longifolia (Karw. ex Schult. & Schult. f.) Hemsl. by 0.12%.
Table 1. Structural traits and number of the considered tree species inside the Campus of the Sapienza University of Rome. H = plant height, DBH = diameter at breast height, n˚ = number of trees.
Table 2. Structural traits of the tree species growing in the Experimental Botanical Garden of the Sapienza University of Rome. H = plant height, DBH = diameter at breast height, n˚ = number of trees.
Trees are keystone structures in forest ecosystems, including those in urban areas    . On the whole, the results highlight that in the Campus there are 41 tree species and a total of 647 trees. In the Garden there are 85 trees. The most abundant species are P. pinea, Q. ilex, T. × europaea, C. deodara and C. sempervirens. There are centenarian P. pinea (47 trees) and C. deodara (35 trees) already present in the 1930s. Q. ilex (215 trees) and T. × europaea (86 trees) characterize the tree-lined avenues inside the Campus.
Among the benefits provided by greening, trees are excellent regulators of air temperature, heat and dampness in urban surroundings . In particular, tree structure defines patterns of light-capturing areas and air temperature buffering effects of the canopy   , which contribute to mitigate the urban “heat island” . The trees growing in the Campus contribute to decrease air temperature in summer by 8% and 3% at the Garden (site B) and in the center of the Campus (site C) than the surrounding streets (sites A and D), while RH increases by 23% and by 9%, respectively. In Autumn Ta decreases by 7% and 6% at B and C sites, while in winter by 7% and 10%, respectively. The urban C cycle has its own driving forces, significantly different from those of natural ecosystems . Humans and automobile activity produced more than 80% input of CO2 into the urban environment  and motor vehicles are significant sources of air pollution emissions . C is stored in plant tissues at different quantities depending on factors such as age , growth rate and leaf life span  , thus contributing to decrease the atmospheric CO2 concentration. Trees with a large crown store more C than trees with a small crown . In particular, the total C stored by trees growing in the Campus is 374 Mg of C to which C. deodara, Q.
Table 3. The aboveground biomass (AB), carbon stored in the aboveground biomass (CA) and the total carbon stored for each of the considered species inside the Campus of the Sapienza University of Rome.
Table 4. The aboveground biomass (AB), carbon stored in the aboveground biomass (CA) and the total carbon stored for each of the considered species inside the Experimental Botanical Garden.
ilex and T. × europaea contribute by 20%, 18% and 13%, respectively. The highest contribution by C. deodara, Q. ilex and T. × europaea is justified by the large DBH and the high number of trees per species. The tree-lined avenues in the Campus have a total length of 835 m. In particular, Q. ilex C storage of the tree-lined avenues (520 m total length) is 68.07 Mg of C and by T. × europaea of the tree-lined avenues (315 m total length), 43.52 Mg of C. P. pinea C storage ranges from 0.40 Mg of C in 15-years old trees to 106.20 Mg of C in 100-years-old trees, according to the results of  for the same species. In the Garden there are 83 trees stocking 32 Mg of C, the centenarian P. orientalis giving the highest contribution (4010 Kg of C). Moreover, trees at B and C sites reduce the mean yearly CO2 concentration by 13 % compared to streets outside the Campus, which are characterized by all day high traffic level (25 ± 5 vehicles∙min−1, mean value during the study period), as confirmed by the significant positive correlation between the two variables. The highest CO2 concentration was monitored in winter (549 ± 15 ppm) decreasing by 17% and 20% in spring and summer, respectively.
The results highlight also the role of trees in reducing noise level. Noise is considered the third most serious kind of pollution because it affects human health unfavourably both physically and psychologically. General annoyance, disturbance in psychosocial well-being and reduction in sleep quality are commonly reported effects of noise exposure . The mechanism of noise attenuation by plants is due to the capability of leaves to absorb acoustic energy by transferring the kinetic energy which vibrates air molecules in a sound field to the vibration pattern of leaves   . In particular, B site (Garden) decreases noise level by 44% compared to A site (81 ± 4db). Areas characterized by a noise level above 65 dB are considered “black areas”, while a noise level between 55 and 65 dB are “grey areas” . The noise level monitored in C (54 ± 2 dB, mean value during the study period) follows in the “grey areas”, thus resulting in a more comfortable environment for people.
Despite the importance of green areas in improving urban air quality, up to date, few attention has been paid to the role of the greening in Universities. The planning of these areas has been considered only from an ornamental point of view with the aim to create a “beautiful and relaxing environment”. In addition, the preservation of biodiversity has become an important driver in many contemporary landscapes. Thus, the conservation of tree species and spreading information on their capability of environmental quality amelioration contribute to sensitize the public and, in particular, young people on the importance of naturalistic conservation. Our research highlighted that trees inside the Campus contribute significantly to create a healthy environment where people can reach a satisfactory wellbeing. The results, including tree traits and their air amelioration capability, can be incorporated in a database to monitor plant response over time also in consideration of changing environmental conditions. The Campus of the Sapienza University of Rome through the conservation of its collections, supported by scientific research, is a preferential way to spread information not only on plant biodiversity but also on its environmental quality amelioration.
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