Evaluating heavy metals contamination in campus dust in Wuhan, the university cluster in Central China: distribution and potential human health risk analysis

The potential health risk of heavy metals (HMs) in campus dust may threaten the health of thousands of students, teachers, and their families in Wuhan, the university cluster in Central China every day. In this research, the pollution characteristics and health risk with HMs was the first time presented in campus dust from the canteen, playground, dormitory, and school gate to date. The average HMs concentration in campus dusts ranked Pb (83.5 mg kg−1) > Cu (70.2 mg kg−1) > Zn (47.2 mg kg−1) > Cr (46.0 mg kg−1) > Ni (22.7 mg kg−1) > As (15.2 mg kg−1) > Cd (3.38 mg kg−1). The HMs would more likely to accumulate in dormitory dust and canteen dust. In the downtown area, Zn, As, and Cd had been preliminarily identified from fossil fuel combustion and natural geochemical processes. Cu and Pb would source from cooking and traffic transportation. Ni and Cr would likely reflect the contributions of natural soil weathering. No significant non-carcinogenic health risks were found to students or teachers from campus dust. Their children would more likely to exposure health risks when eating in the canteen, playing on the playground, or walking around the school gate. While the incremental lifetime cancer risk values revealed respiratory intake of HMs does not pose a carcinogenic risk on the campus.


Introduction
Heavy metals (HMs) are ubiquitous in the environment. They originate from both natural and anthropogenic activities (Wei and Yang 2010). Based on recent studies, HMs would have strong capacities to migrate, enrich, and contaminate (Rahman et al. 2019). Additionally, HMs are usually non-degradable and there is no known homeostasis mechanism for them (Doabi et al. 2018). People would be exposed to them via multi-pathway exposure (Sun et al. 2019). HMs in particulates, such as chromium (Cr), zinc (Zn), copper (Cu), lead (Pb), nickel (Ni), cadmium (Cd), and arsenic (As), have already been proved to lead to significant threats to ecosystems and cause carcinogenic and non-carcinogenic risk for people (Doabi et al. 2018;Men et al. 2018;Sahakyan et al. 2019). Additionally, as the source and sink for HMs, surface dust has become a hot topic in environmental pollution research, especially for urban atmospheric particulate (Men et al. 2018). Among all the assessment methods, the geo-accumulation index has been widely in HMs pollution assessment due to its comprehensive consideration of anthropogenic influences as well as natural sources for environmental input (Qadeer et al. 2020;). Moreover, health risk models origination at the U.S. Environmental Protection Agency (USEPA), have also been widely used to evaluate the health risk of HMs pollutants in urban dust, such as Kermanshah (Doabi et al. 2018), Beijing (Wei et al. 2015), and Dhaka (Rahman et al. 2019). Indicating, the infrastructural development in urban areas has placed great stress on the local environment (Soltani et al. 2015).
Even though lots of studies about HMs health assessment had been done in modernize cities (Doabi et al. 2018), the information about the health assessment to a particular group in a specific living environment, such as the education area, was still limited. Only a few pieces of research had a focus on HMs pollution in the education area. For example, based on the pollution characteristics and spatial distribution of HMs from nursery and primary school dust in Xi'an, Chen et al. (2014) had revealed the hot-spot area of HMs area mainly associated with industrial activities and traffic density, and limited adverse non-cancer health risk to children due to dust exposure. Li et al. (2017) had compared the pollution characteristics and risk assessment of HMs from street dust in different functional areas in Chengdu. Revealing, the concentration of HMs in the education area was relatively lower than in commercial area, traffic area, residential area, and park area.
As we know, universities or colleges is a place with a high density of students, teachers, and their families Wei et al. 2015). They study, work, and live on campus every day. With relatively large-scale campuses, universities or colleges can be always considered relatively isolated communities . Especially in Wuhan, one of the four biggest capitals of education in China, with 84 colleges and universities including over 150,000 graduate students and 1 million undergraduate students by the end of 2019. The lack of studies would limit our understanding of the contributions of spatial distribution characteristics, pollution, and potential human health risks to HMs in dust from different functional areas on campus, such as dormitory, canteen, playground, and school gate. Indicating, thousands of students, teachers, and their families may expose to the danger of HMs when they are studying, eating, playing, and resting every day, and we never evaluate the potential health risk at these places.
To fill the knowledge gap discussed above, in the present research, our study were (1) to determine the current status of HMs (including Cu, Pb, Zn, Cd, Ni, As, Cr) in dust from different universities and colleges in Wuhan; (2) to analyze the spatial distribution of these HMs in dust from four different functional areas (including the playground, dormitory, canteen, and school gate) in universities and colleges; (3) to evaluate the pollution of these HMs in campus dust using the Geo-accumulation Index; and (4) to assess the carcinogenic and non-carcinogenic health risks associated with these HMs.

Study area
Wuhan is the capital of Hubei province in Central China (Fig. 1), with a total resident population of over 10 million. With a total of eighty-four universities and colleges, Wuhan is the university cluster in Central China. Most of the colleges and universities are located on the east side of the Yangtze River, which is the educational and resident area in Wuhan. Moreover, Wuhan is also the biggest developing city in Central China. The GDP of Wuhan had reached 1.62 trillion yuan by the end of 2019. The climate of the area is humid subtropical with an average annual temperature of 15.8-17.5 ℃ and an annual rainfall of 1269 mm. Based on the meteorological statistics of the Hubei meteorological service since 1990, the local dominant wind direction is northeaster in winter (Liu et al. 2020b).
Geologically, Wuhan is located in the Yangtze River Basin, which is situated on the Yangtze Block and drains into several geotectonic units including Qinling-Dabie orogenic belt, Songpan-Ganzi terrane, and Cathaysia Blocak. In the area, the bedrock exposes ranging from Archean to Quaternary (Zheng et al. 2013). In the area, clastic rocks and carbonates wildly distribute the Upper Yangtze Block, while granites and metamorphic rocks dominate in the Middle and Lower Yangtze Block (Li et al. 2021). In the upper Yangtze Block, the concentration of CaO and MgO is relatively high in the constitution of the crustal materials. And these crustal materials create the characteristic of relatively high concentration of CaO and MgO in environmental mediums, such as soil, sediment, and ect (Ma et al. 2005).

Sampling and preparation
From November 5th to 9th, 2019, a total of seventy samples were collected from fourteen universities and colleges in two parallel zones (Fig. 1). Zone A is the downtown area with heavy traffic and intensive residence, while Zone B is the economic development area with construction projects and industrial parks, but with less traffic jams (Fig. 1).
The sampling universities and colleges are including famous universities, such as Wuhan University (WH-U), Huazhong University of Science and Technology (HZ-U), and Wuhan University of Technology (WT-U). The campus area of them were 3.47 km 2 , 4.67 km 2 , and 2.66 4.67 km 2 , respectively (Fig. 1). These kinds of universities are almost small independent communities. However, some local universities would have a relatively small campus. The campus area of Wuhan University of Science and Technology (ST-U), Hubei University (HB-U), Zhongnan University of Economics and Law (ZE-U), Hubei University Of Technology (HT-U), China University Of Geosciences (CG-U), Wuhan Textile University (WHT-U), Hubei University Of Education (HE-U), City College, Wuhan University of Science and Technology (CC-C), Hubei University of Traditional Chinese Medicine (CM-U) and Wuchang University of Technology (WCT-U) was1.70 km 2 , 1.4 km 2 , 1.87 km 2 , 1.11 km 2 , 1.43 km 2 , 1.33 km 2 , 1.14 km 2 , 0.57 km 2 , 0.79 km 2 , and 0.82 km 2 , respectively (Fig. 1). These kinds of universities would have a relatively tight link to local development. Moreover, the ZE-U was divided into Shouyi Campus (ZE-SC) and Nanhu Campus (ZE-NC), which are located in different areas (Fig. 1).
Moreover, ST-U located in the north of Zone A. HB-U, WH-U, ZE-SC, WT-U, and HT-U located in the center of Zone A. CM-U located in the southwest of Zone A. While, CC-C located in the northeast of Zone B. HZ-U, CG-U, WHT-U, HE-U and ZE-NC located in the center of the Zone B. WCT-U located in the south of Zone B (Fig. 1). Additionally, four different functional areas in each campus were chosen to collect dust samples, including playground dust, dormitory dust, canteen dust, and school gate dust. Details of the sampling sites are provided in Table S1.
During sampling, approximately 100 g of the dust particles were collected using plastic brushes and dustpans by a gentle sweeping motion from buildings at a height of 1.5-2 m. After each sampling, brushes, and dustpans were cleaned with paper towels. All samples were stored in paper bags wrapped with solvent-rinsed aluminum foil and then sealed in polyethylene bags for transport to the laboratory. The samples were then placed in a desiccator to get rid of moisture, and then a 100 µm sieve was used to remove coarse debris and small stones. And an agate mortar was used to grind and homogenize. Then all the samples had been sieved to 63 μm. Eventually, after homogenization, samples were placed in an air-tight container for storage.

Chemical analyses
Seven kinds of heavy metals (Cu, Pb, Zn, Cd, Ni, As, and Cr) in all dust had been determined in this research. They were analyzed according to the procedure explained by Cui et al. (2020). Briefly, the sieved samples (0.2 g) were weighed and placed into a digestion vessel with HNO 3 , HCl, and HF. The vessel was sealed tightly and placed in a digestion chamber. After cooling, the samples were collected, filtered, and diluted to a constant volume. To prevent contamination of the samples, all-glass dished and digestion vessels were immersed in 5% nitric acid for 24 h, then washed and dried before use. The concentrations of As were measured using an AFS-203E atomic fluorescence spectrophotometer. The concentrations of Cu, Pb, Zn, Cd, Ni, and Cr were measured with an inductively coupled plasma source-mass spectrometer (Perkin-Elmer Elan 9000).
The purity of all reagents was an excellent level of purity. The accuracy and precision of analysis were established by analysis of the national one-level soil standard materials. These tests showed that the analytical results were accurate and reliable. The logarithmic deviation (Δlg[C]) for all heavy metals was smaller than 0.05, and the quoted rate was 100%. Procedural blanks, spiked blanks, sample duplicates (10%) were analyzed to evaluate the precision. The relative double difference (RD) is < 10% and the analysis yield was up to 100%. The heavy metals found in the procedural blanks were generally below the limit of detection. No target heavy metals were detected in blanks. All the test results conform to monitoring requirements.

Heavy metals contamination assessment
The geo-accumulation index (I geo ) was used to estimate the natural variation in the heavy metal distribution in soil and identify the effects of human activities on the environment by Muller (1969) by using the following equation.
where C n is the concentration of heavy metal in the surface dust and B n is the geochemical background concentration value of corresponding measured heavy metals in Hubei province, China. Factor 1.5 is considered to be a background matrix correction value to accommodate some human effects and to allow possible fluctuations and variations in the reference background values (Kusin et al. 2018). The I geo is evaluated by dividing it into seven classes as given in Table S2.

Source apportionment method
To evaluate the obtained results, principal component analysis (PCA) was used. It was widely used to extract a smaller number of independent factors among available data for analyzing variables relationships (Liu et al. 2020a). PCA could make it easier to interpret a given multidimensional system by displaying the correlations among the original variables (Zhao et al. 2020). Additionally, PCA has also been widely applied to various environmental media, to identify pollution sources and to apportion natural versus anthropogenic contributions (Bi et al. 2020). The components of the PCA were transformed using varimax rotation with Kaiser Normalization after the analysis (Kaiser 1960). In the current study, PCA was used to elucidate the latent relationships between variables and for investigating pollutant sources. (1) The statistical analyses were performed using SPSS package version 22.0.

Health risk assessment
Nowadays, health risk assessment has been used to quantitatively describe the possibility of carcinogenic and non-carcinogenic risks of heavy metal pollutants to human beings, thus human health with linking environmental pollution. Basing on behavioral and physiological differences, people could be divided into adults and children (Liu et al. 2019). In Chain, most of the undergraduate and graduate students are over 18 years old. Indicating, they have already been adults. Therefore, in our research, adults mainly refer to students and teachers. Moreover, surface dust mainly enters the human body through skin contact, respiration, and handmouth direct intake (USEPA 2009). The average daily dose (ADD) was calculated for the three exposure pathway: ingestion, inhalation, and dermal absorption using the following formulas (USEPA 2009;Zhang et al. 2019) where ADD ing is the average daily exposure to particulates in dust through the hand-mouth intake in mg (kg d) −1 , ADD inh is the average daily exposure to particulates in dust through respiration pathways in (kg d) −1 , ADD derm is the average daily exposure to particulates in dust through skin contact in (kg d) −1 . The other parameters are defined, and values are provided in Table S3. Parameters were taken from the USEPA evaluation standards and corrected for local factors in China.
Non-carcinogenic risks were evaluated by comparison to the reference dosage associated with chronic toxicity. The heavy metals are unlikely to cause harm when the dose is below the reference value, otherwise they are risks. The noncarcinogenic risk posed by heavy metals can be expressed as follow (USEPA 2009;Wahab et al. 2020;Zhang et al. 2019): where RfD is the reference dose (mg kg −1 d −1 ), which is regarded as an estimate of daily exposure to the human , HQ is the ratio of the average daily dose to the RfD of a specific metal for a single pathway, HI is a cumulative metric for HQs for individual heavy metals and exposure pathways. Base on USEPA (2001) report, if HI < 1, it is unlikely to hurt the health of the exposed individual. However, if HI > 1, it indicates that heavy metals would cause non-carcinogenic risk to the population (Eziz et al. 2018).
Unlike the non-carcinogenic risk, for health risks associated with carcinogenic heavy metals, the incremental lifetime cancer risk (ILCR) was estimated as the incremental probability of an individual developing cancer over time due to exposure to carcinogenic heavy metals (USEPA 1989). The ILCR was determined as in the following formula (Doabi et al. 2018;Zhang et al. 2019): where SF is the carcinogenic slop factor of heavy metals (mg kg −1 d −1 ). If the ILCR value is below 1 × 10 -6 it is accepted that there are no significant health risks for humans. While the acceptable range of ILCR is between 1 × 10 -6 and 1 × 10 -4 (Liu et al. 2019). According to the previous researches, RfD and SF values in different exposure routes are given in Table S4 (Chen et al. 2015;Eziz et al. 2018;Ferreira-Baptista and De Miguel 2005;Lu et al. 2014).

Data analysis
The minimum, maximum, median, mean, standard deviation (SD), and coefficient of variations (CV) of research data were calculated with SPSS 22.0 statistical package (Statistical Product and Service Solutions, SPSS Inc., USA). The standard deviation and coefficient of variations were incorporated to reflect the degree of dispersion distribution of different heavy metals (Cui et al. 2020). Two data mapping software packages were used including ArcGIS desktop 10.5 (ESRI, Redlands, CA, USA) and OriginPro 2018C (Origin-Lab, Northampton, Massachusetts, USA). Table 1 had shown the concentrations of HMs (Cu, Pb, Zn, Cd, Ni. As, and Cr) in campus dust in different universities and colleges. In all samples, HMs concentration was ranked Pb (83.5 ± 57.8 mg kg −1 ) > Cu (70.2 ± 52.2 mg kg −1 ) > Zn (47.2 ± 102 mg kg −1 ) > Cr (46.0 ± 27.8 mg kg −1 ) > Ni (22.7 ± 13.2 mg kg −1 ) > As (15.2 ± 6.20 mg kg −1 ) > Cd (3.38 ± 2.25 mg kg −1 ). Moreover, the CV values of all HMs in all campus dust were relatively high (over 39.9%). The CV values were usually used to reflect the average degree (7) ILCR = ADD × SF of variation between HM contents at different sampling sites (Cui et al. 2020). Indicating, HM concentrations in campus dust in Wuhan were highly variable. Especially, the CV value of Zn was 122%, indicating a spatially heterogeneous distribution of Zn. The concentration of Zn varies significantly in campus dust in Wuhan. This is attributed to local pollution sources or artificial non-point pollution sources (Lyu et al. 2017). Comparing with local background values, the median concentrations of Cu, Pb, Zn, Ni, As, Cr, and Cd were 2.54, 3.61, 1.00, 0.73, 1.26, 0.58, and 22.4 times higher than their corresponding background values, respectively.

Heavy metal concentration in campus dust
Comparing the concentration of HMs in school dust and road dust in the education area of some typical cities in China, the concentrations of Cu, Pb, Ni, and Cr in campus dust from Wuhan was similar to those in road dust in education from Chengdu  and Beijing (Wei et al. 2015) (Table S5). Moreover, the concentrations of Pb, Ni, and Cr in campus dust from Wuhan were lower than those in school dust from Xi'an . Especially, the concentrations of Zn in Wuhan campus dust were typically lower than those from Chengdu , Beijing (Wei et al. 2015), Shanghai (Bi et al. 2018) and Xi'an ) (Table S5). A big city like Wuhan is an assembly of different land-use types, the distinctive artificial activities in each functional area could release different kinds of heavy metals content (Trujillo-Gonzalez et al. 2016). Such as, in Wuhan, the concentration of Zn and Cr from road dust in urban and industrial areas is higher than that in campus dust (Yang et al. 2011). And the concentration of Ni and Zn in campus dust is similar to that in surface dust in the urban area (Gong et al. 2010), while the concentration of Cu, Pb, and As in campus dust are similar to that in suburb area (Tadesse et al. 2018). All the results indicated the concentration of most HMs in campus dust from Wuhan related with the local development and artificial activities.
Previous studies had already supported that Cd had a relatively higher concentration in Wuhan (Tadesse et al. 2018). In Yangtze Block, the relative abundance of Cd was 0.089 × 10 -6 in carbonatite (Talor and Mclennan 1995). It indicates the content of Cd was relatively high in crustal rocks in the area. Moreover, the previous study had already supported that the concentration of Cd had a positive correlation with Zn, Cu, Pb, and Mn in the sediment in Yangtze River in the Wuhan area (Ma et al. 2005). And it was also believed that the high concentration of Cd in alluvial soils in Wuhan was from the erosion of minerals and crust rocks (Li et al. 2021). It indicates that the natural factors may be a source for the relatively high level of Cd concentration in Wuhan . Still, fossil fuel combustion and industrial discharges from smelting and electric plating may significantly contribute to the wide spreading of Cd in Wuhan (Wei et al. 2009;Zhang et al. 2015).

Spatial distribution of heavy metal pollution
The mean values of I geo for Cu, Pb, Zn, Cd, Ni, As, and Cr in dust samples of universities and colleges were shown in Fig. 2. The contamination level of Cd was the highest of the seven HMs, followed by Pb and Cu. According to Fig. 2 Spatial distribution of Geo-accumulation index (I geo ) for HMs in campus dusts from different universities and colleges. The I geo value lower than zero, indicating no contamination, was not shown in the figure the standard of contamination degree by I geo (Förstner et al. 1990), the mean values of I geo indicated heavily contaminated with campus dust by Cd, slightly to moderately contaminated by Cu and Pb, uncontaminated to slightly contaminated by As and Zn, uncontaminated by Ni and Cr. These results also revealed that the education areas were relatively low contaminated by most HMs (Pan et al. 2017). Indicating, artificial activities would have less influence on universities and colleges ). However, as Cd had a relatively higher concentration in Wuhan (Tadesse et al. 2018), education areas were also contaminated by Cd. Additionally, based on the mean concentration of all kinds of HMs in Zone A and B (Table 1), the I geo values of Cu and Pb were 0.68 and 1.10 in Zone A, respectively, while those were 0.51 and 1.03 in Zone B, respectively. The difference of the development characteristics in the two areas might affect the source of Cu and Pb. As we know, Zone B is an economic development area. Cu and Pb may be source of traffic emission, industrial emission, and city construction (Dong et al. 2017). While Zone A is the downtown area with heavy traffic. The Cu accumulation may commonly release through the wear of vehicular materials, such as brakes (Świetlik et al. 2015) and Pb may also be from anthropogenic source, such as the use of leaded gasoline (Doabi et al. 2018). Figure 2 also showed the local dominant wind, which is northeaster in winter, may affect the distribution of I geo values of HMs. Such as, in Zone A, the mean I geo values of HMs in campus dust from the seven universities were ranked as follows: ST-U (northeast of Zone A) < HB-U, ZE-SC, WH-U, WT-U, and HT-U (center of Zone A) < CM-U (southwest of Zone A). Additionally, the same results were also found in zone B, such as CC-C (northeast of Zone B) < CG-U, HZ-U, WHT-U, HE-U, and ZE-NC (center of Zone B) < WCT-U (southwest of Zone B), indicating the accumulation of HMs in campus dust would be influenced by local meteorological conditions.

Pollution characteristics of different functional areas dusts
The results of I geo of HMs from different functional areas were presented in Fig. 3 and Table S6. Generally, for most HMs, the I geo value from different functional areas showed as similar in Fig. 3. Indicating, the pollution characteristics for most HMs in campus dust were effect by local atmospheric conditions (Liu et al. 2020b). Moreover, the mean values of I geo of As, Ni, Zn, and Cr were lower than 0. Indicating, the campus area in Wuhan had less affected by these metals. All the I geo values for Ni and Cr in playground dust, dormitory dust, and school gate dust were lower than 0. Revealing, these areas were not threatened by these metals. Figure 3 and Table S6 also showed, the playground dust was uncontaminated or slightly contaminated by As and Zn, while it was slight to moderately contaminated by Cu and Pb in most universities and colleges. The highest I geo value for Cd (5.99) was found in playground dust. And all the I geo values for Cd were over 2. Indicating, playground dust was heavy to extremely contaminated by Cd. In dormitory dust, the mean I geo value for Pb (1.43) and Cu (0.86) was almost significantly higher than that in playground dust, respectively. While it was uncontaminated or moderately contaminated by Zn. The mean I geo value for Cd was 3.89 in dormitory dust. Showing, dormitory dust was also heavily to extremely contaminated by Cd. Comparing with dormitory dust and playground dust, the I geo values for all HMs were relatively lower in school gate dust. Most I geo values for As and Zn were below 0. The I geo values for Cu in 87% samples and Pb in 67% samples were below 1. Indicating, school gate dust was uncontaminated or moderately contaminated by these metals. Moreover, all the I geo values for Cd were between 3 and 4. Heavily contaminated by Cd could be revealed in school gate dust. Canteen dust was contaminated by all the HMs in different degrees. The I geo value for Cr in 5% samples, As in 47% samples, Ni in 11% samples, Zn in 21% samples, Cu in 99% samples, Pb in all samples, and Cd in all samples was over 0 in canteen dust. The I geo value for Zn in 5% samples and Pb in 11% samples was over 2. Additionally, 16% of the I geo value for Cd was over 4 and others were over 3. Revealing, the canteen dust was also heavily to extremely contaminated by Cd.
As far as the overall behavior of the HMs understudy is concerned, based on I geo , it could reveal that the playground dust, dormitory dust, school gate dust and canteen dust samples in universities and colleges were practically uncontaminated to moderately contaminated for Cr, Ni, As and Zn, practically uncontaminated to heavily contaminated for Cu and Pb, and heavily to extremely contaminated for Cd. The highest I geo value for Cd (5.99) was shown in playground dust.
According to the I geo values, only canteen areas were threatened by all the HMs. In general, cooking fumes may be the main reason for these HMs (Sun et al. 2017). Li et al. (2017) had already revealed the direct emission of food, cooking oil, ingredients, and fuel in the cooking process in Chinese kitchens would increase the content of HMs, such as Pb, Zn, As, Fe, Cu, and Cr. Additionally, unqualified cookstoves and other cooking utensils would also release heavy metals at high temperatures . Indicating, HMs would easily accumulate in the dust around the canteen. Except for the highest I geo value for Cd (5.99) in playground dust, the mean I geo values for HMs were lower in playground dust and school gate dust than that in dormitory dust and canteen dust. As the playground and school gate area are relatively spacious areas. The dust in spacious areas would easily effect by local atmospheric flow and hardly accumulate for a long time (Kolakkandi et al. 2020).
However, the dormitory and canteen areas are always surrounded by buildings, which would benefit HMs accumulation (Adimalla et al. 2020).

Source apportionment of HMs in campus dust
Source identification of HMs is critical for pollution prevention and human health protection . In general, significant correlations between pairs of HMs always suggest a common or combined origin, whereas weak correlations indicate different origins .
For the universities in Zone A, the Kaiser-Meyer-Olkin index was 0.739 and the result of Bartlett's sphericity test was significant at p < 0.001. Revealing, the HMs concentrations in Zone A was suitable for PCA (Liu et al. 2020a). The loading plot of PCA was shown in Fig. 4. The results demonstrate that there are three eigenvalues higher than 1.00, and these three factors explain 71.8% of the total variance.
The first principal component (PC1) explains 38.3% of the total variance. It includes significant loadings for Zn, As, and Cd with loading values of 0.85, 0.80, and 0.56, respectively. Moreover, the concentration of Cd was significantly higher than the local background value. Many studies (Bhuiyan et al. 2021;Zhang et al. 2015) had already revealed Cd may relatively abundant in the crust rocks of the Yangtze River basin, indicating that Cd probably originated from natural geochemical processes such as weathering. Additionally, universities would like a small community, people would use fossil fuel for cooking every day. Indicating, fossil fuel combustion would also be the probable source for Cd (Bi et al. 2020). The concentration of Zn was relatively lower Fig. 3 The statistic of Geo-accumulation index (I geo ) values of HMs in campus dusts around the canteen, dormitory, playground, and school gate areas. The I geo Class 0, 1, 2, 3, 4, 5, and 6 represented no contaminated, slightly contaminated, moderately contaminated, moderately to heavily contaminated, heavily contaminated, heavily to extremely contaminated, and extremely contaminated, respectively, which is shown in Table S2 210 Page 10 of 13 than the local background value. While the concentration of As was slightly higher than the local background value. Indicating, they may source from natural geochemical processes. Additionally, Kolakkandi et al. (2020) also proved As and Zn may also source from fossil fuel combustion. Indicating, the sources of As, Zn, and Cd had been preliminarily identified to be a mixture of anthropogenic sources, such as fossil fuel combustion and natural geochemical processes such as weathering. In the loading plot (Fig. 4), Pb and Cu formed a group, with similar loading for PC2. I geo values indicate the campus dust was practically uncontaminated to be heavily contaminated for Cu and Pb. Revealing, they would source from many anthropogenic activities, such as heavy traffic, fossil fuel combustion, and industrial exhausting (Zhang et al. 2012). However, in Wuhan, the universities would be more like isolated communities. Teachers and students learning, eating, and living here. Especially, in Zone A, which is the downtown area without industrial activities, the Cu and Pb in campus dust would more likely source from cooking. In Chinese kitchens, the use of cooking oil, ingredients, and fuel would emission Pb and Cu . And the unqualified cookstoves and other cooking utensils would also release Pb and Cu at high temperatures . Moreover, previous researches also revealed, the accumulation of Cu and Pb would commonly release through traffic sources, such as the wearing of the vehicular materials and using leaded gasoline (Zhang et al. 2012). Therefore, in some universities with a relatively small campus in Zone A, traffic problems would also affect by anthropogenic activity. Indicating, the sources of Cu and Pb had been preliminarily identified to be anthropogenic sources, such as cooking and traffic transportation. PC3 accounted for 15.3% of the total variance and was dominated by Ni and Cr. The concentration of these two HMs was lower than their soil background values. We observed no obvious geoaccumulation of Ni and Cr for most campus dust from Zone A. Therefore, PC3 would likely reflect the contributions of the natural soil weathering.
However, for the universities in Zone B, the Kaiser-Meyer-Olkin index was 0.372 and the result of Bartlett's sphericity test was significant at p > 0.001. Indicating, the HMs concentrations in Zone B were not suitable for PCA (Liu et al. 2020a). Moreover, Table S7 also revealed the HMs from campus dust showed no significant correlation with each other in Zone B. Zone B is the economic development area with lots of construction projects and industrial parks in Wuhan. HMs in this area would from multiple sources. Indicating, the source of HMs from campus dust in Zone B would mainly infect affect by local development, such as industrial activities, heavy traffic, local construction, etc.

Potential health risk assessment of heavy metals in campus
The non-carcinogenic health risks posed by HMs in campus dust for different intake pathways were shown in Table S8. The non-carcinogenic health risk posed by different HMs in campus dust and for the different exposure pathways varies significantly. Generally speaking, among the three routes of exposure, the HQ value of the ingestion pathway was the highest. Similarly, results are also revealed from surface dust and street dust (Tang et al. 2017). Considering the lower body weight than adults, children are believed to be of higher intake of HMs . Additionally, health risks through ingestion are greater for children also due to their hand-to-mouth activity (Liu et al. 2020b;Zhang et al. 2020). Their nervous system is still developing and prone to high rates of HMs diffusion (Cui et al. 2020).
For all the people, the health risks were ranked As > Pb > Cr > Cd > Cu > Ni > Zn, based on the HQ value. Additionally, the HQ values for single heavy metal did not exceed the USEPA safe threshold (Wei et al. 2015). Indicating, for teachers and students, single heavy metal would not cause significant non-carcinogenic health risks on campus in Wuhan. However, for children, the HI values of HMs in campus dust from HB-U, WH-U, ZE-SC, WT-U, HT-U, CM-U, CG-U, HZ-U, WHT-U, HE-U, ZE-NC, and WCT-U were 1.39, 1.40, 1.38, 1.25, 1.55, 1.89, 1.37, 1.26, 1.32, 1.50, 1.74, and 1.52, respectively. Indicating, multiple HMs from campus dust from these universities above would cause harm to the physical health of children, and measures should be taken to mitigate the risks. Figure S1 showed for all the people, the HI values of different areas campus dust were ranked Fig. 4 PCA results of HMs from campus dust in Zone A in the threedimensional space: plot of loading of the first three principal components canteen > dormitory > playground > school gate. For children, the HI values for HMs in these places were all over 1.00. Most children living in university would be the teacher's son and daughter. They would barely go to the dormitory, which is the living place for undergraduate and graduate students. Indicating, the children would be more likely to exposure health risks, when eating in the canteen, playing on the playground, or walking around the school gate. Moreover, Fig. S1 also suggested that HMs in campus dust will not damage the physical health of teacher, undergraduate, or graduate students.
Additionally, the carcinogenic risks posed by Pb, Cd, Ni, As, and Cr in campus dust were shown in Table S9. Based on the findings, the ILCR values of students and teachers in the study area were higher than that of children. Indicating, the relatively high respiration rate would increase the carcinogenic risks for students and teachers (Wahab et al. 2020). However, the carcinogenic risks posed by HMs in campus dust were lower than 10 -6 . Indicating, it was significantly lower than the carcinogenic risk level (Adimalla et al. 2020). Therefore, the respiratory intake of HMs does not pose a carcinogenic risk and will not damage human physical health on the campus.

Conclusions
Our study demonstrated that the average concentrations of HMs in campus dust from universities or colleges in Wuhan ranked Pb > Cu > Cr > Zn > Ni > As > Cd. The contamination level of Cd was the highest of the seven HMs, followed by Pb and Cu. And I geo values also showed uncontaminated to slightly contaminated with campus dust by As and Zn, while uncontaminated by Ni and Cr. The distribution of I geo values in all universitiess revealed the accumulation of HMs in campus dust would be influenced by local meteorological conditions. According to the I geo values, only canteen areas were threatened by all the HMs. The HMs would more likely to accumulate in dormitory dust and canteen dust, as the dormitory and canteen areas were always surrounded by buildings. In Zone A, according to the results of PCA, Zn, As, and Cd had been preliminarily identified to be a mixture of anthropogenic sources, such as fossil fuel combustion and natural geochemical processes such as weathering. Cu and Pb would source from anthropogenic activities, such as cooking and traffic transportation. While Ni and Cr would likely reflect the contributions of the natural soil weathering. However, HMs from campus dust showed no significant correlation with each other in Zone B. Indicating, the source of HMs from campus dust in Zone B would mainly affect by the local development, such as industrial activities, heavy traffic, local construction, etc. No significant non-carcinogenic health risks were found to students and teachers by campus dust. However, multiple HMs from campus dust would cause harm to the physical health of children. They would more likely to exposure health risks when eating in the canteen, playing on the playground, or walking around the school gate, especially around the canteen. While the ILCR values revealed respiratory intake of HMs does not pose a carcinogenic risk and will not damage human physical health on campus. However, the accumulation process of HMs in different functional areas in universities would still need to be solved in further research.