Experimental research on the RUDN University campus on the issue of exhaust fumes

. The object of the study is the campus/student housing of the Russian Peoples' Friendship University named after Patrice

The described results of the vehicle counts during the day allow us to summarise that Miklukho-Maklaya Street has a high traffic load (about 21531 TV per day).Thanks to the data obtained, it is also possible to generate a graph of average daily traffic congestion on Miklukho-Maklaya Street.The resulting graph and the statistical data for Miklukho-Maklaya Street suggest the following patterns:  The greatest impact on the environment is caused by the exhaust fumes emitted by the concentration of TV on the street in question during the periods from 9:00 to 10:00 and from 17:00 to 18:00.At that time, the number of TVs on the street reaches almost 1,000 vehicles per hour.This is due to the predominant part of the urban population moving to workplaces. The least negative impact from TV traffic on Miklukho-Maklaya Street occurs from 13:00 to 15:00 when the number of vehicles per hour is not more than 500.This is due to the fact that, on weekdays, the majority of the city population is at their workplaces for this time period. The largest number of vehicles passing through Miklukho-Maklaya Street per day is category M1.The second most numerous are category M2 TVs (minivans, SUVs, minibuses).These vehicles emit the most exhaust fumes due to the greater number of traffic vehicles.In the Miklukho-Maklaya street section, ambulances were very rarely found, so they are not counted in these statistics.Congestion on the Akademika Oparina street section (Table 2) The following facts can be summarised through the diagram in Figure 2 and Table 2:  The highest traffic congestion on the street in question is observed in the periods from 9:00 to 10:00 and from 18:00 to 19:00.In this period of time the number of TV in the area reaches 200 units (pcs.).This is due to the majority of the urban population moving to workplaces. The least traffic congestion on the Akademika Oparina Street section is observed in the period from 13:00 to 16:00.During this period, the number of vehicles reaches a maximum of 70-80 vehicles (units) and a minimum of 60 vehicles. As in the previously considered section of Miklukho-Makal Street, the main TV types are TV categories M1 and M2, as well as category M3 (buses, minivans, SUVs, pickups, minibuses).Detection of TV category M3 is explained by the presence of an ambulance station in Samora Macela Street, as well as two hospitals.Congestion on the Samora Machel Street section (Table 3)  The data obtained reveal the following features of the street section in question:  The highest congestion occurs in the time periods from 8:40 to 10:00 and from 17:00 to 18:00.As in the previous cases, this is due to the periods when people are travelling to and from their workplaces. The least congestion is between 13:00 and 15:00.This is due to the fact that on weekdays the majority of the urban population is at their workplaces for this time period. The largest total exhaust emissions will come from vehicles of categories M1, M2, and M3.There is a noticeable increase in the number of category M3 TV in the study area, which is due to the presence of an ambulance station on the street as well as two hospitals.Traffic on Leninsky Avenue.The vehicular traffic on Leninsky Avenue is extremely heavy.The impact of exhaust fumes and noise from vehicles on the avenue in question has a significant impact on the environment and human beings.
The section of Leninsky Avenue that is closest to the RUDN campus will not be considered and taken into account in this study due to the following factors:  The shortest distance between the avenue and the campus is reached via Miklukho-Maklaya Street and is 142 metres. The negative impact of vehicle exhaust from Leninsky Avenue is extremely low due to the distance and natural and anthropogenic barriers.Buildings and tree crops planted along the avenue protect the environment at the back of the district from noise and exhaust substances.Like any other buildings along the roadway, the buildings along Leninsky Avenue have protective layers / reinforcements against the effects of noise and exhaust fumes.The following conclusions can be drawn from observation of traffic congestion on a number of street sections: 1.The major sources of pollutants -exhaust gases, on the specified street sections are vehicles of the following categories:  TV category M1-cars with up to 8 passenger seats;  TV category M2-motor vehicles with more than 8 passenger seats with a total weight of not more than 5 tonnes;  TV category M3-motor vehicles with more than 8 passenger seats with a total mass exceeding 5 tonnes.M1-cars are observed to be most numerous on all street segments; M1-cars are present in many times greater numbers on the roads along the RUDN campus and, therefore, contribute more negatively by emitting exhaust fumes into the campus area.
2. Considering the time intervals of vehicular traffic, the heaviest traffic is achieved during the following time intervals:  from 9:00 am to 10:00 am;  from 17:00 to 19:00; These time periods are called "rush hours", when there is a large accumulation of motor vehicles on the road which results in an intense emission and spread of exhaust gases into the environment.3.
3. The biggest traffic flow is on the section of Miklukho-Maklaya Street, followed by the section of Samara Machel Street in terms of traffic intensity.The RUDN campus has the lowest traffic intensity, and thus the lowest impact on the environment, on the section of Akademika Oparina Street.

Correlation of measured parameters
Determining the relationship/dependence between the parameters under study is one of no small importance in the process of forming a statistical distribution of the exhaust gas.
A correlation matrix was generated to study the dependence of the measured parameters on each other (Table 4).With the help of a correlation matrix and the construction of correlation plots it was possible to determine the following correlation:  PM 2.5 and PM 10 weighted substances have a weak positive correlation (Fig. 5).This is explained by the fact that finely dispersed substances up to 2.5 micrometres in size are part of the finely dispersed substances up to 10 micrometres, respectively, when the concentration of PM 2.5 increases, the concentration of PM 10 also increases.The obtained measurement results of the substances were shown in Figure 6.The PM 2.5 substance distribution map shows three areas in which exceedance of MPC c.c. and MPC c.d. values can be observed:

PM 2.5 suspended solids concentration on the RUDN campus
1.The section of Miklukho-Maklaya Street near fast food outlets (People's Kitchen, KFC, etc.).Excessive concentration of up to 40 µg/m 3 has been detected at the site.The excessive concentration is related to the traffic jams formed in this area, increased traffic load, and the presence of fast-food outlets that also emit various substances into the atmosphere, having a negative impact on it.
The distribution of substances from this site across the campus is not uniform: due to a number of factors (wind direction and speed, physical barriers -buildings/buildings, trees) most of the emitted substances are dispersed towards the main building.There is also a large number of parked vehicles in this area -vehicles are often parked in the city car parks as well as the RUDN car parks, which also contributes significantly to the distribution of exhaust on the campus.
2. The second area of excess concentrations is near dormitory buildings 6, 7 and 13.The PM 2.5 exceedance of suspended solids is associated with the life processes of the residents in these buildings, as well as the vehicle maintenance facility.Due to climatic factors, vehicles and car service activities have a significant negative impact on the air basin of the campus area.The vegetation barrier forested area behind the car service station and the southwest wind direction shifts the high concentration of suspended matter deep into the dormitory area.The PM exceedance of 2.5 at this site varies from 36 to 39 µg/m 3 .
3. The third plot is located on the eastern side of the campus (east of the second point).The buildings on this site include: -Interclub; -Grocery shops; -Restaurants and cafés.The high concentration of PM 2.5 in this area is due to the above-mentioned sources.Vehicles have the least negative impact on this area due to the presence of natural barrierstrees on the eastern side and buildings constructed along the stretch of Miklukho-Maklaya Street.
The concentration of fine sediment PM 2.5 reaches 37-38 µg/m 3 at this site.The dispersion of substances is uniform throughout the campus due to the evenly spaced campus buildings -dormitories, restaurants and cafes.However, this factor is compromised by the lack of high buildings in the north-west of the site, thereby joining the second and third areas of exceedance of PM 2.5 concentrations of finely dispersed substances.
The fine sediment concentration distribution map of PM 2.5 revealed three areas of exceedance of the average daily maximum permissible concentrations.These are associated with sources of exposure such as: -Vehicles; -Fast food outlets; -Automobile service stations; -Restaurants and cafés.
It is these sources of suspended matter that emit the greatest amount of substances into the environment and therefore have the greatest negative impact on people and the environment.

PM 10 suspended solids concentration on the RUDN campus
During the processing of the measured results, a PM 10 suspended matter distribution map was generated: The following conclusions about the nature of concentration exceedance can be drawn from the generated RM 10 fine particulate matter concentration distribution map: The data obtained show an area where an exceedance of 60 to 67 µg/m 3 of concentration occurs.This site is located on the carriageway as well as the car park near the Humanities and Social Sciences building, the dormitory buildings and the car park of the RUDN medical building.
The dispersion of substances to the north and south is complicated due to the barriersacademic buildings and RUDN dormitories, as well as trees planted along the Miklukho-Maklaya street section, this can be observed due to the frequency of concentration change isolines at short distances.
The increased distance between isolines along the Miklukho-Maklaya section indicates a smooth change in concentration towards the northwest and southeast due to the lack of barriers, wind effects as well as regular vehicle traffic along the entire Miklukho-Maklaya section.
The increased concentrations of PM10 in this area are due to the following factors: 1.The checkpoint of RUDN dormitories near the 7th dormitory building.Every day near this checkpoint a great number of cars and taxis are formed; 2. The entrance to the car park along the dormitory buildings is located near the checkpoint.Vehicles (mostly taxis) pass through, park and wait with the TV running at this very spot; 3. Turning around on the road in reverse or into the parking area.More often than not, vehicles make a U-turn in this section.During a U-turn the fuel consumption increases and consequently the amount of exhaust gases (PM 10) also increases.4. Car park on the side of the Humanities and Social Sciences Building.This car park is one of the largest in the whole campus of RUDN, therefore, the accumulation and distribution of exhaust gases in this area is increased.5.The construction of the underground and the construction of the residential complex.
Both of these processes take place in the immediate vicinity of the site with elevated concentrations, releasing suspended matter into the atmosphere.The single area of elevated PM 10 substance concentration identified in the mapping has an exceedance of at least 5 µg/m 3 .

Volatile Organic Compound Concentration (TVOS) on the RUDN campus
The processing of VOC (volatile organic compound) measurements resulted in a TVOS distribution map (Figure 8) Considering the TVOS concentration standards previously outlined in Section 3.2, it can be concluded that there are three sites on the campus with elevated concentrations of volatile organic compounds which may have a negative impact on humans and the environment.
The first site is located in the south-west of the study area.TVOS concentration there reaches 4 mg/m3.The presumed source of the compounds is an automobile technical centre located just on the southern boundary of the campus.
The second area of excessive concentrations is located to the north-east of the RUDN main building, on the territory of the park.VOC concentration at this site reaches 3 mg/m3.Excessive concentration is explained by possible impact of several factors (sources) on this environment:  Vehicles moving along the section of Miklukho-Maklaya Street, as well as those located in the parking area;  Spraying substances when fertilising and watering the area;  Substances delivered from public catering facilities (canteens, cafés etc.); The third site is located in the north-east area of the campus, with exceedences of up to 2.9 mg/m3.This excessive concentration is due to the presence of a garage cooperative with a number of unauthorised dumps.Construction works in the area and the snow-melting facility to the east of the study area also play a significant role in exceeding concentrations.Due to the previously described equivalent and maximum noise level standards, the following conclusions can be drawn on the noise pollution of the RUDN campus: 1.There are no areas throughout the RUDN campus in which the equivalent and maximum sound levels exceed the MAC (maximum allowable concentration).This indicates that the noise characteristics of the campus have the best performance in the urban environment, as well as the absence of noise pollution.2. There are two areas on the RUDN campus with elevated sound levels -on the roadway of Miklukho-Maklaya street.In these areas the noise level reaches 46-48 dBA.The maximum recorded noise level in this section is 52 dBA.This factor has a direct correlation with the volume of traffic on the section of Miklukho-Maklaya Street.Due to high traffic congestion, as well as the peculiarities of the intersection with Leninsky Prospekt, daily "traffic jams" are observed in this section of the street, where vehicles can create noise pollution.The recorded exceedance of the MPL is due to the creation of traffic jams as well as turning into the other lane.

Conclusion
Phenols were not described in this work due to the fact that no nodes on the campus grid identified these substances when they were measured.Therefore, it is not possible to create a distribution map of the HCHO substances.The calculated correlation matrix revealed a weak direct correlation between the concentration of PM 2.5 and PM 10 due to the inclusion of PM 10 particles, PM 2.5 particles in suspended particles.
The generated maps revealed the following:  MPC s.c.exceeded in three areas of the RUDN campus for suspended PM 2.5 due to the presence of the following sources-vehicles; fast food outlets; car service; restaurants and cafes.MPC exceedance reaches 5-9 µg/m3. Exceedance of MPC sc. in an area of the RUDN campus for suspended solids PM 10 is caused by car parks, checkpoints, as well as roadway turnarounds, which are sources of measured substances.In this area, PM10 concentrations increase to 7 µg/m3 from the MPC. Elevated TVOC concentrations in the three areas of the campus have different sources of negative impact, but the main ones are the TC, the Vehicle Garage, and the construction of a residential complex near the study area. The absence of exceedance of noise levels indicates the absence of noise pollution on the RUDN campus due to the range of measures currently taken to reduce this type of pollution.The traffic congestion of the Miklukho-Maklaya street section plays a key role in the formation of most of the areas with elevated concentrations of suspended particulate matter PM 10 and PM 2.5.

Fig. 3 .
Fig. 3. Average traffic congestion on a section of Samora Machel Street

Fig. 4 .
Fig. 4. Distribution of exhaust gas from the section of Leninsky Avenue across Miklukho-Maklaya Street.

Fig. 8 .
Fig. 8. Concentration of volatile organic compounds on the RUDN campus

Table 1 .
Baseline data on the Miklukho-Maklaya street section

Table 2 .
Baseline data on the Akademika Oparina street section

Table 3 .
Baseline data for the Samora Machel Street section

Table 4 .
Correlation matrix of measured parameters.