Urban Air Pollution by Laser Photoacoustic Spectroscopy and

Simplified Numerical Modeling of Gas Pollution in Urban Canyon

MIOARA PETRUS1, CRISTINA POPA1, ANA-MARIA BRATU1

1Laser Department,

National Institute for Laser, Plasma, and Radiation Physics,

409 Atomistilor St., PO Box MG 36, 077125 Magurele, Ilfov,

ROMANIA

Abstract: - With rapid urbanization and industrialization, atmospheric pollution has emerged as a significant

environmental challenge in Romania. Employing a laser photoacoustic spectroscopy detector, researchers

analyzed ethylene, benzene, and toluene simultaneously across three distinct environmental settings in the

country's southern region. This investigation spanned from March to August 2021, covering both spring and

summer seasons. Measurements were taken at a breathing height of 1.5 meters above ground level. The highest

concentrations of ethylene (116.82 ± 82.37 ppb), benzene (1.13 ± 0.32 ppb), and toluene (5.48 ± 3.27 ppb) were

recorded at measurement point P1, situated within the city amidst residential buildings during the summer

season. Additionally, the highest ozone levels (154.75 ± 68.02 ppb) were observed at point P3, located in an

industrial area, during the summer. The behavior of gas concentrations is influenced by meteorological factors

such as temperature, wind speed, and direction. The high toluene/benzene ratio suggests that traffic and

industrial emissions are the primary sources of these pollutants. Notably, benzene and ozone concentrations

exceeded prescribed limit values based on the measurements. Concurrently, a numerical model was employed

to assess the impact of greenery on mitigating pollution in urban canyons. Specifically, the study focused on

how wind velocity affects the dispersion of benzene pollutants in a street canyon. This study's governing

equations utilized for air pollutant flow were the Reynolds-averaged Navier–Stokes (RANS) equations for

compressible turbulent flow and moisture transport in air, implemented through Comsol software.

Key-Words: - laser photoacoustic spectroscopy, air pollution, ethylene, benzene, toluene, numerical simulation.

Received: February 16, 2023. Revised: December 19, 2023. Accepted: February 15, 2024. Published: April 10, 2024.

1 Introduction

Clean air is essential for all life forms on Earth. Not

only does air quality impact human health, but it

also affects crucial environmental components such

as water, soil, and forests, which are vital resources

for human development, [1]. Urbanization,

characterized by a relative increase in a country's

urban population alongside a faster growth in the

economic, political, and cultural significance of

cities compared to rural areas, is an integral aspect

of economic development, [1]. However,

urbanization brings various challenges, including

the rise in urban population, high population

density, expansion of industrial activities (both

medium and small scale within urban areas and

large scale in surrounding areas), the proliferation of

high-rise buildings, and increased vehicular traffic,

[2]. These activities collectively contribute to air

pollution. The configuration of a city and the

distribution of land use determine the placement of

emission sources and the flow of urban traffic,

which significantly impacts urban air quality.

Factors such as geographical location, climate,

meteorological conditions, city planning and design,

and human activities play crucial roles in the

dispersion and distribution of air pollutants, thereby

influencing urban air quality, [3].

2 Problem Formulation

Various types of pollution, including air, water,

thermal, noise, and soil contamination, present

significant environmental challenges. Among these,

air pollution stands out as the primary cause of

mortality globally, with reports indicating millions

of lives lost due to pollution-related causes, [4]. Key

air pollutants mainly stem from industrial activities,

factories, and transportation sources, such as carbon

dioxide, volatile organic compounds (VOCs),

nitrogen dioxide, ozone particles, and sulfur

dioxide. In urban areas, vehicle emissions notably

contribute to air pollution, particularly in densely

populated centers, placing a significant burden on

the transportation sector, [5].

International Journal of Environmental Engineering and Development

DOI: 10.37394/232033.2024.2.9

Mioara Petrus, Cristina Popa, Ana-Maria Bratu

E-ISSN: 2945-1159

Volume 2, 2024

Given the adverse effects of air pollution on public

health, it is crucial to understand how to maintain

acceptable air quality levels, particularly in urban

settings like street canyons. Implementing strategies

to mitigate air pollution in these areas is essential

for safeguarding public health and promoting

environmental well-being, [6].

Despite advancements in providing information

on air quality, there remains a critical need for

national-level studies on air quality, which serves as

the primary motivation for this research. This study

aims to passively quantify ambient air

concentrations of ethylene (C2H4), benzene (C6H6),

and toluene (C7H8) at a breathing level of 1.5 meters

above ground using a multi-component laser

photoacoustic spectroscopy detector. Additionally,

the research seeks to examine data related to

environmental factors and meteorological variables.

Our analysis focuses on investigating the influence

of temperature, wind speed, and direction on ozone

concentrations, as well as identifying daily and

seasonal patterns and differences in environmental

structural architecture.

3 Problem Solution

Passive measurements of ozone concentration were

conducted utilizing a laser-based photoacoustic

spectroscopy (LPAS) system. This advanced

technique is renowned for its high sensitivity,

capable of detecting gas molecules at the parts per

billion (ppb) level. LPAS offers numerous

advantages, including high accuracy and selectivity,

a wide dynamic range, and the capability to analyze

multiple components simultaneously, [7]. The

diagram of the photoacoustic detector (PA) utilized

for determining ozone concentration in ambient air

is illustrated in Figure 1. This system comprises a

CO2 laser, a PA cell, the detection unit, and a

vacuum/gas handling system. The CO2 laser utilized

in this setup is a frequency-stabilized laser source

emitting in continuous wave (cw) across 57

different lines within the range of 9.2 – 10.8 µm.

This range is further divided into 4 branches: 9R,

9P, 10R, and 10P. The continuous-wave, tunable

CO2 laser beam is subjected to chopping, focused by

a ZnSe lens, and then directed into the

photoacoustic cell (PA). Inside the PA cell, the laser

beam's power is measured using a laser radiometer,

specifically the Rk-5700 model from Laser Probe

Inc., with a measuring head designated as RkT-30.

The digital output from this measurement is

integrated into the data acquisition interface module

alongside the output from the lock-in amplifier.

Experimental data are subsequently processed and

stored using a computer.

The light beam is modulated using a high-

quality mechanical chopper, specifically the

DigiRad C-980 or C-995 models (30-slot aperture),

known for low vibration noise and variable speed

capabilities ranging from 4 to 4000 Hz. Importantly,

the chopper operates at the resonant frequency of

the cell, set at 564 Hz. Acoustic waves generated

within the cell are captured by microphones

strategically positioned in the cell wall. These

microphone signals are then directed to a lock-in

amplifier synchronized with the modulation

frequency. The lock-in amplifier serves as a

versatile signal recovery and analysis tool, capable

of accurately measuring a single-frequency signal

even in the presence of noise sources thousands of

times its magnitude. Notably, it effectively filters

out random noise, transients, incoherent discrete

frequency interference, and harmonics of the

measurement frequency.

A dual-phase, digital lock-in amplifier is

employed, specifically the Stanford Research

Systems model SR 830, which offers full-scale

sensitivity ranging from 2 nV to 1 V; input noise at

6 nV (rms)/ Hz at 1 kHz; dynamic reserve

exceeding 100 dB; a broad frequency range

spanning from 1 mHz to 102 kHz; and flexible time

constants ranging from 10 μs to 30 s (for reference

frequencies > 200 Hz) or extending up to 30,000 s

(for reference frequencies < 200 Hz).

Fig. 1: A schematic representation of the LPAS

system employed for determining the ambient air

pollutant concentrations

This research initiative forms part of a broader

campaign aimed at determining the concentrations

of various pollutants in the atmosphere utilizing a

multicomponent detector based on laser

photoacoustic spectroscopy, [8]. Specifically,

monitoring of tropospheric ozone levels was

conducted in the town of Magurele (located at

44°20′58″N, 26°01′47″E, with an altitude of 93

meters) in Romania. This monitoring took place

from March to August 2021, spanning the spring

and summer seasons. Atmospheric air sampling was

conducted at three distinct locations in Magurele:

International Journal of Environmental Engineering and Development

DOI: 10.37394/232033.2024.2.9

Mioara Petrus, Cristina Popa, Ana-Maria Bratu

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Volume 2, 2024

P1: Latitude 44°21'02.7"N, Longitude 26°01'42.0"E.

This point is situated within the city, amidst

residential buildings and adjacent to a traffic

roundabout. It is approximately 150 meters away

from a school with over 1000 students and a

kindergarten accommodating over 300 children

aged 3 to 6 years. P2: Latitude 44°21'10.4"N,

Longitude 26°02'31.0"E. Positioned in a small forest

area dominated by oak (Quercus robur) and acacia

(Robinia pseudoacacia) trees, P2 is bordered by two

heavily trafficked roads, one of which is the

Bucharest beltway. P3: Latitude 44°22'09.6"N,

Longitude 26°02'34.2"E. Located in an industrial

area, P3 is characterized by heavy vehicular traffic,

including cars, gas stations, and a concrete station.

Greenery is notably absent in this vicinity.

Ambient air samples were gathered at a height

of 1.5 meters above the ground using specialized

containers or bags. Sampling activities were

conducted exclusively on working days, from

Monday to Friday, within a designated time frame

spanning from 8:30 am to 8:30 pm. At each

sampling location, a total of six samples were

collected: three during the morning period from

8:30 to 11:30 am, and three during the evening

period from 5:30 to 8:30 pm. This sampling strategy

was designed to provide a comprehensive

representation of environmental conditions at

various times of the day, enabling a more thorough

analysis of variations in trace gases or other

pertinent parameters over the day. By incorporating

dual sampling timeframes, the study aimed to

capture potential diurnal fluctuations, ensuring a

robust understanding of the environmental

characteristics at each specific location. The mean

week value of concentrations of ethylene, benzene,

and toluene in the three locations during the spring

and summer seasons are presented in Table 1.

Table 1. Ethylene, benzene, and toluene mean± SD

in P1, P2, and P3 points in the spring and summer

seasons

VOCs

Spring

Concentration ± SD [ppb]

Summer

Concentration ± SD [ppb]

C2H4

56.14

±21.49

58.34

±25.06

55.76

±31.61

116.86

±82.37

104.28

±41.17

87.23

±46.43

C6H6

0.62

±0.32

0.35±

0.17

0.57±

0.21

1.13 ±

0.32

0.624

± 0.19

0.98

±0.26

C7H8

1.99 ±

0.84

1.49 ±

0.73

1.80 ±

0.88

5.48 ±

3.27

4.32 ±

3.07

5.26 ±

3.11

(a)

(b)

Fig. 2: (b) Distribution of the VOC concentrations

in the three measurement locations according to the

wind direction in the March-August 2021 period;

(b) Wind rose in Magurele from March to August

2021

Fig. 3: The distribution of the VOC concentrations

in the three measurement locations according to the

wind speed in the March–August 2021 period

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Mioara Petrus, Cristina Popa, Ana-Maria Bratu

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Figure 2 illustrates the distribution of ozone

concentrations at measuring points P1, P2, and P3

relative to wind direction. The data suggests a

correlation between ozone levels and wind

direction, with lower ozone concentrations observed

when the wind originates from the east (E) or

northeast (NE) direction (54 - 91.5 degrees), and

higher ozone levels recorded when the wind blows

from the south (S) or southwest (SV) direction (180

- 273.9 degrees). In Figure 3, the distribution of

ozone concentrations at points P1, P2, and P3 is

depicted as a function of wind speed. Notably, a

significant portion of ozone concentrations appears

to fall within the range of 2.5 - 4 meters per second

(m/s) wind speeds.

Elevated levels of ethylene, benzene, and

toluene were observed in association with southwest

and northeast wind directions, particularly at wind

speeds ranging between 2-4 m/s and 6-7 m/s.

Various studies have investigated the influence of

wind direction and speed on urban air quality,

including its impact on gaseous pollutants, [9].

Notably, higher wind speeds have been linked to a

decrease in air pollutant concentrations. Wind

direction plays a critical role in determining the flow

patterns and dispersion of pollutants within a given

area. For instance, in elongated street canyons, wind

direction influences airflow and the distribution of

pollutants, resulting in differing concentrations on

leeward and windward-facing walls. Additionally,

factors such as street size and geometry contribute,

with irregular streets potentially restricting pollutant

dispersion and exposing nearby residents to higher

concentrations of pollutants, [10], [11].

The toluene/benzene (T/B) ratio serves as a

valuable indicator for discerning the sources of

VOCs, particularly aromatics, [12]. Different

sources exhibit distinct T/B ratio ranges: i) Vehicle

Emissions: In areas heavily impacted by vehicle

emissions, the T/B ratio typically falls within the

range of 0.9–2.2. ii) Solvent Use: Higher T/B ratios,

exceeding 8.8, are commonly reported for activities

involving solvent use. iii) Industrial Processes: T/B

ratios ranging from 1.4 to 5.8 have been observed in

industrial settings, indicating emissions from

various industrial processes. iv) Burning Source

Emissions: Studies focusing on emissions from

burning sources, including combustion processes

and raw materials, have reported T/B ratios below

0.6. By analyzing the T/B ratio in ambient air

samples, researchers can gain insights into the

predominant sources of aromatic compounds

present in a specific environment. Table 2 presents

the T/B ratio values obtained in this study. This

implies that the atmospheric occurrence of benzene

and toluene in the measurement areas can be

attributed to emissions from both traffic and

industrial sources.

Table 2. The values of T/B ratio

Location

Spring

Summer

T/B ratio value

3.21

4.26

3.16

4.85

6.92

5.37

4 Numerical Simulation

Turbulence presents a longstanding challenge in

classical physics, demanding resolution due to its

prevalence in natural phenomena and various

technological processes. The significance of this

problem stems from the fact that the majority of

flows observed in nature and industrial applications

exhibit turbulent characteristics. To tackle

turbulence mathematically, several approaches have

been developed. Among these, the Reynolds

approach is the most prevalent. This approach leads

to the derivation of a Reynolds-averaged Navier–

Stokes system of equations (RANS), which serves

as a fundamental framework for understanding and

modeling turbulent flow behavior, [13].

Although RANS methods are widely employed,

certain hydrodynamic problems may not yield

satisfactory results, necessitating high

computational cell resolution. COMSOL

Multiphysics is a robust software package used for

modeling physical phenomena across various

disciplines, including fluid dynamics and chemical

reactions. It employs the Finite Element Method to

solve hydrodynamic equations. In addressing

aerodynamic profile problems, the initial

distribution of velocity and pressure is determined

by the potential field of velocities. The velocity

potential must adhere to the continuity equation for

incompressible flow. Following the calculation of

the velocity potential, pressure can be approximated

using the Bernoulli equation. The k-ε turbulence

model stands out as one of the most common

models utilized in CFD to simulate mean flow

characteristics under turbulent flow conditions, [13],

[14].

To depict the transport of C6H6 within a street

canyon using Comsol, a transport model was

formulated for the system. In the context of a single-

pollutant approach focusing on C6H6, the governing

equations for the problem during an adiabatic

process are the RANS equations. In the numerical

simulation, identical dimensions were employed for

the city corridor as those at the P1 measurement

point. Benzene was selected as the pollutant due to

its severe impact on human health, being classified

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Mioara Petrus, Cristina Popa, Ana-Maria Bratu

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as a Class 1 human carcinogen. The size of the

geometry used in the numerical simulation was: L

(length) = 165 m, l (width) = 72 m, h (height of the

buildings) = 17 m. On the street segment used, there

are several 7 residential buildings 3 floors each. The

parameters of benzene used in the simulation are

presented in Table 3.

Table 3. Benzene parameters used in numerical

simulation

Parameter

Value

Density [kg/m3]

3.486

Dynamic viscosity [Pa*s]

569.8e-6

Temperature [K]

303.15

Initially, a mesh independence analysis was

conducted for the three geometries under

consideration. The selected criterion aimed to strike

a reasonable balance between accuracy and

computational efficiency. Consequently, for the

final simulations, the mesh ensuring that the average

concentration on the outlet surface remained within

a confidence range lower than 4% was adopted. A

structured mesh composed of hexahedral elements

was employed in the final computations for the

urban canyon. In the numerical simulation, identical

experimental parameters for benzene in the urban

canyon were utilized, with a wind inlet velocity of

0.5 m/s. Figure 4 shows the mesh of the urban

canyon geometry, Figure 5 shows the benzene gas

flow velocity, and Figure 6 shows the pressure

distribution in the urban canyon.

Fig. 4: Mesh of the urban canyon geometry

Fig. 5: Benzene gas flow velocity

Fig. 6: Pressure distribution in the Urban Canyon

5 Conclusion

This study represents the first assessment of

ethylene, benzene, and toluene concentrations in the

city of Magurele, Romania. These gas air pollutants

were measured during the spring and summer

seasons, spanning from March to August 2021, at a

height of 1.5 meters above the ground.

Relationships between the concentrations of these

compounds, criteria air pollutants, and

meteorological variables were explored across both

seasons using a multicomponent detector based on

LPAS.

The gas concentrations observed in the

environment were found to be influenced by

meteorological variables and exhibited seasonal

trends. Higher concentrations of these gases were

typically recorded during the summer season,

particularly on days with elevated temperatures.

Wind speed and direction were identified as

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DOI: 10.37394/232033.2024.2.9

Mioara Petrus, Cristina Popa, Ana-Maria Bratu

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Volume 2, 2024

significant parameters influencing gas

concentrations, with airflow from industrial areas

and heavily trafficked roads contributing to

increased gas levels. Regarding benzene and

toluene, the highest concentrations were observed at

points situated within the city and in industrial areas

compared to the levels detected in areas surrounded

by trees. Ethylene exhibited higher values across all

three sampling points, attributed to its involvement

in plant physiology. Vehicles and industries

emerged as important sources of VOCs. The T/B

ratio was utilized to identify these sources, revealing

higher values during the spring and summer

seasons, indicative of traffic and industrial

emissions as predominant contributors. To gain a

comprehensive understanding of the behavior of

polluting gases in the ambient air, gas

concentrations will be determined during both

autumn and winter seasons. This approach aims to

provide a holistic overview spanning an entire year.

Furthermore, this paper presents a preliminary

3D simulation of benzene gas dispersion within

street canyons using Comsol Multiphysics

numerical modeling, governed by the RANS

equations of compressible turbulent airflow. When

performing simulations using the RANS equations

in COMSOL Multiphysics or any other CFD

software, several types of errors or sources of

discrepancy may arise. These errors stem from the

discretization of the governing equations and the

solution of the resulting algebraic equations using

numerical methods. Numerical errors can arise from

improper mesh resolution, inadequate numerical

schemes, and convergence issues. The RANS

equations rely on several assumptions and

simplifications, such as the turbulence closure

model, boundary conditions, and neglecting certain

physical effects (e.g., compressibility effects in

incompressible flow simulations). Incorrect

specification of boundary conditions, such as inlet

velocity profiles, pressure conditions, and wall

treatments, can lead to errors in the simulation

results. Some errors can come from the quality of

the mesh, including element shape, aspect ratio, and

mesh density, which can significantly impact the

accuracy of the simulation. Poorly structured

meshes or insufficient mesh refinement in critical

regions can lead to errors. To mitigate these errors,

it is essential to conduct thorough verification and

validation studies, refine the mesh appropriately,

select suitable turbulence models and boundary

conditions, and carefully tune solver settings to

ensure convergence and accuracy of the simulation

results.

In the future, numerical simulations are needed

with the modification of the parameters related to

the boundary conditions and the size of the mesh.

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Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

- Mioara Petrus carried out the conceptualization,

data curation, simulation, and optimization.

- Cristina Popa has executed the spectroscopic

experiments, methodology.

- Ana-Maria Bratu has executed the spectroscopic

experiments and methodology.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

This research was funded by a grant from the

Ministry of Research, Innovation, and Digitization,

CNCS-UEFISCDI, project TE 82/2022, number

PN-III-P1-1.1-TE-2021-0717, within PNCDI III.

Conflict of Interest

The authors have no conflicts of interest to declare.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en

_US

International Journal of Environmental Engineering and Development

DOI: 10.37394/232033.2024.2.9

Mioara Petrus, Cristina Popa, Ana-Maria Bratu

E-ISSN: 2945-1159

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Volume 2, 2024