Evaluation of air quality in Sunway City, Selangor, Malaysia from a mobile monitoring campaign using air pollution micro-sensors

被引:13
|
作者
Lee, Chia Chun [1 ]
Tran, Manh-Vu [1 ]
Choo, Cheng Wai [1 ]
Tan, Chee Pin [1 ]
Chiew, Yeong Shiong [1 ]
机构
[1] Monash Univ Malaysia, Sch Engn, Jalan Lagoon Selatan, Bandar Sunway 47500, Selangor, Malaysia
关键词
Air pollution; Mobile monitoring campaign; Sunway city; CO2; NO2; USE REGRESSION-MODELS; CARBON-DIOXIDE; NITROGEN-OXIDES; PM10; EXPOSURE; OZONE; NO2; ABSORPTION; POLLUTANTS; TORONTO;
D O I
10.1016/j.envpol.2020.115058
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Due to the increase of the human population and the rapid industrial growth in the past few decades, air quality monitoring is essential to assess the pollutant levels of an area. However, monitoring air quality in a high-density area like Sunway City, Selangor, Malaysia is challenging due to the limitation of the local monitoring network. To establish a comprehensive data for air pollution in Sunway City, a mobile monitoring campaign was employed around the city area with a duration of approximately 6 months, from September 2018 to March 2019. Measurements of air pollutants such as carbon dioxide (CO2) and nitrogen dioxide (NO2) were performed by using mobile air pollution sensors facilitated with a GPS device. In order to acquire a more in-depth understanding on traffic-related air pollution, the measurement period was divided into two different time blocks, which were morning hours (8 a.m.-12 p.m.) and afternoon hours (3 p.m.-7 p.m.). The data set was analysed by splitting Sunway City into different zones and routes to differentiate the conditions of each region. Meteorological variables such as ambient temperature, relative humidity, and wind speed were studied in line with the pollutant concentrations. The air quality in Sunway City was then compared with various air quality standards such as Malaysian Air Quality Standards and World Health Organisation (WHO) guidelines to understand the risk of exposure to air pollution by the residence in Sunway City. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
相关论文
共 50 条
  • [21] Air Quality Prediction Based on Air Pollution Emissions in the City Environment Using XGBoost with SMOTE
    Nababan, Adli A
    Sutarman
    Zarlis, Muhammad
    Nababan, Erna B
    ICOSNIKOM 2022 - 2022 IEEE International Conference of Computer Science and Information Technology: Boundary Free: Preparing Indonesia for Metaverse Society, 2022,
  • [22] Topographic and spatial impacts of temperature inversions on air quality using mobile air pollution surveys
    Wallace, Julie
    Corr, Denis
    Kanaroglou, Pavlos
    SCIENCE OF THE TOTAL ENVIRONMENT, 2010, 408 (21) : 5086 - 5096
  • [23] Assessment of an air quality surveillance network through passive pollution measurement with mobile sensors
    Lorenzo-Saez, Edgar
    Oliver-Villanueva, Jose-Vicente
    Lemus-Zuniga, Lenin-Guillermo
    Coll-Aliaga, Eloina
    Castillo, Carolina Perpina
    Lavalle, Carlo
    ENVIRONMENTAL RESEARCH LETTERS, 2021, 16 (05)
  • [24] Can Air Quality Gas Sensors Be Used for Emission Monitoring of Small-Scale Local Air Pollution Sources? Pilot Test Evaluation
    Bucek, Pavel
    Bilek, Jiri
    Marsolek, Petr
    Bilek, Ondrej
    ATMOSPHERE, 2023, 14 (02)
  • [25] Evaluation of Precalibrated Electrochemical Gas Sensors for Air Quality Monitoring Systems
    Malky, Saeed
    Kostanic, Ivica
    Altheiab, Khalid
    Alharbai, Waleed
    2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, : 967 - 973
  • [26] Monitoring air quality in Paulinia and region using a mobile station
    Tresmondi, ACCL
    Tomaz, E
    AIR POLLUTION IX, 2001, 10 : 597 - 606
  • [27] Air quality monitoring using mobile microscopy and machine learning
    Yi-Chen Wu
    Ashutosh Shiledar
    Yi-Cheng Li
    Jeffrey Wong
    Steve Feng
    Xuan Chen
    Christine Chen
    Kevin Jin
    Saba Janamian
    Zhe Yang
    Zachary Scott Ballard
    Zoltán Göröcs
    Alborz Feizi
    Aydogan Ozcan
    Light: Science & Applications, 2017, 6 : e17046 - e17046
  • [28] Air quality monitoring using mobile microscopy and machine learning
    Wu, Yi-Chen
    Shiledar, Ashutosh
    Li, Yi-Cheng
    Wong, Jeffrey
    Feng, Steve
    Chen, Xuan
    Chen, Christine
    Jin, Kevin
    Janamian, Saba
    Yang, Zhe
    Ballard, Zachary Scott
    Gorocs, Zoltan
    Feizi, Alborz
    Ozcan, Aydogan
    LIGHT-SCIENCE & APPLICATIONS, 2017, 6 : e17046 - e17046
  • [29] On the Prediction of Air Quality within Vehicles using Outdoor Air Pollution: Sensors and Machine Learning Algorithms
    Baldi, Thomas
    Delnevo, Giovanni
    Girau, Roberto
    Mirri, Silvia
    PROCEEDINGS OF THE ACM SIGCOMM 2022 WORKSHOP ON NETWORKED SENSING SYSTEMS FOR A SUSTAINABLE SOCIETY, NET4US 2022, 2022, : 14 - 19
  • [30] Air Pollution Monitoring and Control System for Subway Stations Using Environmental Sensors
    Kim, Gyu-Sik
    Son, Youn-Suk
    Lee, Jai-Hyo
    Kim, In-Won
    Kim, Jo-Chun
    Oh, Joon-Tae
    Kim, Hiesik
    JOURNAL OF SENSORS, 2016, 2016