Indoor Air Quality in the Most Crowded Public Places of Tehran: An Inhalation Health Risk Assessment

Derikvand, Ahmad; Taherkhani, Ali; Hassanvand, Mohammad Sadegh; Naddafi, Kazem; Nabizadeh, Ramin; Shamsipour, Mansour; Niazi, Sadegh; Heidari, Mohsen; Mokammel, Adel; Faridi, Sasan

doi:10.3390/atmos14071080

Cited by 3 publications

(1 citation statement)

References 57 publications

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“…CO is a hazardous air pollutant that negatively impacts air quality and poses risks to all forms of life. While present in trace amounts, it can severely impair oxygen supply in the body, leading to severe health problems which include drowsiness and irritation in the eyes [20]. The main sources of CO include vehicular emissions, fossil fuel combustion, industry, home heating, and vegetation burning, as well as natural sources like forest fires and volcanoes [2].…”

Section: Introductionmentioning

confidence: 99%

Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques

Mumtaz,

Amin,

Khan

et al. 2023

Energies

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Transitioning to green energy transport systems, notably electric vehicles, is crucial to both combat climate change and enhance urban air quality in developing nations. Urban air quality is pivotal, given its impact on health, necessitating accurate pollutant forecasting and emission reduction strategies to ensure overall well-being. This study forecasts the influence of green energy transport systems on the air quality in Lahore and Islamabad, Pakistan, while noting the projected surge in electric vehicle adoption from less than 1% to 10% within three years. Predicting the impact of this change involves analyzing data before, during, and after the COVID-19 pandemic. The lockdown led to minimal fossil fuel vehicle usage, resembling a green energy transportation scenario. The novelty of this work is twofold. Firstly, remote sensing data from the Sentinel-5P satellite were utilized to predict air quality index (AQI) trends before, during, and after COVID-19. Secondly, deep learning models, including long short-term memory (LSTM) and bidirectional LSTM, and machine learning models, including decision tree and random forest regression, were utilized to forecast the levels of NO2, SO2, and CO in the atmosphere. Our results demonstrate that implementing green energy transportation systems in urban centers of developing countries can enhance air quality by approximately 98%. Notably, the bidirectional LSTM model outperformed others in predicting NO2 and SO2 concentrations, while the LSTM model excelled in forecasting CO concentration. These results offer valuable insights into predicting air pollution levels and guiding green energy policies to mitigate the adverse health effects of air pollution.

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Section: Introductionmentioning

confidence: 99%

Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques

Mumtaz,

Amin,

Khan

et al. 2023

Energies

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Design and Analysis of SAW Gas Sensor Utilizing AIN/Diamond/Si Multilayered Structure for VOCs Detection

Abu Waar,

Moustafa

2024

J. Electron. Mater.

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Indoor Radon and Its Health Risk Assessment in Iran: A Comprehensive Review Study

Yousefian,

Nasiri,

Kordi

et al. 2024

Indoor Air

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Understanding radon‐prone areas is vital to prevent radon‐related health problems, enhance public safety, and ensure adherence to regulations aimed at minimizing radon exposure. We conducted a comprehensive review of cross‐sectional studies reporting on residential radon exposure in Iran. Our review encompassed studies published until February 13, 2022. Out of the 966 articles initially identified, 37 studies were included in our analysis, which measured indoor radon levels in a total of 3480 residential buildings in Iran. Notably, the highest residential radon levels (Bq.m−3) were found in Mazandaran province, with the most hazardous recorded levels in Talesh Mahalleh (3235), followed by Ramsar (1299). Conversely, Tehran, the capital city of Iran, had the lowest recorded levels of residential radon, at 11.0 Bq.m−3. Remarkably, indoor radon concentration exceeded both the reference levels recommended by the World Health Organization (WHO) and the standard levels set by the U.S. Environmental Protection Agency (US.EPA), with approximately 51% and 26%, respectively. The mean effective doses received by Iranian residents were 5.0 mSv.y−1 (0.3–81.7). Moreover, the mean excess lifetime cancer risk (ELCR) associated with indoor radon exposure was determined to be two per 1000 people. The annual incidence of lung cancer cases (LCCs) per million people attributed to indoor radon exposure in Iranian residential buildings ranged from 5.00E − 06 to 1.47E − 03. The included studies addressed a wide range of variables affecting radon levels, but they did not cover all factors comprehensively. These factors encompass the meteorological parameters, geological characteristics, building construction materials, building type, window type, occupancy information, and ventilation rates in enclosed spaces. The potential health risks associated with indoor radon exposure necessitate the implementation of effective control measures. These should include raising public awareness, revising construction regulations, enhancing ventilation systems, identifying high‐risk areas, and conducting more comprehensive studies to better understand the factors that influence radon concentration.

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Indoor Air Quality in the Most Crowded Public Places of Tehran: An Inhalation Health Risk Assessment

Cited by 3 publications

References 57 publications

Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques

Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques

Design and Analysis of SAW Gas Sensor Utilizing AIN/Diamond/Si Multilayered Structure for VOCs Detection

Indoor Radon and Its Health Risk Assessment in Iran: A Comprehensive Review Study

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