A Hybrid Wavelet-Based Deep Learning Model for Accurate Prediction of Daily Surface PM2.5 Concentrations in Guangzhou City

Toxics, Journal Year: 2025, Volume and Issue: 13(4), P. 254 - 254

Published: March 28, 2025

Surface air pollution affects ecosystems and people’s health. However, traditional models have low prediction accuracy. Therefore, a hybrid model for accurately predicting daily surface PM2.5 concentrations was integrated with wavelet (W), convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM), gated recurrent unit (BiGRU). The data meteorological factors pollutants in Guangzhou City from 2014 to 2020 were utilized as inputs the models. W-CNN-BiGRU-BiLSTM demonstrated strong performance during phase, achieving an R (correlation coefficient) of 0.9952, root mean square error (RMSE) 1.4935 μg/m3, absolute (MAE) 1.2091 percentage (MAPE) 7.3782%. Correspondingly, accurate is beneficial control urban planning.

Language: Английский

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Air pollution mitigation and suspended particulate matter retention potential of selected plant species across seasonal variation in the urban area

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(32), P. 45035 - 45054

Published: July 3, 2024

Language: Английский

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Particulate matter and potentially toxic element content in urban ornamental plant species to assess pollutants trapping capacity

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 124058 - 124058

Published: Jan. 9, 2025

Language: Английский

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Evaluating the Role of Tree Flora in Air Pollution Mitigation and Heavy Metals Accumulation Near Brick Kilns

Atmospheric Pollution Research, Journal Year: 2025, Volume and Issue: unknown, P. 102436 - 102436

Published: Jan. 1, 2025

Language: Английский

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Optimizing plant species selection for alleviating air pollution: Modified Anticipated Performance Index–based evaluation in Delhi, India

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(5)

Published: April 21, 2025

Language: Английский

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Evaluation of air pollution tolerance index of urban roadside young leaf and the correlation with its capturing capacity for water-insoluble fine particulate matters

Air Quality Atmosphere & Health, Journal Year: 2024, Volume and Issue: 17(11), P. 2675 - 2691

Published: June 25, 2024

Language: Английский

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Impact of automobile exhaust on biochemical and genomorphic characteristics of Mimusops elengi L. growing along roadsides of Lahore city, Pakistan

Heliyon, Journal Year: 2024, Volume and Issue: 10(6), P. e28157 - e28157

Published: March 1, 2024

Automobile exhaust releases different types of pollutants that are at great risk to the air quality environment and incidental distress nature roadside plants. Mimusops elengi L. is an evergreen medicinal tree cultivated along Lahore City. This research aimed investigate physiological, morphological genomorphic characteristics M. under influence pollution from vehicles. Healthy mature leaves were collected trees on Canal Bank Mall roads as experimental sites control 20 km away site. Different physiochemical, morphological, tolerance index (APTI) molecular analysis for detection DNA damage performed through comet assay. The results demonstrated mean accumulated Cd, Pb, Cu Ni heavy metal contents higher than plants (1.27, 3.22, 1.32 1.46 μg mg−1). APTI was 9.04. Trees in these significantly (p < 0.01) had a lower leaf area, petiole length dry matter content comparison Increased tail showed area. For pollution, it necessary check value polluted road side city. long-term screening, source type consistent monitoring various responses given by should be known.

Language: Английский

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Seasonal Assessment of Biochemical Characteristics and Suspended Particulate Matter (SPM) Retention Potential of Plant Species

Authorea (Authorea), Journal Year: 2024, Volume and Issue: unknown

Published: March 15, 2024

Plants play a crucial role in mitigating air pollution, which can be evaluated by examining their biochemical characteristics, including ascorbic acid, total chlorophyll content, pH, and relative water content. These traits provide valuable insights into plants’ capacity to counteract atmospheric pollutants. Moreover, combining pollution tolerance Suspended Particulate Matter (SPM) retention potentials could lead an adequate assessment of plant species for greenbelt development. This study assessed characteristics SPM potential six selected ( Ficus benghalensis L, religiosa Polyalthia longifolia (Sonn.) Thwaites, Azadirachta indica A.Juss, benjamina L , Bougainvillea glabra ) at polluted (Okhla Phase-2) non-polluted (Siri Fort) sites Delhi, India, during pre- post-monsoon. In addition, based on the Air Pollution Tolerance Index (APTI) has been calculated. Also, impact changes independent variables such as content APTI different was using linear regression. The found that A.indica exhibited highest 9.43 F.benghalensis lowest 8.3 maximum minimum recorded values adhesion leaves F. post-monsoon were 1305.46 g/cm 185.51 g/cm, respectively. Additionally, statistical analysis, regression coefficient (R = 0.93) observed between & with APTI, indicating substantial calculation these parameters. demonstrated plants elevated parameters, effectively reduce pollutants from atmosphere. findings highlight importance considering specific when selecting

Language: Английский

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Assessment of metals and metalloids agglutinated to airborne suspended particulate matter in selected plant species during the pre-and post-monsoon in the urban area

Environmental Pollution, Journal Year: 2024, Volume and Issue: 356, P. 124300 - 124300

Published: June 5, 2024

Language: Английский

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Identification of urban street trees for green belt development for optimizing pollution mitigation in Delhi, India

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(42), P. 54962 - 54978

Published: Sept. 2, 2024

Language: Английский

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