A spatiotemporal deep learning ensemble for multi-step PM2.5 prediction: A case study of Bangkok metropolitan region in Thailand

Atmospheric Pollution Research, Journal Year: 2025, Volume and Issue: unknown, P. 102406 - 102406

Published: Jan. 1, 2025

Language: Английский

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Estimation of Near-Surface High Spatiotemporal Resolution Ozone Concentration in China Using Himawari-8 AOD

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 528 - 528

Published: Feb. 4, 2025

Near-surface ozone is a secondary pollutant, and its high concentrations pose significant risks to human plant health. Based on an Extra Tree (ET) model, this study estimated near-surface with the spatiotemporal resolution based Himawari-8 aerosol optical depth (AOD) data meteorological variables from 1 January 2016 31 December 2020. The SHapley Additive exPlanation (SHAP) method was employed evaluate contribution of AOD factors concentration. results indicate that (1) ET model achieves sample-based cross-validation R2 0.75–0.87 RMSE (μg/m3) 17.96–20.30. coefficient determination (R2) values in spring, summer, autumn, winter are 0.81, 0.80, 0.87, 0.75, respectively. (2) Higher temperature boundary layer heights were found positively contribute concentration, whereas higher relative humidity exerted negative influence. (3) From 11:00 15:00 (Beijing time, UTC+08:00), concentration increases gradually, highest occurring followed by spring. This has obtained spatial temporal data, offering valuable insights for development fine-scale pollution prevention control strategies.

Language: Английский

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Spatiotemporal changes of desertification areas in the Alxa Desert obtained from satellite imagery

Earth Surface Processes and Landforms, Journal Year: 2025, Volume and Issue: 50(2)

Published: Feb. 1, 2025

Abstract Desertification is defined as land degradation in arid, semi‐arid and dry sub‐humid areas resulting from various factors. High‐spatial‐resolution desertification monitoring with long time series accurate area quantification the Alxa Desert has yet to be fully elucidated. Here, we exploited Landsat satellite images develop a method for of high‐resolution, large‐scale dynamics using Difference Index (DDI) model based on albedo Topsoil Grain Size (TGSI). On this basis, examined spatial–temporal changes extent desertified ascertained impact factors (temperature, precipitation, total livestock) process. We made detailed classification (five types) found that non‐desertification accounted smallest proportion entire study region (annual mean 2.00 × 10 4 km 2 , 7.8%), while severe contributed largest 7.88 30.9%). Over past 20 years, there been substantial reduction extremely (−251 /yr) moderate (−230 areas, demonstrating effectiveness desert management. Regionally, considerable attention should paid eastern Tengger terms control; temporally, special summer. High temperatures can exacerbate severe, desertification, contrary effect increasing precipitation. Dynamic will become more complex under predicted climate change patterns, indicating prevention prioritized over control.

Language: Английский

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Chemical Composition and Source of PM2.5 during Winter Heating Period in Guanzhong Basin

Atmosphere, Journal Year: 2023, Volume and Issue: 14(11), P. 1640 - 1640

Published: Oct. 31, 2023

An intensive field campaign was carried out from December 2022 to March 2023 at six different sites across five major cities (Xi’an, Baoji, Xianyang, Weinan, and Hancheng) in the Guanzhong Basin, China, covering most of heating period there, which is characterized by high PM2.5 pollution levels. During campaign, mean concentrations these exceeded 24 h standard (75 μg m−3), except site Hancheng, with 57.8 ± 32.3 m−3. The source apportionment varied significantly sites, vehicle exhaust being dominant urban located Xi’an coal combustion suburban comparable contribution industrial emissions Xianyang Weinan. Compared clean condition, secondary inorganic sources (SIs) were largely enhanced during heavy periods, while biomass burning (BB) dust decreased all sites. Combined an analysis meteorological parameters, study further found that higher contributions SIs generally associated relative humidity (RH). In addition, related lower wind speeds, could be explained stagnant condition favoring accumulation local as well formation pollutants. contrast, (e.g., Xianyang), more strong influence slightly speeds.

Language: Английский

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Estimating visibility and understanding factors influencing its variations at Bangkok airport using machine learning and a game theory–based approach

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 5, 2024

Language: Английский

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Joint estimation of PM2.5 and O3 concentrations using a hybrid model in Beijing-Tianjin-Hebei, China

Atmospheric Pollution Research, Journal Year: 2024, Volume and Issue: 15(8), P. 102174 - 102174

Published: May 7, 2024

Language: Английский

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Industrial Heat Source-Related PM2.5 Concentration Estimates and Analysis Using New Three-Stage Model in the Beijing–Tianjin–Hebei Region

Atmosphere, Journal Year: 2024, Volume and Issue: 15(1), P. 131 - 131

Published: Jan. 20, 2024

The prevalent high-energy, high-pollution and high-emission economic model has led to significant air pollution challenges in recent years. industrial sector the Beijing–Tianjin–Hebei (BTH) region is a notable source of atmospheric pollutants, with heat sources (IHSs) being primary contributors this pollution. Effectively managing emissions from these pivotal for achieving control goals region. A new three-stage using multi-source long-term data was proposed estimate atmospheric, delicate particulate matter (PM2.5) concentrations caused by IHS. In first stage, region-growing algorithm used identify IHS radiation areas. second third stages, based on seasonal trend decomposition procedure Loess (STL), multiple linear regression, U-convLSTM models, IHS-related PM2.5 meteorological anthropogenic conditions were removed 2012 2021. Finally, study analyzed spatial temporal variations BTH findings reveal that areas higher than background areas, approximately 33.16% attributable activities. decreasing observed. Seasonal analyses indicated industrially dense southern region, particularly during autumn winter. Moreover, case Handan’s She County demonstrated dynamic fluctuations concentrations, reductions periods inactivity. Our results aligned closely previous studies actual operations, showing strong positive correlations related indices. This study’s outcomes are theoretically practically understanding addressing regional quality IHSs, contributing positively environmental improvement sustainable development.

Language: Английский

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Estimating visibility and understanding factors influencing its variations at Bangkok airport using machine learning and a game theory-based approach

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: April 2, 2024

In this study, a range of machine learning (ML) models including random forest, adaptive boosting, gradient extreme light cat and stacked ensemble model, were employed to predict visibility at Bangkok airport. Furthermore, the impact influential factors was examined using Shapley method, an interpretable ML technique inspired by game theory-based approach. Air pollutant data from seven Pollution Control Department monitoring stations, visibility, meteorological Thai Meteorological Department's Weather station Airport, ERA5_LAND, ERA5 datasets, time-related dummy variables considered. Daytime ((here, 8–17 local time) screened for rainfall, developed prediction during dry season (November – April). The boosting model is identified as most effective individual with superior performance in three out four evaluation metrics (i.e., highest ρ, zero MB, second lowest ME, RMSE). However, SEM outperformed all both hourly daily time scales. seasonal mean standard deviation normalized are lower than those original indicating more influence meteorology emission reduction on improvement. analysis RH, PM_2.5, PM₁₀, day year, O₃ five important variables. At low relative humidity (RH), there no notable visibility. Nevertheless, beyond threshold, negative correlation between RH An inverse PM_2.5 PM₁₀ identified. Visibility negatively correlated moderate concentrations, diminishing very high concentrations. year Julian day) (JD) exhibits initial later positive association suggesting periodic effect. dependence values equal step size method understand effects, suggest effect hygroscopic growth aerosol Findings research feasibility employing techniques predicting comprehending influencing its fluctuations. Based above findings, certain policy–related implications, future work have been suggested.

Language: Английский

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Perbandingan Performa Algoritma Metode Bagging dan Boosting pada Prediksi Konsentrasi PM10 di Jakarta Utara

Jurnal Nasional Teknologi dan Sistem Informasi, Journal Year: 2024, Volume and Issue: 10(1), P. 72 - 81

Published: May 16, 2024

Jakarta Utara merupakan salah satu wilayah di DKI yang mengalami peningkatan hari dengan kualitas udara berkategori tidak sehat, yakni 21 pada tahun 2017 menjadi 117 2018, tetapi kemudian menurun 45 2019. Kategori sehat tersebut dipengaruhi oleh polusi udara. Salah polutan ada adalah PM10. Saat ini, dapat diprediksi menggunakan pendekatan algoritma machine learning. Contoh metode learning terkenal Metode Bagging dan Boosting Ensemble. Random Forest, sedangkan Catboost XGBoost. Penelitian ini bertujuan membandingkan performa berupa Forest XGBoost dalam memprediksi konsentrasi PM10 Utara. Data digunakan data harian 2017—2019 untuk faktor meteorologis lainnya tersebut. Faktor karena memengaruhi pembentukan polutan. Sementara itu, beberapa penelitian sebelumnya dilakukan studi literatur, pemerolehan data, pra-pemprosesan pemodelan data. Beberapa metrik evaluasi juga melihat dari pemodelan. Berdasarkan hasil pemodelan, menghasilkan akurasi testing lebih tinggi (R2 = 0,6424) dibandingkan 0,6340) 0,6294).

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Mining of dynamic traffic-meteorology-atmospheric pollutant association rules based on eclat method

Atmospheric Pollution Research, Journal Year: 2024, Volume and Issue: unknown, P. 102305 - 102305

Published: Sept. 1, 2024

Language: Английский

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