How does the impact of a two-stage air pollution control policy on air quality different? Evidence from 258 cities in China

Atmospheric Pollution Research, Год журнала: 2024, Номер 15(7), С. 102148 - 102148

Опубликована: Апрель 16, 2024

Язык: Английский

---

Determination of major drive of ozone formation and improvement of O3 prediction in typical North China Plain based on interpretable random forest model

The Science of The Total Environment, Год журнала: 2024, Номер 934, С. 173193 - 173193

Опубликована: Май 12, 2024

Язык: Английский

---

Spatio-temporal differentiation characteristics and the influencing factors of PM2.5 emissions from coal consumption in Central Plains Urban Agglomeration

The Science of The Total Environment, Год журнала: 2024, Номер 945, С. 173778 - 173778

Опубликована: Июнь 7, 2024

Язык: Английский

---

Optimizing the Architecture of a Quantum–Classical Hybrid Machine Learning Model for Forecasting Ozone Concentrations: Air Quality Management Tool for Houston, Texas

Atmosphere, Год журнала: 2025, Номер 16(3), С. 255 - 255

Опубликована: Фев. 23, 2025

Keeping track of air quality is paramount to issue preemptive measures mitigate adversarial effects on the population. This study introduces a new quantum–classical approach, combining graph-based deep learning structure with quantum neural network predict ozone concentration up 6 h ahead. The proposed architecture utilized historical data from Houston, Texas, major urban area that frequently fails comply regulations. Our results revealed smoother transition between classical framework and its counterpart enhances model’s results. Moreover, we observed min–max normalization increased ansatz repetitions also improved hybrid performance. was evident evaluating assessment metrics root mean square error (RMSE), coefficient determination (R2) forecast skill (FS). Values for R2 FS horizons considered were 94.12% 31.01% 1 h, 83.94% 48.01% 3 75.62% 57.46% forecasts. A comparison existing literature both QML models methodology could provide competitive results, even surpass some well-established forecasting models, proving be valuable resource forecasting, thus validating this approach.

Язык: Английский

---

Lossless and closed co-occurring pattern mining algorithm for spatio-temporal datasets (C-STCOP)

International Journal of Information Technology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 8, 2025

Язык: Английский

---

A comprehensive analysis of O3 variation and source contributions of VOCs-oriented to O3 pollution episodes over Jinan city, China

Atmospheric Pollution Research, Год журнала: 2025, Номер unknown, С. 102552 - 102552

Опубликована: Апрель 1, 2025

Язык: Английский

---

Assessing the contribution of VOCs to SOA formation and identifying their key species during ozone pollution episodes in a typical petrochemical city

Environmental Pollution, Год журнала: 2025, Номер unknown, С. 126315 - 126315

Опубликована: Апрель 1, 2025

Язык: Английский

---

Quantitative Estimation of the Impacts of Precursor Emissions on Surface O3 and PM2.5 Collaborative Pollution in Three Typical Regions of China via Multi-Task Learning

Sustainability, Год журнала: 2024, Номер 16(6), С. 2475 - 2475

Опубликована: Март 16, 2024

The coordinated control of PM2.5 and O3 pollution has become a critical factor restricting the improvement air quality in China. In this work, precursors related influencing factors were utilized to establish estimation models North China Plain (NCP), Yangzi River Delta (YRD), Pearl (PRD) using multi-task-learning (MTL) model. prediction accuracy these three MTL was high, with R2 values ranging from 0.69 0.83. Subsequently, used quantitatively reveal relative importance each collaborative simultaneously. Precursors meteorological two most for regions, their larger than 29.99% 15.89%, respectively. Furthermore, response precursor region. NCP YRD, important are SO2 HCHO, while HCHO NO2. Therefore, VOC emissions reduction is measure pollution, NO2 emission regions. terms PRD, SOX, Thus, NO2, SO2, PRD. Overall, study provides clues references NCP,

Язык: Английский

---

Seasonal patterns, vertical profiles, and sensitivity analysis of long-term O3 pollution observations in Hefei City, China

Atmospheric Pollution Research, Год журнала: 2024, Номер 15(7), С. 102145 - 102145

Опубликована: Апрель 4, 2024

Язык: Английский

---

Quantitative Analysis of Spatiotemporal Patterns and Factor Contributions of Surface Ozone in the North China Plain

Applied Sciences, Год журнала: 2024, Номер 14(12), С. 5026 - 5026

Опубликована: Июнь 9, 2024

Over the past decade, surface ozone has emerged as a significant air pollutant in China, especially North China Plain (NCP). For effective management NCP, it is crucial to accurately estimate levels and identify primary influencing factors for pollution this region. This study utilized precursors such volatile organic compounds (VOCs) nitrogen oxides (NOX), meteorological data, land cover, normalized difference vegetation index (NDVI), terrain, population data build an extreme gradient boosting (XGBoost)-based estimation model NCP during 2019 2021. Four models were developed using different NO2 formaldehyde (HCHO) datasets from Sentinel-5 TROPOMI observations Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data. Site-based validation results of these four showed high accuracy with R2 values above 0.86. Among models, two higher spatial coverage ratio selected, their averaged produce final products. The indicated that VOCs NOX main pollutants causing relative contributions accounted more than 23.34% 10.23%, respectively, while HCHO also played role, contributing over 5.64%. Additionally, had notable impact, 28.63% pollution, each individual factor 2.38%. distribution identified Hebei–Shandong–Henan junction hotspot, peak occurring summer, particularly June. Therefore, hotspot region promoting reduction NOx can play important role mitigation O3 improvement quality

Язык: Английский

---