Analysis of Ozone Formation Sensitivity in Chinese Representative Regions Using Satellite and Ground-Based Data DOI Creative Commons
Y. Li, Chao Yu,

Jinhua Tao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 316 - 316

Published: Jan. 12, 2024

O3 poses a significant threat to human health and the ecological environment. In recent years, pollution has become increasingly serious, making it difficult accurately control precursor emissions. Satellite indicator methods, such as FNR (formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2 ratio)), provide an effective way identify ozone areas on large geographical scale due their simple acquisition of datasets. This can help determine primary factors contributing assist in managing it. Based TROPOMI data from May 2018 December 2022, combined with ground-based monitoring China National Environmental Monitoring Centre, we explored uncertainty associated using HCHO/NO2 (FNR) area determination. We focused four representative regions China: Jing-Jin-Ji-Lu-Yu (JJJLY), Jiang-Zhe-Hu-Wan (JZHW), Chuan-Yu (CY), South China. By statistical curve-fitting method, found that thresholds were 3.5–5.1, 2.0–4.0, 2.5–4.2, 1.7–3.5, respectively. Meanwhile, analyzed spatial temporal characteristics HCHO, NO2, areas. The HCHO concentrations NO2 had obvious cyclical patterns, higher column densities occurring summer winter. These high values always appeared dense population activities well-developed economies. distribution indicated during periods, urban industrial primarily controlled by VOCs, suburban gradually shifted VOC-limited regimes transitional eventually reverted back regimes. contrast, rural other remote relatively less development mainly NOx. also exhibited periodic variations, mostly appearing lower study identifies main different serve valuable reference for control.

Language: Английский

Photodissociation-Driven Photoacoustic Spectroscopy with UV-LEDs for Ozone Detection DOI Creative Commons

Lukas Escher,

Thomas Rück, Simon Jobst

et al.

Photoacoustics, Journal Year: 2025, Volume and Issue: 43, P. 100718 - 100718

Published: April 1, 2025

This study presents the development and evaluation of a UV-LED based photoacoustic (PA) measurement system for ozone (O3) detection to demonstrate its potential low-cost accurate sensing while first time addressing importance photodissociation PA signal generation O3 in UV range. With limit 7.9 ppbV, exhibits significant advancement over state-of-the-art UV-PA is on par with laser-based setups. Following novel discussion arising from products, cross-sensitivity effects due environmental factors such as temperature gas composition were systematically analyzed. A digital twin driven compensation these influences was implemented evaluated. Despite challenges associated modeling H2O CO2, shows considerable potential, though further studies real world applications must be conducted.

Language: Английский

Citations

0
Recycling of an ion-adsorption type rare earth tailing in a low-carbon construction material: Performance modulation and life cycle assessment DOI
Baifa Zhang, Zhihui Peng, Mohammad Fahimizadeh

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 475, P. 141167 - 141167

Published: April 11, 2025

Language: Английский

Citations

0
Machine learning algorithms for air quality and air pollution monitoring using GEE DOI

Prakriti Prakriti,

Manivannan Karuppaiyan,

Asfa Siddiqui

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 135 - 175

Published: Jan. 1, 2025

Language: Английский

Citations

0
Exploring the Influencing Factors of Surface Ozone Variability by Explainable Machine Learning: A Case Study in the Basilicata Region (Southern Italy) DOI Creative Commons

Roberta Valentina Gagliardi,

Claudio Andenna

Atmosphere, Journal Year: 2025, Volume and Issue: 16(5), P. 491 - 491

Published: April 24, 2025

Exposure to high surface ozone (O3) concentrations, which is a major air pollutant and greenhouse gas, constitutes significant public health concern, especially considering the potential adverse impact of climate change on future O3 values. The implementation increasingly effective methods assess factors determining formation variability is, therefore, great significance. In this study, methodological approach combining both supervised unsupervised machine learning algorithms (MLAs) with Shapley additive explanations (SHAP) method was used understand key behind explore nonlinear relationships linking these factors. SHAP analysis carried out at different event scales indicated (i) dominant role meteorological variables in driving variability, mainly relative humidity, wind speed, temperature throughout study period; (ii) an increase contribution temperature, nitrogen oxides, carbon monoxide concentrations during selected pollution event; (iii) predominant effect speed humidity shaping daily patterns clustered using k-means technique. results obtained are expected be useful for definition measures prevent and/or mitigate damage associated exposure.

Language: Английский

Citations

0
Analysis of Ozone Formation Sensitivity in Chinese Representative Regions Using Satellite and Ground-Based Data DOI Creative Commons
Y. Li, Chao Yu,

Jinhua Tao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 316 - 316

Published: Jan. 12, 2024

O3 poses a significant threat to human health and the ecological environment. In recent years, pollution has become increasingly serious, making it difficult accurately control precursor emissions. Satellite indicator methods, such as FNR (formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2 ratio)), provide an effective way identify ozone areas on large geographical scale due their simple acquisition of datasets. This can help determine primary factors contributing assist in managing it. Based TROPOMI data from May 2018 December 2022, combined with ground-based monitoring China National Environmental Monitoring Centre, we explored uncertainty associated using HCHO/NO2 (FNR) area determination. We focused four representative regions China: Jing-Jin-Ji-Lu-Yu (JJJLY), Jiang-Zhe-Hu-Wan (JZHW), Chuan-Yu (CY), South China. By statistical curve-fitting method, found that thresholds were 3.5–5.1, 2.0–4.0, 2.5–4.2, 1.7–3.5, respectively. Meanwhile, analyzed spatial temporal characteristics HCHO, NO2, areas. The HCHO concentrations NO2 had obvious cyclical patterns, higher column densities occurring summer winter. These high values always appeared dense population activities well-developed economies. distribution indicated during periods, urban industrial primarily controlled by VOCs, suburban gradually shifted VOC-limited regimes transitional eventually reverted back regimes. contrast, rural other remote relatively less development mainly NOx. also exhibited periodic variations, mostly appearing lower study identifies main different serve valuable reference for control.

Language: Английский

Citations

3