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

Assessing the Impact of Climate Change on Summertime Tropospheric Ozone in the Eastern Mediterranean: Insights from Meteorological and Air Quality Modeling DOI
Reza Rezaei, Gülen Güllü, Alper Ünal

et al.

Atmospheric Environment, Journal Year: 2025, Volume and Issue: 344, P. 121036 - 121036

Published: Jan. 7, 2025

Language: Английский

Citations

2
Effect of ozone stress on crop productivity: A threat to food security DOI
Ambikapathi Ramya, Periyasamy Dhevagi,

Ramesh Poornima

et al.

Environmental Research, Journal Year: 2023, Volume and Issue: 236, P. 116816 - 116816

Published: Aug. 4, 2023

Language: Английский

Citations

28
Machine learning model to predict vehicle electrification impacts on urban air quality and related human health effects DOI
Vicent Calatayud, J. J. Diéguez, Evgenios Agathokleous

et al.

Environmental Research, Journal Year: 2023, Volume and Issue: 228, P. 115835 - 115835

Published: April 3, 2023

Language: Английский

Citations

24
Climate change, air quality, and respiratory health: a focus on particle deposition in the lungs DOI Creative Commons
Jer‐Hwa Chang, Yueh‐Lun Lee, Li-Te Chang

et al.

Annals of Medicine, Journal Year: 2023, Volume and Issue: 55(2)

Published: Oct. 6, 2023

This review article delves into the multifaceted relationship between climate change, air quality, and respiratory health, placing a special focus on process of particle deposition in lungs. We discuss capability change to intensify pollution alter particulate matter physicochemical properties such as size, dispersion, chemical composition. These alterations play significant role influencing particles lungs, leading consequential health effects. The paper provides broad exploration change's direct indirect modifying features its interaction with other pollutants, which may ability In conclusion, an important regulating lungs by changing physicochemistry pollution, therefore, increasing risk disease development.Climate influences thereby escalating development.It is crucial for healthcare providers educate patients about health.People conditions asthma, COPD, allergies must understand how changes weather, allergens can exacerbate their symptoms.Instruction understanding quality indices pollen predictions, along recommendations adapting everyday activities medication regimens response, essential.

Language: Английский

Citations

19
Explainable sequence-to-sequence GRU neural network for pollution forecasting DOI Creative Commons

Sara Mirzavand Borujeni,

Leila Arras, Vignesh Srinivasan

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: June 19, 2023

Abstract The goal of pollution forecasting models is to allow the prediction and control air quality. Non-linear data-driven approaches based on deep neural networks have been increasingly used in such contexts showing significant improvements w.r.t. more conventional like regression mechanistic approaches. While learning were deemed for a long time as black boxes, recent advances eXplainable AI (XAI) look through model’s decision-making process, providing insights into decisive input features responsible prediction. One XAI technique explain predictions which was proven useful various domains Layer-wise Relevance Propagation (LRP). In this work, we extend LRP sequence-to-sequence network model with GRU layers. explanation heatmaps provided by us identify important meteorological temporal accumulation four major pollutants ( $$\text {PM}_{10}$$ PM 10 , {NO}_{2}$$ NO 2 {NO}$$ {O}_{3}$$ O 3 ), our findings can be backed up prior knowledge environmental research. This illustrates appropriateness understanding forecastings opens new avenues controlling mitigating pollutants’ load air.

Language: Английский

Citations

18
Machine learning-based global air quality index development using remote sensing and ground-based stations DOI Creative Commons
Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti

et al.

Environmental Advances, Journal Year: 2023, Volume and Issue: 15, P. 100456 - 100456

Published: Nov. 19, 2023

Air pollution refers to the presence of hazardous substances in air that has adverse effects on health, causing millions premature deaths annually. Ground-based stations can provide accurate measurements for monitoring pollution. However, spatial coverage is limited by number measurement instruments available specific hotspot areas. Satellite remote sensing reduce uncertainty; however, results are mostly upper atmosphere with high sensitivity. To better represent surface conditions, this study aims model Quality Index pollutants CO, NO2, SO2, PM2.5, and PM10 global region using remotely sensed data. support study, 425 data points from distributed globally combined Machine Learning Linear Regression methods. Furthermore, socioeconomic environmental satellite form Multiple models. According Models more than single models, showing addition enhance accuracy. The expected help regions without estimate quality index data, turn, preventing disasters.

Language: Английский

Citations

18
Risk analysis for preventive conservation of heritage collections in Mediterranean museums: case study of the museum of fine arts in Alexandria (Egypt) DOI Creative Commons
Abdelrazek Elnaggar,

Mahmoud Said,

Ida Kraševec

et al.

Heritage Science, Journal Year: 2024, Volume and Issue: 12(1)

Published: Feb. 19, 2024

Abstract The impacts of climate change on heritage collections in Mediterranean museums are serious and lead to accelerated material degradation, loss value, increasing conservation costs climatisation. Climate scenarios simulation models have been developed predict the extreme average future environmental conditions assess long-term risks caused by global warming for museum buildings their countries, with Egypt being particularly at risk. This paper presents results risk analysis indoor outdoor environments Alexandria Museum Fine Arts (AMFA) provide an overview current situation management evidence-based data support decision-making regarding preventive given museum's limited funding, capacity resources. Unfortunately, air quality cannot be considered satisfactory specific measures need taken improve level building management. enabled assessment provided information potential collections, including variations temperature (T) relative humidity (RH), concentrations NO 2 , SO O 3 CO acetic formic acid lighting conditions, as well location museum. necessitate development a plan address challenges associated high T/RH fluctuations pollution pressure. requires more regular use HVAC system within certain set points minimising light exposure UV-filtering glazing. Care should ensure that housekeeping emergency preparedness reduce damping salt florescence building. However, dealing impact holistic adaptive approach includes joint collaboration, research, training strategic planning preservation valuable cultural different climates customised adaptations based local resources needs. Resilience region-specific take into account weather events, sea rise other climate-related challenges.

Language: Английский

Citations

4
Leaf senescence in forage and turf grass: progress and prospects DOI Creative Commons
Kangning Zhang,

Hongli Xie,

Jiangqi Wen

et al.

Grass Research, Journal Year: 2024, Volume and Issue: 4(1), P. 0 - 0

Published: Jan. 1, 2024

Leaf senescence is a complex biological process regulated by development, phytohormones, and various environmental factors. For forage turf grasses, controlling leaf can greatly improve quality, the amenity of lawn turf, grasses' stress tolerances. involves multitude gene regulation metabolic changes, including alteration chlorophyll metabolism. Here, we summarized recent progress studies on in major grass species, such as Medicago truncatula, M. sativa, Lolium perenne, Panicum virgatum, Agrostis stolonifera, to provide an insight into development effective methods for delaying species.

Language: Английский

Citations

4
Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany) DOI Creative Commons
Leona Hoffmann, Lorenza Gilardi, Marie‐Therese Schmitz

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 12, 2024

Abstract When analyzing health data in relation to environmental stressors, it is crucial identify which variables include the statistical model exclude dependencies among variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure four outdoor air pollution ozone ( $$\text{O}_3$$ O 3 ), nitrogen dioxide $$\text{NO}_2$$ NO 2 particulate matter $$PM_{2.5}$$ P M 2.5 , $$PM_{10}$$ 10 ) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban rural compartments including mountainous river areas. A temporal spatial analysis of internal relationships was performed using (a) cross-correlations, both grand ensemble as well within subsets, (b) Local Indications Spatial Association (LISA) method. Meteorological strongly correlated themselves time space. We found strong interaction between ozone, with correlation coefficients varying over time. The ranged from negative correlations January (−0.84), April (−0.47), October (−0.54) positive July (0.45). cross-correlation plot showed noticeable change direction . Spatially, concentrations significantly higher than regions. For this effect reversed. LISA confirmed distinct hot cold spots stressors. work examined quantified spatio-temporal relationship conditions recommended prioritize future impact analyses. results are line underlying physico-chemical atmospheric processes. It also identified postal code areas dominant stressors further studies.

Language: Английский

Citations

4
Forecasting ground-level ozone and fine particulate matter concentrations at Craiova city using a meta-hybrid deep learning model DOI
Youness El Mghouchi, Mihaela Tinca Udriștioiu, Hasan Yıldızhan

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 57, P. 102099 - 102099

Published: Aug. 16, 2024

Language: Английский

Citations

4