Large-scale and rapid perception of regional economic resilience from data-driven insights DOI Creative Commons
Tong Cheng, Le Ma,

Yonghua Zhao

et al.

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: June 25, 2024

Developing general resilience measures that take into account spatio-temporal dynamics to withstand the adverse effects of shocks on economy is urgent during COVID-19 pandemic. However, rapid perception city economic at large scales currently a challenge disasters. Using machine learning massively simulate hourly anthropogenic NO2 emissions from 2016 2020, quantification framework based an undesired output perspective proposed assess Chinese cities' operations The results show can characterize activity except for primary industry. Spatially, cities different stages pandemic showed binary pattern Huanyong Hu line divergence and north-south divergence, respectively. Temporally, had hysteresis effect. Moreover, with larger economies recovered more quickly, despite being hit harder. Measurement required integration information fluctuations trends in emissions. Our study provides new tool perceiving disasters provide support insight management planning post-pandemic era.

Language: Английский

Vertically resolved meteorological adjustments of aerosols and trace gases in Beijing, Taiyuan, and Hefei by using RF model DOI

Junaid Khayyam,

Pinhua Xie,

Jin Xu

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 948, P. 174795 - 174795

Published: July 17, 2024

Language: Английский

Citations

6
Assessing Influential Variables Affecting Outdoor Levels of Formaldehyde (HCHO) DOI Creative Commons
Marija Meišutovič-Akhtarieva, Luís Valença Pinto, Miguel Inácio

et al.

Environmental Processes, Journal Year: 2025, Volume and Issue: 12(2)

Published: May 6, 2025

Language: Английский

Citations

0
Synergistic effects and optimal control strategies of air pollutant and carbon emission reduction from mobile sources DOI

Chuanda Wang,

Wenjiao Duan,

Shuiyuan Cheng

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 478, P. 143824 - 143824

Published: Oct. 9, 2024

Language: Английский

Citations

3
Vertically Resolved Meteorological Adjustments of Aerosols and Trace Gases in Beijing, Taiyuan, and Hefei by Using Rf Model DOI

Junaid Khayyam,

Pinhua Xie,

Jin Xu

et al.

Published: Jan. 1, 2024

Air pollution represents a complex phenomenon defined by the presence of various gases and particulate matter, leading to intricate spatio-temporal fluctuations. This study aims enhance our understanding how meteorological factors influence trace aerosols, exacerbating air in geographical locations, specifically Beijing's Fengtai (BJFT), Taiyuan City (SXTY), Hefei's Science Island (HFDP). The employs 2D-MAX-DOAS observations utilizes Random Forest (RF) model decouple conditions from pollutant data. vertical profile nitrogen dioxide (NO2), sulfur (SO2), formaldehyde (HCHO), aerosols at each site was classified into four distinct layers, followed conducting decoupling analysis on layer. demonstrates that meteorology significantly influences across all sites, with reductions ranging 75% 95% after de-weathering. SO2 shows minimal susceptibility, changes ±20% ±60% Among BJFT's pollutants exhibit less susceptibility overall, while HFDP are more susceptible. findings further reveal significant interventions surface layers (0.05 km 0.2 – 0.4 km) BJFT, some exceptions SXTY. However, pollutants, particularly NO2 higher (0.6 0.8 1.0 1.2 HFDP, also experience interferences. SXTY removing adjusts shape pollutants. For instance, during winter season shifted bimodal an exponential Overall, this sheds light interplay between altitudes different geographic offering insights crucial for holistic effective mitigation strategies.

Language: Английский

Citations

0
Large-scale and rapid perception of regional economic resilience from data-driven insights DOI Creative Commons
Tong Cheng, Le Ma,

Yonghua Zhao

et al.

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: June 25, 2024

Developing general resilience measures that take into account spatio-temporal dynamics to withstand the adverse effects of shocks on economy is urgent during COVID-19 pandemic. However, rapid perception city economic at large scales currently a challenge disasters. Using machine learning massively simulate hourly anthropogenic NO2 emissions from 2016 2020, quantification framework based an undesired output perspective proposed assess Chinese cities' operations The results show can characterize activity except for primary industry. Spatially, cities different stages pandemic showed binary pattern Huanyong Hu line divergence and north-south divergence, respectively. Temporally, had hysteresis effect. Moreover, with larger economies recovered more quickly, despite being hit harder. Measurement required integration information fluctuations trends in emissions. Our study provides new tool perceiving disasters provide support insight management planning post-pandemic era.

Language: Английский

Citations

0