A Pre- to Post-COVID-19 Change of Air Quality
Patterns in Anhui Province Using Path Analysis
and Regression

Bhatti, Uzair Aslam; Wu, Guilu; Bazai, Sibghat Ullah; Nawaz, Saqib Ali; Baryalai, Mehmood; Bhatti, Mughair Aslam; Hasnain, Ahmad; Nizamani, Mir Muhammad

doi:10.15244/pjoes/148065

Cited by 37 publications

(13 citation statements)

References 21 publications

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“…6 and 7, S1-4 ). These findings agreed well with the prior studies documented by Hasnain et al (2021) and Bhatti et al (2022) . Compared with the air quality status of Jiangsu Province, the reductions in the concentrations of different air pollutants in Anhui were relatively lower during the first phase ( Table S1 ).…”

Section: Resultssupporting

confidence: 93%

“…The reduction ratio for PM 2.5 concentration was greater than other pollutants, while PM 10 , SO 2 and NO 2 indicated relatively similar tendencies with some fluctuations in Zhejiang. Past studies also reported that except for O 3 , the concentrations of different air pollutants were decreased during the COVID-19 control period compared with the prior years in different areas and regions across China ( Chen et al, 2020 ; Zhao et al, 2020a ; Hasnain et al, 2021 ; Bhatti et al, 2022 ).…”

Section: Resultsmentioning

confidence: 91%

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Assessing the ambient air quality patterns associated to the COVID-19 outbreak in the Yangtze River Delta: A random forest approach

et al. 2023

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 91%

Assessing the ambient air quality patterns associated to the COVID-19 outbreak in the Yangtze River Delta: A random forest approach

et al. 2023

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“…On the contrary, infrared images can highlight thermal targets in low light or severe weather and contain little texture information because of their low spatial resolution. Infrared and visible image fusion can integrate the complementary virtues from infrared and visible images into synthetic images, which not only conform to human visual perception but also adapt to the application in various vision systems ( Bhatti et al., 2022a ; Bhatti et al., 2022b ).…”

Section: Introductionmentioning

confidence: 99%

RADFNet: An infrared and visible image fusion framework based on distributed network

Feng

Wu²,

Lin³

et al. 2023

Front. Plant Sci.

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IntroductionThe fusion of infrared and visible images can improve image quality and eliminate the impact of changes in the agricultural working environment on the information perception of intelligent agricultural systems.MethodsIn this paper, a distributed fusion architecture for infrared and visible image fusion is proposed, termed RADFNet, based on residual CNN (RDCNN), edge attention, and multiscale channel attention. The RDCNN-based network realizes image fusion through three channels. It employs a distributed fusion framework to make the most of the fusion output of the previous step. Two channels utilize residual modules with multiscale channel attention to extract the features from infrared and visible images, which are used for fusion in the other channel. Afterward, the extracted features and the fusion results from the previous step are fed to the fusion channel, which can reduce the loss in the target information from the infrared image and the texture information from the visible image. To improve the feature learning effect of the module and information quality in the fused image, we design two loss functions, namely, pixel strength with texture loss and structure similarity with texture loss.Results and discussionExtensive experimental results on public datasets demonstrate that our model has superior performance in improving the fusion quality and has achieved comparable results over the state-of-the-art image fusion algorithms in terms of visual effect and quantitative metrics.

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“…For instance, during the COVID-19 pandemic lockdown period, a sharp drop in air pollution was noticed in several areas and regions all around the world shown by satellite images (Holcombe and O'Key 2020). The lockdown is vital to the public health response to COVID-19, and it has also brought unexpected benefits for the environment (Abdullah et al, 2020;Bhatti et al, 2022a).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal impact of the COVID-19 pandemic lockdown on air quality pattern in Nanjing, China

Sun

Wagan²,

Hasnain³

et al. 2022

Front. Environ. Sci.

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In response to the COVID-19 outbreak, severe steps have been taken to control its rapid spread by countries globally. A nationwide lockdown was executed at the end of January 2020 in China, which resulted in a significant change and an improvement in air quality patterns. In this study, the objectives were to assess the spatiotemporal impact of the COVID-19 lockdown on air quality in Nanjing, China. The present study researched the six air pollutant parameters, namely, PM10, PM2.5, SO2, NO2, CO, and O3. The data were divided into six periods, P1–P3: pre-lockdown, during lockdown, and after lockdown periods, P4–P6: 2017–19 (same dates of lockdown). The results reveal that during the COVID-19 control period, a significant drop and an improvement in air quality were observed. According to our findings, the PM10, PM2.5, SO2, NO2, and CO concentrations were reduced by -33.03%, -35.41%, -21.26%, -39.79%, and -20.65%, respectively, while the concentration of O3 significantly increased by an average of 104.85% in Nanjing. From the previous 3 years to lockdown variations, PM10 (-40.60%), PM2.5 (-40.02%), SO2 (-54.19%), NO2 (-33.60%), and CO (23.16%) were also reduced, while O3 increased (10.83%). Moreover, compared with those in the COVID-19 period, the levels of PM10, SO2, NO2, CO, and O3 increased by 2.84%, 28.55%, 4.68%, 16.44%, and 37.36%, respectively, while PM2.5 reduced by up to -14.34% after the lockdown in Nanjing. The outcomes of our study provide a roadmap for the scientific community and local administration to make policies to control air pollution.

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A Pre- to Post-COVID-19 Change of Air Quality Patterns in Anhui Province Using Path Analysis and Regression

Cited by 37 publications

References 21 publications

Assessing the ambient air quality patterns associated to the COVID-19 outbreak in the Yangtze River Delta: A random forest approach

Assessing the ambient air quality patterns associated to the COVID-19 outbreak in the Yangtze River Delta: A random forest approach

RADFNet: An infrared and visible image fusion framework based on distributed network

Spatiotemporal impact of the COVID-19 pandemic lockdown on air quality pattern in Nanjing, China

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