Assessment of ambient air quality in urban places of Mosul City, Iraq

Asmel, Nabel Kalel; Muhammed, F. I.; Hassan, Shahnawaz; Ganiyu, A. A.; Lakkaboyana, S. K.

doi:10.1007/s13762-022-04197-6

Cited by 3 publications

(2 citation statements)

References 62 publications

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“…The analytical process of the Mantel Test primarily involves calculating the distance matrix using the Euclidean distance formula (Breiding et al, 2021) and obtaining compressed distance columns for correlation calculation, enabling a signi cance test to determine whether there exists a signi cant correlation between the two matrices (Crabot et al, 2019). In this study, we employ Pearson correlation coe cient (Asmel et al, 2022) as a Model description.…”

Section: Mantel Testmentioning

confidence: 99%

Impact of COVID-19 Restrictions Liberalization on Air Quality: A Case Study of Chongqing, Southwest China

Wang,

Zhang,

Chen

et al. 2024

Preprint

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To mitigate the societal impact of the COVID-19 pandemic, China implemented long-term restrictive measures. The sudden liberalization at the end of 2022 disrupted residents’ daily routines, making it scientifically intriguing to explore its effect on air quality. Taking Chongqing City in Southwest China as an example, we examined the impact of restriction liberalization on air quality, identified potential sources of pollutants, simulated the effects of abrupt anthropogenic control relaxation using a Random Forest Model, and applied an optimized model to predict the post-liberalization pollutant concentrations. The results showed increases in PM2.5 (72.3%), PM10 (67.7%), and NO2 (21.9%) concentrations while O3 concentration decreased by 20.5%. Although potential pollution source areas contracted, pollution levels intensified with northeastern Sichuan, interior Chongqing, and northern Guizhou being major contributors to pollutant emissions. Anthropogenic emissions accounted for 26.7% ~ 33% changes in PM2.5、PM10 concentrations while meteorological conditions contributed to 40.2% ~ 43.3% variations observed during the period. The optimized model demonstrated correlation between predicted and observed values with R2 ranging from 0.70 to 0.89, enabling accurate prediction of post-liberalization pollutant concentrations. This study can enhance our understanding regarding the impact of sudden social lockdown relaxation events on air quality while providing support for urban air pollution prevention.

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Section: Mantel Testmentioning

confidence: 99%

Impact of COVID-19 Restrictions Liberalization on Air Quality: A Case Study of Chongqing, Southwest China

Wang,

Zhang,

Chen

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Figure 5 and Figure 6 show monthly monitoring and analysis of ambient air quality indicators for 37 monitoring sites in Xiamen. This can realize the near-real-time statistical analysis of year, quarter, month, and day, grasp the ambient air quality status of each site, locate existing problems, and analyze indicators such as major pollutants and excessive pollutants to judge the future trend of ambient air quality and detect abnormal situations in time [5] .…”

Section: Analysis Of Air Quality Status At Monitoring Pointsmentioning

confidence: 99%

Multidimensional Data Analysis of Ambient Air Quality Based on Apache Kylin

Yuan

2023

J. Phys.: Conf. Ser.

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While the environmental monitoring department increases the number of monitoring points and the frequency of monitoring, it will also bring about a surge in the amount of monitoring data and computational response events. However, the traditional data statistics methods based on relational databases are ineffective in the face of huge environmental monitoring data. Aiming at ambient air quality data analysis, this paper uses Hadoop, Hive, Kylin, and other tools to build a multi-dimensional analysis platform for ambient air quality big data in a distributed environment, which realizes the unified storage, calculation, and analysis of ambient air quality monitoring data. Compared with the traditional relational database statistical analysis scheme, the proposed solution significantly improves the efficiency of statistical analysis of ambient air quality data under the condition of large data. The response time is shortened by 98%, reaching the sub-second level.

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Ambient levels of BTEX at roadside in northern Iraq and its relationship with traffic volume

Shihab

I.AL-Jarrah

2023

Environ Monit Assess

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Assessment of ambient air quality in urban places of Mosul City, Iraq

Cited by 3 publications

References 62 publications

Impact of COVID-19 Restrictions Liberalization on Air Quality: A Case Study of Chongqing, Southwest China

Impact of COVID-19 Restrictions Liberalization on Air Quality: A Case Study of Chongqing, Southwest China

Multidimensional Data Analysis of Ambient Air Quality Based on Apache Kylin

Ambient levels of BTEX at roadside in northern Iraq and its relationship with traffic volume

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