Dataset Information

A dataset of urban traffic flow for 13 Romanian cities amid lockdown and after ease of COVID19 related restrictions.

ABSTRACT: This dataset comprises street-level traces of traffic flow as reported by Here Maps™ for 13 cities of Romania from 15th. of May 2020 and until 5th. of June 2020. This covers the time two days before lifting of the mobility restrictions imposed by the COVID19 nation-wide State of Emergency and until four days after the second wave of relaxation, announced for 1st. of June 2020. Data were sampled at a 15-min interval, consistent with the Here API update time. The data are annotated with relevant political decisions and religious events which might influence the traffic flow. Considering the relative scarcity of real-life traffic data, one can use this data set for micro-simulation during development and validation of Intelligent Transportation Solutions (ITS) algorithms while another facet would be in the area of social and political sciences when discussing the effectiveness and impact of statewide restriction during the COVID19 pandemic.

SUBMITTER: Iovanovici A

PROVIDER: S-EPMC7495175 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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A dataset of urban traffic flow for 13 Romanian cities amid lockdown and after ease of COVID19 related restrictions.

Iovanovici Alexandru A Avramoni Dacian D Prodan Lucian L

Data in brief 20200917

This dataset comprises street-level traces of traffic flow as reported by Here Maps™ for 13 cities of Romania from 15th. of May 2020 and until 5th. of June 2020. This covers the time two days before lifting of the mobility restrictions imposed by the COVID19 nation-wide State of Emergency and until four days after the second wave of relaxation, announced for 1st. of June 2020. Data were sampled at a 15-min interval, consistent with the Here API update time. The data are annotated with relevant p ...[more]

PMID: 32959019

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Project description:Covid19-induced lockdown measures caused modifications in atmospheric pollutant and greenhouse gas emissions. Urban road traffic was the most impacted, with 48-60% average reduction in Italy. This offered an unprecedented opportunity to assess how a prolonged (∼2 months) and remarkable abatement of traffic emissions impacted on urban air quality. Six out of the eight most populated cities in Italy with different climatic conditions were analysed: Milan, Bologna, Florence, Rome, Naples, and Palermo. The selected scenario (24/02/2020-30/04/2020) was compared to a meteorologically comparable scenario in 2019 (25/02/2019-02/05/2019). NO2, O3, PM2.5 and PM10 observations from 58 air quality and meteorological stations were used, while traffic mobility was derived from municipality-scale big data. NO2 levels remarkably dropped over all urban areas (from -24.9% in Milan to -59.1% in Naples), to an extent roughly proportional but lower than traffic reduction. Conversely, O3 concentrations remained unchanged or even increased (up to 13.7% in Palermo and 14.7% in Rome), likely because of the reduced O3 titration triggered by lower NO emissions from vehicles, and lower NOx emissions over typical VOCs-limited environments such as urban areas, not compensated by comparable VOCs emissions reductions. PM10 exhibited reductions up to 31.5% (Palermo) and increases up to 7.3% (Naples), while PM2.5 showed reductions of ∼13-17% counterbalanced by increases up to ∼9%. Higher household heating usage (+16-19% in March), also driven by colder weather conditions than 2019 (-0.2 to -0.8 °C) may partly explain primary PM emissions increase, while an increase in agriculture activities may account for the NH3 emissions increase leading to secondary aerosol formation. This study confirmed the complex nature of atmospheric pollution even when a major emission source is clearly isolated and controlled, and the need for consistent decarbonisation efforts across all emission sectors to really improve air quality and public health.

Project description:The objective of this study was to investigate the impact of COVID-19 lockdown on different air pollutants in eight cities of Kazakhstan by employing the data from the National Air Quality Monitoring Network. We selected eight cities located in different regions of the country with varied climatic and geographic conditions and emissions sources, providing good conditions for studying the differences in responses of air quality to COVID-19. Due to severe winters, the heating season in Kazakhstan has a significant impact on air quality; therefore, annual winter/spring changes in air quality were also compared. The positive effect of the COVID-19 lockdown (spring 2020) on NO2 and CO levels was observed in 5 and 3 cities, respectively (out of 8). Total Suspended Particles and SO2 exhibited a more complicated response to COVID-19 lockdown: cities had a varying effect. No impact of lockdown measures was observed in industrial cities (Ust-Kamenegorsk and Karagandy), but seasonal changes were significant. In addition, despite some improvements during the lockdown period, the air quality in seven out of eight cities was still below the safety levels. The atmospheric quality in urban areas of Kazakhstan has not improved significantly due to the lockdown measures. This study underscores the importance of imposing stricter air quality emission control over industrial enterprises and coal-fired power plants. Supplementary Information The online version contains supplementary material available at 10.1007/s40710-022-00603-w. Highlights Response of air quality to COVID-19 lockdown in eight cities of Kazakhstan was examined The positive effect of the COVID-19 lockdown on NO2 and CO was observed in 5 and 3 cities, respectively The effect of the quarantine measures on SO2 and TSP was different in different cities Industrial cities were not affected by the lockdown, but seasonal changes were significant NO2 and SO2 concentrations exceeded the WHO limits during the COVID-19 lockdown period Supplementary Information The online version contains supplementary material available at 10.1007/s40710-022-00603-w.

Dataset Information

A dataset of urban traffic flow for 13 Romanian cities amid lockdown and after ease of COVID19 related restrictions.

Publications

A dataset of urban traffic flow for 13 Romanian cities amid lockdown and after ease of COVID19 related restrictions.

Similar Datasets

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