Characterizing spatiotemporal patterns of elevated PM2.5 exposures in a megacity of China using combined mobile and stationary measurements

Exposure to PM2.5 (particles with an aerodynamic diameter equal to or less than 2.5 μm) is associated with a variety of negative health outcomes. Measurements from sparsely situated air quality monitoring stations (AQMSs) may be inappropriate to represent real PM2.5 exposures, particularly in traffic-related environments. In this study, efforts were made to characterize spatiotemporal variation of PM2.5 pollutions over Shenzhen, China from July 2019 to June 2020 using combined mobile (on-road PM2.5) and stationary (AQMS PM2.5) measurements. Monthly-average concentrations of on-road PM2.5 ranged from 10.4 ± 6.1 to 47.3 ± 23.9 μg/m3, and showed consistent trend with AQMS PM2.5 concentrations which ranged from 8.3 ± 3.1 to 37.2 ± 12.9 μg/m3. On-road PM2.5 and AQMS PM2.5 concentrations dropped by 54.6% and 30.2% in February 2020, probably due to the low anthropogenic emissions during the period of Spring Festival and COVID-19 lockdown. Weekend effect on both on-road and AQMS PM2.5 concentrations was not noticeable. Relative high on-road PM2.5 concentrations were observed during morning and evening rush hours. An "elevated concentration” concept was applied to estimate the influence of emissions on PM2.5 exposures. Elevated concentrations showed strong diurnal and spatial variation, and was about 5.0 μg/m3 on-average. Mappings of on-road PM2.5 and elevated concentrations confirmed the heterogeneity of spatial distribution of PM2.5 exposures in Shenzhen where PM2.5 pollutions were more severe in western and northern areas. Our results highlight the elevated PM2.5 exposures in traffic-related environments, and the inequity in urban exposure levels and health.

Air pollution assessment in Seoul, South Korea, using an updated daily air quality index

The variability of daily air quality index DAQx* was analyzed for types of air quality monitoring stations (AQMSs) in Seoul, South Korea, from 2018 to 2021. Daily maximum 1-h means of O3 and NO2 and daily 24-h means of PM10 and PM2.5 from 42 AQMSs were used to calculate the DAQx*. The frequencies of DAQx* values in DAQx* classes 3 (satisfactory) and 4 (sufficient) dominated for all station types, followed by DAQx* class 5 (poor). The variability of DAQx* values within station types mostly corresponded approximately to one DAQx* class, with mean frequencies of 82% for roadside, 81% for urban, and 72% for background stations. Lower air pollution levels on weekends than weekdays were shown for roadside stations by frequencies of DAQx* values in classes 3 (11% higher) and 4 (12% lower) during summer. NO2 was the air pollutant that annually most frequently formed DAQx* at roadside (48%) and urban (32%) stations, while O3 was the dominant pollutant (38%) at background stations. In winter, PM10 was the most common contributor to the DAQx* (at least 47%) at all station types. The dominant air pollutants in summer were NO2 at roadside stations (72%) and O3 at urban (63%) and background (68%) stations. Air quality improvement during a stronger social distancing period in 2020 due to the COVID-19 pandemic was evidenced by higher frequencies in DAQx* class 3 (up to 26%) but lower frequencies in DAQx* class 4 (up to 24%) than that during the reference period, especially for the roadside stations. © 2023 Turkish National Committee for Air Pollution Research and Control

Characteristics and source apportionment of PM 2.5 under the dual influence of the Spring Festival and the COVID-19 pandemic in Yuncheng city

Based on the online and membrane sampling data of Yuncheng from January 1st to February 12th, 2020, the formation mechanism of haze under the dual influence of Spring Festival and COVID-19 (Corona Virus Disease) was analyzed. Atmospheric capacity, chemical composition, secondary transformation, source apportionment, backward trajectory, pollution space and enterprise distribution were studied. Low wind speed, high humidity and small atmospheric capacity inhibited the diffusion of air pollutants. Four severe pollution processes occurred during the period, and the pollution degree was the highest around the Spring Festival. In light, medium and heavy pollution periods, the proportion of SNA (SO 4 2 ???, NO 3 ??? and NH 4 + ) was 59.6%, 56.0% and 54.9%, respectively, which was the largest components of PM 2.5 ;the [NO 3 ???]/[SO 4 2 ???] ratio was 2.1, 1.5 and 1.7, respectively, indicating that coal source had a great influence;the changes of NOR (nitrogen oxidation ratio, 0.44, 0.45, 0.61) and SOR (sulphur oxidation ratio, 0.40, 0.49, 0.65) indicated the accumulation of secondary aerosols with increasing pollution. The coal combustion, motor vehicle, secondary inorganic sources and industrial sources contributed 36.8%, 26.59%, 11.84% and 8.02% to PM 2.5 masses, respectively. Backward trajectory showed that the influence from the east was greater during the Spring Festival, and the pollutants from the eastern air mass were higher, which would aggravate the pollution. Meteorological and Spring Festival had a great impact on heavy pollution weather. Although some work could not operate due to the impact of the COVID-19 epidemic, the emission of pollutants did not reduce much. ?? 2022 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Working in the Metaverse: Does Telework in a Metaverse Office Have the Potential to Reduce Population Pressure in Megacities? Evidence from Young Adults in Seoul, South Korea

Despite the growing number of teleworkers and the unsustainable challenges (e.g., environmental pollution) facing megacities due to population pressure, few studies have investigated whether telework can reduce population pressure in megacities. This study conducts a scenario-based experiment and proposes that telework can reduce population pressure in megacities by enticing megacity residents to leave the megacity. Specifically, given the increasing number of companies that are adopting metaverse teleworking offices, this study classifies telework into metaverse telework and non-metaverse telework and empirically demonstrates that both types of telework positively influence an individual’s intention to relocate from a megacity to a non-megacity. Additionally, this study further shows that metaverse telework has a greater impact on an individual’s intention to relocate from a megacity to a non-megacity than non-metaverse telework. This study demonstrates how different types of telework can differentially reduce population pressure in megacities and provides practical recommendations for policymakers and strategy managers to support this practice.

Impact of restrictions during the coronavirus pandemia on air pollution in Moscow

This paper presents the analysis of the data on suspended PM2.5 particle concentrations changing during the time periods before and after the stay-at-home restrictions aimed at preventing spread of COVID-19 in Moscow. The data used for this analysis were obtained at the Mosecomonitoring network stations and the Center of Geophysical Monitoring of Moscow at IDG RAS. © 2021 SPIE.

COVID-19 strict lockdown impact on urban air quality and atmospheric temperature in four megacities of india

COVID-19 pandemic has forced to lockdown the entire India starting from 24th March, 2020 to 14th April, 2020 (first phase), extended up to 3rd May, 2020 (second phase), and further extended up to 17th May, 2020 (third phase) with limited relaxation in non-hotspot areas. This strict lockdown has severely curtailed human activity across India. Here, aerosol concentrations of particular matters (PM) i.e., PM10, PM2.5, carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), ammonia (NH3) and ozone (O3), and associated temperature fluctuation in four megacities (Delhi, Mumbai, Kolkata, and Chennai) from different regions of India were investigated. In this pandemic period, air temperature of Delhi, Kolkata, Mumbai and Chennai has decreased about 3°C, 2.5°C, 2°C and 2°C respectively. Compared to previous years and pre-lockdown period, air pollutants level and aerosol concentration (–41.91%, –37.13%, –54.94% and –46.79% respectively for Delhi, Mumbai, Kolkata and Chennai) in these four megacities has improved drastically during this lockdown period. Emission of PM2.5 has experienced the highest decrease in these megacities, which directly shows the positive impact of restricted vehicular movement. Restricted emissions produce encouraging results in terms of urban air quality and temperature, which may encourage policymakers to consider it in terms of environmental sustainability.

Effect of COVID-19 pandemic-induced lockdown (general holiday) on air quality of Dhaka City.

A worldwide pandemic of COVID-19 has forced the Government of Bangladesh to implement a lockdown during April-May 2020 by restricting people's movement; shutdown of industries and motor vehicles; and closing markets, public places, and schools to contain the virus. This type of strict measures caused an outcome, the reduction of urban air pollution, around the world. The present study aims to investigate the reduction of the concentration of pollutants in the air of Dhaka City and the reduction of the Air Quality Index (AQI). Necessary time-series data of the concentration of PM2.5, NO2, SO2, and CO have been collected from the archive of the Air Quality Monitoring Station of the US Embassy in Dhaka and Sentinel-5P. The time-series data have been analyzed by descriptive statistics, and AQI was calculated following an appropriate formula suggested by the Environmental Protection Agency (EPA) based on the criteria pollutants. The study found that the concentrations of PM2.5, NO2, SO2, and CO during April-May 2020 have been reduced by 26, 30, 07, and 07%, respectively, compared with the preceding year's concentrations. Moreover, the AQI has also been reduced by about 35% on average during the lockdown period than the same times of the previous year. However, the magnitude of pollution reduction in Dhaka is lower than in other cities and countries globally, including Delhi, Sao Paulo, Wuhan, Spain, Italy, the USA. The main reasons may include, among others, the poor implementation of lockdown (especially in the first week of April and the second fortnight of May), pre-existing pollution, transboundary pollution, incineration of solid waste, etc. This study will help policymakers figure out how to regulate pollution sources and improve the air quality of Dhaka.

A high-resolution typical pollution source emission inventory and pollution source changes during the COVID-19 lockdown in a megacity, China.

To control the spread of COVID-19, China has imposed national lockdown policies to restrict the movement of its population since the Chinese New Year of January 2020. In this study, we quantitatively analyzed the changes of pollution sources in Shanghai during the COVID-19 lockdown; a high-resolution emission inventory of typical pollution sources including stationary source, mobile source, and oil and gas storage and transportation source was established based on pollution source data from January to February 2020. The results show that the total emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), particulate matter (PM), and volatile organic compounds (VOCs) were 9520.2, 37,978.6, 2796.7, and 7236.9 tons, respectively, during the study period. Affected by the COVID-19 lockdown, the mobile source experienced the largest decline. The car mileage and oil sales decreased by about 80% during the COVID-19 lockdown (P3) when compared with those during the pre-Spring Festival (P1). The number of aircraft activity decreased by approximately 50%. The impact of the COVID-19 epidemic on industries such as iron and steel and petrochemicals was less significant, while the greater impact was on coatings, chemicals, rubber, and plastic. The emissions of SO2, NOx, PM2.5, and VOCs decreased by 11%, 39%, 37%, and 47%, respectively, during P3 when compared with those during P1. The results show that the measures to control the spread of the COVID-19 epidemic made a significant contribution to emission reductions. This study may provide a reference for other countries to assess the impact of the COVID-19 epidemic on emissions and help establish regulatory actions to improve air quality.

Effects of COVID-19 pandemic control measures on air pollution in Lima metropolitan area, Peru in South America.

The sanitary measures implemented to control and prevent an increase in infections due to the COVID-19 pandemic have produced an improvement in the air quality of many urban areas around the world. We assessed air quality during the COVID-19 pandemic for particulate matter (PM2.5 and PM10), NO2 and O3 in in metropolitan area of Lima, Peru between pre-lockdown period (February 1 and March 15 of 2020), historical period (March 16 to April 30 2017-2019) and lockdown period (March 16 to April 30, 2020). The complete national lockdown that was implemented in Peru produced statistically significant reductions in the in-air pollutant (PM10 (-40% and -58%), PM2.5 (-31% and -43%) and NO2 (-46% and -48%)), as recorded by the by the ground-based air quality monitoring network throughout the metropolitan area, compared with the corresponding concentrations for the previous weeks and over the same period for 2017-2019. Analysis of the spatial Distribution of satellite data also show decreases in the concentrations of PM10, PM2.5 and NO2 as a result of the containment measures and suspension of activities implemented by the Peruvian government. The concentrations of O3 significantly increased (11% and 170%) as a result of the decrease in the concentration of NO2, confirming that the study area is a hydrocarbon-limited system, as previously reported. The results obtained contribute to the assessment by the regulatory agencies of the possible strategies of control and monitoring of air pollution in the study area. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-00990-3.

Chemistry of Atmospheric Fine Particles During the COVID-19 Pandemic in a Megacity of Eastern China.

Air pollution in megacities represents one of the greatest environmental challenges. Our observed results show that the dramatic NOx decrease (77%) led to significant O3 increases (a factor of 2) during the COVID-19 lockdown in megacity Hangzhou, China. Model simulations further demonstrate large increases of daytime OH and HO2 radicals and nighttime NO3 radical, which can promote the gas-phase reaction and nocturnal multiphase chemistry. Therefore, enhanced NO3 - and SO4 2- formation was observed during the COVID-19 lockdown because of the enhanced oxidizing capacity. The PM2.5 decrease was only partially offset by enhanced aerosol formation with its reduction reaching 50%. In particular, NO3 - decreased largely by 68%. PM2.5 chemical analysis reveals that vehicular emissions mainly contributed to PM2.5 under normal conditions in Hangzhou. Whereas, stationary sources dominated the residual PM2.5 during the COVID-19 lockdown. This study provides evidence that large reductions in vehicular emissions can effectively mitigate air pollution in megacities.

Living environment matters: Unravelling the spatial clustering of COVID-19 hotspots in Kolkata megacity, India.

The emergence of COVID-19 has brought a serious global public health threats especially for most of the cities across the world even in India more than 50 % of the total cases were reported from large ten cities. Kolkata Megacity became one of the major COVID-19 hotspot cities in India. Living environment deprivation is one of the significant risk factor of infectious diseases transmissions like COVID-19. The paper aims to examine the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. COVID-19 hotspot maps were prepared using Getis-Ord-Gi* statistic and index of multiple deprivations (IMD) across the wards were assessed using Geographically Weighted Principal Component Analysis (GWPCA).Five count data regression models such as Poisson regression (PR), negative binomial regression (NBR), hurdle regression (HR), zero-inflated Poisson regression (ZIPR), and zero-inflated negative binomial regression (ZINBR) were used to understand the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. The findings of the study revealed that living environment deprivation was an important determinant of spatial clustering of COVID-19 hotspots in Kolkata megacity and zero-inflated negative binomial regression (ZINBR) better explains this relationship with highest variations (adj. R2: 71.3 %) and lowest BIC and AIC as compared to the others.

The Episode of National Lockdown in the Pandemic: Air Traffic Restriction as the Control Strategy and Its Impact on Existing Cases and Recovery Rate of Novel Coronavirus Disease in Megacities of China.

OBJECTIVE: The effectiveness of air traffic restriction in containing the spread of infectious diseases is full of controversy in prior literature. In January 2020, the Civil Aviation Administration of China (CAAC) announced air traffic restriction in response to the coronavirus disease (COVID-19) pandemic. This study's aim is to empirically examine the policy effectiveness. METHOD: The data from 2 third-party platforms are used in this investigation. The COVID-19 data from the platform DXY and the air traffic data from Airsavvi are matched to each other. The robust panel regression with controlling city effect and time effect is conducted. RESULTS: The curvilinear relations are found between the air traffic restriction and the existing cases, and the recovery rate (quadratic term = 9.006 and -0.967, respectively). As the strength of air traffic restriction is growing, the negative effect (-8.146) of air traffic restriction on the existing cases and the positive effect (0.961) of air traffic restriction on the recovery rate, respectively, begin decreasing. CONCLUSION: On the macro level, the air traffic restriction may help alleviate the growth of existing cases and help raise the recovery rate of COVID-19 in megacities of China, but both these effects will marginally recede as the restriction strength is intensifying.

The airline transport regulation and development of public health crisis in megacities of China.

BACKGROUND: The Civil Aviation Administration of China (CAAC) declares the airline transport regulation in January 2020 to help retard the spread of the novel coronavirus disease in China. This study is to examine the effect of airline transport regulation on confirmed cases of the novel coronavirus disease in megacities in China. METHODS: This study combines the multi-source data from the health data platform DXY, the airline data platform Airsavvi, the China Economic Internet Statistical Database and the China Railway website. The megacities whose airports have a passenger throughput of over 30 million per year (11 megacities: Wuhan, Beijing, Shanghai, Guangzhou, Chengdu, Shenzhen, Kunming, Xi'an, Chongqing, Hangzhou, Nanjing) are included in the analysis. The regression analysis is conducted in this study. RESULTS: The curvilinear relationship between the limitation on air traffic and confirmed cases of the novel coronavirus disease is identified (coefficient of the linear term = -4.650, p-value < 0.01; coefficient of the quadratic term = 4.089, p-value < 0.01). CONCLUSIONS: This study confirms the effectiveness of airline transport regulation in suppressing the development of this pandemic. The limitation on air traffic is found to negatively affect the confirmed cases in China's megacities. However, such effect marginally recedes as the strength of limitation intensifies. It suggests that comprehensive policy intervention is in need and air traffic can be one of important determinants that affect the epidemic development.

Jakarta: A city of cities.

Jakarta, Indonesia's primate city and the world's second largest urban agglomeration, is undergoing a deep transformation. A fresh city profile of Jakarta is long overdue, given that there have been major events and developments since the turn of the millennium (the Asian Financial crisis and decentralisation in Indonesia, among the most important), as well as the fact that the city is a living entity with its own processes to be examined. The inhabitants of the city have also taken centre stage now in these urban processes, including the recent pandemic COVID-19 response. Our paper profiles Jakarta heuristically in two cuts: presenting the city from conventional and academic perspectives of megacities like it, which includes contending with its negative perceptions, and more originally, observing the city from below by paying attention to the viewpoints of citizens and practitioners of the city. In doing so, we draw from history, geography, anthropology, sociology and political science as well as from our experience as researchers who are based in the region and have witnessed the transformation of this megacity from within, with the idea that the portrayal of the city is a project permanently under construction.

Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India.

Amid the COVID-19 pandemic, a nationwide lockdown is imposed in India initially for three weeks from 24th March to 14th April 2020 and extended up to 3rd May 2020. Due to the forced restrictions, pollution level in cities across the country drastically slowed down just within few days which magnetize discussions regarding lockdown to be the effectual alternative measures to be implemented for controlling air pollution. The present article eventually worked on this direction to look upon the air quality scenario amidst the lockdown period scientifically with special reference to the megacity Delhi. With the aid of air quality data of seven pollutant parameters (PM10, PM2.5, SO2, NO2, CO, O3 and NH3) for 34 monitoring stations spread over the megacity we have employed National Air Quality Index (NAQI) to show the spatial pattern of air quality in pre and during-lockdown phases. The results demonstrated that during lockdown air quality is significantly improved. Among the selected pollutants, concentrations of PM10 and PM2.5 have witnessed maximum reduction (>50%) in compare to the pre-lockdown phase. In compare to the last year (i.e. 2019) during the said time period the reduction of PM10 and PM2.5 is as high as about 60% and 39% respectively. Among other pollutants, NO2 (-52.68%) and CO (-30.35%) level have also reduced during-lockdown phase. About 40% to 50% improvement in air quality is identified just after four days of commencing lockdown. About 54%, 49%, 43%, 37% and 31% reduction in NAQI have been observed in Central, Eastern, Southern, Western and Northern parts of the megacity. Overall, the study is thought to be a useful supplement to the regulatory bodies since it showed the pollution source control can attenuate the air quality. Temporary such source control in a suitable time interval may heal the environment.