Traffic-induced atmospheric pollution during the COVID-19 lockdown: Dispersion modeling based on traffic flow monitoring in Turin, Italy

Quantifying the impact of urban road traffic on air quality: activity pre-pandemic and during partial and full lockdowns

The impact of partial and full COVID lockdowns in 2020 on vehicle miles traveled (VMT) in Kuwait was estimated using data extracted from the Directions API of Google Maps and a Python script running as a cronjob. This approach was validated by comparing the predictions based on the app to measuring traffic flows for 1 week across four road segments considered in this study. VMT during lockdown periods were compared to VMT for the same calendar weeks before the pandemic. NOx emissions were estimated based on VMT and were used to simulate the spatial patterns of NOx concentrations using an air quality model (AERMOD). Compared to pre-pandemic periods, VMT was reduced by up to 25.5% and 42.6% during the 2-week partial and full lockdown episodes, respectively. The largest reduction in the traffic flow rate occurred during the middle of these 2-week periods, when the traffic flow rate decreased by 35% and 49% during the partial and full lockdown periods, respectively. The AERMOD simulation results predicted a reduction in the average maximum concentration of emissions directly related to VMT across the region by up to 38%, with the maximum concentration shifting to less populous residential areas as a result of the lockdown.

California's zero-emission vehicle adoption brings air quality benefits yet equity gaps persist

Zero-emission vehicle (ZEV) adoption is a key climate mitigation tool, but its environmental justice implications remain unclear. Here, we quantify ZEV adoption at the census tract level in California from 2015 to 2020 and project it to 2035 when all new passenger vehicles sold are expected to be ZEVs. We then apply an integrated traffic model together with a dispersion model to simulate air quality changes near roads in the Greater Los Angeles. We found that per capita ZEV ownership in non-disadvantaged communities (non-DACs) as defined by the state of California is 3.8 times of that in DACs. Racial and ethnic minorities owned fewer ZEVs regardless of DAC designation. While DAC residents receive 40% more pollutant reduction than non-DACs due to intercommunity ZEV trips in 2020, they remain disproportionately exposed to higher levels of traffic-related air pollution. With more ZEVs in 2035, the exposure disparity narrows. However, to further reduce disparities, the focus must include trucks, emphasizing the need for targeted ZEV policies that address persistent pollution burdens among DAC and racial and ethnic minority residents.

Tracking air quality trends and vehicle traffic dynamics at urban scale using satellite and ground data before and after the COVID-19 outbreak

The implications of the COVID-19 outbreak are subjected to an increasing number of studies. So far, air quality trends related to the lockdown due to the pandemic have been analysed in large cities or entire regions. In this work, the region studied is the metropolitan area of Cagliari, which is the main city on the island of Sardinia (Italy) and can be representative of a coastal city that includes industrial settlements. The purpose of the study is to evaluate the effect of restrictions related to the COVID-19 outbreak on air quality levels and the traffic dynamics in this type of urban area. Nitrogen Dioxide (NO₂) levels before, during and after COVID-19 lockdown have been investigated using data acquired from the Sentinel-5P/TROPOMI satellite combined with on-site measurements. Both TROPOMI detected and ground-based data have revealed higher levels of NO₂ before and after the lockdown, compared to those during the period of COVID-related restrictions, in particular in the urban area of Cagliari. On the other hand, NO2 registered in the oil refinery area did not show significant differences associated with lockdown. The correlation of TROPOMI NO₂ tropospheric column with ground data (surface NO2) on a monthly mean basis showed different values based on the background and the highest Pearson's coefficient was of about 0.78 near to the city centre, where traffic can be considered a significant source of emission. In addition, a comparison of the air pollution level with the dynamics of vehicle traffic was investigated. The study highlighted a remarkable correlation between the reduction of the number of vehicles and the corresponding tropospheric NO₂ values that decreased on a weekly mean basis.

Potential of Coupling Metaheuristics-Optimized-XGBoost and SHAP in Revealing PAHs Environmental Fate

Polycyclic aromatic hydrocarbons (PAHs) refer to a group of several hundred compounds, among which 16 are identified as priority pollutants, due to their adverse health effects, frequency of occurrence, and potential for human exposure. This study is focused on benzo(a)pyrene, being considered an indicator of exposure to a PAH carcinogenic mixture. For this purpose, we have applied the XGBoost model to a two-year database of pollutant concentrations and meteorological parameters, with the aim to identify the factors which were mostly associated with the observed benzo(a)pyrene concentrations and to describe types of environments that supported the interactions between benzo(a)pyrene and other polluting species. The pollutant data were collected at the energy industry center in Serbia, in the vicinity of coal mining areas and power stations, where the observed benzo(a)pyrene maximum concentration for a study period reached 43.7 ngm-3. The metaheuristics algorithm has been used to optimize the XGBoost hyperparameters, and the results have been compared to the results of XGBoost models tuned by eight other cutting-edge metaheuristics algorithms. The best-produced model was later on interpreted by applying Shapley Additive exPlanations (SHAP). As indicated by mean absolute SHAP values, the temperature at the surface, arsenic, PM10, and total nitrogen oxide (NOx) concentrations appear to be the major factors affecting benzo(a)pyrene concentrations and its environmental fate.

Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis

As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.

Waste management beyond the COVID-19 pandemic: Bibliometric and text mining analyses

The outbreak of the COVID-19 pandemic has significantly increased the demand for personal protective equipment, in particular face masks, thus leading to a huge amount of healthcare waste generated worldwide. Consequently, such an unprecedented amount of newly emerged waste has posed significant challenges to practitioners, policy-makers, and municipal authorities involved in waste management (WM) systems. This research aims at mapping the COVID-19-related scientific production to date in the field of WM. In this vein, the performance indicators of the target literature were analyzed and discussed through conducting a bibliometric analysis. The conceptual structure of COVID-19-related WM research, including seven main research themes, were uncovered and visualized through a text mining analysis as follows: (1) household and food waste, (2) personnel safety and training for waste handling, (3) sustainability and circular economy, (4) personal protective equipment and plastic waste, (5) healthcare waste management practices, (6) wastewater management, and (7) COVID-19 transmission through infectious waste. Finally, a research agenda for WM practices and activities in the post-COVID-19 era was proposed, focusing on the following three identified research gaps: (i) developing a systemic framework to properly manage the pandemic crisis implications for WM practices as a whole, following a systems thinking approach, (ii) building a circular economy model encompassing all activities from the design stage to the implementation stage, and (iii) proposing incentives to effectively involve informal sectors and local capacity in decentralizing municipal waste management, with a specific focus on developing and less-developed countries.

COVID-19 and Sustainable Development Goals (SDGs): Scenario analysis through fuzzy cognitive map modeling

The COVID-19 crisis has immensely impacted the implementation of the 2030 Agenda for Sustainable Development worldwide. This research aims at providing a policy response to support achieving the Sustainable Development Goals (SDGs) taking the COVID-19 long-term implications into account. To do so, a qualitative analytical method was employed in the following four steps. First, a fuzzy cognitive map was developed to specify causal-effect links of the interdependent SDGs in Iran as a developing country in the Middle East. Second, potential effects of the pandemic on the SDGs achievement were analyzed. Third, five strategies were formulated, including green management, sustainable food systems, energizing the labor market, inclusive education, and supporting research and technology initiatives in the energy sector. And finally, different scenarios corresponding to the five proposed strategies were tested based on the identified interconnections among the SDGs. The analysis showed that applying each of the five considered strategies or their combination would mitigate the effect of COVID-19 on the SDGs only in case of a medium pandemic activation level. Moreover, implementing a single strategy with a high activation level leads to better outcomes on the SDGs rather than applying a combination of strategies in low or medium activation levels during the pandemic situation. The provided insights support stakeholders and policy-makers involved in the post-COVID-19 recovery action plan towards implementing the 2030 Agenda for Sustainable Development.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM_2.5: 67 µg m^-3 (lockdown) versus 81 µg m^-3 (pre-lockdown); PM₁₀: 171 µg m^-3 versus 235 µg m^-3; CO: 0.9 mg m^-3 versus 1.1 mg m^-3) except ozone which increased during the lockdown period (57 µg m^-3 versus 39 µg m^-3). The variation in pollutant concentrations revealed that PM_2.5, PM₁₀ and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

As a key node city of the "Silk Road Economic Belt" Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. This study analyzed the air quality before and during the COVID-19 (Coronavirus disease 2019) pandemic and its potential health effects based on the data of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃_8h levels from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021. As per the results, the concentrations of the air pollutants PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃_8h in Urumqi from 2017 to 2021 showed a cyclical trend, and the implementation of COVID-19 prevention and control measures could effectively reduce the concentration(ρ) of air pollutants. The mean value of ρ(PM_2.5) decreased from 2017 to 2021, whereas ρ(O₃_8h) showed a waveform change trend (increased in 2017-2018, decreased in 2018-2020, and increased after 2020). Meanwhile, the maximum annual average values of ρ(PM_2.5) and ρ(O₃_8h) for the six monitoring stations during 2017-2021 occurred at sites S2 (74.37 µg m^-3) and S6 (91.80 µg m^-3), respectively; rapid industrialization had a greater impact on PM_2.5 and O₃_8h concentrations compared to commercial and residential areas. In addition, the air quality index data series can characterize the fluctuation trend of PM_2.5. The high pollution levels (Class IV and V) of the air pollutants PM_2.5 and O₃_8h in Urumqi have been decreasing annually, and good days can account for 80-95% of the total number of days in the year, indicating that the number of days with a potential threat to residents' health is gradually decreasing. Therefore, more attention should be paid in controlling and managing air pollution in Urumqi.

An overview and thematic analysis of research on cities and the COVID-19 pandemic: Toward just, resilient, and sustainable urban planning and design

Since early 2020, researchers have made efforts to study various issues related to cities and the pandemic. Despite the wealth of research on this topic, there are only a few review articles that explore multiple issues related to it. This is partly because of the rapid pace of publications that makes systematic literature review challenging. To address this issue, in the present study, we rely on bibliometric analysis techniques to gain an overview of the knowledge structure and map key themes and trends of research on cities and the pandemic. Results of the analysis of 2,799 articles show that research mainly focuses on six broad themes: air quality, meteorological factors, built environment factors, transportation, socio-economic disparities, and smart cities, with the first three being dominant. Based on the findings, we discuss major lessons that can be learned from the pandemic and highlight key areas that need further research.

Exposure and health: A progress update by evaluation and scientometric analysis

Several hands are now working worldwide to reduce exposure to air pollution, especially in developing nations. Future steps should be determined and classified as possible research solutions and gaps from the massive bulk of research output. Therefore, a scientometric approach has been applied using VOSviewer to show an accurate picture and trend in the mentioned area "Air pollution exposure and health," and its signify issues. According to the proposed study, complete 26,859 documents were retrieved from the database (ISI Web of Science) related to air pollution exposure and health effects during 2018-2022. The mapping analysis is been conducted on the country's collaboration, co-authorship, institutional collaboration, and co-occurrence of keywords. The data collected shows the information about published articles (upward trend) over the years. Based on the citations and publication database, countries like China and the USA play a prominent role in air pollution exposure and health-related research. The study clearly defines the 3 domains of research and 4 major themes that have been currently focused. The case studies related to pollution and its impact on climate and health, studies involving chemical characteristics and management practices, also Hazardous health effects, theme like association of air pollutants, chemical composition and characterization of aerosols, health impacts due to exposure and modelling and analytical approach have been the most researched topics in the past 5 years. The developing and developed countries might potentially change the research network and work structure in order to obtain advancement in the field of Air pollution and enhance measures on exposure and health. The following research attempts to provide insights to the researchers and health sectors by straightening out developments up to date and raveling the research gaps that are needed to be addressed regarding Air pollution health and exposure.

Build Healthier: Post-COVID-19 Urban Requirements for Healthy and Sustainable Living

The COVID-19 pandemic has brought a renewed interest in urban environment and healthy living and the changes in urban environments which can make for a healthier living. Today, more than 50% of the global population lives in urban areas, and in Europe the number is 75%. We present a narrative review to explore considerations and necessary requirements to achieve health and well-being within strategies for healthy design and urban planning whilst rethinking urban spaces for a post-COVID-19 and carbon-neutral future. The achievement of health and well-being demands healthy design strategies, namely, (1) moving from the concept of infrastructure for processes to the infrastructure for healthy living—requirements for healthy places, cycling, walking, disintegrating the role of polluting traffic from the urban environments, social vulnerability and equality; (2) physical space that will achieve standards of ‘liveable communities’—open, green space requirements and standards for any built environment; (3) mainstreaming ‘in-the-walking distance’ cities and neighbourhoods for healthy physical activities for daily living; (4) exploring any of the new concepts that connect the nexus of urban spaces and public health and improving of the population’s well-being. Public health needs to be prioritised systematically in planning of built environments, energy generations, sustainable food production, and nutrition.

Living Lab Experience in Turin: Lifestyles and Exposure to Black Carbon

State-of-the-art, continuous personal monitoring is a reference point for assessing exposure to air pollution. European air-quality standards for particulate matter (PM) use mass concentration of PM (PM with aerodynamic diameters ≤ 10 μm (PM10) or ≤2.5 μm (PM2.5)) as the metric. It would be desirable to determine whether black carbon (BC) can be used as a better, newer indicator than PM10 and PM2.5. This article discusses the preliminary results of one of the three living laboratories developed in the project "Combination of traditional air quality indicators with an additional traffic proxy: Black Carbon (BC)". The Living Lab#1 (LL#1) involved 15 users in the city of Turin, Italy. Three portable aethalometers (AE51) were used to detect personal equivalent black carbon (eBC) concentrations in the respiratory area of volunteers at 10-s intervals as they went about their normal daily activities. The Geo-Tracker App and a longitudinal temporal activity diary were used to track users' movements. The sampling campaign was performed in November for one week. and each user was investigated for 24 h. A total of 8640 eBC measurements were obtained with an average daily personal exposure of 3.1 µg/m³ (±SD 1.3). The change in movement patterns and the variability of microenvironments were decisive determinants of exposure. Preliminary results highlight the potential utility of Living Labs to promote innovative approaches to design an urban-scale air-quality management plan which also includes BC as a new indicator.

A European-Wide Study on the Effects of the COVID-19 Threat on Active Transport Modes

In the past year and a half, we have been forced to make many major changes which, besides other issues, have led to considerable changes in transport mode choices. While we observed an increase in the share of cars as a mode of transport, we also observed an increase in the level of engagement in other active mobility modes, such as walking and cycling. Relevant literature shows that although the restrictions adopted during the COVID-19 pandemic have effects on people’s mobility behaviour, they can be viewed as a catalyst for positive changes as far as active forms of mobility are concerned. This work focuses on the thorough understanding of the changes in citizens’ needs and attitudes toward mobility and transport mode choice during the COVID-19 pandemic. To reach this aim, we analysed the responses to an interview consisting of eight open-ended questions about the effects of the COVID-19 pandemic threat and situation of citizens in selected European countries and Russia. In total, 497 respondents participated by responding to an online questionnaire. The conclusions of this study confirmed that active traffic modes could benefit from the momentum generated by the COVID-19 pandemic. However, this can only happen if appropriate preconditions can be provided, which is not the case so far. To prevent a massive return of private motorised vehicles into urban centres, we must focus on support for active traffic modes, specifically on the improvement of the preconditions, especially as far as traffic infrastructure is concerned.

The Effect of the COVID-19 Pandemic on Traffic Flow Characteristics, Emissions Production and Fuel Consumption at a Selected Intersection in Slovakia

The surveyof traffic intensity is used to obtain information on the number of vehicles on roads during the day. Subsequently, it is possible to derive from this the daily, weekly, and other road traffic intensity information. This survey represents the basis for the calculation of the annual average daily traffic volume and the basic characteristics of traffic flow. The COVID-19 pandemic has caused extensive economic and social damage around the world. These damages have also affected traffic. Changes in traffic behavior have mainly affected the reduction in traffic intensity on road networks. Thanks to the reduction in the demand for transport, there has also been a significant reduction in traffic delays, fuel consumption and emissions. An examination of changes in traffic intensity took place at a selected intersection in 2019, 2020 and 2021. This paper describes the effects of reducing the traffic intensity, fuel consumption and emissions obtained by microsimulation. The results obtained confirmed the reduction in traffic, which also contributed to a significant reduction in vehicle delays.

Air pollution in five Indian megacities during the Christmas and New Year celebration amidst COVID-19 pandemic

Urban air quality and COVID-19 have been considered significant issues worldwide in the last few years. The current study highlighted the variation in air pollutants (i.e., PM_2.5, PM₁₀, NO₂, and SO₂) profile between Christmas and new year celebrations in 2019, 2020, and 2021. It can be seen that the concentration of selected air pollutants shows a substantially higher concentration in celebration periods in all reported years. The results indicate that air pollutants values are always higher than permissible limits. This observation indicates that people gather and reunite during Christmas and new year celebrations than the preceding years (2020 and 2021) amidst the pandemic. In the pandemic year, a higher margin enhanced the transportation and firework-induced air pollutant load in urban city Jodhpur, Rajasthan. In all states, a significant tendency was observed to retain the concentration profile of air pollutants in baseline concentration for almost more than one week after the celebration. This study addresses the pandemic situation, but it also dealt with the air pollutant parameter that brings down the sustainable quality of the environment due to the high usage of private vehicles, and crackers. In addition, a study on COVID-19 (cases and death rate) indicates a clear picture of the increasing trend after the event in probably all states. Thus, this approach suggested that stringent law enforcement is needed to ameliorate gatherings/reunions and pollution levels due to such events.