Air Quality Implications of COVID-19 in California

Hydrogen Production Using a Nickel Catalyst Combining Redox Activity and Pendent Base Effects

With the mounting need for clean and renewable energy, catalysts for hydrogen production based on earth abundant elements are of great interest. Herein, we describe the synthesis, characterization, and catalytic activity of two nickel complexes based on the pyridinediimine ligand that possess basic nitrogen moieties of pyridine and imidazole that could potentially serve as pendent bases to enhance catalysis. Although these ligands have previously been reported to be complexed to some metal ions, they have not been applied to nickel. The nickel complex with the pendent pyridines was found to be the most active of the two, catalyzing proton reduction electrochemically with an overpotential of 490 mV. The appearance of a wave that preceded the Ni(I/0) redox couple in the presence of protons suggests that protonation of a dissociated pyridine was likely. Further evidence of this was provided with density functional theory calculations, and a mechanism of hydrogen production is proposed. Furthermore, in a light-driven system containing Ru(bpy)32+ and ascorbic acid, TON of 1400 were obtained.

Change in the air due to the coronavirus outbreak in four major cities of India: What do the statistics say?

The onset of the novel Coronavirus (COVID-19) has impacted all sectors of society. To avoid the rapid spread of this virus, the Government of India imposed a nationwide lockdown in four phases. Lockdown, due to COVID-19 pandemic, resulted a decline in pollution in India in general and in dense cities in particular. Data on key air quality indicators were collected, imputed, and compiled for the period 1st August 2018 to 31st May 2020 for India's four megacities, namely Delhi, Mumbai, Kolkata, and Hyderabad. Autoregressive integrated moving average (ARIMA) model and machine learning technique e.g. Artificial Neural Network (ANN) with the inclusion of lockdown dummy in both the models have been applied to examine the impact of anthropogenic activity on air quality parameters. The number of indicators having significant lockdown dummy are six (PM2.5, PM10, NOx, CO, benzene, and AQI), five (PM2.5, PM10, NOx, SO2 and benzene), five (PM10, NOx, CO, benzene and AQI) and three (PM2.5, PM10, and AQI) for Delhi, Kolkata, Mumbai and Hyderabad respectively. It was also observed that the prediction accuracy significantly improved when a lockdown dummy was incorporated. The highest reduction in Mean Absolute Percentage Error (MAPE) is found for CO in Hyderabad (28.98%) followed by the NOx in Delhi (28.55%). Overall, it can be concluded that there is a significant decline in the value of air quality parameters in the lockdown period as compared to the same time phase in the previous year. Insights from the COVID-19 pandemic will help to achieve significant improvement in ambient air quality while keeping economic growth in mind.

COVID-19 impacts on mobility, environment, and health of active transportation users

Active transportation could be an effective way to promote healthy physical activity, especially during pandemics like COVID-19. A comprehensive evaluation of health outcomes derived from COVID-19 induced active transportation can assist multiple stakeholders in revisiting strategies and priorities for supporting active transportation during and beyond the pandemic. We performed a two-step reviewing process by combining a scoping review with a narrative review to summarize published literature addressing the influence of COVID-19 on mobility and the environment that can lead to various health pathways and health outcomes associated with active transportation. We summarized the COVID-19 induced changes in active transportation demand, built environment, air quality, and physical activity. The results demonstrated that, since the pandemic began, bike-sharing users dropped significantly while recreational bike trips and walking activities increased in some areas. Meanwhile, there have been favorable changes to the air quality and the built environment for active transportation users. We then discussed how these changes impact health outcomes during the pandemic and their implications for urban planning and policymaking. This review also suggests that walking and biking can make up for the reduced physical activities during the pandemic, helping people stay active and healthy.

Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.

A Novel Method for Traffic Estimation and Air Quality Assessment in California

Motor vehicle traffic is recognized as one of the critical factors that causes air pollution; however, the relationship between traffic volume and air pollutant concentrations is unclear, especially at a local level. Traditional traffic volume monitoring systems collect traffic data through counting the number of vehicles, using either sensors or surveillance cameras, but they have clear limitations such as they can only monitor certain areas and specific occasions. To overcome such limitations, we introduce a method of monitoring traffic volume in the local area by collecting estimated travel times for virtual trips in Google Maps. We began collecting the data in January 2020; ironically, the COVID-19 pandemic provided a natural experimental environment of showing unusual trends in traffic volume and unexpected changes in air pollutants. We demonstrate monthly traffic volumes in urban areas and analyze the correlation of traffic volume with typical traffic-related air pollutants using the proposed traffic volume monitoring method.

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO₂), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

Simulation of the Air Quality in Southern California, USA in July and October of the Year 2018

A numerical investigation of the air quality in Southern California, USA in the year 2018 is presented using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). In July, a heat wave occurred, and in October, Santa Ana conditions prevailed; these conditions and their impact on air quality are the scope of the present numerical study.The high spatial resolution in the simulation includes two nested domains of 1 km and 3 km, respectively. Local climate zones land use categories are combined with the complex urban model building effect parameterization coupled with the building energy model (BEP+BEM) and the detailed MOZCART-T1 chemical reaction mechanism, which is the MOZART-T1 mechanism for trace gases with GOCART aerosols. Thus, the model is suitable to compare simulation results to in situ and satellite measurements of O3, NO2, CH4, and CO. The meteorology is captured well by the model. Comparison of simulation results with observations shows a good agreement of NO2 and ozone, whereas CO mixing ratios are generally underestimated. This hints at missing emissions in the 2017 National Emissions Inventory (NEI) dataset. Both the heat wave and the Santa Ana winds increase the air pollution with gas-phase species in Los Angeles. In both cases, nighttime boundary layer heights are small, which causes emissions to reside near the ground. During Santa Ana winds, NOx removal on aerosols is reduced. Methane mixing ratios are modeled very well at most stations in Los Angeles, but predictions of low emissions near the University of California cause inaccuracies at that location. Modeled and observed PM2.5 agree well on low-pollution days, but high-pollution events are generally missed by the model. During the heat wave, both modeled and observed PM2.5 concentrations exceed the recommended NAAQS National Ambient Air Quality Standards value of 12.5 g/m3. The present modeling approach serves as a base for the study and prediction of special weather events and their impact on air pollution.

A comprehensive study of the COVID-19 impact on PM2.5 levels over the contiguous United States: A deep learning approach

We investigate the impact of the COVID-19 outbreak on PM_2.5 levels in eleven urban environments across the United States: Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, Phoenix, and Seattle. We estimate daily PM_2.5 levels over the contiguous U.S. in March-May 2019 and 2020, and leveraging a deep convolutional neural network, we find a correlation coefficient, an index of agreement, a mean absolute bias, and a root mean square error of 0.90 (0.90), 0.95 (0.95), 1.34 (1.24) μg/m³, and 2.04 (1.87) μg/m³, respectively. Results from Google Community Mobility Reports and estimated PM_2.5 concentrations show a greater reduction of PM_2.5 in regions with larger decreases in human mobility and those in which individuals remain in their residential areas longer. The relationship between vehicular PM_2.5 (i.e., the ratio of vehicular PM_2.5 to other sources of PM_2.5) emissions and PM_2.5 reductions (R = 0.77) in various regions indicates that regions with higher emissions of vehicular PM_2.5 generally experience greater decreases in PM_2.5. While most of the urban environments ⸺ Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, and Seattle ⸺ show a decrease in PM_2.5 levels by 21.1%, 20.7%, 18.5%, 8.05%, 3.29%, 3.63%, 6.71%, 4.82%, 13.5%, and 7.73%, respectively, between March-May of 2020 and 2019, Phoenix shows a 5.5% increase during the same period. Similar to their PM_2.5 reductions, Washington DC, New York, and Boston, compared to other cities, exhibit the highest reductions in human mobility and the highest vehicular PM_2.5 emissions, highlighting the great impact of human activity on PM_2.5 changes in eleven regions. Moreover, compared to changes in meteorological factors, changes in pollutant concentrations, including those of black carbon, organic carbon, SO₂, SO₄, and especially NO₂, appear to have had a significantly greater impact on PM_2.5 changes during the study period.

Intra-city variability of fine particulate matter during COVID-19 lockdown: A case study from Park City, Utah

Urban air quality is a growing concern due a range of social, economic, and health impacts. Since the SARS-CoV-19 pandemic began in 2020, governments have produced a range of non-medical interventions (NMIs) (e.g. lockdowns, stay-at-home orders, mask mandates) to prevent the spread of COVID-19. A co-benefit of NMI implementation has been the measurable improvement in air quality in cities around the world. Using the lockdown policy of the COVID-19 pandemic as a natural experiment, we traced the changing emissions patterns produced under the pandemic in a mid-sized, high-altitude city to isolate the effects of human behavior on air pollution. We tracked air pollution over time periods reflecting the Pre-Lockdown, Lockdown, and Reopening stages, using high quality, research grade sensors in both commercial and residential areas to better understand how each setting may be uniquely impacted by pollution downturn events. Based on this approach, we found the commercial area of the city showed a greater decrease in air pollution than residential areas during the lockdown period, while both areas experienced a similar rebound post lockdown. The easing period following the lockdown did not lead to an immediate rebound in human activity and the air pollution increase associated with reopening, took place nearly two months after the lockdown period ended. We hypothesize that differences in heating needs, travel demands, and commercial activity, are responsible for the corresponding observed changes in the spatial distribution of pollutants over the study period. This research has implications for climate policy, low-carbon energy transitions, and may even impact local policy due to changing patterns in human exposure that could lead to important public health outcomes, if left unaddressed.

The Impact of COVID-19 Lockdowns on Air Quality—A Global Review

The outbreak of the COVID-19 pandemic has emerged as a serious public health threat and has had a tremendous impact on all spheres of the environment. The air quality across the world improved because of COVID-19 lockdowns. Since the outbreak of COVID-19, large numbers of studies have been carried out on the impact of lockdowns on air quality around the world, but no studies have been carried out on the systematic review on the impact of lockdowns on air quality. This study aims to systematically assess the bibliographic review on the impact of lockdowns on air quality around the globe. A total of 237 studies were identified after rigorous review, and 144 studies met the criteria for the review. The literature was surveyed from Scopus, Google Scholar, PubMed, Web of Science, and the Google search engine. The results reveal that (i) most of the studies were carried out on Asia (about 65%), followed by Europe (18%), North America (6%), South America (5%), and Africa (3%); (ii) in the case of countries, the highest number of studies was performed on India (29%), followed by China (23%), the U.S. (5%), the UK (4%), and Italy; (iii) more than 60% of the studies included NO2 for study, followed by PM2.5 (about 50%), PM10, SO2, and CO; (iv) most of the studies were published by Science of the Total Environment (29%), followed by Aerosol and Air Quality Research (23%), Air Quality, Atmosphere & Health (9%), and Environmental Pollution (5%); (v) the studies reveal that there were significant improvements in air quality during lockdowns in comparison with previous time periods. Thus, this diversified study conducted on the impact of lockdowns on air quality will surely assist in identifying any gaps, as it outlines the insights of the current scientific research.

How changes in human activities during the lockdown impacted air quality parameters: A review

The health emergency linked to the spread of COVID-19 has led to important reduction in industrial and logistics activities, as well as to a drastic changes in citizens' behaviors and habits. The restrictions on working activities, journeys and relationships imposed by the lockdown have had important consequences, including for environmental quality. This review aims to provide a structured and critical evaluation of the recent scientific bibliography that analyzed and described the impact of lockdown on human activities and on air quality. The results indicate an important effect of the lockdown during the first few months of 2020 on air pollution levels, compared to previous periods. The concentrations of particulate matter, nitrogen dioxide, sulfur dioxide and carbon monoxide have decreased. Tropospheric ozone, on the other hand, has significantly increased. These results are important indicators that can become decision drivers for future policies and strategies in industrial and logistics activities (including the mobility sector) aimed at their environmental sustainability. The scenario imposed by COVID-19 has supported the understanding of the link between the reduction of polluting emissions and the state of air quality and will be able to support strategic choices for the future sustainable growth of the industrial and logistics sector.

Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan

Background and objectives: The impacts of COVID-19 are like two sides of one coin. During 2020, there were many research papers that proved our environmental and climate conditions were improving due to lockdown or large-scale restriction regulations. In contrast, the economic conditions deteriorated due to disruption in industry business activities and most people stayed at home and worked from home, which probably reduced the noise pollution. Methods: To assess whether there were differences in noise pollution before and during COVID-19. In this paper, we use various statistical methods following odds ratios, Wilcoxon and Fisher’s tests and Bayesian Markov chain Monte Carlo (MCMC) with various comparisons of prior selection. The outcome of interest for a parameter in Bayesian inference is complete posterior distribution. Roughly, the mean of the posterior will be clear with point approximation. That being said, the median is an available choice. Findings: To make the Bayesian MCMC work, we ran the sampling from the conditional posterior distributions. It is straightforward to draw random samples from these distributions if they have regular shapes using MCMC. The case of over-standard noise per time frame, number of noise petition cases, number of industry petition cases, number of motorcycles, number of cars and density of vehicles are significant at α=5%. In line with this, we prove that there were differences of noise pollution before and during COVID-19 in Taiwan. Meanwhile, the decreased noise pollution in Taiwan can improve quality of life.

Remote-Working Carbon-Saving Footprint: Could COVID-19 Pandemic Establish a New Working Model with Positive Environmental Health Implications?

Urban air pollution is a major problem with known negative health implications, such as respiratory and cardiovascular diseases. Lockdown measures have caused the reductions of various urban pollutants, such as nitrogen dioxide (NO₂), particulate matters (PMs), and polycyclic aromatic hydrocarbons (PAHs). COVID-19 pandemic has also established remote-working as an antidote to declining economic activity due to lockdown measures. The environmental health implications of the new hybrid-working model, which drastically reduces the number of circulating vehicles, appear to be positive enough to reveal an emerging opportunity. Since this hybrid model may have started becoming a widely accepted working model, the current situation has revealed the opportunity of remote-working arrangements to serve as a supplementary mitigative and adaptive measure against urban environmental deterioration. Also, a remote-working carbon-saving footprint may be introduced in order to evaluate a firm's carbon footprint reduction due to remote-working arrangements. These workings arrangements may be accompanied by improvements and expansions of urban green spaces and with broader use of electric vehicles, transforming our cities into more sustainable, safe, healthy, and worth-living environments.

Changes in Air Quality during the COVID-19 Pandemic and Associated Health Benefits in Korea

The COVID-19 pandemic was caused by a highly contagious coronavirus that has triggered worldwide control actions such as social distancing and lockdowns. COVID-19 control actions have resulted in improved air quality locally and around the world in the short-term by limiting human activity. We analyzed the impacts of social distancing and transboundary pollutants on air quality changes using open data and examined the corresponding health benefits focusing on two domestic cities (Seoul and Daegu) in Korea where the spread of coronavirus was severe. During the COVID-19 pandemic, PM2.5, PM10, and NO2 concentrations decreased significantly by 31%, 61%, and 33%, respectively, compared to the previous three years. In particular, the PM2.5/PM10 ratio fell 24.5% after the implementation of social distancing, suggesting a decrease in anthropogenic emissions. Moreover, we found that the air quality index (AQI) also improved significantly, with a focus on reducing exposure to sensitive groups. In Seoul and Daegu, improved air quality prevented 250 and 78 premature deaths, and health costs were USD 884 million and USD 278 million, respectively. On the other hand, health loss due to COVID-19 deaths was in sharp contrast to USD 7.1 million and USD 543.6 million. Our findings indicate a significant association between COVID-19 prevalence patterns and health outcomes.

Atmospheric Emission Changes and Their Economic Impacts during the COVID-19 Pandemic Lockdown in Argentina

This work studied the emission changes and their economic effects during the Argentina’s COVID-19 pandemic lockdown. We have analyzed the atmospheric emissions of the main greenhouse gases (GHG: CO2, CH4, and N2O) and other pollutants (NOx, CO, NMVOC, SO2, PM10, PM2.5, and BC) from various sectors such as private road transport, freight, public transport, agriculture machines, thermal power plants, residential, commercial, and governmental from January 2005 to April 2020. We focused on the months with the greatest restrictions of COVID-19 pandemic in Argentina (March and April 2020). The results show emissions reduction up to 37% for PM10, PM2.5, and BC, consistent with observed from satellite images and up to 160% for NOx, CO, NMVOC, and SOx. However, the residential sector has increased their emissions by 8% for the same period. As a consequence, 3337 Gg of CO2eq of GHG emissions were reduced, corresponding to a 20% reduction compared to the same period in 2019. Besides, a 26% reduction in gross domestic product (GDP) was observed due to the COVID-19 pandemic. Our results show that each Tg of GHG reduction was associated to a 0.16% reduction of the GDP from the analyzed sectors. Thus, without a voluntary reduction in consumption associated to significant cultural and technological changes, reduction in GHG would still be associated with deepening inequalities and asymmetries between high and low consumption sectors (i.e., with better (lesser) education, health, and job opportunities), even within countries and cities.