Fifteen Years of Community Exposure to Heavy-Duty Emissions: Capturing Disparities over Space and Time.

Disparities in exposure to traffic-related air pollution have been widely reported. However, little work has been done to simultaneously assess the impact of various vehicle types on populations of different socioeconomic/ethnic backgrounds. In this study, we employed an extreme gradient-boosting approach to spatially distribute light-duty vehicle (LDV) and heavy-duty truck emissions across the city of Toronto from 2006 to 2020. We examined associations between these emissions and different marginalization indices across this time span. Despite a large decrease in traffic emissions, disparities in exposure to traffic-related air pollution persisted over time. Populations with high residential instability, high ethnic concentration, and high material deprivation were found to reside in regions with significantly higher truck and LDV emissions. In fact, the gap in exposure to traffic emissions between the most residentially unstable populations and the least residentially unstable populations worsened over time, with trucks being the larger contributor to these disparities. Our data also indicate that the number of trucks and truck emissions increased substantially between 2019 and 2020 whilst LDVs decreased. Our results suggest that improvements in vehicle emission technologies are not sufficient to tackle disparities in exposure to traffic-related air pollution.

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India.

The accent of the present study is determination of Urban Aerosol Pollution Island (UAPI) intensity and spatial variability in particulate matter concentration (PM10 and PM2.5) over Delhi. For analysis, the hourly concentration dataset of PM2.5 and PM10 from January 2019 to December 2020 was obtained from ten air quality monitoring stations of Delhi. Additionally, UAPI Index has been calculated to assess the intensity of particulate pollution. The daily, monthly, and annual variations in the trends of PM10, PM2.5, and UAPI index along with related meteorological parameters have been analyzed. Particulate pollution peaked majorly during two seasons, i.e., summer and winter. The highest concentration of PM10 was observed to be 426.77 µg/m3 while that of PM2.5 was observed to be 301.91 µg/m3 in January 2019 for traffic-affected regions. During winters, higher PM2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM10 concentrations led to an increment in pollution episodes during summers over most of the sites in Delhi. The UAPI index was found to be declining in 2020 over traffic affected regions (77.92 and 27.22 for 2019 and 2020, respectively) as well as in the background regions (64.91 and 19.80 for 2019 and 2020, respectively) of Delhi. Low traffic intensity and reduced pollutant emission could have been responsible for the reduction of UAPI intensity in the year 2020. The result indicates that lockdown implemented to control the COVID-19 outbreak led to an unexpected decrease in the PM10 pollution over Delhi.

Preliminary Results of COVID-19 Restriction Measures on the Air Pollution Levels in the City Center of Athens, Greece

COVID-19 is evolving into one of the worst pandemics in recent history. The lockdown measures implemented worldwide to slow the spread of the COVID-19 pandemic have caused an unprecedented reduction in global economic activity. Strict lockdown measures came into force in Greece from March 23th 2020. This study aims to assess the changes in air pollution levels during the restriction measures in Athens, the city with the most COVID-19 cases in the whole country. Measurements in a central location during the lockdown (24/03/2020 -07/04/2020) were compared with levels during the pre-lockdown (19/02/2020 -11/03/2020) period. Urban air pollution markedly decreased but with substantial differences among pollutants. The most significant impact during the lockdown period was observed for the concentrations of carbon monoxide (CO) and nitrogen oxides (NOx) with reduction percentages of -47% and - 35%, respectively, compared to the pre-lockdown period. These air pollutants are mainly related to traffic emissions. A lower reduction was recorded for coarse particulate matters (PMio) (-24%), probably due to the existence of other local sources of emission along with secondary formation. Nevertheless, this result must be further examined in order to be interpreted. Additionally, meteorological parameters such as wind speed found to play a key role on the results as most air pollutants were negatively correlated with higher air velocities. The scope of this study is to provide short term air quality results to the existing literature, in order to enhance decision making on life quality improvement in respect to the urban environment. © 2022 American Institute of Physics Inc.. All rights reserved.

A decade of CO2 flux measured by the eddy covariance method including the COVID-19 pandemic period in an urban center in Sakai, Japan.

Cities constitute an important source of greenhouse gases, but few results originating from long-term, direct CO2 emission monitoring efforts have been reported. In this study, CO2 emissions were quasi-continuously measured in an urban center in Sakai, Osaka, Japan by the eddy covariance method from 2010 to 2021. Long-term CO2 emissions reached 22.2 ± 2.0 kg CO2 m-2 yr-1 from 2010 to 2019 (± denotes the standard deviation) in the western sector from the tower representing the densely built-up area. Throughout the decade, the annual CO2 emissions remained stable. According to an emission inventory, traffic emissions represented the major source of CO2 emissions within the flux footprint. The interannual variations in the annual CO2 flux were positively correlated with the mean annual traffic counts at two highway entrances and exits. The CO2 emissions decreased suddenly, by 32% ± 3.1%, in April and May 2020 during the period in which the first state of emergency associated with COVID-19 was declared. The annual CO2 emissions also decreased by 25% ± 3.1% in 2020. Direct long-term observations of CO2 emissions comprise a useful tool to monitor future emission reductions and sudden disruptions in emissions, such as those beginning in 2020 during the COVID-19 pandemic.

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts.

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO2 emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO2 fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

Traffic restrictions during COVID-19 lockdown improve air quality and reduce metal biodeposition in tree leaves.

The coronavirus disease (COVID-19) has had a great global impact on human health, the life of people, and economies all over the world. However, in general, COVID-19´s effect on air quality has been positive due to the restrictions on social and economic activity. This study aimed to assess the impact on air quality and metal deposition of actions taken to reduce mobility in 2020 in two different urban locations. For this purpose, we analysed air pollution (NO2, NO, NOx, SO2, CO, PM10, O3) and metal accumulation in leaves of Tilia cordata collected from April to September 2020 in two cities in northern Spain (Pamplona-PA and San Sebastián-SS). We compared their values with data from the previous year (2019) (in which there were no mobility restrictions) obtained under an identical experimental design. We found that metal accumulation was mostly lower during 2020 (compared with 2019), and lockdown caused significant reductions in urban air pollution. Nitrogen oxides decreased by 33%-44%, CO by 24%-38%, and PM10 by 16%-24%. The contents of traffic-related metals were significantly reduced in both studied cities. More specifically, significant decreases in metals related to tyre and brake wear (Zn, Fe, and Cu) and road dust resuspension (Al, Ti, Fe, Mn, and Ca) were observed. With these results, we conclude that the main reason for the improvement in urban air pollutants and metals was the reduction in the use of cars due to COVID-19 lockdown. In addition, we offer some evidence indicating the suitability of T. cordata leaves as a tool for biomonitoring metal accumulation. This information is relevant for future use by the scientific community and policy makers to implement measures to reduce traffic air pollution in urban areas and to improve environmental and human health.

Impact of Corona Virus Stay-at-Home Policies on Traffic Emissions and Ambient Pollutant Concentrations in Ghana, West Africa

The objective of this study is to determine how policies for stay-at-home (lockdown) and phases of easing the lockdown, implemented by the Government of Ghana to slow the spread of COVID-19, impacted traffic emissions and ambient concentrations of particulate matter (PM10, PM2.5). Monthly data was collected from January 2020 to June 2020 from four roadside monitoring locations using mini vol air samplers. High-volume ambient samplers were used to collect PM data at two permanent (industrial and residential) locations. Monthly concentrations were presented in tables over the six-month period. Results showed that PM2.5 concentrations decreased over Greater Accra in the month of April during the initial lockdown, when only essential workers went to work, and increased thereafter. Compared with 2019 data, the PM2.5 concentrations of roadside monitoring points at Kaneshie First Light, Shangri-la, Tantra Hill and Amasaman were lowered by 45.5%, 46.7%, 82.4%, 72.7%, respectively. This was consistent with the measured reductions in mobility during the lock-down. However, PM10 concentrations were higher at the same four roadside monitoring points and industrial monitoring points near the power plant during the lockdown compared to the same period in 2019. This increase may have been due to residential biomass burning during stay-at-home orders, or increased electricity production to support home activity. In conclusion, worldwide researches collected pollution data using remote sensing and satellite where as in this study conducted in Ghana pollution data was collected using ground-level monitors. © Engineered Science Publisher LLC 2022

NOx and CO Fluctuations in a Busy Street Canyon

Busy street canyons can have a large flow of vehicles and reduced air exchange and wind speeds at street level, exposing pedestrians to high pollutant concentrations. The airflow tended to move with vehicles along the canyon and the 1-s concentrations of NO, NO2 and CO were highly skewed close to the road and more normally distributed at sensors some metres above the road. The pollutants were more autocorrelated at these elevated sensors, suggesting a less variable concentration away from traffic in the areas of low turbulence. The kerbside concentrations also showed cyclic changes approximating nearby traffic signal timing. The cross-correlation between the concentration measurements suggested that the variation moved at vehicle speed along the canyon, but slower vertically. The concentrations of NOx and CO were slightly higher at wind speeds of under a metre per second. The local ozone concentrations had little effect on the proportion of NOx present as NO2. Pedestrians on the roadside would be unlikely to exceed the USEPA hourly guideline value for NO2 of 100 ppb. Across the campaign period, 100 individual minutes exceeded the guidelines, though the effect of short-term, high-concentration exposures is not well understood. Tram stops at the carriageway divider are places where longer exposures to higher levels of traffic-associated pollutants are possible.

The impact of coal combustion, nitrous oxide emissions, and traffic emissions on COVID-19 cases: a Markov-switching approach.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread to more than 200 countries with a current case fatality ratio (CFR) of more than 2% globally. The concentration of air pollutants is considered a critical factor responsible for transmitting coronavirus disease among the masses. The photochemical process and coal combustions create respiratory disorders that lead to coronavirus disease. Based on the crucial fact, the study evaluated the impact of nitrous oxide (N2O) emissions, coal combustion, and traffic emissions on COVID-19 cases in a panel of 39 most affected countries of the world. These three air pollution factors are considered to form a lethal smog that negatively affects the patient's respiratory system, leading to increased susceptibility to coronavirus worldwide. The study used the Markov two-step switching regime regression model for obtaining parameter estimates. In contrast, an innovation accounting matrix is used to assess smog factors' intensity on possibly increasing coronavirus cases over time. The results show that N2O emissions, coal combustion, and traffic emissions increase COVID-19 cases in regime-1. On the other hand, N2O emissions significantly increase coronavirus cases in regime-2. The innovation accounting matrix shows that N2O emissions would likely have a more significant share of increasing coronavirus cases with a variance of 33.902%, followed by coal combustion (i.e., 6.643%) and traffic emissions (i.e., 2.008%) over the time horizon. The study concludes that air quality levels should be maintained through stringent environmental policies, such as carbon pricing, sustainable urban planning, green technology advancement, renewable fuels, and pollution less accessible vehicles. All these measures would likely decrease coronavirus cases worldwide.

From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO2, O3, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO2 and particulate matter with aerodynamic diameters <2.5 µm by -30.1% and -17.5%, respectively, but a 5.7% increase in O3 Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO2 levels.

Analysis of lockdown for CoViD-19 impact on NO2 in London, Milan and Paris: What lesson can be learnt?

Nitrogen dioxide (NO2) can have harmful effects on human health and can act as a precursor for the formation of other air pollutants in urban environment such as secondary PM2.5 and ozone. The lockdown measures for CoViD-19 allowed to simulate on a large scale the massive and prolonged reduction of road traffic (the main source for NO2 in urban environment). This work aims to selectively assess the maximum impact that total traffic blocking measures can have on NO2. For this reason, three megacities (London, Milan and Paris) were chosen which had similar characteristics in terms of climatic conditions, population, policies of urban traffic management and lockdown measures. 52 air quality control units have been used to compare data measured in lockdown and in the same periods of previous years, highlighting a significant decrease in NO2 concentration due to traffic (London: 71.1 % - 80.8 %; Milan: 8.6 % - 42.4 %; Paris: 65.7 % - 79.8 %). In 2020 the contribution of traffic in London, Milan and Paris dropped to 3.3 ± 1.3 µg m-3, 6.1 ± 0.8 µg m-3, and 13.4 ± 1.5 µg m-3, respectively. Despite the significant reduction in the NO2 concentration, in UT stations average NO2 concentrations higher than 40 µg m-3 were registered for several days. In order to reduce the pollution, the limitation of road traffic could be not enough, but a vision also aimed at rethink the vehicles and their polluting effects should be developed.

Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India.

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM2.5 and PM10) and gaseous pollutants (NO2, O3, CO, and SO2) during lockdown (25th March - 3rd May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM2.5, PM10, NO2, and CO has been found in all the regions during the lockdown. SO2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM2.5, PM10, and NO2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O3 has increased over IGP due to less O3 loss. The most significant reduction (∼40-60%) was found in PM2.5 and PM10. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM2.5, PM10, NO2, and enhancement in O3 was proportional to the population density. Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.

Changes in air quality related to the control of coronavirus in China: Implications for traffic and industrial emissions.

Measures taken to control the disease (Covid-19) caused by the novel coronavirus dramatically reduced the number of vehicles on the road and diminished factory production. For this study, changes in the air quality index (AQI) and the concentrations of six air pollutants (PM2.5, PM10, CO, SO2, NO2, and O3) were evaluated during the Covid-19 control period in northern China. Overall, the air quality improved, most likely due to reduced emissions from the transportation and secondary industrial sectors. Specifically, the transportation sector was linked to the NO2 emission reductions, while lower emissions from secondary industries were the major cause for the reductions of PM2.5 and CO. The reduction in SO2 concentrations was only linked to the industrial sector. However, the reductions in emissions did not fully eliminate air pollution, and O3 actually increased, possibly because lower fine particle loadings led to less scavenging of HO2 and as a result greater O3 production. These results also highlight need to control emissions from the residential sector.