How mobility restrictions policy and atmospheric conditions impacted air quality in the State of São Paulo during the COVID-19 outbreak

Elemental composition of atmospheric PM10 during COVID-19 lockdown and recovery periods in Moscow (April-July 2020)

Changes in the concentrations of PM10-bound potentially toxic elements (PTEs) during the COVID-19 lockdown period and after the revocation of restrictions were analyzed using the data received at the Aerosol Complex of Moscow State University in April-July 2020. During the lockdown, the input of biomass combustion products enriched in PTEs from the Moscow region hindered the decrease in pollutant concentrations. After the introduction of the self-isolation regime, lower concentrations of most PTEs occurred due to the decrease in anthropogenic activity and the rainy meteorological conditions. After the revocation of restrictive measures, the PTE concentrations began to increase. Multivariate statistical analysis (APCA-MLR) identified the main sources of atmospheric pollutants as urban dust, non-exhaust traffic emissions, and combustion and exhaust traffic emissions. PM10 particles were significantly enriched with Sb, Cd, Sn, Bi, S, Pb, Cu, Mo, and Zn. The total non-carcinogenic and carcinogenic risks, calculated according to the U.S. EPA model, decreased by 24% and 23% during the lockdown; after the removal of restrictions, they increased by 61% and 72%, respectively. The study provides insight into the PTE concentrations and their main sources at different levels of anthropogenic impact.

Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak

Atmospheric pollutant data retrieved through satellite sensors are continually used to assess changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several studies started to use satellite measurements to evaluate changes in air quality in many different regions worldwide. However, although satellite data is continuously validated, it is known that its accuracy may vary between monitored areas, requiring regionalized quality assessments. Thus, this study aimed to evaluate whether satellites could measure changes in the air quality of the state of São Paulo, Brazil, during the COVID-19 outbreak; and to verify the relationship between satellite-based data [Tropospheric NO₂ column density and Aerosol Optical Depth (AOD)] and ground-based concentrations [NO₂ and particulate material (PM; coarse: PM₁₀ and fine: PM_2.5)]. For this purpose, tropospheric NO₂ obtained from the TROPOMI sensor and AOD retrieved from MODIS sensor data by using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm were compared with concentrations obtained from 50 automatic ground monitoring stations. The results showed low correlations between PM and AOD. For PM₁₀, most stations showed correlations lower than 0.2, which were not significant. The results for PM_2.5 were similar, but some stations showed good correlations for specific periods (before or during the COVID-19 outbreak). Satellite-based Tropospheric NO₂ proved to be a good predictor for NO₂ concentrations at ground level. Considering all stations with NO₂ measurements, correlations >0.6 were observed, reaching 0.8 for specific stations and periods. In general, it was observed that regions with a more industrialized profile had the best correlations, in contrast with rural areas. In addition, it was observed about 57% reductions in tropospheric NO₂ throughout the state of São Paulo during the COVID-19 outbreak. Variations in air pollutants were linked to the region economic vocation, since there were reductions in industrialized areas (at least 50% of the industrialized areas showed >20% decrease in NO₂) and increases in areas with farming and livestock characteristics (about 70% of those areas showed increase in NO₂). Our results demonstrate that Tropospheric NO₂ column densities can serve as good predictors of NO₂ concentrations at ground level. For MAIAC-AOD, a weak relationship was observed, requiring the evaluation of other possible predictors to describe the relationship with PM. Thus, it is concluded that regionalized assessment of satellite data accuracy is essential for assertive estimates on a regional/local level. Good quality information retrieved at specific polluted areas does not assure a worldwide use of remote sensor data.

2030 Agenda: discussion on Brazilian priorities facing air pollution and climate change challenges

The advance of human activities in a disorderly way has accelerated in recent decades, intensifying the environmental impacts directly linked to these practices. The atmosphere, essential for the maintenance of life, is increasingly saturated with pollutants, offering risks to practically all the inhabitants of the planet, a process that, in addition to causing illness and early mortality, is related to serious financial losses (including in the production of goods), dangerous temperature increase and severe natural disasters. Although this perception is not recent, the global initiative to control the different mechanisms that trigger the commitment of biodiversity and irreversible climate changes arising from pollution is still very incipient, given that global initiatives on the subject emerged just over 50 years ago. Brazil is a territory that centralizes many of these discussions, as it still faces both political and economic obstacles in achieving a sustainable growth model as it was agreed through the United Nations 2030 Agenda. Even though there is little time left for the completion of these goals, much remains to be done, and despite the fulfillment of this deadline, the works will certainly need to be extended for much longer until an effective reorientation of consciousness occurs. Scientific researches and discussions are fundamental tools to the understanding of issues still little explored in this field.

The Apple Mobility Trends Data in Human Mobility Patterns during Restrictions and Prediction of COVID-19: A Systematic Review and Meta-Analysis

The objective of this systematic review with PRISMA guidelines is to discover how population movement information has epidemiological implications for the spread of COVID-19. In November 2022, the Web of Science and Scopus databases were searched for relevant reports for the review. The inclusion criteria are: (1) the study uses data from Apple Mobility Trends Reports, (2) the context of the study is about COVID-19 mobility patterns, and (3) the report is published in a peer-reviewed venue in the form of an article or conference paper in English. The review included 35 studies in the period of 2020-2022. The main strategy used for data extraction in this review is a matrix proposal to present each study from a perspective of research objective and outcome, study context, country, time span, and conducted research method. We conclude by pointing out that these data are not often used in studies and it is better to study a single country instead of doing multiple-country research. We propose topic classifications for the context of the studies as transmission rate, transport policy, air quality, re-increased activities, economic activities, and financial markets.

Atmospheric Formaldehyde Monitored by TROPOMI Satellite Instrument throughout 2020 over São Paulo State, Brazil

We aimed to study the daily formaldehyde (HCHO) columns over urban and forested areas in São Paulo State, Brazil, from rhe TROPOMI spectrometer onboard the Sentinel-5P satellite during 2020. Nineteen specific areas were defined in four regions: 3 areas in each of two preserved Atlantic Forests (PEMD and PETAR), 3 in a sugarcane growing region (NERG) and 10 in the Metropolitan Area of São Paulo (MASP), among which 2 areas are in the Morro Grande reserve, which is a significant remnant of Atlantic Forest outside the densely urbanized area of MASP. An analysis of variance and Tukey’s test showed that the mean annual columns over the Morro Grande reserve (1.69±1.05×10−4 mol/m² and 1.73±1.07×10−4 mol/m²) presented greater statistical similarity with the forest and rural areas of the state (<1.70×10−4 mol/m²) than with MASP (>2.00×10−4 mol/m²), indicating few effects from megacity anthropogenic emissions. Case studies addressing selected days in 2020 showed that fires in and around the state were related to episodes of maximum density of HCHO columns. The results showed significant seasonality, with lower concentrations during summer (wet season) and higher concentrations during winter and spring (dry and transition dry–wet seasons).

Empirical evidence shows that air quality changes during COVID-19 pandemic lockdown in Jakarta, Indonesia are due to seasonal variation, not restricted movements

Implementing a lockdown or activity restriction to reduce the spread of COVID-19 cases is assumed to improve air quality in highly populated cities. The effect of lockdown on air quality is often quantified by comparing pre- and during-lockdown air quality parameters without considering confounding meteorological factors. We demonstrated that rainfall can explain changes in PM10 and PM2.5 parameters in the city of Jakarta during lockdown. This article shows that comparing air quality pre- and during lockdown is misleading. Variables affecting air quality such as meteorological variables should be taken into account. The air quality in Jakarta as measured by PM10 and PM2.5 did not change significantly during the lockdown period after removing the seasonal effect.

Heterogeneous impacts of mobility restrictions on air quality in the State of Sao Paulo during the COVID-19 pandemic

Air quality in the State of Sao Paulo was evaluated during the first general State plan of mobility restrictions due to the COVID-19 pandemic (24th March to May 31, 2020). Nitrogen dioxide (NO₂), ozone (O₃), particulate matter PM₁₀ and PM_2.5 and sulphur dioxide (SO₂) concentrations were assessed in cities of the Sao Paulo State with a monitoring station and compared to historical data. Linear regression models were built to investigate the relationship between the isolation of the population - determined using mobile phone monitoring data - and the concentration of each pollutant during the studied period. Although the reduction of pollutants such as NO₂, SO₂ and PM_2.5 is very clear, the economic and climatic characteristics of each region were decisive in the general behaviour of O₃ and PM₁₀. It was not possible to establish a correlation between the pollutants and the isolation index, partly due to the lack of data, partly due to the compliance of the population to those measurements, which was variable over time. Another important limitation factor was the absence of data related to the pollutants of interest in many of the stations. However, the isolation measures carried out in the State opened the opportunity to individually assess the air quality measurements in each of the stations, enabling an understanding that will allow in the future the design of air quality policies together with local sanitary policies.

Spatial analysis of socio-economic factors and their relationship with the cases of COVID-19 in Pernambuco, Brazil

OBJECTIVES

To analyse the spatial distribution of rates of COVID-19 cases and its association with socio-economic conditions in the state of Pernambuco, Brazil.

METHODS

Autocorrelation (Moran index) and spatial association (Geographically weighted regression) models were used to explain the interrelationships between municipalities and the possible effects of socio-economic factors on rates.

RESULTS

Two isolated clusters were revealed in the inner part of the state in sparsely inhabited municipalities. The spatial model (Geographically Weighted Regression) was able to explain 50% of the variations in COVID-19 cases. The variables proportion of people with low income, percentage of rented homes, percentage of families in social programs, Gini index and running water had the greatest explanatory power for the increase in infection by COVID-19.

CONCLUSIONS

Our results provide important information on socio-economic factors related to the spread of COVID-19 and can serve as a basis for decision-making in similar circumstances.

Has COVID-19 Lockdown Affected on Air Quality?—Different Time Scale Case Study in Wrocław, Poland

Due to the COVID-19 pandemic, there are series of negative economic consequences, however, in limiting mobility and reducing the number of vehicles, positive effects can also be observed, i.e., improvement of air quality. The paper presents an analysis of air quality measured by concentrations of NO2, NOx and PM2.5 during the most restrictive lockdown from 10 March to 31 May 2020 on the case of Wrocław. The results were compared with the reference period—2016–2019. A significant reduction in traffic volume was identified, on average by 26.3%. The greatest reduction in the concentration of NO2 and NOx was recorded at the station farthest from the city center, characterized by the lowest concentrations: 20.1% and 22.4%. Lower reduction in the average concentrations of NO2 and NOx was recorded at the municipal station (7.9% and 7.7%) and the communication station (6.7% and 10.2%). Concentrations of PMs in 2020 were on average 15% and 13.4% lower than in the reference period for the traffic station and the background station. The long-term impact of the lockdown on air quality was also examined. The analysis of the concentrations of the pollutants throughout 2020, and in the analyzed period of 2021, indicated that the reduction of concentrations and the improvement in air quality caused by the restrictions should be considered as a temporary anomaly, without affecting long-term changes and trends.

Assessment of COVID-19 pandemic effects on ship pollutant emissions in major international seaports

This study aims to investigate the coronavirus disease (COVID-19) pandemic effects and associated restrictive rules on ship activities and pollutant emissions (CO2, SOX, NOX, PM, CO, CH4) in four major seaports, namely the Ports of Singapore, Long Beach, Los Angeles, and Hamburg. We used 2019 as the baseline year to show the business-as-usual emission and compared with the estimated quantity during the July 2020-July 2021 pandemic period. We also project future ship emissions from August 2021-August 2022 to illustrate two potential port congestion scenarios due to COVID-19. The results show that the ship emissions in all four ports generally increased by an average of 79% because of the prolonged turnaround time in port. Importantly, majority of ship emissions occurred during the extended hoteling time at berth and anchorage areas as longer operational times were needed due to pandemic-related delays, with increases ranging from 27 to 123% in the total emissions across ports. The most affected shipping segments were the container ships and dry bulk carriers which the total emissions of all pollutants increased by an average of 94-142% compared with 2019. Overall, the results of this study provide a comprehensive review of the ship emission outlook amid the pandemic uncertainty.