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: PM2.5)]. 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 PM2.5 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.

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

Mobility restrictions are among actions to prevent the spread of the COVID-19 pandemic and have been pointed as reasons for improving air quality, especially in large cities. However, it is crucial to assess the impact of atmospheric conditions on air quality and air pollutant dispersion in the face of the potential variability of all sources. In this study, the impact of mobility restrictions on the air quality was analyzed for the most populous Brazilian State, São Paulo, severely impacted by COVID-19. Ground-based air quality data (PM10, PM2.5, CO, SO2, NOx, NO2, NO, and O3) were used from 50 automatic air quality monitoring stations to evaluate the changes in concentrations before (January 01 - March 25) and during the partial quarantine (March 16 - June 30). Rainfall, fires, and daily cell phone mobility data were also used as supplementary information to the analyses. The Mann-Whitney U test was used to assess the heterogeneity of the air quality data during and before mobility restrictions. In general, the results demonstrated no substantial improvements in air quality for most of the pollutants when comparing before and during restrictions periods. Besides, when the analyzed period of 2020 is compared with the year 2019, there is no significant air quality improvement in the São Paulo State. However, special attention should be given to the Metropolitan Area of São Paulo (MASP), due to the vast population residing in this area and exposed to air pollution. The region reached an average decrease of 29% in CO, 28% in NOx, 40% in NO, 19% in SO2, 15% in PM2.5, and 8% in PM10 concentrations during the mobility restrictions period compared to the same period in 2019. The only pollutant that showed an increase in concentration was ozone, with a 20% increase compared to 2019 during the mobility restrictions period. Before the mobility restrictions period, the region reached an average decrease of 30% in CO, 39% in NOx, 63% in NO, 12% in SO2, 23% in PM2.5, 18% in PM10, and 16% in O3 concentrations when compared to the same period in 2019. On the other hand, Cubatão, a highly industrialized area, showed statistically significant increases above 20% for most monitored pollutants in both periods of 2020 compared to 2019. This study reinforces that the main driving force of pollutant concentration variability is the dynamics of the atmosphere at its various time scales. An abnormal rainy season, with above average rainfall before the restrictions and below average after it, generated a scenario in which the probable significant reductions in emissions did not substantially affect the concentration of pollutants.

p53 genetic alterations, protein expression and autoantibodies in human colorectal carcinoma: A comparative study.

This study investigated a total number of 120 colorectal malignant tumor tissues by applying a new quantitative luminometric assay (LIA)-mat, immunohistochemistry (IHC) (n=100), PCR/SSCP (n=42), and sequencing (n=7). Sera were collected from 235 patients suffering from colorectal carcinoma in addition to 195 healthy individuals as a control group. Manual ELISA kit was developed to detect p53 autoantibodies in the sera of those patients. Our data demonstrated that the LIA-mat yields reliable estimates of p53 expression in soluble cell extracts as compared with results obtained by immunohistochemistry which showed positive immunostaining in 63% of the studied cases. Using a cut-off value of 1.8 ng/mg protein, 65 tumors out of 120 (54%) were classified to be positive by LIA-mat, manifesting protein overexpression, while 22 out of 42 (52%) tumor samples showed p53 gene alteration when applying single strand conformation polymorphism (SSCP) analysis on polymerase chain reaction products. In tumor samples without a p53 gene alteration, the median soluble p53 protein level was 4.3 ng/mg protein, whereas the median p53 protein level for tumor samples with p53 gene alteration was 7.5 times higher. Despite a significant correlation between the outcome of LIA and SSCP, a disagreement was found in 30% of cases. We found no significant correlation between p53 protein overexpression and clinicopathological findings except for distant metastasis (p=0.33), indicating p53 immunoreactivity to be an independent prognostic factor. Our data showed that 18% of patients suffering from colorectal cancer developed autoantibodies against p53 in their sera which might be an early indicator for tumor development and distant metastasis.