PMC:7547912 / 17843-19002 JSONTXT

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T17","span":{"begin":1060,"end":1068},"obj":"Disease"}],"attributes":[{"id":"A17","pred":"mondo_id","subj":"T17","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"}],"text":"Site 1—ITO, Delhi\nAt this site, the perfect positive correlation was observed between AQI and PM2.5, a strong positive correlation between AQI-PM10 and PM2.5-PM10, whereas a negative correlation was observed for ozone with AQI and other pollutants. The correlation coefficient between AQI-PM2.5, AQI-PM10, and PM2.5-PM10 was found as 0.98, 0.82, and 0.77 respectively, showing a significantly higher positive relationship. This indicate the changes in PM2.5 and PM10 concentrations have a great influence on AQI content; i.e., an increase in their concentration will directly elevate the air quality index. Besides, AQI-ozone, PM2.5-ozone, and PM10-ozone confirmed low negatively correlated variables, i.e., − 0.31, − 0.38, and − 0.18 respectively indicating the higher values of AQI, PM2.5, and PM10 will lower down the ozone concentration. A feeble correlation exists between AQI-NH3 (0.46), AQI-NO2 (0.38), AQI-SO2 (0.28), and AQI-CO (0.11) showing mild effect on AQI (Fig. 5 (a)).\nFig. 5 Pearson’s correlation heatmap for air pollutants during the pre and COVID-19 pandemic confinement, 2020 among populous sites of four major metropolitan cities in India"}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T68","span":{"begin":101,"end":102},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T69","span":{"begin":172,"end":173},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T70","span":{"begin":377,"end":378},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T71","span":{"begin":487,"end":488},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T72","span":{"begin":842,"end":843},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T73","span":{"begin":980,"end":981},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"Site 1—ITO, Delhi\nAt this site, the perfect positive correlation was observed between AQI and PM2.5, a strong positive correlation between AQI-PM10 and PM2.5-PM10, whereas a negative correlation was observed for ozone with AQI and other pollutants. The correlation coefficient between AQI-PM2.5, AQI-PM10, and PM2.5-PM10 was found as 0.98, 0.82, and 0.77 respectively, showing a significantly higher positive relationship. This indicate the changes in PM2.5 and PM10 concentrations have a great influence on AQI content; i.e., an increase in their concentration will directly elevate the air quality index. Besides, AQI-ozone, PM2.5-ozone, and PM10-ozone confirmed low negatively correlated variables, i.e., − 0.31, − 0.38, and − 0.18 respectively indicating the higher values of AQI, PM2.5, and PM10 will lower down the ozone concentration. A feeble correlation exists between AQI-NH3 (0.46), AQI-NO2 (0.38), AQI-SO2 (0.28), and AQI-CO (0.11) showing mild effect on AQI (Fig. 5 (a)).\nFig. 5 Pearson’s correlation heatmap for air pollutants during the pre and COVID-19 pandemic confinement, 2020 among populous sites of four major metropolitan cities in India"}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T103","span":{"begin":212,"end":217},"obj":"Chemical"},{"id":"T104","span":{"begin":620,"end":625},"obj":"Chemical"},{"id":"T105","span":{"begin":633,"end":638},"obj":"Chemical"},{"id":"T106","span":{"begin":649,"end":654},"obj":"Chemical"},{"id":"T107","span":{"begin":821,"end":826},"obj":"Chemical"},{"id":"T108","span":{"begin":882,"end":885},"obj":"Chemical"},{"id":"T109","span":{"begin":898,"end":901},"obj":"Chemical"},{"id":"T111","span":{"begin":914,"end":917},"obj":"Chemical"},{"id":"T112","span":{"begin":934,"end":936},"obj":"Chemical"}],"attributes":[{"id":"A103","pred":"chebi_id","subj":"T103","obj":"http://purl.obolibrary.org/obo/CHEBI_25812"},{"id":"A104","pred":"chebi_id","subj":"T104","obj":"http://purl.obolibrary.org/obo/CHEBI_25812"},{"id":"A105","pred":"chebi_id","subj":"T105","obj":"http://purl.obolibrary.org/obo/CHEBI_25812"},{"id":"A106","pred":"chebi_id","subj":"T106","obj":"http://purl.obolibrary.org/obo/CHEBI_25812"},{"id":"A107","pred":"chebi_id","subj":"T107","obj":"http://purl.obolibrary.org/obo/CHEBI_25812"},{"id":"A108","pred":"chebi_id","subj":"T108","obj":"http://purl.obolibrary.org/obo/CHEBI_16134"},{"id":"A109","pred":"chebi_id","subj":"T109","obj":"http://purl.obolibrary.org/obo/CHEBI_16301"},{"id":"A110","pred":"chebi_id","subj":"T109","obj":"http://purl.obolibrary.org/obo/CHEBI_33101"},{"id":"A111","pred":"chebi_id","subj":"T111","obj":"http://purl.obolibrary.org/obo/CHEBI_18422"},{"id":"A112","pred":"chebi_id","subj":"T112","obj":"http://purl.obolibrary.org/obo/CHEBI_17245"}],"text":"Site 1—ITO, Delhi\nAt this site, the perfect positive correlation was observed between AQI and PM2.5, a strong positive correlation between AQI-PM10 and PM2.5-PM10, whereas a negative correlation was observed for ozone with AQI and other pollutants. The correlation coefficient between AQI-PM2.5, AQI-PM10, and PM2.5-PM10 was found as 0.98, 0.82, and 0.77 respectively, showing a significantly higher positive relationship. This indicate the changes in PM2.5 and PM10 concentrations have a great influence on AQI content; i.e., an increase in their concentration will directly elevate the air quality index. Besides, AQI-ozone, PM2.5-ozone, and PM10-ozone confirmed low negatively correlated variables, i.e., − 0.31, − 0.38, and − 0.18 respectively indicating the higher values of AQI, PM2.5, and PM10 will lower down the ozone concentration. A feeble correlation exists between AQI-NH3 (0.46), AQI-NO2 (0.38), AQI-SO2 (0.28), and AQI-CO (0.11) showing mild effect on AQI (Fig. 5 (a)).\nFig. 5 Pearson’s correlation heatmap for air pollutants during the pre and COVID-19 pandemic confinement, 2020 among populous sites of four major metropolitan cities in India"}

{"project":"LitCovid-PubTator","denotations":[{"id":"79","span":{"begin":1060,"end":1068},"obj":"Disease"},{"id":"92","span":{"begin":139,"end":142},"obj":"Chemical"},{"id":"93","span":{"begin":212,"end":217},"obj":"Chemical"},{"id":"94","span":{"begin":462,"end":466},"obj":"Chemical"},{"id":"95","span":{"begin":616,"end":619},"obj":"Chemical"},{"id":"96","span":{"begin":620,"end":625},"obj":"Chemical"},{"id":"97","span":{"begin":627,"end":632},"obj":"Chemical"},{"id":"98","span":{"begin":633,"end":638},"obj":"Chemical"},{"id":"99","span":{"begin":644,"end":648},"obj":"Chemical"},{"id":"100","span":{"begin":649,"end":654},"obj":"Chemical"},{"id":"101","span":{"begin":785,"end":788},"obj":"Chemical"},{"id":"102","span":{"begin":796,"end":800},"obj":"Chemical"},{"id":"103","span":{"begin":821,"end":826},"obj":"Chemical"}],"attributes":[{"id":"A79","pred":"tao:has_database_id","subj":"79","obj":"MESH:C000657245"},{"id":"A93","pred":"tao:has_database_id","subj":"93","obj":"MESH:D010126"},{"id":"A96","pred":"tao:has_database_id","subj":"96","obj":"MESH:D010126"},{"id":"A98","pred":"tao:has_database_id","subj":"98","obj":"MESH:D010126"},{"id":"A100","pred":"tao:has_database_id","subj":"100","obj":"MESH:D010126"},{"id":"A103","pred":"tao:has_database_id","subj":"103","obj":"MESH:D010126"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Site 1—ITO, Delhi\nAt this site, the perfect positive correlation was observed between AQI and PM2.5, a strong positive correlation between AQI-PM10 and PM2.5-PM10, whereas a negative correlation was observed for ozone with AQI and other pollutants. The correlation coefficient between AQI-PM2.5, AQI-PM10, and PM2.5-PM10 was found as 0.98, 0.82, and 0.77 respectively, showing a significantly higher positive relationship. This indicate the changes in PM2.5 and PM10 concentrations have a great influence on AQI content; i.e., an increase in their concentration will directly elevate the air quality index. Besides, AQI-ozone, PM2.5-ozone, and PM10-ozone confirmed low negatively correlated variables, i.e., − 0.31, − 0.38, and − 0.18 respectively indicating the higher values of AQI, PM2.5, and PM10 will lower down the ozone concentration. A feeble correlation exists between AQI-NH3 (0.46), AQI-NO2 (0.38), AQI-SO2 (0.28), and AQI-CO (0.11) showing mild effect on AQI (Fig. 5 (a)).\nFig. 5 Pearson’s correlation heatmap for air pollutants during the pre and COVID-19 pandemic confinement, 2020 among populous sites of four major metropolitan cities in India"}

{"project":"LitCovid-sentences","denotations":[{"id":"T109","span":{"begin":0,"end":17},"obj":"Sentence"},{"id":"T110","span":{"begin":18,"end":248},"obj":"Sentence"},{"id":"T111","span":{"begin":249,"end":422},"obj":"Sentence"},{"id":"T112","span":{"begin":423,"end":606},"obj":"Sentence"},{"id":"T113","span":{"begin":607,"end":841},"obj":"Sentence"},{"id":"T114","span":{"begin":842,"end":984},"obj":"Sentence"},{"id":"T115","span":{"begin":985,"end":1159},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Site 1—ITO, Delhi\nAt this site, the perfect positive correlation was observed between AQI and PM2.5, a strong positive correlation between AQI-PM10 and PM2.5-PM10, whereas a negative correlation was observed for ozone with AQI and other pollutants. The correlation coefficient between AQI-PM2.5, AQI-PM10, and PM2.5-PM10 was found as 0.98, 0.82, and 0.77 respectively, showing a significantly higher positive relationship. This indicate the changes in PM2.5 and PM10 concentrations have a great influence on AQI content; i.e., an increase in their concentration will directly elevate the air quality index. Besides, AQI-ozone, PM2.5-ozone, and PM10-ozone confirmed low negatively correlated variables, i.e., − 0.31, − 0.38, and − 0.18 respectively indicating the higher values of AQI, PM2.5, and PM10 will lower down the ozone concentration. A feeble correlation exists between AQI-NH3 (0.46), AQI-NO2 (0.38), AQI-SO2 (0.28), and AQI-CO (0.11) showing mild effect on AQI (Fig. 5 (a)).\nFig. 5 Pearson’s correlation heatmap for air pollutants during the pre and COVID-19 pandemic confinement, 2020 among populous sites of four major metropolitan cities in India"}