| Literature DB >> 32822915 |
Juan F Mendez-Espinosa1, Nestor Y Rojas2, Jorge Vargas2, Jorge E Pachón3, Luis C Belalcazar2, Omar Ramírez4.
Abstract
Lockdown measures led to air pollution decrease in several countries around the world such as China and India, whereas other regions experimented an increase in pollutant concentrations. Northern South America (NSA) was one of those areas where pollution changed during lockdown due to high fire activity. This study aims to analyze, for the first time in NSA, the behavior of selected criteria air pollutants during the implementation of the SARS-CoV-2 lockdown in two high populated cities of the region: Bogotá and Medellín in Colombia. A set of tools including surface measurements, as well as satellite and modeled data were used. 24-hour average concentrations of PM10, PM2.5, and NO2 were collected from air quality stations for the lockdown period ranging from February 21 to June 30, 2020. The Copernicus Atmosphere Monitoring Service (CAMS) was used to analyze the fire flux OC as a biomass burning (BB) indicator, and tropospheric NO2 concentrations were retrieved from TROPOMI. The HYSPLIT model was used to analyze back trajectories and fire data were obtained from MODIS sensor measurements. Our analysis shows short-term background NO2, PM10, and PM2.5 concentration reductions of 60%, 44%, and 40%, respectively, for the strict lockdown; and 62%, 58%, and 69% for the relaxed lockdown. Corresponding long-term reductions were of 50%, 32%, and 9% for the strict lockdown; and 37%, 29%, and 19% for the relaxed lockdown. Regional BB increased PM2.5 concentrations by 20 μg/m3 during the strict lockdown, and the Saharan dust event increased PM10 concentrations up to 168 μg/m3 in Bogotá, and 104 μg/m3 in Medellín, bringing an additional risk of morbidity and mortality for population. Regional BB has several causes that need to be properly managed to benefit local air quality improvement plans. Future cleaner transport policies equivalent to reduced lockdown mobility could bring pollution close to WHO guidelines.Entities:
Keywords: Biomass burning; Lockdown; NO(2); Pandemic; Particulate matter; SARS-CoV-2
Year: 2020 PMID: 32822915 PMCID: PMC7418784 DOI: 10.1016/j.scitotenv.2020.141621
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963
Fig. 1Map of the NSA region, with a focus on the main cities located in the Colombian Andes.
Air quality monitoring stations. NA: Not available.
| City | Station | Type of station | Location | Background | Traffic | ||||
|---|---|---|---|---|---|---|---|---|---|
| PM10 | NO2 | PM2.5 | PM10 | NO2 | PM2.5 | ||||
| Bogotá | Centro de Alto Rendimiento | Urban background | 4.6585 | x | x | x | |||
| Las Ferias | Traffic | 4.6907 | x | x | x | ||||
| Medellín | Concejo de Itagüí | Suburban background | 6.1685 | x | NA | x | |||
| Estación Tráfico Centro | Traffic | 6.2525 | x | x | x | ||||
Average concentrations of PM10, PM2.5, and NO2 for the periods before lockdown (February 21 to March 19), strict lockdown (March 20 to April 26), and relaxed lockdown (April 27 to June 30), and their relative variation between periods. NA: Not Available.
| Concentration (μg/m3) | Variation | Traffic variation (%) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Before lockdown | Strict lockdown | Relaxed lockdown | Strict lockdown | Relaxed lockdown | Strict lockdown | Relaxed lockdown | ||||
| Station | Pollutant | μg/m3 | % | μg/m3 | % | |||||
| Background | NO2 | 42.6 ± 6.2 | 17.0 ± 6.9 | 16.4 ± 8.0 | −25.6 | −60 | −26.2 | −62 | −73 | −50 |
| PM10 | 40.2 ± 12.1 | 24.4 ± 13.2 | 14.8 ± 12.8 | −15.8 | −39 | −25.4 | −63 | |||
| PM2.5 | 29.6 ± 10.1 | 19.4 ± 12.4 | 7.4 ± 5.5 | −10.2 | −34 | −22.2 | −75 | |||
| Traffic | NO2 | 48.7 ± 8.4 | 18.0 ± 8.1 | 18.7 ± 10.2 | −30.8 | −63 | −30.0 | −62 | ||
| PM10 | 47.2 ± 12.7 | 29.9 ± 13.6 | 16.0 ± 13.5 | −17.3 | −37 | −31.1 | −66 | |||
| PM2.5 | 32.3 ± 9.9 | 20.7 ± 13.9 | 7.9 ± 5.0 | −11.6 | −36 | −24.5 | −76 | |||
| Background | NO2 | NA | NA | NA | NA | NA | NA | NA | −73 | −49 |
| PM10 | 61.8 ± 14.2 | 31.6 ± 16.1 | 29.1 ± 10.0 | −30.2 | −49 | −32.8 | −53 | |||
| PM2.5 | 41.9 ± 11.6 | 23.1 ± 14.7 | 15.9 ± 4.3 | −18.8 | −45 | −26.0 | −62 | |||
| Traffic | NO2 | 45.3 ± 13.4 | 15.8 ± 10.5 | 32.6 ± 10.4 | −29.6 | −65 | −12.7 | −28 | ||
| PM10 | 81.9 ± 17.0 | 38.9 ± 17.5 | 40.8 ± 13.5 | −42.9 | −52 | −41.1 | −50 | |||
| PM2.5 | 50.6 ± 12.0 | 25.6 ± 15.4 | 18.5 ± 5.7 | −25.0 | −49 | −32.1 | −63 | |||
Fig. 2Time series of daily average concentrations of NO2, PM10, and PM2.5 between February 21, 2020, and June 30, 2020 in Bogotá and Medellín, Colombia.
Average concentrations of PM10, PM2.5, and NO2 for the equivalent periods before lockdown (February 21 to March 19), strict lockdown (March 20 to April 26), and relaxed lockdown (April 27 to June 30) from 2015 to 2019, and the relative variation with 2020. NA: Not Available.
| Concentration 2015 to 2019 (μg/m3) | Variation: 2020 – (2015 to 2019) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Before lockdown eq. | Strict lockdown eq. | Relaxed lockdown eq. | Before lockdown | Strict lockdown | Relaxed lockdown | |||||
| Station | Pollutant | μg/m3 | % | μg/m3 | % | μg/m3 | % | |||
| Background | NO2 | 35.0 ± 7.9 | 33.9 ± 6.9 | 25.9 ± 6.1 | 7.6 | 22 | −16.9 | −50 | −9.6 | −37 |
| PM10 | 43.5 ± 7.5 | 35.4 ± 5.8 | 22.3 ± 5.2 | −3.3 | −7 | −11.0 | −31 | −7.5 | −34 | |
| PM2.5 | 26.1 ± 3.7 | 22.2 ± 3.3 | 11.4 ± 2.2 | 3.4 | 13 | −2.8 | −13 | −4.0 | −35 | |
| Traffic | NO2 | 47.0 ± 9.3 | 47.8 ± 8.9 | 36.8 ± 7.0 | 1.7 | 4 | −29.8 | −62 | −18.1 | −49 |
| PM10 | 48.2 ± 8.3 | 41.3 ± 6.3 | 26.1 ± 5.0 | −1.1 | −2 | −11.5 | −28 | −10.0 | −38 | |
| PM2.5 | 25.1 ± 4.5 | 21.9 ± 3.4 | 11.4 ± 2.3 | 7.2 | 29 | −1.2 | −5 | −3.5 | −31 | |
| Background | NO2 | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| PM10 | 62.9 ± 13.1 | 47.4 ± 8.7 | 38.6 ± 9.6 | −1.1 | −2 | −15.7 | −33 | −9.5 | −25 | |
| PM2.5 | 35.1 ± 6.6 | 24.6 ± 4.5 | 16.3 ± 4.5 | 6.8 | 19 | −1.5 | −6 | −0.5 | −3 | |
| Traffic | NO2 | 54.2 ± 13.0 | 51.2 ± 12.1 | 50.4 ± 11.6 | −8.9 | −16 | −35.5 | −69 | −17.8 | −35 |
| PM10 | 74.2 ± 11.1 | 58.5 ± 10.7 | 50.1 ± 11.7 | 7.6 | 10 | −19.6 | −33 | −9.4 | −19 | |
| PM2.5 | 49.4 ± 7.9 | 39.3 ± 7.3 | 27.9 ± 6.9 | 1.1 | 2 | −13.8 | −35 | −9.5 | −34 | |
Fig. 3Back trajectories density of air masses calculated with HYSPLIT and MODIS fires (orange dots) for (a.) Before lockdown, (b.) Strict lockdown, and (c.) Relaxed lockdown. The arrival points of air masses were at 500 m AGL.
Average concentrations of PM10 and PM2.5 during the lockdown (March 20 to June 30) and the relative variation between days with high and low fire counts. NA: Not Available.
| Concentration (μg/m3) | Variation (Low – High) | ||||
|---|---|---|---|---|---|
| High fire count | Low fire count | ||||
| Station | Pollutant | μg/m3 | % | ||
| Background | PM10 | 33.8 ± 10.4 | 14.2 ± 8.8 | −19.6 | −58 |
| PM2.5 | 27.9 ± 10.5 | 9.4 ± 7.8 | −18.5 | −66 | |
| Traffic | PM10 | 38.2 ± 11.3 | 15.9 ± 9.2 | −22.3 | −58 |
| PM2.5 | 29.6 ± 11.2 | 9.1 ± 7.8 | −20.4 | −69 | |
| Background | PM10 | 45.4 ± 15.4 | 26.6 ± 10.0 | −18.8 | −41 |
| PM2.5 | 35.0 ± 14.6 | 16.6 ± 9.0 | −18.3 | −52 | |
| Traffic | PM10 | 54.6 ± 19.4 | 35.8 ± 12.3 | −18.8 | −34 |
| PM2.5 | 38.6 ± 17.0 | 18.5 ± 9.6 | −20.2 | −52 | |
Fig. 4Organic Carbon fluxes in the NSA region for (a.) Before Lockdown, (b.) Strict lockdown, and (c.) Relaxed lockdown.
Fig. 5Tropospheric NO2 column in Bogotá and Medellín for (a.) March 6, 2020 (Before lockdown), (b.) April 7, 2020 (Strict lockdown), and (c.) June 26, 2020 (Relaxed lockdown). Data obtained from ESA Sentinel 5p/TROPOMI.
Fig. 6Comparison of pollutant concentration changes associated to lockdowns in Almaty (Kerimray et al., 2020), Beijing, Delhi, Dubai, Mumbai, Shanghai, Rome, Zaragoza (Chauhan and Singh, 2020), Malaysian cities (Kanniah et al., 2020), Northern China (Shi and Brasseur, 2020), Seoul, several cities in China, Tehran, Brussels, Madrid, Milan (a), Paris, New York (a) (Bauwens et al., 2020), several cities in China (Zambrano-Monserrate et al., 2020), Taiwan (Griffith et al., 2020), the Yangtze River Delta (Li et al., 2020), Barcelona (Tobías et al., 2020), Milan (b) (Collivignarelli et al., 2020), Western Europe (Menut et al., 2020), California (Bashir et al., 2020), New York (b) (Zangari et al., 2020), Rio de Janeiro (a: Dantas et al., 2020; b: Siciliano et al., 2020), and Sao Paulo (a: Krecl et al., 2020, b: Nakada and Urban, 2020).