RESUMEN

A total of 188,859 meteorological-PM[Formula: see text] data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM[Formula: see text] in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM[Formula: see text] for San Juan de Miraflores (SJM) (PM[Formula: see text]-SJM: 78.7 [Formula: see text]g/m[Formula: see text]) and the lowest in Santiago de Surco (SS) (PM[Formula: see text]-SS: 40.2 [Formula: see text]g/m[Formula: see text]). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM[Formula: see text] values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM[Formula: see text] at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM[Formula: see text] (r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE [Formula: see text]) and the NSE-MLR criterion (0.3804) was acceptable. PM[Formula: see text] prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.

Asunto(s)

RESUMEN

BACKGROUND: Coronavirus disease 2019 (COVID-19) originated in the People's Republic of China in December 2019. Thereafter, a global logarithmic expansion of cases occurred. Some countries have a higher rate of infections despite the early implementation of quarantine. Air pollution might be related to high susceptibility to the virus and associated case fatality rates (deaths/cases*100). Lima, Peru, has the second highest incidence of COVID-19 in Latin America and also has one the highest levels of air pollution in the region. METHODS: This study investigated the association of levels of PM2.5 exposure in previous years (2010-2016) in 24 districts of Lima with cases, deaths and case fatality rates for COVID-19. Multiple linear regression was used to evaluate this association controlled by age, sex, population density and number of food markets per district. The study period was from March 6 to June 12, 2020. RESULTS: There were 128,700 cases in Lima and 2382 deaths due to COVID-19. The case fatality rate was 1.93%. Previous exposure to PM2.5 (2010-2016) was associated with the number of COVID-19- cases (ß = 0.07; 95% CI: 0.034-0.107) and deaths (ß = 0.0014; 95% CI: 0.0006-0.0.0023) but not with the case fatality rate. CONCLUSIONS: After adjusting for age, sex and number of food markets, the higher rates of COVID-19 in Metropolitan Lima are attributable to the increased PM2.5 exposure in the previous years, among other reasons. Reduction in air pollution from a long-term perspective and social distancing are needed to prevent the spread of virus outbreaks.

Asunto(s)

RESUMEN

Background: Corona virus disease (COVID-19) originated in China in December 2019. Thereafter, a global logarithmic expansion of the cases has occurred. Some countries have a higher rate of infections despite of early implementation of quarantine. Air pollution could be related to the high susceptibility to SARS-CoV-2 and the associated case-fatality rates (deaths/cases*100). Lima, Peru has the second highest incidence of COVID-19 in Latin America, and it is also one of the cities with highest levels of air pollution in the Region. Methods: This study investigated the association of the levels of PM2.5 exposure in the previous years (2010-2016) in 24 districts of Lima with the positive-cases, deaths and case-fatality rates of COVID-19. Multiple Linear regression was used to evaluate this association controlled by age, sex, population density and number of food markets per district. The study period was from March 6 to June 12, 2020. Results: There were in Lima 128,700 SARS-CoV-2 positive cases, and 2,382 deaths due to COVID-19. The case-fatality rate was 1.93%. Previous exposure to PM2.5 (years 2010-2016) was associated with number of Covid-19 positive-cases (ß = 0.07; 95% CI: 0.034-0.107) and deaths (ß = 0.0014; 95% CI: 0.0006-0.0.0023), but not with case-fatality rate. Conclusions: the higher rates of COVID-19 in Metropolitan Lima is attributable, among others, to the increased PM2.5 exposure in the previous years after adjusting for age, sex and number of food markets. Reduction of air pollution since a long-term perspective, and social distancing are needed to prevent spreads of virus outbreak.

RESUMEN

The Weather Research and Forecasting-Chemistry (WRF-Chem) model was used to develop an operational air quality forecast system for the Metropolitan Area of Lima-Callao (MALC), Peru, that is affected by high particulate matter concentrations episodes. In this work, we describe the implementation of an operational air quality-forecasting platform to be used in the elaboration of public policies by decision makers, and as a research tool to evaluate the formation and transport of air pollutants in the MALC. To examine the skills of this new system, an air pollution event in April 2016 exhibiting unusually elevated PM2.5 concentrations was simulated and compared against in situ air quality measurements. In addition, a Model Output Statistic (MOS) algorithm has been developed to improve outputs of inhalable particulate matter (PM10) and fine particulate matter (PM2.5) from the WRF-Chem model. The obtained results showed that MOS increased the accuracy in terms of mean normalized bias for PM10 and PM2.5 from -43.1% and 71.3% to 3.1%, 7.3%, respectively. In addition, the mean normalized gross error for PM10 and PM2.5 were reduced from 48% and 92.3% to 13.4% and 10.1%, respectively. The WRF-Chem Model results showed an appropriate relationship between of temperature and relative humidity with observations during April 2016. Mean normalized bias for temperature and relative humidity were approximately - 0.6% and 1.1% respectively. In addition, the mean normalized gross error for temperature and relative humidity were approximately 4.0% and 0.1% respectively. The results showed that this modelling system can be a useful tool for the analysis of air quality in MALC.

RESUMEN

This study describes and compares the key structural units present in water-soluble organic carbon (WSOC) fraction of atmospheric aerosols collected in different South American (Colombia - Medellín and Bogotá, Peru - Lima, Argentina - Buenos Aires, and Brazil - Rio de Janeiro, São Paulo, and Porto Velho, during moderate (MBB) and intense (IBB) biomass burning) and Western European (Portugal - Aveiro and Lisbon) locations. Proton nuclear magnetic resonance (1H NMR) spectroscopy was employed to assess the relative distribution of non-exchangeable proton functional groups in aerosol WSOC of diverse origin, for the first time to the authors' knowledge in South America. The relative contribution of the proton functional groups was in the order H-C > H-C-C= > H-C-O > Ar-H, except in Porto Velho during MBB, Medellín, Bogotá, and Buenos Aires, for which the relative contribution of H-C-O was higher than that of H-C-C=. The 1H NMR source attribution confirmed differences in aging processes or regional sources between the two geographic regions, allowing the differentiation between urban combustion-related aerosol and biological particles. The aerosol WSOC in Aveiro, Lisbon, and Rio de Janeiro during summer are more oxidized than those from the remaining locations, indicating the predominance of secondary organic aerosols. Fresh emissions, namely of smoke particles, becomes important during winter in Aveiro and São Paulo, and in Porto Velho during IBB. The biosphere is an important source altering the chemical composition of aerosol WSOC in South America locations. The source attribution in Medellín, Bogotá, Buenos Aires, and Lima confirmed the mixed contributions of biological material, secondary formation, as well as urban and biomass burning emissions. Overall, the information and knowledge acquired in this study provide important diagnostic tools for future studies aiming at understanding the water-soluble organic aerosol problem, their sources and impact at a wider geographic scale.

Asunto(s)

RESUMEN

This study was conducted at three sites of different characteristics in São Paulo State: São Paulo (SPA), Piracicaba (PRB) and Mata Atlântica Forest (MAT). PM(10), n-alkanes, pristane and phytane, PAHs, water-soluble ions and biomass burning tracers like levoglucosan and retene, were determined in quartz fiber filters. Samplings occurred on May 8th to August 8th, 2007 at the MAT site; on August 15th to 29th in 2007 and November 10th to 29th in 2008 at the PRB site and, March 13th to April 4th in 2007 and August 7th to 29th in 2008 at the SPA site. Aliphatic compounds emitted biogenically were less abundant at the urban sites than at the forest site, and its distribution showed the influence of tropical vascular plants. Air mass transport from biomass burning regions is likely to impact the sites with specific molecular markers. The concentrations of all species were variable and dependent of seasonal changes. In the most dry and polluted seasons, n-alkane and cation total concentrations were similar between the megacity and the biomass burning site. PAHs and inorganic ion abundances were higher at São Paulo than Piracicaba, yet, the site influenced by biomass burning seems to be the most impacted by the organic anion abundance in the atmosphere. Pristane and phytane confirm the contamination by petroleum residues at urban sites; at the MAT site, biological activity and long range transport of pollutants might influence the levels of pristane.

Asunto(s)

RESUMEN

In the metropolitan area of São Paulo, Brazil, ozone and particulate matter (PM) are the air pollutants that pose the greatest threat to air quality, since the PM and the ozone precursors (nitrogen oxides and volatile organic compounds) are the main source of air pollution from vehicular emissions. Vehicular emissions can be measured inside road tunnels, and those measurements can provide information about emission factors of in-use vehicles. Emission factors are used to estimate vehicular emissions and are described as the amount of species emitted per vehicle distance driven or per volume of fuel consumed. This study presents emission factor data for fine particles, coarse particles, inhalable particulate matter and black carbon, as well as size distribution data for inhalable particulate matter, as measured in March and May of 2004, respectively, in the Jânio Quadros and Maria Maluf road tunnels, both located in São Paulo. The Jânio Quadros tunnel carries mainly light-duty vehicles, whereas the Maria Maluf tunnel carries light-duty and heavy-duty vehicles. In the Jânio Quadros tunnel, the estimated light-duty vehicle emission factors for the trace elements copper and bromine were 261 and 220 microg km(-1), respectively, and 16, 197, 127 and 92 mg km(-1), respectively, for black carbon, inhalable particulate matter, coarse particles and fine particles. The mean contribution of heavy-duty vehicles to the emissions of black carbon, inhalable particulate matter, coarse particles and fine particles was, respectively 29, 4, 6 and 6 times higher than that of light-duty vehicles. The inhalable particulate matter emission factor for heavy-duty vehicles was 1.2 times higher than that found during dynamometer testing. In general, the particle emissions in São Paulo tunnels are higher than those found in other cities of the world.

Asunto(s)