Ozone and volatile organic compounds in the metropolitan area of Lima-Callao, Peru

This study analyzes ozone formation in the metropolitan area of Lima-Callao as a function of meteorological patterns and the concentrations of nitrogen oxides and reactive organic gases. The study area is located on the west coast of South America (12°S) in an upwelling region that is markedly affected by the Southeast Pacific anticyclone. The vertical stability and diurnal evolution of the mixing layer were analyzed from radiosondes launched daily during 1992–2014 and from two intensive campaigns in 2009. Vertical profiles show that during June–November, the subsidence inversion base ranges from 0.6 to 0.9 km above sea level (asl). In contrast, during December–May, subsidence inversion dissipates, leading to weak surface inversions from 0.1 to 0.6 km asl. At the surface level, compliance with the ozone standard of 51 parts per billion by volume (ppbv) is explained by the marine boundary layer effect and by strong inhibition of ozone formation due to titration with nitric oxide. Day-of-the-week variations in ozone and nitrogen oxides suggest a VOC-limited ozone-formation regime in the atmosphere of Lima. Furthermore, the pattern of C6–C12 species indicates that gasoline-powered vehicles are the main source of volatile organic compounds (VOCs), whereas the species with the greatest ozone-forming potential corresponded to the sum of the isomers m- and p-xylene. Mean benzene concentrations exceeded the standard of 0.63 ppbv, reaching 1.2 ppbv east of Lima. Nevertheless, the cancer risk associated with the inhalation of benzene was deemed acceptable, according to USEPA and WHO criteria

The Effect of COVID-19 Lockdowns on the Air Pollution of Urban Areas of Central and Southern Chile

We present the effects of the confinement and physical distancing policies applied during the COVID-19 pandemic on the concentrations of PM10, PM2.5, NO, NO2 and O3 in 16 cities in central and southern Chile. The period between March and May in 2020 was compared with the corresponding months during 2017–2019, using surface data and satellite information. The relative percent changes in the concentration of atmospheric pollutants, and the meteorological variables observed between these two periods were used to quantify the effects of the lockdowns on the local air quality of the urban areas studied. The results showed statistically significant changes in 11 of the 16 cities. Significant relative changes between +14% and –33% were observed for PM10 in 9 cities; while statistically significant changes between –6% and –48% were evident for PM2.5 in 10 cities. Significant decreases between –27% and –55%, were observed in 4 cities in which NO2 data were available; while significant increases in O3, between 18% and 43%, were found in 4 of the 5 cities with available data. The local meteorological variables did not show significant changes between both periods. In all the cities studied, one of the main PM sources is wood burning for residential heating. Although the quarantine imposed during the health emergency could have induced an increase in residential emissions, these were compensated with the reductions in vehicular and/or industrial emissions. Therefore, these results should be carefully interpreted and should inspire new research considering the social, cultural, and economic factors that could alter the common emission patterns and air quality of urban centers

Photochemical sensitivity to emissions and local meteorology in Bogotá, Santiago, and São Paulo: An analysis of the initial COVID-19 lockdowns

This study delves into the photochemical atmospheric changes reported globally during the pandemic by analyzing the change in emissions from mobile sources and the contribution of local meteorology to ozone (O3) and particle formation in Bogotá (Colombia), Santiago (Chile), and São Paulo (Brazil). The impact of mobility reductions (50%–80%) produced by the early coronavirus-imposed lockdown was assessed through high-resolution vehicular emission inventories, surface measurements, aerosol optical depth and size, and satellite observations of tropospheric nitrogen dioxide (NO2) columns. A generalized additive model (GAM) technique was also used to separate the local meteorology and urban patterns from other drivers relevant for O3 and NO2 formation. Volatile organic compounds, nitrogen oxides (NOx), and fine particulate matter (PM2.5) decreased significantly due to motorized trip reductions. In situ nitrogen oxide median surface mixing ratios declined by 70%, 67%, and 67% in Bogotá, Santiago, and São Paulo, respectively. NO2 column medians from satellite observations decreased by 40%, 35%, and 47%, respectively, which was consistent with the changes in mobility and surface mixing ratio reductions of 34%, 25%, and 34%. However, the ambient NO2 to NOx ratio increased, denoting a shift of the O3 formation regime that led to a 51%, 36%, and 30% increase in the median O3 surface mixing ratios in the 3 respective cities. O3 showed high sensitivity to slight temperature changes during the pandemic lockdown period analyzed. However, the GAM results indicate that O3 increases were mainly caused by emission changes. The lockdown led to an increase in the median of the maximum daily 8-h average O3 of between 56% and 90% in these cities

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015–2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015–2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.Peer reviewedFinal Published versio

Contaminación del Aire

Los problemas más graves de contaminación del aire empezaron a ocurrir asociada a la “revolución industrial” iniciada en el siglo XVIII en Inglaterra. Los eventos de contaminación del aire están condicionados por el comportamiento de las variables meteorológicas. Muchos eventos ocurridos y organizados a nivel mundial sirvieron para que se empiece a normar y establecer límites en los niveles de contaminación del aire. El congreso de los EEUU aprobó el acta de Aire Limpio en 1963. El monitoreo del estado del aire o calidad del aire en Perú la empezó el Ministerio de Salud (MINSA) aproximadamente en los años 90 a través de la Dirección General de Salud Ambiental (DIGESA). En el año 2008, el SENAMHI a través de la Dirección General de Investigación y Asuntos Ambientales (DGIA) elaboró un proyecto denominado “Implementación de un Servicio de Pronóstico de Calidad de Aire en la Zona Metropolitana de Lima y Callao”. El PM10 y PM2.5 tienen una estacionalidad marcada por las condiciones meteorológicas. El PM10 muestra mayores concentraciones durante periodos con temperaturas altas (verano), debido a los procesos de transporte de polvo por los vientos. En periodos con temperaturas más bajas (invierno) favorecen los procesos de conversión gas-partícula incrementando la concentración del PM2.5 en el ambiente. En el 2019, en Lima y Callao, las concentraciones en el aire de los gases NO2, SO2, CO y O3 evidencian el cumplimiento de los ECA – Aire; sin embargo, los valores hallados de material particulado (PM10 y PM2.5), exceden los valores establecidos en la normativa vigente, tanto para el promedio de 24 horas como el anual. Con el proyecto “Mejoramiento y Ampliación del Servicio de Control de la Calidad Ambiental a Nivel Nacional” se espera implementar más redes de monitoreo automático de la calidad del aire en las ciudades de Piura, Chiclayo, Trujillo, Iquitos, Huancayo y Cuzco en un mediado plazo.The most serious problems of air pollution began to occur associated to the “industrial revolution“ that began in the 18th century in England. Air pollutionevents are conditioned by the behavior of weather variables. Many events that occurred and organized globally helped to start to set limits on air pollution levels. The U.S. Congress passed the Clean Air Act in 1963. Monitoring of air status or air quality in Peru was started by the Ministry of Health (MINSA) in approximately 1990s through the Directorate-General for Environmental Health (DIGESA). In 2008, SENAMHI through the Directorate General of Research and Environmental Affairs (DGIA) developed a project called “Implementation of an Air Quality Forecasting Service in the Metropolitan Area of Lima and Callao“ The PM10 and PM2.5 have a seasonality marked by weather conditions. The PM10 shows higher concentrations during periods with high temperatures (summer), due to wind dust transport processes. In periods with lower temperatures (winter) they favor the processes of gas-particle conversion increasing the concentration of PM2.5 in the environment. In 2019, in Lima and Callao, air concentrations of NO2, SO2, CO and O3 gases show compliance with the ECA – Air; however, the values of particulate matter (PM10 and PM2.5) exceed the reference values in the current regulations, both for the 24-hour average and the annual average. With the Project “Improvement and Expansion of the Environmental Quality Control Service at the National Level“ it is hoped to implement more networks of automatic air quality monitoring in the cities of Piura, Chiclayo, Trujillo, Iquitos, Huancayo and Cuzco in the mid-term

Evaluación de la calidad del aire en Lima Metropolitana 2014

"El objetivo de este informe es realizar la caracterización de la contaminación del aire en Lima Metropolitana mediante la descripción de los valores horarios, diarios, semanales, mensuales y anuales de los aerosoles atmosféricos. La evaluación de la contaminación del aire en el año 2014 tomó en cuenta el material particulado inhalable PM10 (partículas atmosféricas con diámetro aerodinámico menor de 10 micrómetros) y el material particulado fino PM2.5 (partículas atmosféricas con diámetro aerodinámico menor de 2.5 micrómetros), además de las siguientes variables meteorológicas: altura de inversión térmica, temperatura del aire, humedad relativa y velocidad del viento en Lima Metropolitana".-- Presentación

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao, Peru

The temporal and spatial trends in the variability of PM10 and PM2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM10 and PM2.5 have ranges (averages) of 133–45 μg m−3 (84 μg m−3) and 35–16 μg m−3 (26 μg m−3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM2.5 value is approximately 40% of the PM10 value. This proportion can be explained by PM10 re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM10 concentrations on the order of −4.3 and −5.3% year−1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM10 and PM2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount

Chemical characteristics and identification of PM10 sources in two districts of Lima, Peru

This study evaluates the concentration of PM10 and PM2.5 andidentifies the sources of pollution in the districts of San Juan de Lurigancho (SJL) and Puente Piedra (PPD) located in the eastern and northern zones of the Metropolitan area of Lima,Peru. The samples were collected between April and May 2017 by the National Meteorology and Hydrology Service of Peru (SENAMHI). The concentrations of PM10 and PM2.5, measured using gravimetric techniques, exceeded the international (WHO) and national reference values; with maximum values for PM10 and PM2.5 of 160 and 121.56 µg/ m3 in PPD and 295.06 and 154.58 µg/ m3 in SJL respectively. Pollution sources were identified using the Positive Matrix Factorization Model (PMF 5.0) and Principal Component Analysis (PCA), and showed similar sources for both districts. In SJL, sources were determined to be a combination of vehicular traffic and the resuspension of soil dust, marine aerosols and iron and steel industry by-products, while in PPD they consisted of the resuspension of soil dust, vehicular traffic, industrial activity and marine aerosols

Association Between Air Pollution in Lima and the High Incidence of COVID-19: Findings from a Post Hoc Analysis

Until June 12, 2020, there were 6,308 deaths and 220,749 SARS-CoV-2 positive cases in Peru. In Lima, the total number of COVID-19 deaths in all metropolitan areas was 2,382. The case-fatality rate at the national level was 2.58% and 1.93% in Lima. Higher PM2.5 levels are associated with higher number of cases and deaths of COVID-19. The case-fatality rate (Deaths/cases*100) did not increase with the increase in PM2.5 levels. A higher number of food markets was associated with higher incidence and mortality of COVID-19 (p < 0.01 for both); these associations persisted when cases (r = 0.49; p < 0.01) and deaths (r = 0.58; p < 0.01) were adjusted by the population density. The association of PM2.5 with cases of COVID-19 was maintained after controlling analysis by age, sex and number of food markers

Chemical Characteristics and Identification of PM10 Sources in Two Lima Districts, Peru

This study evaluates the concentration of PM10 and PM2.5 and identification of source in the districts of San Juan de Lurigancho and Puente Piedra (PPD) in Lima-Peru. The samples were collected from April to May 2017 by the National Meteorology and Hydrology Service of Peru (Senamhi). The concentration of PM10 and PM2.5, measured by gravimetric techniques, exceeded the international (WHO) and national standards; with maximum values for PM10 and PM2.5 of 160 and 121.56 µg/ m3 in PPD and 295.06 and 154.58 µg/ m3 in SJL. Identification of sources by the Positive Matrix Factorization Model (PMF 5.0) and Principal Component Analysis (ACP), showed similar sources for both districts. In SJL, the combination of vehicular traffic and resuspension of soil dust, marine aerosol and iron and steel industry was determined, while in PPD the resuspension of soil dust, vehicular source, industrial activity and marine aerosol.El presente estudio evalúa la concentración de PM10 y PM2.5 e identifica las fuentes contaminantes en los distritos de San Juan de Lurigancho (SJL) y Puente Piedra (PPD), Lima-Perú. Las muestras fueron colectadas por el servicio nacional de Meteorología e Hidrología del Perú en Abril a mayo del 2017. La concentración de PM10 y PM2.5, registradas a través de técnicas gravimétricas, excedieron el estándar internacional (OMS) y nacional; encontrándose valores máximos para PM10 y PM2.5 de 160 y 121.56 µg/ m3 en PPD y 295.06 y 154.58 µg/ m3 en SJL. La identificación de fuentes contaminantes para PM10 y PM2.5, obtenidas mediante el Modelo de Factorización de Matriz Positiva (PMF v. 5.0) y análisis por componentes principales (ACP), mostraron fuentes similares para ambos. En SJL se determinó la combinación de tráfico vehicular + resuspensión de polvo de suelo, aerosol marino e industria de hierro y acero; mientras que, en PPD se logró identificar la resuspensión de polvo del suelo, fuente vehicular, actividad industrial y aerosol marino