Maria de Fatima Andrade

This commentary paper from the recently formed International Global Atmospheric Chemistry (IGAC) Southern Hemisphere Working Group outlines key issues in atmospheric composition research that particularly impact the Southern Hemisphere. In this article, we present a broad overview of many of the challenges for understanding atmospheric chemistry in the Southern Hemisphere, before focusing in on the most significant factors that differentiate it from the Northern Hemisphere. We present sections on the importance of biogenic emissions and fires in the Southern Hemisphere, showing that these emissions often dominate over anthropogenic emissions in many regions. We then describe how these and other factors influence air quality in different parts of the Southern Hemisphere. Finally, we describe the key role of the Southern Ocean in influencing atmospheric chemistry and conclude with a description of the aims and scope of the newly formed IGAC Southern Hemisphere Working Group.

Severe episodic air pollution blankets entire cities and regions and have a profound impact on humans and their activities. We compiled daily fine particle (PM2.5) data from 100 cities in five continents, investigated the trends of number, frequency, and duration of pollution episodes, and compared these with the baseline trend in air pollution. We showed that the factors contributing to these events are complex; however, long-term measures to abate emissions from all anthropogenic sources at all times is also the most efficient way to reduce the occurrence of severe air pollution events. In the short term, accurate forecasting systems of such events based on the meteorological conditions favouring their occurrence, together with effective emergency mitigation of anthropogenic sources, may lessen their magnitude and/or duration. However, there is no clear way of preventing events caused by natural sources affected by climate change, such as wildfires and desert dust outbreaks.

In the Metropolitan Area of São Paulo (MASP), located in southeastern Brazil, surface ozone concentrations are often well above the national air quality standards. In this experimental study, we attempted to characterize the vertical profile of atmospheric ozone and transport of the ozone plume in the boundary layer, using data from the first ozone soundings ever taken in the MASP. In 2006, we launched fifteen ozonesondes: eight from 15 to 18 May (dry season); and seven from 30 October to 1 November (wet season). Vertical ozone mixing ratios in the troposphere were approximately 40 ppb, reaching maximum values of approximately 60 ppb during the dry-season campaign and approximately 100 ppb during the wet-season campaign. In the first and second campaigns, the mean tropospheric ozone column abundance was 28.2 and 41.3 DU, respectively, which can be attributed to the considerable variation in the annual temperature cycle over the region. To determine the effect that biomass burning ha...

Using a 3-D Air Quality Model to Assess Ground-Level Ozone Production in São Paulo. Paper # 1089-AWMA. Andréa Moreira. PETROBRAS/CENPES, Atmospheric Monitoring; Cidade Universitária – Quadra 7 – Ilha do Fundão, andreamoreira@petrobras.com.br. ...

1 University of Hamburg, Germany; *benjamin.bechtel@uni-hamburg.de 2 University College Dublin, Ireland 3 University of North Carolina, USA 4 IIASA, Austria 5 National University of Ireland Maynooth, Ireland 6 Federal University of Minas Gerais, Brazil 7 University of Sao Paulo, Brazil 8 Politecnico de Milano, Italy 9 Jadavpur University, India 10 University of Coimbra, Portugal Institute for Research on Urban Sciences and Techniques, France 12 Government College University Lahore, Pakistan 13 National University of Colombia, Colombia 14 University of Vienna, Austria 15 University of Kansas, USA 16 University of Moratuwa, Sri Lanka 17 International Islamic University Malaysia, Malaysia 18 Wageningen University, The Netherlands 19 University of Szeged, Hungary

The broad expanse of the urban metropolitan area of São Paulo (MASP) has made buses, the predominant public transport mode for commuters in the city. In 2016, the bus fleet in the MASP reached 56,354 buses and it was responsible for more than 12 million daily trips. Here, we evaluate for the first time, the emission profile of gaseous and particulate pollutants from buses running on 7% biodiesel + 93% petroleum diesel and their spatial distribution in the MASP. This novel study, based on four bus terminal experiments, provides an extensive analysis of atmospheric pollutants of interest to public health and climate changes, such as CO2, CO, NOx, VOCs, PM10, PM2.5 and their constituents (black carbon (BC) and elements). Our results suggest that the renovation of the bus fleet from Euro II to Euro V and the incorporation of electric buses had a noticeable impact (by a factor of up to three) on the CO2 emissions and caused a decrease in NO emissions, by a factor of four to five. In addi...

In this work, the possible benefits obtained due to the implementation of evaporative emissions control measures, originating from vehicle fueling processes, on ozone concentrations are verified. The measures studied are: (1) control at the moment when the tank trucks supply the fuel to the gas stations (Stage 1); (2) control at the moment when the vehicles are refueled at the gas stations, through a device installed in the pumps (Stage 2); (3) same as the previous control, but through a device installed in the vehicles (ORVR). The effects of these procedures were analyzed using numerical modeling with the VEIN and WRF/Chem models for a base case in 2018 and different emission scenarios, both in 2018 and 2031. The results obtained for 2018 show that the implementation of Stages 1 and 2 would reduce HCNM emissions by 47.96%, with a consequent reduction of 19.9% in the average concentrations of tropospheric ozone. For 2031, the greatest reductions in ozone concentrations were obtained...

Heavy metals are natural and essential elements of the environment and living beings, produced from natural (e.g. volcanic activity and cosmic ray-induced spallation) and anthropogenic processes (e.g. industrial and fossil fuel combustion). Studies showed increase of heavy metal and Polonium-210 concentrations in lung autopsies linked to urban and industrial air pollution. In this preliminary study, we analyzed the levels of heavy metals and Polonium-210 (210Po) in lung tissues in autopsies from residents of the city of Sao Paulo, SP, Brazil. In order to identify the generating sources of the heavy metals in lung a factor analysis was performed. Of the first four factors, which explain 66% of the total variability, three were associated with vehicular sources. The fitting of a regression model with Polonium-210 as the response variable and with the four factors as explanatory variables, controlling for age, sex and tobacco, showed a significant association between the concentration ...

Car microenvironments significantly contribute to the daily pollution exposure of commuters, yet health and socioeconomic studies focused on in-car exposure are rare. This study aims to assess the relationship between air pollution levels and socioeconomic indicators (fuel prices, city-specific GDP, road density, the value of statistical life (VSL), health burden and economic losses resulting from exposure to fine particulate matter ≤2.5 µm; PM2.5) during car journeys in ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Data collected by portable laser particle counters were used to develop a proxy of car-user exposure profiles. Hotspots on all city routes displayed higher PM2.5 concentrations and disproportionately high inhaled doses. For instance, the time spent at the hotspots in Guangzhou and Addis Ababa was 26% and 28% of total trip time, but corresponded to 54% and 56%, respectively, of the total PM2.5 inhaled dose. With the exception of Guangzhou, all the cities showed a decrease in per cent length of hotspots with an increase in GDP and VSL. Exposure levels were independent of fuel prices in most cities. The largest health burden related to in-car PM2.5 exposure was estimated for Dar-es-Salam (81.6 ± 39.3 μg m-3), Blantyre (82.9 ± 44.0) and Dhaka (62.3 ± 32.0) with deaths per 100,000 of the car commuting population per year of 2.46 (2.28-2.63), 1.11 (0.97-1.26) and 1.10 (1.05-1.15), respectively. However, the modest health burden of 0.07 (0.06-0.08), 0.10 (0.09-0.12) and 0.02 (0.02-0.03) deaths per 100,000 of the car commuting population per year were estimated for Medellin (23 ± 13.7 μg m-3), São Paulo (25.6 ± 11.7) and Sulaymaniyah (22.4 ± 15.0), respectively. Lower GDP was found to be associated with higher economic losses due to health burdens caused by air pollution in most cities, indicating a socioeconomic discrepancy. This assessment of health and socioeconomic parameters associated with in-car PM2.5 exposure highlights the importance of implementing plausible solutions to make a positive impact on peoples' lives in these cities.

Cyclists are exposed to direct traffic emissions due to their proximity to on-road vehicles. Several studies associate black carbon (BC) exposure with both mortality and morbidity caused by cardiovascular and respiratory diseases. We did a comparative assessment of cyclists' exposure to BC in three cities: London, Rotterdam and Sao Paulo. We measured personal exposure to BC during the peak and off-peak hours in all three cities using the same instrument. Three origin-destination (O-D) pairs, each with two routes, for a total of six routes, were chosen in each city. The first route of each O-D pair was along busy major roads and the other perceived to be clean passing close to green/blue/quiet areas. This work brings together results from three different Latin American and European cities, with an aim to understand the BC exposure variabilities while cycling during peak and off-peak hours, identify main pollution hotspots resulting in enhanced exposure and associate the measured concentrations with proximity to green areas and waterways. BC concentrations were higher during the morning-peak hours compared with evening-peak hours in Rotterdam and Sao Paulo. London showed an opposite trend, with higher concentrations during evening hours. In most cases, the cyclists using the alternative route were found to be less exposed to BC in London and Sao Paulo. In Rotterdam, the differences in absolute concentrations between main and alternate routes were modest. Each city is different but the common features among all were that the exposure is related to route choice, a period of the day and proximity with the mobile sources. These findings have implications in terms of considering the pollutants exposure when establishing new cycle routes.

# The Author(s) 2010. This article is published with open access at Springerlink.com Abstract In urban areas of Brazil, vehicle emissions are the principal source of fine particulate matter (PM2.5). The World Health Organization air quality guidelines state that the annual mean concentration of PM2.5 should be below 10 μg m −3. In a collaboration of Brazilian institutions, coordinated by the University of São Paulo School of Medicine and conducted from June 2007 to August 2008, mass was monitored at sites with high traffic

Abstract. We evaluate the performance of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) in simulating ozone (O 3 ) and nitrogen oxides (NO x ) concentrations within the urban street canyons in the Sao Paulo metropolitan area (SPMA). The MUNICH simulations are performed inside the Pinheiros neighborhood (a residential area) and Paulista Avenue (an economic hub), which are representative urban canyons in the SPMA. Both zones have air quality stations maintained by the Sao Paulo Environmental Agency (CETESB), providing data (both pollutant concentrations and meteorological) for model evaluation. Meteorological inputs for MUNICH are produced by a simulation with the Weather Research and Forecasting model (WRF) over triple-nested domains with the innermost domain centered over the SPMA at a spatial grid resolution of 1 km. Street coordinates and emission flux rates are retrieved from the Vehicular Emission Inventory (VEIN) emission model, representing the real f...

Urban air pollution is a matter of concern due to its health hazards and the continuous population growth exposed to it at different urban areas worldwide. Nowadays, more than 55% of the world population live in urban areas. One of the main challenges to guide pollution control policies is related to pollutant source assessment. In this line, U.S. Environmental Protection Agency's Positive Matrix Factorization (EPA-PMF) has been extensively employed worldwide as a reference model for quantification of source contributions. However, EPA-PMF presents issues associated to source identification and discrimination due to the collinearities among the source tracers. Multi-Isotopic Fingerprints (MIF) have demonstrated good resolution for source discrimination, since urban sources are characterized by specific isotopic signatures. Source quantification based on total aerosol mass is the main limitation of MIF. This study reports strategies for PMF and MIF combination to improve source i...

Brazil, one of the world’s fastest-growing economies, is the fifth most populous country and is experiencing accelerated urbanization. This combination of factors causes an increase in urban population that is exposed to poor air quality, leading to public health burdens. In this work, the Weather Research and Forecasting Model with Chemistry is applied to simulate air quality over Brazil for a short time period under three future emission scenarios, including current legislation (CLE), mitigation scenario (MIT), and maximum feasible reduction (MFR) under the Representative Concentration Pathway 4.5 (RCP4.5), which is a climate change scenario under which radiative forcing of greenhouse gases (GHGs) reach 4.5 W m−2 by 2100. The main objective of this study is to determine the sensitivity of the concentrations of ozone (O3) and particulate matter with aerodynamic diameter 2.5 µm or less (PM2.5) to changes in emissions under these emission scenarios and to determine the signal and spa...

We evaluate the performance of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) in simulating Ozone (O3) and Nitrogen Oxides (NOx) concentrations within the urban street canyons in the Sao Paulo 10 Metropolitan Area (SPMA). The MUNICH simulations are performed inside Pinheiros neighborhood (a residential area) and Paulista Avenue (an economic hub), which are representative urban canyons in the SPMA. Both zones have air quality stations maintained by the Sao Paulo Environmental Agency (CETESB), providing data (both pollutants concentrations and meteorological) for model evaluation. Meteorological inputs for MUNICH are produced by a simulation with the Weather Research and Forecasting model (WRF) over triple-nested domains with the innermost domain centered over the SPMA at a 15 spatial grid resolution of 1 km. Street links coordinates and emission flux rates are retrieved from the Vehicular Emission Inventory (VEIN) emission model, representing the real fleet ...

Vehicles are an important source of air pollutants and greenhouse gases. Their emissions are controlled since the 1970’s by laboratory tests, but divergences are often found between the results and real-world emissions. Real Driving Emissions procedure was implemented in many countries, in order to evaluate the vehicle closer to actual operation. In order to reduce the dispersion of the results, some dynamic parameters, such as speed and acceleration, are controlled, but the influence of the road grade has not being taken into account. This paper presents an alternative for the dynamic metrics, based on the Vehicle Specific Power, that allows evaluating more accurately the vehicle dynamics and representing better both the up-and-downhill effect as well the low engine power driving requirement, even when the regulatory parameters are into their limits.

Understanding the impact on human health during peak episodes in air pollution is invaluable for policymakers. Particles less than PM2.5 can penetrate the respiratory system, causing cardiopulmonary and other systemic diseases. Statistical regression models are usually used to assess air pollution impacts on human health. However, when there are databases missing, linear statistical regression may not process well and alternative data processing should be considered. Nonlinear Artificial Neural Networks (ANN) are not employed to research environmental health pollution even though another advantage in using ANN is that the output data can be expressed as the number of hospital admissions. This research applied ANN to assess the impact of air pollution on human health. Three well-known ANN were tested: Multilayer Perceptron (MLP), Extreme Learning Machines (ELM) and Echo State Networks (ESN), to assess the influence of PM2.5, temperature, and relative humidity on hospital admissions d...

Most of the world’s population lives in rural areas or small to medium-sized cities (totalling 68% of the world population), all of which are impacted by distant air pollution sources. In Brazil, primary pollutant emissions have decreased in urban centres because of government actions, while secondary pollutants such as surface ozone (O3) increased. In addition, O3 and its precursors can be worsening air quality in areas already affected by biofuels production, especially ethanol. We provide almost 3 months of hourly data (June 7, 2019 to August 25, 2019) for concentrations of O3, CO2 and other priority pollutants from a mobile station positioned to distinguish among pollutant plumes (biomass burning, metropolitan area of São Paulo (MASP) and other cities). Although the concentrations of O3 and CO2 were highest in the plumes from biomass burning, the MASP accounted for up to 80% of the O3 concentration in communities over 200 km away.

Since 2001, four emission measurement campaigns have been conducted in multiple traffic tunnels in the megacity of São Paulo, Brazil, an area with a fleet of more than 7 million vehicles running on fuels with high biofuel contents: gasoline + ethanol for light-duty vehicles (LDVs) and diesel + biodiesel for heavy-duty vehicles (HDVs). Emission factors for LDVs and HDVs were calculated using a carbon balance method, the pollutants considered including nitrogen oxides (NOx), carbon monoxide (CO), and sulfur dioxide, as well as carbon dioxide and ethanol. From 2001 to 2018, fleet-average emission factors for LDVs and HDVs, respectively, were found to decrease by 4.9 and 5.1% per year for CO and by 5.5 and 4.2% per year for NOx. These reductions demonstrate that regulations for vehicle emissions adopted in Brazil in the last 30 years improved air quality in the megacity of São Paulo significantly, albeit with a clear delay. These findings, especially those for CO, indicate that official emission inventories underestimate vehicle emissions. Here, we demonstrated that the adoption of emission factors calculated under real-world conditions can dramatically improve air quality modeling in the region.

The role of particulate matter (PM) in the COVID-19 pandemic is currently being discussed by the scientific community. Long-term (years) exposure to PM is known to affect human health by increasing susceptibility to viral infections as well as to the development of respiratory and cardiovascular symptoms. In the short-term (days to months), PM has been suggested to assist airborne viral transmission. However, confounding factors such as urban mobility prevent causal conclusions. In this study, we explore short-term relationships between PM concentrations and the evolution of COVID-19 cases in a number of cities in the United States of America. We focus on the role of PM in facilitating viral transmission in early stages of the pandemic. We analyzed PM concentrations in two particle size ranges, < 2.5 µm, and between 10 and 2.5 µm (PM2.5 and PM10 respectively) as well as carbon monoxide (CO) and nitrogen dioxide (NO2). Granger causality analysis was employed to identify instantane...

In this paper we show measurements of air pollutants for a mixed vehicle fleet, heavy and light duty vehicles (HDV, LDV), in the Rodoanel and Janio Quadros tunnels in the Metropolitan Region of Sao Paulo (MRSP) in May-July 2011. Measurements of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx) and Particle Matter (PM10) were performed by the air quality monitoring net from CETESB (Environmental Agency of Sao Paulo State). High concentrations correlated with high density traffic (approximately 3,000 ± 1,000 vehicles per hour), especially during weekdays, and have a characteristic diurnal pattern with two peaks: at morning (06:00–9:00 h) and at afternoon (16:00–19:00 h).

<p>Commuters are vulnerable to traffic air pollutants, especially to fine particulate matter (PM<sub>2.5</sub>) and black carbon (BC) because of their proximity to on-road vehicles. Both pollutants have been extensively associated to adverse health effects (i.e., stroke, diabetes, cardiovascular and respiratory diseases, and cancer). Therefore, this work aims to investigate the extreme concentrations of PM<sub>2.5</sub> and BC occurrence in commuters in the megacity of São Paulo, Brazil. We carried out a field campaign measuring the commuter exposure to PM<sub>2.5</sub> and BC concentrations inside buses, cars and undergrounds in São Paulo during morning and evening peak-hours. We fitted an Extreme Value Distribution to the collected data to investigate the behavior of the extreme values in the different transport modes and periods of the day. The results suggest that higher concentrations of PM<sub>2.5</sub> and BC occur more frequently inside buses, followed by cars and undergrounds. Extreme concentrations for both pollutants are more likely to happen during morning peak-hours when compared to evening peak-hours. Our findings add further evidence that the transport mode and period of the day affect substantially the PM<sub>2.5</sub> and BC exposure in commuters. Furthermore, the results are quite useful for supporting urban policies that consider the improvement of the efficiency of air filtering systems inside public transport and private cars.</p>

Atmospheric pollutants are strongly affected by transport processes and chemical transformations that alter their composition and the level of contamination in a region. In the last decade, several studies have employed numerical modeling to analyze atmospheric pollutants. The objective of this study is to evaluate the performance of the WRF-SMOKE-CMAQ modeling system to represent meteorological and air quality conditions over São Paulo, Brazil, where vehicular emissions are the primary contributors to air pollution. Meteorological fields were modeled using the Weather Research and Forecasting model (WRF), for a 12-day period during the winter of 2008 (Aug. 10th-Aug. 22nd), using three nested domains with 27-km, 9-km, and 3-km grid resolutions, which covered the most polluted cities in São Paulo state. The 3-km domain was aligned with the Sparse Matrix Operator Kernel Emissions (SMOKE), which processes the emission inventory for the Models-3 Community Multiscale Air Quality Modeling...

Understanding the impact on human health during peak episodes in air pollution is invaluable for policymakers. Particles less than PM2.5 can penetrate the respiratory system, causing cardiopulmonary and other systemic diseases. Statistical regression models are usually used to assess air pollution impacts on human health. However, when there are databases missing, linear statistical regression may not process well and alternative data processing should be considered. Nonlinear Artificial Neural Networks (ANN) are not employed to research environmental health pollution even though another advantage in using ANN is that the output data can be expressed as the number of hospital admissions. This research applied ANN to assess the impact of air pollution on human health. Three well-known ANN were tested: Multilayer Perceptron (MLP), Extreme Learning Machines (ELM) and Echo State Networks (ESN), to assess the influence of PM2.5, temperature, and relative humidity on hospital admissions d...

This study quantified the effects of traffic restrictions on diesel fuel heavy vehicles (HVs) on the air quality of the Bandeirantes corridor using hourly data obtained by continuous monitoring of traffic and air quality at sites located on this avenue. The study addressed the air quality of a city impacted by vehicular emissions and that PM10 and NOX concentrations are mainly due to diesel burning. Data collection was split into two time periods, a period of no traffic constraint on HVs (Nov 2008 and 2009) and a period of constraint (Nov 2010, 2011 and 2012). We found that pollutants on this corridor, mainly PM10 and NOX, decreased significantly during the period from 2008 to 2012 (28 and 43%, 15.8 and 86.9 ppb) as a direct consequence of HV traffic restrictions (a 72% reduction). Rebound effects in the form of increased traffic of light vehicles (LVs) during this time had impacts on the concentration levels, explaining the differences between rates of reduction in HV traffic and p...

The air quality in the Metropolitan Area of São Paulo (MASP) is primarily determined by the local pollution source contribution, mainly the vehicular fleet, but there is a concern about the role of remote sources to the fine mode particles (PM2.5) concentration and composition. One of the most important remote sources of atmospheric aerosol is the biomass burning emissions from São Paulo state's inland and from the central and north portions of Brazil. This study presents a synergy of different measurements of atmospheric aerosol chemistry and optical properties in the MASP in order to show how they can be used as a tool to identify particles from local and remote sources. For the clear identification of the local and remote source contribution, aerosol properties measurements at surface level were combined with vertical profiles information. Over 15 days in the austral winter of 2012, particulate matter (PM) was collected using a cascade impactor and a Partisol sampler in São P...