Health impact assessment of air pollution in Lisbon, Portugal

ABSTRACT

Background: Lisbon has about 500,000 inhabitants and it’s the capital and the main economic hub of Portugal. Studies have demonstrated that exposure to Particulate Matter with an aerodynamic diameter<2.5 μm (PM_2.5) have strong association with health effects. Researchers continue to identify new harmful air pollutants effects in our health even in low levels. Objectives: This study evaluates air pollution scenarios considering a Health Impact Assessment approach in Lisbon, Portugal. Methods: We have studied abatement scenarios of PM_2.5 concentrations and the health effects in the period from 2015 to 2017 using the APHEKOM tool and the associated health costs were assessed by Value of Life Year. Results: The mean concentration of PM_2.5 in Lisbon was 23 μg/m³ ± 10 μg/m³ (±Standard Deviation). If we consider that World Health Organization (WHO) standards of PM_2.5 (10 μg/m³) were reached, Lisbon would avoid more than 423 premature deaths (equivalent to 9,172 life years’ gain) and save more than US$45 million annually. If Lisbon city could even diminish the mean of PM_2.5 by 5 μg/m³, nearly 165 deaths would be avoided, resulting in a gain of US$17 million annually. Conclusion: According to our findings, if considered the worst pollution scenario, levels of PM2.5 could improve the life’s quality and save a significant amount of economic resources.

Implications: The manuscript addresses the health effects and costs of air pollution and constitutes an important target for improving public policies on air pollutants in Portugal. Although Portugal has low levels of air pollution, there are significant health and economic effects that, for the most part, are underreported. The health impact assessment approach associated with costs had not yet been addressed in Portugal, which makes this study more relevant in the analysis of policies aimed to drive stricter control on pollutants’ emissions. Health costs are a fundamental element to support decision-making process and to orientate the trade-offs in investments for improving public policies so that to diminish health effects, which can impact the management of the local health services and the population’s quality of life, especially after the pandemic period when resources are scarce.

Introduction

The risks to human health of low levels of ambient air pollution are well established in the epidemiological, clinical and toxicological literature (Broome et al. 2015; Burnett et al. 2014). The Global Burden of Disease (GBD), in 2013, provided important estimates of the global health impacts attributable to ambient air pollution (Brauer et al. 2016). Special attention has been devoted to particulate matter, because of its large capacity to affect the exposed population health (Abe et al. 2018; Anderson, Thundiyil, and Stolbach 2012; Silva, Abe, and Miraglia 2017; Torres et al. 2018). Ambient particulate matter air pollution, in particular PM_2.5 (particulate matter with aerodynamic diameter 2.5 μm or smaller) was identified as a leading risk factor for global disease burden with an estimated 2.9 million attributable deaths in the year 2013 (Forouzanfar et al. 2015). This pollutant was selected as indicator of exposure to ambient air pollution based on extensive epidemiological and mechanistic evidence, indicating independent adverse health impacts (Brauer et al. 2016). Studies have shown that PM_2.5 long term exposure is associated with increased cardiopulmonary mortality (Abe and Miraglia 2016; Cesaroni et al. 2013; Pope et al. 2002, 2004) and short-term exposure is associated with increased daily mortality and hospital admissions (Katsouyanni et al. 2009). In addition to the effects of PM_2.5, numerous epidemiological studies have shown similar effects to urban outdoor air pollution exposure and health outcomes, including increases in mortality and morbidity for cardiovascular and respiratory diseases (Hoek et al. 2013; Likhvar et al. 2015; Raaschou-Nielsen et al. 2013; Thurston et al. 2015). Moreover, it is demonstrated that cardiovascular and respiratory effects due to air pollution exposure could occur after a displacement of time (Abe et al. 2018; Costa et al. 2016).

A recent study showed a higher susceptibility of COVID-19 infection of populations exposed to high concentrations of aerosols. Wu et al (Wu et al. 2020) found in the United States that an increase of only 1 μg/m³ in PM_2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%).

Health effects from exposure to urban air pollution are well known in developing countries with many studies being conducted in China (Liu et al. 2019; Lu et al. 2020), Brazil (Abe and Miraglia 2016; Silva et al. 2012), South Africa (Katoto et al. 2019), Mexico (Liu et al. 2019; Tellez-Rojo et al. 2020) and other countries (Sciences et al. 2019), but also in developed countries, such as Portugal (Almeida, Silva, and Sarmento 2014). When the exposure to pollutants is prolonged (long-term exposure), even if at low concentration levels, adverse health effects may arise (Maji et al. 2017; Torres et al. 2018). In this sense, studies from Multi-City Multi-Country Collaborative Researches has been performing a global assessment of the effects of air pollution on health, even in countries with low pollutants levels, such as Australia, Canada or Finland (Liu et al. 2019; Molter et al. 2015; Romieu et al. 2012).

Regarding economic costs, air pollution impacts on the economies are enormous (Sciences et al. 2019). In Brazil, Miraglia and Gouveia (2014) have estimated the cost of premature deaths due to air pollution in 29 Brazilian capital cities and the result was a loss of US$1.7 billion annually (Miraglia and Gouveia 2014). Another research in Brazil, shows the potential health and economic benefits for São Paulo city through compliance with World Health Organization (WHO) guidelines, evidencing the amount of avoided adverse health effects (about 5,000 deaths) and associated monetary gains were around US$ 15 billion (Abe and Miraglia 2016).

Nevertheless, it is important to apply comprehensive methodologies to approach economic costs of air pollution. One of the recommended methodologies that focuses on the issue is the “Health Impact Assessment” (HIA) methodology. According to the WHO, “HIA is a practical approach used to judge the potential health effects of a policy, program or project on a population, particularly on vulnerable or disadvantaged groups” (WHO 2015). The HIA could be useful to analyze and predict possible impacts of air pollution on public health or the expected benefits in scenarios of reduction of pollution levels. Thus, an HIA could estimate the human health impacts of the current actions or any policies implemented, being an important tool for policy makers and stakeholders (WHO 2015).

This methodology has already been used by other studies combined with one or two predictive scenarios of air pollution (Chanel et al. 2014; Pascal et al. 2013). In this study, we consider the WHO-Air Quality Guideline (WHO-AQG) for PM, chosen as the lowest levels at which total, cardiopulmonary and lung cancer mortality have been shown to significantly increase in response to long-term exposure to PM (WHO 2006). In Portugal, there are no studies involving HIA and associated costs with reducing pollution levels scenarios, aim of the present work.

Materials and methods

Study period and areas

The HIA was performed in Lisbon using the APHEKOM (Improving knowledge and Communication for Decision Making on Air Pollution and Health in Europe) model. This model has already been used in several studies to improve decision-making on air pollution (Chanel et al. 2016; Medina et al. 2009; Pascal et al. 2013; Perez et al. 2013). A common study period, 2015–2017, was chosen based on data availability. A study area was defined according to pollutant database collections in order to ensure that average pollutant levels measured at fixed monitors could be considered acceptable statistical representations of the population’s average exposure.

Population and health data

Lisbon population data and health indicators related to annual number of deaths were collected from public authorities’ sources (PORDATA 2018, 2019d) and are openly available.

Exposure assessment

Data availability

The pollution concentration data that support the findings of this study are openly available in Portuguese Environment Agency database QualAr. Health effects were collected from open public authorities’ sources (PORDATA 2018, 2019d).

Air quality data

The pollutants concentrations for PM₁₀ and PM_2.5 in ambient air were obtained through the APA’s (Portuguese Environment Agency) Online Database on Air Quality (QualAr), a web tool that centralize all air quality data measured in Portugal, such as information on air quality indexes and pollutant concentrations statistics at each air quality monitoring station. The station considered in this study was Lisbon, Liberdade Avenue. Hourly data of PM₁₀ for the period starting January 01, 2015 and ending December 31, 2017 was obtained from the QualAr website.

QualAr database results from information collected from the national Quality Monitoring Stations Network, providing continuous measurements based on 1 h averages with every 15-min data registry. The air quality monitoring stations are placed according to specific legislation, to guarantee the representativeness of the Portuguese territory (Torres et al. 2018). The spatial divisions are referred to as Air Quality Index zones (IQAr zones). Stations in the central region of Lisbon that had more than 70% of the data for PM10 were considered for the period studied. From these, Av. Liberdade Station was chosen considering data availability. However, it is important to note that this air quality monitoring station is located in a place with one of the busiest traffic flow. For Lisbon, PM_2.5 concentration was estimated from daily PM₁₀ values using a 0.7 conversion factor, as defined in the Apheis project (Medina, Boldo, and Saklad 2005; Pascal et al. 2013).

Calculation of the health impacts

In this study, we evaluated the health benefits that could be achieved if pollutant concentrations were decreased. Regarding PM₁₀, the short-term exposure was estimated and the health impact was computed as follows (Pascal et al. 2013) (Equation (1)(1) $\mathrm{\Delta }\mathrm{y}={\mathrm{y}}_0\left(1-{\mathrm{e}}^{-\beta \mathrm{\Delta }\mathrm{x}}\right)$(1) :

(1) $\mathrm{\Delta }\mathrm{y}={\mathrm{y}}_0\left(1-{\mathrm{e}}^{-\beta \mathrm{\Delta }\mathrm{x}}\right)$(1)

Where:

Δy – means the decrease in the annual number of hospitalizations or deaths associated with the reduction of pollutant concentrations.

y₀ – means the baseline health outcome, in annual number of deaths or hospitalizations.

β – is the coefficient of the concentration response function.

Δx – is the decrease in the pollutant concentration in a specific scenario, shown in μg/m³.

The scenarios were built as following characteristics: (1) a decrease in the annual mean by a fixed amount of 5 μg/m³ and (2) a decrease of the annual mean down to the annual WHO-Air Quality Standards (WHO-AQS). The WHO-AQS values of pollutants’ concentration were 10 μg/m³ for PM_2.5. Regarding PM_2.5 long-term health effects exposure, we applied a standard abridged life table methodology as described by Pascal et al. (2013).

The number of avoided deaths and the additional life expectancy at age 30 are the results presented in each scenario.

The Guidelines for conducting an air pollution health impacts HIA (APHEKOM 2011) contains the detailed methodology, concentration response functions and equations utilized in the present study. Furthermore, all databases concerning Lisbon data used Microsoft Excel® spreadsheets model developed by the APHEKOM software, which has been utilized in several studies (Abe and Miraglia 2016; Chanel et al. 2016; Pascal et al. 2013).

Economic valuation

Mortality

Several approaches to express trade-offs between mortality and economic costs (Pascal et al. 2013) have aroused interest in the past years. The Value of a Statistical Life (VSL) is estimated using the economic value of preventing adverse health effects related to air pollution reducing the mortality risk. VSL depends on health outcomes and the population’s characteristics and the risk of death such as age, time between exposure and death and the nature of the underlying risk (Cropper, Hammitt, and Robinson 2011; Dekker et al. 2011).

Hence, we applied the Disability-Adjusted Life Years (DALY) method in order to estimate the burden of disease due to air pollution. The DALY method was elaborated by the World Bank and WHO as an initiative to standardize a worldwide health cost estimative using a single measure of health outcome (Miraglia, Saldiva, and Böhm 2005). This method involves two components: the first component refers to Years of Life Lost due to premature death (YLLs) and the second component refers to Years of Life Lived with Disability (YLDs) (Abe et al., 2018; Miraglia, Saldiva, and Böhm 2005). In this study, we have only assessed the YLL component of DALY. The total amount of YLL can be expressed in economic terms by utilizing the estimate for the monetary value of a life year (VOLY), which was adopted to be € 50,000 (Bickel and Friedrich 2005).

This value was provided by ExternE methodology based on questionnaires where researchers directly pose contingent or hypothetical questions to respondents, called contingent valuation, was applied in France, Italy and the UK (ExternE 2004). On this valuation method people are asked to state their willingness to pay, contingent on a specific hypothetical scenario and description of the environmental service. The ExternE project is a major research programme launched by the European Commission at the beginning of the 1990s to provide a scientific basis for the quantification of externalities and to give guidance supporting the design of internalization measures, became a well-recognized standard source for external cost data. A crucial point that needs to be explained is that air pollution mortality does not cut off a few months of misery at the end of life but causes “accelerated ageing”. Based on the results in France, Italy and the UK, ExtenE is now using a VOLY of €50,000 (Bickel et al, 2005).

For YLL economic valuation estimative, we utilized a similar concept that is called Years of Life Gain, that is, Years of Life Lost which were avoided by the diminish in pollutants’ concentration scenarios, as displayed in Table 4.

Table 1. The annual mean number and annual rate per 100000 of deaths to the period 2015–2017 in Lisbon, Portugal.

Health outcome	ICD9	ICD10		Annual mean number	Annual rate per
			Age		100,000
Cardiovascular mortality	390–459	I00-I99	>30	2,096	602
Total mortality	000–999	A00-Y98	>30	5,766	1,655

*ICD: International Classification of Diseases.

Table 2. Descriptive statistics of pollutant concentration (period 2015–2017).

Pollutant	Daily mean (μg/m3)	Standard deviation	Minimum	Maximum
		(μg/m^3)	(μg/m^3)	(μg/m^3)
PM2.5 (daily average)	23	10	3	83
PM10 (daily average)	33	15	5	119

Particulate Matter (PM) with an aerodynamic diameter <10 μm (PM₁₀) or <2.5 μm (PM_2.5).

Table 3. Potential benefits of reducing annual PM_2.5 levels on total cardiovascular mortality.

Scenarios	Annual number of deaths avoided	Annual number of deaths avoided per
		100,000
Decrease by 5 μg/m^3	115.5	33.1
Decrease to 10 μg/m^3	288.8	82.9

Table 4. Potential health and economic benefits of reducing annual PM_2.5 levels over the long term in terms of total mortality.

Scenarios	Annual number of deaths avoided	Annual number of deaths avoided per	Gain in life expectancy (months)	Life Years Gain	Economic Valuation
		100,000
Decrease by 5 μg/m^3	165.6	47.5	7.0	3,437.7	€ 17,188,273.10
Decrease to 10 μg/m^3	423.1	121.4	18.7	9,172.0	€ 45,860,099.95

* Monetary valuation is based on Life Years Gain.

Results

Characteristics of the study region and population

The study area is the municipality of Lisbon, capital of Portugal and the westernmost capital in mainland Europe. Lisbon is set on Seven Hills, north of the Tagus estuary and in close proximity to the Atlantic Ocean. It is the largest urban area in Portugal with a population of about 500,000 inhabitants (PORDATA 2019c).

Lisbon has specific social characteristics such as a large proportion of the residential population are over 65 years (24%) and it has one of the highest population densities (6,134 inhabitants per square kilometers) in the country. It is, thus, not surprising that it has one of the highest mortality rates (14.1‰), significantly higher than the national rate of 9.7‰ (PORDATA 2019c).

Services are the main economic sectors in the city, although there is some industrial activity. The latter includes textiles, chemicals, steel, oil and sugar refining, shipbuilding, and waste incineration units. However, traffic is the main source of local atmospheric emission. Apart from road traffic, the international airport located in the north of the city is also a significant contributor to local emissions (Garrett and Casimiro 2011).

The annual mean number due to total mortality varied from 5,813 in 2015 to 5,694 in 2017. The mortality due to cardiac causes for >30 age varied from 2,175 in 2015 to 2,018 in 2015 (Table 1).

Descriptive analysis of pollutants

For the PM_10, the maximum daily value was 119 µg/m³ and the minimum was 5 µg/m³ for the period 2015–2017. For the PM_2.5, the daily average was 23 ± 10 µg/m³, with maximum value of 83 µg/m³. The values are summarized in Table 2.

Potential benefits of reducing annual PM2.5 levels on total cardiovascular mortality

Regarding PM_2.5 levels, compliance with the WHO standard of 10 μg/m³ for the maximum daily PM_2.5 mean would have resulted in the avoidance of more than 288 deaths avoided annually (Table 3). In addition, if the PM_2.5 mean concentration had been reduced by 5 μg/m³, it would have resulted in an annual decrease of more than 115 deaths, representing more than 33 deaths avoided per 100,000 inhabitants (Table 3).

Long-term impacts of PM_2.5 chronic exposure on mortality

In Lisbon, if the PM_2.5 WHO standards had been reached (10 µg/m³), the annual number of postponed deaths would have been more than 423 annually and life expectancy would have increased by 18.7 months (Table 4). That is equivalent to a 9,172 life years’ gain and almost € 46 million annually. If Lisbon city could diminish the mean of PM_2.5 levels only by 5 μg/m³, approximately 165 annual deaths would be postponed and the population would gain more than 7 months in life expectancy. It would represent a gain of more than € 17 millions.

Discussion

Lisbon is largest city in Portugal and is located in western of Portugal, on the estuary of the Tagus (Tejo) River. In fact, it is the western most capital city in continental Europe and serves as the country’s main port. It exerts a strong regional influence in commerce, finance, politics, culture and tourism. Lisbon has a mild and equable climate, with a mean annual temperature about 17°C (Britannica 2018).

Although Lisbon has a population of about 500,000 inhabitants (Stat 2019a), representing a smaller number of people when compared to other capitals in Europe (Paris has about 2 million (Stat 2020) and Madrid count more than 3,2 million people (Stat 2019b), for example), the concentration of pollutants, such as PM_2.5 and PM₁₀ are closer to cities which presents high levels of pollution and vehicle traffic, such as São Paulo city in Brazil, whose population is over than 11 million people (Abe and Miraglia 2016; IBGE, 2010). This is a concerning issue, as it indicates that measures and public policies related to the air pollution control need to be improved.

According to our results, if the city of Lisbon managed to meet the WHO-AQG for PM_2.5, approximately 288 deaths due to cardiovascular diseases could be avoided annually (Table 3). In addition, 423 additional annual deaths from non-external causes would be avoided representing more than 121 deaths avoided per 100,000 inhabitants (Table 4). This value is higher than once already disclosed for developing countries. A comparison with a similar study of PM_2.5 abatement scenarios, conducted in São Paulo city, shows about 83 deaths preventable per 100,000 inhabitants (Abe and Miraglia 2016). In this sense, the situation of air pollution in Lisbon and the impact on the population and life expectancy is as critical as in developing countries.

If Lisbon meets the PM_2.5 WHO standards, it would represent a gain in life expectancy of almost 19 months for the population in entire population (Table 4). Even if PM_2.5 concentrations could be decreased by 5ug/m³, this could represent more than 165 preventable deaths over the course of a year and an increase in life expectancy of around 7 months (Table 4). This scenario is important for planning intermediate policies and actions, which can lead to an improvement in the region’s air quality.

According to the transportation rail data, Lisbon has 4 subway lines since 1998 with an increase of 56% in total line distance built in 2016, totalizing 44 km (PORDATA 2019a). The Lisbon subway system is responsible for transportation of about 169,150 passengers annually (PORDATA 2019b). However, when compared to other European capitals, the number of kilometers of rail transport is less than in Madrid (292 km) (Urbanrail 2015) or Paris (213 km) (Technology 2020), for example. As the main source of air pollution in major city centers is transportation, there is an urgent need to regulate pollutants from major sources such as transportation, industry and energy production in accordance with the most stringent standards. A recent study analyzed the economic benefits on active transportation in Porto, Portugal and the researchers related economic benefits of reduction in mortality varying from € 3 894 million to € 6 769 million (Rodrigues et al. 2020).

In addition to the impact on the population health, achieving the PM_2.5 limits suggested by WHO could lead to 45 million euros saving for the city of Lisbon, represented in more than 9,000 years of life gain by the improvement in air quality conditions (Table 4). This figure is underestimated since there may have a higher level of mortality due to respiratory diseases. All these results suggest the needed of better public policies regarding air quality in large cities in Portugal. In Portugal, some measures to reduce air pollution can be taken, such as improving public transport and active transportation.

Pascal et al. (2013) conducted a large APHEKOM study in 25 European cities and the main result regarding mortality benefits of complying with the WHO standards for PM_2.5, would represent an average gain of €31 billion euros including savings on health expenditures, absenteeism and intangible costs such as well-being, life expectancy and quality of life. In the 25 cities analyzed, compliance with the WHO-AQG of 10 μg/m³ resulted in an increase in life expectancy at age 30 ranging from 0 (Stockholm) to 22 months (Bucharest). In most cities, much of the population is still exposed to air pollutant levels higher than those recommended by the WHO. The largest health burden was attributable to the impacts of chronic exposure to PM_2.5 (Pascal et al. 2013). In addition, a Belgian study conducted a similar analysis where the authors concluded that a 10% reduction of pollutants mean a potential annual hospital cost saving of €13.2 million (Devos et al. 2015). If WHO annual guidelines for PM₁₀ and PM_2.5 were met, more than triple these amounts would be saved (Devos et al. 2015).

Pascal et al. (Pascal et al. 2013) research underestimated cardiovascular mortality due to the limitations of the study (which are the same limitations of the present study, since both studies have considered the analysis of a small number of pollutants and use of the average concentration exposure for the population). In addition, Lisbon or any other Portugal city was not included in the APHEKOM study (Malmqvist et al. 2018; Pascal et al. 2013).

Due to the proposition by Wu et al. (Wu et al. 2020) that SARS-CoV-2 may have the potential to be transmitted via aerosols, the implications for environmental control of ambient particles are essential. Regarding this additional infectivity promotion of PM_2.5, an HIA is important to be carried out in a participatory approach that helps stakeholders to gather different types of evidence, especially the health sector.

In this sense, the HIA applied in Lisbon could estimate the mortality rates due to current levels of air pollution and the public health impact that would be expected if the levels of air pollution would change to a certain extent. Few studies have examined the air pollution impacts on YLL and its economic valuation, and this information is crucial to stakeholders (Abe et al. 2018).

Despite the relevance of this study results, is important to recognize some important limitations. Air pollution is a mixture of gases and particles in the air, and each component can have different health effects. In this study, we focused on the impact of particle exposure measured as PM_2.5 or PM₁₀; however, some studies have also included the effects of ozone, NOx or nitrogen dioxide (NO₂) that were not accounted for, in part of lack of data availability and in order to avoid double counting mixture effects, as PM and NOx/NO₂ may have similar or same sources and/or are markers for same mixture effect of air pollution (Malmqvist et al. 2018). Additionally, data used in this study resulted from a single air quality monitoring station of the overall Lisbon air quality monitoring network, located in one of the most polluted places of the city. This may have influenced some of this study conclusions.

Scientists continue to identify new effects that air pollution can harm our health, for example, there is increasing evidence linking long-term exposure to air pollution and higher risk of dementia (Grande et al. 2020) and new researches and evidence has shown that particles of air pollution travel through the lungs of pregnant women and can affect their placentas (Lyon-Caen et al. 2019; Maghbooli et al. 2018).

In a more comprehensive review of the new evidence linking PM exposure with cardiovascular disease, studies have shown that exposure to PM_2.5 over a few hours to weeks can trigger cardiovascular disease-related mortality and nonfatal events; and longer-term exposure could increase the adverse effects on microvascular functions and the risk for cardiovascular mortality (Brook et al. 2010; Pope et al. 2015). In this sense, the gain in quality of life and health outcomes due to the reduction of air pollution levels could be perceived by the population, becoming essentially the implementation of more stringent public policies on air quality in Lisbon and other large Portugal cities, as Porto.

Conclusion

Although the WHO declares that no level of air pollution can be considered “safe” (WHO 2006), countries must strive to try to reduce the levels of air pollutants, through public policies, avoiding costs to health systems and decreasing the quality of life of the population. Concerning the potential of PM_2.5 to spread SARS-CoV-2 and the high susceptibility of the population exposed chronically to high levels of air pollution, it is essential for environmental management to minimize human health effects of urban air pollution through quantification and emissions’ control.

Lisbon city could avoid more than 423 premature deaths (equivalent to 9,172 life years’ gain) and save more than US$ 45 million annually if compliance with the PM_2.5 WHO-AQG. The economic savings could represent a gain of US$ 17 million annually. Investments in public policies regarding air quality improvement are essential, to reduced air pollutants levels leading a significant savings of resources, lives and hospital care demand.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Derived data supporting the findings of this study are available from the corresponding author Abe, KC on request by email [email protected].

Additional information

Funding

This work was supported by National Council for Scientific and Technological Development (CNPq) – process number 308378/2021-0.

Notes on contributors

Karina Camasmie Abe

Karina Camasmie Abe has a bachelor’s degree in Biomedicine and Chemistry. She works as a professor at Cruzeiro do Sul University and has a postdoctoral fellow in the interdisciplinary area of Integrated Environmental Health, with emphasis on Health Economics, at the Federal University of São Paulo (UNIFESP) in collaboration with the Polytechnic Institute of Porto (IPP- Portugal). She holds a doctorate from the same University, in the area of Health Management and Technologies.

Matilde Alexandra Rodrigues

Matilde Alexandra Rodrigues works as adjunct Professor in the Technical-Scientific area of Environmental Health at the Escola Superior de Saúde – IPP. She is a researcher at the Center for Research in Health and Environment, Escola Superior de Saúde | P. Porto, and collaborator of the ALGORITMI Research Center in the research line “Industrial Engineering and Management (IEM)”, “Ergonomics and Human Factors” group, University of Minho, as well as the Research Center in Rehabilitation (CIR), Escola Superior de Saúde | P. Porto. She has a degree in Environmental Health from the Polytechnic Institute of Porto, a master's degree in Human Engineering (Ergonomics and Human Factors) from the University of Minho and a PhD in Industrial and Systems Engineering from the same institution.

Simone Georges El Khouri Miraglia

Simone Georges El Khouri Miraglia is an engineer. She holds a BSc and a MSc degrees from the Polytechnic School of the University of São Paulo (Poli-USP), where she developed a dissertation on transportation and fuels impacts on air pollution. She holds a PhD from the Medical School of the University of São Paulo (FM-USP), where she wrote a thesis on a new approach for DALY health indicator and cost estimation for the air pollution health effects for São Paulo and a Pos-Doctorate focusing on the “Environmental Valuation of the Health Impacts due to Atmospheric Pollution in São Paulo, Brazil”. Mr Miraglia has a degree of full professor obtained in 2019. Studies impacts of air pollution on health, environmental and health costs, Health Impact Assessment (HIA) and climate change. Since 2009 Simone Miraglia is a professor in the Federal University of São Paulo (UNIFESP) where she has achieved a position which enables her to develop her research with focus on health indicators and valuation estimates for urban environmental pollution impacts. Mrs Miraglia has developed a research of the use of Health Impact Assessment (HIA) in Brazil funded by the Brazilian Ministry of Health. Mrs Miraglia has developed a project concerning Climate Change Health Effects funded by FAPESP which also models economic impacts considering São Paulo urban center.