Air quality assessment for Portugal

Evidence for an association of prenatal exposure to particulate matter with clinical severity of Autism Spectrum Disorder

Early-life exposure to air pollutants, including ozone (O₃), particulate matter (PM_2.5 or PM₁₀, depending on diameter of particles), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) has been suggested to contribute to the etiology of Autism Spectrum Disorder (ASD). In this study, we used air quality monitoring data to examine whether mothers of children with ASD were exposed to high levels of air pollutants during critical periods of pregnancy, and if higher exposure levels may lead to a higher clinical severity in their offspring. We used public data from the Portuguese Environment Agency to estimate exposure to these pollutants during the first, second and third trimesters of pregnancy, full pregnancy and first year of life of the child, for 217 subjects with ASD born between 2003 and 2016. These subjects were stratified in two subgroups according to clinical severity, as defined by the Autism Diagnostic Observational Schedule (ADOS). For all time periods, the average levels of PM_2.5, PM₁₀ and NO₂ to which the subjects were exposed were within the admissible levels defined by the European Union. However, a fraction of these subjects showed exposure to levels of PM_2.5 and PM₁₀ above the admissible threshold. A higher clinical severity was associated with higher exposure to PM_2.5 (p = 0.001), NO₂ (p = 0.011) and PM₁₀ (p = 0.041) during the first trimester of pregnancy, when compared with milder clinical severity. After logistic regression, associations with higher clinical severity were identified for PM_2.5 exposure during the first trimester (p = 0.002; OR = 1.14, 95%CI: 1.05-1.23) and full pregnancy (p = 0.04; OR = 1.07, 95%CI: 1.00-1.15) and for PM₁₀ (p = 0.02; OR = 1.07, 95%CI: 1.01-1.14) exposure during the third trimester. Exposure to PM is known to elicit neuropathological mechanisms associated with ASD, including neuroinflammation, mitochondrial disruptions, oxidative stress and epigenetic changes. These results offer new insights on the impact of early-life exposure to PM in ASD clinical severity.

Association between respiratory hospital admissions and air quality in Portugal: A count time series approach

Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.

The impact of COVID-19 on air quality levels in Portugal: A way to assess traffic contribution

The pandemic caused by coronavirus COVID-19 is having a worldwide impact that affects health, the economy and indirectly affects the air pollution in cities. In Portugal, the number of cases increased continually (32700 confirmed cases as of May 31, 2020), which has affected the health system and caused movement restrictions which in turn affects the air pollution in the country. This article analyses the indirect effect produced by this pandemic on air pollution in Portugal, by comparison of data from a period of movement restriction of the citizens by the government - COVID lockdown period (March-May 2020) with data from baseline conditions (mean of the mirrored periods from the five previous years (March-May from 2015 to 2019)). Air quality data - in particular NO₂ and PM₁₀ hourly concentration - from more than 20 monitoring stations spread over mainland Portugal was used to perform this evaluation. The mean reduction observed on pollutant concentrations was higher for NO₂ (41%) than for PM₁₀ (18%). For NO₂, mean reductions were more significant in traffic (reaching values higher than 60% in some monitoring stations) and background urban sites than in rural stations. The reduction of NO₂ concentration observed in traffic sites were compared to the estimation of traffic contribution by the incremental method, suggesting that this latter approach is not consistent (lower in same sites and higher in others) and alerting to the careful use of this approach in future works.

Comparison of Methodologies for Assessing Desert Dust Contribution to Regional PM10 and PM2.5 Levels: A One-Year Study Over Portugal

Desert dust outbreaks may affect air quality. This study estimates the importance of African dust contribution to the PM10 and PM2.5 concentrations observed in rural regional background sites in Portugal. Desert dust contribution is evaluated by two different approaches: A measurement-approach methodology based on the monthly moving 40th percentile, and a model-approach methodology based on WRF-CHIMERE simulations, whose performance is also assessed within this work. Several desert dust episodes affected atmospheric aerosols in the planetary boundary layer over Portugal during 2016. Their intensity was variable, with at least two events (21–22 February and 27–28 October) contributing to exceedances to the PM10 daily limit value defined in the European Air Quality Directive. African dust contributions obtained for the year 2016 with the measurement-approach methodology are higher than the ones simulated by WRF-CHIMERE. Contributions to PM10 and to PM2.5 concentrations range from 0 to 90 µg m−3 and from 0 to 30 µg m−3, respectively, in most of the regions and days. Caution must be employed when using measurement-approach methodologies to quantify dust contributions to PM levels when forest fires occur simultaneously with the long-range transport of desert dust, as happened in August 2016.

Assessment of source contribution to air quality in an urban area close to a harbor: Case-study in Porto, Portugal

Several harbors, like the Port of Leixões (Porto, Portugal), are located near urban and industrial areas, places where residential urban areas, highways and the refinery industry coexist. The need for assessing the contribution of the port to the air quality in its vicinity around the port is the motivation for the present study. This contribution was investigated using a numerical modelling approach based on the web-based research screening tool C-PORT. The impact of the meteorological conditions (namely atmospheric stability and wind direction) was first evaluated, and the most critical conditions for pollutants dispersion were identified. The dominant wind direction, from WSW, was responsible for the transport of pollutants over the surrounding urban area, which was potentiated by the diurnal sea breeze circulation. Multiple scenario runs were then performed to quantify the contribution of each emission sector/activity (namely maritime emissions; port activities; road traffic and refinery) to the ambient air quality. The multiple scenario runs indicated that land-based emission sources at the Port (including trucks, railways, cargo handling equipment and bulk material stored) were the major contributors (approximately 80%) for the levels of surface PM₁₀ concentrations over the study area. Whereas, the main drivers of NO_X concentrations were docked ships, responsible for 55-73% of the total NO_X concentrations.

How important are maritime emissions for the air quality: At European and national scale

Due to its dependence on fossil fuel combustion, emissions from the marine transport sector can significantly contribute to air pollution. This work aims to evaluate the impact of maritime transport emissions on air quality in Portugal using a numerical air quality modelling approach, with high-resolution emission data. Emissions from the European TNO inventory were compiled and pre-processed at hourly and high spatial (∼3 × 3 km²) resolutions. Scenarios with and without these maritime emissions were then simulated with the WRF-CHIMERE modelling system, extensively tested and validated for Portugal domain, in order to evaluate their impact on air quality. A simulation was performed for one year (2016) and the resulting differences were analysed in terms of spatial distribution, time series and deltas. The main deltas for NO₂ and PM10 are located over international shipping routes and major ports, while O₃ concentrations are impacted in a larger area. The modelling results also indicate that shipping emissions are responsible for deltas in the concentration of NO₂ higher than 20% over specific urban areas located in the west coast of Portugal, and less than 5% for PM10. For O₃ the relative contribution is low (around 2%) but this contribution is also observed at locations more than 50 km from the coast.

A cost-efficiency and health benefit approach to improve urban air quality

When ambient air quality standards established in the EU Directive 2008/50/EC are exceeded, Member States are obliged to develop and implement Air Quality Plans (AQP) to improve air quality and health. Notwithstanding the achievements in emission reductions and air quality improvement, additional efforts need to be undertaken to improve air quality in a sustainable way - i.e. through a cost-efficiency approach. This work was developed in the scope of the recently concluded MAPLIA project "Moving from Air Pollution to Local Integrated Assessment", and focuses on the definition and assessment of emission abatement measures and their associated costs, air quality and health impacts and benefits by means of air quality modelling tools, health impact functions and cost-efficiency analysis. The MAPLIA system was applied to the Grande Porto urban area (Portugal), addressing PM10 and NOx as the most important pollutants in the region. Four different measures to reduce PM10 and NOx emissions were defined and characterized in terms of emissions and implementation costs, and combined into 15 emission scenarios, simulated by the TAPM air quality modelling tool. Air pollutant concentration fields were then used to estimate health benefits in terms of avoided costs (external costs), using dose-response health impact functions. Results revealed that, among the 15 scenarios analysed, the scenario including all 4 measures lead to a total net benefit of 0.3M€·y(-1). The largest net benefit is obtained for the scenario considering the conversion of 50% of open fire places into heat recovery wood stoves. Although the implementation costs of this measure are high, the benefits outweigh the costs. Research outcomes confirm that the MAPLIA system is useful for policy decision support on air quality improvement strategies, and could be applied to other urban areas where AQP need to be implemented and monitored.

Assessment of regional air quality by a concentration-dependent Pollution Permeation Index

Although air quality monitoring networks have been greatly improved, interpreting their expanding data in both simple and efficient ways remains challenging. Therefore, needed are new analytical methods. We developed such a method based on the comparison of pollutant concentrations between target and circum areas (circum comparison for short), and tested its applications by assessing the air pollution in Jing-Jin-Ji, Yangtze River Delta, Pearl River Delta and Cheng-Yu, China during 2015. We found the circum comparison can instantly judge whether a city is a pollution permeation donor or a pollution permeation receptor by a Pollution Permeation Index (PPI). Furthermore, a PPI-related estimated concentration (original concentration plus halved average concentration difference) can be used to identify some overestimations and underestimations. Besides, it can help explain pollution process (e.g., Beijing’s PM_2.5 maybe largely promoted by non-local SO₂) though not aiming at it. Moreover, it is applicable to any region, easy-to-handle, and able to boost more new analytical methods. These advantages, despite its disadvantages in considering the whole process jointly influenced by complex physical and chemical factors, demonstrate that the PPI based circum comparison can be efficiently used in assessing air pollution by yielding instructive results, without the absolute need for complex operations.

Nitrogen oxides and ozone in Portugal: trends and ozone estimation in an urban and a rural site

This study provides an analysis of the spatial distribution and trends of NO, NO2 and O3 concentrations in Portugal between 1995 and 2010. Furthermore, an estimation model for daily ozone concentrations was developed for an urban and a rural site. NO concentration showed a significant decreasing trend in most urban stations. A decreasing trend in NO2 is only observed in the stations with less influence from emissions of primary NO2. Several stations showed a significant upward trend in O3 as a result of the decrease in the NO/NO2 ratio. In the northern rural region, ozone showed a strong correlation with wind direction, highlighting the importance of long-range transport. In the urban site, most of the variance is explained by the NO2/NOX ratio. The results obtained by the ozone estimation model in the urban site fit 2013 observed data. In the rural site, the estimated ozone during extreme events agrees with observed concentration.

Impact of forest biomass residues to the energy supply chain on regional air quality

The increase of the share of renewable energy in Portugal can be met from different sources, of which forest biomass residues (FBR) can play a main role. Taking into account the demand for information about the strategy of FBR to energy, and its implications on the Portuguese climate policy, the impact of energy conversion of FBR on air quality is evaluated. Three emission scenarios were defined and a numerical air quality model was selected to perform this evaluation. The results reveal that the biomass thermal plants contribute to an increment of the pollutant concentrations in the atmosphere, however restricted to the surrounding areas of the thermal plants, and most significant for NO₂ and O₃.

Emission inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain)

Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO₂. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.

Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal

Despite the increasing concern given to air quality in urban and industrial areas in recent years, particular emphasis on regulation, control, and reduction of air pollutant emissions is still necessary to fully characterize the chain emissions-air quality-exposure-dose-health effects, for specific sources. The Estarreja region was selected as a case study because it has one of the largest chemical industrial complexes in Portugal that has been recently expanded, together with a growing urban area with an interesting location in the Portuguese coastland and crossed by important road traffic and rail national networks. This work presents the first air quality assessment for the region concerning pollutant emissions and meteorological and air quality monitoring data analysis, over the period 2000-2009. This assessment also includes a detailed investigation and characterization of past air pollution episodes for the most problematic pollutants: ozone and PM10. The contribution of different emission sources and meteorological conditions to these episodes is investigated. The stagnant meteorological conditions associated with local emissions, namely industrial activity and road traffic, are the major contributors to the air quality degradation over the study region. A set of measures to improve air quality--regarding ozone and PM10 levels--is proposed as an air quality management strategy for the study region.

Climate change and environmental impacts on maternal and newborn health with focus on Arctic populations

BACKGROUND

In 2007, the Intergovernmental Panel on Climate Change (IPCC) presented a report on global warming and the impact of human activities on global warming. Later the Lancet commission identified six ways human health could be affected. Among these were not environmental factors which are also believed to be important for human health. In this paper we therefore focus on environmental factors, climate change and the predicted effects on maternal and newborn health. Arctic issues are discussed specifically considering their exposure and sensitivity to long range transported contaminants.

METHODS

Considering that the different parts of pregnancy are particularly sensitive time periods for the effects of environmental exposure, this review focuses on the impacts on maternal and newborn health. Environmental stressors known to affects human health and how these will change with the predicted climate change are addressed. Air pollution and food security are crucial issues for the pregnant population in a changing climate, especially indoor climate and food security in Arctic areas.

RESULTS

The total number of environmental factors is today responsible for a large number of the global deaths, especially in young children. Climate change will most likely lead to an increase in this number. Exposure to the different environmental stressors especially air pollution will in most parts of the world increase with climate change, even though some areas might face lower exposure. Populations at risk today are believed to be most heavily affected. As for the persistent organic pollutants a warming climate leads to a remobilisation and a possible increase in food chain exposure in the Arctic and thus increased risk for Arctic populations. This is especially the case for mercury. The perspective for the next generations will be closely connected to the expected temperature changes; changes in housing conditions; changes in exposure patterns; predicted increased exposure to Mercury because of increased emissions and increased biological availability.

CONCLUSIONS

A number of environmental stressors are predicted to increase with climate change and increasingly affecting human health. Efforts should be put on reducing risk for the next generation, thus global politics and research effort should focus on maternal and newborn health.

Procedures for estimation of modelling uncertainty in air quality assessment

The main objectives of this work focus, firstly, on a review of the current existent methodologies to estimate air quality modelling uncertainty, and, secondly, in the preparation of guidelines for modelling uncertainty estimation, which can be used by local and regional authorities responsible for air quality management. From the application exercise, it was concluded that it is possible to define a subset of statistical parameters able to reproduce the general uncertainties estimation. Concerning the quality indicators defined by EU directives, the results show that the legislated uncertainty estimation measures are ambiguous and inadequate in several aspects, mainly in what concerns the error measures for hourly and daily indicators based on the highest observed concentration. A relative error at the percentile correspondent to the allowed number of exceedances of the limit value was suggested and tested, showing that is a more robust and appropriate parameter for model performance evaluation.