Temporal patterns and trends of surface ozone concentrations over Portugal

2021 ◽  
Author(s):  
Carla Gama ◽  
Alexandra Monteiro ◽  
Myriam Lopes ◽  
Ana Isabel Miranda
Keyword(s):  
Air Quality ◽  
Iberian Peninsula ◽  
Human Health ◽  
Temporal Variability ◽  
Urban Areas ◽  
Surface Ozone ◽  
Quality Data ◽  
Ozone Concentrations ◽  
Long Term Study

<p>Tropospheric ozone (O<sub>3</sub>) is a critical pollutant over the Mediterranean countries, including Portugal, due to systematic exceedances to the thresholds for the protection of human health. Due to the location of Portugal, on the Atlantic coast at the south-west point of Europe, the observed O<sub>3</sub> concentrations are very much influenced not only by local and regional production but also by northern mid-latitudes background concentrations. Ozone trends in the Iberian Peninsula were previously analysed by Monteiro et al. (2012), based on 10-years of O<sub>3</sub> observations. Nevertheless, only two of the eleven background monitoring stations analysed in that study are located in Portugal and these two stations are located in Porto and Lisbon urban areas. Although during pollution events O<sub>3</sub> levels in urban areas may be high enough to affect human health, the highest concentrations are found in rural locations downwind from the urban and industrialized areas, rather than in cities. This happens because close to the sources (e.g., in urban areas) freshly emitted NO locally scavenges O<sub>3</sub>. A long-term study of the spatial and temporal variability and trends of the ozone concentrations over Portugal is missing, aiming to answer the following questions:</p><p>-           What is the temporal variability of ozone concentrations?</p><p>-           Which trends can we find in observations?</p><p>-           How were the ozone spring maxima concentrations affected by the COVID-19 lockdown during spring 2020?</p><p>In this presentation, these questions will be answered based on the statistical analysis of O<sub>3</sub> concentrations recorded within the national air quality monitoring network between 2005 and 2020 (16 years). The variability of the surface ozone concentrations over Portugal, on the timescales from diurnal to annual, will be presented and discussed, taking into account the physical and chemical processes that control that variability. Using the TheilSen function from the OpenAir package for R (Carslaw and Ropkins 2012), which quantifies monotonic trends and calculates the associated p-value through bootstrap simulations, O<sub>3</sub> concentration long-term trends will be estimated for the different regions and environments (e.g., rural, urban).  Moreover, taking advantage of the unique situation provided by the COVID-19 lockdown during spring 2020, when the government imposed mandatory confinement and citizens movement restriction, leading to a reduction in traffic-related atmospheric emissions, the role of these emissions on ozone levels during the spring period will be studied and presented.</p><p> </p><p>Carslaw and Ropkins, 2012. Openair—an R package for air quality data analysis. Environ. Model. Softw. 27-28,52-61. https://doi.org/10.1016/j.envsoft.2011.09.008</p><p>Monteiro et al., 2012. Trends in ozone concentrations in the Iberian Peninsula by quantile regression and clustering. Atmos. Environ. 56, 184-193. https://doi.org/10.1016/j.atmosenv.2012.03.069</p>

scholarly journals Atmospheric aerosols and their influence on air quality in urban areas

2006 ◽  
Vol 4 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Mirjana Tasic ◽  
Slavica Rajsic ◽  
Velibor Novakovic ◽  
Zoran Mijic
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Atmospheric Aerosols ◽  
Urban Areas ◽  
Ground Level ◽  
Urban Atmosphere ◽  
Basic Knowledge ◽  
Pm10 And Pm2.5 ◽  
Air Quality Assessment

The quality and pollution of air and its impact on the environment and particularly on human health, is an issue of significant public and governmental concern. The emission of the main air pollutants (sulfur dioxide, nitrogen oxides) has declined significantly but the trends in concentrations of a particulate matter are less clear and this pollutant still pose a risk to human health. The studies on the quality of air in urban atmosphere related to suspended particles PM10 and PM2.5, and first measurements of their mass concentrations have been initiated in our country in 2002, and are still in progress. The results of preliminary investigations revealed the need for the continuous and long-term systematical sampling measurements and analysis of interaction of the specific pollutants ? PM10 and PM2.5 as well as ozone, heavy metals in the ground level. Survey of some basic knowledge and features of atmospheric particles will be given and the results of air quality assessment in Belgrade will be presented as well.

scholarly journals The use of tunnel concentration profile data to determine the ratio of NO<sub>2</sub>/NO<sub>x</sub> directly emitted from vehicles

2005 ◽  
Vol 5 (6) ◽  
pp. 12723-12740 ◽  
Author(s):  
X. Yao ◽  
N. T. Lau ◽  
C. K. Chan ◽  
M. Fang
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Air Pollutants ◽  
Quality Data ◽  
Concentration Profiles ◽  
Profile Data ◽  
Annual Average ◽  
Air Quality Data ◽  
Monitoring Platform

Abstract. Recently, it is reported that primary vehicular NO2/NOx ratio to be 10–30% and primary vehicular NO2 has raised much interest and concern in the control of NO2 in urban areas. In this study, primary vehicular NO2/NOx ratio in Hong Kong was investigated based on intensive long tunnel (3.7–4 km in length) experiments where concentration profiles of air pollutants along the entire lengths of the tunnels were obtained. Long tunnels were selected because of the inherent low O3 concentrations in the partially enclosed environment. In addition the concentrations of pollutants from vehicles are high. Thus, the NO2 measured inside long tunnels would be more representative of the primary NO2 emitted by vehicles and contribution due to atmospheric transformation would be limited. This dataset was supported by a long-term on-road air quality dataset (June 2002–August 2003). Both datasets were obtained using the Mobile Real-time Air Monitoring Platform (MAP). The primary on-road vehicular NO2/NOx ratio was less than 2%, detected in the mid sections of tunnels investigated, where O3 concentration was at a minimum. In sections of the tunnels (entrance and exit) where O3 concentrations were relatively high, the NO2/NOx ratio could be as high as 19%. Long-term (annual average) on-road air quality data in open air yielded NO2/NOx ratios up to 28%. Thus, it is apparent that directly emitted NO2 from vehicles is not significant in atmospheric NO2 concentration. A simple model was used to segregate the contribution of background NO2 and transformed NO2 measured in vehicle plumes.

Changes in European surface ozone air quality over the 21st century

2020 ◽  
Author(s):  
Christoph Stähle ◽  
Harald Rieder ◽  
Monika Mayer
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Climate Model ◽  
Surface Ozone ◽  
Photochemical Reactions ◽  
Air Pollutant ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Recent Past ◽  
Target Value ◽  
Ozone Concentrations

&lt;p&gt;&lt;span&gt;Surface ozone is a criteria air pollutant, formed by photochemical reactions involving nitrogen oxides (NO&lt;/span&gt;&lt;sub&gt;&lt;span&gt;x&lt;/span&gt;&lt;/sub&gt;&lt;span&gt;) and volatile organic compounds (VOCs). Despite recent reductions in the surface ozone burden following precursor emission controls (predominantly concerning NOx) the recent European air quality report published by the European Environment Agency (EEA) highlights that to date still 17 EU member states are reporting ozone concentrations that exceed the target value set for the protection of human health (120 &amp;#181;g/m&amp;#179;, maximum daily 8-hour average (MDA8) not to be exceeded more than 25 times per year (3-year average)). In total, 20 percent of all ozone monitoring sites showed ozone concentrations exceeding the EU target value for the protection of human health, and only 5% of monitoring sites showed ozone concentrations in compliance with the more stringent WHO target value. Here we focus on past and future changes in European surface ozone abundances in a set of simulations performed with the Geophysical Fluid Dynamics Laboratory (GFDL) chemistry-climate model CM3. First, we evaluate the general model performance for the recent past by comparing model output to observations available from the EEA Airbase database. The evaluation is performed on the basis of interpolation of the historic site level observations to a grid of 2.5&amp;#176; x 2&amp;#176;, matching the dimensions of the CM3 model. Our results for the recent past show that the modelled ozone abundances are biased high compared to observations. Therefore, we apply a suite of correction techniques (quantile mapping, delta function) to obtain modelled ozone fields in agreement with observations. Emanating from remediated model data the correction functions derived are applied to transient (2006-2100) simulations following selected Representative Concentration Pathways (RCPs). Using these bias-corrected future simulations we illustrate next potential changes in future European surface ozone air pollution over the course of the 21&lt;/span&gt;&lt;sup&gt;&lt;span&gt;st&lt;/span&gt;&lt;/sup&gt;&lt;span&gt; century.&lt;/span&gt;&lt;/p&gt;

scholarly journals The Diamond League athletic series: does the air quality sparkle?

2021 ◽  
Author(s):  
James R. Hodgson ◽  
Lee Chapman ◽  
Francis D. Pope
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Performance Metrics ◽  
Urban Air Pollution ◽  
Quality Data ◽  
Performance Variation ◽  
Short And Long Term ◽  
Respiratory Conditions ◽  
Race Performance

AbstractUrban air pollution can have negative short- and long-term impacts on health, including cardiovascular, neurological, immune system and developmental damage. The irritant qualities of pollutants such as ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM) can cause respiratory and cardiovascular distress, which can be heightened during physical activity and particularly so for those with respiratory conditions such as asthma. Previously, research has only examined marathon run outcomes or running under laboratory settings. This study focuses on elite 5-km athletes performing in international events at nine locations. Local meteorological and air quality data are used in conjunction with race performance metrics from the Diamond League Athletics series to determine the extent to which elite competitors are influenced during maximal sustained efforts in real-world conditions. The findings from this study suggest that local meteorological variables (temperature, wind speed and relative humidity) and air quality (ozone and particulate matter) have an impact on athletic performance. Variation between finishing times at different race locations can also be explained by the local meteorology and air quality conditions seen during races.

scholarly journals Modelling the impact of megacities on local, regional and global tropospheric ozone and the deposition of nitrogen species

2013 ◽  
Vol 13 (24) ◽  
pp. 12215-12231 ◽  
Author(s):  
Z. S. Stock ◽  
M. R. Russo ◽  
T. M. Butler ◽  
A. T. Archibald ◽  
M. G. Lawrence ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Climate Model ◽  
Surface Ozone ◽  
Global Scale ◽  
Chemical Environment ◽  
Ozone Production ◽  
The Uk ◽  
The Impact ◽  
Local Emissions

Abstract. We examine the effects of ozone precursor emissions from megacities on present-day air quality using the global chemistry–climate model UM-UKCA (UK Met Office Unified Model coupled to the UK Chemistry and Aerosols model). The sensitivity of megacity and regional ozone to local emissions, both from within the megacity and from surrounding regions, is important for determining air quality across many scales, which in turn is key for reducing human exposure to high levels of pollutants. We use two methods, perturbation and tagging, to quantify the impact of megacity emissions on global ozone. We also completely redistribute the anthropogenic emissions from megacities, to compare changes in local air quality going from centralised, densely populated megacities to decentralised, lower density urban areas. Focus is placed not only on how changes to megacity emissions affect regional and global NOx and O3, but also on changes to NOy deposition and to local chemical environments which are perturbed by the emission changes. The perturbation and tagging methods show broadly similar megacity impacts on total ozone, with the perturbation method underestimating the contribution partially because it perturbs the background chemical environment. The total redistribution of megacity emissions locally shifts the chemical environment towards more NOx-limited conditions in the megacities, which is more conducive to ozone production, and monthly mean surface ozone is found to increase up to 30% in megacities, depending on latitude and season. However, the displacement of emissions has little effect on the global annual ozone burden (0.12% change). Globally, megacity emissions are shown to contribute ~3% of total NOy deposition. The changes in O3, NOx and NOy deposition described here are useful for quantifying megacity impacts and for understanding the sensitivity of megacity regions to local emissions. The small global effects of the 100% redistribution carried out in this study suggest that the distribution of emissions on the local scale is unlikely to have large implications for chemistry–climate processes on the global scale.

scholarly journals Impacts of changes in land use and land cover on atmospheric chemistry and air quality over the 21st century

2011 ◽  
Vol 11 (5) ◽  
pp. 15469-15495 ◽  
Author(s):  
S. Wu ◽  
L. J. Mickley ◽  
J. O. Kaplan ◽  
D. J. Jacob
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Land Use Change ◽  
Land Cover ◽  
21St Century ◽  
Secondary Organic Aerosols ◽  
Surface Ozone ◽  
Organic Aerosols ◽  
Ozone Concentrations ◽  
Anthropogenic Land Use

Abstract. The effects of future land use and land cover change on the chemical composition of the atmosphere and air quality are largely unknown. To investigate the potential effects associated with future changes in vegetation driven by atmospheric CO2 concentrations, climate, and anthropogenic land use over the 21st century, we performed a series of model experiments combining a general circulation model with a dynamic global vegetation model and an atmospheric chemical-transport model. Our results indicate that climate- and CO2-induced changes in vegetation composition and density could lead to decreases in summer afternoon surface ozone of up to 10 ppb over large areas of the northern mid-latitudes. This is largely driven by the substantial increases in ozone dry deposition associated with changes in the composition of temperate and boreal forests where conifer forests are replaced by those dominated by broadleaf tree types, as well as a CO2-driven increase in vegetation density. Climate-driven vegetation changes over the period 2000–2100 lead to general increases in isoprene emissions, globally by 15 % in 2050 and 36 % in 2100. These increases in isoprene emissions result in decreases in surface ozone concentrations where the NOx levels are low, such as in remote tropical rainforests. However, over polluted regions, such as the northeastern United States, ozone concentrations are calculated to increase with higher isoprene emissions in the future. Increases in biogenic emissions also lead to higher concentrations of secondary organic aerosols, which increase globally by 10 % in 2050 and 20 % in 2100. Surface concentrations of secondary organic aerosols are calculated to increase by up to 1 μg m−3 for large areas in Eurasia. When we use a scenario of future anthropogenic land use change, we find less increase in global isoprene emissions due to replacement of higher-emitting forests by lower-emitting cropland. The global atmospheric burden of secondary organic aerosols changes little by 2100 when we account for future land use change, but both secondary organic aerosols and ozone show large regional changes at the surface.

scholarly journals Emission of fine particles (PM2.5) from residential biomass combustion in Croatia and how to reduce it

2020 ◽  
Vol 7 (2) ◽  
pp. 84-94
Author(s):  
Mirela Poljanac
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Urban Areas ◽  
Fine Particles ◽  
Biomass Combustion ◽  
Rural And Urban Areas ◽  
Wood Burning ◽  
Rural And Urban ◽  
The Impact ◽  
Pm2.5 Emissions

Wood burning in residential appliances is very represented in the Republic of Croatia. It is a main or an additional form of heating for many households in rural and urban areas and is therefore an important source of air pollution. The choice of energy and the combustion appliance used in home have a significant impact on PM2.5 emissions. The paper informs the reader about PM2.5 emissions, their main sources and impacts on human health, environment, climate, air quality, and the reason why PM2.5 emissions from residential wood burning are harmful. Paper also gives an overview of spatial PM2.5 emission distribution in Croatia, their five air quality zones and four agglomerations. The paper analyses the sources and their contribution to PM2.5 emissions with the relevance of PM2.5 emissions from residential plants, the use of fuels in residential plants and their contribution to PM2.5 emissions and PM2.5 emissions by fuel combustion technologies in residential sector. Appropriate strategies, policies, and actions to reduce the impact of residential biomass (wood) burning on the environment, air quality and human health are considered.

scholarly journals Explicit Modeling of Meteorological Explanatory Variables in Short-Term Forecasting of Maximum Ozone Concentrations via a Multiple Regression Time Series Framework

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1304
Author(s):  
Sigfrido Iglesias-Gonzalez ◽  
Maria E. Huertas-Bolanos ◽  
Ivan Y. Hernandez-Paniagua ◽  
Alberto Mendoza
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Multiple Regression ◽  
Urban Areas ◽  
Moving Average ◽  
Time Series Forecasting ◽  
Air Pollutant ◽  
Short Term ◽  
Ozone Level ◽  
Ozone Concentrations

Statistical time series forecasting is a useful tool for predicting air pollutant concentrations in urban areas, especially in emerging economies, where the capacity to implement comprehensive air quality models is limited. In this study, a general multiple regression with seasonal autoregressive moving average errors model was estimated and implemented to forecast maximum ozone concentrations with a short time resolution: overnight, morning, afternoon and evening. In contrast to a number of short-term air quality time series forecasting applications, the model was designed to explicitly include the effects of meteorological variables on the ozone level as exogenous variables. As the application location, the model was constructed with data from five monitoring stations in the Monterrey Metropolitan Area of Mexico. The results show that, together with structural stochastic components, meteorological parameters have a significant contribution for obtaining reliable forecasts. The resulting model is an interpretable, useful and easily implementable model for forecasting ozone maxima. Moreover, it proved to be consistent with the general dynamics of ozone formation and provides a suitable platform for forecasting, showing similar or better performance compared to models in other existing studies.

scholarly journals Air Pollution Prediction Using Long Short-Term Memory (LSTM) and Deep Autoencoder (DAE) Models

2020 ◽  
Vol 12 (6) ◽  
pp. 2570 ◽  
Author(s):  
Thanongsak Xayasouk ◽  
HwaMin Lee ◽  
Giyeol Lee
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Short Term Memory ◽  
Batch Size ◽  
Quality Data ◽  
Short Term ◽  
Optimal Learning ◽  
Term Memory ◽  
Batch Sizes ◽  
Long Short Term Memory

Many countries worldwide have poor air quality due to the emission of particulate matter (i.e., PM10 and PM2.5), which has led to concerns about human health impacts in urban areas. In this study, we developed models to predict fine PM concentrations using long short-term memory (LSTM) and deep autoencoder (DAE) methods, and compared the model results in terms of root mean square error (RMSE). We applied the models to hourly air quality data from 25 stations in Seoul, South Korea, for the period from 1 January 2015, to 31 December 2018. Fine PM concentrations were predicted for the 10 days following this period, at an optimal learning rate of 0.01 for 100 epochs with batch sizes of 32 for LSTM model, and DAEs model performed best with batch size 64. The proposed models effectively predicted fine PM concentrations, with the LSTM model showing slightly better performance. With our forecasting model, it is possible to give reliable fine dust prediction information for the area where the user is located.

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