Evolution of NO₂ levels in Spain from 1996 to 2012

Evaluating the influence of air pollution on solar radiation observations over the coastal region of Alicante (Southeastern Spain)

The present study evaluates ground-based downward surface shortwave radiation (R_s) over the coastal region of Alicante (Southeastern Spain). Hourly measurements collected over the eleven-year period 2010-2020 are used. Two weather stations located over the region capital, Alicante, have been selected as representative of urban and suburban typologies. Two additional weather stations far from the city have been selected representing rural typologies. R_s is significantly reduced over the urban station during the morning hours within the winter season compared to the observations recorded over the suburban and rural stations, with a global mean difference of -81 and -120 W/m² at 10 LT, respectively. However, no significant differences are obtained during the midday sun, with a global mean difference of -20 W/m² between the urban and rural stations. With the aim of explaining these differences, the current paper investigates the relationship between R_s and different air pollutants: NO_x, SO₂, and fine particulate matter (PM_2.5 and PM₁₀) as well as the wind field measured at the urban and suburban stations. The results found in this work point towards a close relationship between R_s and NO_x concentrations annual cycles, which are also influenced by the prevailing wind circulations observed over the study area. A global mean NO_x concentration of 107 µg/m³ is observed over the urban station at 10 LT during the winter season. In contrast, these high concentrations are significantly reduced over the suburban station, with global mean value of 40 µg/m³ at 10 LT, for this period of the year.

16 Years (2006-2021) of Surface Ozone Measurements in Córdoba (Southern Spain): Trends and the Impact of the COVID-19 Lockdown

Surface ozone concentrations (O₃) during the period 2006-2021 are analysed at Córdoba city (southern Iberian Peninsula) in suburban and urban sampling sites. The aims are to present the levels and temporal variations, to explore trends and to quantity the variation in O₃ concentrations in the context of the COVID-19 lockdown. The O₃ means are higher in the suburban station (62 µg m^-3 and 51.3 µg m^-3), being the information level threshold only exceeded twice during this period. The daily evolution shows a maximum at about 17:00 UTC, whereas the minimum is reached at about 9:00 UTC, with higher levels in the suburban station. The seasonal evolution of this daily cycle also presents monthly differences in shape and intensity between stations. The trends are analysed by means of daily averages and daily 5th and 95th percentiles, and they show a similar increase in all of these parameters, with special emphasis on the daily P95 concentrations, with 0.27 µg m^-3 year^-1 and 0.24 µg m^-3 year^-1. Finally, the impact of the COVID-19 lockdown shows a decline in O₃ concentrations over 10%.

Analysis of emissions-driven changes in the oxidation capacity of the atmosphere in Europe

Anthropogenic emissions in Europe have been gradually reduced thanks to a combination of factors, including restrictive regulation and policy implementation, fuel switching, technological developments, and improved energy efficiencies. Many measures have been specifically introduced to meet the annual and hourly limit value of NO₂ for the protection of human health, mainly targeting traffic emissions. Due to NO_X reduction policies in Europe, NO₂ levels have generally declined, but O₃ concentrations have been found to increase. This phenomenon would cause changes in the oxidant capacity of the atmosphere, altering the concentration of tropospheric oxidants in urban areas. The Community Multiscale Air Quality (CMAQ) modelling system has been used to study concentration changes of NO₂, O₃ and the main radicals in Europe between 2007 and 2015 for two months representatives of winter and summer conditions (January and July). In addition to describing the general situation in Europe, variations in pollutants along with NO_X emission changes over 67 large European cities have been analysed by means of statistical methods. NO_X emissions and NO₂ concentrations decreased in both seasons during the period in all the selected cities. In most of them O₃ concentrations increased in winter but decreased in summer. The concentration of the OH radical, the main oxidant during the daytime, shows an increase in winter. This is also the case for the main cities in summer although we found a general decrease in continent for this season. The NO₃ radical, the main night-time oxidant, was found to increase in winter and decrease in summer. HNO₃ shows a concentration decline in both seasons. The studied cities are classified in five groups by means of k-mean clustering procedure. We identified five groups with specific patterns, suggesting that the oxidant capacity of the European urban atmospheres has reacted differently to NO_X emission abatement policies.

Bidirectional convolutional LSTM for the prediction of nitrogen dioxide in the city of Madrid

Nitrogen dioxide is one of the pollutants with the most significant health effects. Advanced information on its concentration in the air can help to monitor and control further consequences more effectively, while also making it easier to apply preventive and mitigating measures. Machine learning technologies with available methods and capabilities, combined with the geospatial dimension, can perform predictive analyses with higher accuracy and, as a result, can serve as a supportive tool for productive management. One of the most advanced machine learning algorithms, Bidirectional convolutional LSTM, is being used in ongoing work to predict the concentration of nitrogen dioxide. The model has been validated to perform more accurate spatiotemporal analysis based on the integration of temporal and geospatial factors. The analysis was carried out according to two scenarios developed on the basis of selected features using data from the city of Madrid for the periods January-June 2019 and January-June 2020. Evaluation of the model's performance was conducted using the Root Mean Square Error and the Mean Absolute Error which emphasises the superiority of the proposed model over the reference models. In addition, the significance of a feature selection technique providing improved accuracy was underlined. In terms of execution time, due to the complexity of the Bidirectional convolutional LSTM architecture, convergence and generalisation of the data took longer, resulting in the superiority of the reference models.

Formaldehyde, acrolein and other carbonyls in dwellings of university students. Levels and source characterization

Fifteen carbonyl compounds were investigated in the living rooms and bedrooms of 25 university student flats in the urban area of Ciudad Real (Central Southern Spain) in wintertime. Carbonyls were sampled using Radiello ® passive samplers refilled in the laboratory according to the method described in ISO 16000-3 Standard. The most abundant carbonyls in the living rooms and bedrooms were formaldehyde, acetone, acetaldehyde, hexaldehyde and butyraldehyde. The median concentration levels in the living rooms and bedrooms were: 28.6 and 34.2 μg m^-3 for formaldehyde, 18.3 and 23.1 μg m^-3 for acetone, 14.3 and 15.8 μg m^-3 for acetaldehyde, 11.4 and 14.1 μg m^-3 for hexaldehyde and 10.8 and 12.4 μg m^-3 for butyraldehyde. The median concentration of formaldehyde, benzaldehyde, valeraldehyde and hexaldehyde was significantly higher in the bedrooms than in the living rooms. Indoor concentrations were significantly higher than outdoor concentrations for all carbonyl measured, indicating that sources in the indoor environment are prevailing in all flats. Principal component analysis, multiple linear regressions and Spearman correlation coefficients were used to investigate the origin, the indoor pollutants determinants and to establish common sources between carbonyls. Eight components were extracted from the application of PCA to the indoor and outdoor measurements accounting for 97.7% of the total variance. Formaldehyde, acetone, acetaldehyde and acrolein presented different indoor sources. In the multiple linear regression analysis, higher formaldehyde concentrations were found in those living rooms with wood floor and smoking was positively associated to acetone, propionaldehyde, benzaldehyde and isovaleraldehyde. Formaldehyde, acetaldehyde, acrolein, acetone, propionaldehyde and benzaldehyde concentrations were compared with relevant international guidelines, being their concentrations below recommended values except acrolein, where all measured flats exceeded the reference levels; it would be important to focus on the characterization of emission sources of acrolein in indoor air in order to minimise the exposure and health risk.

Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain

While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020-1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future.

Exploring the linkage between seasonality of environmental factors and COVID-19 waves in Madrid, Spain

Like several countries, Spain experienced a multi wave pattern of COVID-19 pandemic over more than one year period, between spring 2020 and spring 2021. The transmission of SARS-CoV-2 pandemics is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation.This study aims to quantify the impact of climate and air pollution factors seasonality on incidence and severity of COVID-19 disease waves in Madrid metropolitan region in Spain. We employed descriptive statistics and Spearman rank correlation tests for analysis of daily in-situ and geospatial time-series of air quality and climate data to investigate the associations with COVID-19 incidence and lethality in Madrid under different synoptic meteorological patterns. During the analyzed period (1 January 2020-28 February 2021), with one month before each of three COVID-19 waves were recorded anomalous anticyclonic circulations in the mid-troposphere, with positive anomalies of geopotential heights at 500 mb and favorable stability conditions for SARS-CoV-2 fast diffusion. In addition, the results reveal that air temperature, Planetary Boundary Layer height, ground level ozone have a significant negative relationship with daily new COVID-19 confirmed cases and deaths. The findings of this study provide useful information to the public health authorities and policymakers for optimizing interventions during pandemics.

Identifying the driving factors of NO2 pollution of One Belt One Road countries: satellite observation technique and dynamic spatial panel data analysis

To recover the global economy, China in 2013 called for a new global strategy, namely, "One Belt and One Road Initiative" (BRI), which aims at reinforcing regional economic cooperation, enhancing regional collaboration of economic policy, and realizing the goal of rapid economic development of member countries. Accelerating industrialization not only has been recognized as an effective way to stimulate economic development, but also lead to the serious issue of environmental pollution, which challenges the environmental sustainability. In this study, we focus on the industrializing region as a study area to investigate the driving factors of environmental pollution. Technically, we utilized satellite observation technique to obtain NO₂ columns data to denote environmental pollution and then applied dynamic spatial panel data models to evaluate what affects NO₂ pollution levels. The findings are the following. (1) NO₂ pollution exhibits significant and positive spatial autocorrelation, indicating spatial spillovers of NO₂ pollution. (2) Lebanon, Bangladesh, Kyrgyzstan, and India experienced the largest increase of NO₂ pollution while NO₂ pollution in Singapore, Hungary, Greece, and Ukraine was substantially reduced. (3) The results of the dynamic spatial panel data models show that both the time dynamics effects and the spatial spillover effects are found to be significant and positive. In other words, both effects should be considered. Population is the foremost contributor to increase NO₂ pollution while urbanization is an effective way to reduce pollution. An EKC relationship between NO₂ pollution and per capita income was verified. Besides, industrialization, foreign direct investment, and trade openness have positive impacts on NO₂ pollution.

Impact of SARS-CoV-2 lockdown and de-escalation on air-quality parameters

The SARS-CoV-2 health crisis has temporarily forced the lockdown of entire countries. This work reports the short-term effects on air quality of such unprecedented paralysis of industry and transport in different continental cities in Spain, one of the countries most affected by the virus and with the hardest confinement measures. The study takes into account sites with different sizes and diverse emission sources, such as traffic, residential or industrial emissions. This work reports new field measurement data for the studied pandemic period and assesses the air quality parameters within the historic trend of each pollutant and site. Thus, 2013-2020 data series from ground-air quality monitoring networks have been analysed to find out statistically significant changes in atmospheric pollutants during March-June 2020 due to this sudden paralysis of activity. The results show substantial concentration drops of primary pollutants, including NO_x, CO, BTX, NMHC and NH₃. Particulate matter changes were smaller due to the existence of other natural sources. During the lockdown the ozone patterns were different for each studied location, depending on the VOCs-NOx ratios, with concentration changes close to those expected from the historical series in each site and not statistically attributable to the health crisis effects. Finally, the gradual de-escalation and progressive increase of traffic density within cities reflects a slow recovery of primary pollutants. The results and conclusions for these cities, with different sizes and population, and specific emission sources, may serve as a behavioural model for other continental sites and help understand future crises.

Evaluation of different methods and data sources to optimise modelling of NO2 at a global scale

BACKGROUND

In countries where air pollution stations are unavailable or scarce, station measurements from other countries and atmospheric remote sensing could jointly provide information to estimate ambient air quality at a sufficiently fine resolution to study the relationship between air pollution exposure and health. Predicting NO₂ concentration globally with sufficient spatial and temporal resolution and accuracy for health studies is, however, not a trivial task. Challenges are data deficiency, in terms of NO₂ measurements and NO₂ predictors, and the development of a statistical model that can typify the regional and continental differences, such as traffic regulations, energy sources, and local weather.

OBJECTIVE

We investigated the feasibility of mapping daytime and nighttime NO₂ globally at a high spatial resolution (25 m), by including TROPOMI (TROPOspheric Monitoring Instrument) data and comparing various statistical learning techniques.

METHOD

We separated daytime (7:00 am - 9:59 pm) and nighttime (10:00 pm - 6:59 am) based on the local times. To study if one should build models for each country separately, national models in 4 selected countries (the US, China, Germany, Spain) were developed. We build the models for 2017 and used 3636 stations. Seven statistical learning techniques were applied and the impact of the predictors, model fitting, and predicting accuracy was compared between different techniques, national models, national and global models, and models with and without including the NO₂ vertical column density retrieved from TROPOMI.

RESULT AND CONCLUSION

The ensemble tree-based methods obtained higher accuracy compared to the linear regression-based methods in national and global models. The global tree-based methods obtained similar accuracy to national models. Different spatial prediction patterns are observed even when the prediction accuracy is very similar. Separating between day and night can be important for more accurate air pollution exposure assessment. The TROPOMI variable is ranked as one of the most important variables in the statistical learning techniques but adding it to global models that contain other precedent remote sensing products does not improve the prediction accuracy.

Stream chemistry response to changing nitrogen and sulfur deposition in two mountain areas in the Iberian Peninsula

Sulfur (S) and nitrogen (N) increasing anthropogenic emissions in the last century has arisen wide concern on the ecological effects of S and N deposition. In this paper, we use bulk deposition and stream water measurements in the central Pyrenees (PYR-C and PYR-AT sites) and Montseny (MSY-TM0) covering different time lengths in the period 1983-2017 to investigate how these mountain environments respond to ongoing changes of regional emissions to the atmosphere. PYR-C, in spite of its position far away from urban and industrial areas, presented higher SO₄-S, NO₃-N and NH₄-N bulk deposition than the Montseny site closer to Barcelona and the inclusion of dry deposition only reversed this pattern for NO₃-N. This indicates that distance to pollution sources does not protect these mountain sites from a considerable impact of pollution. Time-trends in SO₄^2- and NO₃^- concentrations in bulk deposition were similar between sites: SO₄^2- monotonically decreased, while NO₃^- increased until the mid-2000 s and decreased thereafter. In the period 1983 to 2017, SO₂ emissions in Europe (EU-28) decreased by 95%, while in the SO₄^2- concentrations in bulk deposition declined by 35-50% in Pyrenees and Montseny respectively and SO₄^2- concentrations in the streams by 25-35%, respectively. Other sources of SO₄^2- (e.g. episodic African dust) may explain the different reduction rate between anthropogenic emissions and bulk deposition. Net S budget was positive for MSY-TM0 (indicating flushing from the catchment) and negative for the PYR-C site (indicating retention), while it was close to zero for the other Pyrenean site, but in the PYR-C site net retention showed a significant increasing trend tending to lower retention in recent years. Bulk N deposition in the Pyrenees was lower but stream concentrations and export was higher than at Montseny, this leading to less N retention in the Pyrenean sites. However, the MSY-TM0 site showed a trend towards less N retention in recent years. This was driven by higher exports during the wet months, which would correspond to a first stage of N saturation according Stoddard's classification.

Recent increase in NO2 levels in the southeast of the Iberian Peninsula

We report the evolution of tropospheric NO₂ over the south-east of the Iberian Peninsula from 2005 to 2017. We have used hourly NO₂ levels measured at air-quality stations in urban and suburban environments. Annual averages ranged between 14 and 45 μg m^-3, with peaks above 200 μg m^-3. A monthly variation was observed, with higher concentrations in cold months (40-60 μg m^-3) and lower levels in the warm season (13-17 μg m^-3). A diurnal pattern was found in urban and suburban areas. The upward trend in NO₂ observed during the whole period contrasts with the upward trend reported in 2013-2017. The NO₂ tropospheric column levels measured by the Ozone Monitoring Instrument over the Iberian Peninsula indicated a similar behaviour; nevertheless, the largest Spanish metropolitan areas did not show this increase. The mean sea level pressure and wind field data of ERA5 (European Centre for Medium-Range Weather Forecasts) were used to investigate the weather conditions, the NO₂ outputs of the Copernicus Monitoring Services being used for the assessment of the NO₂ spatial distribution. NO₂ regional events, with concentrations in the range 140-150 μg m^-3, and which occurred both in the winter and summer season under anticyclonic conditions, are also described. A local origin is identified in winter, whereas in summer, they are associated with a high-pressure system that blocks Mediterranean outflows towards the Atlantic Ocean. The high NO₂ levels are attributed mainly to two factors: i) local emissions, rather than contributions from the western Mediterranean (or even North Africa), and ii) an increase in the pressure gradient between the Atlantic and the Mediterranean pressure systems, associated with a decrease in wind speed, was found during the last five years compared with the previous eight. Meteorological and chemical changes in mid-latitudes associated with global warming should also be investigated in the future.

Unexpected increase in the oxidation capacity of the urban atmosphere of Madrid, Spain

Atmospheric oxidants such as ozone (O₃), hydroxyl and nitrate radicals (OH and NO₃) determine the ability of the urban atmosphere to process organic and inorganic pollutants, which have an impact on air quality, environmental health and climate. Madrid city has experienced an increase of 30-40% in ambient air O₃ levels, along with a decrease of 20-40% in NO₂, from 2007 to 2014. Using air pollution observations and a high-resolution air quality model, we find a large concentration increase of up to 70% and 90% in OH and NO₃, respectively, in downtown Madrid (domain-wide average increase of 10% and 32% for OH and NO₃, respectively). The results also show an 11% reduction in the nitric acid concentrations, leading to a remarkable denoxification of this urban atmosphere with implications for lower PM_2.5 levels and nitrogen input into ecosystems. This study suggests that projected worldwide NO_x emission reductions, following air quality standards, will lead to important changes in the oxidizing capacity of the atmosphere in and around large cities.

Unraveling Pathways of Guaiacol Nitration in Atmospheric Waters: Nitrite, A Source of Reactive Nitronium Ion in the Atmosphere

The tropospheric aqueous-phase aging of guaiacol (2-methoxyphenol, GUA), a lignocellulosic biomass burning pollutant, is addressed in this work. Pathways of GUA nitration in aqueous solution under atmospherically relevant conditions are proposed and critically discussed. The influence of NaNO2 and H2O2, hydroxyl radical scavenger, and sunlight was assessed by an experimental-modeling approach. In the presence of the urban pollutant, nitrite, GUA is preferentially nitrated to yield 4- and 6-nitroguaiacol. After a short lag-time, 4,6-dinitroguaiacol is also formed. Its production accelerates after guaiacol is completely consumed, which is nicely described by the model function accounting for NO2(•) and NO2(+) as nitrating agents. Although the estimated second-order kinetic rate constants of methoxyphenol nitration with NO2(•) are substantially higher than the corresponding rate constants of nitration with NO2(+), nitration rates are competitive under nighttime and liquid atmospheric aerosol-like conditions. In contrast to concentrations of radicals, which are governed by the interplay between diffusion-controlled reactions and are therefore mostly constant, concentrations of electrophiles are very much dependent on the ratio of NO2(-) to activated aromatics in solution. These results contribute substantially to the understanding of methoxyphenol aging in the atmospheric waters and underscore the importance of including electrophilic aromatic substitution reactions in atmospheric models.

Abrupt recent trend changes in atmospheric nitrogen dioxide over the Middle East

Nitrogen oxides, released from fossil fuel use and other combustion processes, affect air quality and climate. From the mid-1990s onward, nitrogen dioxide (NO2) has been monitored from space, and since 2004 with relatively high spatial resolution by the Ozone Monitoring Instrument. Strong upward NO2 trends have been observed over South and East Asia and the Middle East, in particular over major cities. We show, however, that a combination of air quality control and political factors, including economical crisis and armed conflict, has drastically altered the emission landscape of nitrogen oxides in the Middle East. Large changes, including trend reversals, have occurred since about 2010 that could not have been predicted and therefore are at odds with emission scenarios used in projections of air pollution and climate change in the early 21st century.