Cytokine profiles in cord blood in relation to prenatal traffic-related air pollution: The NELA cohort.

BACKGROUND: Outdoor air pollution may disturb immune system development. We investigated whether gestational exposure to traffic-related air pollutants (TRAP) is associated with unstimulated cytokine profiles in newborns. METHODS: Data come from 235 newborns of the NELA cohort. Innate response-related cytokines (IL-6, IFN-α, IL1-ß, and TNF-α), Th1-related (IFN-γ and IL-2), Th2-related (IL-4, IL-5, and IL-13), Th17-related (IL-17 and IL-23), and immunomodulatory cytokine IL-10 were quantified in the supernatant of unstimulated whole umbilical cord blood cells after 7 days of culture using the Luminex technology. Dispersion/chemical transport modeling was used to estimate long-term (whole pregnancy and trimesters) and short-term (15 days before delivery) residential exposures to traffic-related nitrogen dioxide (NO2 ), particulate matter (PM2.5 and PM10 ), and ozone (O3 ). We fitted multivariable logistic regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression models. RESULTS: NO2 during the whole pregnancy increased the odds of detection of IL-1ß (OR per 10 µg/m3 increase = 1.37; 95% CI, 1.02, 1.85) and IL-6 (OR per 10 µg/m3 increase = 1.32; 95% CI 1.00, 1.75). Increased odds of detected concentrations of IL-10 was found in newborns exposed during whole pregnancy to higher levels of NO2 (OR per 10 µg/m3 increase = 1.30; 95% CI 0.99, 1.69), PM10 (OR per 10 µg/m3 increase = 1.49; 95% CI 0.95, 2.33), and PM2.5 (OR per 5 µg/m3 increase = 1.56; 95% CI 0.97, 2.51). Exposure to O3 during the whole pregnancy increased the odds of detected IL-13 (OR per 10 µg/m3 increase = 1.22; 95% CI 1.01, 1.49). WQS model revealed first and third trimesters of gestation as windows of higher susceptibility. CONCLUSIONS: Gestational exposure to TRAP may increase detection of pro-inflammatory, Th2-related, and T regulatory cytokines in newborns. These changes might influence immune system responses later in life.

Effects of air pollution on dementia over Europe for present and future climate change scenarios.

The scientific literature is scarce when referring to the influence of atmospheric pollutants on neurodegenerative diseases for present and future climate change scenarios. In this sense, this contribution evaluates the incidence of dementia (Alzheimer's disease, AD, and dementia from unspecified cause, DU) occurring in Europe associated with the exposure to air pollution (essentially NO2 and PM2.5) for the present climatic period (1991-2010) and for a future climate change scenario (RCP8.5, 2031-2050). The GEMM methodology has been applied to air pollution simulations using the chemistry/climate regional model WRF-Chem. Present population data were obtained from NASA's Center for Socioeconomic Data and Applications (SEDAC); while future population projections for the year 2050 were derived from the United Nations (UN) Department of Economic and Social Affairs-Population Dynamics. Overall, the estimated incidence rate (cases per year) of AD and DU associated with exposure to air pollution over Europe is 498,000 [95% confidence interval (95% CI) 348,600-647,400] and 314,000 (95% CI 257,500-401,900), respectively. An important increase in the future incidence rate is projected (around 72% for both types of dementia) when considering the effect of climate change together with the foreseen changes in the future population, because of the expected aging of European population. The climate penalty (impacts of future climate change alone on air quality) has a limited effect on the total changes of dementia (approx. 0.5%), because the large increase in the incidence rate over southern Europe is offset by its decrease over more northern countries, favored by an improvement of air pollution caused by the projected enhancement of rainfall.

The Nutrition in Early Life and Asthma (NELA) birth cohort study: Rationale, design, and methods.

BACKGROUND: Primary prevention strategies for asthma are lacking. Its inception probably starts in utero and/or during the early postnatal period as the developmental origins of health and disease (DOHaD) paradigm suggests. OBJECTIVES: The main objective of Nutrition in Early Life and Asthma (NELA) cohort study is to unravel whether the following factors contribute causally to the developmental origins of asthma: (1) maternal obesity/adiposity and foetal growth; (2) maternal and child nutrition; (3) outdoor air pollution; (4) endocrine disruptors; and (5) maternal psychological stress. Maternal and offspring biological samples are used to assess changes in offspring microbiome, immune system, epigenome and volatilome as potential mechanisms influencing disease susceptibility. POPULATION: Randomly selected pregnant women from three health areas of Murcia, a south-eastern Mediterranean region of Spain, who fulfilled the inclusion criteria were invited to participate at the time of the follow-up visit for routine foetal anatomy scan at 19-22 weeks of gestation, at the Maternal-Fetal Medicine Unit of the "Virgen de la Arrixaca" University Clinical Hospital over a 36-month period, from March 2015 to April 2018. DESIGN: Prospective, population-based, maternal-child, birth cohort study. METHODS: Questionnaires on exposures and outcome variables were administered to mothers at 20-24 gestation week; 32-36 gestation week; and delivery. Children were surveyed at birth, 3 and 18 months of age and currently at 5 years. Furthermore, physical examinations were performed; and different measurements and biological samples were obtained at these time points. PRELIMINARY RESULTS: Among the 1350 women invited to participate, 738 (54%) were finally enrolled in the study and 720 of their children were eligible at birth. The adherence was high with 612 children (83%) attending the 3 months' visit and 532 children (72%) attending the 18 months' visit. CONCLUSION: The NELA cohort will add original and unique knowledge to the developmental origins of asthma.

Exhaled volatilome analysis as a useful tool to discriminate asthma with other coexisting atopic diseases in women of childbearing age.

The prevalence of asthma is considerably high among women of childbearing age. Most asthmatic women also often have other atopic disorders. Therefore, the differentiation between patients with atopic diseases without asthma and asthmatics with coexisting diseases is essential to avoid underdiagnosis of asthma and to design strategies to reduce symptom severity and improve quality of life of patients. Hence, we aimed for the first time to conduct an analysis of volatile organic compounds in exhaled breath of women of childbearing age as a new approach to discriminate between asthmatics with other coexisting atopic diseases and non-asthmatics (with or without atopic diseases), which could be a helpful tool for more accurate asthma detection and monitoring using a noninvasive technique in the near future. In this study, exhaled air samples of 336 women (training set (n = 211) and validation set (n = 125)) were collected and analyzed by thermal desorption coupled with gas chromatography-mass spectrometry. ASCA (ANOVA (analysis of variance) simultaneous component analysis) and LASSO + LS (least absolute shrinkage and selection operator + logistic regression) were employed for data analysis. Fifteen statistically significant models (p-value < 0.05 in permutation tests) that discriminated asthma with other coexisting atopic diseases in women of childbearing age were generated. Acetone, 2-ethyl-1-hexanol and a tetrahydroisoquinoline derivative were selected as discriminants of asthma with other coexisting atopic diseases. In addition, carbon disulfide, a tetrahydroisoquinoline derivative, 2-ethyl-1-hexanol and decane discriminated asthma disease among patients with other atopic disorders. Results of this study indicate that refined metabolomic analysis of exhaled breath allows asthma with other coexisting atopic diseases discrimination in women of reproductive age.

Contribution of fine particulate matter to present and future premature mortality over Europe: A non-linear response.

The World Health Organization estimates that around 7 million people die every year from exposure to fine particles (PM2.5) inpolluted air. Here, the number of premature deaths in Europe from different diseases associated to the ambient exposure to PM2.5 have here been studied both for present (1991-2010) and future periods (2031-2050, RCP8.5 scenario). This contribution combines different state-of-the-art approaches (use of high-resolution climate/chemistry simulations over Europe for providing air quality data; use of different baseline mortality data for specific European regions; inclusion of future population projections and dynamical changes for 2050 obtained from the United Nations (UN) Population Projections or use of non-linear exposure-response functions) to estimate the premature mortality due to PM2.5. The mortality endpoints included in this study are Lung Cancer (LC), Chronic Obstructive Pulmonary Disease (COPD), Cerebrovascular Disease (CEV), Ischemic Heart Disease (IHD), Lower Respiratory Infection (LRI) and other Non-Communicable Diseases (other NCDs). Different risk ratio and baseline mortalities for each disease end each age range have been estimated individually. The results indicate that the annual excess mortality rate from fine particulate matter in Europe is 904,000 [95% confidence interval (95% CI) 733,100-1,067,800], increasing by 73% in 2050s (1,560,000; 95% CI 1,260,000-1,840,000); meanwhile population decreases from 808 to 806 million according to the UN estimations. The results show that IHD is the main cause of premature mortality in Europe associated to PM2.5 (around 48%) both for the present and future periods. Despite several marked regional differences, premature deaths associated to all the endpoints included in this study will increase in the future period due to the climate penalty but especially because of changes in the population projected and its aging.

Air pollution from traffic during pregnancy impairs newborn's cord blood immune cells: The NELA cohort.

BACKGROUND: Hazards of traffic-related air pollution (TRAP) on the developing immune system are poorly understood. We sought to investigate the effects of prenatal exposure to TRAP on cord blood immune cell distributions; and to identify gestational windows of susceptibility. METHODS: In-depth immunophenotyping of cord blood leukocyte and lymphocyte subsets was performed by flow cytometry in 190 newborns embedded in the Nutrition in Early Life and Asthma (NELA) birth cohort (2015-2018). Long-term (whole pregnancy and trimesters) and short-term (15-days before delivery) residential exposures to traffic-related nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10), and ozone (O3) were estimated using dispersion/chemical transport modelling. Associations between TRAP concentrations and cord blood immune cell counts were assessed using multivariate Poisson regression models. RESULTS: Mean number of natural killer (NK) cells decreased 15% in relation to higher NO2 concentrations (≥36.4 µg/m3) during whole pregnancy (incidence relative risk (IRR), 0.85; 95% CI, 0.72, 0.99), with stronger associations in the first trimester. Higher PM2.5 concentrations (≥13.3 µg/m3) during whole pregnancy associated with a reduced mean number of cytotoxic T cells (IRR, 0.88; 95% CI, 0.78, 0.99). Newborns exposed to higher PM10 (≥23.6 µg/m3) and PM2.5 concentrations during the first and third trimester showed greater mean number of helper T type 1 (Th1) cells (P < 0.05). Decreased number of regulatory T (Treg) cells was associated with greater short-term NO2 (IRR, 0.90; 95% CI, 0.80, 1.01) and PM10 (IRR, 0.88; 95% CI, 0.77, 0.99) concentrations. CONCLUSIONS: Prenatal exposure to TRAP, particularly in early and late gestation, impairs fetal immune system development through disturbances in cord blood leukocyte and lymphocyte distributions.

Population exposure to particulate-matter and related mortality due to the Portuguese wildfires in October 2017 driven by storm Ophelia.

In October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM10) and study associations between PM10 and short-term mortality in the Portuguese population exposed to PM10 due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM10 concentrations during the wildfires. The effects of PM10 on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM10 level of 11.7 µg/m3 during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM10 levels that varied from 16.2 to 120.6 µg/m3 in smoky days with dust and from 6.1 to 20.9 µg/m3 in dust-free smoky days. Results suggest that PM10 had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m3 of PM10, there was a 0.89% (95% confidence interval, CI, 0-1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99-3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.

Climate drivers of the 2017 devastating fires in Portugal.

A record 500,000 hectares burned in Portugal during the extreme wildfire season of 2017, with more than 120 human lives lost. Here we analyse the climatic factors responsible for the burned area (BA) from June to October series in Portugal for the period 1980-2017. Superposed onto a substantially stationary trend on BA data, strong oscillations on shorter time scales were detected. Here we show that they are significantly affected by the compound effect of summer (June-July-August) drought and high temperature conditions during the fire season. Drought conditions were calculated using the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI). Then the extent to which the burned area has diverged from climate-expected trends was assessed. Our results indicate that in the absence of other drivers, climate change would have led to higher BA values. In addition, the 2017 extreme fire season is well captured with the model forced with climate drivers only, suggesting that the extreme fire season of 2017 could be a prelude to future conditions and likewise events. Indeed, the expected further increase of drought and high temperature conditions in forthcoming decades, point at a potential increase of fire risk in this region. The climate-fire model developed in this study could be useful to develop more skilled seasonal predictions capable of anticipating potentially hazardous conditions.

Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions.

An accurate simulation of the absorption properties is key for assessing the radiative effects of aerosol on meteorology and climate. The representation of how chemical species are mixed inside the particles (the mixing state) is one of the major uncertainty factors in the assessment of these effects. Here we compare aerosol optical properties simulations over Europe and North America, coordinated in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII), to 1 year of AERONET sunphotometer retrievals, in an attempt to identify a mixing state representation that better reproduces the observed single scattering albedo and its spectral variation. We use a single post-processing tool (FlexAOD) to derive aerosol optical properties from simulated aerosol speciation profiles, and focus on the absorption enhancement of black carbon when it is internally mixed with more scattering material, discarding from the analysis scenes dominated by dust. We found that the single scattering albedo at 440 nm (ω 0,440) is on average overestimated (underestimated) by 3-5 % when external (core-shell internal) mixing of particles is assumed, a bias comparable in magnitude with the typical variability of the quantity. The (unphysical) homogeneous internal mixing assumption underestimates ω 0,440 by ~ 14 %. The combination of external and core-shell configurations (partial internal mixing), parameterized using a simplified function of air mass aging, reduces the ω 0,440 bias to -1/-3 %. The black carbon absorption enhancement (E abs) in core-shell with respect to the externally mixed state is in the range 1.8-2.5, which is above the currently most accepted upper limit of ~ 1.5. The partial internal mixing reduces E abs to values more consistent with this limit. However, the spectral dependence of the absorption is not well reproduced, and the absorption Ångström exponent AAE 675 440 is overestimated by 70-120 %. Further testing against more comprehensive campaign data, including a full characterization of the aerosol profile in terms of chemical speciation, mixing state, and related optical properties, would help in putting a better constraint on these calculations.

Combining monitoring and modelling approaches for BaP characterization over a petrochemical area.

In this study, air concentrations of BaP in two different seasons (winter 2015 and summer 2016) and BaP levels in ground vegetation from Tarragona County were used as control simulations performed with the WRF-CHIMERE air quality modelling system, in order to reproduce the incidence of that hazardous chemical in air and soils. The CTM was validated for the present climatology, showing a good ability to represent air and soil concentrations of BaP over the target domain (petrochemical, chemical, urban and background sites), particularly in the winter. Then, the variation of the BaP concentrations in air and soils were simulated for the time series 1996-2015 and for the climate change scenario RCP8.5 (2031-2050). While an increase is projected for the levels in air, particularly in chemical and remote sites where the variation can go up to 10%, in terms of soil deposition the findings are the opposite, with an evident decrease in soil BaP concentrations, particularly for background sites. Finally, a potential health effect of BaP for the local population (lung cancer) was assessed. Although according to the projections the EU threshold for BaP atmospheric incidence (1 ng m-3) will not be reached by 2050, there will be an increase in the life-time risk of lung cancer, particularly in the most populated areas within the simulation domain.

Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3.

In the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), and as contribution to the second phase of the Hemispheric Transport of Air Pollution (HTAP2) activities for Europe and North America, the impacts of a 20 % decrease of global and regional anthropogenic emissions on surface air pollutant levels in 2010 are simulated by an international community of regional-scale air quality modeling groups, using different state-of-the-art chemistry and transport models (CTMs). The emission perturbations at the global level, as well as over the HTAP2-defined regions of Europe, North America and East Asia, are first simulated by the global Composition Integrated Forecasting System (C-IFS) model from European Centre for Medium-Range Weather Forecasts (ECMWF), which provides boundary conditions to the various regional CTMs participating in AQMEII3. On top of the perturbed boundary conditions, the regional CTMs used the same set of perturbed emissions within the regional domain for the different perturbation scenarios that introduce a 20 % reduction of anthropogenic emissions globally as well as over the HTAP2-defined regions of Europe, North America and East Asia. Results show that the largest impacts over both domains are simulated in response to the global emission perturbation, mainly due to the impact of domestic emission reductions. The responses of NO2, SO2 and PM concentrations to a 20 % anthropogenic emission reduction are almost linear (~ 20 % decrease) within the global perturbation scenario with, however, large differences in the geographical distribution of the effect. NO2, CO and SO2 levels are strongly affected over the emission hot spots. O3 levels generally decrease in all scenarios by up to ~ 1 % over Europe, with increases over the hot spot regions, in particular in the Benelux region, by an increase up to ~ 6 % due to the reduced effect of NOx titration. O3 daily maximum of 8 h running average decreases in all scenarios over Europe, by up to ~ 1 %. Over the North American domain, the central-to-eastern part and the western coast of the US experience the largest response to emission perturbations. Similar but slightly smaller responses are found when domestic emissions are reduced. The impact of intercontinental transport is relatively small over both domains, however, still noticeable particularly close to the boundaries. The impact is noticeable up to a few percent, for the western parts of the North American domain in response to the emission reductions over East Asia. O3 daily maximum of 8 h running average decreases in all scenarios over north Europe by up to ~ 5 %. Much larger reductions are calculated over North America compared to Europe. In addition, values of the Response to Extra-Regional Emission Reductions (RERER) metric have been calculated in order to quantify the differences in the strengths of nonlocal source contributions to different species among the different models. We found large RERER values for O3 (~ 0.8) over both Europe and North America, indicating a large contribution from non-local sources, while for other pollutants including particles, low RERER values reflect a predominant control by local sources. A distinct seasonal variation in the local vs. non-local contributions has been found for both O3 and PM2.5, particularly reflecting the springtime long-range transport to both continents.

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3.

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). The modeled surface concentrations of O3, CO, SO2 and PM2.5 are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs from each individual model. Along with a base case simulation, additional runs were performed introducing 20 % anthropogenic emission reductions both globally and regionally in Europe, North America and east Asia, as defined by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2). Health impacts estimated by using concentration inputs from different chemistry-transport models (CTMs) to the EVA system can vary up to a factor of 3 in Europe (12 models) and the United States (3 models). In Europe, the multi-model mean total number of premature deaths (acute and chronic) is calculated to be 414 000, while in the US, it is estimated to be 160 000, in agreement with previous global and regional studies. The economic valuation of these health impacts is calculated to be EUR 300 billion and 145 billion in Europe and the US, respectively. A subset of models that produce the smallest error compared to the surface observations at each time step against an all-model mean ensemble results in increase of health impacts by up to 30 % in Europe, while in the US, the optimal ensemble mean led to a decrease in the calculated health impacts by ~ 11 %. A total of 54 000 and 27 500 premature deaths can be avoided by a 20 % reduction of global anthropogenic emissions in Europe and the US, respectively. A 20 % reduction of North American anthropogenic emissions avoids a total of ~ 1000 premature deaths in Europe and 25 000 total premature deaths in the US. A 20 % decrease of anthropogenic emissions within the European source region avoids a total of 47 000 premature deaths in Europe. Reducing the east Asian anthropogenic emissions by 20 % avoids ~ 2000 total premature deaths in the US. These results show that the domestic anthropogenic emissions make the largest impacts on premature deaths on a continental scale, while foreign sources make a minor contribution to adverse impacts of air pollution.

Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more?

In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)-Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13-16 % compared to G and by 2-3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.

Modelling benzo[a]pyrene in air and vegetation for different land uses and assessment of increased health risk in the Iberian Peninsula.

The ability of the modelling system WRF + CHIMERE implemented with high spatial and temporal resolution over the Iberian Peninsula (IP) to represent the levels of benzo[a]pyrene (BaP) in air and vegetation was tested in areas where different land uses are observed. Biomonitoring data available on the levels of polycyclic aromatic hydrocarbons (PAHs) in pine needles from the IP were used to estimate the atmospheric concentrations of BaP and, at the same time, fuelled the comparison of the vegetation representations given by the model. A total of 70 sites were sampled, including urban, industrial, rural and remote locations, which revealed different performances of the method for air and vegetation concentrations of BaP. The validation of this chemistry transport model (CTM) was complemented with the data available from the European Monitoring and Evaluation Programme (EMEP) air sampling network. This, in association with a quantitative risk assessment (QRA) method, allowed the estimation of the increased risk of lung cancer due to exposure to BaPs in the IP for three target values set by the European Union.

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown.

Through the comparison of several regional-scale chemistry transport modeling systems that simulate meteorology and air quality over the European and North American continents, this study aims at (i) apportioning error to the responsible processes using timescale analysis, (ii) helping to detect causes of model error, and (iii) identifying the processes and temporal scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overallsense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance, and covariance) can help assess the nature and quality of the error. Each of the error components is analyzed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intraday) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emission and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high interdependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. This will require evaluaion methods that are able to frame the impact on error of processes, conditions, and fluxes at the surface. For example, error due to emission and boundary conditions is dominant for primary species (CO, particulate matter (PM)), while errors due to meteorology and chemistry are most relevant to secondary species, such as ozone. Some further aspects emerged whose interpretation requires additional consideration, such as the uniformity of the synoptic error being region- and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.

Organochlorine pesticides removal from wastewater by pine bark adsorption after activated sludge treatment.

Pesticides have been responsible for strong environmental impacts, mainly due to their persistence in the environment. Removal technologies are usually combined, because degradation of organic matter is needed prior to a tertiary treatment to guarantee pesticides elimination to levels below legal limits (normally 0.1 microg L(-1)). Pine bark was studied as an alternative to activated carbon, for organochlorine pesticides removal. A combination of technologies based on biodegradation with activated sludge followed by pine bark adsorption treatment was used for lindane (LIN) and heptachlor (HEP) removal from contaminated waters. Pesticides were quantified throughout the process by GC-ECD preceded by solid-phase microextraction (SPME). An experimental set-up was maintained for 4 months, by feeding a standard solution with pesticides concentration of 1 microg L(-1) each and known organic matter (Chemical Oxygen Demand, COD, -563 mg O2 L(-1)) on a daily basis. COD suffered a reduction of about 81% in the biological step and no increase was detected in the subsequent adsorption treatment. Overall removal efficiency was 76.6% and above 77.7% for LIN and HEP, respectively.

Emissions variation in urban areas resulting from the introduction of natural gas vehicles: application to Barcelona and Madrid greater areas (Spain).

On-road traffic is the major contributor to pollutant emissions in urban areas. Nowadays different emission abatement strategies are being tested in order to improve urban air quality (e.g. the European Commission currently promotes the use of natural gas as an alternative fuel). Several feasible scenarios regarding the introduction of natural gas vehicles (NGV) are studied in the two main cities of Spain (Barcelona and Madrid) by using the HERMES emission model. The most suitable emission factors to NGV are selected among those available in the literature. The account of emissions in the base case scenario estimated for a typical summertime polluted day of the year 2004 reflects that in Barcelona 86% of primary pollutants come from on-road traffic compared to 93% in Madrid, because of the heavier industrial activity in the former. The introduction of NGV in urban zones would have a positive effect on emissions, whose extent largely depends on the substituted fleets and the conurbation characteristics. Maximum reductions in NO(x) emissions in Madrid are attributed to the substitution of 10% of the oldest diesel and petrol cars, while in Barcelona the change of 50% of the oldest commercial light vehicles becomes more effective. PM(2.5) and SO(2) emissions can be significatively reduced with the introduction of NGV instead of the oldest commercial light vehicles. The substitution of conventional fuels by natural gas must reach around 4% to achieve significative reductions in traffic emissions (larger than 5%). This work focuses on air quality issues, therefore GHG emissions are not included, nevertheless this kind of associated impact has to be considered by the decision makers. Assessing the efficacy of environmental improvement strategies entails a realistic design of emission scenarios and their evaluation. The detailed emission account provides a fundamental basis for the air quality modelling and its comparison among scenarios.

High resolution modeling of the effects of alternative fuels use on urban air quality: introduction of natural gas vehicles in Barcelona and Madrid Greater Areas (Spain).

The mitigation of the effects of on-road traffic emissions on urban air pollution is currently an environmental challenge. Air quality modeling has become a powerful tool to design environment-related strategies. A wide range of options is being proposed; such as the introduction of natural gas vehicles (NGV), biofuels or hydrogen vehicles. The impacts on air quality of introducing specific NGV fleets in Barcelona and Madrid (Spain) are assessed by means of the WRF-ARW/HERMES/CMAQ modeling system with high spatial-temporal resolution (1 km(2), 1 h). Seven emissions scenarios are defined taking into account the year 2004 vehicle fleet composition of the study areas and groups of vehicles susceptible of change under a realistic perspective. O(3) average concentration rises up to 1.3% in Barcelona and up to 2.5% in Madrid when introducing the emissions scenarios, due to the NO(x) reduction in VOC-controlled areas. Nevertheless, NO(2), PM10 and SO(2) average concentrations decrease, up to 6.1%, 1.5% and 6.6% in Barcelona and up to 20.6%, 8.7% and 14.9% in Madrid, respectively. Concerning SO(2) and PM10 reductions the most effective single scenario is the introduction of 50% of NGV instead of the oldest commercial vehicles; it also reduces NO(2) concentrations in Barcelona, however in Madrid lower levels are attained when substituting 10% of the private cars. This work introduces the WRF-ARW/HERMES/CMAQ modeling system as a useful management tool and proves that the air quality improvement plans must be designed considering the local characteristics.

The use of a modelling system as a tool for air quality management: annual high-resolution simulations and evaluation.

The high levels of air pollutants over the North-Western Mediterranean (NWM) exceed the thresholds set in current air quality regulations. They demand a detailed diagnosis of those areas where the exceedances of thresholds related to human health are found. In this sense, there is a need for modelling studies for the specific area of the NWM that take into account the annual cycle to address the diagnosis of air pollution. A new approach to the modelling of air quality in the NWM has been adopted by combining the WRF-EMICAT-CMAQ-DREAM modelling system to diagnose the current status of the levels of photochemical air pollution (focusing on ozone, O(3); nitrogen dioxide, NO(2); carbon monoxide, CO; and particulate matter, PM10) in the area during an annual cycle (year 2004). The complexity of the area of study requires the application of high spatial and temporal resolution (2 km and 1 h). The annual simulations need to cover the complex different meteorological situations and types of episodes of air pollution in the area of study. The outputs of the modelling system are evaluated against observations from 52 meteorological and 59 air quality stations belonging to the Environmental Department of the Catalonia Government (Spain), which involve a dense and accurate spatial distribution of stations in the territory (32,215 km(2)). The results indicate a good behaviour of the model in both coastal and inland areas of the NWM, with a slight trend to the overestimation of tropospheric O(3) concentrations and the underestimation of other photochemical pollutants (NO(2), CO and PM10). The modelling diagnosis indicates that the main air quality-related problems in the NWM are the exceedances of the 1-hr O(3) information threshold set in the Directive 2002/3/EC (180 microg m(-3)) as a consequence of the transport of O(3) precursors downwind the Barcelona Greater Area (BGA); and the exceedances of the annual value for the protection of human health for NO(2) and PM10 (40 microg m(-3), Directive 1999/30/EC), both in the BGA, as a consequence of the high traffic-related emissions.