Oceanic phytoplankton, atmospheric aerosol and Raman scattering impacts on space-based ultraviolet radiance measurements

International audienceOceanic phytoplankton can affect in-water and atmospheric radiation fields. In this study, we develop case 1 (without noncovarying particles) and case 2 (including noncovarying particles) waters model including Raman scattering in order to examine the chlorophyll impacts on the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index and aerosol single scattering albedo. The waters model is coupled with a radiation transfer model (VLIDORT) for calculating TOMS Aerosol Index and retrieval of aerosol single scattering albedo. The retrieval is constrained by chlorophyll concentration from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging SpectroRadiometer (MODIS) data, aerosol optical depth from MODIS, and aerosol vertical profiles from a global chemical transport model (GEOS-CHEM). We find the retrieved aerosol single scattering albedo is strongly influenced by chlorophyll concentration, particularly in the regions of subtropical Atlantic Ocean and Indian Ocean. The maximum deviation between the aerosol single scattering albedo retrieved with and withouout considering chlorophyll can reach 10 percent. Thus, it is important to take account of the phytoplankton impacts on atmospheric remote sensing measurements

Examination of the Community Multiscale Air Quality (CMAQ) model performance over the North American and European domains

Copyright 2011 Elsevier B.V., All rights reserved.The CMAQ modeling system has been used to simulate the air quality for North America and Europe for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII). The operational model performance of tropospheric ozone (O), fine particulate matter (PM) and total particulate matter (PM) for the two continents has been assessed. The model underestimates daytime (8am-8pm LST) O mixing ratios by 13% in the winter for North America, primarily due to an underestimation of daytime O mixing ratios in the middle and lower troposphere from the lateral boundary conditions. The model overestimates winter daytime O mixing ratios in Europe by an average of 8.4%. The model underestimates daytime O by 4-5% in the spring for both continents, while in the summer daytime O is overestimated by 9.8% for North America and slightly underestimated by 1.6% for Europe. The model overestimates daytime O in the fall for both continents, grossly overestimating daytime O by over 30% for Europe. The performance for PM varies both seasonally and geographically for the two continents. For North American, PM is overestimated in the winter and fall, with an average Normalized Mean Bias (NMB) greater than -30%, while performance in the summer is relatively good, with an average NMB of -4.6%. For Europe, PM is underestimated throughout the entire year, with the NMB ranging from -24% in the fall to -55% in the winter. PM is underestimated throughout the year for both North America and Europe, with remarkably similar performance for both continents. The domain average NMB for PM ranges between -45% and -65% for the two continents, with the largest underestimation occurring in the summer for North American and the winter for Europe.Peer reviewedSubmitted Versio

Advances in air quality research – current and emerging challenges

This review provides a community's perspective on air quality research focusing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizing sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions, and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground-based and remote sensing instruments, including in particular those on satellites. The research should also capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposure to air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high-resolution distributions of these metrics over cities. The review also examines how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy

Quantifying effects of long-range transport of NO2 over Delhi using back trajectories and satellite data

© 2024 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Exposure to air pollution is a leading public health risk factor in India, especially over densely populated Delhi and the surrounding Indo-Gangetic Plain. During the post-monsoon seasons, the prevailing north-westerly winds are known to influence aerosol pollution events in Delhi by advecting pollutants from agricultural fires as well as from local sources. Here we investigate the year-round impact of meteorology on gaseous nitrogen oxides (NOxCombining double low lineNO+NO2). We use bottom-up NOx emission inventories (anthropogenic and fire) and high-resolution satellite measurement based tropospheric column NO2 (TCNO2) data, from S5P aboard TROPOMI, alongside a back-trajectory model (ROTRAJ) to investigate the balance of local and external sources influencing air pollution changes in Delhi, with a focus on different emissions sectors. Our analysis shows that accumulated emissions (i.e. integrated along the trajectory path, allowing for chemical loss) are highest under westerly, north-westerly and northerly flow during pre-monsoon (February-May) and post-monsoon (October-February) seasons. According to this analysis, during the pre-monsoon season, the highest accumulated satellite TCNO2 trajectories come from the east and north-west of Delhi. TCNO2 is elevated within Delhi and the Indo-Gangetic Plain (IGP) to the east of city. The accumulated NOx emission trajectories indicate that the transport and industry sectors together account for more than 80% of the total accumulated emissions, which are dominated by local sources (>70%) under easterly winds and north-westerly winds. The high accumulated emissions estimated during the pre-monsoon season under north-westerly wind directions are likely to be driven by high NOx emissions locally and in nearby regions (since NOx lifetime is reduced and the boundary layer is relatively deeper in this season). During the post-monsoon season the highest accumulated satellite TCNO2 trajectories are advected from Punjab and Haryana, where satellite TCNO2 is elevated, indicating the potential for the long-range transport of agricultural burning emissions to Delhi. However, accumulated NOx emissions indicate local (70%) emissions from the transport sector are the largest contributor to the total accumulated emissions. High local emissions, coupled with a relatively long NOx atmospheric lifetime and shallow boundary layer, aid the build-up of emissions locally and along the trajectory path. This indicates the possibility that fire emissions datasets may not capture emissions from agricultural waste burning in the north-west sufficiently to accurately quantify their influence on Delhi air quality (AQ). Analysis of daily ground-based NO2 observations indicates that high-pollution episodes (>90th percentile) occur predominantly in the post-monsoon season, and more than 75% of high-pollution events are primarily caused by local sources. But there is also a considerable influence from non-local (30%) emissions from the transport sector during the post-monsoon season. Overall, we find that in the post-monsoon season, there is substantial accumulation of high local NOx emissions from the transport sector (70% of total emissions, 70% local), alongside the import of NOx pollution into Delhi (30% non-local). This work indicates that both high local NOx emissions from the transport sector and the advection of highly polluted air originating from outside Delhi are of concern for the population. As a result, air quality mitigation strategies need to be adopted not only in Delhi but in the surrounding regions to successfully control this issue. In addition, our analysis suggests that the largest benefits to Delhi NOx air quality would be seen with targeted reductions in emissions from the transport and agricultural waste burning sectors, particularly during the post-monsoon season.Peer reviewe

COVID-19 lockdown induced changes in NO2 levels across India observed by multi-satellite and surface observations

© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.We have estimated the spatial changes in NO 2levels over different regions of India during the COVID-19 lockdown (25 March-3 May 2020) using the satellite-based tropospheric column NO 2observed by the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), as well as surface NO 2concentrations obtained from the Central Pollution Control Board (CPCB) monitoring network. A substantial reduction in NO 2levels was observed across India during the lockdown compared to the same period during previous business-as-usual years, except for some regions that were influenced by anomalous fires in 2020. The reduction (negative change) over the urban agglomerations was substantial (~20 %-40 %) and directly proportional to the urban size and population density. Rural regions across India also experienced lower NO 2values by ~15 %-25 %. Localised enhancements in NO 2associated with isolated emission increase scattered across India were also detected. Observed percentage changes in satellite and surface observations were consistent across most regions and cities, but the surface observations were subject to larger variability depending on their proximity to the local emission sources. Observations also indicate NO 2enhancements of up to~25%during the lockdown associated with fire emissions over the north-east of India and some parts of the central regions. In addition, the cities located near the large fire emission sources show much smaller NO 2reduction than other urban areas as the decrease at the surface was masked by enhancement in NO 2due to the transport of the fire emissions.Peer reviewedFinal Published versio

Modelling the dispersion of particle numbers in five European cities

We present an overview of the modelling of particle number concentrations (PNCs) in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008. Novel emission inventories of particle numbers have been compiled both on urban and European scales. We used atmospheric dispersion modelling for PNCs in the five target cities and on a European scale, and evaluated the predicted results against available measured concentrations. In all the target cities, the concentrations of particle numbers (PNs) were mostly influenced by the emissions originating from local vehicular traffic. The influence of shipping and harbours was also significant for Helsinki, Oslo, Rotterdam, and Athens, but not for London. The influence of the aviation emissions in Athens was also notable. The regional background concentrations were clearly lower than the contributions originating from urban sources in Helsinki, Oslo, and Athens. The regional background was also lower than urban contributions in traffic environments in London, but higher or approximately equal to urban contributions in Rotterdam. It was numerically evaluated that the influence of coagulation and dry deposition on the predicted PNCs was substantial for the urban background in Oslo. The predicted and measured annual average PNCs in four cities agreed within approximatelyPeer reviewe

Trace gas/aerosol boundary concentrations and their impacts on continental-scale AQMEII modeling domains

Copyright 2011 Elsevier B.V., All rights reserved.Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe for 2006 full-year simulations for model inter-comparisons and evaluations. To better understand the reasons for differences in model results among these participating groups, each group was asked to use the same source of emissions and boundary concentration data for their simulations. This paper describes the development and application of the boundary concentration data for this AQMEII modeling exercise. The European project known as GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) has produced global-scale re-analyses of air quality for several years, including 2006 (http://gems.ecmwf.int). The GEMS trace gas and aerosol data were made available at 3-hourly intervals on a regular latitude/longitude grid of approximately 1.9° resolution within 2 "cut-outs" from the global model domain. One cut-out was centered over North America and the other over Europe, covering sufficient spatial domain for each modeling group to extract the necessary time- and space-varying (horizontal and vertical) concentrations for their mesoscale model boundaries. Examples of the impact of these boundary concentrations on the AQMEII continental simulations are presented to quantify the sensitivity of the simulations to boundary concentrations. In addition, some participating groups were not able to use the GEMS data and instead relied upon other sources for their boundary concentration specifications. These are noted, and the contrasting impacts of other data sources for boundary data are presented. How one specifies four-dimensional boundary concentrations for mesoscale air quality simulations can have a profound impact on the model results, and hence, this aspect of data preparation must be performed with considerable care.Peer reviewedFinal Accepted Versio

Cognitive behavioural therapy for adults with dissociative seizures (CODES): a pragmatic, multicentre, randomised controlled trial.

BACKGROUND: Dissociative seizures are paroxysmal events resembling epilepsy or syncope with characteristic features that allow them to be distinguished from other medical conditions. We aimed to compare the effectiveness of cognitive behavioural therapy (CBT) plus standardised medical care with standardised medical care alone for the reduction of dissociative seizure frequency. METHODS: In this pragmatic, parallel-arm, multicentre randomised controlled trial, we initially recruited participants at 27 neurology or epilepsy services in England, Scotland, and Wales. Adults (≥18 years) who had dissociative seizures in the previous 8 weeks and no epileptic seizures in the previous 12 months were subsequently randomly assigned (1:1) from 17 liaison or neuropsychiatry services following psychiatric assessment, to receive standardised medical care or CBT plus standardised medical care, using a web-based system. Randomisation was stratified by neuropsychiatry or liaison psychiatry recruitment site. The trial manager, chief investigator, all treating clinicians, and patients were aware of treatment allocation, but outcome data collectors and trial statisticians were unaware of treatment allocation. Patients were followed up 6 months and 12 months after randomisation. The primary outcome was monthly dissociative seizure frequency (ie, frequency in the previous 4 weeks) assessed at 12 months. Secondary outcomes assessed at 12 months were: seizure severity (intensity) and bothersomeness; longest period of seizure freedom in the previous 6 months; complete seizure freedom in the previous 3 months; a greater than 50% reduction in seizure frequency relative to baseline; changes in dissociative seizures (rated by others); health-related quality of life; psychosocial functioning; psychiatric symptoms, psychological distress, and somatic symptom burden; and clinical impression of improvement and satisfaction. p values and statistical significance for outcomes were reported without correction for multiple comparisons as per our protocol. Primary and secondary outcomes were assessed in the intention-to-treat population with multiple imputation for missing observations. This trial is registered with the International Standard Randomised Controlled Trial registry, ISRCTN05681227, and ClinicalTrials.gov, NCT02325544. FINDINGS: Between Jan 16, 2015, and May 31, 2017, we randomly assigned 368 patients to receive CBT plus standardised medical care (n=186) or standardised medical care alone (n=182); of whom 313 had primary outcome data at 12 months (156 [84%] of 186 patients in the CBT plus standardised medical care group and 157 [86%] of 182 patients in the standardised medical care group). At 12 months, no significant difference in monthly dissociative seizure frequency was identified between the groups (median 4 seizures [IQR 0-20] in the CBT plus standardised medical care group vs 7 seizures [1-35] in the standardised medical care group; estimated incidence rate ratio [IRR] 0·78 [95% CI 0·56-1·09]; p=0·144). Dissociative seizures were rated as less bothersome in the CBT plus standardised medical care group than the standardised medical care group (estimated mean difference -0·53 [95% CI -0·97 to -0·08]; p=0·020). The CBT plus standardised medical care group had a longer period of dissociative seizure freedom in the previous 6 months (estimated IRR 1·64 [95% CI 1·22 to 2·20]; p=0·001), reported better health-related quality of life on the EuroQoL-5 Dimensions-5 Level Health Today visual analogue scale (estimated mean difference 6·16 [95% CI 1·48 to 10·84]; p=0·010), less impairment in psychosocial functioning on the Work and Social Adjustment Scale (estimated mean difference -4·12 [95% CI -6·35 to -1·89]; p<0·001), less overall psychological distress than the standardised medical care group on the Clinical Outcomes in Routine Evaluation-10 scale (estimated mean difference -1·65 [95% CI -2·96 to -0·35]; p=0·013), and fewer somatic symptoms on the modified Patient Health Questionnaire-15 scale (estimated mean difference -1·67 [95% CI -2·90 to -0·44]; p=0·008). Clinical improvement at 12 months was greater in the CBT plus standardised medical care group than the standardised medical care alone group as reported by patients (estimated mean difference 0·66 [95% CI 0·26 to 1·04]; p=0·001) and by clinicians (estimated mean difference 0·47 [95% CI 0·21 to 0·73]; p<0·001), and the CBT plus standardised medical care group had greater satisfaction with treatment than did the standardised medical care group (estimated mean difference 0·90 [95% CI 0·48 to 1·31]; p<0·001). No significant differences in patient-reported seizure severity (estimated mean difference -0·11 [95% CI -0·50 to 0·29]; p=0·593) or seizure freedom in the last 3 months of the study (estimated odds ratio [OR] 1·77 [95% CI 0·93 to 3·37]; p=0·083) were identified between the groups. Furthermore, no significant differences were identified in the proportion of patients who had a more than 50% reduction in dissociative seizure frequency compared with baseline (OR 1·27 [95% CI 0·80 to 2·02]; p=0·313). Additionally, the 12-item Short Form survey-version 2 scores (estimated mean difference for the Physical Component Summary score 1·78 [95% CI -0·37 to 3·92]; p=0·105; estimated mean difference for the Mental Component Summary score 2·22 [95% CI -0·30 to 4·75]; p=0·084), the Generalised Anxiety Disorder-7 scale score (estimated mean difference -1·09 [95% CI -2·27 to 0·09]; p=0·069), and the Patient Health Questionnaire-9 scale depression score (estimated mean difference -1·10 [95% CI -2·41 to 0·21]; p=0·099) did not differ significantly between groups. Changes in dissociative seizures (rated by others) could not be assessed due to insufficient data. During the 12-month period, the number of adverse events was similar between the groups: 57 (31%) of 186 participants in the CBT plus standardised medical care group reported 97 adverse events and 53 (29%) of 182 participants in the standardised medical care group reported 79 adverse events. INTERPRETATION: CBT plus standardised medical care had no statistically significant advantage compared with standardised medical care alone for the reduction of monthly seizures. However, improvements were observed in a number of clinically relevant secondary outcomes following CBT plus standardised medical care when compared with standardised medical care alone. Thus, adults with dissociative seizures might benefit from the addition of dissociative seizure-specific CBT to specialist care from neurologists and psychiatrists. Future work is needed to identify patients who would benefit most from a dissociative seizure-specific CBT approach. FUNDING: National Institute for Health Research, Health Technology Assessment programme

The “Is mpMRI Enough” or IMRIE Study: A Multicentre Evaluation of Prebiopsy Multiparametric Magnetic Resonance Imaging Compared with Biopsy

Background: Multiparametric magnetic resonance imaging (mpMRI) is now recommended prebiopsy in numerous healthcare regions based on the findings of high-quality studies from expert centres. Concern remains about reproducibility of mpMRI to rule out clinically significant prostate cancer (csPCa) in real-world settings. / Objective: To assess the diagnostic performance of mpMRI for csPCa in a real-world setting. / Design, setting, and participants: A multicentre, retrospective cohort study, including men referred with raised prostate-specific antigen (PSA) or an abnormal digital rectal examination who had undergone mpMRI followed by transrectal or transperineal biopsy, was conducted. Patients could be biopsy naïve or have had previous negative biopsies. / Outcome measurements and statistical analysis: The primary definition for csPCa was International Society of Urological Pathology (ISUP) grade group (GG) ≥2 (any Gleason ≥7); the accuracy for other definitions was also evaluated. / Results and limitations: Across ten sites, 2642 men were included (January 2011–November 2018). Mean age and PSA were 65.3 yr (standard deviation [SD] 7.8 yr) and 7.5 ng/ml (SD 3.3 ng/ml), respectively. Of the patients, 35.9% had “negative MRI” (scores 1–2); 51.9% underwent transrectal biopsy and 48.1% had transperineal biopsy, with 43.4% diagnosed with csPCa overall. The sensitivity and negative predictive value (NPV) for ISUP GG ≥ 2 were 87.3% and 87.5%, respectively. The NPVs were 87.4% and 88.1% for men undergoing transrectal and transperineal biopsy, respectively. Specificity and positive predictive value of MRI were 49.8% and 49.2%, respectively. The sensitivity and NPV increased to 96.6% and 90.6%, respectively, when a PSA density threshold of 0.15 ng/ml/ml was used in MRI scores 1–2; these metrics increased to 97.5% and 91.2%, respectively, for PSA density 0.12 ng/ml/ml. ISUP GG ≥ 3 (Gleason ≥4 + 3) was found in 2.4% (15/617) of men with MRI scores 1–2. They key limitations of this study are the heterogeneity and retrospective nature of the data. / Conclusions: Multiparametric MRI when used in real-world settings is able to rule out csPCa accurately, suggesting that about one-third of men might avoid an immediate biopsy. Men should be counselled about the risk of missing some significant cancers. / Patient summary: Multiparametric magnetic resonance imaging (MRI) is a useful tool for ruling out prostate cancer, especially when combined with prostate-specific antigen density (PSAD). Previous results published from specialist centres can be reproduced at smaller institutions. However, patients and their clinicians must be aware that an early diagnosis of clinically significant prostate cancer could be missed in nearly 10% of patients by relying on MRI and PSAD alone

MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes