Person-Specific Template Matching Using a Dynamic Time Warping Step-Count Algorithm for Multiple Walking Activities

This study aimed to develop and evaluate a new step-count algorithm, StepMatchDTWBA, for the accurate measurement of physical activity using wearable devices in both healthy and pathological populations. We conducted a study with 30 healthy volunteers wearing a wrist-worn MOX accelerometer (Maastricht Instruments, NL). The StepMatchDTWBA algorithm used dynamic time warping (DTW) barycentre averaging to create personalised templates for representative steps, accounting for individual walking variations. DTW was then used to measure the similarity between the template and accelerometer epoch. The StepMatchDTWBA algorithm had an average root-mean-square error of 2 steps for healthy gaits and 12 steps for simulated pathological gaits over a distance of about 10 m (GAITRite walkway) and one flight of stairs. It outperformed benchmark algorithms for the simulated pathological population, showcasing the potential for improved accuracy in personalised step counting for pathological populations. The StepMatchDTWBA algorithm represents a significant advancement in accurate step counting for both healthy and pathological populations. This development holds promise for creating more precise and personalised activity monitoring systems, benefiting various health and wellness applications.

Supporting Pain Self-Management in Patients With Cancer: App Development Based on a Theoretical and Evidence-Driven Approach

BACKGROUND

To inform the development of an intervention, it is essential to have a well-developed theoretical understanding of how an intervention causes change, as stated in the UK Medical Research Council guidelines for developing complex interventions. Theoretical foundations are often ignored in the development of mobile health apps intended to support pain self-management for patients with cancer.

OBJECTIVE

This study aims to systematically set a theory- and evidence-driven design for a pain self-management app and specify the app's active features.

METHODS

The Behavior Change Wheel (BCW) framework, a step-by-step theoretical approach to the development of interventions, was adopted to achieve the aim of this study. This started by understanding and identifying sources of behavior that could be targeted to support better pain management. Ultimately, the application of the BCW framework guided the identification of the active contents of the app, which were characterized using the Behavior Change Technique Taxonomy version 1.

RESULTS

The theoretical analysis revealed that patients may have deficits in their capability, opportunity, and motivation that prevent them from performing pain self-management. The app needs to use education, persuasion, training, and enablement intervention functions because, based on the analysis, they were found the most likely to address the specified factors. Eighteen behavior change techniques were selected to describe precisely how the intervention functions can be presented to induce the desired change regarding the intervention context. In other words, they were selected to form the active contents of the app, potentially reducing barriers and serving to support patients in the self-management of pain while using the app.

CONCLUSIONS

This study fully reports the design and development of a pain self-management app underpinned by theory and evidence and intended for patients with cancer. It provides a model example of the BCW framework application for health app development. The work presented in this study is the first systematic theory- and evidence-driven design for a pain app for patients with cancer. This systematic approach can support clarity in evaluating the intervention's underlying mechanisms and support future replication.

The Application of Artificial Intelligence in Digital Physical Activity and Falls Prevention Interventions for Older Adults

This article discusses the practical applications of artificial intelligence in digital physical activity and falls prevention interventions for older adults. It notes the range of technologies that can be used to collect digital datasets on older adult health and how machine learning algorithms can be applied to these to improve our understanding of physical activity and falls. In particular, these advanced computational techniques could help personalize exercises, feedback, and notifications to older people, improve adherence to and reduce attrition from digital health interventions, and enhance monitoring by providing predictive analytics on the physiological and environmental conditions that contribute to physical activity and falls in aging populations.

Contactless hand tremor amplitude measurement using smartphones: development and pilot evaluation

Background - Physiological tremor is defined as an involuntary and rhythmic shaking. Tremor of the hand is a key symptom of multiple neurological diseases, and its frequency and amplitude differs according to both disease type and disease progression. In routine clinical practice, tremor frequency and amplitude are assessed by expert rating using a 0 to 4 integer scale. Such ratings are subjective and have poor inter-rater reliability. There is thus a clinical need for a practical and accurate method for objectively assessing hand tremor.Objective - to develop a proof-of-principle method to measure hand tremor amplitude from smartphone videos.Methods - We created a computer vision pipeline that automatically extracts salient points on the hand and produces a 1-D time series of movement due to tremor, in pixels. Using the smartphones' depth measurement, we convert this measure into real distance units. We assessed the accuracy of the method using 60 videos of simulated tremor of different amplitudes from two healthy adults. Videos were taken at distances of 50, 75 and 100 cm between hand and camera. The participants had skin tone II and VI on the Fitzpatrick scale. We compared our method to a gold-standard measurement from a slide rule. Bland-Altman methods agreement analysis indicated a bias of 0.04 cm and 95% limits of agreement from -1.27 to 1.20 cm. Furthermore, we qualitatively observed that the method was robust to limited occlusion.Clinical relevance - We have demonstrated how tremor amplitude can be measured from smartphone videos. In conjunction with tremor frequency, this approach could be used to help diagnose and monitor neurological diseases.

Outlier detection of vital sign trajectories from COVID-19 patients

In this work, we present a novel trajectory comparison algorithm to identify abnormal vital sign trends, with the aim of improving recognition of deteriorating health.There is growing interest in continuous wearable vital sign sensors for monitoring patients remotely at home. These monitors are usually coupled to an alerting system, which is triggered when vital sign measurements fall outside a predefined normal range. Trends in vital signs, such as increasing heart rate, are often indicative of deteriorating health, but are rarely incorporated into alerting systems.We introduce a dynamic time warp distance-based measure to compare time series trajectories. We split each multi-variable sign time series into 180 minute, non-overlapping epochs. We then calculate the distance between all pairs of epochs. Each epoch is characterized by its mean pairwise distance (average link distance) to all other epochs, with clusters forming with nearby epochs.We demonstrate in synthetically generated data that this method can identify abnormal epochs and cluster epochs with similar trajectories. We then apply this method to a real-world data set of vital signs from 8 patients who had recently been discharged from hospital after contracting COVID-19. We show how outlier epochs correspond well with the abnormal vital signs and identify patients who were subsequently readmitted to hospital.

A novel temporal generative adversarial network for electrocardiography anomaly detection

Cardiac abnormality detection from Electrocardiogram (ECG) signals is a common task for cardiologists. To facilitate efficient and objective detection, automated ECG classification by using deep learning based methods have been developed in recent years. Despite their impressive performance, these methods perform poorly when presented with cardiac abnormalities that are not well represented, or absent, in the training data. To this end, we propose a novel one-class classification based ECG anomaly detection generative adversarial network (GAN). Specifically, we embedded a Bi-directional Long-Short Term Memory (Bi-LSTM) layer into a GAN architecture and used a mini-batch discrimination training strategy in the discriminator to synthesis ECG signals. Our method generates samples to match the data distribution from normal signals of healthy group so that a generalised anomaly detector can be built reliably. The experimental results demonstrate our method outperforms several state-of-the-art semi-supervised learning based ECG anomaly detection algorithms and robustly detects the unknown anomaly class in the MIT-BIH arrhythmia database. Experiments show that our method achieves the accuracy of 95.5% and AUC of 95.9% which outperforms the most competitive baseline by 0.7% and 1.7% respectively. Our method may prove to be a helpful diagnostic method for helping cardiologists identify arrhythmias.

Artificial intelligence for falls management in older adult care: A scoping review of nurses' role

AIM

This study aims to synthesize evidence on nurses' involvement in artificial intelligence research for managing falls in older adults.

BACKGROUND

Artificial intelligence techniques are used to analyse health datasets to aid clinical decision making, patient care and service delivery but nurses' involvement in this area of research for managing falls in older adults remains unknown.

EVALUATION

A scoping review was conducted. CINAHL, the Cochrane Library, Embase, MEDLI and PubMed were searched. Results were screened against inclusion criteria. Relevant data were extracted, and studies summarized using a descriptive approach.

KEY ISSUES

The evidence shows many artificial intelligence techniques, particularly machine learning, are used to identify falls risk factors and build predictive models that could help prevent falls in older adults, with nurses leading and participating in this research.

CONCLUSION

Further rigorous experimental research is needed to determine the effectiveness of algorithms in predicting aspects of falls in older adults and how to implement artificial intelligence tools in gerontological nursing practice.

IMPLICATIONS FOR NURSING MANAGEMENT

Nurses should pursue interdisciplinary collaborations and educational opportunities in artificial intelligence, so they can actively contribute to research on falls management. Nurses should facilitate the collection of digital falls datasets to support this emerging research agenda and the care of older adults.

Prognostic value of patient-reported outcome measures (PROMs) in adults with non-small cell Lung Cancer: a scoping review

Background

There is growing interest in the collection and use of patient-reported outcome measures (PROMs) to support clinical decision making in patients with non-small cell lung cancer (NSCLC). However, an overview of research into the prognostic value of PROMs is currently lacking.

Aim

To explore to what extent, how, and how robustly the value of PROMs for prognostic prediction has been investigated in adults diagnosed with NSCLC.

Methods

We systematically searched Medline, Embase, CINAHL Plus and Scopus for English-language articles published from 2011 to 2021 that report prognostic factor study, prognostic model development or validation study. Example data charting forms from the Cochrane Prognosis Methods Group guided our data charting on study characteristics, PROMs as predictors, predicted outcomes, and statistical methods. Two reviewers independently charted the data and critically appraised studies using the QUality In Prognosis Studies (QUIPS) tool for prognostic factor studies, and the risk of bias assessment section of the Prediction model Risk Of Bias ASsessment Tool (PROBAST) for prognostic model studies.

Results

Our search yielded 2,769 unique titles of which we included 31 studies, reporting the results of 33 unique analyses and models. Out of the 17 PROMs used for prediction, the EORTC QLQ-C30 was most frequently used (16/33); 12/33 analyses used PROM subdomain scores instead of the overall scores. PROMs data was mostly collected at baseline (24/33) and predominantly used to predict survival (32/33) but seldom other clinical outcomes (1/33). Almost all prognostic factor studies (26/27) had moderate to high risk of bias and all four prognostic model development studies had high risk of bias.

Conclusion

There is an emerging body of research into the value of PROMs as a prognostic factor for survival in people with NSCLC but the methodological quality of this research is poor with significant bias. This warrants more robust studies into the prognostic value of PROMs, in particular for predicting outcomes other than survival. This will enable further development of PROM-based prediction models to support clinical decision making in NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10151-z.

The pathway of impacts of aerosol direct effects on secondary inorganic aerosol formation

Airborne aerosols reduce surface solar radiation through light scattering and absorption (aerosol direct effects, ADEs), influence regional meteorology, and further affect atmospheric chemical reactions and aerosol concentrations. The inhibition of turbulence and the strengthened atmospheric stability induced by ADEs increases surface primary aerosol concentration, but the pathway of ADE impacts on secondary aerosol is still unclear. In this study, the online coupled meteorological and chemistry model (WRF-CMAQ; Weather Research and Forecasting-Community Multiscale Air Quality) with integrated process analysis was applied to explore how ADEs affect secondary aerosol formation through changes in atmospheric dynamics and photolysis processes. The meteorological condition and air quality in the Jing-Jin-Ji area (denoted JJJ, including Beijing, Tianjin, and Hebei Province in China) in January and July 2013 were simulated to represent winter and summer conditions, respectively. Our results show that ADEs through the photolysis pathway inhibit sulfate formation during winter in the JJJ region and promote sulfate formation in July. The differences are attributed to the alteration of effective actinic flux affected by single-scattering albedo (SSA). ADEs through the dynamics pathway act as an equally or even more important route compared with the photolysis pathway in affecting secondary aerosol concentration in both summer and winter. ADEs through dynamics traps formed sulfate within the planetary boundary layer (PBL) which increases sulfate concentration in winter. Meanwhile, the impact of ADEs through dynamics is mainly reflected in the increase of gaseous-precursor concentrations within the PBL which enhances secondary aerosol formation in summer. For nitrate, reduced upward transport of precursors restrains the formation at high altitude and eventually lowers the nitrate concentration within the PBL in winter, while such weakened vertical transport of precursors increases nitrate concentration within the PBL in summer, since nitrate is mainly formed near the surface ground.

Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs

Background. Twelve lead ECGs are a core diagnostic tool for cardiovascular diseases. Here, we describe and analyse an ensemble deep neural network architecture to classify 24 cardiac abnormalities from 12 lead ECGs.Method. We proposed a squeeze and excite ResNet to automatically learn deep features from 12-lead ECGs, in order to identify 24 cardiac conditions. The deep features were augmented with age and gender features in the final fully connected layers. Output thresholds for each class were set using a constrained grid search. To determine why the model made incorrect predictions, two expert clinicians independently interpreted a random set of 100 misclassified ECGs concerning left axis deviation.Results. Using the bespoke weighted accuracy metric, we achieved a 5-fold cross-validation score of 0.684, and sensitivity and specificity of 0.758 and 0.969, respectively. We scored 0.520 on the full test data, and ranked 2nd out of 41 in the official challenge rankings. On a random set of misclassified ECGs, agreement between two clinicians and training labels was poor (clinician 1:κ= -0.057, clinician 2:κ= -0.159). In contrast, agreement between the clinicians was very high (κ= 0.92).Discussion. The proposed prediction model performed well on the validation and hidden test data in comparison to models trained on the same data. We also discovered considerable inconsistency in training labels, which is likely to hinder development of more accurate models.

Understanding how the design and implementation of online consultations impact primary care quality: Systematic review of evidence with recommendations for designers, providers, and researchers (Preprint)

Background

Online consultations (OCs) allow patients to contact their care providers on the web. Worldwide, OCs have been rolled out in primary care rapidly owing to policy initiatives and COVID-19. There is a lack of evidence regarding how OC design and implementation influence care quality.

Objective

We aimed to synthesize research on the impacts of OCs on primary care quality, and how these are influenced by system design and implementation.

Methods

We searched databases from January 2010 to February 2022. We included quantitative and qualitative studies of real-world OC use in primary care. Quantitative data were transformed into qualitative themes. We used thematic synthesis informed by the Institute of Medicine domains of health care quality, and framework analysis informed by the nonadoption, abandonment, scale-up, spread, and sustainability framework. Strength of evidence was judged using the GRADE-CERQual approach.

Results

We synthesized 63 studies from 9 countries covering 31 OC systems, 14 (22%) of which used artificial intelligence; 41% (26/63) of studies were published from 2020 onward, and 17% (11/63) were published after the COVID-19 pandemic. There was no quantitative evidence for negative impacts of OCs on patient safety, and qualitative studies suggested varied perceptions of their safety. Some participants believed OCs improved safety, particularly when patients could describe their queries using free text. Staff workload decreased when sufficient resources were allocated to implement OCs and patients used them for simple problems or could describe their queries using free text. Staff workload increased when OCs were not integrated with other software or organizational workflows and patients used them for complex queries. OC systems that required patients to describe their queries using multiple-choice questionnaires increased workload for patients and staff. Health costs decreased when patients used OCs for simple queries and increased when patients used them for complex queries. Patients using OCs were more likely to be female, younger, and native speakers, with higher socioeconomic status. OCs increased primary care access for patients with mental health conditions, verbal communication difficulties, and barriers to attending in-person appointments. Access also increased by providing a timely response to patients’ queries. Patient satisfaction increased when using OCs owing to better primary care access, although it decreased when using multiple-choice questionnaire formats.

Conclusions

This is the first theoretically informed synthesis of research on OCs in primary care and includes studies conducted during the COVID-19 pandemic. It contributes new knowledge that, in addition to having positive impacts on care quality such as increased access, OCs also have negative impacts such as increased workload. Negative impacts can be mitigated through appropriate OC system design (eg, free text format), incorporation of advanced technologies (eg, artificial intelligence), and integration into technical infrastructure (eg, software) and organizational workflows (eg, timely responses).

Trial Registration

PROSPERO CRD42020191802; https://tinyurl.com/2p84ezjy

Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI

Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO _x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO₂ columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO _x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO _x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO₂. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO₂ reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative J NO 2 [ NO 2 ] - k NO + O 3 [ NO ] [ O 3 ] become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.

Accuracy of Smartphone Video for Contactless Measurement of Hand Tremor Frequency

Background

Computer vision can measure movement from video without the time and access limitations of hospital accelerometry/electromyography or the requirement to hold or strap a smartphone accelerometer.

Objective

To compare computer vision measurement of hand tremor frequency from smartphone video with a gold standard measure accelerometer.

Methods

A total of 37 smartphone videos of hands, at rest and in posture, were recorded from 15 participants with tremor diagnoses (9 Parkinson's disease, 5 essential tremor, 1 functional tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier transform and Bland-Altman analysis were applied. Tremor amplitude was scored by 2 clinicians.

Results

Bland-Altman analysis of dominant tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement -0.38 Hz to +0.35 Hz. In 36 of 37 videos (97%), there was <0.5 Hz difference between computer vision and accelerometer measurement. There was no significant correlation between the level of agreement and tremor amplitude.

Conclusion

The study suggests a potential new, contactless point-and-press measure of tremor frequency within standard clinical settings, research studies, or telemedicine.

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, elemental carbon, tropospheric O₃ residual, and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀ that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO _x ), volatile organic compounds (VOCs), and PM_2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O₃) and fine particulate matter (PM_2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O₃, sulfate, nitrate, ammonium, elemental carbon, tropospheric O₃ residual, and column nitrogen dioxide (NO₂). For example, the mean biases have been reduced by more than 10 W m^-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O₃. However, relatively large biases still exist for cloud predictions, some PM_2.5 species, and PM₁₀ that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O₃, nitrogen oxide (NO _x ), volatile organic compounds (VOCs), and PM_2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

A new approach for health-oriented ozone control strategy: Adjoint-based optimization of NOx emission reductions using metaheuristic algorithms

While levels of particulate matters in the Pearl River Delta Region (PRD) show a significant reduction, ozone (O₃) has an opposite increasing trend, becoming the critical air quality target in this decade. Emission control strategies are typically formulated sector by sector, spatial variability in emissions reductions and health impacts of air pollutants may not be taken into account, affecting the overall effectiveness of control strategies. This study proposes an adjoint-based optimization framework to facilitate health-oriented O₃ control over PRD. The location-specific adjoint sensitivity coefficients, which reflect the spatiotemporal influences from emissions of nitrogen dioxide (NO_x) on O₃ health impacts, are combined with metaheuristic algorithms to minimize the O₃-related premature mortalities over receptor regions. Using the proposed optimization methodology, the regional O₃ health benefits under current emission reduction policy can be increased by 16-27%. The results show that relatively larger NO_x emissions reductions occurred at highly developed and populated areas. Particularly, significant reductions in NO_x emissions are observed at Shenzhen and urban Guangzhou. Furthermore, implementing regional NO_x emissions abatement has advantages to achieve an overall O₃ health benefits for all cities. The interregional influences of NO_x emissions abatement between cities indicate a promising strategy of health-oriented O₃ control in PRD.

The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation

The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O₃ and daily PM_2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O₃, CMAQ531 has higher O₃ in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O₃ bias (2-4 ppbv monthly average). MDA8 O₃ is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O₃ from the lateral boundary conditions (BCs), which generally increases MDA8 O₃ bias in spring and fall ( 0.5 μg m^-3). For daily 24 h average PM_2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O₃ mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O₃ dry deposition to snow in CMAQ53) and lower O₃ mixing ratios in middle and lower latitudes year-round (due to reduced O₃ over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O₃ mixing ratios and higher PM_2.5 concentrations (0.1-0.25 μg m^-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O₃ is generally higher with M3Dry outside of summer, while PM_2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH₃, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.

Role of sea fog over the Yellow Sea on air quality with the direct effect of aerosols

In this study, we investigate the impact of sea fog over the Yellow Sea on air quality with the direct effect of aerosols for the entire year of 2016. Using the WRF-CMAQ two-way coupled model, we perform four model simulations with the up-to-date emission inventory over East Asia and dynamic chemical boundary conditions provided by hemispheric model simulations. During the spring of 2016, prevailing westerly winds and anticyclones caused the formation of a temperature inversion over the Yellow Sea, providing favorable conditions for the formation of fog. The inclusion of the direct effect of aerosols enhanced its strength. On foggy days, we find dominant changes of aerosols at an altitude of 150-200 m over the Yellow Sea resulted by the production through aqueous chemistry (~12.36% and ~3.08% increases in sulfate and ammonium) and loss via the wet deposition process (~-2.94% decrease in nitrate); we also find stronger wet deposition of all species occurring in PBL. Stagnant conditions associated with reduced air temperature caused by the direct effect of aerosols enhanced aerosol chemistry, especially in coastal regions, and it exceeded the loss of nitrate. The transport of air pollutants affected by sea fog extended to a much broader region. Our findings show that the Yellow Sea acts as not only a path of long-range transport but also as a sink and source of air pollutants. Further study should investigate changes in the impact of sea fog on air quality in conjunction with changes in the concentrations of aerosols and the climate.

Quantity and type of peer-reviewed evidence for popular free medical apps: Cross-sectional review

INTRODUCTION

- Mobile apps are being increasingly used as a tool to deliver clinical care. Evidence of efficacy for such apps varies, and appropriate levels of evidence may depend on the app's intended use. The UK's National Institute for Health and Care Excellence (NICE) recently developed an evidence standards framework, aiming to explicitly set out the required standards of evidence for different categories of digital health technologies. To determine current compliance with the evidence standards framework, the current study quantified the amount and type of peer-reviewed evidence associated with a cross-section of popular medical apps.

METHODS

- Apps were identified by selecting the top 100 free medical apps in the Apple App Store and all free apps in the NHS Apps Library. Each app was assigned to one of the four tiers (1, 2, 3a, 3b) in the NICE evidence standards framework. For each app, we conducted searches in Ovid-MEDLINE, Web of Science, Google Scholar, and via manufacturer websites to identify any published articles that assessed the app. This allowed us to determine our primary outcome, whether apps in tiers 3a/3b were more likely than apps in tier 1/2 to be associated with academic peer-reviewed evidence.

RESULTS

- We reviewed 125 apps in total (Apple App Store (n = 72), NHS Apps Library (n = 45), both (n = 8), of which 54 were categorized into the higher evidence standards framework tiers, 3a/3b. After screening, we extracted 105 relevant articles which were associated with 25 of the apps. Only 6 articles, pertaining to 3 apps, were reports of randomised controlled trials. Apps in tiers 3a/3b were more likely to be associated with articles than apps in lower tiers (χ² = 5.54, p = .01). The percentage of tier 3a/3b apps with associated articles was similar for both the NHS Apps Library (10/28) and Apple App store (7/24), (χ² = 0.042, p = .84).

DISCUSSION

- Apps that were in higher tiers 3a and 3b, indicating higher clinical risk, were more likely to have an associated article than those in lower categories. However, even in these tiers, supporting peer-reviewed evidence was missing in the majority of instances. In our sample, Apps from the NHS Apps Library were more no more likely to have supporting evidence than popular Apple App Store apps. This is of concern, given that NHS approval may influence uptake of app usage.

Supervised classification of bradykinesia in Parkinson's disease from smartphone videos

BACKGROUND

Slowness of movement, known as bradykinesia, is the core clinical sign of Parkinson's and fundamental to its diagnosis. Clinicians commonly assess bradykinesia by making a visual judgement of the patient tapping finger and thumb together repetitively. However, inter-rater agreement of expert assessments has been shown to be only moderate, at best.

AIM

We propose a low-cost, contactless system using smartphone videos to automatically determine the presence of bradykinesia.

METHODS

We collected 70 videos of finger-tap assessments in a clinical setting (40 Parkinson's hands, 30 control hands). Two clinical experts in Parkinson's, blinded to the diagnosis, evaluated the videos to give a grade of bradykinesia severity between 0 and 4 using the Unified Pakinson's Disease Rating Scale (UPDRS). We developed a computer vision approach that identifies regions related to hand motion and extracts clinically-relevant features. Dimensionality reduction was undertaken using principal component analysis before input to classification models (Naïve Bayes, Logistic Regression, Support Vector Machine) to predict no/slight bradykinesia (UPDRS = 0-1) or mild/moderate/severe bradykinesia (UPDRS = 2-4), and presence or absence of Parkinson's diagnosis.

RESULTS

A Support Vector Machine with radial basis function kernels predicted presence of mild/moderate/severe bradykinesia with an estimated test accuracy of 0.8. A Naïve Bayes model predicted the presence of Parkinson's disease with estimated test accuracy 0.67.

CONCLUSION

The method described here presents an approach for predicting bradykinesia from videos of finger-tapping tests. The method is robust to lighting conditions and camera positioning. On a set of pilot data, accuracy of bradykinesia prediction is comparable to that recorded by blinded human experts.

Time series clustering to examine presence of decrement in Parkinson's finger-tapping bradykinesia

Parkinson's disease is diagnosed based on expert clinical observation of movements. One important clinical feature is decrement, whereby the range of finger motion decreases over the course of the observation. This decrement has been assumed to be linear but has not been examined closely.We previously developed a method to extract a time series representation of a finger-tapping clinical test from 137 smart- phone video recordings. Here, we show how the signal can be processed to visualize archetypal progression of decrement. We use k-means with features derived from dynamic time warping to compare similarity of time series. To generate the archetypal time series corresponding to each cluster, we apply both a simple arithmetic mean, and dynamic time warping barycenter averaging to the time series belonging to each cluster.Visual inspection of the cluster-average time series showed two main trends. These corresponded well with participants with no bradykinesia and participants with severe bradykinesia. The visualizations support the concept that decrement tends to present as a linear decrease in range of motion over time.Clinical relevance- Our work visually presents the archetypal types of bradykinesia amplitude decrement, as seen in the Parkinson's finger-tapping test. We found two main patterns, one corresponding to no bradykinesia, and the other showing linear decrement over time.

Impact of wildfire on particulate matter in the southeastern United States in November 2016

In November 2016, a large area of wildfire occurred in the southeastern United States, concomitant with the occurrence of severe drought during the same period. Whereas the previous studies on biomass burning over this region mainly focused on the prescribed fire, this study investigated the impact of wildfire using the two-way-coupled Weather Research and Forecasting model and Community Multiscale Air Quality model. Two episodic wildfire burning events (November 6 to 9 and November 13 to 16, 2016) were selected, and the mean contribution to fine particulate matter (PM_2.5) in the southeastern United States from wildfires reached 9.6 to 42.5 μg m^-3 and 10.9 to 26.1 μg m^-3, with mean relative contributions of 41% and 49%, respectively, during these two events. The effect of wildfire propagates along the path of the smoke plume, which is determined by the wind speed and direction. For instance, during the first event, the dominant low-altitude wind vector displayed an anticyclonic-type flow with low wind speed, resulting in relatively localized influence and high intensity. In contrast, during the second event, relatively fast eastward wind, particularly over the latter part of the event, strengthened the diffusion and affected larger areas in comparison with the first event. Moreover, differently from the previous studies, this study took a further step to reveal the mechanism of the aerosol direct effect on the deterioration of air quality during wildfire, mainly through the modulation of reduction in surface downward shortwave radiation, planetary boundary layer height and wind speed, subsequently, facilitating pollution accumulation. Quantification analysis showed an average of 10% to 14% extra enhancement of PM_2.5 during the November 6 to 8 episode. Considering that more frequent drought is projected to occur in the southeastern United States, wildfire may play an even more important role in modulating the air quality in this region.

Significant ground-level ozone attributed to lightning-induced nitrogen oxides during summertime over the Mountain West States

Using lightning flash data from the National Lightning Detection Network with an updated lightning nitrogen oxides (NOx) emission estimation algorithm in the Community Multiscale Air Quality (CMAQ) model, we estimate the hourly variations in lightning NOx emissions for the summer of 2011 and simulate its impact on distributions of tropospheric ozone (O3) across the continental United States. We find that typical summer-time lightning activity across the U.S. Mountain West States (MWS) injects NOx emissions comparable to those from anthropogenic sources into the troposphere over the region. Comparison of two model simulation cases with and without lightning NOx emissions show that significant amount of ground-level O3 in the MWS during the summer can be attributed to the lightning NOX emissions. The simulated surface-level O3 from a model configuration incorporating lightning NOx emissions showed better agreement with the observed values than the model configuration without lightning NOx emissions. The time periods of significant reduction in bias in simulated O3 between these two cases strongly correlate with the time periods when lightning activity occurred in the region. The inclusion of lightning NOx increased daily maximum 8 h O3 by up to 17 ppb and improved model performance relative to measured surface O3 mixing ratios in the MWS region. Analysis of model results in conjunction with lidar measurements at Boulder, Colorado during July 2014 corroborated similar impacts of lightning NOx emissions on O3 emissions estimated for other summers is comparable to the 2011 air quality. The magnitude of lightning NOx estimates suggesting that summertime surface-level O3 levels in the MWS region could be significantly influenced by lightning NOx.

Bedside breath tests in children with abdominal pain: a prospective pilot feasibility study

Background

There is no definitive method of accurately diagnosing appendicitis before surgery. We evaluated the feasibility of collecting breath samples in children with abdominal pain and gathered preliminary data on the accuracy of breath tests.

Methods

We conducted a prospective pilot study at a large tertiary referral paediatric hospital in the UK. We recruited 50 participants with suspected appendicitis, aged between 5 and 15 years. Five had primary diagnosis of appendicitis. The primary outcome was the number of breath samples collected. We also measured the number of samples processed within 2 h and had CO₂ ≥ 3.5%. Usability was assessed by patient-reported pain pre- and post-sampling and user-reported sampling difficulty. Logistic regression analysis was used to predict appendicitis and evaluated using the area under the receiver operator characteristic curve (AUROC).

Results

Samples were collected from all participants. Of the 45 samples, 36 were processed within 2 h. Of the 49 samples, 19 had %CO₂ ≥ 3.5%. No difference in patient-reported pain was observed (p = 0.24). Sampling difficulty was associated with patient age (p = 0.004). The logistic regression model had AUROC = 0.86.

Conclusions

Breath tests are feasible and acceptable to patients presenting with abdominal pain in clinical settings. We demonstrated adequate data collection with no evidence of harm to patients. The AUROC was better than a random classifier; more specific sensors are likely to improve diagnostic performance.

Trial registration

ClinicalTrials.gov, NCT03248102. Registered 14 Aug 2017.

Simulating lightning NO production in CMAQv5.2: evolution of scientific updates

This work describes the lightning nitric oxide (LNO) production schemes in the Community Multiscale Air Quality (CMAQ) model. We first document the existing LNO production scheme and vertical distribution algorithm. We then describe updates that were made to the scheme originally based on monthly National Lightning Detection Network (mNLDN) observations. The updated scheme uses hourly NLDN (hNLDN) observations. These NLDN-based schemes are good for retrospective model applications when historical lightning data are available. For applications when observed data are not available (i.e., air quality forecasts and climate studies that assume similar climate conditions), we have developed a scheme that is based on linear and log-linear parameters derived from regression of multiyear historical NLDN (pNLDN) observations and meteorological model simulations. Preliminary assessment for total column LNO production reveals that the mNLDN scheme overestimates LNO by over 40% during summer months compared with the updated hNLDN scheme that reflects the observed lightning activity more faithfully in time and space. The pNLDN performance varies with year, but it generally produced LNO columns that are comparable to hNLDN and mNLDN, and in most cases it outperformed mNLDN. Thus, when no observed lightning data are available, pNLDN can provide reasonable estimates of LNO emissions over time and space for this important natural NO source that influences air quality regulations.

Source contributions of surface ozone in China using an adjoint sensitivity analysis

Air pollution has become an adverse environmental problem in China, resulting in serious public health impacts. This study advanced and applied the CMAQ adjoint model to quantitatively assess the source-receptor relationships between surface ozone (O₃) changes over different receptor regions and precursor emissions across all locations in China. Five receptor regions were defined based on the administrative division, including northern China (NC), southern China (SC), Pearl River Delta region (PRD), Yangtz River Delta region (YRD), and Beijing-Tianjin-Hebei region (BTH). Our results identified the different influential pathways of atmospheric processes and emissions to O₃ pollution. We found that the atmospheric processes such as horizontal and vertical advection could offset the O₃ removal through chemical reactions in VOC-limited areas inside the receptor regions. In addition, O₃ pollution can be induced by transport of O₃ directly or its precursors. Our results of relative source contributions to O₃ show that transboundary O₃ pollution was significant in SC, NC and YRD, while the O₃ pollution in PRD and BTH were more contributed by local sources. Anhui, Hubei and Jiangsu provinces were the three largest source areas of NO_x and VOC emissions to O₃ in SC (>52%) and YRD (>69%). NO_x and VOC emissions from Tianjin and Beijing were the largest contributors to O₃ in NC (>34%) and BTH (>51%). PRD was the dominant source areas of NO_x (>89%) and VOC emissions (~98%) to its own regional O₃.

The impact of air pollutant deposition on solar energy system efficiency: An approach to estimate PV soiling effects with the Community Multiscale Air Quality (CMAQ) model

Deposition and accumulation of aerosol particles on photovoltaics (PV) panels, which is commonly referred to as "soiling of PV panels," impacts the performance of the PV energy system. It is desirable to estimate the soiling effect at different locations and times for modeling the PV system performance and devising cost-effective mitigation. This study presents an approach to estimate the soiling effect by utilizing particulate matter (PM) dry deposition estimates from air quality model simulations. The Community Multiscale Air Quality (CMAQ) modeling system used in this study was developed by the U.S. Environmental Protection Agency (U.S. EPA) for air quality assessments, rule-making, and research. Three deposition estimates based on different surface roughness length parameters assumed in CMAQ were used to illustrate the soling effect in different land-use types. The results were analyzed for three locations in the U.S. for year 2011. One urban and one suburban location in Colorado were selected because there have been field measurements of particle deposition on solar panels and analysis on the consequent soiling effect performed at these locations. The third location is a coastal city in Texas, the City of Brownsville. These three locations have distinct ambient environments. CMAQ underestimates particle deposition by 40% to 80% when compared to the field measurements at the two sites in Colorado due to the underestimations in both the ambient PM₁₀ concentration and deposition velocity. The estimated panel transmittance sensitivity due to the deposited particles is higher than the sensitivity obtained from the measurements in Colorado. The final soiling effect, which is transmittance loss, is estimated as 3.17 ± 4.20% for the Texas site, 0.45 ± 0.33%, and 0.31 ± 0.25% for the Colorado sites. Although the numbers are lower compared to the measurements in Colorado, the results are comparable with the soiling effects observed in U.S.

The impact of the direct effect of aerosols on meteorology and air quality using aerosol optical depth assimilation during the KORUS-AQ campaign

To quantify the impact of the direct aerosol effect accurately, this study incorporated the Geostationary Ocean Color Imager (GOCI) aerosol optical depth (AOD) into a coupled meteorology-chemistry model. We designed three model simulations to observe the impact of AOD assimilation and aerosol feedback during the KORUS-AQ campaign (May - June 2016). By assimilating the GOCI AOD with high temporal and spatial resolutions, we improve the statistics from the comparison AOD and AERONET data (RMSE: 0.12, R: 0.77, IOA: 0.69, MAE: 0.08). The inclusion of the direct effect of aerosols produces the best model performance (RMSE: 0.10, R: 0.86, IOA: 0.72, MAE: 0.07). AOD values were increased as much as 0.15, which is associated with an average reduction in solar radiation of -31.39 W/m², a planetary boundary layer height (-104.70 m), an air temperature (-0.58 °C), and a surface wind speed (-0.07 m/s) over land. In addition, concentrations of major gaseous and particulate pollutants at the surface (SO₂, NO₂, NH₃, SO 4 2 - , NO 3 - , NH 4 + , PM_2.5) increase by 7.87 - 34% while OH concentration decreases by -4.58 %. Changes in meteorology and air quality appear to be more significant in high-aerosol loading areas. The integrated process rate analysis shows decelerated vertical transport, resulting in an accumulation of air pollutants near the surface and the amount of nitrate, which is higher than that of sulfate because of its response to reduced temperature. We conclude that constraining aerosol concentrations using geostationary satellite data is a prerequisite for quantifying the impact of aerosols on meteorology and air quality.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment in the Pacific Northwest focused on cropland residue burning was used to evaluate model performance in capturing surface and aloft impacts from the burning events. The Community Multiscale Air Quality (CMAQ) model was used to simulate multiple crop residue burns with 2 km grid spacing using field-specific information and also more general assumptions traditionally used to support National Emission Inventory based assessments. Field study specific information, which includes area burned, fuel consumption, and combustion completeness, resulted in increased biomass consumption by 123 tons (60% increase) on average compared to consumption estimated with default methods in the National Emission Inventory (NEI) process. Buoyancy heat flux, a key parameter for model predicted fire plume rise, estimated from fuel loading obtained from field measurements can be 30% to 200% more than when estimated using default field information. The increased buoyancy heat flux resulted in higher plume rise by 30% to 80%. This evaluation indicates that the regulatory air quality modeling system can replicate intensity and transport (horizontal and vertical) features for crop residue burning in this region when region-specific information is used to inform emissions and plume rise calculations. Further, previous vertical emissions allocation treatment of putting all cropland residue burning in the surface layer does not compare well with measured plume structure and these types of burns should be modeled more similarly to prescribed fires such that plume rise is based on an estimate of buoyancy.

Long-term trends in the ambient PM2.5- and O3-related mortality burdens in the United States under emission reductions from 1990 to 2010

Concentrations of both fine particulate matter (PM2.5) and ozone (O3) in the United States (US) have decreased significantly since 1990, mainly because of air quality regulations. Exposure to these air pollutants is associated with premature death. Here we quantify the annual mortality burdens from PM2.5 and O3 in the US from 1990 to 2010, estimate trends and inter-annual variability, and evaluate the contributions to those trends from changes in pollutant concentrations, population, and baseline mortality rates. We use a fine-resolution (36 km) self-consistent 21-year simulation of air pollutant concentrations in the US from 1990 to 2010, a health impact function, and annual county-level population and baseline mortality rate estimates. From 1990 to 2010, the modeled population-weighted annual PM2.5 decreased by 39 %, and summertime (April to September) 1 h average daily maximum O3 decreased by 9 % from 1990 to 2010. The PM2.5-related mortality burden from ischemic heart disease, chronic obstructive pulmonary disease, lung cancer, and stroke steadily decreased by 54% from 123 700 deaths year-1 (95% confidence interval, 70 800-178 100) in 1990 to 58 600 deaths year-1 (24 900-98 500) in 2010. The PM2.5-related mortality burden would have decreased by only 24% from 1990 to 2010 if the PM2.5 concentrations had stayed at the 1990 level, due to decreases in baseline mortality rates for major diseases affected by PM2.5. The mortality burden associated with O3 from chronic respiratory disease increased by 13% from 10 900 deaths year-1 (3700-17 500) in 1990 to 12 300 deaths year-1 (4100-19 800) in 2010, mainly caused by increases in the baseline mortality rates and population, despite decreases in O3 concentration. The O3-related mortality burden would have increased by 55% from 1990 to 2010 if the O3 concentrations had stayed at the 1990 level. The detrended annual O3 mortality burden has larger inter-annual variability (coefficient of variation of 12%) than the PM2.5-related burden (4%), mainly from the inter-annual variation of O3 concentration. We conclude that air quality improvements have significantly decreased the mortality burden, avoiding roughly 35 800 (38%) PM2.5-related deaths and 4600 (27%) O3-related deaths in 2010, compared to the case if air quality had stayed at 1990 levels (at 2010 baseline mortality rates and population).

High reduction of ozone and particulate matter during the 2016 G-20 summit in Hangzhou by forced emission controls of industry and traffic

Many regions in China experience air pollution episodes because of the rapid urbanization and industrialization over the past decades. Here we analyzed the effect of emission controls implemented during the G-20 2016 Hangzhou summit on air quality. Emission controls included a forced closure of highly polluting industries, and limiting traffic and construction emissions in the cities and surroundings. Particles with aerodynamic diameter lower than 2.5 µm (PM_2.5) and ozone (O₃) were measured. We also simulated air quality using a forecast system consisting of the two-way coupled Weather Research and Forecast and Community Multi-scale Air Quality (WRF-CMAQ) model. Results show PM_2.5 and ozone levels in Hangzhou during the G-20 Summit were considerably lower than previous to the G-20 Summit. The predicted concentrations of ozone were reduced by 25.4%, whereas the predicted concentrations of PM_2.5 were reduced by 56%.

Historical Trends in PM2.5-Related Premature Mortality during 1990-2010 across the Northern Hemisphere

BACKGROUND

Air quality across the northern hemisphere over the past two decades has witnessed dramatic changes, with continuous improvement in developed countries in North America and Europe, but a contrasting sharp deterioration in developing regions of Asia.

OBJECTIVE

This study investigates the historical trend in the long-term exposure to PM2.5 and PM2.5-related premature mortality (PM2.5-mortality) and its response to changes in emission that occurred during 1990-2010 across the northern hemisphere. Implications for future trends in human exposure to air pollution in both developed and developing regions of the world are discussed.

METHODS

We employed the integrated exposure-response model developed by Health Effects Institute to estimate the PM2.5-mortality. The 1990-2010 annual average PM2.5 concentrations were obtained from the simulations using the WRF-CMAQ model. Emission mitigation efficiencies of sulfur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), and primary PM are estimated from the PM2.5-mortality responses to the emission variations.

RESULTS

Estimated PM2.5-mortalities in East Asia and South Asia increased by 21% and 85% respectively, from 866,000 and 578,000 in 1990, to 1,048,000 and 1,068,000 in 2010. PM2.5-mortalities in developed regions (i.e., Europe and high-income North America) decreased substantially by 67% and 58% respectively.

CONCLUSIONS

Over the past two decades, correlations between population and PM2.5 have become weaker in Europe and North America due to air pollution controls but stronger in East Asia due to deteriorating air quality. Mitigation of primary PM appears to be the most efficient way for increasing health benefits (i.e., providing the largest mortality reduction per unit emissions). However, reductions in emissions of NH3 are needed to maximize the effectiveness of NOx emission controls. Citation: Wang J, Xing J, Mathur R, Pleim JE, Wang S, Hogrefe C, Gan CM, Wong DC, Hao J. 2017. Historical trends in PM2.5-related premature mortality during 1990-2010 across the northern hemisphere. Environ Health Perspect 125:400-408; http://dx.doi.org/10.1289/EHP298.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O₃) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM_2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O₃ mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM_2.5 bias (PM_2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O₃ and PM_2.5 on average in January and July. Overall, the seasonal variation in simulated PM_2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM_2.5 concentrations decrease in the winter (when PM_2.5 is generally overestimated by CMAQ) and increase in the summer (when PM_2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O₃ mean bias, as O₃ tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O₃ is low); however, O₃ correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO _x (NO + NO₂), VOC and SO _x (SO₂ + SO₄) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O₃ due to large, widespread reductions in observed emissions.

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency.

Impacts of aerosol direct effects on tropospheric ozone through changes in atmospheric dynamics and photolysis rates

Aerosol direct effects (ADEs), i.e., scattering and absorption of incoming solar radiation, reduce radiation reaching the ground and the resultant photolysis attenuation can decrease ozone (O₃) formation in polluted areas. One the other hand, evidence also suggests that ADE-associated cooling suppresses atmospheric ventilation, thereby enhancing surface-level O₃. Assessment of ADE impacts is thus important for understanding emission reduction strategies that seek co-benefits associated with reductions in both particuate matter and O₃ levels. This study quantifies the impacts of ADEs on tropospheric ozone by using a two-way online coupled meteorology and atmospheric chemistry model, WRF- CMAQ, using a process analysis methodology. Two mani-festations of ADE impacts on O3 including changes in atmospheric dynamics (ᐃDynamics) and changes in photolysis rates (∆Photolysis) were assessed separately through multiple scenario simulations for January and July of 2013 over China. Results suggest that ADEs reduced surface daily maxima 1 h O₃ (DM1O₃) in China by up to 39μgm^-3 through the combination of ∆Dynamics and ∆Photolysis in January but enhanced surface DM1O₃ by up to 4μgm^-3 in July. Increased O₃ in July is largely attributed to ∆Dynamics, which causes a weaker O₃ sink of dry deposition and a stronger O₃ source of photochemistry due to the stabilization of the at-mosphere. Meanwhile, surface OH is also enhanced at noon in July, though its daytime average values are reduced in January. An increased OH chain length and a shift towards more volatile organic compound (VOC)-limited conditions are found due to ADEs in both January and July. This study suggests that reducing ADEs may have the potential risk of increasing O₃ in winter, but it will benefit the reduction in maxima O₃ in summer.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O₃) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM_2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O₃ mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM_2.5 bias (PM_2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O₃ and PM_2.5 on average in January and July. Overall, the seasonal variation in simulated PM_2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM_2.5 concentrations decrease in the winter (when PM_2.5 is generally overestimated by CMAQ) and increase in the summer (when PM_2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O₃ mean bias, as O₃ tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O₃ is low); however, O₃ correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO _x (NO + NO₂), VOC and SO _x (SO₂ + SO₄) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O₃ due to large, widespread reductions in observed emissions.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O₃) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM_2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O₃ mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM_2.5 bias (PM_2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O₃ and PM_2.5 on average in January and July. Overall, the seasonal variation in simulated PM_2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM_2.5 concentrations decrease in the winter (when PM_2.5 is generally overestimated by CMAQ) and increase in the summer (when PM_2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O₃ mean bias, as O₃ tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O₃ is low); however, O₃ correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO _x (NO + NO₂), VOC and SO _x (SO₂ + SO₄) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O₃ due to large, widespread reductions in observed emissions.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2.5 bias (PM2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2.5 on average in January and July. Overall, the seasonal variation in simulated PM2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2.5 concentrations decrease in the winter (when PM2.5 is generally overestimated by CMAQ) and increase in the summer (when PM2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low); however, O3 correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO x (NO + NO2), VOC and SO x (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions.

Unexpected Benefits of Reducing Aerosol Cooling Effects

Impacts of aerosol cooling are not limited to changes in surface temperature since modulation of atmospheric dynamics resulting from the increased stability can deteriorate local air quality and impact human health. Health impacts from two manifestations of the aerosol direct effects (ADE) are estimated in this study: (1) the effect on surface temperature and (2) the effect on air quality through atmospheric dynamics. Average mortalities arising from the enhancement of surface PM2.5 concentration due to ADE in East Asia, North America and Europe are estimated to be 3-6 times higher than reduced mortality from decreases of temperature due to ADE. Our results suggest that mitigating aerosol pollution is beneficial in decreasing the impacts of climate change arising from these two manifestations of ADE health impacts. Thus, decreasing aerosol pollution gets direct benefits on health, and indirect benefits on health through changes in local climate and not offsetting changes associated only with temperature modulations as traditionally thought. The modulation of air pollution due to ADE also translates into an additional human health dividend in regions (e.g., U.S. Europe) with air pollution control measures but a penalty for regions (e.g., Asia) witnessing rapid deterioration in air quality.

Transient macular edema after intracameral injection of a moderately elevated dose of cefuroxime during phacoemulsification surgery

IMPORTANCE

Intracameral injection of cefuroxime sodium (1 mg/0.1 mL) has been reported to reduce the risk of endophthalmitis following cataract surgery. In the United States it must be compounded, which is subject to dilution error. We describe a series of 13 eyes that received intracameral injection of cefuroxime sodium, 9 mg/0.1 mL, intraoperatively.

OBSERVATIONS

On postoperative day 1, 6 of 13 eyes (46%; 95% CI, 19%-75%) had visual acuity of 20/70 or worse and macular edema. Spectral-domain optical coherence tomography of 2 eyes revealed central subfield thicknesses of 909 and 873 µm. On postoperative day 4, the mean (SD) central subfield thickness was 309 (78) µm in the 6 eyes with diagnosed macular edema, 279 (23) µm in the fellow eyes, and 271 (38) µm in the 7 exposed eyes without macular edema. The mean (SD) time to resolution of macular edema was 5.2 (1.3) days; the final central subfield thickness ranged from 193 to 293 µm. All eyes, except 2 with preexisting ocular comorbidity, had a best-corrected final visual acuity at 1 month of 20/30 or better. Significant corneal edema was not observed.

CONCLUSIONS AND RELEVANCE

Intracameral injection of cefuroxime sodium at a dose of 9 mg/0.1 mL was associated with transient macular edema and diminished visual acuity in 6 of 13 exposed eyes (46%), resolving largely within 1 week.

Sensitivity and linearity analysis of ozone in East Asia: the effects of domestic emission and intercontinental transport

In this study, ozone (O3) sensitivity and linearity over East Asia (EA) and seven urban areas are examined with an integrated air quality modeling system under two categories of scenarios: (1) The effects of domestic emission are estimated under local emission reduction scenarios, as anthropogenic NO(x) and volatile organic compounds (VOC) emissions are reduced by 20%, 50%, and 100%, respectively and independently; and (2) the influence of intercontinental transport is evaluated under Task Force on Hemispheric Transport of Air Pollution (TF HTAP) emission reduction scenarios, as anthropogenic NO(x) emission is reduced by 20% in Europe (EU), North America (NA), and South Asia (SA), respectively. Simulations are conducted for January and July 2001 to examine seasonal variation. Through the domestic O3 sensitivity investigation, we find O3 sensitivity varies dynamically depending on both time and location: North EA is VOC limited in January and NO(x) limited in July, except for the urban areas Beijing, Shanghai, Tokyo, and Seoul, which are VOC limited in both months; south EA is NO(x) limited in both January and July, except for the urban areas Taipei, which is VOC-limited in both months, and Pearl River Delta, which is VOC limited in January. Surface O3 change is found to be affected more by NO(x) than by VOC over EA in both January and July. We also find different O3 linearity characteristics among urban areas in EA: O3 at Beijing, Tokyo, and Seoul shows a strong negative linear response to NO(x) emission in January; O3 at Shanghai, Pearl River Delta, and Taipei shows a strong positive response to VOC emission in both January and July. Through the long-range transport investigation, monthly O3 changes over EA resulting from different source regions indicate the largest source contribution comes from NA (0.23 ppb), followed by SA (0.11 ppb) and EU (0.10 ppb). All of the three regions show higher impacts in January than in July.

IMPLICATIONS

This study examine O3 sensitivities and linear response of NO(x) and VOC emission over EA and seven urban areas based on regional air quality modeling system MM5/CMAQ. We also quantify the intercontinental transport effect from EU, SA, and NA over EA. The result provide a theoretical basis for emission control strategy design in EA, and also reveal the O3 special nonlinearity features for further related studies that are applicable to other continents. The HTAP multimodel experiments need to examine the potential impacts on ground-level O3 of changes in meteorology and transport patterns expected as a result of the regional scale.

Cost Impacts of Anti-Reflection Coatings on Silicon Solar Cells

Despite the early discovery of the Photovoltaic effect by Bechquerel almost 107 years ago, its commercial value had never been seriously considered because of its high cost in production and low in energy conversion efficiency. A familiar predicament has restrained demand for photovoltaic application: People won't use them until they are affordable, but they won't get affordable until there is a mass market for them. As has happened in other expensive markets, businesses are desperate to crack the conundrum. Since the oil shortage in the 70s, crystalline solar cell efficiency has increased from 8% to over 13% to date on 100 mm2 commercial silicon cells by refining the process with advanced device technologies. Together with increased production volume, the cost per watt has been reduced from over $ 8 in the 80's to as low as $3 to day. However, the cost is still considered too high to compete with fossil fuel energy. Further cost reduction is necessary by improving the cell and module conversion efficiency. The increase in cell efficiency and the process to achieve the goal, however, have to follow the golden rule of economics that the operational cost is a fraction of the profit in return. It is shown numerically in this paper that Anti Reflection (AR) coating on silicon solar cells by Atmospheric Pressure Chemical Vapor Deposition (APCVD) technique for large volume production could have over 650% profit return.

Comparison of magnetic resonance imaging–fluorodeoxy- glucose positron emission tomography fusion with pathological staging in rectal cancer

Background

This study represents an initial experience with combined magnetic resonance imaging (MRI) and [18F]fluorodeoxyglucose positron emission tomography (FDG PET) (MRI–PET fusion) in the primary staging of rectal carcinoma.

Methods

A retrospective analysis of data recorded on patients with rectal cancer was undertaken. Patients requiring long-course radiotherapy were excluded. Chest radiography, abdominal computed tomography and endorectal ultrasonography were performed. In addition, MRI of the pelvis, whole-body FDG PET and MRI–PET fusion were carried out. All patients subsequently underwent anterior resection.

Results

Twenty-three patients with rectal carcinoma (15 men), of median age 60 (range 46–75) years, were enrolled. In tumour (T) assessment, MRI correctly staged 14 of 22 T2/T3 tumours. In lymph node assessment, MRI–PET fusion had a sensitivity of 44 per cent, with a specificity and positive predictive value of 100 per cent. No additional information was acquired from MRI–PET fusion over MRI plus abdominal computed tomography and chest radiography.

Conclusion

MRI–PET fusion adds little to conventional investigations for staging rectal carcinoma.

Ultrasonography of the hand and wrist

Musculoskeletal ultrasonography (US) of the hands and wrist has recently been increasing in popularity. Recent rapid technical advances in the US, such as new ultra-high frequency probes and smaller probe sizes, have led to improved image quality. This, in turn, has accelerated the growth of musculoskeletal US. Known advantages of US are its lack of ionising radiation, noninvasiveness, portability and low cost. Dynamic and real-time assessment and Doppler imaging are additional benefits of this modality, especially in the imaging of the hands and wrist. Superficial structures of the hands and wrist, including the tendons, ligaments, nerves and vessels, are amenable to imaging with high frequency US. In this article, we demonstrate a spectrum of hand and wrist pathology using US, including entrapment neuropathy, inflammatory conditions, traumatic injury and masses. Ultrasound-guided procedures applicable to the hand and wrist are also briefly discussed.

Erdheim-Chester disease: a rare cause of acute renal failure

Erdheim-Chester disease (ECD) is a rare systemic histiocytic infiltrative disease of unknown aetiology. In radiology it is characterized by symmetrical sclerotic bone lesions predominantly affecting the diaphyses and metaphyses of long bones. Perivascular fibrosis has been reported in the literature as being a feature of this disease and we report one such case that presented with an encased aorta and renal arteries leading to acute renal failure. The diagnosis of ECD was delayed until a biopsy of the retroperitoneal infiltrate was performed. Further imaging with fluorine 18 deoxyglucose positron emission tomography, bone scintigraphy, plain films of the long bones and CT of the chest, abdomen and pelvis were performed to assess the extent of the patient's systemic disease involvement. To our knowledge, this is the first reported case of ECD presenting with acute renal failure secondary to bilateral occlusion of the renal arteries.