A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution.

Monitoring of volatile organic compounds (VOCs) in air is crucial for understanding their atmospheric impacts and advancing their emission reduction plans. This study presents an innovative integrated methodology suitable for achieving semireal-time high spatiotemporal resolution three-dimensional measurements of VOCs from ground to hundreds of meters above ground. The methodology integrates an active AirCore sampler, custom-designed for deployment from unmanned aerial vehicles (UAV), a proton-transfer-reaction mass spectrometry (PTR-MS) for sample analysis, and a data deconvolution algorithm for improved time resolution for measurements of multiple VOCs in air. The application of the deconvolution technique significantly improves the signal strength of data from PTR-MS analysis of AirCore samples and enhances their temporal resolution by 4 to 8 times to 4-11 s. A case study demonstrates that the methodology can achieve sample collection and analysis of VOCs within 45 min, resulting in >120-360 spatially resolved data points for each VOC measured and achieving a horizontal resolution of 20-55 m at a UAV flight speed of 5 m/s and a vertical resolution of 5 m. This methodology presents new possibilities for acquiring 3-dimensional spatial distributions of VOC concentrations, effectively tackling the longstanding challenge of characterizing three-dimensional VOC distributions in the lowest portion of the atmospheric boundary layer.

Quantification of Methane Emissions from Cold Heavy Oil Production with Sand Extraction in Alberta and Saskatchewan, Canada.

Cold heavy oil production with sand (CHOPS) is an extraction process for heavy oil in Canada, with the potential to lead to higher CH4 venting than conventional oil sites, that have not been adequately characterized. In order to quantify CH4 emissions from CHOPS activities, a focused aerial measurement campaign was conducted in the Canadian provinces of Alberta and Saskatchewan in June 2018. Total CH4 emissions from each of 10 clusters of CHOPS wells (containing 22-167 well sites per cluster) were derived using a mass balance computation algorithm that uses in situ wind data measurement on board aircraft. Results show that there is no statistically significant difference in CH4 emissions from CHOPS wells between the two provinces. Cluster-aggregated emission factors (EF) were determined using correspondingly aggregated production volumes. The average CH4 EF was 70.4 ± 36.9 kg/m3 produced oil for the Alberta wells and 55.1 ± 13.7 kg/m3 produced oil for the Saskatchewan wells. Using these EF and heavy oil production volumes reported to provincial regulators, the annual CH4 emissions from CHOPS were estimated to be 121% larger than CHOPS emissions extracted from Canada's National Inventory Report (NIR) for Saskatchewan. The EF were found to be positively correlated with the percentage of nonpiped production volumes in each cluster, indicating higher emissions for nonpiped wells while suggesting an avenue for methane emission reductions. A comparison with recent measurements indicates relatively limited effectiveness of regulations for Saskatchewan compared to those in Alberta. The results of this study indicate the substantial contribution of CHOPS operations to the underreporting observed in the NIR and provide measurement-based EF that can be used to develop improved emissions inventories for this sector and mitigate CH4 emissions from CHOPS operations.

Adherence to ACSM exercise guidelines and its influence on Fibromyalgia treatment outcomes: a meta-analysis of randomized controlled trials.

Background: The Fibromyalgia Syndrome (FMS) is a multifaceted chronic pain disorder that exerts a substantial impact on the overall state of health and quality of life of patients. Purpose: Investigate the effects of exercise therapy and adherence to the American College of Sports Medicine (ACSM) guidelines on treatment outcomes in FMS patients. Methods: The literature search, which concluded in October 2023, encompassed studies investigating the impact of exercise interventions on patients diagnosed with FMS and providing adequate data for calculating standardized mean difference (SMD). The primary outcome measures encompassed the Fibromyalgia Impact Questionnaire (FIQ) and Health Assessment Questionnaire (HAQ), while secondary outcome measures comprised pain levels, sleep quality, fatigue, and mental health. Results: Among 4,008 records, 19 studies (patients = 857) were eligible for qualitative synthesis. The meta-analysis revealed that the SMD for overall state of health impact was -0.94 (95%CI -1.26, -0.63), and the pooled SMD for the subgroup with high adherence to ACSM guidelines was -1.17 (95%CI -1.65, -0.69). The SMD for the subgroup with low or uncertain adherence was -0.73 (95%CI -1.12, -0.34). The overall effects included a -1.21 (95%CI -1.62, -0.79) SMD for pain relief, with high adherence achieving a -1.32 (95%CI -2.00, -0.64) SMD and low adherence a -1.06 (95%CI -1.55, -0.57) SMD. Mental health improvements showed a -0.95 (95%CI -1.32, -0.57) overall SMD, with high and low adherence subgroups at -0.96 (95%CI -1.62, -0.30) and -0.94 (95%CI -1.29, -0.60), respectively. Sleep quality impact was -1.59 (95%CI -2.31, -0.87) overall, with high adherence at -1.71 (95%CI -2.58, -0.83) and low adherence at -1.11 (95%CI -1.88, -0.33). Fatigue impact had a -1.55 (95%CI -2.26, -0.85) overall SMD, with -1.77 (95%CI -3.18, -0.36) for high adherence and -1.35 (95%CI -2.03, -0.66) for low adherence. Conclusion: Exercise therapy can improve the overall state of health, pain, sleep, and fatigue of FMS patients, particularly when adhering to ACSM guidelines. However, adherence levels do not affect mental health gains, indicating a need for future research on psychological impact. Systematic Review Registration: https://inplasy.com/inplasy-2024-3-0106/, identifier INPLASY202430106.

The reliability and validity of a novel wearable inertial sensor to measure the cervical proprioception.

BACKGROUND: Proprioceptive function assessment is crucial in clinical practice for patients with chronic non-specific neck pain (CNNP) as it is a major issue affecting their condition. PURPOSE: To verify the reliability and validity of baiobit sensor in measuring the neck proprioceptive function of CNNP patients. METHODS: Fifty-three CNNP patients were recruited (36 females, 17 males; age range 21-60 years) and were assessed for cervical joint position error by two blinded raters using the Baiobit sensor and laser pointer devices. The second measurement was conducted by the same rater 48 h later. Intra and inter-rater reliability of the Baiobit sensor was evaluated using the intra-class correlation coefficient (ICC), while the validity of the Baiobit sensor was established using the Spearman correlation coefficient. RESULTS: The Baiobit sensor demonstrated moderate to excellent intra-rater reliability in flexion, extension, left lateral flexion, right lateral flexion, and right rotation (ICCs=0.71∼0.85, 95 %CIs: 0.50∼0.91), left-rotation shows poor to good intra-rater reliability (ICC=0.56, 95 %CI: 0.25∼0.75). The Baiobit sensor also demonstrated moderate to excellent inter-rater reliability in flexion, extension, left lateral flexion, right lateral flexion, and right rotation (ICCs=0.80∼0.88, 95 %CIs: 0.65∼0.91), left-rotation shows poor to good intra-rater reliability (ICC=0.59, 95 %CI: 0.29∼0.76). Validity analysis showed that the Baiobit sensor had a range of low to high validity (r = 0.46∼0.88) for measuring cervical proprioception function, with lower validity observed in the left flexion direction. The Baiobit showed good absolute reliability with low SEM and MDC90 values (0.35°âˆ¼2.42°). CONCLUSION: The new device could be used as an alternative tool to evaluate neck proprioception.

Spatial mapping of greenhouse gases using a UAV monitoring platform over a megacity in China.

Urban environments are recognized as main anthropogenic contributors to greenhouse gas (GHG) emissions, characterized by unevenly distributed emission sources over the urban environments. However, spatial GHG distributions in urban regions are typically obtained through monitoring at only a limited number of locations, or through model studies, which can lead to incomplete insights into the heterogeneity in the spatial distribution of GHGs. To address such information gap and to evaluate the spatial representation of a planned GHG monitoring network, a custom-developed atmospheric sampler was deployed on a UAV platform in this study to map the CO2 and CH4 mixing ratios in the atmosphere over Zhengzhou in central China, a megacity of nearly 13 million people. The aerial survey was conducted along the main roads at an altitude of 150 m above ground, covering a total distance of 170 km from the city center to the suburbs. The spatial distributions of CO2 and CH4 mixing ratios in Zhengzhou exhibited distinct heterogeneities, with average mixing ratios of CO2 and CH4 at 439.2 ± 10.8 ppm and 2.12 ± 0.04 ppm, respectively. A spatial autocorrelation analysis was performed on the measured GHG mixing ratios across the city, revealing a spatial correlation range of approximately 2 km for both CO2 and CH4 in the urban area. Such a spatial autocorrelation distance suggests that the urban GHG monitoring network designed for emission inversion purposes need to have a spatial resolution of 4 km to characterize the spatial heterogeneities in the GHGs. This UAV-based measurement approach demonstrates its capability to monitor GHG mixing ratios across urban landscapes, providing valuable insights for GHG monitoring network design.

Cross-cultural adaptation and validation of the Mental Health Quality of Life (MHQoL) questionnaire in a Chinese-speaking population with chronic musculoskeletal pain.

BACKGROUND: The Mental Health Quality of Life (MHQoL) questionnaire is concise and suitable for rapid assessment of CMP (chronic musculoskeletal pain) patients in primary care. However, there is a lack of Chinese versions of the MHQoL. OBJECTIVE: To cross-culturally translate the MHQoL into Chinese and to assess its psychometric properties in Chinese-speaking patients with CMP. METHODS: The MHQoL was translated into Chinese according to the International Guidelines for the Cross-Cultural Adaptation of Self-Report Measures. 171 CMP patients were recruited to receive the Chinese versions of the MHQoL, SF-36, and HADS tests, and the MHQoL was retested seven days later. RESULT: The Chinese version of MHQoL had good retest reliability (MHQoL-7D: ICC = 0.971; MHQoL-VAS: ICC = 0.988) and internal consistency (Cronbach's alpha = 0.829). It showed a moderate correlation with the SF-36 total score (r=-0.509); the MHQoL-VAS moderately correlated with the Hospital Anxiety Depression Scale (r=-0.548). The MHQoL-7D showed no correlations with the SF-36's PF (r=-0.083) and BP (r=-0.170), weak correlations with RP (r=-0.284), RE (r=-0.298), and SF (r=-0.380), and moderate-to-strong correlations with GH (r=-0.638), VT (r=-0.480), and MH (r=-0.632). CONCLUSION: The Chinese version of the MHQoL can be used in clinical practice and research in Chinese-speaking CMP patients.

A newly developed Lagrangian chemical transport scheme: Part 1. Simulation of a boreal forest fire plume.

Forest fire research over the last several decades has improved the understanding of fire emissions and impacts. Nevertheless, the evolution of forest fire plumes remains poorly quantified and understood. Here, a Lagrangian chemical transport model, the Forward Atmospheric Stochastic Transport model coupled with the Master Chemical Mechanism (FAST-MCM), has been developed to simulate the transport and chemical transformations of plumes from a boreal forest fire over several hours since their emission. The model results for NOx (NO and NO2), O3, HONO, HNO3, pNO3 and 70 VOC species are compared with airborne in-situ measurements within plume centers and their surrounding portions during the transport. Comparisons between simulation results and measurements show that the FAST-MCM model can properly reproduce the physical and chemical evolution of forest fire plumes. The results indicate that the model can be an important tool used to aid the understanding of the downwind impacts of forest fire plumes.