ABSTRACT
Background: Cancer-related cognitive impairment (CRCI) can include persistent memory symptoms, and affects many cancer survivors. Memory and Attention Adaptation Training (MAAT) is an evidencebased cognitive behavioral therapy (CBT) that improves CRCI with demonstrated efficacy in telehealth delivery. MAAT consists of 8 weekly (45-minute) video visits. The aims of this study are to confirm MAAT telehealth efficacy in a phase III RCT (MAAT versus Supportive Therapy;ST) across large catchment areas of two comprehensive cancer centers. A secondary aim is to evaluate treatment-induced brain activation as assessed by functional MRI (fMRI) in a subset of participants. We present remote treatment and data capture methods of this open NCI-sponsored (R01CA244673) randomized clinical trial (NCT 04586530). These methods have high success in participant accrual despite COVID-19 pandemic conditions, and can be readily adopted to other clinical trials to enhance rural/underserved enrollment. Methods: We are enrolling 200 adult, stage I-III breast cancer survivors 1-5 years post-chemotherapy with cognitive complaints. Individuals with CNS disease, previous brain injury, dementia or psychiatric disorder are excluded. All study procedures are completed from the participant's home (except fMRI). Eligibility screening is a semi-structured phone interview followed by detailed informed consent online (Research Electronic Data Capture: REDCap) with staff phone guidance. Consented participants complete baseline brief phone-based neurocognitive assessment and validated patient-reported outcome measures (PROs) of cognition and quality of life via REDCap. Participants are randomized to MAAT or ST and assigned treating clinicians at respective cancer centers. All 8 visits are completed through secure telehealth platforms, followed by repeat phone/online assessment posttreatment and again at 6 months. Enrollment began in 3/2021. As of 1/2022 (9 months), 56 participants are enrolled (28% of the planned sample), 47 randomized (MAAT 24;ST 23), with 24 completing post-treatment assessments. If all assessments and treatment visits were in person, travel burden per participant is 968 miles/20.5 hours driven, and $542 (US 2021 Federal rate). Thus, study travel savings to date are $30,352. Participant feedback indicates telehealth makes participation possible, similar to previous MAAT research. The current RCT demonstrates utility, efficiency and cost-savings of telehealth and remote data capture technology in the conduct of cancer control research. Elements of methods described can also be adopted for cancer therapeutic trials. Comprehensive cancer centers, where most clinical trials are based, can enhance participation of remote and/or underserved populations that have higher rates of cancer, more disease burden and less opportunity for trial participation.
ABSTRACT
In situ measurements have suggested vehicle emissions may dominate agricultural sources of NH3 in many cities, which is alarming given the potential for urban NH3 to significantly increase human exposure to ambient particulate matter. However, confirmation of the prevalence of vehicle NH3 throughout a city has been challenging because of mixing with agricultural sources, and the latter are thus routinely assumed to dominate. Here we report vehicle NH3 emissions based on TROPOMI NO2 and CrIS NH3 (0.152 kg s(-1)) that are consistent with a model-based estimate (0.178 kg s(-1)) and show that COVID-19 lockdowns provide a unique opportunity for making the first satellite-based constraints on vehicle NH3 emissions for an entire urban region (western Los Angeles), which we find make up 60-95% of total NH3 emissions, substantially higher than the values of 13-22% in state and national inventories. This provides a new means of constraining a component of transportation emissions whose impacts may rival those of NOx yet which has been largely under-recognized and uncontrolled.
ABSTRACT
Nitrogen oxides (NOx) are air pollutants critical to ozone and fine particle production in the troposphere. Here, we present fuel‐based emission inventories updated to 2018, including for mobile source engines using the Fuel‐based Inventory of Vehicle Emissions (FIVEs) and oil and gas production using the Fuel‐based Oil and Gas (FOG) inventory. The updated FIVE emissions are now consistent with the NEI17 estimates differing within 2% across the contiguous US (CONUS). Tropospheric NO2 columns modeled by the Weather Research and Forecasting with Chemistry model (WRF‐Chem) are compared with those observed by TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) during the summer of 2018. Modeled NO2 columns show strong temporal and spatial correlations with TROPOMI (OMI), identified with biases of −3% (−21%) over CONUS, and +8% (−6%) over point sources plus urban regions. Taking account of the negative bias (∼20%) in early version of TROPOMI over polluted regions, WRF‐Chem shows good performance with updated FIVE and FOG emissions. Our model tends to under‐predict the tropospheric NO2 columns over background and rural regions (bias of −21% to −3%). Through model sensitivity analyses, we demonstrate the important roles of emissions from soils (11.7% average over CONUS), oil and gas production (4.1%), wildfires (10.6%), and lightning (2.3%) with greater contributions at regional scales. This work provides a roadmap for satellite‐based evaluations for emission updates from various sources.Alternate :Plain Language SummarySatellite observations of tropospheric NO2 columns provide important constraints on air pollutants from space, which have been widely used to validate the performance of atmospheric models. To gain better knowledge of the accuracy of the recently updated fuel‐based emissions inventory, we conducted NO2 assessments between a regional chemical transport model (Weather Research and Forecasting with Chemistry model, WRF‐Chem), with the TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) over the contiguous United States. We find that model simulation results show strong spatial and temporal correlations with satellite observations across point sources, urban, oil and gas production, and rural regions. With updated emissions, our regional atmospheric model can reconcile with satellite retrievals differing from −3% (TROPOMI) to −21% (OMI) overall. Soils, oil and gas production, wildfires and lightning emissions can play key roles in regional air quality. This work provides an important baseline of a pre‐COVID year by which sharp changes in anthropogenic NOx emissions due to the pandemic can be assessed.
ABSTRACT
Abstract Most countries around the world including the United States took actions to control COVID-19 spread that led to an abrupt shift in human activity. On-road NOx emissions from light and heavy-duty vehicles decreased by 9% to 19% between February and March at the onset of the lockdown period in the middle of March in most of the US;between March and April, the on-road NOx emissions dropped further by 8% to 31% when lockdown measures were the most stringent. These precipitous drops in NOx emissions correlated well (r = 0.75) with tropospheric NO2 column amount observed by the Sentinel 5 Precursor TROPOspheric Monitoring Instrument (S5P TROPOMI). Furthermore, the changes in TROPOMI tropospheric NO2 across the continental US between 2020 and 2019 correlated well with changes in on-road NOx emissions (r = 0.68) but correlated weakly with changes in emissions from the power plants (r = 0.35). At the height of lock-down related unemployment in the second quarter of 2020, the tropospheric NO2 values decreased at the rate of 0.8 µmoles/m2 per unit percentage increase in the unemployment rate. Despite the lifting of lockdown measures, parts of the US continued to have ?20% below normal on-road NOx emissions. To achieve this new normal urban air quality in the US, continuing remote work policies that do not impede economic growth may become one of the many options.
ABSTRACT
The coronavirus-19 (COVID-19) pandemic led to government interventions to limit the spread of the disease which are unprecedented in recent history;for example, stay at home orders led to sudden decreases in atmospheric emissions from the transportation sector. In this review article, the current understanding of the influence of emission reductions on atmospheric pollutant concentrations and air quality is summarized for nitrogen dioxide (NO2), particulate matter (PM2.5), ozone (O3), ammonia, sulfur dioxide, black carbon, volatile organic compounds, and carbon monoxide (CO). In the first 7 months following the onset of the pandemic, more than 200 papers were accepted by peer-reviewed journals utilizing observations from ground-based and satellite instruments. Only about one-third of this literature incorporates a specific method for meteorological correction or normalization for comparing data from the lockdown period with prior reference observations despite the importance of doing so on the interpretation of results. We use the government stringency index (SI) as an indicator for the severity of lockdown measures and show how key air pollutants change as the SI increases.The observed decrease of NO2 with increasing SI is in general agreement with emission inventories that account for the lockdown. Other compounds such as O3, PM2.5, and CO are also broadly covered. Due to the importance of atmospheric chemistry on O3 and PM2.5 concentrations, their responses may not be linear with respect to primary pollutants. At most sites, we found O3 increased, whereas PM2.5 decreased slightly, with increasing SI. Changes of other compounds are found to be understudied. We highlight future research needs for utilizing the emerging data sets as a preview of a future state of the atmosphere in a world with targeted permanent reductions of emissions. Finally, we emphasize the need to account for the effects of meteorology, emission trends, and atmospheric chemistry when determining the lockdown effects on pollutant concentrations. Copyright: © 2021 The Author(s).