Remote continental aerosol characteristics in the Rocky Mountains of Colorado and Wyoming

2013 Spring.Includes bibliographical references.The Rocky Mountains of Colorado and Wyoming enjoy some of the cleanest air in the United States, with few local sources of particulate matter or its precursors apart from fire emissions, windblown dust, and biogenic emissions. However, anthropogenic influences are also present with sources as diverse as the populated Front Range, large isolated power plants, agricultural emissions, and more recently emissions from increased oil and gas exploration and production. While long-term data exist on the bulk composition of background fine particulate matter at remote sites in the region, few long-term observations exist of aerosol size distributions, number concentrations and size resolved composition, although these characteristics are closely tied to important water resource issues through the potential aerosol impacts on clouds and precipitation. Recent modeling work suggests sensitivity of precipitation-producing systems to the availability of aerosols capable of serving as cloud condensation nuclei (CCN); however, model inputs for these aerosols are not well constrained due to the scarcity of data. In this work I present aerosol number and volume concentrations, size distributions, chemical composition and hygroscopicity measurements from long-term field campaigns. I also explore the volatility of organic material from biomass burning and the potential impacts on aerosol loading. Relevant aerosol observations were obtained in several long-term field studies: the Rocky Mountain Atmospheric Nitrogen and Sulfur study (RoMANS, Colorado), the Grand Tetons Reactive Nitrogen Deposition Study (GrandTReNDS, Wyoming) and as part of the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen project (BEACHON, Colorado). Average number concentrations (0.04 < Dp < 20 &#956;m) measured during the field studies ranged between 1000 - 2000 cm-3 during the summer months and decreased to 200 - 500 cm-3 during the winter. These seasonal changes in aerosol number concentrations were correlated with the frequency of events typical of new particle formation. Measured sub-micron organic mass fractions were between 70 - 90% during the summer months, when new particle formation events were most frequent, suggesting the importance of organic species in the nucleation or growth process, or both. Aerosol composition derived from hygroscopicity measurements indicate organic mass fractions of 50 - 60% for particles with diameters larger than 0.15 &#956;m during the winter. The composition of smaller diameter particles appeared to be organic dominated year-round. High organic mass fractions led to low values of aerosol hygroscopicity, described using the &#954; parameter. Over the entire year-long BEACHON study, &#954; had an average value of 0.16 ± 0.08, similar to values determined during biologically active periods in tropical and boreal forests, and lower than the commonly assumed value of &#954;continental = 0.3. There was also an observed increase in &#954; with size, due to external mixing of the fine mode aerosol. Incorrect representations of &#954; or its size dependence led to erroneous values of calculated CCN concentrations, especially for supersaturation values less than 0.3%. At higher supersaturations, most of the measured variability in CCN concentrations was captured by changes in total measured aerosol number concentrations. While data from the three measurement sites were generally well correlated, indicating similarities in seasonal cycles and in total number concentrations, there were some variations between measurements made at different sites and during different years that may be partly due to the effects of local emissions. The averaged data provide reasonable, observationally-based parameters for modeling of aerosol number size distributions and corresponding CCN concentrations. Field observations clearly indicated the episodic influence of wildfire smoke on particle number concentrations and compositions. However, the semi-volatile nature of the organic carbon species emitted makes it difficult to predict how much of the emitted organic mass will remain in the condensed phase downwind. To better constrain the volatility of organic species in smoke, emissions from laboratory biomass combustion experiments were subjected to quantified dilution, resulting in reduction of aerosol mass concentrations over several orders of magnitude and a corresponding volatilization response of the organic particles that was fit to the commonly-applied Volatility Basis Set. Organic emissions from all burns with initial organic aerosol concentrations greater than 1000 &#956;g m-3 contained material with saturation concentration values ranging between 1 and 10,000 &#956;g m-3, with most of the organic mass falling at the two extremes of this range. For most burns, a single distribution was able to capture the volatility behavior of the organic material, within experimental uncertainty, despite the considerable variability in fuel and fire characteristics, suggesting that a simplified two-product model of gas-aerosol partitioning may be adequate to describe the evolution of biomass burning organic aerosol in models

Strengthening VITA to Boost Financial Security at Tax Time and Beyond

At the beginning of every year, the vast majority of American households turn their attention to the ritual of filing their federal and state income tax returns. Some see it as a civic duty, others as a burdensome chore. But for tens of millions of low- and moderate-income families and individuals, tax time represents a springboard to economic opportunity and financial security.Key PointsEvery year, the VITA program helps millions of low- and moderate-income Americans file their taxes for free.The VITA program is driven by thousands of community organizations nationwide, which leverage a modest federal grant matched with significant local investment.VITA tax preparation has the highest accuracy rate of any tax preparation service, and VITA has increased the number of returns filed every year since the program was authorized.There is an overwhelming demand for VITA services, but VITA sites need more flexibility to innovate and respond to local community needs.Congress, the Administration and states should expand VITA and make key reforms to spur local innovation

Filtering With the Crowd: CrowdScreen Revisited

Filtering a set of items, based on a set of properties that can be verified by humans, is a common application of CrowdSourcing. When the workers are error-prone, each item is presented to multiple users, to limit the probability of misclassification. Since the Crowd is a relatively expensive resource, minimizing the number of questions per item may naturally result in big savings. Several algorithms to address this minimization problem have been presented in the CrowdScreen framework by Parameswaran et al. However, those algorithms do not scale well and therefore cannot be used in scenarios where high accuracy is required in spite of high user error rates. The goal of this paper is thus to devise algorithms that can cope with such situations. To achieve this, we provide new theoretical insights to the problem, then use them to develop a new efficient algorithm. We also propose novel optimizations for the algorithms of CrowdScreen that improve their scalability. We complement our theoretical study by an experimental evaluation of the algorithms on a large set of synthetic parameters as well as real-life crowdsourcing scenarios, demonstrating the advantages of our solution

The network structure of ICD-11 adjustment disorder: A comparison of clinical and nonclinical samples

Background: International Classification of Diseases, 11th revision (ICD-11) adjustment disorder (AjD) is characterized by two main symptom clusters: preoccupation with the stressor and failure to adapt to the stressor. The network analytic approach provides important information on the structural validity of a disorder and reveals which symptoms are most prominent. To date, no study compared the network structure of AjD symptoms in clinical and nonclinical samples, which could potentially inform our understanding of psychopathological mechanisms that underlie AjD and identify core targets for therapy. Methods: A network analysis was conducted on AjD symptoms as assessed by the Adjustment Disorder—New Module (ADNM-8) using data from 330 clinical participants from the UK and a nonclinical sample of 699 participants from Switzerland. Results: Comparisons of network structure invariance revealed differences between the network structure of the clinical and the nonclinical samples. Results highlight that in terms of both edges strength and centrality, failure to adapt symptoms was more prominent in the clinical sample, while the preoccupation symptoms were more prominent in the nonclinical sample. Importantly, global strength was similar across networks. Conclusions: Results provide evidence of the coherence of AjD in the ICD-11 as assessed by the ADNM questionnaire. They tentatively suggest that subclinical AjD may be characterized by emerging preoccupation symptoms that may result in failure to adapt and functional impairment in clinical manifestation of AjD. However, there is a need for replication and longitudinal research to further validate this hypothesis

Relationship between adjustment disorder symptoms and probable diagnosis before and after second lockdown in Israel: longitudinal symptom network analysis

BACKGROUND There is cumulative evidence of the importance of exploring the change of dynamics between symptoms over time as reflective of consolidation of psychopathology. AIMS To explore the interactions between symptoms of ICD-11 adjustment disorder before and after the second lockdown of the COVID-19 pandemic in Israel and identify the most central symptoms and their concurrent and prospective associations with probable adjustment disorder. METHOD This is a population-based study drawn from a probability-based internet panel. A representative sample of the adult Israeli population was assessed at two time points (T1, pre-second lockdown, n = 1029, response rate 76.17%; T2, post-second lockdown, n = 764, response rate 74.24%). Symptoms of adjustment disorder were assessed by the International Adjustment Disorder Questionnaire (IADQ). RESULTS Although the overall strength of associations at the two measurement points was similar and two same communities were found, there was a significant change in their structure, with a more consolidated network at T2. The most central item was 'difficult to relax' in both networks. Cross-sectionally, all symptoms of failure to adapt significantly predicted adjustment disorder. 'Worry a lot more' (preoccupation) and 'difficult to adapt to life' (failure to adapt) at T1 significantly predicted this diagnosis at T2. CONCLUSIONS Adjustment disorder symptoms consolidated during the second lockdown of the pandemic. In line with the ICD-11 conceptualisation of adjustment disorder, both preoccupation and failure-to-adapt symptoms have prognostic validity. This highlights the importance of identifying and targeting adjustment disorder symptoms during a period of stress such as the COVID-19 pandemic

The network structure of ICD-11 adjustment disorder: A comparison of clinical and non-clinical samples

Background: ICD-11 adjustment disorder (AjD) is characterized by two main symptom clusters; preoccupation with the stressor and failure to adapt to the stressor. The network analytic approach provides important information on the structural validity of a disorder and reveals which symptoms are most prominent. To date, no study compared the network structure of AjD symptoms in clinical and non-clinical samples, which could potentially inform our understanding of psychopathological mechanisms that underlie AjD and identify core targets for therapy. Methods: A network analysis was conducted on AjD symptoms as assessed by the adjustment disorder –New Module (ADNM-8) using data from 330 clinical participants from the UK and a non-clinical sample of 699 participants from Switzerland. Results: Comparisons of network structure invariance revealed differences between the network structure of the clinical and the non-clinical samples. Results highlight that in terms of both edges strength and centrality, failure to adapt symptoms were more prominent in the clinical sample, while the preoccupation symptoms were more prominent in the non-clinical sample. Importantly, global strength was similar across networks. Discussion: Results provide evidence of the coherence of AjD in the ICD-11 as assessed by the ADNM questionnaire. They tentatively suggest that subclinical AjD may be characterized by emerging preoccupation symptoms that may result in failure to adapt and functional impairment in clinical manifestation of AjD. However, there is a need for replication and longitudinal research to further validate this hypothesis

The network structure of ICD-11 Adjustment Disorder: A cross-cultural comparison of three African countries

Background: Adjustment disorder (AjD) is one of the most widespread mental disorders worldwide. In ICD-11, AjD is characterized by two main symptom clusters; preoccupation with the stressor and failure to adapt. The network analytic approach has been applied to most ICD-11 stress related disorders. However, no study to date explored the relations between symptoms of AjD using network analysis. Aims: We aimed to explore AjD symptoms network and whether its structure replicates across questionnaire versions and samples. Methods: A network analysis was conducted on AjD symptoms as assessed by the Adjustment Disorder–New Module (ADNM-8) and an ultra-brief version (ADNM-4) using data from 2,524 participants in Nigeria (n = 1006), Kenya (n = 1018), and Ghana (n = 500).Results: There were extensive connections between items across all samples in both ADNM versions. Results highlight that preoccupation symptoms seem to be more prominent in terms of edges strengths and had the highest centrality in all networks across samples and ADNM versions. Comparisons of network structure invariance revealed one difference between Nigeria and Ghana in both ADNM versions. Importantly, the ADNM-8 global strength was similar in all networks whereas in the ADNM-4 Kenya had a higher global strength score compared to Nigeria Conclusions: Results provide evidence of the coherence of AjD in the ICD-11 as assessed by the ADNM questionnaire. The prominence of preoccupation symptoms in AjD highlight a possible therapeutic target to alleviate distress. There is a need to further replicate the network structure of AjD in non-African samples