Search

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation‐constrained estimate, which is several times larger than the bottom‐up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry‐transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top‐down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error. When comparing the black carbon model at a resolution of 2° × 2° with local measurements, the global representativeness error is 30% for AErosol RObotic NETwork sites, compared to 7% for Global Atmosphere Watch sites. It demonstrates that, in absence of high‐resolution models, the current top‐down estimate of black carbon direct radiative forcing is overestimated by 30%. The distribution of spatial representativeness error is right‐skewed for AERONET networkSpatial representativeness error is 30% when constraining a model at a resolution of 2° × 2° with AERONET retrievalsSpatial representativeness error is less for GAW or a subset of the AERONET sites outside of emission hot spots

Aerosol forcing uncertainty represents the largest climate forcing uncertainty overall. Its magnitude has remained virtually undiminished over the past 20 years despite considerable advances in understanding most of the key contributing elements. Recent work has produced modest increases only in the confidence of the uncertainty estimate itself. This review summarizes the contributions toward reducing the uncertainty in the aerosol forcing of climate made by satellite observations, measurements taken within the atmosphere, as well as modeling and data assimilation. We adopt a more measurement‐oriented perspective than most reviews of the subject in assessing the strengths and limitations of each; gaps and possible ways to fill them are considered. Currently planned programs supporting advanced, global‐scale satellite and surface‐based aerosol, cloud, and precursor gas observations, climate modeling, and intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved, are all essential. But in addition, new efforts are needed: (a) to obtain systematic aircraft in situ measurements capturing the multi‐variate probability distribution functions of particle optical, microphysical, and chemical properties (and associated uncertainty estimates), as well as co‐variability with meteorology, for the major aerosol airmass types; (b) to conceive, develop, and implement a suborbital (aircraft plus surface‐based) program aimed at systematically quantifying the cloud‐scale microphysics, cloud optical properties, and cloud‐related vertical velocities associated with aerosol‐cloud interactions; and (c) to focus much more research on integrating the unique contributions of satellite observations, suborbital measurements, and modeling, to reduce the persistent uncertainty in aerosol climate forcing. Aerosols, such as airborne wildfire smoke, desert dust, volcanic and pollution particles, affect Earth's climate by reflecting (some also absorb) sunlight. These aerosol particles also play key roles in cloud formation and evolution, further affecting the planet's energy balance. The magnitudes of these effects, and even the underlying mechanisms, represent the largest uncertainty in climate modeling. Despite two decades of advances in many aspects of aerosol‐climate science, aerosol climate forcing uncertainty is virtually undiminished. Yet, reducing this uncertainty is critical for any effort to attribute, mitigate, or predict climate changes. We adopt a measurement‐oriented perspective to assess the strengths and limitations of measurement and modeling programs, and conclude that current and planned efforts need to continue. However, in addition, new efforts are needed: (a) to obtain aircraft in situ measurements that capture systematically aerosol particle properties for the major aerosol airmass types, globally, (b) to conceive, develop, and implement an aircraft and surface‐based program aimed at filling gaps in our understanding of the interactions between aerosol particles and clouds, along with (c) much more research focused on integrating the unique contributions of satellite observations, suborbital measurements, and modeling, to reduce the uncertainty in our understanding of Earth's changing climate. Aerosol climate forcing uncertainty is virtually undiminished despite two decades of advances in many aspects of aerosol‐climate scienceThis review concludes that current and planned aerosol modeling, satellite and ground‐based observation programs remain essentialNew, systematic aircraft aerosol‐particle and cloud‐process measurements are also needed, along with better model‐measurement integration Aerosol climate forcing uncertainty is virtually undiminished despite two decades of advances in many aspects of aerosol‐climate science This review concludes that current and planned aerosol modeling, satellite and ground‐based observation programs remain essential New, systematic aircraft aerosol‐particle and cloud‐process measurements are also needed, along with better model‐measurement integration

The article offers guidelines for personal trainers on helping inactive clients make lifestyle changes, in relation to the partnership of Carol Kennedy-Armbruster and Martin Siegel. One solution for inactive clients is to focus on lifestyle activity. Activities that can burn calories include cleaning, dancing and gardening. Instead of explaining exercise guidelines, Siegel was given a pedometer and instructed to record daily steps. Kennedy-Armbruster looked for activities that could just easily be done standing up as sitting down.

Public funding agencies are increasingly requiring “broader impact” components in research grants. Concurrently, national educational leaders are calling for scientists to partner with educators to reform science education. Through the use of survey and interview data, our study examined the participation of researchers, faculty members, and graduate students from federal research laboratories and a Research I university, who were involved in K-12 and public outreach activities.We found that scientists were often recruited into K-12 outreach activities by local departmental liaisons, colleagues, or professors. Scientists most frequently gave presentations, tutored, and organized or judged science fairs. Outreach participation varied by career stage, job type, and gender. The strongest motivating factors were a desire to contribute and enjoying their outreach experiences. For graduate students and researchers, a third motivating factor was the chance to improve their teaching and communication skills. Scientists of all types, however, viewed outreach as a form of volunteer work that was auxiliary to their other responsibilities. Time constraints due to other, higher priorities, the lower value placed on outreach by departments, and a lack of detailed information about outreach opportunities were significant barriers to participation. Even so, only a few scientists viewed their outreach experiences negatively, mostly due to classroom management, logistical, or organizational problems, or a lack of outreach skills.

Sézary syndrome (SS) is characterized by erythroderma, peripheral lymphadenopathy, and circulating Sézary cells and is clinically heterogeneous. T-cell receptor (TCR) gene analysis was performed using DNA extracted from peripheral blood mononuclear cells from 74 patients, and the results were correlated with a variety of other diagnostic parameters and patient outcomes. Two groups were identified: 66 patients with clonal TCR gene rearrangement (clonal patients) detected with Southern blot analysis and/or polymerase chain reaction/single-strand conformational polymorphism analysis and 8 patients with no clonal rearrangement detected (nonclonal patients) using either technique. Clonal patients were compared with nonclonal patients. The following median blood parameters were significantly greater in the clonal group: total white cell count (13.7 10⁹/L vs. 9.6 10⁹/L), lymphocyte count (4.9 10⁹/L vs. 2.2 10⁹/L), absolute Sézary count (3.22 10⁹/L vs. 0.99 10⁹/L), CD4 count (3.17 10⁹/L vs. 1.36 10⁹/L), and CD4:CD8 ratio (15.86 vs. 3.21). An expanded population of T-cells of a specific TCR variable β subset was detected in 7 of 36 clonal patients and in 1 of 4 nonclonal patients. Cytogenetic analysis of peripheral blood from 1 nonclonal patient and 6 clonal patients was normal. The median survival from the time of diagnosis was 45 months in the clonal group, and 40 of 49 deaths were cutaneous T-cell lymphoma (CTCL)-related, whereas 3 deaths in the nonclonal group were unrelated to CTCL (P < 0.01; log-rank test). Multivariate proportional hazards analysis showed that the absolute Sézary count and lymph node status were independent prognostic variables (P = 0.016 and P = 0.036, respectively). TCR gene analysis defines a distinct clinicopathologic group of patients with SS. Clonal patients have a poor prognosis and are likely to die from leukemia/lymphoma, whereas nonclonal patients may have a reactive, inflammatory T-cell disorder. The authors suggest that the definitive diagnostic criteria for patients with SS should include the presence of a clonal TCR gene rearrangement. Cancer 2001;92:1745–52. © 2001 American Cancer Society.

Erythrodermic cutaneous T-cell lymphoma (CTCL) includes patients with erythrodermic mycosis fungoides who may or may not exhibit blood involvement and Sézary syndrome and in whom hematological involvement is, by definition, present at diagnosis. These patients were stratified into 5 hematologic stages (H0-H4) by measuring blood tumor burden, and these data were correlated with survival. The study identified 57 patients: 3 had no evidence of hematologic involvement (H0), 8 had a peripheral blood T-cell clone detected by polymerase chain reaction (PCR) analysis of the T-cell receptor gene and less than 5% Sézary cells on peripheral blood smear (H1), and 14 had either a T-cell clone detected by Southern blot analysis or PCR positivity with more than 5% circulating Sézary cells (H2). Twenty-four patients had absolute Sézary counts of more than 1 × 109 cells per liter (H3), and 8 patients had counts in excess of 10 × 109 cells per liter (H4). The disease-specific death rate was higher with increasing hematologic stage, after correcting for age at diagnosis. A univariate analysis of 30 patients with defined lymph node stage found hematologic stage (P = .045) and lymph node stage (P = .013) but not age (P = .136) to be poor prognostic indicators of survival. Multivariate analysis identified only lymph node stage to be prognostically important, although likelihood ratio tests indicated that hematologic stage provides additional information (P = .035). Increasing tumor burden in blood and lymph nodes of patients with erythrodermic CTCL was associated with a worse prognosis.The data imply that a hematologic staging system could complement existing tumor-node-metastasis staging criteria in erythrodermic CTCL.

Erythrodermic cutaneous T-cell lymphoma (CTCL) includes patients with erythrodermic mycosis fungoides who may or may not exhibit blood involvement and Sézary syndrome and in whom hematological involvement is, by definition, present at diagnosis. These patients were stratified into 5 hematologic stages (H0-H4) by measuring blood tumor burden, and these data were correlated with survival. The study identified 57 patients: 3 had no evidence of hematologic involvement (H0), 8 had a peripheral blood T-cell clone detected by polymerase chain reaction (PCR) analysis of the T-cell receptor gene and less than 5% Sézary cells on peripheral blood smear (H1), and 14 had either a T-cell clone detected by Southern blot analysis or PCR positivity with more than 5% circulating Sézary cells (H2). Twenty-four patients had absolute Sézary counts of more than 1 × 109cells per liter (H3), and 8 patients had counts in excess of 10 × 109cells per liter (H4). The disease-specific death rate was higher with increasing hematologic stage, after correcting for age at diagnosis. A univariate analysis of 30 patients with defined lymph node stage found hematologic stage (P= .045) and lymph node stage (P= .013) but not age (P= .136) to be poor prognostic indicators of survival. Multivariate analysis identified only lymph node stage to be prognostically important, although likelihood ratio tests indicated that hematologic stage provides additional information (P= .035). Increasing tumor burden in blood and lymph nodes of patients with erythrodermic CTCL was associated with a worse prognosis.The data imply that a hematologic staging system could complement existing tumor-node-metastasis staging criteria in erythrodermic CTCL.

Climate change and land use are altering the landscape of the U.S. Great Plains, producing increases in windblown dust. These increases are investigated by combining coarse mode aerosol observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor in addition to the Aerosol Robotic Network (AERONET) and Interagency Monitoring of Protected Visual Environments (IMPROVE) aerosol monitoring networks. Increasing trends of up to 5%/year in MODIS aerosol optical depth for dust observations are observed throughout the Great Plains (2000–2018). Cropland coverage has increased 5–10% over the majority of the Great Plains (2008–2018), and positive monthly trends in IMPROVE (1988–2018) and AERONET (1995–2018) coarse mode 90th percentile observations coincide with planting and harvesting seasons of predominant crops. Presently, results suggest increased dust due to agricultural expansion is negatively influencing human health and visibility in the Great Plains. Furthermore, results foreshadow a future where desertification becomes an increasing risk in the Great Plains. Throughout the U.S. Great Plains, satellite data combined with surface networks have shown a significant increase in airborne dust over the last two decades. This airborne dust is negatively influencing human health and visibility and coincides with increases in agricultural production. Dust loading throughout the U.S. Great Plains has increased over the last two decadesPositive correlations between cropland expansion and dust trends downwind suggest that agriculture contributed to these increasesIn the event of enhanced drought due to climate change, results support an increased risk of desertification from agricultural development

A cloud condensation nucleus (CCN) closure experiment is carried out using data from the Chebogue Point, Nova Scotia, ground site during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) field experiment in 2004. The number concentration of CCN at five supersaturations (∼0.07% to ∼0.5%) is predicted from measurements of aerosol size distribution, composition, and hygroscopic growth and is compared to measured CCN concentrations. It is shown that CCN can be predicted quite reliably using measured size distributions, a simple aerosol model to derive the solute‐to‐water mole ratio, and the diameter growth factor g(RH) or the optical growth factor f(RH). The mean error ranges from an overestimate in CCN of ≤5% at high supersaturation to a factor of 2.4 at low supersaturation with regression coefficients r2of 0.90 and 0.53, respectively. The poor agreement at low supersaturation is primarily a result of high flow rates in the CCN counter that prevented small particles from growing to detectable sizes. Precise knowledge of the temperature gradient, and flow rates of the instrument, is essential to establish the correct supersaturation, particularly at low supersaturation, where errors translate into a large percentage of the activated number. There may also be some contribution from simplified composition assumptions, e.g., neglecting variability with size and/or mixing state. The mostly oxygenated organic aerosol could be modeled as insoluble, within the above uncertainties, from the point of view of hygroscopicity and activation. The generality of these conclusions will have to be tested at other locations.

This study investigates the aerosol humidification effect (AHE) using 70 profiles of the aerosol scattering coefficients at high (∼80%) and low (∼40%) relative humidity (RH) levels and absorption coefficient at a low RH level obtained by a light aircraft (Cessna C‐172N) over the Southern Great Plains (SGP) site from April 2003 to June 2004. The column aerosol humidification factor, R(RH), defined as the ratio of the aerosol optical thickness (AOT) at the ambient RH to that at RH = 40% throughout the column rarely exceeded 1.3 (mean, 1.09 ± 0.12) over the SGP site. However, for an atmospheric column of a constant RH = 85%, R(RH) is greater than 1.5 for the majority of cases (mean, 1.57 ± 0.28). R(RH) was fitted to a function of column RH based on this unique aerosol data set. Several methods were proposed to estimate R(RH) for use when direct measurements of R(RH) are not available. It was found that the relationship between R(RH) and aerosol extinction coefficient weighted column‐mean RH works best. Performance of other methods depends on the measurements available. Sensitivity of R(RH) to a very humid (RH = 99%) layer with varying thickness values (0.1–0.3 km) is examined. The results indicate that the AHE on the AOT over the SGP site is not likely to exceed 50% on the average. The methods and results of this study may be utilized with caution to remove the AHE from the AOT retrieved from satellite or automated Sun photometer measurements, which will be useful for studies on aerosol indirect effect or quantifying cloud contamination in aerosol retrievals.