ALBERT

Description: We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (〈1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

Description: An intercomparison of radiance and irradiance ocean color radiometers (the second laboratory comparison exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: (1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; (2) indoor, laboratory intercomparison using stable radiance and irradiance sources in a controlled environment; (3) outdoor, field intercomparison of natural radiation sources over a natural water surface. The aim of the experiment was to provide a link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether di�erent instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the third phase of LCE-2: The results of the field experiment. The calibration of radiometers and laboratory comparison experiment are presented in a related paper of the same journal issue. Compared to the laboratory comparison, the field intercomparison has demonstrated substantially larger variability between freshly calibrated sensors, because the targets and environmental conditions during radiometric calibration were di�erent, both spectrally and spatially. Major di�erences were found for radiance sensors measuring a sunlit water target at viewing zenith angle of 139� because of the di�erent fields of view. Major di�erences were found for irradiance sensors because of imperfect cosine response of di�users. Variability between individual radiometers did depend significantly also on the type of the sensor and on the specific measurement target. Uniform SI traceable radiometric calibration ensuring fairly good consistency for indoor, laboratory measurements is insu�cient for outdoor, field measurements, mainly due to the di�erent angular variability of illumination. More stringent specifications and individual testing of radiometers for all relevant systematic e�ects (temperature, nonlinearity, spectral stray light, etc.) are needed to reduce biases between instruments and better quantify measurement uncertainties.

Description: An intercomparison of radiance and irradiance ocean color radiometers (The Second Laboratory Comparison Exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: 1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; 2) Indoor intercomparison using stable radiance and irradiance sources in controlled environment; and 3) Outdoor intercomparison of natural radiation sources over terrestrial water surface. The aim of the experiment was to provide one link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether di�erent instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the activities and results of the first two phases of LCE-2: the SI-traceable radiometric calibration and indoor intercomparison, the results of outdoor experiment are presented in a related paper of the same journal issue. The indoor experiment of the LCE-2 has proven that uniform calibration just before the use of radiometers is highly e�ective. Distinct radiometers from di�erent manufacturers operated by di�erent scientists can yield quite close radiance and irradiance results (standard deviation s 〈 1%) under defined conditions. This holds when measuring stable lamp-based targets under stationary laboratory conditions with all the radiometers uniformly calibrated against the same standards just prior to the experiment. In addition, some unification of measurement and data processing must be settled. Uncertaint of radiance and irradiance measurement under these conditions largely consists of the sensor’s calibration uncertainty and of the spread of results obtained by individual sensors measuring the same object.

Description: Because of its high phosphorus (P) demands, it is likely that the abundance, distribution, and N-fixing capacity of Alnus in boreal forests are tightly coupled with P availability and the mobilization and uptake of soil P via ectomycorrhizal fungi (EMF). We examined whether Alnus shifts EMF communities in coordination with increasingly more complex organic P forms across a 200-year-old successional sequence along the Tanana River in interior Alaska. Root-tip activities of acid phosphatase, phosphodiesterase, and phytase of A. tenuifolia-associated EMF were positively intercorrelated but did not change in a predictable manner across the shrub, to hardwood to coniferous forest successional sequence. Approximately half of all Alnus roots were colonized by Alnicola and Tomentella taxa, and ordination analysis indicated that the EMF community on Alnus is a relatively distinct, host-specific group. Despite differences in the activities of the two Alnus dominants to mobilize acid phosphatase and phosphodiesterase, the root-tip activities of P-mobilizing enzymes of the Alnus-EMF community were not dramatically different from other co-occurring boreal plant hosts. This suggests that if Alnus has a greater influence on P cycling than other plant functional types, additional factors influencing P mobilization and uptake at the root and/or whole-plant level must be involved.

Description: The Midwestern U.S. landscape is one of the most highly altered and intensively managed ecosystems in the country. The predominant crops grown are maize (Zea mays L.) and soybean [Glycine max (L.) Merr]. They are typically grown as monocrops in a simple yearly rotation or with multiple years of maize (2 to 3) followed by a single year of soybean. This system is highly productive because the crops and management systems have been well adapted to the regional growing conditions through substantial public and private investment. Furthermore, markets and supporting infrastructure are highly developed for both crops. As maize and soybean production have intensified, a number of concerns have arisen due to the unintended environmental impacts on the ecosystem. Many areas across the Midwest are experiencing negative impacts on water quality, soil degradation, and increased flood risk due to changes in regional hydrology. The water quality impacts extend even further downstream. We propose the development of an innovative system for growing maize and soybean with perennial groundcover to recover ecosystem services historically provided naturally by predominantly perennial native plant communities. Reincorporating perennial plants into annual cropping systems has the potential of restoring ecosystem services without negatively impacting grain crop production and offers the prospect of increasing grain crop productivity through improving the biological functioning of the system.

Description: This paper presents two control strategies: (i) An optimal exergy destruction (OXD) controller and (ii) a decentralized power apportionment (DPA) controller. The OXD controller is an analytical, closed-loop optimal feedforward controller developed utilizing exergy analysis to minimize exergy destruction in an AC inverter microgrid. The OXD controller requires a star or fully connected topology, whereas the DPA operates with no communication among the inverters. The DPA presents a viable alternative to conventional P − ω / Q − V droop control, and does not suffer from fluctuations in bus frequency or steady-state voltage while taking advantage of distributed storage assets necessary for the high penetration of renewable sources. The performances of OXD-, DPA-, and P − ω / Q − V droop-controlled microgrids are compared by simulation.

Description: Porous Asphalt (PA) pavements are an increasingly adopted tool in the green stormwater infrastructure toolbox to manage stormwater in urbanized watersheds across the United States. This technology has seen particular interest in western Washington State, where permeable pavements are recognized as an approved best management practice per the National Pollutant Discharge Elimination System (NPDES) municipal stormwater permit. Stormwater effluent concentrations from six PA cells were compared with runoff concentrations from three standard impervious asphalt cells to quantify pollutant removal efficiencies by porous asphalt systems. Additionally, the effects of maintenance and pavement age on pollutant removal efficiencies were examined. Twelve natural and artificial storms were examined over a five-year period. Street dirt and pollutant spikes were added to the pavements prior to some storm events to simulate high loading conditions. Results from this work show that porous asphalt pavements are highly efficient at removing particulate pollutants, specifically coarse sediments (98.7%), total Pb ( 98.4%), total Zn (97.8%), and total suspended solids (93.4%). Dissolved metals and Polycyclic Aromatic Hydrocarbons (PAH) were not significantly removed. Removal efficiencies for total Pb, total Zn, motor oil, and diesel H. improved with the age of the system. Annual maintenance of the pavements with a regenerative air street sweeper did not yield significant pollutant removal efficiency differences between maintained and unmaintained PA cells.

Description: Clouds are critical in mechanisms that impact climate sensitivity studies, air quality and solar energy forecasts, and a host of aerodrome flight and safety operations. However, cloud forecast accuracies are seldom described in performance statistics provided with most numerical weather prediction (NWP) and climate models. A possible explanation for this apparent omission involves the difficulty in developing cloud ground truth databases for the verification of large-scale numerical simulations. Therefore, the process of developing highly accurate cloud cover fraction truth data from manually generated cloud/no-cloud analyses of multispectral satellite imagery is the focus of this article. The procedures exploit the phenomenology to maximize cloud signatures in a variety of remotely sensed satellite spectral bands in order to create accurate binary cloud/no-cloud analyses. These manual analyses become cloud cover fraction truth after being mapped to the grids of the target datasets. The process is demonstrated by examining all clouds in a NAM dataset along with a 24 h WRF cloud forecast field generated from them. Quantitative comparisons with the cloud truth data for the case study show that clouds in the NAM data are under-specified while the WRF model greatly over-predicts them. It is concluded that highly accurate cloud cover truth data are valuable for assessing cloud model input and output datasets and their creation requires the collection of satellite imagery in a minimum set of spectral bands. It is advocated that these remote sensing requirements be considered for inclusion into the designs of future environmental satellite systems.

Description: Agriculture accounts for 5% of the entire energy used worldwide. Most of it is not in a renewable form, so it can be linked to greenhouse gas emissions. According to the Paris Agreement, on climate change, one of its major targets is the reduction of greenhouse gas emissions. Therefore, the agricultural production process must drastically change. Currently, the sustainable use of water is critical for any agricultural development. Agricultural production effects water quality and sufficiency, as well as, freshwater wetlands. Energy balance, carbon, and water footprint are crucial for sustainable agricultural production. Agroforestry systems are important in reducing high inputs of non-renewable energy and greenhouse gas emissions, along with better water use, leading to the most minimal influence on climate change. Energy analysis, carbon, and water footprint can be applied to agroforestry systems’ production. An outline could be applied by adopting a modified—for agricultural production—life cycle assessment methodology to assess energy use, greenhouse gas emissions, and water consumption in agroforestry ecosystems.

Description: The objective was to determine if cooking skills and meal planning behaviors are associated with greater fruit and vegetable intake and lower body mass index (BMI) in first-year college students who are at risk for excessive weight gain. A cross-sectional analysis was conducted using baseline data from a multi-state research project aimed at preventing weight gain in first-year college students. Cooking type, frequency and confidence, self-instruction for healthful mealtime behavior intention, self-regulation of healthful mealtime behavior, and cup equivalents of fruits and vegetables (FV) were measured using validated surveys. BMI was calculated from measured height and weight. First-year students (n = 1108) considered at risk for weight gain from eight universities completed baseline assessments within the first month of entering college. Multiple linear regression was used to determine associations among independent variables of cooking patterns, meal planning behaviors, and dependent variables of fruit and vegetable intake and BMI, after controlling for the influence of sex. Cooking more frequently, cooking with greater skills, and practicing meal planning behaviors are associated with greater fruit and vegetable intake and lower BMI in first-year college students. Interventions aimed at improving health in college students may be enhanced by incorporating cooking and meal planning components.