Urban wind field analysis from the Jack Rabbit II Special Sonic Anemometer Study

Near-surface wind variability over spatiotemporal scales relevant to plume tracking insects

Odor plume tracking is important for many organisms, and flying insects have served as popular model systems for studying this behavior both in field and laboratory settings. The shape and statistics of the airborne odor plumes that insects follow are largely governed by the wind that advects them. Prior atmospheric studies have investigated aspects of microscale wind patterns with an emphasis on characterizing pollution dispersion, enhancing weather prediction models, and for assessing wind energy potential. Here, we aim to characterize microscale wind dynamics through the lens of short-term ecological functions by focusing on spatial and temporal scales most relevant to insects actively searching for odor sources. We collected and compared near-surface wind data across three distinct environments (sage steppe, forest, and urban) in Northern Nevada. Our findings show that near-surface wind direction variability decreases with increasing wind speeds and increases in environments with greater surface complexity. Across environments, there is a strong correlation between the variability in the wind speed (i.e., turbulence intensity) and wind direction (i.e., standard deviation in wind direction). In some environments, the standard deviation in the wind direction varied as much as 15°-75° on time scales of 1-10 min. We draw insight between our findings and previous plume tracking experiments to provide a general intuition for future field research and guidance for wind tunnel design. Our analysis suggests a hypothesis that there may be an ideal range of wind speeds and environment complexity in which insects will be most successful when tracking odor plumes over long distances.

Near-surface wind profile test based on accuracy verification of UAV anemometer lifting height in an urban fringe built-up area

Multirotor UAVs (unmanned aerial vehicles) have been widely used in urban vertical wind environment testing, whereas less attention has been given to the accuracy of wind speed captured by anemometers as drones fly. This paper aims to identify the ideal location of the anemometer on the UAV to obtain more accurate wind speeds and to assess the variation characteristics of wind speed in different spatial types in urban fringe areas. Accuracy verification of the lifting height of the anemometer in the UAV and wind profile test was carried out at three locations (a tennis court, a residential area, and a green park) on the iHarbour campus of Xi'an Jiaotong University. The following results were obtained: (1) the background wind speed was captured more accurately (R = 0.727, P = 0.001) when the lifting height of the anemometer was 0.00 m (as the height of the anemometer was the same as the rotors) and when the multirotor UAV was hovering in the air. However, this optimal lifting height lost 29.6% of the accuracy for capturing the background wind speed. Interestingly, when the lifting height was 0.75 m, the anemometer captured by the anemometer on the drone showed a significant negative correlation (R =  - 0.682, P = 0.005) with the background wind speed. (2) The wind speed at an altitude of 1.5 m in the residential area was significantly lower than that noted at other heights, and the wind speed at 24 m was significantly lower than that at 100 m. (3) In addition, a sudden increase in wind speeds was always observed near the surface of 12 m inside the campus, which may be due to the interaction of hot surface air in this newly built-up area with the cool rural winds around it. The study presents methods and quantitative references for the application of multirotor UAVs in urban vertical wind environment testing and the evaluation of ventilation performance at different heights inside high-rise houses in urban fringe areas.

Case of study on a sustainability building: Environmental risk assessment related with allergenicity from air quality considering meteorological and urban green infrastructure data on BIM

Digitisation is gaining importance with 3D workflow for architecture-specific annotation of built heritage. The objective is to use the Building Information Modeling (BIM) methodology in order to carry out a study of alternatives of impact on environmental sustainability associated with the potential allergenicity with green infrastructure on a new housing, located in Mérida (SW Spain). It is intended to simulate the meteorology (direction and speed of the wind) in the study city with the compass rose for 18 years (2003-2020) to assess the meteorological pattern associated with the wind on the studied housing. 3 green infrastructure garden alternatives (considering 5 ornamental species of cypress trees) were designed to evaluate the potential impact of allergenicity on the housing. AIROT index was applied to project the results on the frontage of the housing. This index was developed in the field of large areas of urban environments. The calculation was carried out in the most exact way possible in specific sections of the frontage of the housing and automatically with tools associated with the BIM environment (such as Autodesk Revit, Dynamo, Enscape, Wrplot and Bim One) to the discipline of Architecture (such as Autodesk Autocad and Autodesk Flow Design). The obtained results were applied to evaluate 3 scenario designs, trying to minimize the potential exposure to urban green infrastructure (focus on cypress trees) in this current project, and offering a health reference guide in future projects, from the design phase considering appropriate measures and proposing recommendations.

Simulations of dispersion through an irregular urban building array

Following the release of a harmful substance within an urban environment, buildings and street canyons create complex flow regimes that affect dispersion and localized effluent concentrations. While some fast-response dispersion models can capture the effects caused by individual buildings, further research is required to refine urban characterizations such as plume channeling and spreading, and initial dispersion, especially within the presence of a nonhomogeneous array of structures. Field, laboratory, and modeling experiments that simulate urban or industrial releases are critical in advancing current dispersion models. This project leverages the configuration of buildings used in a full-scale, mock urban field study to examine the concentrations of a neutrally buoyant tracer in a series of wind tunnel and Embedded Large Eddy Simulation (ELES) experiments. The behavior, propagation, and magnitude of the plumes were examined and compared to identify microscale effects. After demonstrating excellent quantitative and qualitative comparisons between the wind tunnel and ELES via lateral and vertical concentration profiles, we show that a nonlinear least squares fit of the Gaussian plume equation well represents these profiles, even within the array of buildings and network of street canyons. The initial plume dispersion depended strongly on the structures immediately adjacent to the release, and consequently, the near-surface plume spread very rapidly in the first few street canyons downwind of the source. The ELES modeling showed that under slightly oblique incoming wind directions of 5° and 15°, an additional 5° and 14° off-axis channeling of the plume occurred at ground level, respectively. This indicates how building structures can cause considerable plume drift from the otherwise expected centerline axis, especially with greater wind obliquity. Additionally, AERMOD was used to represent the class of fast-running, Gaussian dispersion models to inform where these types of models may be usefully applied within urban areas or groups of buildings. Using an urban wind speed profile and other parameters that may be locally available after a release, AERMOD was shown to qualitatively represent the ground-level plume while somewhat underestimating peak concentrations. It also overestimated the lateral plume spread and was challenged in the very near-field to the source. Adding a turbulence profile from the ELES data into AERMOD's meteorological input improved model estimates of lateral plume spread and centerline concentrations, although peak concentration values were still underestimated in the far field. Finally, we offer some observations and suggestions for Gaussian dispersion modeling based on this mock urban modeling exercise.