Relative Wind Direction Research Articles

Consideration of the cloud motion for aircraft-based stereographically derived cloud geometry and cloud top heights

Abstract. Cloud geometry and in particular cloud top heights can be derived from 2-D camera measurements by applying a stereographic method to data from an overflight over a scene of clouds (see, e.g., Kölling et al., 2019). Although airplane overpasses are relatively fast, cloud motion with the wind is important and can result in errors in the cloud localization. Here, the impact of the wind is investigated using the method from Kölling et al. (2019) for measurements of the airborne hyperspectral imaging system spectrometer of the Munich Aerosol Cloud Scanner (specMACS). Further, a method for cloud motion correction using model winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) is presented. It is shown that the update is important as the original algorithm without the cloud motion correction can over- or underestimate the cloud top heights by several hundred meters, depending on the wind speed and the relative wind direction. This is validated using data from the Elucidating the role of clouds–circulation coupling in climate (EUREC4A) campaign and realistic 3-D radiative transfer simulations. From the comparison of the derived cloud top heights with the expected ones from the model input, an average accuracy of the cloud top heights of less than (20±140) m (mean deviation and 1 standard deviation) is estimated for the updated method.

Performance of the Earth Explorer 11 SeaSTAR Mission Candidate for Simultaneous Retrieval of Total Surface Current and Wind Vectors

Interactions between ocean surface currents, winds and waves at the atmosphere-ocean interface are key controls of lateral and vertical exchanges of water, heat, carbon, gases and nutrients in the global Earth System. The SeaSTAR satellite mission concept proposes to better quantify and understand these important dynamic processes by measuring two-dimensional fields of total surface current and wind vectors with unparalleled spatial and temporal resolution (1 × 1 km2 or finer, 1 day) and unmatched precision over one continuous wide swath (100 km or more). This paper presents a comprehensive numerical analysis of the expected performance of the Earth Explorer 11 (EE11) SeaSTAR mission candidate in the case of idealised and realistic 2D ocean currents and wind fields. A Bayesian framework derived from satellite scatterometry is adapted and applied to SeaSTAR’s bespoke inversion scheme that simultaneously retrieves total surface current vectors (TSCV) and ocean surface vector winds (OSVW). The results confirm the excellent performance of the EE11 SeaSTAR concept, with Root Mean Square Errors (RMSE) for TSCV and OSVW at 1 × 1 km2 resolution consistently better than 0.1 m/s and 0.4 m/s, respectively. The analyses highlight some performance degradation in some relative wind directions, particularly marked at near range and low wind speeds. Retrieval uncertainties are also reported for several variations around the SeaSTAR baseline three-azimuth configuration, indicating that RMSEs improve only marginally (by ∼0.01 m/s for TSCV) when including broadside Radial Surface Velocity or broadside dual-polarisation data in the inversion. In contrast, our results underscore a) the critical need to include broadside Normalised Radar Cross Section data in the inversion; b) the rapid performance degradation when broadside incidence angles become steeper than 20° from nadir; and c) the benefits of maintaining ground squint angle separation between fore and aft lines-of-sight close to 90°. The numerical results are consistent with experimental performance estimates from airborne data and confirm that the EE11 SeaSTAR concept satisfies the requirements of the mission objectives.

A bioinspired triboelectric wireless anemometer with low cut-in wind speed for meteorological UAVs

Currently, unmanned aerial vehicles (UAVs) play a pivotal role in meteorological wind speed measurements. Nevertheless, existing anemometers exhibit notable issues, including excessive weight, high cost and high cut-in wind speed. This investigation introduces a biomimetic owl wing airfoil wind speed sensor utilizing the principles of the triboelectric nanogenerator (BOW-TENG) designed for UAV applications. Inspired by owl wings, an airfoil configuration with superior aerodynamic characteristics is ascertained, subsequently fabricating it into an impeller, and a wind speed sensor with low weight, low cost and low cut-in wind speed is developed. Experimental results affirm the BOW-TENG’s precision in depicting wind speed across the range of 1.6–10.7 m/s, featuring a sensitivity of 21.893 Hz/(m·s−1), a goodness of fit R2 of 0.9995, and a remarkable resolution of 0.057 m/s. The sensor weighs only 30 g. Furthermore, a cost-effective triboelectric signal processing system is devised for integrating the BOW-TENG into the UAV, as well as the optimal positioning for BOW-TENG on the UAV is identified through simulations. The relative wind direction can be calculated from signals of the BOW-TENGs on the four arms of the UAV. Ultimately, application experiments demonstrate the feasibility of employing BOW-TENG for wireless wind speed transmission from UAVs. This work incorporates bionics and proposes a practical application of triboelectric sensors for UAVs, as well as a solution for developing wind speed sensors in the field of meteorological UAV detection.

Computational Fluid Dynamics Investigation of the Spacing of the Aerodynamic Characteristics for Multiple Wingsails on Ships

Wind energy, as an inexhaustible energy source, has become a focal point in the development of new energy for ships. Sail-assisted technology, which leverages wind power, has been successfully applied to ship propulsion. The propulsion performance of sail-assisted ships is affected by the interference characteristics among multiple wingsails. To investigate interference characteristics, an arrangement scheme involving two-element wingsails and considering the relative wind direction angle was established. To obtain the inter-stage interference characteristics of wingsails, the Reynolds average N-S equation was used in the numerical simulation conducted under steady operating conditions. The results indicate that, at the relative wind angles of 30°, 90°, and 120°, the minimum horizontal spacing in a single row arrangement scheme is 1.5c. However, at relative wind angles of 90° and 120°, inter-stage interference may induce stall conditions in the wingsails. In a double-row arrangement scheme, the wake of the upstream wingsail interferes with the flow of the downstream sail at relative wind angles of 90°. An optimal propulsion performance is achieved with a horizontal spacing of 4c and a longitudinal spacing of 10c. Moreover, the interference performance of the two-element wingsails can be enhanced through a horizontal offset arrangement. This study provides a reference for the arrangement of wingsails on ships.

Development of X-Band Geophysical Model Function for Sea Surface Wind Speed Retrieval with ASNARO-2

In the present study, a new geophysical model function (GMF) is developed for the X-band synthetic aperture radar (SAR) on board the Advanced Satellite with New System Architecture for Observation-2 (ASNARO-2) to retrieve accurate offshore wind speeds. Equivalent neutral wind speeds based on the local forecast model (LFM) are employed as reference wind vectors, and 12,259 matching points from 502 SAR images obtained with horizontal transmitting, horizontal receiving polarization around Japan are collected. To ensure convergence of the calculation, 8129 points are selected from the matching points to determine the basic formula for the GMF and 23 coefficients based on the relationships among the normalized radar cross section, wind speed, incidence angle, and relative wind direction. Compared with the reference wind speeds, the GMF wind speeds showed reproducibility with a bias of −0.10 m/s and an RMSD of 1.37 m/s. Additionally, it can be confirmed that the retrieved wind speed has the bias of 0.03 and the RMSD of 1.68 m/s when compared to the in situ wind speed from the Kuroshio Extension Observatory (KEO) buoy. The accuracy of these retrieved wind speeds is comparable to previous studies, and it is indicated that the developed GMF can be used to retrieve offshore winds from ASNARO-2 images.

Polarized Bidirectional Reflectance Distribution Function Matrix Derived from Two-Scale Roughness Theory and Its Applications in Active Remote Sensing

A polarized bidirectional reflectance distribution function (pBRDF) matrix was developed based on the two-scale roughness theory to provide consistent simulations of fully polarized microwave emission and scattering, required for the ocean–atmosphere-coupled radiative transfer model. In this study, the potential of the two-scale pBRDF matrix was explored for simulating ocean full-polarization backscattering and bistatic-scattering normalized radar cross sections (NRCSs). Comprehensive numerical simulations of the two-scale pBRDF matrix across the L-, C-, X-, and Ku-bands were carried out, and the simulations were compared with experimental data, classical electromagnetic, and GMFs. The results show that the two-scale pBRDF matrix demonstrates reasonable dependencies on ocean surface wind speeds, relative wind direction (RWD), geometries, and frequencies and has a reliable accuracy in general. In addition, the two-scale pBRDF matrix simulations were compared with the observations from the advanced scatterometer (ASCAT) onboard MetOP-C satellites, with a correlation coefficient of 0.9634 and a root mean square error (RMSE) of 2.5083 dB. In the bistatic case, the two-scale pBRDF matrix simulations were compared with Cyclone Global Navigation Satellite System (CYGNSS) observations, demonstrating a good correlation coefficient of 0.8480 and an RMSE of 1.2859 dB. In both cases, the two-scale pBRDF matrix produced fairly good simulations at medium-to-high wind speeds. The relatively large differences at low wind speeds (<5 m/s) were due probably to the swell effects. This study proves that the two-scale pBRDF matrix is suitable for the applications of multiple types of active instruments and can consistently simulate the ocean surface passive and active signals.

Characteristics, sources, and health risks of PM2.5-bound trace metals in northern Zhejiang Province: The effects of meteorological variables based on machine learning

Atmospheric metals have recently attracted the attention of governments recently due to their significant health risks. In retrospect, a five-year (2017–2021) continuous measurement of airborne metals (13 elements) was conducted in northern Zhejiang Province. A declining trend of total metals (22%) was found from 2017 to 2021, with K, Fe, Zn, Ca, and Mn being its predominant compositions (95.3%). The Random Forest model simulation demonstrated the important roles of meteorological conditions in the trace metal reduction, such as Ca, As, K, Cr, and Zn. In addition, the emission controls contributed more than 50% to most of the remaining metals, especially for Cu (92.6%) and V (85.9%), which demonstrated the effectiveness of the government policies. The relative humidity, wind speed and wind direction were found to be the most important variables affecting the ambient concentration of trace metals. Meteorology was demonstrated to be the worst for trace metal diffusion in 2018. The primary noncarcinogenic metal was Mn (85.9%), while the major carcinogenic metal was Cd (63.4%). Six sources were resolved by positive matrix factorization (PMF). Anthropogenic source emission was largest in winter, followed by spring, summer, and autumn. The reduction of ferrous metal smelting and coal combustion emissions might be the major goal for reducing the public health risk of trace metals in the future.

A Fuzzy-Based System for Autonomous Unmanned Aerial Vehicle Ship Deck Landing.

This paper introduces a fuzzy logic-based autonomous ship deck landing system for fixed-wing unmanned aerial vehicles (UAVs). The ship is assumed to maintain a constant course and speed. The aim of this fuzzy logic landing model is to simplify the task of landing UAVs on moving ships in challenging maritime conditions, relieving operators from this demanding task. The designed UAV ship deck landing model is based on a fuzzy logic system (FLS), which comprises three interconnected subsystems (speed, lateral motion, and altitude components). Each subsystem consists of three inputs and one output incorporating various fuzzy rules to account for external factors during ship deck landings. Specifically, the FLS receives five inputs: the range from the deck, the relative wind direction and speed, the airspeed, and the UAV's flight altitude. The FLS outputs provide data on the speed of the UAV relative to the ship's velocity, the bank angle (BA), and the angle of descent (AOD) of the UAV. The performance of the designed intelligent ship deck landing system was evaluated using the standard configuration of MATLAB Fuzzy Toolbox.

Continuous observations from horizontally pointing lidar, weather parameters and PM2.5: a pre-deployment assessment for monitoring radioactive dust in Fukushima, Japan

Abstract. A horizontally pointing lidar is planned for deployment with other instruments in Fukushima, Japan, to continuously monitor and characterize the optical properties of radioactive aerosols and dust in an uninhabited area. Prior to installation, the performance of the lidar is tested at Chiba University. Data from the continuous operation of the lidar from August 2021 to February 2022 are analyzed for extinction and volume linear depolarization ratio. These are compared with the weather sensor and particulate matter (PM2.5) measurements to quantify the relationships between atmospheric conditions and optical properties of near-ground aerosols. The results show that the lidar data's extinction coefficient and depolarization ratio can have a quantifiable relationship with relative humidity (RH), absolute humidity, rain rate, wind speed, wind direction and PM2.5 concentration. Analysis of the 7-month data shows that the optical properties of aerosol and dust depend on the combined effects of the weather parameters. An increase in RH or PM2.5 concentration does not imply an increase in radioactive aerosols. The average extinction coefficient and depolarization ratio of aerosols and dust, originating from the land and ocean, show different values and opposing trends, which can aid in determining the occurrence of ground-based radioactive dust and aerosols. The information obtained from analyzing the inter-relationship among lidar, weather parameters and PM2.5 concentration is essential in assessing the occurrence of radioactive aerosols and characterizing local aerosol–weather relationships in a radioactive area. This result provides essential information in describing radioactive aerosols in Fukushima.

PSXIV-16 Evaluation of Water Intake Equations with an Emphasis on Physiological Status and Evaluation of Current Relevance Behind Environmental Parameters

Abstract Water requirements for beef cattle are often computed according to body weight (BW) and environmental variables. Inherent variation in environmental conditions within geographical locations, in addition to a cascade of physiological changes triggered as consequence of such variability are somewhat fomented by multicollinearity amongst these variables. This conundrum generates instability of current predictive models in reaching optimization equilibrium inflating its overall predictability and robustness. The goals herein involved the identification of physiologically relevant parameters and the generation of robust, data-driven, individualistic models through high frequency data loggers. Further, we evaluate re-parametrized and current proposed equations (e.g.: Hicks et al., 1988 and Arias and Mader, 2011) for the prediction of water intake for beef cattle at different life stages and physiological conditions. The dataset utilized consisted of more than 30,000 observations, including longitudinal data on lactating animals (n = 23), grass finished steers (n = 12), grain finished steers (n = 21), and grain finished implanted steers (n = 9), steers backgrounded on a low (n = 20) or moderate (n = 20) plane of nutrition bulls under negative (n = 13), maintenance (n = 13) and positive energy balance (n = 13). Individual monitoring systems allowed for the daily collection of BW, water and feed intake, and ingestive behavior. Additionally, an on-site data-logging weather station (1-min intervals) collected relative humidity, temperature, wind speed, wind direction, solar radiation, and precipitation. All reported statistics were generated on out-of-bag randomly split portions of the dataset. For identification of relevant predictive parameters of water intake, several feature selection and penalization techniques were examined. When comparing our equations to current, the errors generated for water intake predictions using physiological classification and on-site environmental variables, explained 50% more of the variation in predicting water intake (r2 = 0.38 vs r2 = 0.22-0.27). When evaluating the errors of prediction (root mean squared error, RMSE and mean absolute error, MAE), significant decreases of up to three-fold were observed on the equations generated herein (RMSE = 9.05 vs 28.8 to 35.31, MAE = 7.04 vs 26.9 to 33.9). Accurate monitoring of individual parameters such as feed intake were better predictors of water intake than environmental parameters when evaluating re-parametrization of models. Further, inclusion of a physiological stage (categorical variable) was more significant than any of the other environmental predictors. Overall, the results discussed highlight the importance of appropriately accounting for the water requirements of beef cattle and how far-off current assumptions are. Further, it raises concern on current equations that use environmental monitoring equations and techniques that attempt to describe nutrient requirements of the animals, and potentially brings the approach to requirements rather than environment.

Assessment of Fungal Aerosols Dispersion from Municipal Solid Waste Disposal Site: A Case Study of Karaj, Iran

Introduction: Fungal aerosols from landfill sites can play a fundamental role in environmental pollution and health. The present study aimed to assess the dispersion of fungal aerosols from municipal solid waste disposal site.
 Materials and Methods: In this cross-sectional study, the concentration of fungal aerosols was determined in four geographical directions at distances of 250, 500, 750, and 1000 m around landfill site. Relative humidity and temperature were also measured. Moreover the concentration and type of the fungal taxa isolated from landfill site under different environmental and metrological conditions were evaluated.
 Results: The results showed that the maximum and minimum concentrations of fungal aerosol in the landfill site were 256.18 ± 59.7 CFU/m3 and 76.56 ± 23.2 CFU/m3, respectively. The most frequent fungi detected from municipal landfill site included Penicillium (43.67%), Cladosporium (33.54%), Yeast (7.60%), Aspergillus (5.91%), Curvularia (3.62%), Chrysosporium (1.57%), Alternaria (1.54%), Scopulariopsis (0.84%), and Ulocladium (0.60%) taxa. The maximum identified fungal aerosol concentration in the area around the solid waste landfill was 350 CFU/m3. Furthermore, the concentration of fungal aerosols in the environment was significantly related to relative humidity, wind direction, and temperature in spring and winter (P < 0.05).
 Conclusion: Municipal solid waste disposal site can be a potential source for fungal aerosol dispersion. Moreover, fungal aerosols concentration is correlated with wind direction and speed, relative humidity, and temperature

Identification of varying modal parameters of a tall building from the full-scale wind-induced responses

The dynamic behaviour of a tall building can change notably during the construction phases, under the varying degree of occupation, loading patterns, wind conditions, and aeroelastic phenomena. In this study, acceleration measurements taken over a period of one year and the corresponding wind conditions for a 150 m tall building in London, UK, are analysed to identify the reasons for variations in the structural modal parameters. Several environmental parameters are investigated, including the magnitude and the relative directions of the wind with respect to the building motion. The identified dominant effects are the response amplitude and the observation time. A finite element model of the tower is employed to support the experimental observations. The amplitude-dependent behaviour is studied for the natural frequencies and damping ratios of the first three vibration modes. The changes in the identified natural frequencies, with the monitoring time and response amplitudes, are attributed to the mass increase under the increasing occupancy and large-amplitude structural softening, respectively. In particular, it is shown that the natural frequencies experience an asymptotic drop of up to 5% with increasing time. The identified trends between the measured total damping and wind speed for different relative wind directions indicate that the amplitude of the lateral building motion, rather than aerodynamic wind characteristics, primarily influence the observed variation in the modal damping. Based only on the operational observations, an updated empirical model is proposed and compared against previous results from the literature. The established empirical model indicates the increase of the damping ratio values from around 0.6 % for the near-zero amplitude conditions to up to 2.1 % for the high amplitude conditions.

Dome seeing analysis of the Anglo-Australian Telescope

Dome seeing is an often overlooked avenue for seeing improvement for a telescope. Because most existing telescope domes have not been characterized for turbulence, there is an opportunity to improve the overall seeing by minimizing the dome contribution, thereby optimizing scientific productivity and operations. A dome turbulence sensor has recorded data in the Anglo-Australian Telescope (AAT) over the past year. The instrument consists of a collimated laser beam that propagates (and double passes) between the AAT’s primary mirror box and a flat mirror on the secondary strut. The angle-of-arrival fluctuations are used to derive a dome-seeing-proxy in arcsec. We found the dominant effects to be the temperature gradients and wind speed. Convection conditions are considerably more detrimental to the dome-seeing-proxy than thermal inversion conditions. Unlike other large telescopes, there is no discernible relationship between the dome-seeing-proxy and relative wind direction. Concerning telescope operations, it would be worth considering lowering the air-conditioning set point temperature to include a higher proportion of observations under thermal inversion. Nevertheless, this must be carefully weighed with the risk of condensation in the dome, a major concern for a site with frequent high relative humidity.

The relationship between PM10 and meteorological variables in the mega city Istanbul

PM10, one of the air pollutants, occurs regularly in İstanbul during the winter months, namely in December, January, and February. PM10 pollutant is affected by numerous factors. Among these factors are various meteorological variables and climatological factors. This article aims to determine the relationship between PM10 and meteorological variables (wind speed, wind direction, temperature, and relative humidity) and to interpret these results. PM10 and meteorological data were examined between 2011 and 2018. To determine the relationship, multiple linear regression, Pearson's correlation coefficient (PCC), Spearman's rank correlation, Kendall Tau correlation, autocorrelation function (ACF), cross-correlation function (CCF), and visuals were determined using the R program (open-air) packages. In the study, the relationship between wind, temperature, and relative humidity with PM10 was determined, and it was observed that the PM10 concentration was maximum between January and February. PM10 concentrations have a positive relationship with relative humidity and wind direction, while a negative relationship with wind speed and temperature was observed. The correlation values for relative humidity and temperature were found to be 0.01 and - 0.15, respectively. Furthermore, the relationship between wind speed and PM10 was calculated from multiple linear regression model, and the estimated value was - 0.12 while looking at the wind direction value, it was approximately 0.03.

Probing Climate Change in Greece with a 2m dish radio telescope

We study the effect of solar activity on the climate in Greece. We search for correlations between solar and terrestrial indicators. The solar proxies which are representative of the activity of our star include the number of sunspots, the intensity of solar radiation, the radio flux at 10.7cm and the galactic cosmic rays. Earth’s weather indicators include six parameters, temperature, relative air humidity, wind direction and intensity, atmospheric pressure and precipitation. The solar data span several years starting from 1975 to 2005, including decades-long variations. The meteorological data come from 12 stations located in various parts of Greece. The main part of the research is the unique experiment in Greece which aims to continuously monitor and record the solar radio flux at 10.7 cm using a 2m paraboloid radio telescope (the pilot project of the THERMOpYlae Hellenic radio telescope).

Aerodynamic Performance Analysis of VTOL Arm Configurations of a VTOL Plane UAV Using a Computational Fluid Dynamics Simulation

A vertical take-off and landing plane (VTOL plane) is a fixed-wing unmanned aerial vehicle (FWUAV) configuration with the ability to take off and land vertically. It combines the benefits of fixed-wing and multirotor configurations, which gives it a high cruising range and independence from a runway. This configuration requires arms as mountings for the VTOL’s motors. This study discusses the design of a VTOL Plane with various VTOL arm configurations, and a computational fluid dynamics (CFD) simulation was conducted to find out which configuration performs the best aerodynamically. The VTOL arm configurations analyzed were a quad-plane, a twin-tail boom, a tandem wing, and a transverse arm. The interpreted performances were the lift and drag performances, stall conditions, flight efficiency, stability, and maneuverability. The relative wind directions toward the longitudinal axis of the UAV, which are the sideslip angle and the angle of attack, were varied to simulate various flying conditions. The results showed that the twin tail-boom is the most advantageous based on the interpreted performances.

Impact of COVID-19 lockdown and meteorology on the air quality of Srinagar city: A temperate climatic region in Kashmir Himalayas

The deadly transmission of the coronavirus forced all countries to implement lockdowns to restrict the transmission of this highly infectious disease. As a result of these lockdowns and restrictions, many urban centers have seen a positive impact on air quality with a significant reduction in air pollution. Therefore, in this study, the impact of COVID-19 lockdown vis-a-vis meteorological parameters on the ambient air quality of Srinagar city was examined. In this regard, we have evaluated the temporal variation of six different key air pollutants (PM10, PM2.5, SO2, NO2, O3, and NH3) along with meteorological parameters (relative humidity, rainfall, temperature, wind speed, and wind direction). The duration of the study was divided into three periods: Before Lockdown(BLD), Lockdown (LD), and Partial Lockdown(PLD). Daily average data for all the parameters was accessed from one of the real-time continuous monitoring stations of the central pollution control board (CPCB) at Rajbagh Srinagar. Some air pollutants have decreased, according to the results, while others have increased. The air quality index (AQI) decreases overall by 6.15 percent compared to before lockdown, and it never exceeds the "moderate" category. The AQI was in the following order for both lockdown and pre-lockdown periods: satisfactory > moderate > good. However, for partial lockdown, it was moderate > satisfactory > good. It was observed that the maximum decrease was seen in the concentration of NO2, NH3 with 75.11% and 69.18%. A modest decrease was observed in PM10 at 3.8%. While SO2 and O3 had an upward trend of 85.82% and 48.74%, The NO2 to SO2 ratio reveals that the emissions of NO2 have substantially decreased due to the complete restriction of transport systems. From principal component analysis for all three study periods, PM10 and PM2.5 were combined into a single component, inferring their shared behavior and source of origin. SO2 and O3 demonstrated identical behavior during the lockdown and partial lockdown periods of study. According to the findings of the study, it is beneficial for the government, environmentalists, and policymakers to impose rigorous lockdown measures, particularly during extreme air pollution events, in order to reduce the damage caused by automotive and industrial emissions.

Air pollution relevance analysis in the bay of Algeciras (Spain)

The aim of this work is to accomplish an in-depth analysis of the air pollution in the two main cities of the Bay of Algeciras (Spain). A large database of air pollutant concentrations and weather measurements were collected using a monitoring network installed throughout the region from the period of 2010–2015. The concentration parameters contain nitrogen dioxide (NO2), sulphur dioxide (SO2) and particulate matter (PM10). The analysis was developed in two monitoring stations (Algeciras and La Línea). The higher average concentration values were obtained in Algeciras for NO2 (28.850 µg/m3) and SO2 (11.966 µg/m3), and in La Línea for PM10 (30.745 µg/m3). The analysis shows patterns that coincide with human activity. One of the goals of this work is to develop a useful virtual sensor capable of achieving a more robust monitoring network, which can be used, for instance, in the case of missing data. By means of trends analysis, groups of equivalent stations were determined, implying that the values of one station could be substituted for those in the equivalent station in case of failure (e.g., SO2 weekly trends in Algeciras and Los Barrios show equivalence). On the other hand, a calculation of relative risks was developed showing that relative humidity, wind speed and wind direction produce an increase in the risk of higher pollutant concentrations. Besides, obtained results showed that wind speed and wind direction are the most important variables in the distribution of particles. The results obtained may allow administrations or citizens to support decisions.

Microclimatic field measurements to support microclimatological modelling with ENVI-met for an urban study area in Cologne

Abstract. Cities are particularly affected by climate change impacts. Due to global warming, the frequency and intensity of summer heat events increases for many cities around the globe. Urban climatological studies have shown significant positive trends in the number of hot days and tropical nights. Heat stress is an important health as well as economic risk. Thus, urban planning needs to adapt to climate change. This requires a sound scientific analysis of different adaptation measures and management options, which must be based on appropriate data, models and scenarios to assess their suitability and efficacy. The goal of this paper is to assess the suitability of a low cost weather station network consisting of 33 NETATMO weather sensors and ultrasonic anemometers to measure air temperature, relative air humidity, wind speed and wind direction of a 16 ha study area in Cologne with high temporal and spatial resolution to support microclimatological modelling. The temperature and humidity sensors were calibrated against a research grade reference sensor under laboratory conditions. In addition, a research grade meteorological station (Campbell Sci.) was set up in the study area as a reference. The NETATMO sensors were placed to identify local microclimatic effects due to different surface types, vegetation and building structures. Using descriptive statistical analyses and pairwise comparisons, significant differences in the microclimatic conditions of the various sites were found, which can clearly be attributed to specific small scale microclimate factors. Significant differences were particularly identified comparing an avenue and a narrow street as well as a backyard and an urban park area. The sensors proved to provide data reliably and with suitable quality to measure microclimatic effects. The choice of sensors lends itself well for citizen participation, needed to facilitate climate change adaptation. In our further research, the data will be used as reference data for microclimatological modelling with ENVI-met investigating particularly options of mitigating climate change effects.

Evaluation of data preprocessing and feature selection process for prediction of hourly PM10 concentration using long short-term memory models

Studies have confirmed that PM10, defined as respirable particles with diameters of 10 μm and smaller, has adverse effects on human health and the environment. Various estimation methods are employed to determine the PM10 concentration using historical data on controlling PM10 air pollution, early warning, and protecting public health and the environment. The present study analyses different Long Short-Term Memory (LSTM) models that can predict hourly PM10 concentration. In parallel, the study also investigates the effectiveness of the data preprocessing and feature selection (DPFS) process on the prediction accuracy of the LSTM models. For this purpose, three different LSTM models, namely Vanilla, Bi-Directional, and Stacked, were developed. Then, a comprehensive data preprocessing stage is used to eliminate missing and erroneous data and outliers from real-world raw data, and a feature selection process is applied to extract unnecessary features. The LSTM models consider three air quality parameters, including SO2, O3, and CO, and three meteorological factors, including relative humidity, wind direction, and wind speed. The prediction performances of the LSTM models are compared using the RMSE, MAE and R2 performance index according to whether DPFS is used in the models or not. As a result, when the DPFS process was applied, the proposed LSTM models achieved high prediction performance and can be used to predict hourly PM10 concentrations. Overall, the DPFS process significantly enhanced the developed LSTM models’ prediction performance. Furthermore, the proposed model might be a useful tool for city administrators to make decisions and improve air quality management efforts.