Integrating demographic and meteorological data in urban ecology: a case study of container-breeding mosquitoes in temperate Argentina

Area ◽  
2014 ◽  
Vol 46 (1) ◽  
pp. 18-26 ◽  
Author(s):  
María Victoria Cardo ◽  
Darío Vezzani ◽  
Alejandra Rubio ◽  
Aníbal E Carbajo
Keyword(s):  
Urban Ecology ◽  
Meteorological Data

scholarly journals Rain Erosion Maps for Wind Turbines Based on Geographical Locations: A Case Study in Ireland and Britain

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
K. Pugh ◽  
M. M. Stack
Keyword(s):  
Wind Turbine ◽  
Western Europe ◽  
Meteorological Data ◽  
Turbine Blades ◽  
Weather Conditions ◽  
Annual Rainfall ◽  
Wind Turbine Blades ◽  
Weather Patterns ◽  
The Uk

AbstractErosion rates of wind turbine blades are not constant, and they depend on many external factors including meteorological differences relating to global weather patterns. In order to track the degradation of the turbine blades, it is important to analyse the distribution and change in weather conditions across the country. This case study addresses rainfall in Western Europe using the UK and Ireland data to create a relationship between the erosion rate of wind turbine blades and rainfall for both countries. In order to match the appropriate erosion data to the meteorological data, 2 months of the annual rainfall were chosen, and the differences were analysed. The month of highest rain, January and month of least rain, May were selected for the study. The two variables were then combined with other data including hailstorm events and locations of wind turbine farms to create a general overview of erosion with relation to wind turbine blades.

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

scholarly journals A Study on Indoor Particulate Matter Variation in Time Based on Count and Sizes and in Relation to Meteorological Conditions

2021 ◽  
Vol 13 (15) ◽  
pp. 8263
Author(s):  
Marius Bodor
Keyword(s):  
Particulate Matter ◽  
Meteorological Data ◽  
Monitoring Network ◽  
Pollution Monitoring ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Indoor Location ◽  
Particle Matter ◽  
Indoor Particulate Matter

An important aspect of air pollution analysis consists of the varied presence of particulate matter in analyzed air samples. In this respect, the present work aims to present a case study regarding the evolution in time of quantified particulate matter of different sizes. This study is based on data acquisitioned in an indoor location, already used in a former particulate matter-related article; thus, it can be considered as a continuation of that study, with the general aim to demonstrate the necessity to expand the existing network for pollution monitoring. Besides particle matter quantification, a correlation of the obtained results is also presented against meteorological data acquisitioned by the National Air Quality Monitoring Network. The transformation of quantified PM data in mass per volume and a comparison with other results are also addressed.

A Hybrid Method for Estimating Natural Lighting Potential in Buildings

Solar Energy ◽  
2004 ◽  
Author(s):  
Kelly Kissock
Keyword(s):  
Energy Use ◽  
Meteorological Data ◽  
Total Solar Radiation ◽  
Industrial Facilities ◽  
Natural Lighting ◽  
Tilted Surface ◽  
Engineering Society ◽  
Lighting Energy ◽  
Local Cloud

This paper describes data and algorithms to estimate typical average interior illuminance from daylighting using a hybrid of Hay, Davies, Klucher, Reindl (HDKR) method for calculating total solar radiation on a tilted surface and the Illuminating Engineering Society (IES) Lumen Method for estimating interior illuminance from daylighting. This hybrid algorithm, in conjunction with typical meteorological data, directly accounts for shading and typical local cloud cover effects on an hour-by-hour basis, which is difficult to do using the IES sky-cover or sky-ratio methods. Several experiments show reasonable agreement between measured and calculated results. Case study examples demonstrate of use of the method, when incorporated into software, to quickly analyze daylighting potential in industrial facilities, and the use of this information to develop specific recommendations for cost-effectively reducing lighting energy use in industrial facilities by improving the utilization of natural lighting.

scholarly journals A reliability engineering case study of sugarcane harvesters

2020 ◽  
Vol 27 (4) ◽  
Author(s):  
Diego Carvalho do Nascimento ◽  
Pedro Luiz Ramos ◽  
André Ennes ◽  
Camila Cocolo ◽  
Márcio José Nicola ◽  
...  
Keyword(s):  
Tracking System ◽  
Meteorological Data ◽  
Reliability Engineering ◽  
Embedded Computer ◽  
Equipment Failures ◽  
Process Failures ◽  
A Company ◽  
Different Sources ◽  
Two Machines

Abstract: The present study aimed to analyze factors associated with the equipment failures of the sugarcane harvester, whose machineries has high importance in the harvest process and cost involved. Part of the data was originally provided by a company located in the countryside of Sao Paulo State, from two machines, collected from January 2015 to August 2017, corresponding to 2.5 crops. The overall dataset was obtained from three different sources: a stop-tracking system, which provides the track of a preventive and corrective maintenance historical of the analyzed equipment; telemetry data of the equipment, captured through embedded computer systems, installed in the machine’ type under study, which provide information on its operation; and meteorological data from the Brazilian National Institute of Meteorology. Multivariate analyzes were used such as principal components and multiple regression models, therefore creating a model for prediction considering the next equipment’ break, then pointing to causes of process failures. Thus, the results point to some improvements concerned with individualized reliability scheme in order to reduce the number of corrective stops given the equipment.

Performance Analysis With Future Predictions of Different Solar Cooling Systems in Guayaquil, Ecuador

2014 ◽  
Author(s):  
Carlos Naranjo-Mendoza ◽  
Jesús López-Villada ◽  
Gabriel Gaona ◽  
Jerko Labus
Keyword(s):  
Flow Rate ◽  
Cooling System ◽  
Meteorological Data ◽  
Cooling Systems ◽  
Great Opportunity ◽  
Constant Flow Rate ◽  
Solar Cooling ◽  
Average Annual Temperature ◽  
System Configurations

This paper presents a comparative analysis of three different solar cooling system configurations developed for a case study building in Guayaquil, Ecuador. Guayaquil is a city located at the Ecuadorian coast with an average annual temperature of 25°C. The city’s need for air conditioning throughout the year and the relatively intense solar radiation provide a great opportunity for implementation of solar cooling systems. The first cooling system includes a 175 kWc single-effect absorption chiller powered by evacuated tubes solar thermal collectors. This system was compared with two 140 kWc compression chiller systems (air-cooled (AC) and water-cooled (WC)) powered by grid-connected photovoltaics. Both constant flow rate (CFR) and variable flow rate (VFR) of chilled water were analyzed. The three systems have to satisfy a cooling demand of the top floor in one governmental building (app. 1296 m2) which was selected as case study. Additionally, two 140 kWc conventional compression chiller systems (AC and WC) were included in the comparison as reference systems. Cooling demand of the building was simulated in EnergyPlus and coupled with the appropriate system configurations developed in TRNSYS. The weather file (TMY) was developed based on real meteorological data collected in the last decade. The present analysis was extended with the prediction scenarios for the years 2020, 2050 and 2080 using climate change adapted weather files.

scholarly journals A comparative analysis of air pollutant concentrations and inflow trajectories: a case study of selected cities in South-Eastern Poland

2018 ◽  
Vol 45 ◽  
pp. 00060 ◽  
Author(s):  
Robert Oleniacz ◽  
Tomasz Gorzelnik ◽  
Adriana Szulecka
Keyword(s):  
Meteorological Data ◽  
Road Transport ◽  
Air Pollutant ◽  
Hysplit Model ◽  
Urban Background ◽  
South Eastern ◽  
Pollutant Concentrations ◽  
High Concentrations ◽  
Air Pollutant Concentrations

The paper presents a comparison of air pollutant concentrations in three cities in South-Eastern Poland (Krakow, Tarnow and Rzeszow) using statistical analyses and backward trajectory modelling (the HYSPLIT model). The analyses were based on particulate matter (PM10), nitrogen dioxide (NO2) and sulphur dioxide (SO2) levels as well as meteorological data from year 2017. The performed analyses revealed, among others, that the PM10 and SO2 concentrations in the air depend on the season of the year, while the NO2 concentrations are seasonally independent, which is mainly associated with emissions from road transport. Air quality in the analysed cities depends on local meteorological conditions and the structure of emission sources, including the inflowing background. The most unfavourable situation regarding high concentrations of PM10 and NO2 occurs in Krakow. For all analysed urban background stations very similar low SO2 air concentrations are observed which proves the decreasing significance of emissions from coal combustion sources.

scholarly journals Time-Dependent Integration of Solar Thermal Technology in Industrial Processes

2020 ◽  
Vol 12 (6) ◽  
pp. 2322 ◽  
Author(s):  
Calvin Kong Leng Sing ◽  
Jeng Shiun Lim ◽  
Timothy Gordon Walmsley ◽  
Peng Yen Liew ◽  
Masafumi Goto ◽  
...  
Keyword(s):  
Waste Heat ◽  
Meteorological Data ◽  
Hot Water ◽  
Solar Thermal ◽  
Critical Parameters ◽  
Physical Constraints ◽  
Levelized Cost ◽  
Thermal Integration ◽  
Levelized Cost Of Heat

Solar energy is currently an underutilized renewable energy source that could fulfill low-temperature industrial heat demands with significant potential in high solar irradiance counties such as Malaysia. This study proposes a new systematic method for optimization of solar heat integration for different process options to minimize the levelized cost of heat by combining different methods from the literature. A case study from the literature is presented to demonstrate the proposed method combined with meteorological data in Malaysia. The method estimates capital cost and levelized cost of solar heating considering important physical constraints (e.g., available space) and recovery of waste heat. The method determines and optimizes important physical dimensions, including collector area, storage size, and control design. As the result of the case study, the solar thermal integration with Clean-In-Place streams (hot water) gives the lowest levelized cost of heat with RM 0.63/kWh (0.13 EUR/kWh) due to its lowest process temperature requirement. The sensitivity analysis indicates that collector price and collector efficiency are the critical parameters of solar thermal integration.

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