Rooftop Of Building Research Articles

Energy yield measurement of an elevated PV system on a white flat roof and a performance comparison of monofacial and bifacial modules

Bifacial solar panels installed on flat rooftop of industrial buildings are an effective way to boost the yield. The albedo of the flat roof determines to great extent the bifacial gain. However, because it changes due to soiling and moss growth, the power output of bifacial PV installations over time is difficult to calculate. For the purpose of evaluating and rating the effect of bifacial PV rooftop systems, a small plant with 20 modules including dummies was installed. To guarantee an optimized output, a commercial bifacial PV module supporting construction was placed on a flat roof that was painted white. By using an east-west orientation, an optimum for the use of available roof space was reached. The yield for each module was determined with power optimizers and the extracted data, provided by the monitoring portal, were analysed. The data were collected for each day over a time of one year. Three different modules, both east and west orientated, were investigated. The bifacial module with a transparent backsheet compared to a module with the same bifacial cells but with a black backsheet, showed initially a benefit of 17% for the east and 15% for the west orientated panels. After one year of operation, a measured benefit of 7% for the east and 5% for the west orientated panels remained due to albedo loss because of moss growth and pollution. The use of panels with 92% bifaciality resulted in a higher yield of up to 3% compared to panels with 70% bifaciality.

Design and simulation of solar roof-top projects for an energy self-reliant university campus

A University campus becoming self-reliant in terms of electricity generation is always important. The power requirement of a University campus is mainly for its academic blocks for different departments. The laboratories, libraries, and hostel facilities also require continuous power needs. Conventionally, the electricity needs are met utilizing the power received from the local utility and the University will be paying for it based on the tariff fixed by the local regulators and agreed by the utility. It is proposed to install Solar Roof-top PV power plants in shade-free rooftops of the buildings inside a University campus to offset the University’s electricity needs and to make the University self-reliant in terms of electricity generation and consumption. This integrated and comprehensive solar project is intended to reduce the carbon footprint of the University and aiming for a carbon-neutral campus. Detailed feasibility studies have been conducted for installing solar roof-top power plants in the selected building roof-tops of the University. Based on the feasibility study, design and simulation have been carried out for a total 1.6MWp capacity of solar roof-top projects to completely offset the total electricity needs of the University based on the current electricity consumption patterns. The design and simulation are accomplished utilizing PVsyst software and the economic and environmental analysis has been carried out utilizing RETscreen software for arriving at the results.

Estimation of Wind Load on Stepped Tall Building Using CFD Simulation

The behavior of wind around stepped tall building is quite different comparing with the symmetric plan shape tall building. Setback roof of stepped buildings is widely responsible for the turbulence around the building. The purpose of this work is to understand the behavior of wind load on stepped tall building model. Four different models having the same dimensions and same aspect ratios but different setback distances, namely Models A, B, C and D, are considered. The setback distances are 0.2L, 0.3L, 0.4L and 0.5L (L = length) and are located at H/2 level (H = height) from the base of domain. Computational fluid dynamics simulations are taken out of terrain category 2 with the model scale 1:300. The foreground of this study is the external pressure and force variation around the building face and roof at 0° and 90° wind incidence angles. Maximum positive pressure coefficient develops at 90% of building height from the base of all models and for setback case it goes to 80%. Negative pressure develops at the building roof top, whereas positive pressure develops in the setback roof for the same model and wind angle. This type of pressure variable will be considered in roof design of stepped building.

Layout Optimization of PV Arrays on Building Rooftop: Influence of Geographical Location and Weather Conditions

Layout Optimization of PV Arrays on Building Rooftop: Influence of Geographical Location and Weather Conditions

Recommendation of Pesticide for Roof Top Pest Image Using Convolutional Neural Network Model

Rooftop farming in urban places is gaining more popularity which increases the cultivation of organic vegetables on the rooftop of houses and buildings with the minimal utilization of water. But rooftop farming is more vulnerable to pest infestation which reduces the quality of plants. Urban residents are novices in farming, and they are unaware of the pest attacks. Various researchers have proposed pest identification systems using image processing techniques and machine learning algorithms specific to particular disease which shows less accuracy on generaliztion and not user-friendly. To provide user-friendly pest identification system, this paper proposes a mobile based pest identification system using the concept of pre-trained convolutional neural network model – AlexNet. Experimental results have been analyzed with various rooftop pests using different kernel sizes and layers of convolutional neural network. In addition, the best evaluated pre-trained model has been converted to a mobile application using REST API for the recommendation of pesticide to the novice user.

Towards a Net Zero Building Using Photovoltaic Panels: A Case Study in an Educational Building

The renewable energy production continues to accelerate as the world recognizes the negative impact of fossil fuel consumption on the environment. Among the renewable energy technologies, there has been rapid growth in the use of solar PV systems in the last two decades. The solar PV technology has been widely used to provide green and sustainable energy both in single households and various institutions. Researchers in educational institutions are currently attracted by this technology as it is economically competitive with conventional forms of electricity generation. The aim of this study is to design and assess the potential of a grid-connected solar PV system on the rooftop of an educational building in Morang, Nepal. The performance of the system, which can satisfy 100 % of the energy needs of the campus, is simulated using PVsyst and the results are analyzed. The simulation results show that a 48 kWp solar PV power plant would fulfill the total annual energy demand of 66.009 MWh of the campus; the solar array can produce 75.9 MWh/year of energy. The economic analysis of the proposed system is carried out using PV*SOL software, while the environmental analysis is performed using PVsyst. The environmental analysis shows that the proposed PV electricity generation can save 76.3 tonnes of carbon dioxide production. Hence, this green campus design will be a significant step towards transforming academic campuses in Nepal into energy-efficient and environmentally sustainable communities. an abstract of up to 250 words for all articles. This is a concise summary of the whole paper, not just the conclusions, and is understandable without reference to the rest of the paper. It should contain no citation to other published work. Include up to six keywords that describe your paper for indexing purposes. Define abbreviations and acronyms the first time they are used in the text, even if they have been defined in the abstract. Abbreviations such as IEEE, SI, MKS, CGS, sc, dc, and rms do not have to be defined. Do not use abbreviations in the title unless they are unavoidable. https://dorl.net/dor/20.1001.1.13090127.2021.11.2.36.5

Rooftop layout optimization for PV installation using GIS

In this work, we develop a new modelling process to optimize the PV installation layout on industrial building rooftops; the model searches for maximizing the number of installed PV panels in a defined spot area, characterized by its shape, size, tilt and orientation. The study focuses on areas of latitude between tropics, but is useful for other latitudes. The method is applied to an industrial conglomerate of reference, made up of 34 industries, whose geographical characteristics have been provided by the GIS technique. The proposed model reduces the area of the spot to a very small size (5m x 5m), thanks to the use of the GIS tools, thus increasing the precision of results and making the solution more reliable. The accuracy of the method is over 98.5%. The model takes into account not only the shape and size of the PV panel but also the tilt angle. The model predicts the number of panels as a function of the tilt angle of the panel and the azimuth of the rooftop. The modelling process has allowed obtaining the surface coverage factor of the PV layout for panels facing to the Equator in rooftops with a specific azimuth. The results of the modelling shows that coverage factor increases with the rooftop’s azimuth, having a minimum value of 75% for a rooftop azimuth of 45o and a maximum of 92% for angles of 5o and 85o.

Statistical Analysis of Electrical and Non-Electrical Parameters of Photovoltaic Modules in Controlled Tracking Systems

The paper presents statistical analysis of measurement results of electrical parameters for photovoltaic modules installed in stationary and dual-axis configurations. The parameters which were taken into account included: coefficient of variation, skewness and standard deviation. Also a correlation was determined between independent variables such as insolation, sunshine duration, cloudiness, ambient temperature and atmospheric pressure, and the dependent variable in the form of the daily electricity from photovoltaic conversion. In order to determine the repeatability of electricity waveforms occurring between summer months as well as between summer and winter months, the non-parametric U Mann-Whitney test was used. In order to analyse the repeatability of daily peak hours in which the highest value of the hourly electricity production is observed, the non-parametric Kruskal-Wallis test was used. The tested systems were connected to the power grid and operated independently. Test stands consisting of polycrystalline photovoltaic modules, single-phase on-grid inverters, irradiance sensors and a temperature recorder, were located on the building rooftop of the Faculty of Control Robotics and Electrical Engineering of the Poznan University of Technology in Poland (Central Poland, 52°24.4152′N, 16°55.7958′E) at the height of 30 metres above the ground level. A significant increase in the production of electricity using the PV module spatial positioning system was demonstrated in relation to modules based on the year-round modified design.

Design and Testing of Building Integrated Hybrid Vertical Axis Wind Turbine

Building integrated wind turbine are considered as part of a group of technologies that are suitable for domestic micro-energy generation. Darrieus and Savonius turbines work efficiently in the urban environment at low wind speed, the Savonius rotor is self-starting and creates high torque but has low efficiency, while the Darrieus rotor is very efficient but does not self-start easily. Thus, the combination of these rotors as hybrid system would help to improve the overall efficiency of the wind turbines. The aim of this paper was to design, fabricate and experimentally investigate the performance of hybrid Vertical Axis Wind Turbine (VAWT) on residential buildings. A building model with gable rooftop was design and fabricated for use in testing of the hybrid VAWT. The height of the hybrid VAWT was paced at <I>Y</I> = 150 mm above the rooftop. The results obtained from the studies showed that the hybrid VAWT mounted on the building rooftop yield up to 63% more energy compared to the bare-hybrid VAWT (without building). Similar improvement in performance of the hybrid VAWT is also observed in the rotational speed, mechanical power and the coefficient of torque, where the building integrated hybrid VAWT outperformed the bare-hybrid VAWT. Thus the results indicate that urban buildings are suitable for the mounting of the hybrid VAWT.

Application of GIS tools to the improvement of energy supply in PV rooftop installations

Present work studies the energy supply from photovoltaic (PV) installations in industrial conglomerates using the rooftops as a surface to install the PV panels. The study is based on a modelling procedure that takes into account the specific characteristics of the rooftop, shape, size, azimuth and inclination, using GIS tools to identify these parameters for every single rooftop. Modelling has been developed modifying the tilt angle of the PV panel for vertical and horizontal PV panel layout and analyzing which one of the two configurations generates more energy. The study has been extended for tilt angles from the horizontal plane to the latitude of the location. The methodology uses a previous study in determining the optimum number of PV panels that can be placed on the rooftop. Shading effects have been taken into account for energy supply calculation, resulting in a variation with the tilt angle of the PV panel that depends on the range of the tilt angle; three ranges have been identified, low (0≤β/ϕ≤0.3), medium (0.3≤β/ϕ≤0.8)and high (0.8≤β/ϕ≤1). Maximum variation, 1.6%, has been observed in the low range, while for the high range energy supply does not seem there is no blocking to depend on the tilt angle. The results show that the modelling matches theoretical predictions within accuracy higher than 99.4%. Modelling has also been developed for two different configurations of the PV panel positioning, vertical and horizontal. Tests have been applied to the largest and smallest rooftop; the similar trend in the evolution and the close values of the energy supply with tilt angle proves that the methodology can be applied to any of the industrial building rooftops. The results of the modelling show that there is no much difference between the two configurations; however, horizontal configuration works better for larger areas while vertical one is more suitable for smaller areas. Additional row has been added to the layout provided the shadow is out of rooftop bounds. The increase of the energy is not very relevant, barely 1% for the vertical configuration and 0.2% for the horizontal one.

Identifying Building Rooftops in Hyperspectral Imagery Using CNN With Pure Pixel Index

Identifying Building Rooftops in Hyperspectral Imagery Using CNN With Pure Pixel Index

디지털트윈 기반의 스마트시티 3차원 태양광 발전 시뮬레이션 시스템 개발

The installation of solar photovoltaic panels is gradually spreading even in cities in accordance with the policy of enhancing energy independence and expanding renewable energy through smart city construction. In this paper, a 3-dimensional photovoltaic simulation system suitable for cities such as apartment veranda, rooftop of buildings, parking lot or park site is proposed by generating the shadow of buildings in minutes through the location calculation of the sun every day in the 3D building map. In addition, it is possible to visualize photovoltaic power generation and sunlight volume along with the shadow of 3D buildings moving by time zone by using digital twin technology, and it has the advantage of exploring the optimal direction and angle for maximum generation.

3D-CFD Study of Oblique Streamlining Membranes on the Roof-Top of a Low-Rise Building, Targeting Pedestrian Comfort-A Case Study

Considering the cubic nature of the most frequent geometries among the urban elements and their configurations, the manipulation of the free stream wind flow around the enormous objects, as well as within relatively narrow corridors, such as street canyons is significant in many regards. One of its instances could be mentioned as pedestrian comfort. In this case study, the implementation of an Oblique Streamlining Membrane (OSM) has been studied on a sub-branch of a low rise, but bulky, building, over which a roof-top outdoor food court area has been primarily designed. The OSM serves as the streamlining mechanism, preventing the roof-top area from the intense fluctuations of the wind flow after the flow is separated from the inlet corner side of the building in question. The optimization of sub-geometries and the proof of the concept for the OSM flow controlling mechanism were the subject of the current manuscript, for which a 3D numerical Reynolds Average Navier-Stokes (RANS) scheme has been used. An unstructured computational grid has been applied around the 3D geometry of the entire building and its sub-branching details, which is in contrast with most studies on full-scale geometries, tending to have simplifications on the body to reach a more generalized set of results. All cases have been numerically tested with and without the presence of the OSM. This comparison has been the grounds for proving the effectivity of the said flow controlling mechanism to eliminate high gradient fluctuations of the separated flow off the roof corners. This has led to pedestrian/resident comfort on the roof-top food court area located on top of the building.

Estimating Rooftop Areas of Poultry Houses Using UAV and Satellite Images

Poultry production requires electricity for optimal climate control throughout the year. Demand for electricity in poultry production peaks during summer months when solar irradiation is also high. Installing solar photovoltaic (PV) panels on the rooftops of poultry houses has potential for reducing the energy costs by reducing the electricity demand charges of utility companies. The objective of this research was to estimate the rooftop areas of poultry houses for possible PV installation using aerial images acquired with a commercially available low-cost unmanned aerial vehicle (UAV). Overhead images of 31 broiler houses were captured with a UAV to assess their potential for solar energy applications. Building plan dimensions were acquired and building heights were independently measured manually. Images were captured by flying the UAV in a double grid flight path at a 69-m altitude using an onboard 4K camera at an angle of −80° from the horizon with 70% and 80% overlaps. The captured images were processed using Agisoft Photoscan Professional photogrammetry software. Orthophotos of the study areas were generated from the acquired 3D image sequences using structure from motion (SfM) techniques. Building rooftop overhang obscured building footprint in aerial imagery. To accurately measure building dimensions, 0.91 m was subtracted from building roof width and 0.61 m was subtracted from roof length based on blueprint dimensions of the poultry houses. The actual building widths and lengths ranged from 10.8 to 184.0 m and the mean measurement error using the UAV-derived orthophotos was 0.69% for all planar dimensions. The average error for building length was 1.66 ± 0.48 m and the average error for widths was 0.047 ± 0.13 m. Building sidewall, side entrance and peak heights ranged from 1.9 to 5.6 m and the mean error was 0.06 ± 0.04 m or 1.2%. When compared to the horizontal accuracy of the same building measurements taken from readily available satellite imagery, the mean error in satellite images was −0.36%. The average length error was −0.46 ± 0.49 m and −0.44 ± 0.14 m for building widths. The satellite orthomosaics were more accurate for length estimations and the UAV orthomosaics were more accurate for width estimations. This disparity was likely due to the flight altitude, camera field of view, and building shape. The results proved that a low-cost UAV and photogrammetric SfM can be used to create digital surface models and orthomosaics of poultry houses without the need for survey-grade equipment or ground control points.

Automatic Extraction of Buildings from UAV-Based Imagery Using Artificial Neural Networks

The rapid growth of major cities across the counties demands accurate building extraction techniques. Unmanned Aerial Vehicles (UAV) help in obtaining terrain information that can be used to extract urban features. Recent advancement has led to the capture of aerial images of the earth surface in micro-detail using UAV. These aerial images enable us to perform classification, feature extraction, and height estimation at a finer scale. In this work, aerial images of the university campus were captured using a quadcopter drone equipped with high-resolution camera and satellite navigation system. Approximately 500 images were captured in the study area with necessary overlap and side lap. Captured images were subjected to aerial triangulation, dense image matching, and point cloud generation to produce Digital Surface Models (DSM) and orthophoto. Various machine learning algorithms—random forest (RF), support vector machine (SVM), naive Bayes (NB) and artificial neural networks (ANN)—have been used to extract building rooftops from derivatives of UAV-captured imageries, and accuracies were compared. Algorithms were trained using both spectral and elevation information to extract building rooftops, and improvements shown due to the addition of elevation data in training the model are observed. The proposed method is aimed at improving building-level information extraction and providing accurate building information to aid authorities for better planning and management.

Modelling the yield of 8.64 kW PV panels installed on a rooftop of a building in the Kingdom of Bahrain

PurposeThis paper allows more accurate estimation of the economy in investing in PV electrification for buildings, especially for Gulf Cooperation Council Countries (GCCC) where they have nearly similar climate and building structure. The actual solar electricity yield from this building is used to make empirical modelling.Design/methodology/approachThe accurate automated daily-recorded solar electricity from 8.64 kW solar PV on a rooftop of Sadeem Building at Awali, Bahrain, was modelled to polynomial equations of order of 6. The effect of the tilt (β) and azimuth (Ψ) angle of PV panels for smart and sustainable buildings is studied.FindingsThe correlation of each set of polynomial equation (R2) is listed and had reached a highest value of 0.9792 (for order of 6) with lowest value of 0.1853 (for order of 1). The model may be also applied to the GCCC. The results show that each kW of PV will have a solar electricity yield, on average, of 4.1 kWh. It also shows that the tilt angle has little influence on the solar electricity yield (less than 10%) when the tilt angle changed from 26° to 0° or from 26° to 50°. The influence of the azimuth angle is found to be more than 50% in changing Ψ from 90° to 180°.Research limitations/implicationsThe model may not be restricted to Bahrain but applies – to a certain extent – to GCCC (six countries) and to other countries having buildings with similar roof design and at latitude close to the latitude of Bahrain.Practical implicationsThe model enables developers and investors to estimate, with high accuracy, the solar electricity provided from a building if PV panels are to be installed on its rooftop (or facade) at different tilt (β) and azimuth (Ψ) angle for smart and sustainable buildings.Social implicationsEmpirically finding out how much each kW of solar PV integrated to the building will produce solar energy electricity (in kWh), that is, 1 kW of PV yield, on average, 4.1 kWh.Originality/valueEstablishing empirical models to evaluate the outcome of each installed kW of PV panels. Each 1 kW installation of PV panels is 4.0 kWh/day, on average. This is less than what commercial companies claim for this region, that is, 1 kW produces 5.5 kWh/ day – which affects the estimated economic outcome of PV projects.

Effect of Relative Humidity and Temperature on PM2.5 Concentrations in Kampala, Uganda

Background Scientific evidence reveals that exposure to small particulate matter of 2.5 microns or less in diameter (PM2.5) is very detrimental to health thus resulting in increased risks of cardiovascular and respiratory disease, and cancers. There are three factors that have important effect on PM2.5 mass concentration: domestic pollutant emission sources, external sources outside of the country, and the meteorological conditions. We aimed assessing the effect of relative humidity and temperature on PM2.5 concentrations from 2018 to 2019 using the Beta Attenuation monitor 1022. Methods We measured the relative humidity, temperature, ambient PM2.5 concentrations prospectively from October 2017 to December 2019 using the Beta Attenuation Monitor (BAM) 1022 (Met One Instruments, Inc) at the Eastern Africa GEOHealth Hub air quality monitoring station, that installed at Makerere University School of Public Health Roof top building at height of 15 metres above the ground level, Kampala Uganda. Results The findings showed that annual averages of PM2.5, Ambient Temperature (AT) and Relative Humidity (RH) in 2018 was 41.3 µg/m3, 23.10C and 72.0% and in 2019 was 38.5 µg/m3, 23.80C and 71.9% respectively. The results showed that the annual averages for PM2.5, Ambient Temperature (AT) and Relative Humidity (RH) in 2018 and 2019 was about the same. The findings also revealed that every unit increase in relative humidity increased PM2.5 concentrations by 29.3% and every unit increase in ambient temperature reduced PM2.5 concentrations by 2.14). Notably also in 2018 and 2019 the daily PM2.5 average concentrations decreased when RH reached high a threshold 80%. Conclusion The daily PM2.5 average concentrations decreased when the relative humidity reached a high threshold of 80% in 2018 and 2019 in Kampala Uganda. Funding Sources: NIH Fogarty International Center, NIEHS, CDC/NIOSH, Canada’s IDRC, GACC Grant # 5R24 TW009552 [AAU]; 5R24 TW009548 [USC]; 1U01TW010094 [AAU]; 1U2RTW010125 [USC]

The status of air quality in Kampala city, Uganda 2017-2019: Results from the Eastern Africa GEOHealth Hub using a high-tech reference monitor (Beta Attenuation Monitor 1022)

Introduction: Ambient air pollution (AP), particularly from fine particulate matter &lt;2.5 micrometers in aerodynamic diameter (PM2.5) is a big public health problem especially in low and middle-income countries. Because of apparent high population growth rate (3%) and economic development in Uganda, ambient AP appears to be rising. As such, we are monitoring ambient PM2.5 concentrations in Kampala City in a series of studies about the effect of AP on health. This work is part of research and training objectives of the Global Environmental and Occupational Health (GEOHealth) Hub for Eastern Africa. Methods: Using a Beta Attenuation Monitor (BAM) 1022, we prospectively measured ambient PM2.5 concentration for 2 years. This equipment was installed at Makerere University School of Public Health building rooftop (about 15 meters high). The BAM 1022 generated real-time data on PM2.5, relative humidity and ambient temperature. Results: For the last two years (October 2017 to September 2019), the annual mean of PM2.5 concentrations were 41.3µg/m3 and 39.2µg/m3 respectively. Our two-year data consistently show that dry seasons (January, February, June, July and August) have higher monthly mean PM2.5 concentrations (46.6µg/m3) compared to the wet seasons of March, April, May, September-, October, November and December (35.7µg/m3). We observed that for two years the highest PM2.5 concentration in typical day was between 06.00hrs and 10.00hrs (peak being at 08.00hrs -PM2.5 61.3µg/m3). However, nights were more polluted between 19.00hrs to 04.00hrs (peak being at 23.00hrs (PM2.5 71.2 µg/m3). Further, when we divided the day (07.00hrs-18.00hrs) and night (19.00-06.00hrs), the average PM2.5 concentrations for the two years were 34.5µg/m3 and 46.9µg/m3 respectively.Conclusion: Ambient AP is higher in the dry season. Besides, there is more PM2.5 concentration at night compared to daytime. These results present an opportunity for further studies on AP and its effect on health using hospital mortality and morbidity data.

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Expected to operate in the imminent future, air taxi service (ATS) is an aerial on-demand transport for a single passenger or a small group of riders, which seeks to transform the method of everyday commute. This uncharted territory in the emerging transportation world is anticipated to enable consumers bypass traffic congestion in urban road networks. By adopting an electric vertical takeoff and landing concept (eVTOL), air taxis could be operational from skyports retrofitted on building rooftops, thus gaining advantage from an implementation standpoint. Motivated by the potential impact of ATS, this study provides a review of air taxi systems and associated operations. We first discuss the current developments in the ATS (demand prediction, air taxi network design, and vehicle configuration). Next, we anticipate potential future challenges of ATS from an operations management perspective, and review the existing literature that could be leveraged to tackle these problems (ride-matching, pricing strategies, vehicle maintenance scheduling, and pilot training and recruitment). Finally, we detail future research opportunities in the air taxi domain.

Experiment of wind-driven-rain measurement on building walls and its in-situ validation

This study proposes an empirical equation that estimates the amount of wind-driven rain (WDR) on a building wall, meaning the amount of rainfall intercepted by a building wall. The proposed equation was formulated by analyzing the results obtained in previous studies on the vertical profile and spatial distribution of WDR on building walls. A laboratory experiment was conducted to collect WDR measurements for several building wall models that fit the proposed empirical equation. This study also observed the WDR for a miniature building located on the rooftop of the Engineering Building of Korea University. The proposed empirical equation was validated by comparing its estimates to in-situ observations. The results indicate that the estimations and the observed results are similar overall, but there are some discrepancies particularly when the WDR is small, with a correlation coefficient of 0.71 and root mean square error of 1.90 mm/hr⋅m2. This study also estimates the amount of rainwater that can be collected from a building wall. The result shows that, even for a small building with a ratio of building wall to building roof of one, the amount of rainfall intercepted by the building wall can be up to 50% of the amount of rainwater collected on the building roof. This finding supports the idea that the WDR from a building wall can be a significant source of harvested rainwater.