Typical Meteorological Research Articles

Generation of Typical Meteorological Sequences to Simulate Growth and Production of Biological Systems

Numerical simulation applied to agriculture or wastewater treatment (WWT) is a complementary tool to understand, a priori, the impact of meteorological parameters on productivity under limiting environmental conditions or even to guide investments towards other more relevant circular economic objectives. This work proposes a new methodology to calculate Typical Meteorological Sequences (TMS) that could be used as input data to simulate the growth and productivity of photosynthetic organisms in different biological systems, such as a High-Rate Algae Pond (HRAP) for WWT or in agriculture for crops. The TMS was established by applying Finkelstein-Schafer statistics and represents the most likely meteorological sequence in the long term for each meteorological season. In our case study, 18 locations in the Madrid (Spain) region are estimated depending on climate conditions represented by solar irradiance and temperature. The parameters selected for generating TMS were photosynthetically active radiation, solar day length, maximum, minimum, mean, and temperature range. The selection of potential sequences according to the growth period of the organism is performed by resampling the available meteorological data, which, in this case study, increases the number of candidate sequences by 700%.

Generation of a Typical Meteorological Year for Global Solar Radiation in Taiwan

Solar energy technology is now a mature and environmentally friendly solution. Long-term and credible solar radiation data are required for energy assessments of solar applications. Due to the lack of a typical year and accurate, long-term global solar radiation data for Taiwan, data for the typical meteorological year (TMY) of global solar radiation from 30 weather stations across Taiwan of the Central Weather Bureau were gathered for this study. The database for solar radiation contains data for the 15 years between 2004 and 2018, except for one (Chigu) weather station which provides data for the 12 years between 2004 and 2015, which possesses credible data quality and meets the requirements of the TMY method. The minimum and maximum TMY global radiation observed from the 30 weather stations are 3421.8 and 5479.9 MJ/m2 at the Zhuzihu (Station 2) and Tainan (Station 16) weather stations, respectively. The effects of topography, geography, and latitude on the global radiation distribution in Taiwan are discussed. A trend of increasing annual global radiation from the northeast to the southwest in the Taiwanese mainland, which is attributed to the combined effects of topography and latitude, is observed. This credible, long-term database for global solar radiation is a prerequisite reference for solar information for use in determining the performance of solar energy applications in Taiwan.

PV Solar Yield Applicable Simulator Based on Free Irradiance Data Source: Applied Comprehensive Tool for Solar Engineers

Accurate PV system simulators are implemented with expensive software platforms using paid irradiance data. The main purpose of this paper is to develop and validate a PV system simulator, beginning with a solar cell parameter extraction model, then test and validate long-term Irradiance data using free online source (Typical Meteorological Year TMY in (PVGIS) European website), and finally building full solar generator simulator to run in working real conditions. Comparing results with Accurate Paid PV simulators (which use the Muneer model) showed good accuracy of the proposed simulator. Work flow starts with the Irradiance model’s data processing, then solar cell 5 parameters model data processing (to extract cell parameters), and finally full system simulator. MATLAB coding programs in real working conditions are used for simulation. Results of solar cell parameter extraction show 99.6% to 99.99% matching with data sheet and cell performance under standard test conditions. System model simulation output shows 8% less yearly generated energy compared to the PVGIS 2022 long-term simulation (hourly basis (one-year time)). This is due to incident energy variations (between the years 2016 and 2022) of 4.02%. The novelty of the algorithm is the methodology, as it tests irradiance data on an hourly basis and validates results for a whole continuous year. Also, the 5-parameter solar cell model is used to be validated in long term analysis, not only STC conditions and could be applied on any PV solar cell. The algorithm and block diagram used are scalable, modular, and interchangeable with similar models to be tested. This simulator could test several methods and models in solar pv technology.

A Comparative Analysis of Solar Radiation in Korea’s Typical Meteorological Year for Building Energy Analysis

A Comparative Analysis of Solar Radiation in Korea’s Typical Meteorological Year for Building Energy Analysis

CREATION OF A TYPICAL METEOROLOGICAL YEAR IN SPAIN. STEP BY STEP APPLICATION OF THE METHOD BASED ON UNE-EN ISO-15927-4:2011

Perceptible acceleration of the climate change process makes it necessary to update climate files, which are used, for example, for energy simulation of buildings. The process of preparing a climatic file associated with a geographical location and referring to a period of time, is a laborious task, which begins with the construction of what is known as the Reference or Typical Meteorological Year (TMY) representative of said time frame. The TMY results from the concatenation of the twelve Typical Meteorological Months (TMM) representative of that cycle: the "best" month of January, the "best" month of February, March, etc. This paper presents an example indicating, step by step, an applicable procedure in Spain for the creation of an TMY, taking as reference the guidelines contained in the UNE-EN-ISO-15927-4:2011 Standard. The description is included of the use of the Finkelstein-Schafer statistic as a selection criterion for the best candidate months (with the novelty that in this work a literal application is made of the procedure) and finally a comparative study that gives an idea of the degree of suitability of the AMT selected according to the Standard. Key Words: energy simulation, reference climatic file, Typical Meteorological Year, UNE-EN-ISO-15927-4

Evolution of Monthly Average Temperatures in Four Typical Climatic Zones In Senegal: Comparison Between Ground Temperatures and Temperatures of The Typical Meteorological Year

One of the most obvious signs of climate change is the increase in the global average temperature over the past decades. This work constitutes an evolution of the monthly average temperature over 4 climatic zones of Senegal followed by a correlation study between ground measurement temperatures and temperatures of a typical meteorological year. The sites are located respectively in the west of the country (Dakar), in the north (St Louis), in the east (Tambacounda) and in the south (Ziguinchor). The results showed temperature variations depending on the region under consideration and also on the time of year. The results give a correlation coefficient (R) of 0.937 in Dakar, 0.889 in St Louis, 0.507 in Tambacounda and 0.789 in Ziguinchor. The mean squared error (MSE) ranges from 1.707°C to 3.113°C. The mean absolute percentage error (MAPE) is between 5.3% and 9.6%. The mean absolute deviation (MAD) is between 1.308 °C and 2.873 °C. The low mean bias errors found make it possible to say that the correlations are good and the relationship between the in situ temperatures and those of the typical meteorological year is a relationship of direct proportionality.vegetation biomass changes in the lower levels to middle levels of ECL (Q8 up to Q6 ) and the vegetation distribution dynamics had appeared in upper levels of ECL ( Q4 up to Q1) .

A New Way to Obtain Climate Files in Areas with the Presence of Microclimates by Applying the Sandia Method: A Galician Case Study

In order to obtain reliable energy simulation results, it is essential to have accurate climate files corresponding to specific geographical locations. The present work describes a selection process of the Typical Meteorological Months (TMM) that will generate the Typical Meteorological Years (TMY) in eight locations of the Community of Galicia for an analysis period between 2008 and 2017 (10 years). The region of Galicia, located in the northwest of the Iberian Peninsula, due to its particular orography, is prone to the generation of differentiated microclimates in relatively close locations. The process of selecting the typical meteorological months has been carried out following the Sandia Laboratories method. In the present work, data from terrestrial meteorological stations have been combined with solar radiation data obtained from satellite images. Finally, for the validation and comparative study of results, files have been generated in Energy Plus Weather (epw) format. Trends have been checked and typical statistics have been used to analyse the correlations between the files generated with the Sandia method, and the usual reference files (LT, WY, BY). It is observed that with the eight files generated, new differentiated climates are detected, which will affect the improvement of the precision of the energy simulations of buildings that are going to be carried out. For example, in the case of the Campus Lugo and Pedro Murias stations, located in the same climatic zone according to Spanish regulations, differences are observed in the annual averages: DTm (13.7%), WV (41%) or GHI (9%).

Determining Irrigation Requirements of Extensive Crops Using the Typical Meteorological Year Adjusted to the Growing Cycle Period

In the Castilla-La Mancha (CLM, Spain) region, most of the irrigated area is managed by two different strategies in which the previously defined irrigation requirements of crops affect both the distribution of crops and the sustainable management of groundwater resources. Thus, in the western Mancha system, the amount of irrigation water per farm is limited, while in the eastern Mancha system the irrigable area per farm is limited. Therefore, the use of average irrigation requirements in these areas may cause yield drops in dry years and the overuse of groundwater. Consequently, the main aim was to achieve a better approach to the irrigation requirements of the main extensive crops in CLM (maize (Zea mays L.), onion (Allium cepa L.), garlic (Allium sativum L.), and barley (Hordeum vulgare L.)) to help farmers and water authorities achieve higher yields and a more sustainable use of water resources. The typical meteorological year (TMY) methodology combined with the MOPECO model were used to: (1) determine the distribution of wet, intermediate, and dry years during the growing cycle of the four selected crops; (2) determine the average (AVE) and typical irrigation requirements of these crops for the complete 70 years series (TMYG) or the duration of the crop cycle (TMYC), and under wet (TMYW), intermediate (TMYI), and dry (TMYD) year conditions; and (3) recommend the irrigation depths to be used for the management of farms and water bodies. The results show that the number of wet, intermediate, and dry years depends on the growing cycle of the crop considered, with wet years being unusual, although they notably increase the average rainfall in the area. The irrigation requirements for the average year were between 20.4 and 9.0% lower than the average irrigation requirements calculated for the four studied crops during the 70 years of the series. For western Mancha farmers the recommended irrigation depth for dry years and most profitable crops (garlic and onion) is the one calculated for the driest year of the series, while for the rest of the years and crops is that estimated by the global dry TMY (TMYGD). For eastern Mancha farmers the recommended irrigation depths are also those estimated by the TMYGD.

Performance Analysis of Direct Expansion Solar Assisted Heat Pump Using Typical Meteorological Year

Performance Analysis of Direct Expansion Solar Assisted Heat Pump Using Typical Meteorological Year

Climate adaptive optimization of green roofs and natural night ventilation for lifespan energy performance improvement in office buildings

Green roofs and natural night ventilation are highly coupled and complementary techniques to improve building energy efficiency, but previous studies have not fully explored the synergetic benefits of combining two technologies. Furthermore, the traditional method of design optimization using Typical Meteorological Year (TMY) weather data falls short of providing climate-adaptive designs for new buildings that react differently to weather changes, as well as capturing the applicability and uncertainty of yearly weather variations. Therefore, building long-term performance in practice often deviates significantly from its design expectation. To quantitatively assess the energy savings when integrating green roofs and night ventilation (GR-NV) while taking future long-term weather impacts into account, this study proposes a systematic approach that integrates field testing, sensitivity analysis, building energy simulation, and climate adaptive optimization. The proposed approach is validated and demonstrated in an office building in Chongqing, China. The results show that Chongqing's annual mean air temperature in 2050 would climb by 2.4 °C in comparison to that of TMY. With the global warming effects, the annual night ventilation hours and the amount of sensible heat dissipated by NV increased by 78 h (13.2%) and 15.8 MJ/m2 (18.7%) from 1991 to 2050. The choice of plant species in the GR-NV system would also be impacted by global warming. The optimal design alternative based on FMY could reduce annual energy use by up to 5.07 kWh/m2 (12.2%) in new buildings.

ANALYSIS OF ACTUAL, TYPICAL AND NORMATIVE CLIMATE DATA IN THE CONTEXT OF BUILDINGS ENERGY MODELING

This article analyses the actual, normative monthly and typical detailed climatic data for the city of Kyiv. Data on actual outdoor air temperatures during 2014-2021 were compared with indicators in accordance with Ukrainian regulations and the most common typical hourly climate files used for building energy modeling: International Weather for Energy Calculations (IWEC), Meteonorm, Typical Meteorological Year (TMY) from PVGIS tool and Onebuilding web-site. The values for outside air temperatures were compared on an average monthly basis and using the number of hours of outside air temperature duration. The latter approach allows to more accurately assess the energy efficiency indicators and energy consumption of heat supply systems with heat pumps. As the buildings energy need and energy consumption for heating values are significantly affected by heat gains due to solar radiation, a comparison of the normative value of global radiation on the horizontal surface with the values from the most common typical climatic data was also performed based on an average monthly basis. Taking into account the set of analysed climatic factors using monthly indicators for outside air temperatures and number of hours of outside air temperature duration, it is decided to use Meteonorm hourly data for Kyiv for further dynamic energy modeling of building with heat supply system based on different types of heat pumps, including the air-to-water and water(brine)-to-water ones. Also, climatic data used in RETScreen program show similar figures as normative values and therefore this program will be used for further technical and economic analysis as well and the results will be compared to the specialised program for heat pumps calculations GeoT*SOL, which also provides the detailed calculation of heat pumps system technical performance and economic calculations. In addition, possible deviations in the values of energy need for heating of the building when using different climatic data were estimated using the DesignBuilder / EnergyPlus software product. The potential deviation of energy need for heating results can be around -10…+6.5%.

Adaptation of Users to Future Climate Conditions in Naturally Ventilated Historic Buildings: Effects on Indoor Comfort

User behaviour can significantly affect indoor thermal comfort conditions, as well as energy consumption, especially in existing buildings with high thermal masses where natural cross ventilation is the main strategy to reduce cooling loads. The aims of this paper were: (i) to compare how behavioural changes evaluated by means of rule-based and stochastic models lead to changes in indoor thermal comfort levels, and (ii) to define the patterns of indoor thermal comfort in historic residential buildings in future scenarios. To this end, a historic building located in Molfetta (Southern Italy) was analysed using a dynamic energy simulation engine in five weather scenarios (Typical Meteorological Year, current extreme weather file 2018, predicted weather files for 2020, 2050, and 2080 generated by morphing method), and stochastic and rule-based models for window openings were adopted and compared. The results showed that the stochastic model was more accurate than the rule-based one, resulting in a reduction of discomfort conditions during the summer period between 30% and 50% in all climate scenarios. However, although the differences between predicted discomfort levels using rule-based and stochastic models tended to increase, discomfort levels still appeared to be not acceptable in the 2050 and 2080 scenarios due to the rising temperature driven by climate change.

Historical and future weather data for dynamic building simulations in Belgium using the regional climate model MAR: typical and extreme meteorological year and heatwaves

Abstract. Increasing temperatures due to global warming will influence building, heating, and cooling practices. Therefore, this data set aims to provide formatted and adapted meteorological data for specific users who work in building design, architecture, building energy management systems, modelling renewable energy conversion systems, or others interested in this kind of projected weather data. These meteorological data are produced from the regional climate model MAR (Modèle Atmosphérique Régional in French) simulations. This regional model, adapted and validated over Belgium, is forced firstly, by the ERA5 reanalysis, which represents the closest climate to reality and secondly, by three Earth system models (ESMs) from the Sixth Coupled Model Intercomparison Project database, namely, BCC-CSM2-MR, MPI-ESM.1.2, and MIROC6. The main advantage of using the MAR model is that the generated weather data have a high resolution (hourly data and 5 km) and are spatially and temporally homogeneous. The generated weather data follow two protocols. On the one hand, the Typical Meteorological Year (TMY) and eXtreme Meteorological Year (XMY) files are generated largely inspired by the method proposed by the standard ISO15927-4, allowing the reconstruction of typical and extreme years, while keeping a plausible variability of the meteorological data. On the other hand, the heatwave event (HWE) meteorological data are generated according to a method used to detect the heatwave events and to classify them according to three criteria of the heatwave (the most intense, the longest duration, and the highest temperature). All generated weather data are freely available on the open online repository Zenodo (https://doi.org/10.5281/zenodo.5606983, Doutreloup and Fettweis, 2021) and these data are produced within the framework of the research project OCCuPANt (https://www.occupant.uliege.be/ (last access: 24 June 2022)​​​​​​​ – ULiège).

Impact of Air Density Variation on a Simulated Earth-to-Air Heat Exchanger’s Performance

Due to their simple design and reliable operation, earth-to-air heat exchangers (EAHE) are used in modern buildings to reduce ventilation heat losses. EAHE operation in atmospheric conditions results in variation in ambient air temperature and pressure affecting air density. The paper presents the study on the impact of ambient air density variation on the calculated hourly air temperature at the EAHE outlet and the resulting energy use for space heating and cooling of an exemplary residential building. The ground temperature was computed from the model given in EN 16798-5-1. Then, air density was obtained using five various methods. Energy use for space heating and cooling of the building was computed using the 5R1C thermal network model of EN ISO 13790. Depending on the chosen method and concerning the base case without EAHE, a reduction in annual heating and cooling needs was obtained from 7.5% to 8.8% in heating and from 15.3% to 19% in cooling. Annual heating and cooling gain from EAHE were 600.9 kWh and 628.3 kWh for heating and 616.9 kWh and 603.5 kWh for cooling for the Typical Meteorological Years (TMY) and International Weather for Energy Calculation (IWEC) files, respectively. Unit heating and cooling gains per heat exchanger area were from 34.9 kWh/m2 to 36.8 kWh/m2 and from −35.1 kWh/m2 to −36.3 kWh/m2. Density variation with temperature from the relevant typical Polish meteorological year at constant pressure, in comparison to the method of EN 16798-5-1, resulted in an hourly difference of that unit gain up to 4.3 W/m2 and 2.0 W/m2 for heating and cooling, respectively. The same was true inthe case of IWEC files that resulted in differences of 5.5 W/m2 and 1.1 W/m2.

Generation of meteorological year for the assessment of photovoltaic systems performance in Togo, West Africa

In this paper, the Sandia method, based on the Finkelstein-Schafer (FS) statistical techniques was used to develop a Typical Meteorological Year (TMY) for five cities in Togo (Lomé, Atakpamé, Sokodé, Kara and Mango) with a view to assessing the performance of the 72-cell polycrystalline solar photovoltaic (PV) module in the study areas. Seven daily measurements of meteorological parameters (relative humidity, dew point temperature, minimum and maximum temperatures, mean temperature, wind velocity as well as global solar radiation intensity) obtained from the National Aeronautics and Space Administration (NASA) for 1987–2016 period were used. The TMY predictions were compared with the 30-year Long-Term (LT) average values of the dataset. Two statistical indicators, the Mean Percentage Error (MPE) and the Root Mean Square Error (RMSE), were adopted to evaluate the performance of the PV energy system. Results show close agreements between TMY and LT values for all the parameters considered. The TMY in most cases underestimates the LT mean and fluxes are relatively small. Although the PV energy simulations were found to be underestimated, the generated solar PV energy obtained with TMY compares fairly well with those obtained with LT data. The performance of the TMY data is found to vary over the country but considered ‘very good’ with MPE values ranging between 0.24% and 2.46% as well as RMSE ranging between 8.29 and 16.71 kWh. Slight but insignificant biases (positive in the southern cities of Togo but negative in the north) were found between the estimated PV energy with the TMY when higher weight for global solar radiation was used. This study has implications in building energy simulation for comparative energy efficiency studies.

Are the current incentives sufficient to drive the use of solar PV in the Colombian residential sector? - An analysis from the perspective of the game theory

It is necessary to increase the use of renewable energy sources to supply the world's energy demand to mitigate the harmful effects of climate change. Many countries have incorporated the use of solar energy on a large scale. However, the use of photovoltaic (PV) systems at the residential level has been rather limited because many barriers to their implementation persist (e.g., high investment costs, insufficient government policies and incentives, and lack of knowledge in the implementation and operation of these systems). This paper aims to investigate how the interaction between prosumers and consumers can drive the use of PV systems at the residential level. The interaction is analyzed from the field of game theory. The payoffs of the players' strategies determine not only the Nash equilibrium but also the desirability of the interaction for both investment in the case of prosumer and consumption costs in the case of the consumer. Prosumer strategies consisted of selling power to the grid and to the consumer; selling only to the consumer; selling only to the grid; selling to the grid and giving to the consumer; and only giving to the consumer. The consumer strategies were to buy only from the grid or to buy from both the grid and the prosumer. The prosumer's investment in three sizes of PV systems (2.3, 2.7 and 3.6 kW) were analyzed; the amount of electricity produced was estimated using PVWatts and data from a Typical Meteorological Year in the city of Barranquilla, Colombia. The Net Present Value of each investment was calculated considering the prosumer's strategies and this indicator was taken to an equivalent annual cost to represent the prosumer's payment in the Nash equilibrium. On the other hand, for the consumer's payments, the annual energy purchase costs to supply their demand were used, according to the consumer's strategies. Analysis found that PV systems that can produce surpluses can be attractive to the prosumer if the tax on revenues received from the sale of energy to the grid is eliminated. Profitability is further improved if the prosumer is allowed to sell their surplus to other consumers, with the purchase price to the grid being the maximum price at which they can sell to other consumers. In turn, the cost savings for consumers will be greater to the extent that they can buy cheaper energy from prosumers. Based on these findings, countries such as Colombia, where there has not been a massive use of solar photovoltaic energy at the residential level, can stimulate investments in this sector by eliminating the income tax on the sales of surplus energy of small prosumers, without representing a loss of income for these countries.

The impact of using different weather datasets for predicting current and future energy performance of residential buildings in Egypt

As prognostic methods for buildings’ performance in present and future, energy simulations mainly rely, among other inputs, on weather datasets including Typical Meteorological Years (TMY), where the selected measurement period of the weather station is a crucial parameter. To quantify the predicted energy consumption’s discrepancies that may occur while using a recently generated TMY (2018-TMYx) instead of the commonly used Egyptian TMY (ETMY) that were created in 2003, both weather datasets, in addition to their future climate change projections in 2050 and 2080, were applied into Design Builder’s energy performance simulations for two residential buildings in different regions of Cairo and Aswan, Egypt. Results show that using weather datasets from different periods caused a maximum difference in annual energy consumption per flat by 933 kWh in present and 1508 kWh in 2080. The study proves the obsolescence of the commonly used ETMY due to the significant differences in energy simulation readings compared to the 2018 datasets.

An Evaluation of the Performance of a Ground-to-Air Heat Exchanger in Different Ventilation Scenarios in a Single-Family Home in a Climate Characterized by Cold Winters and Hot Summers

In the present study, the real-world performance of a ground-to-air heat exchanger (GAHE) was analyzed in the Polish climate which is characterized by warm summers and cold winters. The heat exchanger’s performance was monitored over a period of three years (2017 to 2019), and real-world conditions were compared with a Typical Meteorological Year (TMY). The aim of the study was to assess the exchanger’s energy-efficiency potential in various ventilation scenarios in a single-family home under variable real-world conditions, rather than to simply determine its heating and cooling capacity. The analyzed single-family home was a modern, single-story building with a usable floor area of 115 m2. The building’s thermal insulation and airtightness met stringent energy-efficiency standards. Energy consumption in a building equipped with a natural ventilation system was compared with three other scenarios: ventilation coupled with a GAHE, mechanical ventilation with heat recovery and a high-efficiency heat exchanger (HE), and mechanical ventilation with heat recovery coupled with a GAHE. Sensible heating and cooling loads were calculated based on standard ISO 13790:2008, and latent heating and cooling loads were also included in the energy balance. During the year, the GAHE generated around 257.6 W of heating energy per hour and 124.7 W of cooling energy per hour. Presented results can be used to select the optimal HVAC system scenarios for engineering projects as well as private investors.

Energy performance assessment of passive buildings in future climatic scenarios: the case of study of the childcare centre in Putignano (Bari, Italy)

The building sector is a primary target for GreenHouse Gas emissions mitigation efforts, as it accounts for 36% of final energy use. The most effective mitigation strategies include the energy retrofit of the existing building stock. Among existing buildings, particular attention should be paid to school buildings, which are among the most diffuse public buildings in Europe, most of them built decades ago, with a resulting high potential in terms of refurbishment effectiveness. Moreover, schools cover a social function and require high levels of indoor environmental quality. In this field, the research activity is intense, but retrofit strategies are still conceived considering historical weather data, which could not represent correctly present and future climate patterns, reducing the retrofit effectiveness. In this work, an energy retrofit to “Passivhaus standard” of a childcare centre located in the Mediterranean area is analysed through dynamic simulations. A post-retrofit building model is simulated using Typical Meteorological Year (TMY) and compared with the ones simulated in future weather scenarios, created using the morphing method. The analyses aim to assess if the technical solutions currently adopted on the basis of the TMY will lead to acceptable energy performance in future decades. Furthermore, a sensitivity analysis of different design solutions is performed, aiming to assess their effectiveness in future weather conditions.

Modeling Natural Light Availability in Skyscraper Farms

Lighting is a major component of energy consumption in controlled environment agriculture (CEA) operations. Skyscraper farms (multilevel production in buildings with transparent glazing) have been proposed as alternatives to greenhouse or plant factories (opaque warehouses) to increase space-use efficiency while accessing some natural light. However, there are no previous models on natural light availability and distribution in skyscraper farms. This study employed climate-based daylight modeling software and the Typical Meteorological Year (TMY) dataset to investigate the effects of building geometry and context shading on the availability and spatial distribution of natural light in skyscraper farms in Los Angeles (LA) and New York City (NYC). Electric energy consumption for supplemental lighting in 20-storey skyscraper farms to reach a daily light integral target was calculated using simulation results. Natural lighting in our baseline skyscraper farms without surrounding buildings provides 13% and 15% of the light required to meet a target of 17 mol·m−2·day−1. More elongated buildings may meet up to 27% of the lighting requirements with natural light. However, shading from surrounding buildings can reduce available natural light considerably; in the worst case, natural light only supplies 5% of the lighting requirements. Overall, skyscraper farms require between 4 to 11 times more input for lighting than greenhouses per crop canopy area in the same location. We conclude that the accessibility of natural light in skyscraper farms in dense urban settings provides little advantage over plant factories.