Solar Radiation Input Research Articles

Manure temperature prediction for slurry storage in Sweden: Model validation including effects of shading, snow cover and mixing

Measuring and modelling manure temperatures are crucial for estimating greenhouse gas emissions from liquid manure storage. The manure temperature was recorded at various depths in two swine slurry storage tanks situated in Vallentuna (VA) and Örsundsbro (OR) in Sweden. These data were used to assess the effectiveness of a revised mechanistic model for estimating manure temperatures, which incorporates the effects of wall shading, snow cover, and manure input mixing. The average manure temperatures were higher than air temperatures in the summer and fall. This indicated that using air temperature would result in an underestimation of methane emissions when applying the 2019 IPCC Refinement methodology. The revised model estimated manure temperatures for spring, summer, fall, and winter as 4.8, 16.1, 7.8, and 2.6 °C at the VA tank and 11.6, 17.1, 9.5, and 3.6 °C at the OR tank. The root mean square errors between daily simulated and observed temperatures in the summer decreased in both tanks due to incorporating shadow effect into the revised model. Fall estimates did not improve, possibly because of uncertainties from slurry removal and higher precipitation inputs. Sensitivity analysis indicated that solar radiative heat input was reduced with higher tank walls and smaller tank diameters when applying the revised model. Wall shading may influence manure temperatures in tanks with small diameters at high-latitude locations. This study offers insights into understanding the relationship between manure temperatures and its thermal balance influenced by latitude, storage design, snow cover and mixing, and its implications for accurately estimating methane emissions.

Simplified equations for wet bulb globe temperature estimation in Bangladesh

AbstractThe increasing temperatures and shifts in meteorological conditions have heightened the vulnerability of Bangladesh's densely populated regions, known for their high heat and humidity, to potential health hazards. While the Wet Bulb Globe Temperature (WBGT) is a widely acknowledged and robust measure for evaluating heat stress in various occupational and outdoor environments, its widespread application is impeded by the complexity of calculations, the substantial computational resources required, and the need for specialized expertise, particularly in developing nations. Therefore, this study aimed to develop simplified equations for estimating WBGT in Bangladesh using meteorological variables. This study applied Liljegren's model on high‐resolution reanalysis data of the European Centre for Medium‐Range Weather Forecasts (ERA5) to calculate WBGT from 1979 to 2021. Subsequently, linear and nonlinear regressions were used to derive simplified equations for estimating Liljegren WBGT in Bangladesh. The quadratic regression models offer simplified equations for WBGT estimation. The model with only temperature (Ta) as an input estimates WBGT with an R2 of 0.967 and an RMSE of 0.716, effectively capturing a significant portion of WBGT variability. The inclusion of solar radiation (SR) with Ta improved the performance, with an R2 of 0.996 and an RMSE of 0.242. The best parsimonious model, with an R2 of 0.986 and an RMSE of 0.471, is derived when wind speed is considered with Ta and SR inputs, achieving an R2 of 0.993 and an RMSE of 0.331. Comprehensive graphical and statistical analyses confirm the high accuracy of all models. The three‐input model notably demonstrates exceptional performance, attaining optimal values for critical metrics, including extreme WBGT. The results affirm the practical suitability of the derived models for accurate estimations of WBGT in Bangladesh. These equations provide simplified tools for assessing heat stress conditions, contributing to public health initiatives, occupational safety guidelines, and climate change adaptation strategies.

An Analysis of the Influence of Construct Parameters on the Solar Radiation Input in an Insulated Plastic Greenhouse

Insulated plastic greenhouses (IPG) were a new type of facility emerging in production in China. The mechanism of construct parameters on the indoor solar radiation deserves further study. A mathematical model that can well describe the spatial and temporal distribution of solar radiation in the greenhouse was established. Based on this model, the effects of multiple construct parameters, such as insulation blanket shading, height–span ratio, greenhouse azimuth, and geographical latitude, on the indoor solar radiation of IPG were quantitatively specified. The results showed that the spatial and temporal distribution of inside solar radiation was highly variable along the span direction of IPG. And by analyzing the simulation data, it was found that for different heights of greenhouses, the corresponding optimal span is different. Therefore, in the construction of greenhouses, the appropriate height–span ratio should be selected according to the planting demand. And by simulating the inside solar radiation under different greenhouse azimuth angles, it was found that accumulated daily solar radiation in the greenhouse reaches the optimum value when the greenhouse azimuth angle is in the range of 0–20°. This paper can provide theoretical guidance for the design and optimization of structure parameters of IPG in China.

Thermal photogrammetry on a permafrost rock wall for the active layer monitoring

Permafrost and active layer models often cannot explain the high spatial variability, especially in heterogeneous environments like the mountainous regions due to their scarce resolution, paucity of climatic data and topographic details. In this study, we want to introduce a new application of the unmanned aerial vehicle (UAV) in thermal photogrammetry to model the active layer thickness (ALT) of an alpine rock wall through the computation of the thermal inertia and compare the results with a widespread ALT model. On the Gran Zebrù South rock wall, 8 thermal UAV surveys has been conducted in 4 different summer days during 2021-2022 in order to have two 3D thermal models per day at different solar radiation inputs. By analyzing topographic data, visible imagery and the thermal models, the apparent thermal inertias (ATIs) have been converted into heat transfer coefficients (HTCs) and then into ALT of 2021 and 2022. These maps have been validated through the placement of thermistors at different elevations and with variable depths (2, 15 and 40 cm from the rock surface).The resulting ALT has been compared with the Stefan's solution and the alpine permafrost index map (APIM), which showed large underestimations and a noncorrespondence with permafrost occurrence. The average ALT increase of 29.3 cm from 2021 to 2022 has been discussed regarding permafrost formation/degradation future trend under the climatic change and potential risks of alpine areas.

Effect of nonuniform solar radiation on the performance of solar thermoelectric generators

Solar radiation must be concentrated before irradiating hot sides in solar thermoelectric generators (STEGs) to increase the temperature difference between hot and cold sides and thus enhance output performance. However, concentrated solar radiation is often nonuniform. This condition affects the output performance of STEGs. Herein, a thermal–electric coupled model of STEGs was constructed to investigate the thermoelectric performance of STEGs under nonuniform solar radiation. Results demonstrate that when the concentration ratio is low, increasing nonuniformity facilitates the increase in the output power of STEGs. When the concentration ratio is 60, output power increases by a maximum of 3.05 %, whereas the average temperature difference decreases by 4.44 K. When the concentration ratio is high, STEG output power peaks under a specific nonuniformity, and some thermoelectric legs at the edges of STEGs turn into load, affecting the overall STEG output performance. When the cold-side cooling performance is poor, the solar radiation input to STEGs should be made as uniform as possible to ensure the output performance and safe operation of STEGs. The results of this study provide guidance for the design of efficient STEGs.

QUICK PROTOCOL FOR INTEGRATING THE ATTRIBUTE INFORMATION OF UNSTRUCTURED POINT CLOUD DATA INTO A SOLAR ENVELOPE SIMULATION

ABSTRACT This study proposes a novel method of solar geometry by considering the potential application of point cloud data combined with the simulation of solar radiation. With the support of geometric and radiometric information stored in the point cloud such as position information (XYZ) color information (RGB), and reflection intensity (I), architects may compensate for missing information on the existing context during the simulation, especially due to the limited capacity of current 3D modelling sites. However, the dataset often comes in the format of unstructured point cloud data retrieved from merged data scans and as a result, the radiometric information is difficult to occupy due to multiple reference points. Through a 3D subtractive procedure, this study not only examines volumetric samples of the three-dimensional matrix that fulfills the criteria of solar envelopes but also finds the optimal values of the merged data scan for input of solar radiation. In this regard, simulation of solar radiation contributes to identifying the most and the least exposed areas to the sun in existing contexts. This provides information related to visible sun hours that can be used to perform ray tracing analysis between the proposed 3D plot and surrounding contexts. Our proposed method ultimately helps architects not only generate solar geometry based on real contextual settings but also to understand comprehensively the microclimate conditions of the design context.

H2/CO production via high temperature electrolysis of H2O/CO2 coupling with solar spectral splitting at a tunable cut-off wavelength

Solar driven CO2/H2O splitting is a promising path for large-scale and long-term solar energy conversion and storage. In this work, a thermodynamic model of solar driven high-temperature CO2/H2O electrolysis was established, with the full solar spectrum split at a tunable cut-off wavelength for meeting the electrical and thermal energy demands of the process at a high efficiency. Compared with the system without spectral splitting, the solar-to-H2 efficiency can be significantly improved from 36.0 % to 45.5 % by introducing spectral splitting. Besides, the optimal electrolysis temperature can be largely lowered, from 1623 K to 1323 K due to the significant reduction of the solar radiation input for electricity generation. The exergy efficiency of CO2 electrolysis was shown to be higher than that of H2O electrolysis due to the higher molar exergy of CO compared to H2, although the first-law efficiency of H2O electrolysis is higher at Tele < ∼1200 K. A high concentration ratio of the solar-thermal process can lead to both high solar-to-fuel efficiency and high optimal electrolysis temperature because of the reduction of reradiation loss. The electrolysis temperature and the use of excessive CO2/H2O were shown to have an important effect on both the efficiency and the optimal cut-off wavelength because they are closely related with the thermal and electrical energy demands of the whole process. The optimal cut-off wavelength can be as low as 540 nm at electrolysis temperature of 1873 K (Tele = 1873 K) and excessive H2O coefficient of 6 (r = 6), and increases to the working limit of the photovoltaic material (900 nm in this work) as the electrolysis temperature and excessive coefficient decrease to Tele < 1023 K and r < 2.

Identification of a spatial distribution threshold for the development of a solar radiation model using deep neural networks

We propose an approach to develop a solar radiation model with spatial portability based on deep neural networks (DNNs). Weather station networks in South Korea between 33.5–37.9° N latitude were used to collect data for development and internal testing of the DNNs, respectively. Multiple sets of weather station data were selected for cross-validation of the DNNs by standard distance deviation (SDD) among training sites. The DNNs tended to have greater spatial portability when a threshold of spatial dispersion among training sites, e.g. 190 km of SDD, was met. The final formulation of the deep solar radiation (DSR) model was obtained from training sites associated with the threshold of SDD. The DSR model had RMSE values <4 MJ m−2 d−1 at external test sites in Japan that were within ±6° of the latitude boundary of the training sites. The relative difference between the outputs of crop yield simulations using observed versus estimated solar radiation inputs from the DSR model was about 4% at the test sites within the given boundary. These results indicate that the identification of the spatial dispersion threshold among training sites would aid the development of DNN models with reasonable spatial portability for estimation of solar radiation.

Solar irradiance prediction using reinforcement learning pre-trained with limited historical data

Accurate day-ahead forecasting of solar irradiance is crucial for maintaining a steady power supply and minimizing energy losses. To date, various solar irradiance prediction models have been established, but these typically require extensive weather data collected over long periods within the area of prediction or consistent updates using field measurements. This research introduces a reinforcement learning-based model capable of long-term solar irradiance prediction, even in areas with limited accumulated data. Our proposed model can forecast solar radiation for more than a year using just two weeks of solar radiation learning and readily available weather forecasts. It demonstrated a promising performance, with an annual average CVRMSE error of 7.0%, which is a more optimized predictive performance than the 12.8% CVRMSE yielded by the existing LSTM-based Reference model constructed by adding out-of-atmosphere solar radiation input values.

Energy-balance modeling of heterogeneous glacio-hydrological regimes at upper Indus

Study regionThe Upper Indus River Basin (UIB). Study focusThe UIB has experienced marked runoff change due to the accelerated glacier melting under climate warming. Nonetheless, the glacio-hydrological regime in the UIB remains unclear due to considerable uncertainties in precipitation data and glacio-hydrology modeling. Here, we used a state-of-the-art water and energy budget-based distributed glacio-hydrology model (WEB-DHM-S) that employed an energy-balance glacier module for both clean and debris-covered glaciers to analyze the hydrological regimes within the UIB during 2001–2020, particularly the spatial heterogeneity among the Himalaya-Karakoram-Hindu-Kush mountains. New hydrological insights for the regionResults indicated that the high-resolution ERA5-Land precipitation data showed the most reliable estimate (∼750 mm/yr) among available products, which was the model’s forcing data. Our results showed that the mean contributions of snow, glaciers, rainfall, and baseflow to total runoff in the UIB were 41.5%, 23.3%, 34.7%, and 0.5%, respectively. Glacial melting made the largest contribution to total runoff in the Karakoram (35.3%), while the smallest contribution was made in the Hindu Kush (15.9%). Further, we showed that glacial melting was highly sensitive to changes in air temperature and solar radiation inputs. In particular, fluctuating solar radiation could change the magnitude and timing of annual flood peaks in ice melting, which emphasized the crucial role of energy-related forcing data (besides the traditional precipitation and air temperature inputs) in glacio-hydrology modeling.

Design and Assessment of the Solar Energy Based Direct Steam Generation Supercritical CO2 Brayton Cycle

The aim of this study is to examine the performance of the supercritical CO2 Brayton cycle (sCO2-BC)with intercooling and reheating for low-temperature solar energy application. The heat required for the sCO2-BC is supplied from an evacuated tube solar collector. Energy and exergy analyses of the solar energy-assisted sCO2-BCwith intercooling and reheating are investigated. In addition, the effects of operating parameters like solar radiation, collector number, compressor, and turbine input pressure on system performance are examined parametrically.According to the findings of the analysis, the net power production is found to be 0.2687 kW. In addition, the solar energy-based sCO2-BC's energy and exergy efficiencies are found to be 3.68% and 3.95%, respectively. Moreover, it has been determined that the sCO2-BC's energy and exergy efficiencies reduce with the increase of solar irradiation, the collector number, and the compressor inlet pressure, while the system's energy and exergy efficiencies rise with the increase of the turbine input pressure.

Symmetry in Hillslope Steepness and Saprolite Thickness Between Hillslopes With Opposing Aspects

AbstractThe structure of the critical zone (CZ) is a product of feedbacks among hydrologic, climatic, biotic, and chemical processes. Past research within snow‐dominated systems has shown that aspect‐dependent solar radiation inputs can produce striking differences in vegetation composition, topography, and soil depth between opposing hillslopes. However, far fewer studies have evaluated the role of microclimates on CZ development within rain‐dominated systems, especially below the soil and into weathered bedrock. To address this need, we characterized the CZ of a north‐facing and south‐facing slope within a first‐order headwater catchment located in central coast California. We combined terrain analysis of vegetation distribution and topography with soil pit characterization, geophysical surveys and hydrologic measurements between slope‐aspects. We documented denser vegetation and higher shallow soil moisture on north facing slopes, which matched previously documented observations in snow‐dominated sites. However, average topographic gradients were 24° and saprolite thickness was approximately 6 m across both hillslopes, which did not match common observations from the literature that showed widespread asymmetry in snow‐dominated systems. These results suggest that dominant processes for CZ evolution are not necessarily transferable across regions. Thus, there is a continued need to expand CZ research, especially in rain‐dominated and water‐limited systems. Here, we present two non‐exclusive mechanistic hypotheses that may explain these unexpected similarities in slope and saprolite thickness between hillslopes with opposing aspects.

Attractors and bifurcation diagrams in complex climate models.

The climate is a complex nonequilibrium dynamical system that relaxes toward a steady state under the continuous input of solar radiation and dissipative mechanisms. The steady state is not necessarily unique. A useful tool to describe the possible steady states under different forcing is the bifurcation diagram, which reveals the regions of multistability, the position of tipping points, and the range of stability of each steady state. However, its construction is highly time consuming in climate models with a dynamical deep ocean, whose relaxation time is of the order of thousand years, or other feedback mechanisms that act on even longer time scales, like continental ice or carbon cycle. Using a coupled setup of the MIT general circulation model, we test two techniques for the construction of bifurcation diagrams with complementary advantages and reduced execution time. The first is based on the introduction of random fluctuations in the forcing and permits to explore a wide part of phase space. The second reconstructs the stable branches using estimates of the internal variability and of the surface energy imbalance on each attractor, and is more precise in finding the position of tipping points.

A transient model for clean electricity generation using Solar energy and ocean thermal energy conversion (OTEC) - case study: Karkheh dam - southwest Iran

Given the limitations of fossil fuels, humans must develop alternate energy sources. Solar energy and ocean thermal energy are known as a safe, secure, promising, and clean instrument for this purpose due to their enormous potential. A hybrid system of solar energy and ocean thermal energy with a thermoelectric generator is examined in this study to generate clean electricity and utilize the water temperature difference of the Karkheh dam. The system under consideration is made up of flat panel solar collector subsystems and a Rankin organic cycle. To model the analyzed system and acquire system analysis results, thermodynamic software of EES engineering equations solving was employed. The collector area, solar radiation intensity, ambient temperature, and input temperature to the turbine have all been studied as parameters affecting system outputs. The system's economic research revealed that the solar unit, evaporator, and ORC turbine have the highest cost rates among the system components. Furthermore, the system's exergy study revealed that the solar unit and evaporator suffered the highest exergy destruction. For one year, a case study was conducted on the water temperature difference at Karkheh Dam, and the findings of system performance were assessed. The results demonstrated that the best system performance is obtained under summer weather conditions in Andimeshk. The results showed that the proposed system's total output power in relation to the difference in water temperature of Karkheh Dam is 1,192,607/9 kW per year, and that this system can meet the energy needs of 111 households in Andimeshk throughout the year. According to the results, the system described in this study is suitable for the required applications.

CAN ACCURACY ISSUES OF LOW-COST SENSOR MEASUREMENTS BE OVERCOME WITH DATA ASSIMILATION?

The use of mechanistic plant growth models relies on the availability of high-quality inputs to reduce uncertainty in estimates. Measurements of photosynthetically active radiation inside a protected environment are either more expensive to obtain or dependent on assumptions regarding external measurements. This study aimed to reduce the influence of uncertainty in the measurements of low-cost lux meters by using a data assimilation strategy. We first determined, by simulation, the impact of different sensors on the estimates. We then used the Ensemble Kalman Filter to assimilate artificial observations of tomato growth in the Reduced-State Tomgro model, in simulations for which the solar radiation inputs were obtained from a low-cost lux meter. We compared the assimilated estimates to the simulations that used solar radiation obtained with a scientific-grade quantum sensor. For periods of larger radiation intensity, in which the differences in measurements from both instruments are larger, assimilation of observations with low errors lead to estimates that are closer to the ones obtained by scientific grade sensors. These results suggest that low-cost sensors could be used to obtain inputs for growth models in protected environments, provided there are also imperfect observations of the state.

Qualitative Considerations on the Influence of the Gases Water Vapor and Carbon Dioxide on the Global Environmental Temperature from the Point of View of Textbook Knowledge

The solar radiation that hits the Earth conditions the dynamic equilibrium that prevails on our planet. Consideration of basic physical-chemical knowledge shows that this equilibrium can be changed only by additional energy input or prolongation of the interaction time solar radiation—Earth matter. The contribution of H2O(g) and CO2 to the protection of the earth against excessive warming is experimentally and by basic laws of nature secured. For a greenhouse effect, a part of the earth radiation must be radiated back to the earth and then into space. If one understands the earth radiation as radiation of a black body with the average global environmental temperature, from all vibrations normal modes of the gases H2O(g) and CO2 only the bending mode of CO2 with 4% of the solar constant can contribute beside the rotational modes of the water to the greenhouse effect. The contributions of the normal modes of H2O(g) and CO2 to the heat capacity of the atmosphere are negligible. Therefore, in agreement with studies by K. Ångström, CO2 contributes only to the stabilization of the global environmental temperature. Whether the use of renewable energies can actually at least mitigate the increase of the environmental temperature is by no means certain but must be examined for each individual case. With certainty, this goal can only be achieved by reducing the energy consumption of mankind.

Thermoradiative induced absorber-emitter to enhance solar thermoelectric conversion

Solar thermoelectric power, is promising for use in small-scale CSP system due to its flexible architecture and silent operation. However, the conversion performance of standalone solar thermoelectrics is still far from ideal at lower concentration ratio. This paper tends to introduce a self-powered thermoradiative absorber-emitter at the top to enhance the overall solar thermoelectric power generation. Thermodynamic model based on energy balance has been established, and the implications of critical factors on the conversion performance of the thermoradiative-thermoelectric (TR-TE) combined system have been thoroughly examined. The findings show that an optimal ratio of absorber/emitter surface area of 1 is favored due to a tradeoff between thermal radiation loss from the absorber to the ambient and thermoradiative emission dissipation, as well as the thermoradiatives with a low bandgap and a high output voltage. The overall conversion efficiency of the solar TR-TE combined system approaches to 27.86 % at a cold junction temperature of 300 K and a concentration ratio of 50. Accordingly, the maximum efficiency of the combined system is 6.51 times that of independent solar thermoelectrics and is ∼13.67 % higher than independent solar thermoradiatives. In the TR-TE combined system, thermal radiation from the absorber to the environment accounts for 3.83 % of the solar radiation input as compared to 2.47 % in the independent solar TE generator. While the heat dissipated at the cold junction of a solar TR-TE system is 43.66 %, considerably less than that of 84.6 % for independent solar thermoelectrics.

Experimental and thermodynamic analysis of solar air dryer equipped with V-groove double pass collector: Techno-economic and exergetic measures

• Thermodynamic model and experimental validation of v-groove solar dryer. • Optimum flow rate of air within the collector was obtained for maximum efficiency. • SEC was 3.01 kWh/kg at 0.041 kg/s with 59% energy saving for apple drying compared with electricity driven heating. • Sustainability indices of the solar air collector and dryer are 1.50 and 1.047 respectively. • Energy payback period for the system is less than 1 year. Optimised solar air dryers, in terms of efficiency and performance, can solve some major concerns in the agro-industrial processing sector. Solar air dryers can reduce the large share of energy costs of a final product and can provide sustainable energy in rural areas where access to energy is often limited. In this study, a pilot scale v-groove double pass solar air collector has been analysed thermodynamically with real time solar radiation and mass flow rate (0.021-0.061 kg/s) inputs and validated experimentally in terms of first and second law efficiencies. Performance of the process was assessed using experimental drying measures including final moisture content, drying rate and exergy efficiency for drying of Pink Lady apples. Energy payback time and specific energy consumption were calculated to reveal the techno-economic value of the system. The maximum thermal efficiency of the collector was observed to be 88.8% at 0.061 kg/s having exergy efficiency of 6.6% which shows an efficient sourcing for the operation. In terms of the performance of the dryer, mass flow rate of 0.041 kg/s offers a higher moisture removal. Specific energy consumption (SEC) was 3.096 kWh/kg. Thermodynamic model was validated with matching experimentation with acceptable RMSE for the range of investigated measures. Energy payback period time calculated by the embodied energy of the system was obtained to be 0.78 years which implies that the system is capable of addressing a large capacity drying if it is to be scaled-up.

Definition of the daily model of distribution of solar radiation on the curved surfaces of buildings

The development of the integration of renewable energy into the energy supply of buildings leads to the formulation of the problem of efficient placement of solar thermal devices on surfaces of complex shapes (shells). An urgent task is the development of tools that can justify the decision-making by designers about the advisability of placing solar thermal devices and their implementation in the energy-efficient design of buildings. The study solves the problem of finding zones on the surface of the envelope, receiving the maximum amount of solar radiation during a given period of time – an epoch. A method is applied based on discrete geometric modeling of solar radiation input to curved surfaces of buildings. In this case, the interaction of a set of design parameters is taken into account: parameters of the shape of a curved surface and parameters of variable sunlight for the characteristic dates of September 21, March 21 – the solar equinox and December 21, June 21 – the winter and summer solstices. In the course of the study, N is determined – the optimal number of fixed positions of the Sun on the solar trajectory for different angles of solar declination (for June 22 N=17, for September 21, March 21 N=11, for December 21 N=8), for a given geographical location. One of the examples of modeling the amount of solar radiation entering the surface of a hyperbolic paraboloid during the day at the geographical latitude δ=52° (Kyiv, Ukraine) is shown. The simulation results in a family of lines of the same level of solar radiation on a curved surface during the day. Using the values of the averaged daily model, it is possible to proceed to obtaining averaged daily models for the estimated time interval at the stage of pre-project proposals to predict the efficiency of using the solar system

Using airborne lidar to characterize North European terrestrial high‐dark‐diversity habitats

AbstractA key aspect of nature conservation is knowledge of which aspects of nature to conserve or restore to favor the characteristic diversity of plants in a given area. Here, we used a large plant dataset with &gt;40 000 plots combined with airborne laser scanning (lidar) data to reveal the local characteristics of habitats having a high plant dark diversity—that is, absence of suitable species—at national extent (&gt;43 000 km2). Such habitats have potential for reaching high realized diversity levels and hence are important in a conservation context. We calculated 10 different lidar based metrics (both terrain and vegetation structure) and combined these with seven different field‐based measures (soil chemistry and species indicators). We then used Integrated Nested Laplace Approximation for modelling plant dark diversity across 33 North European habitat types (open landscapes and forests) selected by the European communities to be important. In open habitat types high‐dark‐diversity habitats had relatively low pH, high nitrogen content, tall homogenous vegetation, and overall relatively homogenous terrains (high terrain openness) although with a rather high degree of local microtopographical variations. High‐dark‐diversity habitats in forests had relatively tall vegetation, few natural‐forest indicators, low potential solar radiation input and a low cover of small woody plants. Our results highlight important vegetation, terrain‐ and soil‐related factors that managers and policymakers should be aware of in conservation and restoration projects to ensure a natural plant diversity, for example low nutrient loads, natural microtopography and possibly also open forests with old‐growth elements such as dead wood and rot attacks.