Climate Location Research Articles

The effect of year and genotype on productivity and quality of potato

The study presents results of a three-year experiment of variability of different potato varieties in Montenegro: early maturity varieties (Riviera), medium early (Almera, Aladin and Bounty) and medium late (Agria, Margarita, Kennebec and Desiree). The research was conducted during 2015, 2016 and 2017, in acid, brown soil and three different climatic locations: Nedakusi (556 m a.s.l.), Sutivan (680 m a.s.l.) and Orahovica (900 m a.s.l.). Field experiments were set up using standard methodology in random block design in three repetitions. The analysis of variance suggest that number of tubers per plant, mean tuber weight, yield of small tubers, marketable and total yields were significantly fluctuating depending on genotype (G), year (Y) and the location (L). In addition to individual influences of different factors, their interactions were also pronounced (G x Y, G x L, Y x L, G x Y x L). In the three-year period average, the highest total yield was recorded in Nedakusi (31.41 t ha-1), followed by Sutivan (21.35 t ha-1), while the lowest average yield (17.36 t ha-1) was recorded in Orahovica. As expected, on the three-year average, the highest percentage of dry matter was found in late varieties Agria - 25.46%, then Desiree - 25.33%, followed by Kennebec with 25.13%, while the lowest percentage of dry matter was found in medium early variety Almera - 20.82%. The highest average yield of tubers in the three-year period was recorded in the Aladin variety, followed by Agria and Desiree, while the lowest average yield was recorded in the variety Riviera. Obtained results show that the highest yields over observed locations were recorded in medium early varieties that formed high number of tubers per plant (Aladin) and medium late varieties (Desiree and Agria) give satisfactory and stable yields.

Defining guidelines for ditch depth in drained Scots pine dominated peatland forests

We used a process-based hydrological model SUSI to improve guidelines for ditch network maintenance (DNM) operations on drained peatland forests. SUSI takes daily weather data, ditch depth, strip width, peat properties, and forest stand characteristics as input and calculates daily water table depth (WTD) at different distances from ditch. The study focuses on Scots pine ( L.) dominated stands which are the most common subjects of DNM. Based on a literature survey, and consideration of the tradeoffs between forest growth and detrimental environmental impacts, long term median July–August WTD of 0.35 m was chosen as a target WTD. The results showed that ditch depths required to reach such WTD depends strongly on climatic locations, stand volume, ditch spacing, and peat thickness and type. In typical ditch cleaning areas in Finland with parallel ditches placed about 40 m apart and tree stand volumes exceeding 45 m ha, 0.3–0.8 m deep ditches were generally sufficient to lower WTD to the targeted depth of 0.35 m. These are significantly shallower ditch depths than generally recommended in operational forestry. The main collector ditch should be naturally somewhat deeper to permit water outflow. Our study brings a firmer basis on environmentally sound forestry on drained peatlands.Pinus sylvestris3–1

Real-time vulnerability analysis of hydropower projects under changed climatic scenarios

Utilising the kinetic energy of the flowing water and converting it to electrical energy can be a very useful method in the way of sustainable development as energy retrieved from the flowing water is comparatively inexpensive and a reliable renewable energy source which have the potential to substitute the conventional methods. But due to the increasing concentration of unwanted green house gases and global warming the environmental concentration are degrading day by day. The electricity production of hydropower plant will greatly be effected by climate change as the production is directly proportional to the rate of flowing water which directly depends on the climatic location of the power plant. Thus continuous climatic vulnerability monitoring becomes very important factor in order to predict the efficiency of a hydro power plant. In this study continuous climatic vulnerability monitoring is done by decision making-based neuro-genetic models.

Assessing the performance and cost-competitiveness of a dual-source solar assisted heat pump in cold climates

In many cold climates, the coincidence of long heating seasons as well as relatively high levels of solar insolation offer an opportunity to explore the potential for solar-assisted air source heat pumps to meet greenhouse gas reduction objectives for space and water heating systems. This paper presents the results of a detailed performance analysis based on 6 months of field test data of a pre-commercial, dual source solar-assisted heat pump. The data gathered during field-testing as well as the functionality of the system were studied extensively to develop and calibrate an hourly energy model. The model replicates the performance and operating modes of the solar-assisted air source heat pump. It allows for an hourly assessment of the energy savings, greenhouse gas reduction potential and cost competitiveness of this system as compared to other high performance HVAC systems in a variety of climate locations and archetype house loads. A parametric analysis is undertaken to assess the impact of key components on system viability. Results indicate that for some regions and archetype house loads, the dual-source solar-assisted heat pump can lead to significant energy savings and GHG emissions reductions when compared to high performing HVAC systems. These savings may enable a favorable payback period when a competitive capital cost is considered. The objective of the study was to identify locations and archetypes in which this solar-assisted heat pump topology may make sense for further development and demonstration.

Empirical model for estimation of global solar radiation at lowland region Biratnagar using satellite data

This study proposes to find the regression coefficient of the modified Angstrom type model for the estimation of global solar radiation (GSR) in lowland Biratnagar (Lat. 26.5º N, Long. 87.3º E and Alt. 72m) using relative sunshine duration and satellite data of GSR. Using the regression technique, the empirical constants 0.29 and 0.56 are found in the modified Angstrom model. Furthermore, Modified Angstrom model along with other linear models such as Glover and McCulloch model, Page model, Rietveld model, and Turton's model are statistically assessed to evaluate the significance of models. Statistical tests like MPE, MBE, RMSE, and CC reveal that all these models are statistically significant. These findings can be utilized for other locations with a high confidence level at the similar climatic locations of Nepal.
 BIBECHANA 18 (2021) 193-200

Assessment of UVB solar radiation in four different selected climate locations in Saudi Arabia

ABSTRACT In this paper, we used the data measurements of average hourly and monthly of UV solar radiation from 2003 to 2017 at four different selected locations in Saudi Arabia for optimisation and evaluation of UVB, UVBest., UVI and KtUVB solar radiation and total ozone column TOC (DU). The scattering phenomena on by stratospheric ozone is high extremely attenuation of UVB solar radiation. The predicted values of UVB solar radiation are a good agreement with the measurement of the UVB solar radiation. The accuracy between measured and predicted values of UVB solar radiation in selected locations in the present research varies from 1.27 to 3.87%. The maximum values of the total ozone column TOC are occur between March and April months at all selected locations with exception Taif site which occur between April and may months, and in whole the highest values of TOC occur about Spring time in all study locations.The relation between UVI and (SZA) at all selected locations in the present research is discussed. The monthly average has a correlation coefficient equal to 72%, 82%, 85% and 83% at Al-Baha, Abha, Jeddah and Taif sites, respectively, so the SZA is responsible for variations of UVI by 72%, 82%, 85% and 83% at Al-Baha, Abha, Jeddah and Taif locations for the monthly values respectively.

Statistical analysis of modified Hargreaves equation for precise estimation of reference evapotranspiration

There are a lot of meteorological stations around the world, like Pakistan, where all the meteorological parameters are not accessible to analyze Penman-Monteith (PM) method for the estimation of Reference Evapotranspiration (ETo ). So ablative methods such as Hargreaves Samani (HS) equation are therefore a potential solution to this problem, which required small numbers of meteorological parameters to estimate ETo . But, simplification brings imprecision and the need for regional calibration of the HS equation’s constant. In this study, fuzzy logic based calibration of the constants in the HS equation at the various climatic locations of Pakistan for the period of 1980 − 2019 is performed. The precision of HS and Modified HS (MHS) against standard PM method for the approximation of ETo was evaluated and compared the calibration process of HS equation by adjusting the coefficients of the equation gradually. The performance of the MHS is evaluated based on the statistical indicators such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Performance Index (PI). The statistical assessment of the study revealed that the MHS equation performed better as compared to the conventional HS equation and simultaneous adjustment of all the empirical parameters “ah”, “bh”,”ch” and “dh” was the best alternative for calibration of the HS equation. Furthermore, the change point detection analysis has been carried out on ETo (estimated by MHS) using Pettitt’s test, Buishand’s range test and Buishand’s U test. Results of the change point analysis indicated different change points from year 1980 to 2019, mainly due to the industrialization and urbanization during this time period.

Degradation Rate Location Dependency of Photovoltaic Systems

A main challenge towards ensuring improved lifetime performance and reduction of financial risks of photovoltaic (PV) technologies remains the accurate degradation quantification of field systems and the dependency of this performance loss rate to climatic conditions. The purpose of this study is to address these technological issues by presenting a unified methodology for accurately calculating the degradation rate (RD) of PV systems and provide evidence that degradation mechanisms are location dependent. The method followed included the application of data inference and time series analytics, in the scope of comparing the long-term RD of different crystalline Silicon (c-Si) PV systems, installed at different climatic locations. The application of data quality and filtering steps ensured data fidelity for the RD analysis. The yearly RD results demonstrated that the adopted time series analytical techniques converged after 7 years and were in close agreement to the degradation results obtained from indoor standardized procedures. Finally, the initial hypothesis that the RD is location dependent was verified, since the multicrystalline silicon (multi-c-Si) systems at the warm climatic region exhibited higher degradation compared to the respective systems at the moderate climate. For the investigated monocrystalline silicon (mono-c-Si) systems the location-dependency is also affected by the manufacturing technology.

Genome-wide association study in accessions of the mini-core collection of mungbean (Vigna radiata) from the World Vegetable Gene Bank (Taiwan)

BackgroundMungbean (Vigna radiata (L.) R. Wilczek, or green gram) is important tropical and sub-tropical legume and a rich source of dietary protein and micronutrients. In this study we employ GWAS to examine the genetic basis of variation in several important traits in mungbean, using the mini-core collection established by the World Vegetable Center, which includes 296 accessions that represent the major market classes. This collection has been grown in a common field plot in southern European part of Russia in 2018.ResultsWe used 5041 SNPs in 293 accessions that passed strict filtering for genetic diversity, linkage disequilibrium, population structure and GWAS analysis. Polymorphisms were distributed among all chromosomes, but with variable density. Linkage disequilibrium decayed in approximately 105 kb. Four distinct subgroups were identified within 293 accessions with 70% of accessions attributed to one of the four populations. By performing GWAS on the mini-core collection we have found several loci significantly associated with two important agronomical traits. Four SNPs associated with possibility of maturation in Kuban territory of Southern Russia in 2018 were identified within a region of strong linkage which contains genes encoding zinc finger A20 and an AN1 domain stress-associated protein.ConclusionsThe core collection of mungbean established by the World Vegetable Center is a valuable resource for mungbean breeding. The collection has been grown in southern European part of Russia in 2018 under incidental stresses caused by abnormally hot weather and different photoperiod. We have found several loci significantly associated with color of hypocotyl and possibility of maturation under these stressful conditions. SNPs associated with possibility of maturation localize to a region on chromosome 2 with strong linkage, in which genes encoding zinc finger A20 and AN1 domain stress associated protein (SAP) are located. Phenotyping of WorldVeg collection for maturation traits in temperate climatic locations is important as phenology remains a critical breeding target for mungbean. As demand rises for mungbean, production in temperate regions with shorter growing seasons becomes crucial to keep up with needs. Uncovering SNPs for phenology traits will speed breeding efforts.

A systematic approach in constructing typical meteorological year weather files using machine learning

A typical meteorological year weather file, supposedly representing the climatic conditions, is commonly used as an input for building energy simulation to predict the long-term performance of the buildings. Depending on the building type and climatic locations, the deviation between the actual long-term average energy performance and the predicted one may not be insignificant. Weather files are synthetically constructed on historical weather data over a long period of time for an array of weather parameters, such as solar radiation, temperature, wind speed and others. The statistical procedure to construct the weather files depends on the weights assigned to these weather parameters. Under current practice, these weighting factors are universally assigned regardless of climatic locations nor building applications based on experts’ judgment. The objective of this paper is to propose a novel approach in assigning weighting factors systematically, demonstrate its applicability, and quantify the potential reduction in deviation.Instead of basing on experts’ judgement, Random Forest algorithm was deployed to extract the feature importance of the weather parameters in order to assign weighting factors straightly proportional to their impacts on energy performance of buildings. To ensure the assigned weighting factorsfully reflect the climatic characteristics, five different training approaches were proposed, and the resulting climatic location dependent weather files were constructed and cross-validated.The newly constructed typical meteorological year weather files were applied to two different climatic locations to investigate the representativeness of these new weather files as compared to existing weather files and historical weather data of actual years. The representativeness was indicated in terms of the deviation in predicted energy performance of buildings between using the typical meteorological year weather file and actual historical weather data. The results indicated that typical meteorological year weather file based on the novel approach offers better prediction (with statistical significance) on energy performance for climatic locations with wider temperature range. As a result, the suggested approach avoids potential under/oversizing of equipment and promotes energy conservation.

Trace metal accumulation in the commercial mussel M. galloprovincialis under future climate change scenarios

The current trend of climatic alterations will accelerate the modification of the ocean system by, among other aspects, changing the metal speciation and its bioavailability which may have an impact in their accumulation by marine organisms. Understanding the impact of these potential changes is essential for future risk assessment of metal contamination. In the present study, we selected the species Mediterranean mussel (Mytilus galloprovincialis) as the main European aquaculture production bivalve and due to its widespread use for biomonitoring purposes. A long-term test (2 months) was carried out to explore the impact that global change in the marine environment (warming and CO2 increase) may exert on the accumulation of dissolved trace metals (Cu, Co, Pb, Cd, Cr, As and Ni) in different body parts of mussels (foot and rest of soft tissues).Studied mussels were collected at two different climatic locations (Atlantic and Mediterranean Sea) and exposed to unspiked, unpolluted seawater from the Vigo Ria (NW Iberian Peninsula). Results showed that under the global change conditions proposed in this study (1100 pCO2 and 25 °C), the increase in temperature resulted in a lower condition index and byssus strength for mussels from Atlantic Sea, while Mediterranean sea mussels, adapted to higher temperatures, did not show remarkable variations. According to trace metals accumulation in different body parts of the studied mussels, it was observed that the effect of increasing CO2 alone did not show to have an impact in the bioaccumulation, but the combined stressors (increase in CO2 and temperature) may lead to an increase in the bioaccumulation for some elements. The increase in temperature resulted in a decrease of the Cu content of foot tissue (byssus gland) in mussels from Atlantic Sea, which is in accordance with the lower byssus strength observed under such conditions. Our results indicate that the expected seawater temperature increase, which will be produced gradually during next decades, should be further study to ensure the species adaptability and aquaculture production.

Multi-Objective Sizing Optimization of a Grid-Connected Solar–Wind Hybrid System Using Climate Classification: A Case Study of Four Locations in Southern Taiwan

Increased concerns over global warming and air pollution has pushed governments to consider renewable energy as an alternative to meet the required energy demands of countries. Many government policies are deployed in Taiwan to promote solar and wind energy to cope with air pollution and self-dependency for energy generation. However, the residential sector contribution is not significant despite higher feed-in tariff rates set by government. This study analyzes wind and solar power availability of four different locations of southern Taiwan, based on the Köppen–Geiger climate classification system. The solar–wind hybrid system (SWHS) considered in this study consists of multi-crystalline photovoltaic (PV) modules, vertical wind turbines, inverters and batteries. Global reanalysis weather data and a climate-based electricity load profile at a 1-h resolution was used for the simulation. A general framework for multi-objective optimization using this simulation technique is proposed for solar–wind hybrid system, considering the feed-in tariff regulations, environmental regulations and installation area constraints of Taiwan. The hourly load profile is selected using a climate classification system. A decomposition-based differential evolutionary algorithm is used for finding the optimal Pareto set of two economic objectives and one environmental objective with maximum installation area and maximum PV capacity constraints. Two types of buildings are chosen for analysis at four climate locations. Analysis of Pareto sets revealed that the photovoltaic modules are economic options for a grid-connected mode at all four locations, whereas solar–wind hybrid systems are more environmentally friendly. A method of finding the fitness index for the Pareto front sets and a balanced strategy for choosing the optimal configuration is proposed. The proposed balanced strategy provides savings to users—up to 49% for urban residential buildings and up to 32% for rural residential buildings with respect to buildings without a hybrid energy system (HES)—while keeping carbon dioxide (CO2) emissions lower than 50% for the total project lifecycle time of 20 years. The case study reveals that for all four locations and two building types an HES system comprising a 15 kW photovoltaic system and a small capacity battery bank provides the optimal balance between economic and environmental objectives.

Multi-objective optimisation of a seasonal solar thermal energy storage system for space heating in cold climate

Seasonal solar thermal energy storage (SSTES) system is a promising technology to minimise greenhouse gas emissions (GHGE) by harnessing solar energy for space heating applications. The SSTES system in this study includes double U-tube borehole heat exchanger, ground-coupled heat pump and evacuated tube solar collectors. The aim of this investigation is to optimise the design variables of a SSTES system for space heating in cold climate locations. Six cold climate locations were studied namely: Lukla (Nepal), Dras (India), Sivas (Turkey), Harbin (China), Ulaanbaatar (Mongolia), and Verkhoyansk (Russia). The optimisation variables considered are the total solar collector area and total borehole length. There are three separate optimisation investigations: two single-objective and one multi-objective for the SSTES system. The first investigation is to minimise total life cycle greenhouse gas emissions and the second investigation is to minimise total life cycle cost included cost of GHGE. The third investigation is to minimise both life cycle cost of SSTES system and cost of GHGE (multi objectives). The simulation model was developed using TRNSYS 17 and the Multi-Objective Building Optimisation (MOBO) tool was applied for optimisations. The optimal set of design variables and the corresponding value of the objective function were determined for each single-objective optimisation investigation. Pareto front for each location was also identified for the multi-objective optimisation investigation. The technical and financial performance were also analysed and presented.

Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a unified methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More specifically, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (artificial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the final performance accuracy evaluation. The results showed that the application of linear regression coefficients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. The validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.

Simulated performance of a borehole-coupled heat pump seasonal solar thermal storage system for space heating in cold climate

The performance of a seasonal solar thermal energy storage system for space heating in cold climates was investigated. The system includes a double U-tube vertical borehole thermal energy storage integrated with a ground coupled heat pump and evacuated tube solar collectors. A validated TRNSYS model for six cold climate locations: Lukla, Dras, Sivas, Harbin, Ulaanbaatar and Verkhoyansk was applied. The hourly typical metrological year (TMY) data of each location was used. The house model for each location was based on the typical local dwelling. The annual heating loads per unit floor area (GJ m−2) was found in the range of 0.71–2.59 (1.71, 1.79, 0.71, 1.19, 1.45 and 2.59 for Lukla, Dras, Sivas, Harbin, Ulaanbaatar and Verkhoyansk respectively). The sizes of the system components such as solar collector area, borehole length, number of borehole and heat pump capacity were determined for each location. The analysis covered both heat charging and discharging. It was found that the average ground temperatures were stable in each location with solar charging. However, if the system was not charged by solar energy, the average ground temperatures were decreased over the years. The seasonal compressor heating coefficient of performance coefficient of performance were found to be more than 5.8, that shows the potential benefit of the system. The proposed system could fulfil more than 93% of the space heating demand in all selected locations. The results of the study reveal the potential benefits of utilising seasonal solar thermal energy storage system in cold climate locations.

Energetic and Exergetic Performance of Solar-Assisted Direct Expansion Air-Conditioning System with Low-GWP Refrigerants in Different Climate Locations

This study aims to assess an air-conditioning cycle designed to make use of hydrofluoroolefins (HFOs) within a direct expansion air-conditioning system combined with a solar energy source. An energy–exergy analysis was applied in order (i) to examine which HFO working fluid is more efficient and (ii) to draw a comparative analysis between the proposed cycle and the conventional air-conditioning cycle. To achieve this, a simulation has been devised to determine the coefficient of performance (COP), exergetic efficiency, and total irreversibility for three HFOs. These HFO fluids are R1234yf, R1234ze(E), and R1233zd(E) which were compared to R410A and R134a. System operating conditions, such as the impact of storage tank exit temperatures on compressor discharge temperatures and condenser surface augmentation, were also taken into consideration and are being investigated. Results of the study indicated that the use of evacuated tube solar collector within a vapor compression air-conditioning system can improve performance by 15–56% and save 5–40% in electrical energy consumption. The study also concludes that HFOs are excellent alternatives for R410A and R134a. Accordingly, the total irreversibility of the proposed cycle with R1234yf, R1234ze(E) and R1233zd(E) is less than that of R410A and R134a.

Development of transportation types and their usage on caravan roads in middle ages

During the existence of the Bukhara khanate, the economic and trade relations with neighboring countries on the territory of Central Asia have been largely based on transport system of the old network of roads. Along with the formation and development of communication routes, transportation vehicles also improved based on the natural climate and geographical location of different regions. In the following article the info is given on the means of the transport used in the caravan routes in the trade-economic relations of khanate of Bukhara with neighboring countries in medieval times. Included there, the starting of domestication and usage of horse drawn vehicles, camels, donkeys and others, the capacity of daily load of camels, horses, donkeys which were core of caravans, their daily distance, the necessary tasks in the incidents occurred in caravan routes (injuries, bruises, contagious diseases) the stopping regulation of caravans (sand storm, in heat and frost) is thoroughly analyzed.

Influence of tooth wear on the state of public health and its prevention (literature review)

This article deals with the issues related to the dental pathology, tooth wear or dental attrition, and spread of this pathology in the southern regions of the Kyrgyz Republic. Literary review, in which analysis of theoretical material on the pathology of dental attrition in upper and lower jaws depending on various factors, climatic and geographical location, was made in order to study experience on this issue in world practice. Main works of domestic and foreign scientists concerning tooth wear pathology have been reviewed for this purpose. Analysis of studies is made and experience in the field of dental attrition is investigated to find ways for prevention. In order to study this problem and spread of this pathology in the region fully, main factors and methods of eliminating causes of this pathology are taken into consideration. Clinical examinations were studied and the results were analyzed to take into account etiologic factors of tooth wear. Distribution of this pathology in the regions was analyzed. Issues of prevention and role of promoting healthy lifestyle and culture of healthy life among the population are considered. Conclusions on the influence of this pathology on health of population are drawn.

Impact of location and deadband on energy performance of nano aerogel glazing for office building in Saudi Arabia

ABSTRACT The present study has focused on the impact of location and deadband (range of thermostat setpoints for cooling and heating) on the energy performance and economics of nano granular silica aerogel (nanogel) glazing in a multi-storey office building, by considering 26 climatic locations of Saudi Arabia. The selected cities were classified according to the cooling degree days (CDD) and outdoor dry bulb temperature (DBT), as warm, moderately hot, hot, and very hot, and the results were generalized with respect to these climatic zones. The building model was built in Autodesk Revit (2015), and the energy simulation was performed by Ecotect (2011) in two cases: (i) insulated wall and roof, and DG window and (ii) insulated wall and roof, and nanogel glazing. The results show that the location and deadband have crucial impact on the energy performance and economic viability of nanogel glazing. The energy-saving potential and payback period of replacing DG window by nanogel glazing are attractive for cities with higher DBTs and CDD, compared to those with lower DBT and CDD. For all the climatic zones studied, the benefit of replacing DG window by nanogel glazing could be achieved for a specific deadband of 20–24°C.

Net-zero energy building design and life-cycle cost analysis with air-source variable refrigerant flow and distributed photovoltaic systems

Net-zero energy building (NZEB) design has been gaining widespread acceptance as a major driver to reach feasible long-term goals of energy reductions in a building sector for the coming decades. Accordingly, net-zero energy targets for commercial buildings have been specified by federal and/or local government agencies in U.S. Although moving toward NZEB goals has technically feasible long-term advantages, economic issues are one of primarily concerns by building owners and designers for the application of advanced building technologies in NZEB design of their retrofit or new building construction. However, the lack of life cycle cost (LCC) data has still hindered reliable understanding of adopting NZEB design by building owners in a cost-effective manner. In response to this gap, this study conducts life-cycle cost analysis (LCCA) of NZEB design with an energy-efficient heating, ventilation, and air conditioning (HVAC) system and a solar power generation system. To enable NZEB design, an air-source VRF heat pump (HP) type system is considered for energy-efficient HVAC equipment in an office building model with a grid-tied photovoltaic (PV) system. Results reveal that the LCC of NZEBs varies primarily due to a combined effect of annual site EUIs, on-site power generation, and cost-items of each location in U.S. climates. Some hot and mild climate zones in the U.S. represent that LCC values of NZEBs are considerably lower. In contrast, some other cold zones result in unattractive LCC values for NZEBs, caused by a combined effect of relatively lower potential of on-site PV electricity generation and city cost indices. Yet, with subsidized financing by the federal government for PV installation costs, LCC values of NZEBs become significantly attractive in most climate locations.