Different Climate Zones Of Iran Research Articles

Assessing the changeability of precipitation patterns using multiple remote sensing data and an efficient uncertainty method over different climate regions of Iran

While the rain gauge measurements are unevenly distributed in many world regions, it is necessary to use remote sensing-based precipitation data at high spatial and temporal resolutions. On the other hand, quantifying the uncertainty of precipitation is a vital issue for hydrometeorological applications globally. For this purpose, applying a new fusion framework using high-resolution remote sensing datasets can provide accurate precipitation evaluation against local observations with low uncertainty. This study examines three weighted fusion-based models containing the Ordered-Weighted-Averaged (OWA) family approach based on the ORLIKE method (OWA-ORLIKE) and ORNESS method (OWA-ORNESS) as well as the Entropy-weight (EW) method to combine different remote sensing precipitation products over different climate zones of Iran. In this case, multiple monthly remotely sensed datasets, including ERA5, ERA5-Land, TerraClimate, GPM, PERSIANN-CDR, TRMM, and CHIRPS, are utilized to assess precipitation patterns versus local measurements, which were gathered by Google Earth Engine (GEE) platform. Furthermore, the K-means algorithm is employed to cluster ground-based precipitation stations based on the climate zones category across Iran. Additionally, the Genetic Optimization Algorithm (GOA) is applied to specify optimal values of weights in weighting-based models. The performance of single and combination datasets are evaluated using statistical error metrics, including Pearson correlation coefficient (PCC), root mean square error (RMSE), Kling Gupta efficiency (KGE), and bias. The Thiessen polygon method has been applied to calculate each cluster's mean precipitation to obtain the optimal weights of stations. Finally, as an efficient uncertainty approach, Cross Wavelet Transform (XWT) method has been used for uncertainty assessment of monthly and seasonal precipitation series. Results indicated that the OWA family as the best fusion model had almost the lowest uncertainty values and best statistical error indices compared to the EW model and all single products in different clusters of Iran. As a motivation part of this study, unlike the single sources of remotely sensed data, multiple datasets can apply together in different climate conditions with various features using combination models, which mentioned uncertainty method has clearly revealed this claim.

Detecting drought events over Iran during 1983–2017 using satellite and ground-based precipitation observations

Timely and accurate detection of drought events using reliable data with continuous spatial coverage is of great importance to adapt efficient mitigation strategies. Despite several studies that have been carried out to validate satellite precipitation products in Iran, the performance of satellite precipitation products in precipitation amount estimation and drought events detection has not been assessed yet simultaneously. It is unclear if good estimates of mean precipitation values by satellites can also provide good performance in detecting drought events. Here, we used a comprehensive framework to evaluate the accuracy of the satellite-based precipitation and their performance in detecting drought events against ground-based data. We evaluated three satellite precipitation products, namely, TRMM TMPA 3B43 v7, CHIRPS, and PERSIANN-CDR using multiple evaluation metrics, and three different drought indices (Standardized Precipitation Index-SPI, Standardized Precipitation Evapotranspiration Index-SPEI, and Multivariate Standardized Precipitation Index-MSPI) over different climate zones of Iran during 1983–2017. Our results indicated that TRMM and PERSIANN-CDR had mainly overestimation while CHIRPS had mostly underestimation in precipitation over the different climates of Iran. The precipitation overestimation (underestimation) in TRMM, PERSIANN-CDR, and CHIRPS were observed in 80.0% (20.0%), 71.4% (28.6%), and 45.7% (54.3%) of stations, respectively. The most overestimation in satellite products was found to be in the arid-related climate regions, while the most underestimation was detected in humid-related climate regions. The average correlation coefficient values of PERSIANN-CDR (0.6) and TRMM (0.6) products against ground observations were higher than CHIRPS (0.4) dataset. Further, we found a lower correlation coefficient (0.3) between monthly satellite-based and ground-based precipitation in arid-related regions (with Root Mean Square Error, RMSE, ~ 10 mm per month) of the country but a high correlation coefficient (0.6) in humid-related climates (with RMSE ~100 mm per month). The results of the drought assessment indicated that the most severe meteorological drought events identified by SPI, SPEI, and MSPI were in 1998–2001, 2008–2009, 2010–2012, and 2016–2017 in all climate zones. The most intense drought events were in arid and semi-arid climate zones. Overall, in terms of the statistical metrics at multiple timescales, TRMM and PERSIANN-CDR outperformed CHIRPS, when compared against ground-based observations, for drought events detection. Also, TRMM and PERSIANN-CDR with higher scores for Probability of Detection (POD) and Critical Success Index (CSI) and lower scores for False Alarm Ratio (FAR) showed a good ability to detect drought events in arid and semi-arid climates compared to other climate zones. Although the CHIRPS estimated precipitation with acceptable accuracy, it did not detect drought events as the TRMM and PERSIANN-CDR did.

Large-scale climate variability footprint in water levels of alluvial aquifers across Iran

The ability to predict the future variability of groundwater resources in time and space is of critical importance in society’s adaptation to climate variability and change. Periodic control of large-scale ocean-atmospheric circulations on groundwater levels serves as a potentially effective source for relatively long-term forecasting. In this study, as a first national-scale assessment, we use the continuous wavelet transform, global power spectrum, and wavelet coherence analyses to quantify the linkage between the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (ENSO) and the representative groundwater levels of the 24 principal aquifers, scattered across 14 different climate zones of Iran. Aquifer storage variations are found to be partially derived from annual to interdecadal climate variability and not solely a function of pumping variability. Moreover, teleconnections are observed to be both frequency and time-specific. The significant coherence patterns between the climate indices and groundwater levels are concentrated at five frequency bands of the annual (~ 1 year), short-interannual (2–4 years), medium-interannual (4–6 years), decadal (8–12 years), and interdecadal (14–18 years), consistent with the dominant oscillations of climate indices. AMO’s strong linkage to groundwater variability is found to be at interdecadal and annual modes of groundwater levels while PDO’s highest imprint is concentrated in interannual, decadal, and interdecadal periodicities. Unlike ENSO for which the highest modulating influence is found to be across the decadal and interannual modes, the NAO’s footprint in aquifers is marked at annual and interdecadal frequency bands. Findings further show that the groundwater variability is driven primarily by a combination of multiple large-scale atmospheric circulations rather than a single atmospheric circulation index. The decadal and interdecadal oscillation modes are the dominant modes in Iranian aquifers. Findings also mark the unsaturated zone contribution in damping and lagging of the climate variability modes, particularly for the higher-frequency indices of ENSO and NAO so that groundwater variability is more correlated with those climate circulations that have lower frequency such as PDO and AMO. Finally, the data length is found to have a significant effect on the teleconnections if the time series are not contemporaneous and for each particular series, only one value of coherence/correlation is computed instead of separate computations for different frequency bands and different time spans.

Evaluation of ALARO-0 and REMO Regional Climate Models over Iran Focusing on Building Material Degradation Criteria

Understanding how climate change affects material degradation is the first step in heritage conservation. To study such impact, high-resolution climate information is required. However, so far, no regional climate simulations have been evaluated considering building damage criteria over the region of Iran. This paper has a twofold objective: to conduct an overview of climate model performance over Iran by evaluating the output of two regional climate models, ALARO-0 and REMO2015, and to find an optimal approach for model evaluation fitted to studies on building physics. Data of the evaluation run for both models were compared with data of weather stations located in six different climate zones in Iran to assess their performance over the region and gain insight about model uncertainties. Given that the research scope covers the evaluation of climate models to use in studies on building physics, in addition to climate parameters, five degradation risks are analysed. The performance of the two models varies over the studied locations. In general, both models fall within the spread of observations except for wind parameters. Accordingly, indices related to temperature and precipitation are well predicted, in contrast to indices related to wind. The analysis shows that considering the observed biases, selecting an ensemble of representative models based on the evaluation results of climate variables important for hygrothermal simulations would be recommended.

An integrated dynamic model for evaluating the influence of ground to air heat transfer system on heating, cooling and CO2 supply in Greenhouses: Considering crop transpiration

Nowadays, one of the most important challenges in developing greenhouses is meeting their energy demand. The other challenge is the high water consumption of evaporative-cooling systems in arid and semi-arid regions. In this study, a integrated dynamic model is developed to determine the greenhouse relative humidity, carbon dioxide, and temperature, considering transpiration. The model is applied to a greenhouse utilizing a ground to air heat transfer system, located in the Alborz province of Iran and the results are validated with experimental data. Energy and water performance of the greenhouse are evaluated for the case study greenhouse. Then, the model is applied to a greenhouse (similar to the case study) in different climate zones of Iran to study the impact of climatic conditions on greenhouse performance. The results are presented for both cases of presence and absence of plant in greenhouses. Transpiration causes the heating/cooling demand of the greenhouse to increases/decreases by 17–40%/63–71% from climate 1 (cold and dry-humid climatic conditions) to climate 4 (mild and hot-humid climate regions). The water consumption of the evaporative-cooling system decreases by 17–49% from climate 1 to 4 when transpiration is taken into consideration.

The relationship between dysentery and climatic parameters in Iran

Climate plays a key role in gastrointestinal diseases by affecting the environmental conditions of disease-transmitting agents through contributing to the quality of water and access to water resources. Moreover, the association between dysentery and climatic factors in Iran as a vulnerable country to climate change has not been clarified yet. The present retrospective cohort study was therefore conducted to investigate the relationship between climatic factors and dysentery in different climate zones of Iran and diverse age groups of men and women using secondary data. The longitudinal data were analyzed using tests of Poisson regression models. The present findings suggested that the average monthly maximum temperature and the number of rainy days are the most significantly correlated with the risk of dysentery in both genders; for instance, increases were observed in the risk of dysentery in women (IRR = 1.35, 95% CI:1.15,1.59, P < 0.001) and men (IRR = 1.18, 95% CI:1.00–1.40, P = 0.042) in the arid-cold climate (Bwk) with an increase in rainfall, and in Women (IRR = 1.07, 95% CI: 1.05,1.08, P < 0.001) and men (IRR = 1.05, 95% CI:1.04,1.06, P < 0.001) in the semi-arid cold climate (Bsk) with an increase in the average monthly maximum temperature. Significant correlations were also observed between climate and dysentery in the children and adults aged over 65 years. The results suggest that dysentery is associated with different factors in women and men of different ages. Climatic factors were also found to differently affect the risk of dysentery in different climate zones.

Investigation of single-storey residential green roof contribution to buildings energy demand reduction in different climate zones of Iran

ABSTRACT The share of the building sector accounts for one-third of the total energy consumption in the final energy demand in the world, and they are, indeed, paramount factors for CO2 emissions. Energy consumption in developing countries piles up to 40%, while this is higher in Iran, and for this reason, energy saving in this sector plays a prominent role. This paper aims to study the effects of using green roofs (GR) on energy consumption and CO2 emission rate of a sample building in various climate, calls, dry hot, cold, and humid hot, which can correctly represent different climates of Iran. Simulations are done for the entire year using DesignBuilder, which is a popular tool in this regard. Besides, the building construction materials considered in the simulation are the most utilized in Iran, and 15 cm height grass is selected to be used in the roof. Results indicate 6.19%, 2.07%, and 9.45% energy consumption reduction and 238, 100, and 370 kg of emission reduction for Tehran, Tabriz, and Bandar Abbas, respectively. In addition, an economic analysis is conducted to explore the economic viability of green roof implementation. It has been concluded that, according to the tariffs for water and electricity in Iran, the application of green roofs is not economically viable in current economic conditions.

Thermodynamic analysis of a CCHP system for a building using solar collectors and PV panels in two different climate zones in Iran

ABSTRACTIn this paper, a thermodynamic study of a combined cooling, heating, and power system using a combination of solar collectors and photovoltaic panels was presented for a specific building, for two different climates, i.e., Tabriz and Zahedan, Iran. In order to perform the simulations, the Transient System Simulation Tool software was applied for modeling and verifying the simulations. For this reason, an office building measuring 112.7 m2 was evaluated using the Hourly Analysis Program 4.9 software, to calculate the building’s heating and cooling loads during the crucial days of a year. Subsequently, in order to satisfy the heating and cooling demands, a cogeneration system was modeled, and its results were presented for the crucial days of a year as well as for solar fraction. The total cooling energy generated for Tabriz and Zahedan was obtained 188 and 198 kWh, respectively. These amounts of heating energy were 209 and 111 kWh. Moreover, a parametric study was applied to clarify the effect of various parameters on the system’s performance, such as the collector’s area, set point temperature of the auxiliary heater, capacity of storage tanks and the circulating fluid’s flowrate regarding the apparatus performance. Based on the results of this parameter study and the selection of appropriate values for the system parameters, the solar fraction was calculated, and the results indicated the system improvement is of 25.36% in Tabriz and 23.77% in Zahedan. Furthermore, in order to meet the electrical demand of the building in these two cities 12 and 10 solar panels were required by considering the annual and daily demand analyses and the amount of generated power during the range of consumption were 2007.659 and 2179.517 kWh for Tabriz and Zahedan, respectively.

The influence of building material, windows and insulators on energy saving in different climate zones in Iran

One of the most influential factors in measuring the annual energy consumption and dissipation of buildings is heat transfer that occurs between indoor and outdoor of the building areas. In this research, we use The DesignBuilder software to estimate the monthly annual rate of energy consumption to supply the building’s cooling and heating with respect to the type of used walls. This study estimates the load in different walls to compare the effect of the type of walls in terms of heat transfer in buildings in different cities of Iran, namely Tehran, Tabriz, Bandar Abbas, and Mashhad. In addition, the effect of using different insulators and windows on annual energy consumption is calculated. Results demonstrate that the polyurethane metal is the optimum insulator as it reduces the annual energy consumption the most in Tabriz and Mashhad by 11% and 10% and quite less in Bandar Abbas by 7.8%, while the annual energy consumption using expanded polystyrene is the least in all cities. In addition, the results show that the least energy consumption for the four climates is related to wall type 1 (insulated concrete block with brick facade) and the most energy consumption to wall type 7 (normal brick with stone facade). The most significant effect of using double-walled windows is with UPVC Profiles compared to the use of single-walled ones in Mashhad and Tabriz with 26% reduction in the window’s loads, while the least significant is Bandar Abbas and Tehran with 21%.

Optimal insulation thickness of common classic and modern exterior walls in different climate zones of Iran

Insulation thickness optimization has become a prominent factor in building design for energy saving. This study aims to determine ideal insulation thickness of the external wall, energy saving, and payback period of investment in all climate zones of Iran. A classic gray brick wall and three modern walls (Hollow clay block, LECA block, and AAC block) were selected by considering four cardinal orientations. Eight cities were chosen as representatives of all climate zones. Optimization was performed using life-cycle cost analysis method along with a numerical solution to determine the transmission load. Results revealed that the use of thermal insulation in the AAC block wall, which is one of the common modern walls in Iran, is not economical in some cities. The maximum insulation thickness in Iran is not more than 4 cm which is much lower than the reported values for other countries. Also, the figures for energy saving and payback period in Iran are very different. This is due to the economic structure and low energy costs in this country. This study confirms the requirements in reforming regional energy policy and pricing mechanisms as a roadmap for insulation application in building envelope.

In-vitro antifungal susceptibility testing of lanoconazole and luliconazole against Aspergillus flavus as an important agent of invasive aspergillosis

The incidence of Aspergillus infections has recently increased remarkably in certain tropical and sub-tropical countries, with Aspergillus flavus being identified as the leading cause of infections after A.fumigatus. Lanoconazole (LAN) and luliconazole (LUL) are currently approved for topical treatment of cutaneous fungal infections. We aimed the in-vitro antifungal susceptibility testing of two imidazole, LANand LUL against A. flavus. One hundred and eighty-seven clinical and environmental A.flavus were tested originating from different climate zones of Iran between 2008 and 2015. The identification of all isolates was confirmed by using PCR-sequencing of β-tubuline ribosomal DNA gene. In-vitro antifungal susceptibility test was performed using CLSI guidelines against LAN, LUL, itraconazole (ITC), voriconazole (VRC), posaconazole (POS), Isavuconazole (ISA), amphotericin B (AMB), 5-flucytosine (5FC), caspofungin (CAS) and anidulafungin (AFG). The minimum inhibitory concentration (MIC) and minimum effect concentration (MEC) values were evaluated according to CLSI M38-A2 guidelines. The geometric mean MICs for tested antifungals, in increasing order, were: 0.009μg/mL for LUL (ranging from 0.004 to 0.062), 0.02μg/mL for LAN (ranging from 0.004 to 0.125), POS (0.10), ISA (0.16), ITC (0.24), VRC (0.27), AMB (1.8) and 5FC (63.06) μg/mL. The mean value of MECs for AFG and CAS were 0.06 and 0.07, respectively. Overall, LUL and LAN showed the lowest MIC against all isolates of A.flavus. Further studies are required to evaluate the in-vivo efficacy of these agents, and the possibility of using these agents in systemic infections.

Comparison of artificial intelligence methods in estimation of daily global solar radiation

Abstract Assessment of solar potential over a location of interest is introduced as an important step for the successful planning of solar energy systems (photovoltaic or thermal). Due to the absence of meteorological stations and sophisticated solar sensors, solar data may be unavailable for every point of interest. Hence, empirical and intelligence methods are developed to estimate solar irradiance data. In this study, the idea of artificial intelligence methods is employed to predict the daily global solar radiation. The developed models are: group method of data handling (GMDH) type neural network, multilayer feed-forward neural network (MLFFNN), adaptive neuro-fuzzy inference system (ANFIS), ANFIS optimized with particle swarm optimization algorithm (ANFIS-PSO), ANFIS optimized with genetic algorithm (ANFIS-GA) and ANFIS optimized with ant colony (ANFIS-ACO). The data are collected from 12 stations in different climate zones of Iran. The input variables of the models are including month, day, average air temperature, maximum air temperature, minimum air temperature, air pressure, relative humidity, wind speed, top of atmosphere insolation, latitude and longitude. The results demonstrated that although the developed models can successfully predict the global horizontal irradiance, the GMDH model outperforms the other developed models. The values of root mean square error (RMSE), determination coefficient (R2) and mean square error (MSE) for the GMDH model were 0.2466 (kWh/m2/day), 0.9886 and 0.0608 (kWh/m2/day), respectively.

Design Optimization of a Small-Scale Polygeneration Energy System in Different Climate Zones in Iran

Design and performance of polygeneration energy systems are highly influenced by several variables, including the climate zone, which can affect the load profile as well as the availability of renewable energy sources. To investigate the effects, in this study, the design of a polygeneration system for identical residential buildings that are located in three different climate zones in Iran has been investigated. To perform the study, a model has previously developed by the author is used. The performance of the polygeneration system in terms of energy, economy and environment were compared to each other. The results show significant energetic and environmental benefits of the implementation of polygeneration systems in Iran, especially in the building that is located in a hot climate, with a high cooling demand and a low heating demand. Optimal polygeneration system for an identical building has achieved a 27% carbon dioxide emission reduction in the cold climate, while this value is around 41% in the hot climate. However, when considering the price of electricity and gas in the current energy market in Iran, none of the systems are feasible and financial support mechanisms or other incentives are required to promote the application of decentralized polygeneration energy systems.

Multi-objective optimization-simulation model to improve the buildings’ design specification in different climate zones of Iran

The building sector is responsible for approximately 40% of the total annual worldwide consumption of energy. In Iran, subsidy policies of energy supply have caused it to be more than 2.5 times of the global consumption. As a result, buildings’ energy efficiency improvement must be considered important for Iranian designers and researchers. However, this issue has not received due attention yet. Thus, the present study aims to shed new light on the buildings’ energy efficiency planning in Iran by adopting a multi-objective optimization-simulation model in order to provide a set of optimum possible solutions for improving the energy efficiency measures of buildings located in different climate zones of the country. The proposed model aims at determination of envelope materials, and types of active/passive cooling/heating systems to optimize the economic and environmental performance of the overall system. The model is applied to a building categorized as type-one according to the building occupancy typologies of national building regulations in Iran. Simulations are performed by BCS19 software in order to evaluate the quality of the Pareto optimal alternatives. Therefore, amendment of routines in designing buildings according to different climate conditions is proposed.

Sequence analysis of mtDNA COI barcode region revealed three haplotypes within Culex pipiens assemblage

Members of the Culex (Culex) pipiens assemblage are known vectors of deadly encephalitides, periodic filariasis, and West Nile virus throughout the world. However, members of this assemblage are morphologically indistinguishable or hard to distinguish and play distinct roles in transmission of the diseases. The current study aimed to provide further evidence on utility of the two most popular nuclear (ITS2–rDNA) and mitochondrial (COI barcode region) genetic markers to identify members of the assemblage. Culex pipiens assemblage specimens from different climate zones of Iran were collected and identified to species level based on morphological characteristics. Nucleotide sequences of the loci for the specimens plus available data in the GenBank were analyzed to find species specific genetic structures useful for diagnosis purposes. ITS2 region was highly divergent within species or populations suggesting lack of consistency as a reliable molecular marker. In contrast, sequence analysis of 710 bp of COI gene revealed three fixed haplotypes named here “C, T, H” within the assemblage which can be distinguished by HaeIII and AluI enzymes. There were a correlation between the haplotypes and the world climate regions, where the haplotypes H/T and C are present mainly in temperate and tropical regions of the world, respectively. In the New world, Australia, and Japan only haplotype H is found. In conjunction between tropical and temperate regions such Iran, China, and Turkey, a mix of C/H or C/H/T are present. Although, the haplotypes are not strictly species-specific, however, Cx. quinquefasciatus was mainly of haplotype C. Due to the lack of mating barrier and questionable taxonomic situation of the complex members, the mentioned haplotypes in combination with other morphological and molecular characters might be used to address the genetic structure of the studied populations.

Applicability of Radiant Heating-Cooling Ceiling Panels in Residential Buildings in Different Climates of Iran

This paper assess the feasibility of using heating-cooling radiant panel in residential buildings in five different climate zones in Iran. This study leverages simulation modeling to evaluate the thermal performance of heating-cooling radiant panels. By defining new indices, applicability limiting factors of the radiant panels, i.e. condensation risk in cooling, and asymmetric radiation discomfort in heating are evaluated and compared in different climatic conditions. The system capacity and setpoints are calculated based on thermal comfort conditions, using PMV index in heating (PMV= -0.5) and cooling (PMV= +0.5) modes. Results of this study indicate that for dryer regions with less risk of condensation the radiant system can help home owners to save around 11.3% on their heating energy and 9.1% on cooling energy use.

Effects of the height and geographical aspects on potential of soil carbon sequestration in Kermanshah, Iran

Main phenomenon of climate change that is harmful for human being, increased concentration of carbon dioxide in the atmosphere. Regarding to the potential of carbon storage in soil and plant tissues, this approach has a serious interest in recent decades. Due to the different climate zones in IRAN, share and amount of carbon sequestration in any of these areas need more contemplation. Therefore, the ability of soil carbon sequestration of mountain pastures in Kermanshah Province was studied in 3 height and 4 geographical aspects. Then, soil samples were taken from the areas that Astragalus Gossypinus and Astragalus Parrowianus grew at two depths of 0-30cm and 30-60cm. The amount of organic carbon, bulk density, electrical conductivity, pH, moisture content and soil texture in both depths of each soil profile were measured. Stepwise regression results also showed that texture parameters, bulk density and pH, respectively, were the most important factors affecting on soil organic carbon. Based on the results of data analysis using a completely randomized factorial design, significant differences were observed at 1% significance level between the two species and also in height between the classes and geographical aspect on soil carbon sequestration rates.Comparison of results based on SNK tests also indicates that, biggest amount of carbon sequestration taking place in the maximum height in the geographic north aspect. Also according to the results can be stated that capability of Soil Carbon Sequestration in Astragalus Parrowianus is more than Astragalus Gossypinus.

Technical and economic feasibility study of using Micro CHP in the different climate zones of Iran

The growing worldwide demand for less polluting shapes of energy have led to a renewed interest in the use of Micro Combined Heat and Power (Micro CHP) technologies in the residential sector. Micro CHP have been introduced around Iran recently, and expected to diffuse more and more. In this paper, technical and economic studies for the use of Micro CHP in the different climate zones of Iran are executed. These zones are categorized in to five; Tehran, Rasht, Bandar Abbas, Ardebil and Yazd, based on weather conditions. Later on using an economic model, both annual energy savings and percentage of system profitability in each zone are calculated as well as reduction in annual emissions. It should be mentioned that, for economic calculations, gas and electricity price are determined using a sensitivity analysis. This analysis indicated that profitability of Micro CHP systems are sensitive to energy prices, as well as hours needed for heating room in each climate zones. The analysis results show that Ardebil with 38 million RLS (with electricity buyback) annual energy saving is recognized as the best option for installing Micro CHP. On the other hand, Bandar Abbas with 2.5 million RLS annual energy saving is not suitable.

Experimental investigation of dehumidification process in cooling coil by utilizing air-to-air heat exchanger in humid climate of Iran

Energy recovery systems can be used in HVAC to reduce energy consumption by recovering wasted energy from the exhausted air to pre-cool inlet fresh air. In this paper, experimental study of utilizing cooling coil (CC) and cooling coil combined with heat exchanger (CCHE) has been developed. Considering the different climate zones in Iran, the experimental study has been done for the areas with high humidity content. In each case, the effects of air-to-air heat exchanger (HE) on the sensible and latent cooling load are investigated. The analysis gives the applicability of HE in Iran for various operational conditions to obtain air with lower moisture content. In CCHE systems more latent load quota is allocated in cooling coils and lower air humidity ratio can be obtained. Also in the cities with higher dew point depression (difference between dry-bulb and dew point temperature) more humidity reduction is achieved and the difference between latent load quotas of CCHE system is higher than CC system.