Climate Of Iran Research Articles

Strategic analysis of Iran's climate resilient health system.

Climate change is a long-term systematic climate variability caused by human activities that alters the composition of the global atmosphere. Health systems should be adaptive and resilient to climate change. Hence, this research aimed to strategically analyze the resilience of Iran's health system to climate change. This study utilized a multiple methods approach. First, in-depth semi-structured interviews were conducted with 32 key climate change and health experts to identify the strengths, weaknesses, opportunities and threats of the Iranian health system's resilience to climate change. Purposeful and snowball sampling techniques were used to ensure maximum diversity among the participants. Then, a questionnaire was developed based on the findings of the first stage and was completed by 33 climate change and health experts. Finally, the strategic position of Iran's health system's resilience to climate change was determined using the internal - external factors matrix. A total of 84 internal factors and 101 external factors were identified that affect the resilience of Iran's health system against climate change. The internal factors were categorized into seven dimensions (i.e., governance and leadership; health financing; health workforce; facilities, equipment and medicines; health information system; health services delivery, and key results). The external factors were categorized into six dimensions (i.e., political, economic, social, technological, environmental, and legal factors). The average score of internal and external factors were 2.47 and 2.12, out of 4 respectively. Iran's health system was found to be in the strategic position of V in terms of resilience to climate change. Therefore, precautionary strategies such as strengthening the climate resilience of healthcare facilities, promoting healthcare facilities' adaptation to climate change, public-private partnership, strengthening the health service delivery system, quality management and cost management, should be implemented to strengthen the resilience of Iran's health system to climate change. Iran's health system is facing significant weaknesses and challenges that have hindered its resilience to climate change. Iran's health system can better prepare and respond to the health impacts of climate change, and safeguarding the health and well-being of its population by addressing these challenges and implementing adaptive and resilience strategies.

Revisiting Iran's climate classification: A fresh perspective utilizing the köppen-geiger method

Revisiting Iran's climate classification: A fresh perspective utilizing the köppen-geiger method

A newly developed model for estimating snow depth in ungauged areas

The presence of snow significantly affects the hydrological cycle and soil moisture globally. Nowadays, with the expansion of science, different satellites can measure snow depth all over the world. By establishing a conditional relationship between mean temperature and the Proportion of Snowfall to Total Precipitation (PSTP), this study proposes a method for snow depth estimation for ungauged stations. The case study of this research is Iran. Most of Iran's climate is arid due to its location in the Middle East, making it one of the countries with the lowest rainfall worldwide. On the other hand, this country enormously depends on water resources. Consequently, an accurate and valid estimate of snow amounts in Iran is essential. To reach this goal, we analyzed daily data from 12 synoptic and climatological stations between 1970 and 2020, including rainfall, snow depth, and mean temperature. For each station, the PSTP at 0.5 °C air temperature intervals was determined and fitted to a double sigmoid model that allows snow depth estimation. The evaluation of the snow depth approximated by the double sigmoid model was done using R2, RRMSE, EF, and Bias statistics against the observational data. R2 values in the Era-5 dataset in all stations are lower than 0.5. Additionally, it should be noted that in certain stations, the bias values surpass 20 mm. Furthermore, in 75 percent of the stations, the RRMSE values exceed 0.6. By utilizing the DSBE model, it is possible to achieve a reduction of 122.4 and 0.7 in Bias and RRMSE values, respectively. The R2 between observed and estimated snow depth was estimated between 0.81 and 1 in ten of the studied stations and 0.65 and 0.8 in the other two stations. Moreover, the findings imply that the proposed model is a suitable technique for estimating snow depth in remote areas lacking snowfall measurement.

Investigating the economic impact of climate change on agriculture in Iran: Spatial spillovers matter

AbstractIn this study, we enhance our understanding of the economic impacts of climate change on agriculture in Iran to provide further information for moving Iran's climate policy forward by linking farmland net revenue to novel climatic and non‐climatic variables. We take advantage of spatial panel econometrics to better circumvent omitted factors extraneous to the agricultural sector and to develop a more reliable and consistent model when data are inherently spatial. In contrast to conventional panel studies which relied on year‐to‐year weather observations, we exploit a hybrid approach to compromise between the disadvantages and advantages of longer‐term cross‐sectional analysis and shorter‐term panel models. We estimate the potential impacts of climate change on agriculture under several global warming scenarios based on the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). We find that (I) farmlands’ net revenues are projected to decline by 8%–19% and 14%–51% by 2050 and 2080; (II) the distributional impacts of climate change would highly depend on climate zones and geographical locations; (III) a few counties might benefit from climate changes; (IV) finally, failing to account for spatial spillovers when they are present leads to a misspecified model.

Assessment of morpho-physiological and quantitative and qualitative yield of Peppermint (Mentha piperita L.) under different irrigation regimes and application of different nitrogen fertilizer

Introduction Water and nitrogen fertilizer are major determinants of the level of agricultural production in the world, in addition to the quantity and quality of Medicinal plants are also effective. Iran's climate is mainly dry and semi-arid, in such a situation, where abnormal environmental stresses occur for plants. Improving crop yields in these stress conditions require good management of inputs (such as water and nutrients), their amount and type, and knowledge of physiological processes and plant defense mechanisms is essential. Water stress can significantly alter the metabolism of plants and reduce growth and photosynthesis and ultimately yield of plants. In this situation, effective management of water consumption in agriculture is an urgent necessity. In this regard, the use of agronomic techniques such as application of organic fertilizers or enhancement of soil biological conditions may be effective in reducing the effects of water stress and less use of chemical fertilizers for sustainable agriculture and human nutritional health. Also, intensive agriculture with the widespread use of chemical fertilizers, especially nitrogen can cause an increase in costs and environmental pollution. A key component of sustainable agriculture is use of organic fertilizers such as vermicompost and azocompost. Materials and methods In order to investigate the effects of water deficit stress and different nitrogen fertilizers on morphological, physiological traits, biological yield and essential oil percentage of peppermint, a experiment was conducted in a factorial arrangement in a randomized complete block de sign with three replications were carried out in 2018 at the field research station of the Agricultural Research Center of Tarbiat Modares University in Karaj (51 10’E, 33 44’ N, 1305.2 m above sea level). Experimental treatments consisted of three irrigation regimes (irrigation up to field capacity and after unloading 25, 40 and 55% water use in root zone, respectively) as the major factor and six fertilizer treatments based on nitrogen requirement respectively (100% chemical fertilizer, no fertilizer, 50% chemical + 50% azocompost, 100% vermicompost, 100% azocompost and 50% chemical fertilizer + 50% vermicompost) were as sub-factors. After field preparations, this area was divided into 54 experimental plots each of which were 2 m long with six rows, 0.2 m apart. Between all the main plots, a 3 m alley was kept to eliminate the influence of lateral water movement. Plant to plant distance in each row was 0.2 cm. Results Analysis of variance showed that the effect of all the experimental treatments and their interaction on all measured traits was significant. The results showed that mild and severe drought stress decreased plant height (18.2 and 42.92%) and biological yield (15.11 and 51.98%, respectively), while pigment, carotenoid, anthocyanin, proline and essential oil percentage increased. Nitrogen fertilizer application increased all measured traits. In most of the traits measured in this experiment, 50% chemical fertilizer and 50% vermicompost fertilizer were evaluated even better under severe water deficit conditions than other treatments. Conclusion: The results also showed that if the aim of planting peppermint is to improve the quality (essential oil percentage) of the plant by applying high water deficit stress, it can save more than 50% water consumption by producing the highest essential oil percentage. And vermicompost fertilizer can also be substituted for nitrogen chemical fertilizer to promote safe and sustainable

Evaluation of tourism climate conditions at three stations of Noshahr, Ramsar and Rasht using the physiological equivalent temperature and average predicted polling index

Provinces located on the southern shores of the Caspian Sea are one of the most important northern places in the country that have always attracted a great deal of tourists in different seasons of the year due to their various natural, human and historical attractions. Every year, they welcome different tourists. These beaches, while having attractive features for tourists, can also play a vital role in the sustainable development of the natural scenery and conservation area. One of the steps to reach sustainable development is tourism planning. The first step in this area is to assess the tourism climate in the country. In this study, in order to evaluate the conditions of the northern climate of Iran's climate, the meteorological data of synoptic stations of Noshahr, Ramsar and Rasht have been used in a 30-year statistical period divided into three decades of age. The method used to assess the climate of comfort, the physiological equivalent temperature index, and the predicted mean of the survey. The results of this study show that the highest climatic conditions for spending leisure time and tourism activities in this region are two separate periods in the middle of spring (May and June) and the beginning of the fall season (October). The continuation of average heat stress from July to August and cold stress from different periods from November to the end of the winter season is a factor for tourism constraints during these months. For other months, they have relatively good weather conditions in terms of temperature and humidity in a little warm and slightly cool thermal condition. Also, changes over the decades indicate climate change and impact on thermal comfort.

Use of Water Quality Index and Spatial Analysis to Assess Groundwater Quality for Drinking Purpose in Ardakan, Iran

Introduction: Due to water scarcity and increased water consumption during the past years, the importance of water in terms of transmission of diseases, as well as Iran's climate, groundwater aquifers are known as the most important resources of drinking water supply. Using the Water Quality Index (WQI) is considered as strong managerial tool for decision making in water resource management. Therefore, the aim of this study was to evaluate the quality of groundwater in Ardakan for drinking purpose using WQI. Spatial analysis was conducted with the geographic information system (GIS). Materials and Methods: This is a descriptive, cross-sectional study to investigate the quality of groundwater in Ardakan for drinking purpose. Information on total dissolved solids (TDS), total hardness, pH, electrical conductivity (EC), bicarbonate (HCO3-), chlorine (CL-), sulfate (SO42-), nitrate (NO3-), calcium (Ca2+) and magnesium (Mg2+) of 24 wells was obtained from Ardakan Health Center. The characteristics of the stations were determined using the Global Positioning System (GPS) and transmitted to the map prepared in the GIS environment. The calculated values of the WQI were zoned in the GIS environment by Inverse Distance Weighted (IDW) method. Results: Based on the WQI, well no.5 has the best quality water (17.61), which has the lowest WQI, and the highest value of WQI was obtained for well no. 20 (156.86). Conclusion: The results of the study showed that none of wells have drinkable water, 13 wells had good quality water, and 11 wells had poor quality and should be treated for drinking.

Investigating Orchard Men's Behavioral Intentions of Dashtestan County toward Water Conservation Using Stern Value-Belief-Norm Theory

Investigating Orchard Men's Behavioral Intentions of Dashtestan County toward Water Conservation Using Stern Value-Belief-Norm Theory

Effects of summer irrigation and weed control methods on morphological characteristics and yield of saffron in Iran's climate

Effects of summer irrigation and weed control methods on morphological characteristics and yield of saffron in Iran's climate

Determining new threshold temperatures for cooling and heating degree day index of different climatic zones of Iran

Iran is a country with a variety of different climates. Determining the threshold temperatures suitable for providing thermal and climatic comfort is necessary and vital to its population well-being. This research presents new threshold temperatures in order to calculate the degree day index required for heating and cooling by taking advantage of the 12 stations that are representative of the diversity of Iran's climate. Using Olgyay diagram, different bioclimatic ranges of 12 weather stations and their frequencies were compiled, processes and analysed. Mean daily data of temperature and relative humidity were used for the period of 1950–2010. Based on the frequencies of temperature readings falling in Olgyay's diagram comfort zone, representive temperature thresholds were selected based on 40 to 60 percentiles or (P20), 25–75% percentile (P50) and the threshold of 10–90% percentile. The findings of this study shows that Mashhad with 29.6% and Anzali with 2.33% of frequencies, have experienced the maximum and minimum days of comfort. After analyzing various percentiles to determine the threshold temperatures, it was observed that there is a little difference among the stations for determining the minimum threshold for the comfort. Differences are more obvious in the maximum thresholds. In total, minimum base temperatures (HDD) belonged to Ardabil stations that were 20.50, 20.90 and 20 deg C for P20, P50 and P80 respectively. The maximum temperature for calculating CDD with values of (P20 = 25 °C; P50 = 26.25 °C; P80 = 27.50 °C) is dedicated to Zabol station. The findings present more reasonable thermal comfort thresholds that can be used by architects, engineers and policy makers to achieve, in turn, more energy efficient homes and high quality indoor and outdoor living environments.

Climate change impact assessment on water resources in Iran: applying dynamic and statistical downscaling methods

As a result of inappropriate management and rising levels of societal demand, in arid and semi-arid regions water resources are becoming increasingly stressed. Therefore, well-established insight into the effects of climate change on water resource components can be considered to be an essential strategy to reduce these effects. In this paper, Iran's climate change and variability, and the impact of climate change on water resources, were studied. Climate change was assessed by means of two Long Ashton Research Station-Weather Generator (LARS-WG) weather generators and all outputs from the available general circulation models in the Model for the Assessment of Greenhouse-gas Induced Climate Change-SCENario GENerator (MAGICC-SCENGEN) software, in combination with different emission scenarios at the regional scale, while the Providing Regional Climates for Impacts Studies (PRECIS) model has been used for projections at the local scale. A hydrological model, the Runoff Assessment Model (RAM), was first utilized to simulate water resources for Iran. Then, using the MAGICC-SCENGEN model and the downscaled results as input for the RAM model, a prediction was made for changes in 30 basins and runoffs. Modeling results indicate temperature and precipitation changes in the range of ±6 °C and ±60%, respectively. Temperature rise increases evaporation and decreases runoff, but has been found to cause an increased rate of runoff in winter and a decrease in spring.

The parliamentary election in Bangladesh, December 2008

Iran is a country with a variety of different climates. Determining the threshold temperatures suitable for providing thermal and climatic comfort is necessary and vital to its population well-being. This research presents new threshold temperatures in order to calculate the degree day index required for heating and cooling by taking advantage of the 12 stations that are representative of the diversity of Iran's climate. Using Olgyay diagram, different bioclimatic ranges of 12 weather stations and their frequencies were compiled, processes and analysed. Mean daily data of temperature and relative humidity were used for the period of 1950–2010. Based on the frequencies of temperature readings falling in Olgyay's diagram comfort zone, representive temperature thresholds were selected based on 40 to 60 percentiles or (P20), 25–75% percentile (P50) and the threshold of 10–90% percentile. The findings of this study shows that Mashhad with 29.6% and Anzali with 2.33% of frequencies, have experienced the maximum and minimum days of comfort. After analyzing various percentiles to determine the threshold temperatures, it was observed that there is a little difference among the stations for determining the minimum threshold for the comfort. Differences are more obvious in the maximum thresholds. In total, minimum base temperatures (HDD) belonged to Ardabil stations that were 20.50, 20.90 and 20 deg C for P20, P50 and P80 respectively. The maximum temperature for calculating CDD with values of (P20 = 25 °C; P50 = 26.25 °C; P80 = 27.50 °C) is dedicated to Zabol station. The findings present more reasonable thermal comfort thresholds that can be used by architects, engineers and policy makers to achieve, in turn, more energy efficient homes and high quality indoor and outdoor living environments.

The Effects of Four Clonal Rootstocks on Growth Indices, Yield, Fruit Quality, and Quantity of `Golden Smoothee' Apple in Iran's Climate Conditions

In this research the effect of four clonal rootstocks (B9, M9, M26, and MM106) on growth characteristics, flowering and fruiting, and fruit quality and quantity of `Golden Smoothee' apple (Malus × domestica Borkh.) were studied during 2001 and 2003. Trees were 8 years old at the beginning of study. Experiments were planned in randomized complete-block design with four treatments (four rootstocks) and four replications. Rootstocks had significant effects on all growth characteristics. The highest tree height, shoot growth, and tree cross-sectional area were found on MM106; with B9 was the least and M9 and M26 were intermediate. The effect of year, and interaction of year on rootstocks were nonsignificant. Rootstock has highly affected flowering and fruiting characteristics. The highest flowering efficiency related to M9 and B9. The highest primary and secondary fruit set and fruit set efficiency found with M9 and M26. The highest preharvest fruit abscission observed with M26. The M9 had the least preharvest fruit abscission. Yield of M9 was the highest and B9 was the least. The M9 has the most yield efficiency and MM106 had the least. Effect of year was significant in many characteristics related to flowering and fruiting. Generally, trees had better conditions in first year. Among fruit quantitative treatments, rootstock only affected fruit weight significantly. Fruit harvested from B9 had the least weight and other rootstocks had similar fruit weight. Generally rootstock had no noticeable effect on fruit quantity and quality.