azar sheikhzeinoddin

Global and regional environmental issues have become increasingly significant because of rapid population growth and socioeconomic development. Problems such as soil erosion, ecological pollution, land degradation, loss of biodiversity, and diminished ecosystem services pose serious threats to human living conditions and sustainable development of economies and societies. Consequently, as the population increases and economic activities expand, leading to greater consumption of ecological resources, assessing environmental security becomes crucial. This study aims to develop a comprehensive, multi-faceted approach to evaluate the environmental security of Fars Province by utilizing an ecological footprint method.

Typically, this evaluation employs two fundamental concepts: ecological footprint and ecological capacity. In this context, the per capita ecological footprint and ecological capacity of Fars province were analyzed for the years 2011 to 2021. After determining the per capita ecological footprint and capacity, four indices were calculated: ecological deficit (ED), ecological footprint diversity index (EFDI), ecological pressure index (EPI), and ecological coordination coefficient (ECC).

The results of this study showed that the per capita ecological footprint of Fars province increased by more than 17% during the study period, which, along with the population growth of the province, indicates an increase in pressure on the natural resources. Additionally, pollution levels and agricultural production contributed significantly to this strain. On the other hand, the per capita ecological capacity of the province, dropping from 1.23 gha in 2011 to 1.11 gha in 2021 has increased by 10%. It was also concluded that the per capita ecological capacity of Fars province is significantly lower (less than one-fourth) than its per capita ecological footprint, underscoring the region's vulnerability in terms of its capacity to absorb and regenerate natural resources. The findings indicated that throughout the study period, Fars Province consistently experienced an ecological deficit, which has been rising over time. Furthermore, the assessment of four environmental security indicators all indicate the province's environmental insecurity and the lack of coordination between development and the environment.

According to the results obtained using the investigated indicators in this study, the environmental condition of the province is not suitable and it has worsened over time. Therefore, if the policymakers are looking for sustainable economic development, it is necessary to pay more attention to the province's environment. In other words, it is imperative to implement dynamic and periodic environmental monitoring and to evaluate management strategies to enhance environmental health.

Ecological footprint is an index that determines the rate of resource consumption and waste production by humans, and by comparing it with the rate of resource reproduction and waste disposal by the environment, the pressure on the environment can be determined. Therefore, policymakers can design and implement the necessary programs to reduce this pressure. In order to measure the possible effects of future activities and policies of development programs on the environment, it is necessary to investigate the relationship between ecological footprint and economic development. Therefore, the purpose of this study is to investigate the short-term and long-term relationship and determine the factors affecting the per capita ecological footprint in Iran. The ARDL model was used for the 1990 to 2018. Also, the variables of energy consumption, open trade, economic growth and the ratio of capital to labor were considered. Also, in order to analyze the impact of trade on the ecological footprint, the effect of trade was decomposed into the effects of scale, technique and composition. The results of the study showed that the effect of scale and technique on the ecological footprint have a positive and negative effect, respectively, and as a result, the environmental hypothesis of the Kuznets curve is confirmed for Iran. In addition, energy consumption and the combination effect contribute to intensifying the ecological footprint, while trade openness reduces environmental degradation. The error correction coefficient shows that 15% of the per capita ecological footprint imbalance is adjusted annually and approaches its long-term trend.

Due to the increase in population and the need to provide food and preserve the environment, the importance of the water crisis has increased in the years leading to the third millennium and the beginning of the 21st century. The reduction of underground and surface water resources and the destruction of the environment and water ecosystems are signs of the water crisis in Iran and the world. On the other hand, the production of agricultural products is associated with the creation of environmental effects, especially water and soil pollution (due to the use of pesticides and as a result, the loss of environmental balance). Therefore, there is a need for policy-makers to have indicators in the field of the effects of agricultural activities on natural resources and the environment, so that they can measure the economic and environmental effects. The water footprint index was first introduced by Hoekstra and Hung in 2002; and over recent years, it has been widely used by experts in different parts of the world. The water footprint is a multidimensional indicator that shows the volume of water consumed by the type of water source and the volume of polluted water by the type of pollutant. All components of the total water footprint are determined by time and place. The water footprint consists of three components, including blue water footprint, green water footprint and gray water footprint. Therefore, given the importance of sustainability of water resources, in this study, by considering the components of water footprint as inputs in the production function, the economic-environmental efficiency was estimated using the Stochastic Frontier Approach (SFA) for the production of barley in Iran; specifically, Water Footprint- Stochastic Frontier Approach (WF-SFA) framework was used to analyze the economic-environmental efficiency of barley production. Thus, in this study, in order to estimate the environmental effects, the water footprint index was used and the economic-environmental efficiency of barley production was estimated. For this purpose, the components of barley water footprint were calculated in the provinces producing this product. Then, the economic-environmental efficiency of barley production in the provinces of Iran was calculated. In the first step, in order to calculate the water footprint, meteorological data was collected for the cities that had the highest level of barley cultivation in each province. This information included average wind speed (m/s), maximum temperature (c), minimum temperature (c), average temperature, 24-hour precipitation (mm), maximum relative humidity (%), minimum relative humidity (%), average relative humidity (%), sunny hours and daily radiation amount. The total water footprint during crop growth (WF) is the sum of blue, green and gray water components. After calculating the components of barely water footprint in the provinces of the country following Battese and Coelli (1995), an SFA model was created for barely production. In the year t, for the i province, the basic stochastic frontier production where yit is the product obtainable from input Xit (subtraction of inputs) and β is the vector of unknown parameters; in addition, vit represents random errors that are assumed to have a normal distribution with zero mean and variance σv2 and is distributed independently of uit.In this study, in order to calculate the economic-environmental efficiency using the stochastic frontier production function, the appropriate production function form was first selected. The forms of the production function examined in this study are Cobb-Douglas and Translog. After choosing the appropriate production function and model type, the stochastic frontier production function was estimated by the maximum likelihood method as well as the economic-environmental efficiency of barley production was estimated. By examining different barley producing provinces, it could be seen that the highest amount of total water footprint was related to the provinces of Ilam, Kerman, Sistan and Baluchistan and South Khorasan and the lowest amount was related to the provinces of Tehran, Golestan, Qazvin and Ardabil. The total amount of water footprint for most provinces was in the range of 3 to 4 thousand cubic meters. Also, the results showed that the barley water footprint in Iran did not follow a very specific geographical pattern, but in tropical and low-rainfall provinces such as Sistan and Baluchistan, the water footprint was higher and the main difference between the water footprints of the provinces was due to the blue water footprint. The results of the estimation of the stochastic frontier production function of barley production using the variable efficiency model over time showed that the combined input variables, blue water footprint and green water footprint had a significant effect on the production of this product. In this regard, the positive coefficient of the combined input variable (X1) and the green water footprint (X4) indicated that assuming the constancy of other conditions, a 1% increase in the amount of each of these variables would lead to an increase of about 1% in the production of barley among the provinces. These findings indicated the low level of accumulation of combined inputs in the production of barley due to the low production rate of this product and also the low amount of precipitation in the country. The labor force variable (X2) was not statistically significant; and the coefficient of this variable in the estimated production function indicated that the labor force had a very small positive effect on the efficiency of barley production. Therefore, due to the very low contribution of labor in barley production, it is expected that the amount of barley production in Iran will increase with the increase in the degree of mechanization.  The final results showed that the provinces of Ilam, Qom, and Isfahan had the lowest economic-environmental efficiency, and the provinces of Kohgiluyeh and Boyer Ahmad, Kermanshah, and Kurdistan had the highest economic-environmental efficiency in barley production, respectively. The overall average economic and environmental efficiency of wheat production was estimated at 0.94. Furthermore, the results of the estimation of the inefficiency model showed that the economic and environmental efficiency of barley production was higher for regions with higher per capita GDP and more rainfall. In other words, the variables of per capita GDP and annual rainfall negatively affect the economic and environmental inefficiency of barely. So, it is suggested to evaluate the effects of human and social capital on the economic-environmental efficiency of agricultural production in future studies. It is also suggested to follow the following methods to reduce pollution and preserve the environment: changing production methods, more efficient management and the use of superior technologies by ineffective provinces (for example, new irrigation methods to reduce the water footprint), the use of green fertilizers and so-called low-risk chemical fertilizers approved by international organizations to reduce the gray water footprint as one of the factors that reduce the efficiency and biological control instead of using pesticides (to reduce the gray water footprint) to eliminate pests. On the other hand, encouraging incentives and punishments are also very effective for farmers. The government should think of incentive measures to encourage efficient sectors; for example, it can give the priority of using resources with lower prices to farmers who produce less environmental pollution by using fewer chemical fertilizers and pesticides. Paying subsidies to efficient producers is also effective. On the other hand, environmental regulations should be set for producers. Establishing a tax on undesirable products to increase the motivation of producers and farmers to use environmentally friendly methods and techniques is also very effective.

After wheat, rice has the most important role in human nutrition. Despite the vital importance of its cultivation, high water consumption and water shortage crisis, the sustainability of the cultivation of this grain has faced many problems. Therefore, the purpose of this study is to investigate the water footprint and water use efficiency of rice among the provinces in order to move towards crop sustainability.

Methods & Materials: 

In this study, water footprint index was used to calculate water use efficiency in rice production. For this purpose, first the water footprint components for the provinces of the country were calculated and then the water use efficiency was calculated.

The results of calculating water footprint showed that the lowest water footprint is related to Mazandaran and Gilan provinces and the highest water footprint is related to South Khorasan and Sistan & Baluchestan provinces. Also, the highest and lowest amount of green water footprint is related to Gilan and South Khorasan province, respectively. The results of water use efficiency calculation showed that Mazandaran (0.511) and Gilan (0.422) had the highest efficiency and South Khorasan (0.135) and Sistan & Baluchestan (0.171) had the lowest efficiency.

By comparing the water footprint components among the provinces of the country, it is cleared that the ratio of blue, green and grey water footprint in total water footprint is 45-53%, 6-25% and 0-15%, respectively. Also, the total water footprint of the country was obtained in the range of 1958 and 2758 m3 per ton.

Economic Ecological Efficiency is defined as the efficiency of using environmental resources to meet human needs. This concept can be considered as a suitable criterion for evaluating the sustainability of production and its economic efficiency. Due to the fact that the production of agricultural products is associated with environmental effects and the highest amount of water consumption is used to produce agricultural products on a global scale, so in this study, in order to investigate the environmental effects of wheat production, water index was used. For this purpose, first the traces of wheat water in the provinces of the country during the period 2000-2011 were calculated and then the economic-ecological efficiency of wheat production was estimated. The results of water footprint calculation showed that the provinces of Gilan, South Khorasan, Semnan and Sistan and Baluchestan have the average total of more water footprint in wheat production. Also, the average water, green and gray water footprint in the country during the study period was equal to 2625.7, 428.1 and 594.1 cubic meters per ton. The results of estimating the economic-environmental efficiency also showed that among the studied variables, compositional input and green water footprint have the most positive effect on improving the production value of wheat. The results also show that the provinces of East Azerbaijan, North Khorasan and Khorasan Razavi have the lowest average efficiency and the provinces of Gilan, Sistan and Baluchestan, Mazandaran and Ilam have the highest economic-ecological efficiency of wheat production, respectively. The average total economic-ecological efficiency of wheat production was estimated to be 0.84. Also, the results of estimating the inefficiency model showed that the economic-ecological efficiency of crop production is higher for areas with per capita GDP and higher rainfall

Agricultural sector development without sustainability attitude has led to many problems. Sustainability has three dimensions: economic, social and environmental. Over time, increasing agricultural production has led to the overuse of natural resources and therefore, destruction of the environment. Therefore, the purpose of this study is to measure agricultural sustainability using a composite index.

For this purpose, firstly 35 economic, social and environmental indicators were gathered for 30 Iranian provinces. Then agricultural sustainability was measured using the Morris, the Mc-Granahan, and the principal component analysis methods.

The results showed that Khorasan Razavi, Fars, Isfahan, and Khuzestan provinces have higher agricultural sustainability than other provinces. Also, in the economic dimension: Khorasan Razavi, East Azerbaijan, and Isfahan provinces; in the social dimension: Fars, Mazandaran, and West Azerbaijan provinces; and in the environmental dimension: Gilan, South Khorasan, and Chaharmahal and Bakhtiari provinces; are more sustainable. In addition, Qom, Bushehr, and Sistan and Baluchestan provinces have the lowest economic and social sustainability. As well, Qazvin and Bushehr provinces have the lowest level of environmental sustainability.

Findings showed that unsustainable provinces are weak in socio-economic indicators; especially in seeds, fertilizer applications, use of modern irrigation systems, and appropriate agricultural methods. Therefore, it is necessary to invest in the infrastructure of these indicators to upgrade agricultural sustainability.

Resilience is a new concept whose main approach is to design with less vulnerability and more flexibility in the face of stress and accidents so that a resilient province is ready to respond quickly in an emergency. The new conditions respond and continue to work with minimal damage. Therefore, the purpose of this study is to measure the resilience of the country's provinces using economic, social, infrastructure and environmental indicators. For this purpose, 21 indicators were collected for 31 provinces of the country and by combining them, the combined resilience index was calculated. In order to determine the weight of each index, fuzzy hierarchical method was used. Based on the results, the weight of each of the indicators of economic, infrastructural, social and environmental resilience was equal to 0.56, 0.13, 0.24 and 0.07, respectively. Also, based on the results of the combined resilience index, the provinces of Tehran (0.731), Khuzestan (0.498), Isfahan (0.445), Fars (0.439), Gilan (0.420) and Mazandaran (0.375) have the highest resilience among the provinces of the country. Also, Sistan and Baluchestan, Qom, North Khorasan, South Khorasan, Hormozgan, Ardabil and Zanjan provinces are the most vulnerable provinces of the country. Finally, according to the constructive indicators of resilience, the weaknesses of each province were identified and suggestions were made in this regard. Therefore, it is recommended that by increasing investments and creating stability in the economic activities of deprived provinces with the aim of increasing economic resilience, the necessary grounds should be provided to increase the resilience of these provinces.

maize as one of the most important crops has a significant strategic role in Iran, so it is cultivated as an important crop in all provinces of Iran and farmers earn profit from their cultivation. Therefore, in this study, economic benefits, environmental costs and, ultimately, social benefits of maize cultivation were calculated in different provinces of Iran. In order to calculate the environmental costs, the maize gray water was calculated. Results showed that all Iranian provinces have economic benefits, but by calculating the gray water and consequently the environmental cost, it was determined that the provinces of Mazandaran, Fars and North Khorasan have the highest environmental cost. This has led to social losses in some of these provinces. The results showed that the provinces of Kohkiluyeh and Boyer Ahmad, Qazvin and East Azarbaijan have the most social benefits in the cultivation of maize. However, the provinces of Khuzestan, Kermanshah and Fars, which have the most cultivated areas in different years, have lower social benefits, so that Kermanshah province has social losses.

In Iran, conventional tillage practice has resulted in soil erosion and loss of soil organic matter which has been further aggravated by the practice of crop residue removal and burning. Conservation Agriculture (CA) can be regarded as a means to enhancing productivity, reducing poverty, and mitigating the consequences of climate change in rural households. In this study, the theory of planned behavior (TPB) used to understand the factors affecting conservation agriculture acceptance, data collected through a questionnaire, consisting of 260 farmers from Zarghan area, in period 2014-2015. The results of TPB model showed that about 78% variation in farmers' intention is explained by attitude, subjective norms and perceived behavioral control, and farmers' attitude is found to be the stronger predictor of intention. Moreover, high education level and off- farm income had the most significant and positive effects on the farmers' attitude towards adopting the conservation agriculture methods. The findings of this study could help to improve the understanding of farmers' adoption dynamics related to CA, and of how farmers may approach this and other new technologies.

The main objective of this article is analyzing the relationship between agricultural commodity price and oil shock for Iran. To this end, the nonlinear autoregressive distributed lags (NARDL) approach was employed which allows prices to be tied by asymmetric impact both in the long- as well as in the short-run. Linkages between oil price and agricultural commodity prices are examined using seasonal data for 1389:4 to 1395:4. The bounds test of the NARDL specification suggests the presence of co-integration among the variables, which include the agricultural commodity price, oil price and GDP. The estimated NARDL model affirms the presence of asymmetries in the agricultural product price behavior in both Long-run and short-run. Therefore, in the long and short-run, a positive significant relation between oil price increases and agricultural commodity price was found. In addition, the short and long-run significant relation between oil price reduction and the agricultural production price was estimated. Also, the positive oil price shock will result in higher changes in the agricultural commodity price as compared to the oil price reduction shock.

Agricultural activities increasingly use water, fertilizers and pesticides, which may generate negative impacts on environment. Nowadays, nitrogen leaching from agricultural lands is a widespread global problem. Therefore, alternative land management practices such as nutrient management (rate, method and time of application), tillage operations (conservation and no-tillage), and irrigation management are routinely used to reduce non-point source pollution and improve water quality. In fact, a number of studies have illustrated the positive effects of best management practices (BMPs) on water and nutrient losses. The objective of this paper is to develop a bio-economic model and introducing the policy instrument for reducing nitrate from irrigation and drainage Dorudzan. We aim to identify ‘‘win–win’’ opportunities for improving farm profitability and reducing nitrate leaching.
An integrated biophysical-economic model was developed with five components. The first component is based on a process-based biophysical model (SWAT) that simulates the key processes of crop growth within the water and nitrogen cycles. The second component is a meta-model, which is used to link the biophysical model with the economic model. The meta-model employs regression techniques to replace the original simulation model and allow the application of simulation model results in an economic model of farm production. Crop yield is the key link between the two models. A quadratic function (Eq. 1), which allows estimation of the effect of increasing input levels and diminishing marginal returns, particularly when a wide range of inputs need to be incorporated, was used in this study.
(1)
Where, Y, W and N are crop yield, water and nitrogen fertilizer application, respectively.
The third component is a simple farm economic model, which is used to predict farmers’ response behavior under different policy scenarios, and to determine when and how much to irrigate and fertilize, and the farm gross margin that results (Eq. 2).
(2)
Where, GM, , , and C are the farm gross margin (rial/ha), water price (rial/m3), nitrogen fertilizer price (rial/kg), crop price (rial/kg) and other costs, respectively.
The fourth component is a nitrate leaching function which is a function of water and nitrogen fertilizer application (Eq. 3).
(3)
The fifth component is assessment of policy incentives. Regulators have at their disposal a portfolio of policy instruments (such as water pricing or tax on nitrogen fertilizer application) that can be used to influence nitrate leaching.
For running SWAT model, the data for estimating the wheat, barley, corn and rice yield production functions were generated by running the biophysical model hundreds of times with a different range of amount of water and nitrogen applications. The total number of scenarios of combinations of amounts of irrigation and nitrogen applications was about 96, 72, 88 and 84 for wheat, barley, corn and rice, respectively. Then, the yield production function was estimated with the multiple non-linear regression technique in the Eviews software. For model simulation, the economic model was formulated based on the crop production function obtained from the multiple non-linear regression analysis in the SWAT running stage and generate the farm gross margins. The effects of increasing water prices on nitrate leaching were simulated with the biophysical model.
The values of the coefficients from the multiple nonlinear regressions are shown in Table 1.
Table 1-Results from multiple non-linear regressions
Rice corn Barely Wheat Parameters
-6.011*** -11.335** -2.64*** 0.978***
(-6.252) (-2.075) (-4.073) (5.125)
0.0221** 0.047*** 0.0288*** 0.00098***
(8.17) (2.68) (7.00) (11.342)
-1.13*10-5*** -3.21*10-5*** -4.31*10-5*** -1.38*10-5***
(-7.726) (-2.478) (-6.657) (-12.985)
0.000158*** - 0.008*** 0.01***
(6.272) - (5.835) (31.407)
-3.23*10-6*** -4.88*10-6*** -3.24*10-5*** -1.22*10-5***
(-6.378) (-6.815) (-10.422) (-42.378)
- 9.15*10-6*** 2.19*10-5*** 5.89*10-6***
- (7.766) (5.563) (11.27)
0.99 0.98 0.955 0.994 R2
***,** significant in 1% and 5% , Numbers in parentheses ret-statistics
The results for water and nitrogen inputs, crop yield, farm gross margin and nitrate leaching under agronomic optimum, economic optimum and bio-economic optimum, also are shown in Table 2.
Table 2- Comparison between agronomic optimum, economic optimum and bio-economic optimum
Gross margin Nitrate leaching crop yield nitrogen fertilizer Irrigation* Scenario crop
(rial/ha) (kg/ha) (kg/ha) (kg/ha) (m3/ha)
26743460 56.81 5913.2 523 11721.5 Agronomic optimum wheat
26995120 49.83 5882.9 486.4 10727 economic optimum
26354880 37.99 5723.4 408.59 9824.5 bio-economic optimum
16314000 15.08 4203.5 262 10020 Agronomic optimum barely
16416560 14.71 4105.8 245.8 9637.75 economic optimum
16416560 14.71 4105.8 245.8 9637.75 bio-economic optimum
44180040 101.31 9009 750 20000 Agronomic optimum corn
44364700 89.57 8988 684 20000 economic optimum
40805580 37.9 8390 394 20000 bio-economic optimum
66876590 51.98 5020 244.58 24450 Agronomic optimum rice
67111950 42.43 5000 209.91 23918.14 economic optimum
67098590 38 4900 197.2 23918.14 bio-economic optimum
*irrigation efficiency 40%
The results show that there are win-win opportunities for improving farm profitability and reducing nitrate leaching by moving from current status to economic optimum. But from this point onwards, reduction in nitrate leaching is not achievable without profit penalties. In other word, to move from economic optimum to bio-economic optimum point, there is a trade-off relationship between farm profitability and groundwater quality protection. Also results of policy assessment showed that for wheat-water pricing and for corn and rice, because of high elasticity of yields of these crops to water application, tax on nitrogen application are cost effective policies.

The main purpose of this study is to determine welfare impacts of trade liberalization on maize market. For this purpose, we used from time series data for the period 1961/2009 and estimated domestic supply, domestic demand and import demand for maize. Results of estimation showed that price elasticity of supply and demand is 0.32 and -0.25, respectively. Then, by means of these elasticities, we measured welfare impacts of this policy. Regarding to available information, observed that imported price of maize is lower than producer and consumer price. Therefore, we expect that by doing trade liberalization policy, producer and consumer welfare decrease and increase, respectively. That result of this study confirms this pretension. Also, on the track of administration of this policy, government expenditure deceases. Finally, results showed that trade liberalization cause to social welfare increases.

In this study, the social welfare impacts of the interaction of Iranian rice import policies and Thai export policies are analyzed using a game theoretic approach in conjunction with econometric supply and demand models. The joint impacts of increasing the world price of rice, resulting from the export policies in Thailand along with changes in tariff rates in Iran, on social welfare are analyzed in the two countries. Because Iran is a small country in terms of the volume of world rice trade its policies do not influence Thai social welfare. Results of this study show that in order to maximize its own social welfare, the government should impose a modest tariff rate of approximately 3%. This is much less than the actual tariff rate applied in recent years, e.g. 19% in 2007.