RESUMEN
Air quality concerns have become increasingly serious in metropolises such as Tehran (Iran) in recent years. This study aims to assess the contribution of urban trees in Tehran toward mitigating air pollution and to evaluate the economic value of this ecosystem service using the i-Tree Eco model. To accomplish this objective, we utilized Tehran's original land use map, identifying five distinct land use categories: commercial and industrial, parks and urban forests, residential areas, roads and transportation, and urban services. Field data necessary for this analysis were collected from 316 designated plots, each with a radius of 11.3 m, and subsequently analyzed using the i-Tree Eco model. The locations of these plots were determined using the stratified sampling method. The results illustrate that Tehran's urban trees removed 1286.4 tons of pollutants in 2020. Specifically, the annual rates of air pollution removal were found to be 134.8 tons for CO; 299.7 tons for NO2; 270.3 tons for O3; 0.7 tons for PM2.5; 489.4 tons for PM10 (particulate matter with a diameter size between 2.5 and 10 µm); and 91.5 tons for SO2, with an associated monetary value of US$1 536 619. However, despite this significant removal capacity, the impact remains relatively small compared with the total amount of pollution emitted in 2020, accounting for only 0.17%. This is attributed to the high emissions rate and low per capita green space in the city. These findings could serve as a foundation for future research and urban planning initiatives aimed at enhancing green spaces in urban areas, thereby promoting sustainable urban development. Integr Environ Assess Manag 2024;00:1-11. © 2024 SETAC.
RESUMEN
Agrarian landscapes theoretically provide ecosystem services that meet the demands of a wide range of socioecological processes. Consequently, any landscape agroecology approach must tackle the dynamic interaction of land-use distribution and associated social metabolism at different spatiotemporal scales. An agroecological scarcity case study explores how driven agricultural energy flows interact with landscape complexity in arid landscapes of 46 counties in the Qazvin Province (Iran). An Energy-Landscape Integrated Analysis (ELIA) was performed to correlate the energy reinvestment (E) and energy redistribution (I) present within the social metabolism network, with landscape complexity (Le) measured in terms of spatial patterns and related ecological processes. As well, a cluster analysis was run to establish agrarian landscape typologies based on the ELIA indicators. The results of this study provide an explicit sketch of the four strategies that society in Qazvin Province has developed within the dry environments that sustain it. Our findings confirm the hypothesis that there is a positive relationship between optimizing non-dissipative internal energy loops and landscape complexity, which can explain agroecosystem sustainability. This research enables us to define spatially informed agroecological transitions from a territorially explicit socioecological perspective and will make a significant contribution to decisions on agricultural policies given different land-use strategies, especially under scenarios of ecological scarcity.
RESUMEN
Land use/land cover (LULC) changes strongly affect catchment hydrology and sediment yields. The current study aims at analyzing the hydrological consequences of dynamic LULC changes in the Anzali wetland catchment, Iran. The Soil and Water Assessment Tool (SWAT 2012) model was used to assess impacts on evapotranspiration, water yield, and sediment yield. Two model runs were performed using static and dynamic LULC inputs to evaluate the effects of LULC change between 1990 and 2013. For the static model, the LULC map of 1990 was used, whereas for the dynamic model, a gradual change of the LULC distribution was interpolated from 1990, 2000, and 2013 LULC data. The major LULC changes were identified as an increase of agricultural area by 7% of the catchment area and a decrease of forest coverage by 6.8% between 1990 and 2013. At the catchment scale, the differences in the long-term mean annual values for the main water balance components and sediment yield were smaller than 10 mm (<2.8%) and 3 t/km2 (<2.6%), respectively. However, at the sub-basin scale the increase of agricultural land use resulted in an increase of evapotranspiration, water yield, and sediment yield by up to 8.3%, 7%, and 169%, respectively, whereas urban expansion led to a decrease of evapotranspiration, water yield, and sediment yield by up to -3.5%, -2.3%, and -9.4%. According to the results of the monthly time scale analysis, the most significant impact of LULC changes occurs during the dry season months, when the increase of irrigation agriculture results in an increase in water discharge and sediment loads to the Anzali wetland. Overall, the results showed that the implementation of dynamic LULC change into the SWAT model could be adopted as a planning tool to manage LULC change of the Anzali wetland catchment in the future.