Particulate matters have detrimental effects on human health, environment and economic. This pollutant may emit from anthropogenic or natural sources. On global scale, main proportion of natural particulate matter release to the atmosphere because of wind erosion from arid and semi-arid regions. Recently, the amount of dust coming from Arabian countries has dramatically increased, especially dust storms that are affecting western and even central parts of Iran. This phenomenon has caused a lot of environmental problems. Dust source identification and trajectory simulation using numerical techniques are the main aims of this study. HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model dust module and trajectory simulation are utilized in this research and two case studies are investigated (in May and June 2010). The base of the HYSPLIT dust module is the PM₁₀ dust storm emission algorithm for desert land use. This methodology is applied to estimate hotspots and trajectories. Due to the results, dust storms started on May 17th and June 7th because of high wind shear (>8.5 m/s) from the western Syrian Desert. The source region limited to 32.50 °N to 33.80 °N and 38.00 °E to 38.80 °E coordinates. Dust plumes lifted and dispersed towards the east and southeast of the sources and reached Ahvaz on May 18th and June 8th. The average of PM10 concentration in these dates reached 625 and 494 μg m 3 on Ahvaz monitoring stations, respectively. Moreover, the results gained from the model for dust motion simulation are similar to the MODIS satellite images.

The present research introduces a well to wire pseudo comprehensive carbon footprint model for combined cycle power plants. The mentioned model integrates land use change model, operational model and transmission and distribution model into one comprehensive model. The parameters which their effects are considered in the integrated model are: fuel type, fuel transmission type, emission for fuel extraction and processing, own consumption of the plant, degradation, site ambient condition, transmission and distribution losses. For quantifying the effectiveness of each parameter, sensitivity analyses based on different life cycle scenarios are performed. The result shows that the effect of land use change is negligible. The carbon footprint of electrical energy produced in combined cycle plant until it is delivered to the end users varies from 321 to 522 g CO₂ eq/kWh.

In this study a pseudo comprehensive carbon footprint model for fossil fuel power plants is presented. Parameters which their effects are considered in this study include: plant type, fuel type, fuel transmission type, internal consumption of the plant, degradation, site ambient condition, transmission and distribution losses. Investigating internal consumption, degradation and site ambient condition effect on carbon footprint assessment of fossil fuel power plant is the specific feature of the proposed model. To evaluate the model, a sensitivity analysis is performed under different scenarios covering all possible choices for investigated parameters. The results show that carbon footprint of fossil fuel electrical energy that is produced, transmitted and distributed, varies from 321 g CO2 eq/kWh to 980 g CO2 equivalent /kWh. Carbon footprint of combined cycle with natural gas as main fuel is the minimum carbon footprint. Other factors can also cause indicative variation. Fuel type causes a variation of 28%. Ambient condition may change the result up to 13%. Transmission makes the carbon footprint larger by 4%. Internal consumption and degradation influence the result by 2 and 2.5%, respectively. Therefore, to minimize the carbon footprint of fossil fuel electricity, it is recommended to construct natural gas ignited combined cycles in low lands where the temperature is low and relative humidity is high. And the internal consumption is as least as possible and the maintenance and overhaul is as regular as possible.

We developed an artificial neural network as an air quality model and estimated the scope of the impact of climate change on future (until 2064) summertime trends of hourly Ozone (O3) concentrations at an urban air quality station in Tehran, Iran. Our developed scenarios assume that present-time emissions conditions of O3 precursors will remain constant in the future. Therefore, only the impact of climate change on future O3 concentrations is investigated in this study. GCM projections indicate more favorable climate conditions for O3 formation over the study area in the future: the surface temperature increases over all months of the year, solar radiation increases, and precipitation decreases in future summers, and summertime daily maximum temperature increases about 1.2 ∘ C to 3 ∘ C until 2064. In the scenario based on present-time O3 conditions in 2012 summer without any axceedances, the summertime exceedance days of 8-hr O3 standard are projected to increase in the future by about 4.2 days in the short term and about 12.3 days in the mid-term. Similarly, in the scenario based on present-time O3 conditions in 2010 summer with 58 days of exceedance from 8-hr O3 standard, exceedances are projected to increase about 4.5 days in the short term and about 14.1 days in the mid-term. Moreover, the number of Unhealthy and Very Unhealthy days in 8-hr AQI is also projected to increase based on pollution scenarios of both summers.

Quantifying the impact of climate change on future air quality is a challenging subject in air quality studies. An ANN model is employed to simulate hourly O3 concentrations. The model is developed based on hourly monitored values of temperature, solar radiation, nitrogen monoxide, and nitrogen dioxide which are monitored during summers (June, July, and August) of 2009-2012 at urban air quality stations in Tehran, Iran. Climate projections by HadCM3 GCM over the study area, driven by IPCC SRES A1B, A2, and B1 emission scenarios, are downscaled by LARS-WG5 model over the periods of 2015-2039 and 2040-2064. The projections are calculated by assuming that current emissions conditions of O3 precursors remain constant in the future. The employed O3 metrics include the number of days exceeding one-hour (1-hr) (120 ppb) and eight-hour (8-hr) (75 ppb) O3 standards and the number of days exceeding 8-hr Air Quality Index (AQI). The projected increases in solar radiation and decreases in precipitation in future summers along with summertime daily maximum temperature rise of about 1.2 and 3 celsius in the first and second climate periods respectively are some indications of more favorable conditions for O3 formation over the study area in the future. Based on pollution conditions of the violation-free summer of 2012, the summertime exceedance days of 8-hr O3 standard are projected to increase in the future by about 4.2 days in the short term and about 12.3 days in the mid-term. Similarly, based on pollution conditions of the polluted summer of 2010 with 58 O3 exceedance days, this metric is projected to increase about 4.5 days in the short term and about 14.1 days in the mid-term. Moreover, the number of Unhealthy and Very Unhealthy days in 8-hr AQI is also projected to increase based on pollution conditions of both summers.