Spatiotemporal description of BTEX volatile organic compounds in a Middle Eastern megacity: Tehran Study of Exposure Prediction for Environmental Health Research (Tehran SEPEHR).

Characterization and quantification of PM2.5 emissions and PAHs concentration in PM2.5 from the exhausts of diesel vehicles with various accumulated mileages.

Due to its dangerously high level of pollutants, Tehran air quality is a serious concern. Several immediate and emergency solutions have been pursued to mitigate the problem in the short term. Most of the solutions are based on traffic-restriction schemes that pose challenges to citizens’ mobility. As part of such policies, the central part of the city has been converted into a traffic restricted zone (TRZ) in which vehicles are allowed to enter only on certain days of the week based on their license plate number. The purpose of this study was to investigate the effectiveness of such policies on reducing the concentration of various pollutants by using advanced air quality modeling approach. First, the pollutant emissions were calculated using the International Vehicle Emissions (IVE) model, and the results were used in the WRF/CAMx modeling system to investigate the effects of traffic restriction enforcement policy on air quality and pollutants dispersion over Tehran. Measured data at monitoring sites were used to benchmark performance of the modeling system. The results showed satisfactory performance of both models in predicting meteorological parameters and concentration of pollutants. While emission input data was reduced by 40% in the TRZ, the maximum reduction in CO as a primary pollutant was approximately 20%, which is highly related to the traffic conditions. Results suggest that effectiveness of TRZ policies highly depends on the type of pollutant, meteorological conditions, and the location of the study area.

Investigating the influence of traffic emission reduction plans on Tehran air quality using WRF/CAMx modeling tools

Statistically clustering air pollution can provide evidence of underlying spatial processes responsible for intensifying the concentration of contaminants. It may also lead to the identification of hotspots. The patterns can then be targeted to manage the concentration level of pollutants. In this regard, employing spatial autocorrelation indices as important tools is inevitable. In this study, general and local indices of Moran’s I and Getis-Ord statistics were assessed in their representation of the structural characteristics of carbon monoxide (CO) and fine particulate matter (PM2.5) polluted areas in Tehran, Iran, which is one of the most polluted cities in the world. For this purpose, a grid (200 m × 200 m) was applied across the city, and the inverse distance weighted (IDW) interpolation method was used to allocate a value to each pixel. To compare the methods of detecting clusters meaningfully and quantitatively, the pollution cleanliness index (PCI) was established. The results ascertained a high clustering level of the pollutants in the study area (with 99% confidence level). PM2.5 clusters separated the city into northern and southern parts, as most of the cold spots were situated in the north half and the hotspots were in the south. However, the CO hotspots also covered an area from the northeast to southwest of the city and the cold spots were spread over the rest of the city. The Getis-Ord’s PCI suggested a more polluted air quality than the Moran’s I PCI. The study provides a feasible methodology for urban planners and decision makers to effectively investigate and govern contaminated sites with the aim of reducing the harmful effects of air pollution on public health and the environment.

https://www.mdpi.com/2220-9964/6/9/270/pdf

An Assessment of Spatial Pattern Characterization of Air Pollution: A Case Study of CO and PM2.5 in Tehran, Iran

Ground monitoring station data of PM2.5 are not available for each day and all places in urban areas. In this research, taking Tehran as an example, a geographically and temporally weighted regression (GTWR) model was utilized to investigate the spatial and temporal variability relationship between PM2.5 concentrations measured at ground monitoring stations and satellite aerosol optical depth (AOD) data. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor produced AOD values with 3-km spatial resolution. Using meteorological variables and land use information as additional predictors utilized in the GTWR model, the AOD was converted to PM2.5 at ground level for warm (October to March) and cold seasons (April to September) from 2011 to 2017. To improve the accuracy of the correlation coefficient between converted PM2.5 from the GTWR model and PM2.5 concentrations measured at ground monitoring station, the results of a linear model (LR), a nonlinear model (artificial neural network (ANN)), and hybrid models including general regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) were compared. The results of the linear, nonlinear, and hybrid models for the cold season display higher accuracy compared with the results for the warm season. Among the used models, the GRNN model has higher accuracy compared with the other models. This study reveals that AOD conversion to particulate matter by the GTWR model and its simulation to PM2.5 at ground level using a hybrid model such as the GRNN can be used to study air quality.

Evaluation of linear, nonlinear, and hybrid models for predicting PM2.5 based on a GTWR model and MODIS AOD data

Motorcycles are the third most common means of transportation in the megacity of Tehran. Hence, measurements of emission factors are essential for Tehran motorcycle fleets. In this study, 60 carburetor motorcycles of various mileages and engine displacement volumes were tested in a chassis dynamometer laboratory according to cold start Euro-3 emissions certification test procedures. For almost all of the tested samples, the average carbon monoxide (CO) emission factors were about seven times higher than the limits for Euro-3 certification. No motorcycle fell within the Euro-3 certification limit on CO emissions. 125 cc engine displacement volume motorcycles, which are dominant in Tehran, have the most total unburned hydrocarbons and CO emission rates, and they have less nitrous oxides (NO X ) emission rates and fuel consumption compared to those of larger engine volume motorcycles. Calculation of fuel-based emission factors and moles of combustion products shows that about 40% of fuel consumed by 125 cc engine volume motorcycles burns to incomplete combustion products. This proportion is lower for larger engine volume motorcycles. Approximation of relative air–fuel ratio results shows very rich combustion in selected motorcycles. Using a carburetor fuel supply system, low engine compression ratio, aging, and no catalyst could be reasons for high emission rates. These reasons could possibly result in high ultrafine particles emission rates from motorcycles. Comparison of total motorcycle pollutant emissions to that of passenger cars from previous studies in Tehran shows that motorcycles contribute to pollutant much higher than their contribution to the total fleet or total travels.

An assessment of gasoline motorcycle emissions performance and understanding their contribution to Tehran air pollution

The city of Tehran, the capital of Iran, has been facing severe air quality problems. The air quality of Tehran has been stated as unhealthy over one-third of year during the last two decades. According to the last emission inventory of Tehran for the base year of 2013 mobile sources contribute by about 6, 46, 98, 87, and 70% of total primary SOx, NOx, CO, VOC and PM emission. A number of policies have been implemented in Tehran during the last two decades to tackle the air quality issue. Concentrated mostly on transportation sector, these policies aimed to improve fuel quality and emission performance of vehicles. Nevertheless, there is no quantified evaluation regarding the effectiveness of such policies. In order to address the air pollution problem, a comprehensive policy package called Tehran comprehensive clean air action plan have been developed. This study quantifies the impacts of these policies on pollutants emission from mobile sources in Tehran using the emission inventory approach. Furthermore, the mobile source emission inventory of Tehran is updated considering monthly temperature and humidity changes. The results show that after implementation of Tehran clean air act, the emission of CO, VOC, NOx and PM will reduce by 20, 19, 14 and 17%, respectively. The most effective policies are shown to be bus and minibus renovation in case of PM emissions, and implementation of LEZ on passenger cars and motorcycles, taxis renovation and catalyst replacement in case of other air pollutants.

Evaluation of Tehran clean air action plan using emission inventory approach

Nerve repositioning surgery is one of the treatments chosen for the patients with edentulous posterior atrophic mandible. Like any other treatments, this therapy has its advantages and disadvantages, indications and contraindications. The most important complication of this procedure is neurosensory disturbance. This problem may occur at different stages of the treatment. One common time when nerve damage happens is when the nerve is located outside the canal and drilling and insertion of the implant are performed. Accordingly, this report describes a simple and feasible method to retract and protect nerves outside the canal during the treatment of nerve transposition. This will reduce the risk of nerve damage.

/pdf/nerve-retraction-during-inferior-alveolar-nerve-4txx1x0pdk.pdf

Nerve Retraction During Inferior Alveolar Nerve Repositioning Procedure: A New Simple Method and Review of the Literature.

A comparison of light-duty vehicles' high emitters fractions obtained from an emission remote sensing campaign and emission inspection program for policy recommendation

• Projection of passenger cars fleet stock and activity using limited available data. • Passenger cars stock grows 70% by 2035 while activity of fleet stays stable. • Upgrading emission standards cuts 65% of gaseous air pollutants emissions by 2035. • Promotion of CNG bi-fuel cars cause no improvement in curbing air pollutants emissions. • Cutting fuel subsidies is the sole policy that limits PM 2.5 emissions growth to 27%. Passenger cars (PCs) are a major contributor to urban air pollution, greenhouse gas emissions, and energy security challenges in megacities in developing countries because of their high growth potential. Since the PC fleet changes through time, the projection of air pollutant emissions from PCs is essential for effective emission reduction policymaking. However, the extensive amount of data and proper models are required for this purpose that are not available in many developing countries. Hence, this study develops multiple econometric and emission models and integrate them into a framework to simulate the future stock and activity of PCs and projects PCs’ air pollutants and CO 2 emissions and fuel consumption in the megacity of Tehran by 2035. Various data treatments and estimations are used in response to poor transport-related data availability at the city-level. Eight alternative scenarios are considered to assess the effectiveness of different fuel consumption and emission reduction policies. Projections show that the PC stock will grow 70% by 2035 and reach 5.4 million while the activity level stays stable. Annual gasoline consumption of PCs passes 5.8 billion liters and CO 2 and PM 2.5 emissions elevate by 62% and 76%, respectively, under the business-as-usual scenario. Based on the results, implementation of stricter emission standards cuts 65% of gaseous emissions while promotion of compressed natural gas bi-fuel cars has no benefit in reducing air pollutants emissions. Cutting fuel subsidies is the most effective policy to limit PM 2.5 and CO 2 emissions, and fuel consumption growth by controlling the activity level of the fleet. 

Amin Hassani

Papers

An assessment of gasoline motorcycle emissions performance and understanding their contribution to Tehran air pollution

Evaluation of Tehran clean air action plan using emission inventory approach

Nerve Retraction During Inferior Alveolar Nerve Repositioning Procedure: A New Simple Method and Review of the Literature.

A comparison of light-duty vehicles' high emitters fractions obtained from an emission remote sensing campaign and emission inspection program for policy recommendation

Projection of passenger cars’ air pollutants and greenhouse gas emissions and fuel consumption in Tehran under alternative policy scenarios