### 1. Introduction

_{2}S) is a colorless, flammable, very toxic and dangerous gas with rotten egg smell. The main way of exposure is inhalation and can swiftly be absorbed by the lungs. The Human can smell the odor of H

_{2}S at low concentration in the air. H

_{2}S as an irritant and a chemical asphyxiate influences on the control nervous system and oxygen utilization and at the low concentration and irritates the nose, eyes, throat and respiratory system [5, 6].

_{2}S) control is a major concern in the operation of existing landfills as well as in the design of future landfills for complying with the odor standard [7]. The odor emission rate depends on several factors, such as the thickness of the cover, the age of the waste, type of cover, the landfill moisture. The odor emission is affected by the wind speed, wind direction, atmospheric conditions, temperature and topographic conditions of the region [8].

_{2}S of a wastewater treatment plant based on its environmental concentrations and meteorological parameters. Hanna et al. [10] examined the predicted air pollutant concentrations by AERMOD and ISC3 models for the 5 field data series, and the results indicated that the AERMOD predictions was closer to experimental data.

_{2}S. The sandy soil amended with lime and the fine concrete were most effective for control H

_{2}S emission. Xu et al. [12] checked the emission rate of H

_{2}S from a landfill with the different landfill cover material. They indicated that the compost, yard trash and soil amended with quicklime and calcium carbonate covers attenuated H

_{2}S emission rate.

_{2}S and 22 VOCs using ISCST3 to forecast, hourly concentration of odor. Their results indicated that the short term average of three of VOCs namely ethyl mercaptan, methyl mercaptan and H

_{2}S did exceed their odor threshold. Latos et al. [13] measured the H

_{2}S concentration at the different locations during the summer by a portable device in a wastewater treatment plant in Greece and used AERMOD Gaussian model to estimate maximum odor concentration.

_{2}S gas at different locations in Florida landfill and estimated the emission rate by using the modeling method and then calculated the H

_{2}S buffering distance by AERMOD model. Rood [15] reviewed the efficiency of the diffusion modeling software such as AERMOD. He measured the ratio of the simulated to the field and calculating the differences in percentages. The ratio varied between 5% to 85% of cases that indicate the suitability of the AERMOD model.

_{2}S from landfills has not sufficiently been discussed in terms of experimental and mathematical studies.

_{2}S have not been sufficiently addressed and the results of study of different researchers are inconsistent. The vital health effects from a low level and chronic exposure have not still been reported [16]. Nonetheless, the exposure to H

_{2}S in concentrations of 10 ppm to 500 ppm may negatively influence the central nervous system, respiratory and blood issues, especially vulnerable populations such as children with asthma [17, 18].

_{2}S concentrations in the downwind of the Kahrizak landfill during the winter and summer seasons. The measurements were compared with each other to demonstrate the environmental situation in the observed data. Afterwards, we employed the AERMOD and ISCST3 models to estimate the H

_{2}S concentrations at the upwind and downwind. The results were assessed using the observed data to reveal the suitable model for estimating H

_{2}S emission.

### 2. Materials and Methods

### 2.1. The Study Area

^{2}and located in the south of Tehran, Iran [19]. The geographic coordinate of the study area is 35° 27′ 52″ N and 51° 19′ 19″ E. The elevation of the complex varies from 1,020 m to 1,060 m [3]. The prevailing wind directions are westerly and northwesterly winds. The average annual temperature varies from −5°C to 40°C. The annual mean precipitation and evaporation are 240 mm and 250 mm, respectively [20].

### 2.2. Field Measurement of Atmospheric H_{2}S

_{2}S concentration, the variation of the methylene blue after exposure to the ambient air was analyzed (Jacobs method) [20]. Using a sampling pump in a flowrate between 1 to 1.5 L/min, the air was bubbled through 45 mL absorption solution in a macro impinger. The sampling time varied between 30 to 45 min. The sampling pump was universal PCXR8, manufactured by SKC United Kingdom.

_{2}S concentration was obtained using a spectrophotometer (DR 2800) at 670 nm wavelength [23].

### 2.3. Dispersion Models

##### (1)

$$\begin{array}{c}C=\frac{Q}{2\pi {\sigma}_{y}{\sigma}_{z}\overline{u}}exp\left(-\frac{{y}^{2}}{2{\sigma}_{y}^{2}}\right)\\ \left\{exp\left(-\frac{{(z+{H}_{e})}^{2}}{2{\sigma}_{z}^{2}}\right)+exp\left(-\frac{{(z-{H}_{e})}^{2}}{2{\sigma}_{z}^{2}}\right)\right\}\end{array}$$*C*is the concentration (μg/m

^{3}) at (x, y, z) and

*Q*is the emission rate (μg/s.,

*σz*and

*σy*are the vertical and horizontal spread parameters, which are functions of the distance (X) from emission, and atmospheric stability class and

*u*is the average wind speed in (m/s),

*z*is the vertical distance above the ground in (m),

*y*is the horizontal distance from the centerline of the plume (m),

*H*is the effective height of the stack (m).

##### (2)

$$C=\frac{{Q}_{P}}{\pi {\sigma}_{y}{\sigma}_{z}u}exp\left(-\frac{{y}^{2}}{2{\sigma}_{y}^{2}}\right)exp\left(-\frac{{H}^{2}}{2{\sigma}_{z}^{2}}\right)$$##### (3)

$$C=\frac{2{Q}_{L}}{\sqrt{2\pi}{\sigma}_{z}u}\text{exp}\left(-\frac{{H}^{2}}{2{\sigma}_{z}^{2}}\right)$$##### (4)

$$C=\frac{{Q}_{A}}{2\pi u}{\int}_{X}\frac{V}{{\sigma}_{y}{\sigma}_{z}}\left({\int}_{Y}exp\hspace{0.17em}\left[-\frac{{y}^{2}}{2{\sigma}_{y}^{2}}\right]dy\right)dx$$*C*is the downwind pollutant concentration (g/m

^{3}),

*Q*

_{p}is the point source pollutant emission rate (g/s),

*Q*

_{L}is line source pollutant emission rate (g/ms).

*Q*

_{A}is the area source odor emission rate (g/m

^{2}s),

*σ*

*and*

_{y}*σ*

*are the Pasquill-Gifford plume spread parameters based on stability class,*

_{z}*u*is the average wind speed at pollutant release height (m/s).

*H*is the effective height above ground of emission source (m).

*V*is the vertical term used to describe vertical distribution of the plume and

*x*is the upwind direction (m), and

*y*the cross wind direction (m).

*u*

^{*}), Monin-Obukhov length (

*L*), convective velocity scale (

*w*

^{*}), temperature scale (θ

^{*}), mixing height (

*z*

*) and surface heat flux (*

_{i}*H*). Therefore, the vertical profiles of wind speed (

*u*), lateral and vertical turbulence fluctuations (σ

_{v}, σ

_{w}), potential temperature gradients (

*dθ*/

*dz*) and potential temperatures (θ) can be computed [26, 29]. AERMAP uses gridded terrain data to analyze a representative terrain influence height (

*h*

*) in each receptor location.*

_{c}*h*

*can specify the dividing streamline height. In addition, AERMAP presents the receptor’s location (*

_{c}*x*

*,*

_{r}*y*

*), its height above mean sea level (*

_{r}*z*

*) and*

_{r}*h*

*. AERMOD applies the processed data from AERMET and AERMAP to obtain concentrations of the pollutant (Eq. (5)).*

_{c}##### (5)

$${C}_{T}\{{x}_{r},{y}_{r},{z}_{r}\}=f.{C}_{C,S}\{{x}_{r},{y}_{r},{z}_{r}\}+(1-f)\hspace{0.17em}{C}_{C,S}\{{x}_{r},{y}_{r},{z}_{p}\}$$*C*

*{*

_{T}*x*

*,*

_{r}*y*

*,*

_{r}*z*

*} is the total concentration;*

_{r}*C*

_{C}_{,}

*{*

_{S}*x*

*,*

_{r}*y*

*,*

_{r}*z*

*} is the contribution from the horizontal plume state in convective (*

_{r}*C*) and stable (

*S*) condition.

*C*

*{*

_{CS}*x*

*,*

_{r}*y*

*,*

_{r}*z*

*} is the contribution from the terrain – following state.*

_{p}*f*is the plume state weighting function; {

*x*

*,*

_{r}*y*

*,*

_{r}*z*

*} is the coordinate representation of a receptor, which*

_{r}*z*

*measured relative to stack base elevation.*

_{r}*z*

*=*

_{p}*z*

*−*

_{r}*z*

*is the height of a receptor above local ground and*

_{t}*z*

*is the terrain height at a receptor (in flat terrain*

_{t}*z*

*= 0). A complete and comprehensive explanation of the AERMOD can be found in [26].*

_{t}^{TM}, includes EPA’s AERMOD and ISCST3 models. The meteorological data is the backbone of the meteorological processor, which entails wind speed, wind direction, precipitation, station pressure, dew point, temperature, relative humidity and sky cover. The meteorological data was obtained from Imam Khomeini International Airport, located in the distance of 16.5 km from the complex and the altitude of 990 m from the sea level.

### 2.4. Model Efficiency

^{2}), Index of agreement (d) and Nash

**-**Sutcliffe coefficient (E), which are shown in Eq. (6) to (8) [30–32]:

##### (6)

$${R}^{2}=\frac{{(\sum ({O}_{i}-\overline{O})\hspace{0.17em}({P}_{i}-\overline{P}))}^{2}}{\sum {({O}_{i}-\overline{O})}^{2}\sum {({P}_{i}-\overline{P})}^{2}}$$##### (7)

$$d=1-\frac{{\sum}_{i=1}^{N}{({O}_{i}-{P}_{i})}^{2}}{{\sum}_{i=1}^{N}{(|{P}_{i}-\overline{O}|+|{O}_{i}-\overline{O}|)}^{2}}$$##### (8)

$$E=1-\frac{{\sum}_{i=1}^{N}{({P}_{i}-{O}_{i})}^{2}}{{\sum}_{i=1}^{N}{({O}_{i}-\overline{O})}^{2}}$$*O*

*is the observed concentration;*

_{i}*P*

*is the predicted concentration;*

_{i}*N*is the number of stations and

*Ō*is the mean field concentrations. While the results of R

^{2}, d and E approach to one, the model efficiency are very well.

##### (9)

$$MG=exp(\overline{ln\hspace{0.17em}{C}_{o}}-\overline{ln\hspace{0.17em}{C}_{p}})=exp\overline{\left(ln\left(\frac{{C}_{o}}{{C}_{p}}\right)\right)}$$*C*

*and*

_{o}*C*

*represent the measured and estimated concentrations, respectively. The value of 1 for MG, VG and FAC2 shows the perfect performance of the model. FB and MG are measures of mean relative bias and indicate only systematic errors, whereas NMSE and VG are measures of mean relative scatter and reflect both systematic and unsystematic (random) errors.*

_{P}### 3. Results and Discussion

### 3.1. Field Concentrations

_{2}S concentrations in the winter were generally higher than the summer, which demonstrated that the temperature might not be a crucial factor affecting the gas emission. Williams [34] reported that the weather changes might not be effective in the bacteria activities and consequently gas emission rate at the depths of landfill.

_{2}S is 20 ppm and the maximum concentration for 10 min. exposure is 50 ppm [35]. According to the Massachusetts Environmental Protection Organization, an hourly and 8 h limits of H

_{2}S concentration are 30 and 15 ppb, respectively [36]. The station 1 was located near to the Landfill and refinery, where the average measured H

_{2}S concentration was 119.58 ppb. This concentration did not meet the Massachusetts standard. While the detected H

_{2}S in the other stations met the Massachusetts standard.

### 3.2. H_{2}S Emission Rate

_{2}S emissions. The inflowrate, influent and effluent chemical oxygen demand (COD) in the leachate treatment were 1,400 m

^{3}/d, 55.5 g/L and 0.8 g/L, respectively. Therefore, the removal rate of COD was 98.5%. According to Youssefi [37], the emitted biogas could be 0.52 L per 1 g removed of COD. Therefore, the daily production of biogas from the leachate treatment plant could be 728 m

^{3}/d, which H

_{2}S contribution might vary between 0.728 m

^{3}/d to 7.28 m

^{3}/d. Due to the density of H

_{2}S (which is 1.36 g/L), the H

_{2}S emission rates varied between 0.11 to 0.011 g/s. In 2016, the total gas emission from the landfill could be estimated around 14*10

^{6}m

^{3}and the contribution of H

_{2}S varied between 0 to 1%. Therefore, H

_{2}S emission rate from the landfill might be assumed between 0 to 6 g/s. The emission rate of H

_{2}S using Lang-gem software was obtained 1.1 g/s [37].

_{2}S emission rates, as shown below:

- Scenario 1: Emission from the landfill (g/s) = 1.1; Emission from the leachate treatment plant (g/s) = 0.095

- Scenario 2: Emission from the landfill (g/s) = 1; Emission from the leachate treatment plant (g/s) = 0.09

- Scenario 3: Emission from the landfill (g/s) = 0.7; Emission from the leachate treatment plant (g/s) = 0.07

- Scenario 4: Emission from the landfill (g/s) = 0.65; Emission from the leachate treatment plant (g/s) = 0.07

#### 3.2.1. AERMOD output

_{2}S in the sources varied between 100–117 μg/m

^{3}in the summer and between 200–205 μg/m

^{3}in the winter (Fig. 1). R

^{2}, d and E values between predicted and observed data in the summer were 0.98, 0.98 and 0.94, respectively. While, the mentioned values in the winter were 0.96, 0.99 and 0.96, respectively. Therefore, the predictions of the model were acceptable and robust.

#### 3.2.2. ISC output

_{2}S in the summer and winter were 123 μg/m

^{3}and 171 μg/m

^{3}, respectively (Fig. 2). R

^{2}, d and E values between predicted and observed data in the summer were 0.96, 0.98 and 0.94, respectively. While, the mentioned values in the winter were 0.98, 0.98 and 0.95, respectively. Therefore, the predictions of the model were acceptable and robust.

^{2}, d and E for AERMOD and ISCST3 models demonstrated the acceptable performance of both model in the prediction of H

_{2}S emissions from the landfill and treatment plant. Nonetheless, the values of MG, VG, FAC2, FB and NMSE represented a relatively better performance of ISCST3.

_{2}S in the downwind would reach zero at a distance of 35 km from the sources in AERMOD, and at 38 km in ISCST3 (Fig. 3). The AERMOD predicted upwind concentrations of H

_{2}S would reach zero at a distance of 30 km. While the ISCST3 predicted upwind concentrations would reach zero at the distance of 35 km from the sources.

_{2}S around the airport. In addition, using the applied methodologies, the other odor compounds’ influence can be evaluated; this study is helpful in future planning for locating other landfill; the urbanization development brings the population to nearby of landfills. To assess the odor pollution impacts on human health, the study of its emission is inevitable. Consequently, the results are of interest to a great variety of stakeholders such as decision makers, municipal jurisdiction and health bodies.

_{2}S would reach to 8 μg/m

^{3}. While in the normal condition, the maximum concentration was predicted 117 μg/m

^{3}.

### 4. Conclusions

The field measurement during the summer and winter indicated that the temperature changes did not affect the concentration of H

_{2}S in the surrounding area of the complex. H_{2}S levels around the leachate treatment plant were significantly higher than other areas, which might be attributed to the anaerobic treatment of leachate. The average concentration in the summer and winter were 94.7 ppb and 145 ppb, respectively. The average concentration in the other stations was less than 10 ppb.The coefficient of determination (R

^{2}), Index of agreement (d) and Nash**-**Sutcliffe coefficient (E) between the predictions and field measurements were more than 0.94, which shows a good consensus between models performance and observed data. Nevertheless, the coefficients demonstrated that the AERMOD predictions were more robust in comparison with ISCST3.The MG, VG, FAC2, FB and NMSE indicators showed that the ISCST3 predictions were slightly more reliable than in comparison with the AERMOD results. Such that, the AERMOD results were more overestimated.

According to the AERMOD model, the maximum predicted concentrations of H

_{2}S was observed in the leachate treatment plant and was equal to 117 μg/m^{3}in the summer and 205 μg/m^{3}in the winter and in the case of ISCST3 it was equal to 123 μg/m^{3}in the summer and 171 in the winter.The concentration of H

_{2}S in the wind direction reached zero at a distance of 35 km from sources in AERMOD and in the ISCST3 reached zero at a distance of 38 km. In the opposite direction, this distance was 30 km for AERMOD and 35 km for ISCST3.According to the standard of 1 h concentrations of H

_{2}S by the Massachusetts Environmental Protection Agency, which is 30 ppb; in an approximate distance of 2 km around the leachate treatment plant, the amount of H_{2}S was higher than the standard.