Developing a carbon footprint model and environmental impact analysis of municipal solid waste transportation: A case study of Tehran, Iran

The greenhouse gas emitted due to transportation is the third greatest emitter globally, and its impact has become a threat to the environment, public health, and economic development. Waste transportation is excluded in studies of waste management despite its significant environmental impacts such as global warming and human toxicity. The objective of this study is to develop a quantification model to estimate the carbon footprint of waste transportation and environmental impact assessments in three categories applied in Tehran using IPCC guidelines. In Tehran, light and heavy vehicles ran on diesel fuel. Data on fuel and waste characteristics were provided by Tehran's department of transportation and municipality, respectively. In this study, transport-related emissions are 8.47 k tonCO2eq/y, and the carbon footprint of waste transportation is 93.57 g of CO2 eq per ton of waste transported (t.km), which is relevant to three main parameters: the amount of waste transported annually, the freight shipped from the temporary station to the disposal landfill site, and fossil fuels consumed. Also, an environmental impact assessment in three categories - human health (global warming, abiotic depletion, and ozone layer depletion), resources (fossil fuels), and ecosystem quality (acidification and eutrophication) - using SimaPro, a Life Cycle Assessment (LCA) tool is presented. Global warming (3.49 kg CO2 eq/t MSW), human toxicity (0.95 kg 1,4-DB eq/t MSW), and freshwater aquatic eco-toxicity (0.04 kg 1,4-DB eq/t MSW) have the greatest impact among categories. Sensitivity analysis of the effective parameters allows us to conclude one of the potential implications of this study would be the introduction of natural gas or biogas-based trucks replacing diesel fuel vehicles to improve air quality and mitigate the greenhouse gas emission.Implications: This paper addresses the significant issue of global warming, particularly in Iran, a developing country that ranks among the top contributors to greenhouse gas emissions. The study emphasizes the importance of evaluating emissions across various sectors such as electricity, waste, etc., Specifically, in this paper we focus on developing a model to quantify the environmental impact resulting from the combustion of fossil fuels in vehicles, focus on the metropolitan city of Tehran as a case study. By examining the waste transportation process, we aim to provide decision-makers with effective strategies to mitigate the environmental consequences. In this paper, we develop a simple quantification term of Carbon Footprint to calculate total greenhouse gas emission of waste transportation process. Carbon Footprint is a fraction which, its numerator is total greenhouse gas emission and its denominator is total waste transported in traveled distance. Effective parameters have been investigated and based on parameters and emission factors taken out of IPPC, the carbon footprint model have been developed. The total greenhouse gas emission of this study and the carbon footprint has estimated at 8.47 k tonCO2eq/y and 93.57 g CO2eq/t.km respectively. Furthermore, the paper explores additional environmental impacts beyond global warming, including abiotic depletion, ozone layer depletion, acidification, eutrophication, human toxicity, photochemical oxidation, and freshwater aquatic eco-toxicity. Using SimaPro software these eight impact categories have been estimated. in this study we identify fossil fuel consumption, traveled distance, and mass transported are the primary parameters influencing greenhouse gas emissions and the carbon footprint. To reduce emissions in the waste transportation system, we suggest promoting renewable biofuels, highlighting Iran as a suitable candidate due to its high percentage of biodegradable material in municipal solid waste. Additionally, the study assesses nonrenewable energy and mineral extraction using the IMPACT 2002+ V2.15/IMPACT 2002+ method, revealing that global warming (100 years), human toxicity (100 years), freshwater aquatic eco-toxicity, nonrenewable energy, and mineral extraction have the most significant impacts on the municipal solid waste transportation system. Overall, this research underscores the need for quantifying environmental impacts and recommends strategies to mitigate them in waste transportation processes, particularly in developing countries like Iran.

The effect of airtightness required in building energy conservation regulations on indoor and outdoor originated pollutants

The contradiction of indoor air quality (IAQ) and energy conservation by isolating the indoor environment from the outdoor through airtightness is one of the challenges of the building sector. The key issue is, what are the optimum airtightness limits that can ensure IAQ in naturally ventilated buildings, taking into account the paradoxical effect of house leakages on the infiltration of outdoor pollutants and accumulation of indoor-generated pollutants? For this purpose, the effect of different levels of airtightness required in energy-compliant, low-energy, and very low-energy buildings on the concentration of two pollutants with outdoor and indoor origin, PM2.5 and formaldehyde, respectively, were studied. This study used a multizone model, CONTAM(W), which was validated using measured data to study the distribution of selected pollutants in a typical relatively old dwelling, to investigate the situation in Iran. Subsequently, we conducted simulations based on different combinations of scenarios for airtightness, user behavior, source strength, and meteorological parameters. The results showed that increasing the airtightness from the baseline scenario (ACH50 = 11.11/h) to 3, 1.5, and 0.75 in closed window conditions reduced the PM2.5 by 15%, 38%, and 58%, respectively, and elevated formaldehyde by 23%, 77%, and 169%, correspondingly. Under normal outdoor PM2.5 pollution, indoor formaldehyde levels exceeded the permissible limit only in closed window conditions, and IAQ remained acceptable in other scenarios. However, there is no indication that IAQ can be ensured by any degree of airtightness under severe outdoor air pollution, demanding specific solutions, such as those proposed in this work.

Current Status and Future Forecast of Short-lived Climate-Forced Ozone in Tehran, Iran, derived from Ground-Based and Satellite Observations

In this study, the distribution and alterations of ozone concentrations in Tehran, Iran, in 2021 were investigated. The impacts of precursors (i.e., CO, NO₂, and NO) on ozone were examined using the data collected over 12 months (i.e., January 2021 to December 2021) from 21 stations of the Air Quality Control Company (AQCC). The results of monthly heat mapping of tropospheric ozone concentrations indicated the lowest value in December and the highest value in July. The lowest and highest seasonal concentrations were in winter and summer, respectively. Moreover, there was a negative correlation between ozone and its precursors. The Inverse Distance Weighting (IDW) method was then implemented to obtain air pollution zoning maps. Then, ozone concentration modeled by the IDW method was compared with the average monthly change of total column density of ozone derived from Sentinel-5 satellite data in the Google Earth Engine (GEE) cloud platform. A good agreement was discovered despite the harsh circumstances that both ground-based and satellite measurements were subjected to. The results obtained from both datasets showed that the west of the city of Tehran had the highest averaged O₃ concentration. In this study, the status of the concentration of ozone precursors and tropospheric ozone in 2022 was also predicted. For this purpose, the Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) approach was implemented to predict the monthly air quality parameters. Overall, it was observed that the SARIMA approach was an efficient tool for forecasting air quality. Finally, the results showed that the trends of ozone obtained from terrestrial and satellite observations throughout 2021 were slightly different due to the contribution of the tropospheric ozone precursor concentration and meteorology conditions.

Particulate matter concentrations and characterization in urban subway system-case study Tehran, Iran

The present work aims to evaluate the indoor and outdoor air quality in the stations of the Tehran subway system. In this study, the particulate sampling of the four Tehran subway stations was conducted in March-July 2018 during different seasons to determine indoor and outdoor PM10 and PM2.5 concentrations and elemental composition. The samples were analyzed to determine 11 elements such as Pb(Lead), Cd(Cadmium), Ni(Nickel), Co(Cobalt), Mn(Manganese), Zn(Zink), Fe(Iron), Cu(Copper), As(Arsenic), Al(Aluminum) and Cr(Chromium) qualitatively. The experimental results indicated that the average concentrations of both PM10 and PM2.5 in indoor stations (platforms) were approximately 2-5 times higher than those in the outdoors (ambient air). In addition, PM10 and PM2.5 concentrations exceeded the daily-standard values (US-EPA; PM10 = 50 µg.m-3, PM2.5 = 25 µg.m-3) in 100% indoor measurements and 84% outdoor measurements. Moreover, the average indoor PM10 and PM2.5 concentrations in weekday values were 1.4 and 1.5 times higher than those measured on weekends, which may be related to the lower frequency of trains. Further, indoor and outdoor correlation of PM10 concentrations (Pearson r = 0.6) was more than that of PM2.5 concentrations (Pearson r = 0.2), indicating the additional sources for PM2.5 in indoor stations. Additionally, the average PM2.5 / PM10 ratio was 0.52 for indoor measurements and 0.34 for outdoors, indicating that PM10 particles were the dominant particle type in both sampling areas and passengers in indoor stations exposed to higher PM2.5 concentrations than those in outdoor stations. Finally, based on elemental analysis, Fe was the most enriched element in indoor and outdoor PM10 and PM2.5 samples. The concentration of Fe ranged from 16 to 81 µg.m-3 in indoor stations and 0.6 to 2.5 µg.m-3 in outdoors. Other enriched elements were Al, Cu, Zn, and Mn, respectively.

Tropospheric Ozone in Tehran, Iran, during the last 20 years

Air pollution and its effects on human health and the environment are one of the main concerns in urban areas. This study focuses on the distribution and changes in the concentrations of ozone and its precursors (i.e., NO, NO₂ and CO) in Tehran for the 20-year period from 2001 to 2020. The effects of precursors and meteorological conditions (temperature, wind speed, dew point, humidity and rainfall) on ozone were investigated using data from 22 stations of the Air Quality Control Company (AQCC) and meteorological stations. Regression models were applied to evaluate the dependence of ozone concentration on its precursors and meteorological parameters based on monthly average values. Finally, the monthly and annual levels of surface ozone and total column ozone were compared during the study period. The results show that the average ozone concentration in Tehran varied substantially between 2001 and 2008, and decreased after 2008 when stringent air quality control measures were implemented. The highest average concentration of ozone occurred in the southwest of Tehran. Although mobile and resident sources play an important role in the release of precursors, the results also indicate a significant effect of meteorological conditions on the changes in ozone concentration. This study is an effective step toward a better understanding of ozone changes in Tehran under the changing influence of precursors and meteorological conditions.

Estimation of short-lived climate forced sulfur dioxide in Tehran, Iran, using machine learning analysis

This paper presents a time-series analysis of SO₂ air concentration and the effects of particulates (either PM_2.5 and PM₁₀) concentrations and meteorological conditions (relative humidity and wind speed) on SO₂ trend in Tehran for the period from 2011 to 2020. The source data were obtained from 21 monitoring stations of Air Quality Control Company and meteorological stations in Tehran. To predict the status of future concentration of SO₂, PM_2.5 and PM₁₀, a Box-Jenkins ARIMA approach was used to model the monthly time series. Considering the whole period of ten years, a somewhat downward trend was noted for SO₂ air concentration, even though a slight rising trend was observed in 2020 year. Monthly sulfur dioxide concentrations showed the lowest value in June and the highest value in January. Seasonal concentrations were lowest in spring and highest in winter. Then, in the ArcGIS software, the IDW method was used to obtain air pollution zoning maps. As a result, the highest average concentration of SO₂ occurred in the north and southwest of Tehran. In the last step, Relations between the SO₂ concentration and particulate matters and relative humidity and wind speed were calculated statistically using the daily average data. We finally concluded that the combined effect of particulate matters and relative humidity with the increasing role of Sulfur dioxide overcomes the decreasing role of wind speed. This study can contribute to a better understanding of the SO₂ air pollution in Tehran affected by meteorological conditions and the rapid urbanization and industrialization, followed by the possible combustion of fuel oil in power plants and health problems.

Evaluation of short-lived atmospheric fine particles in Tehran, Iran

Fine particles (PM_2.5) have adverse impacts and risks on air quality and human health. The present research focuses on the concentrations of PM_2.5, air quality index (AQI), and assessment of hospital admissions due to COPD attributed to PM_2.5 particle levels in Tehran during the last 10 years from 2011 to 2020. The effects of meteorological parameters (i.e., wind speed, humidity, and temperature) and AQI on PM_2.5 concentrations were examined using data from 21 active monitoring stations of the Air Quality Control Company (AQCC) and Mehrabad Meteorological Station. The health impact assessment of PM_2.5 in terms of hospital admissions due to chronic obstructive pulmonary disease (COPD) was obtained by the AirQ_2.2.3 model. Based on the results, the annual average PM_2.5 concentrations decreased from 2011 through 2020. The results also show a significant effect of meteorological data on the changes in PM_2.5 particle concentration. We also noticed that reduction of annual PM_2.5 concentration from 38.55 (AQI = 104.08) in 2011 to 28.59 μg m⁻³ (AQI = 83.87) in 2020 could prevent 779 (by about 70%) premature deaths, and the estimated number of excess cases human respiratory system attributed to PM_2.5 at central relative risk (RR) during the last decade was 6158 persons. Also, air quality got from unhealthy for sensitive groups of people to moderate air quality. Finally, any reduction in concentrations of PM_2.5 in Tehran can reduce the number of hospital admissions due to COPD significantly. The results of investigations on PM_2.5 particles have shown the need for the national clean air program policies and the necessity of urgent actions to improve the air quality to human health in Tehran.

Changes in short-lived climate pollutants during the COVID-19 pandemic in Tehran, Iran

This study investigates the changes of short-lived climate pollutants and other air pollutants during the COVID-19 pandemic in Tehran, Iran. Concentrations of air pollutants were obtained from 21 monitoring stations for the period from 5 January 2019 to 5 August 2019, representing normal conditions unaffected by COVID-19, and the period 5 January 2020 to 5 August 2020, i.e., during the COVID-19 crisis. We concentrated our analysis on three time windows (23 February 2020 to 15 March 2020, 18 March 2020 to 3 April 2020, and 5 April 2020 to 17 April 2020) during the lockdown when different sets of measures were taken to limit the spread of COVID-19. In comparison to the period not affected by COVID-19 measures, mean concentrations of pollutants were increased during the first lockdown period; when the number of COVID-19 patients increased sharply compared to the other periods, the mean surface concentrations of NO₂, SO₂, and CO were decreased and concentrations of other pollutants (i.e., O₃, PM₁₀, and PM_2.5) were increased during the second lockdown period compared to the corresponding period in 2019. In the third period, the mean concentrations were decreased compared to the corresponding period in 2019. For the full period, decreases in mean concentrations of O₃, NO₂, SO₂, CO, and PM₁₀ and increases in PM_2.5 were observed during the COVID-19 crisis, compared to 2019. Overall, the strongest reductions, 12% and 6%, respectively, were observed for CO and NO₂, pointing to reduced emissions from traffic as a result of lockdown measures. The concentrations of other pollutants changed little, suggesting that the lockdown measures did not result in strong changes in the emissions from stationary sources.

Health impact and related cost of ambient air pollution in Tehran

Ambient air pollution represents one of the biggest environmental risks to health. In this study, we estimated the avoidable mortality burden attributable to ambient air pollution in Tehran, and derived the economic impact associated with these health effects. Using PM_2.5 data from ground-level air pollution measurements in Tehran, we estimated PM_2.5 exposure for 349 neighborhoods in Tehran, by the Environmental Benefits Mapping and Analysis Program (BenMAP-CE). We considered five scenarios related to PM_2.5 levels: an increase to 35 μg/m³; a reduction to 25 μg/m³; a reduction to 15 μg/m³; a reduction to 10 μg/m³ (the WHO's air quality guideline value); and a full roll-back, assuming a reduction to 2.4 μg/m³. All scenarios used 2017 p.m._2.5 levels as a starting point. Using the concentration response function of the Global Exposure Mortality Model (GEMM), we estimated a total of 7146 (95% CI: 6596-7513) adult (age ≥25 years) deaths attributable to PM_2.5 in 2017. The leading causes of death were ischemic heart disease (3437; 95% CI: 3315-3516), stroke (886; 95% CI: 693-1002), lower respiratory infections (531: 95% CI: 414-589), chronic obstructive pulmonary disease (364; 95% CI: 271-420), and lung cancer (274; 95% CI: 236-298). The estimated total annual economic benefit (2017) of reducing PM_2.5 concentration levels to 2.4 μg/m³ was USD 0.591 (95% CI: 0.447-0.624) billion per year, using the value of a life year (VOLY) approach, and USD 2.894 (95% CI: 2.671-3.043) billion per year, using the value of a statistical life (VSL) approach.