پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,500 |
| تعداد مشاهده مقاله | 124,091,196 |
| تعداد دریافت فایل اصل مقاله | 97,195,145 |
ارزیابی ریسک آلاینده‌های هوای منتشره در پایانۀ مسافری بیهقی با روش مدل‌سازی | ||
| محیط شناسی | ||
| مقاله 9، دوره 41، شماره 1، فروردین 1394، صفحه 97-105 اصل مقاله (976.72 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jes.2015.53903 | ||
| نویسندگان | ||
| مجید شفیع پور مطلق1؛ علیرضا پرداختی2؛ مریم معجری* 2 | ||
| 1استادیار گروه مهندسی محیط‌زیست، دانشکدۀ محیط‌زیست دانشگاه تهران | ||
| 2استادیار گروه مهندسی محیط‌زیست، دانشکدۀ محیط‌زیست، دانشگاه تهران | ||
| چکیده | ||
| گسترش شهرها و نیاز به وسایل حمل و نقل عمومی موجب شکل‌گیری پایانههای مسافری شده است که به علت تجمع و تردد تعداد زیادی از خودروها پتانسیل آلودگی هوای ناشی از انتشار آلاینده‌های هوا در پایانههای مسافری برای مسافران، رانندگان و کارکنان پایانه وجود دارد. در این پژوهش به بررسی آلودگی هوای ناشی از انتشار آلاینده‌های هوای NO2، PM10، CO و SO2 در پایانۀ بیهقی در کلان‌شهر تهران با روش مدل‌سازی ریاضی با مدل‌های IVE و BREEZE AERMOD پرداخته شده است. ابتدا با جمع‌آوری آمار و اطلاعات پایۀ مربوط به خودروها، تردد و زمان حضور در پایانه‌ها، انتشار آلاینده‌های هوای CO، NO2، SO2 و PM10 از طریق مدل IVE استخراج شد. تخمین غلظت آلاینده‌های هوا با استفاده از میزان انتشار آلاینده‌های به‌دست‌آمده از مدل IVE، با مدل‌سازی از طریق BREEZE AERMOD انجام شده است. ارزیابی ریسک استنشاق آلاینده‌های هوا بر اساس نتایج خروجی مدل بالا با استفاده از روش ارائه‌شده از سوی RAIS صورت گرفته است. اندیس مخاطرۀ تأثیر غیرسرطانی استنشاق آلاینده‌های هوا در پایانۀ مسافری بیهقی رانندگان 737/3، کارکنان محوطه 838/4 و کارکنان اداری 717/3 است که بیش از حد آستانه بوده است و این افراد در معرض مخاطرات ناشی از آلاینده‌ها به خصوص منو اکسید کربن و دی‌اکسید نیتروژن‌اند. مسافران با اندیس مخاطرۀ 202/0 در خطر کمی قرار دارند. با ارزیابی ریسک سرطانی مشاهده شد خطر ابتلای 5 نفر از کل افراد طی عمر خود در پایانه به انواع بیماری‌های سرطانی افزایش می‌یابد. | ||
| کلیدواژه‌ها | ||
| ارزیابی ریسک؛ آلودگی هوا؛ پایانۀ مسافری؛ مدل IVE؛ مدل AERMOD | ||
| عنوان مقاله [English] | ||
| Risk Assessment of Air Pollutants Emissions in Beihaghi Terminal By Modeling | ||
| نویسندگان [English] | ||
| Majid Shafie-Pour1؛ Alireza Pardakhti2؛ Maryam Mejari2 | ||
| 1Assistant professor, Faculty of Environment, University of Tehran | ||
| 2Assistant professor, Faculty of Environment, University of Tehran | ||
| چکیده [English] | ||
| Introduction Public transportation system is the perfect solution to organize transportation in the city. This system reduces the demand for private car or taxi area provides economic savings. Public transport will not only reduce the use of private vehicles, but it will reduce traffic and air pollution. The public transportation system of buses to be Extremist as one of the most efficient public transportation systems mentioned. Bus terminals play an important role in the regulation of urban transportation. However, these terminals have the potential to become sources of air pollution. The mathematical model can easily estimate emissions of terminal vehicles and concentrations of pollutants. With alternative methods of sampling and measurement model can more quickly and cost less to review existing situation and to anticipate the future. If needed, it can be subject to examination and sampling. The purpose of this study is to assess the risks facing those in the terminal , including drivers , office workers and travelers to the area , and air pollutants CO, NO2, SO2 present at the terminals on modeling and PM10 Payments. Materials and Methods IVE model is designed to estimate emissions from motor vehicles intended to focus control strategies and transportation planning on those that are most effective, predict how different strategies will affect local emissions and measure progress in reducing emissions over time. Input data of this model consist of vehicle types, number of vehicles, their presence time in terminal, engine type, age, exhaust control technology, fuel type and speed. Moreover the essential geographical and meteorological information that were collected by documents, questionnaires and statistical modeling. According to the traffic in the terminal and at different hours of the day, the average amount of estimated emissions of air for NO2, PM10, CO and SO2 were determined which is one of the BREEZE AERMOD inputs. Terminal resource modeling for air pollutants to a level that is unevenly spread is considered. In this way, surface coordinates and the release of three terminals are needed. For more accurate determination of concentrations of air pollutants concentration field is required. Concentrations of air pollutants in the desired period of time without taking into account the effects of air pollutants at the terminal air pollution monitoring stations near the terminals were estimated. Exposure to the range of terminal points needed to determine how the output data set is analyzed . Finally the required parameters and output in period of time were set. After completing all input data, running the model with known concentrations of air pollutants were estimated. Two groups of people directly exposed to air pollutants in the terminal. A group containing of drivers and terminal staff that long at all periods of their career are in contact with the concentrations of air pollutants and the other group contain of passengers with different patterns of exposure to air pollutants. In this research, risk assessment method of RAIS from USEPA is used. Discussion of Results and Conclusions Emissions of air pollutants and their concentrations in the IVE model and BREEZE AERMOD model have been used for risk assessment. Air pollution emissions are calculated by IVE model. The output data of IVE model is used as the input data for the BREEZE AERMOD model which the concentration of pollutants are estimated by this model. Finally the cancer and non-cancer risk of CO, NO2, SO2 and PM10 concentrations is calculated By the RAIS, which is achieved by the use of non-cancer and cancer risk assessment of pollutants, quantitative assessment of risks from inhaled pollutants and populations that are affected. Searches performed for the pollutants NO2, CO and SO2 gradients cancer is currently not available. Only the cancer risk of PM10 has been calculated by its cancer slope factor. After calculation of the cancer risk for the population, the cancer risk is multiplied by the number of people in contact. Inhalation of hazardous air pollutants per passenger in Beihaghi terminal, HQinhale results for the different groups are shown in Table 1. Table 1- Cancer and non-cancer risk assessment of air pollutants in the Beihaghi terminal. Chemical Chronic RfC (mg/m3) Concentration (ug/m3) Inhalation Ambient Air Non-carcinogenic CDI Inhalation Ambient Air Carcinogenic CDI Inhalation Ambient Air HQ Inhalation Ambient Air Risk Drivers CO 0.023 2500 0.6850 294 1.32 - NO2 0.047 923 0.1610 69.2 2.38 - SO2 0.262 80 0.0219 9.39 0.0369 - PM10 5.000 170 0.0466 20 0.0041 0.00264 Site Personnel CO 0.023 2360 0.6470 277 2.81 - NO2 0.047 333 0.0912 39.1 1.94 - SO2 0.262 80 0.0219 9.39 0.0837 - PM10 5.000 80 0.0219 9.39 0.0044 0.00282 Official Personnel CO 0.023 2360 0.49600 212 2.16 - NO2 0.047 333 0.06990 30 1.49 - SO2 0.262 80 0.01680 7.2 0.0641 - PM10 5.000 80 0.01680 7.2 0.0034 0.00216 Passenger CO 0.023 2360 0.0269 3.85 0.117 - NO2 0.047 333 0.0038 0.54 0.0809 - SO2 0.262 80 0.0009 0.13 0.0035 - PM10 5.000 80 0.0009 0.13 0.0002 0000390. The non-carcinogenic hazard quotient estimated for CO express that the most HQ is for site personnel is 2.81 and is more than unit. If the quotient is less than 1, then the systemic effects are assumed not to be of concern; if the hazard quotient is greater than 1, then the systemic effects are assumed to be of concern. HQ for official personnel is 2.16 and drivers is 1.32 is more than unity. So these three groups of people are in risk of CO inhalation. The HQ estimated for passengers is 0.117 which is less than unity and they are not in risk of CO inhalation. The NO2 HQ estimated for drivers is 2.367 who are in the most risk in comparison to the other groups. The HQ for site personnel is 1.94 and for official personnel is 1.49, which is more than unity. So these people are in risk for NO2 inhalation in the passenger terminal. The SO2 HQ estimated for drivers is 0.0369, for site personnel is 0.0837, for official personnel is 0.0641 and the passengers is 0.0035, which is less than unity for all groups of people. None of people in the passenger terminal are in the risk for SO2 inhalation non-carcinogenic risk. The PM10 hazard quotient for all groups of people is less than unity and no one is in the non-carcinogenic risk of this pollutant. The hazard index is the sum of hazard quotients. Hazard Index is calculated by summing hazard quotients for each chemical across all exposure routes. Hazard index for the drivers in 3.737, for site personnel is 4.838, for official personnel is 3.718 and for passengers is 0.202. Consequently the site personnel are in great risk. This population is in the open area and exposed to vehicle exhaust emissions. The official personnel and drivers are also prone to the effects of non-carcinogenic risks of these contaminants. Drivers have the same situation to the site personnel but with the different frequency of contact. Official personnel at the terminal work 8 hours a day in the buildings, but due to indirect emissions from vehicles are in lower risks. The risk Index indicates a low risk of inhalation of air pollutants for passengers in the terminal. The CO pollutant has the greatest share of risk which is 58 percent and then the NO2 with the 40 percent share of the pollution risk in the passenger terminal. In this research, risk assessment based on concentrations of inhaled air pollutants modeled by BREEZE AERMOD was estimated. Hazard index for drivers of all air pollutants is 3.737, for site personnel is 4.838, official personnel 3.718 and passengers 0.202. The risk is minimal inhalation of air pollutants for passengers in the terminal. Most people working in the Terminal and the drivers are at the non-cancer risks. Pollutant that creates the greatest share in the risks of the terminal is emission are NO2 and CO. Share of NO2 emission is 64 percent and share of CO emission is 35 percent of the whole pollution in the Terminal. Cancer risk assessment using cancer slope exists only for particulate matter emission. The cancer risk estimates, this value was multiplied by the number of people who are exposed to pollutants. Carcinogenic risk assessment for PM10 is estimated to the population inhaled. The risk of PM10 inhalation for the drivers is 0.00264, meaning that 3 of them may suffer from cancer in their lifetime. Also there is risk for carcinogen illnesses for one of the site personnel and of the passengers in their lifetime. Therefore Most of the cancer risk to drivers which totally for 3 people risk of cancer increases in their lifetime. In general in this terminal the risk of Cancer is increased for 5 people. | ||
| کلیدواژه‌ها [English] | ||
| City Terminal, Air pollution, risk assessment, IVE model, AERMOD model | ||
| مراجع | ||
|
شریفی، م. 1387. بررسی آلودگی هوای ناشی از پایانههای مسافری در بافت شهری اطراف آن، پایان‌نامۀ کارشناسی ارشد، دانشکدۀ محیط‌زیست، دانشگاه تهران. عباس‌پور، م. 1390. مدل‌سازی آلودگی هوا، انتشارات دانشگاه صنعتی شریف. غیاث‌الدین، م. 1373. آلودگی هوا، انتشارات دانشگاه تهران. فرجی‌ملائی، ا.، عظیمی، آ.، پوراحمد، ا. 1391. ابعاد پایداری حمل و نقل عمومی شهری با تأکید بر BRT، یازدهمین کنفرانس مهندسی حمل و نقل و ترافیک ایران. کهرزادی، ا.، انصاری، ا.، رحیمی، ع.، حسن‌زاده، م. 1391. اتوبوس‌ها‌‌ی تندرو (BRT) و نقش آن در توسعۀ پایدار حمل و نقل شهری، اولین همایش ملی بررسی راهکارهای ارتقای مباحث مدیریت، حسابداری و مهندسی صنابع در سازمان‌ها. نجف، پ.، الهی، ح. 1391. بررسی اثر احداث خطوط ویژۀ اتوبوسرانی (BRT) بر میزان انتشار آلاینده‌ها، دوازدهمین کنفرانس مهندسی حمل و نقل و ترافیک ایران.
Adams, H.S, Nieuwenhuijsen, M.J, N Colvile, R. 2001. Determinants of fine particle (PM2.5) personal exposure levels in transport microenvironments, Atmospheric Environment.
EPA 2002. A Review Of Reference Dose and Reference Concenteration Progress, U.S. EPA. EPA/630/P-02/002A.
EPA 2008. Office of Transportation and Air Quality, Idling Vehicle Emissions for Passenger Cars, Light-Duty Trucks, and Heavy-Duty Trucks, EPA420-F-08-025.
Hall, D.J., Spanton, A.M, Dunkerley, F., Bennett, M., Griffiths, R.F. 2000. An Inter-comparison of the AERMOD, ADMS and ISC Dispersion Models for Regulatory Applications, R&D Technical Report P362. ISBN 1 85705 340 0.
IPCS 2004. IPCS risk assessment terminology, World Health Organization, International Programme on Chemical Safety.
IPCS 2009. Principles for modelling dose–response for the risk assessment of chemicals, World Health Organization, International Programme on Chemical Safety.
Shafie-Pour, M., Tavakoli, A. 2013. On-Road Vehicle Emissions Forecast Using IVE Simulation Model, International Journal of Environmental research, 7(2):367-376. ISSN: 1735-6865.
World Health Report 2002. Reducing Risks, Promoting Healthy Life Geneva. | ||
|
آمار تعداد مشاهده مقاله: 2,609 تعداد دریافت فایل اصل مقاله: 1,742 |
||