کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
11033287 1622607 2018 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimation of the generation rate of different types of plastic wastes and possible revenue recovery from informal recycling
ترجمه فارسی عنوان
برآورد نرخ تولید انواع مختلف ضایعات پلاستیکی و بازده احتمالی درآمد حاصل از بازیافت غیر رسمی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات مهندسی ژئوتکنیک و زمین شناسی مهندسی
چکیده انگلیسی
Plastic waste generation is an inevitable product of human activities, however its management faces challenges in many cities. Understanding the existing patterns of plastic waste generation and recycling is essential for effective management planning. The present study established a relationship between plastic waste generation rate and the identified socioeconomic groups, higher socioeconomic group (HSEG), middle socioeconomic group (MSEG), and lower socioeconomic group (LSEG) of the study area (Dhanbad, India). For identification of the socioeconomic groups, four different socioeconomic parameters were considered (total family income, education, occupation and type of houses). The information related to the identified parameters were obtained using questionnaire survey conducted in the selected households. One week plastic waste sampling was carried out in the households of all the socioeconomic groups. The plastic waste generated in the study area was 5.7% of the total municipal solid waste. In terms of total plastic waste generation rate, it was found that HSEG had maximum (51 g/c/d) and LSEG had minimum (8 g/c/d) generation rate. The present study area does not have any formal waste recycling system. Thus, the amount of plastic waste recovered and the revenue generated from recycling of plastic waste by the active informal recyclers (waste pickers, itinerant waste buyers and scrap dealers) in the study area have been evaluated. Additionally, three non-linear machine learning models i.e., artificial neural network (ANN), support vector machine (SVM) and random forest (RF) have been developed and compared for the prediction of plastic waste generation rate.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Waste Management - Volume 79, September 2018, Pages 781-790
نویسندگان
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