Abstract

To minimize the fuel consumption and CO2 emission by solid waste pickup trucks and prevent air and soil pollution caused by overflowing waste from wastebins, this study proposed a technological process involving collecting real-time data of wastebin holding amount by infrared sensors, selecting an optimum pickup route by a new bi-criteria decision-making method, and generating display of optimum route for end-users through internet. This study provides a decision-making method for optimizing solid waste pickup routing in both urban and suburban areas. Yet, due to lack of residence committee's consent, I was not able to actually install sensors in the trashcans. Instead, I ran the simulation trials at my home, using self-made bins and varying their distance between each other in each trial to increase variability and approach real life. After examining results of trails, I found out that compared to average route, the optimal route calculated using the program significantly reduced CO2 emission in a year, and residents had less likelihood of encountering funny smell issued from kitchen waste disposed outside of the garbage tank. I believe, in the future, if enough investment and time is allowed, this project can be applied in large scale, solving the inefficiency of waste collection in all the districts across the country with the only cost being purchase of detection sensors.

Introduction

Global warming is caused by emission of greenhouse gases, including CO2 and CH4. CO2 emission from transportation sector was accounted for 28% of the total CO2 emission in cities (Gately, Hutyra, and Wing, 2015). Approaches to reduce CO2 emission from transportation sector include deploying electric cars, optimizing traffic routing, applying carbon capture and storage (CCS) ect. A report The promise of carbon capture and storage, and a Texas-sized call to action by Joe Blommaert showed that CSS is expected in Houston to safely capture and permanently store about 50 million metric tons of CO2 annually by 2030. By 2040, it could be 100 million metric tons. On average, a city generates 292.4 million tons of solid waste per day (EPA: National Overview: Facts and Figures on Materials, Wastes and Recycling). When solid waste generation exceeds the holding capacity of wastebins, overflowing waste falls on the ground as shown in Figure 1 and 2, which may lead to degradation of soil environmental quality over time. Accumulation of municipal waste, especially kitchen waste, often causes unpleasant order and impacts the air quality in residential areas.

Fig.1 -A small-sized, overflowing wastebin with scattered solid waste on the ground

Fig.2 -A large-sized, overflowing wastebin with scattered solid waste on the ground
Therefore, optimizing waste collection routing can reduce energy consumption and CO2 emission, as well as ensure the air quality and soil environmental quality in residential areas. Several software packages are used in waste collection optimization. For example, Sensoneo Route Planning tools, adjusting routes and frequencies brought 63% on costs and 70% fewer pickups (SENSONEO company's report) However, they fail to focus on one certain type of waste: kitchen waste, which easily reacts with chemicals and produces products possibly erosive and having unpleasant ordor. Therefore, this projects aims to address kitchen waste, taking account into three main factors: the height of kitchen waste in the trashcan, the time those waste remains, and the fuel consumption of the refuse truck.

Objectives

The project seeks to achieve the following goals:

  1. reduce fuel consumption and therefore CO2 emission of garbage pickup trucks
  2. reduce the probabilities of odor from overflowing bins