Zero Waste Initiative

Overview

Zero Waste offers a systematic approach to avoiding or reusing waste with the aim of minimizing its disposal into landfills. It's a strategic resource management paradigm that is becoming increasingly relevant in today's world, where the need for sustainable development and efficient resource utilization is evident.

Collaborative Development

Core Issues

• Technological Innovations: What new technologies can be utilized for waste collection, sorting, and processing to achieve zero waste?
• Educational Programs: How can public awareness regarding the importance of Zero Waste programs be raised and encourage the adoption of new eco-friendly habits?
• Waste Management in Cities: What urban management strategies can facilitate the successful implementation of Zero Waste programs in large cities?

Methodology

• Understanding People: Gather insights from personal experiences and data obtained from open sources to analyze stakeholders' perspectives on waste management.
• Defining the Issue: Analyze statements from various stakeholder groups to identify key challenges and opportunities in waste management.
• Generating Ideas and Making Progress: Engage in collaborative brainstorming sessions to devise innovative solutions. Test these ideas through simulations or small-scale projects, continuously iterating based on feedback and data analysis.

Problem Identification

Be aware that the full description of this milestone you can find by refer to README

Explore the problem statement based on our team's personal experiences, categorized by the countries where we reside.

• Group Member Experience

Actionable Research Questions:

Throughout the project, we refined our research questions for greater specificity:

1. What is the average per capita household food waste in the studied region, and how does it vary across different income brackets or urban and rural areas?
2. What is the collective economic impact of food waste on a global scale, and how does it affect different regions economically?
3. Are there correlations between the economic prosperity of a region and its success in implementing effective food waste reduction initiatives?

🌱 Problem Identification, Domain Understanding, and Statement

Our project addresses challenges in implementing Zero Waste programs, with a particular focus on cultural and geographical factors hindering the adoption of new consumption practices and waste management strategies within the food industry.

Our team works with global data and analysis, with a focus on countries where team members currently reside.

Data Collection

Be aware that the full description of this milestone you can find by refer to README

Non-Technical Explanation of Domain Modeling

Domain modeling in our Zero Waste project involves creating a simplified representation of key aspects related to waste management. It's a visual guide, akin to a map, helping us understand how economic indicators, cultural differences, and geography influence waste generation and management practices.

This non-technical model serves as a blueprint, aiding communication, identifying challenges, and guiding decision-making for effective waste reduction strategies.

Data Collection and Cleaning Scripts

For transparency and replication, we provide all scripts for data collection and cleaning, covering the entire process, including data partitioning.

Our Research Work

Engaged in Data Science research, our team focuses on implementing zero waste programs, leveraging practical experience and modern data analysis methods to contribute significantly to the field.

For more details on our experience, refer to our_experience and README.

Data Analysis

Be aware that the full description of this milestone you can find by refer to README

The project analyzes the relationship between economic indicators and waste generation using data from the 2021 UNEP Food Waste Index Report.

Non-technical explanation of our findings

Our exploration of the relationship between economic indicators and global waste generation patterns yielded several insights. The dataset, covering diverse countries, allowed us to observe trends and variations in economic factors and waste production.

Key Findings

The overall model does not explain a significant proportion of the variance in the total waste estimate (R-squared = 0.156). Additionally, individual economic indicators do not exhibit strong statistical significance in predicting the total waste production.

Technical description of analysis

Results of the data analysis conducted using Jupyter Notebook can be found here.

Technical explanation of our findings

1. Household Food Waste Across Regions:

   • Poland and the USA exhibit similar per capita household food waste.
   • Canada and Denmark show higher estimates, indicating advanced waste management systems.

2. Global Economic Impact of Food Waste:

   • Global average food waste volume is around 3.17 million tonnes.
   • Higher development level countries like the USA have larger volumes of food waste.

3. Relationship Between Economic Prosperity and Food Waste Reduction Initiatives:

   • Sensitivity to economic indicators suggests regions with higher economic development may have more resources for waste reduction initiatives.
   • Supplementary research is recommended for a comprehensive understanding.

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For a detailed analysis, refer to the Full Project Analysis in the project repository.

Zero Waste Analysis for [Country Name]: Key Questions and Aspects for Consideration

Conclusion:

Adapting methods based on ongoing discoveries ensures a dynamic and thorough analysis approach. Answers for Actionable Research Questions.

Please be aware that the analysis is currently underway, and any updates or improvements will be incorporated into future milestones.

Communicating Results

Be aware that the full description of this milestone you can find by refer to README

Selecting the Target Audience:

Our focus is on Nonprofit Organizations dedicated to addressing social and environmental issues, specifically in the realm of food waste. We aim to engage organizations with significant influence on groups contributing to food waste, such as households, food service, and retail.

Key Suggested Strategies for Nonprofit Organizations to Reduce Food Waste:

• Promoting Conscious Consumption: Tailor information campaigns based on country-specific waste patterns identified through analysis of the relationship between living standards and food waste.

• Supporting Restaurants and Catering Establishments: Advocate for tailored programs in regions exhibiting higher waste estimates.

• Developing Technology to Track and Manage Leftover Food: Emphasize the importance of technology by aligning proposals with the machine learning modeling ideas for waste reduction demonstrated in the project analysis.

• Monitoring and Evaluation: Encourage organizations to adopt analytical approaches for waste reduction, considering regional waste disparities.

Key Data Requests for Nonprofit Organizations:

Our project analysis was carried out based on the latest public information found in various sources. The limit year of information found is 2021. We need the latest data from 2022 onwards, namely:

• Detailed Yearly Waste Breakdown: Requesting country-specific, year-wise waste production data to enhance the precision of our analysis and predictions.

• Recent Emission Reduction Programs Data: Soliciting information on recent emission reduction programs in the food industry to understand their potential influence on waste reduction predictions.

• Socio-Cultural Factors Influencing Food Waste: Requesting data related to socio-cultural factors affecting food waste behaviors in different countries for a more nuanced analysis.

• Machine Learning Model Training Data: Requesting additional training data for our machine learning model, to enhance its predictive capabilities.

Important message:

Based on the analysis, we have developed set of strategies that will lead to a reduction in the amount of food waste. Also, to provide more accurate and extensive analysis, we need more data presented here, and any food waste data after 2022. By collaboration, we will make significant progress in the area of food waste.

Final Presentation Event

1. A 1-minute pitch for your solution.
2. A 3-minute presentation of your group’s process from beginning to end including challenges you faced, lessons you learned, and any advice you have for future learners.
3. A retrospective for this milestone.

Contributing

We welcome contributions from individuals and organizations passionate about waste management and sustainability. To contribute, please follow these guidelines:

• Fork the repository and create a new branch for your contributions.
• Make your changes, ensuring they adhere to project guidelines and standards.
• Submit a pull request detailing the changes you've made and why they're beneficial.

Thank you for helping us make a positive impact on waste management!