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<p>Environmental initiatives are constantly discussed in the media as industrialisation causes irreversible damage to the planet and people's health. This environmental damage is inherently caused by multiple factors such as economic and population growth and increased consumption across the globe. This work aims to understand the impact of population well-being and economic growth on the environment in different cultural contexts and how to reduce these impacts. Multiple datasets, between 2010 and 2020, from five different countries located in different geographical regions and with different socioeconomic backgrounds were collected to achieve this goal. The dataset was subjected to relevant techniques and mathematical modelling to extract the necessary knowledge to reveal solutions to humanity's various environmental challenges. Some solutions emerging from the data processing include increased investment in environmental education, dissemination of sex education, and awareness of economic constraints on family reproduction, ultimately leading to lower consumption.</p>

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Novel predictors for waste generation evolution: a mathematical approach: could a math model answer the waste generation?

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月28日

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  • Rita de Cássia Mendonça Sales-Contini,
  • Francisco José Gomes Silva,
  • Isabel Mendes Pinto,
  • Naiara Poli Veneziani Sebbe,
  • Ana Margarida Fonseca Macedo Teixeira,
  • Maria Teresa Pereira,
  • Ana Rita Fernandes

摘要

Environmental initiatives are constantly discussed in the media as industrialisation causes irreversible damage to the planet and people's health. This environmental damage is inherently caused by multiple factors such as economic and population growth and increased consumption across the globe. This work aims to understand the impact of population well-being and economic growth on the environment in different cultural contexts and how to reduce these impacts. Multiple datasets, between 2010 and 2020, from five different countries located in different geographical regions and with different socioeconomic backgrounds were collected to achieve this goal. The dataset was subjected to relevant techniques and mathematical modelling to extract the necessary knowledge to reveal solutions to humanity's various environmental challenges. Some solutions emerging from the data processing include increased investment in environmental education, dissemination of sex education, and awareness of economic constraints on family reproduction, ultimately leading to lower consumption.