Sustainable development and pollution: the effects of CO2 emission on population growth, food production, economic development, and energy consumption in Pakistan

Rehman A., Ma H., Ozturk I., ULUCAK R.

Environmental Science and Pollution Research, cilt.29, sa.12, ss.17319-17330, 2022 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 12
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1007/s11356-021-16998-2
  • Dergi Adı: Environmental Science and Pollution Research
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Environment Index, Geobase, MEDLINE, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.17319-17330
  • Anahtar Kelimeler: CO2 emission, Population growth, Food production, Environmental pollution, Energy usage, Economic growth, CARBON-DIOXIDE EMISSIONS, ENVIRONMENTAL KUZNETS CURVE, RENEWABLE ENERGY, CLIMATE-CHANGE, NONRENEWABLE ENERGY, STIRPAT MODEL, FINANCIAL DEVELOPMENT, ECOLOGICAL FOOTPRINT, TIME-SERIES, CHINA
  • Kayseri Üniversitesi Adresli: Hayır

Özet

© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Population growth has been a leading driver of global CO2 emissions over the last several decades. CO2 emission and greenhouse gas emissions are a key issue in the world that affects food production and also causes the climate change. The core purpose of this study was to inspect the influence of carbon dioxide emission to population growth, food production, economic growth, livestock and energy utilization in Pakistan. The STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) model with the extension of an ARDL (Autoregressive Distributed Lag) method was utilized to demonstrate the linkage amid variables. Outcomes during short-run investigation reveal that variables population growth, economic growth, rural population growth, livestock production uncovered a productive association with CO2 emission. Furthermore, via long-run population growth, economic growth, rural population growth, livestock production and energy utilization have positive interaction with CO2 emission, while the variables food production and urban population growth demonstrated an adverse influence to CO2 emission during long- and short-run interaction. Similarly, the error correction model exposed that population growth, economic progress, livestock and energy utilization have constructive interaction to CO2 emission, while the variables food production, urban and rural population growth exposed an adverse impact to CO2 emission. On the basis of this analysis, we will address the strategic consequences.