GCF approves Pakistan’s climate change project


Islamabad—The Green Climate Fund (GCF) has approved Pakistan’s US $36 Million Climate Change Adaptation project responding to Glacial Outburst in Northern Pakistan.
GCF approved the project in its 14th board meeting, held in Republic of Korea on October 14. The Ministry of Climate Change together with United Nations Development Programme (UNDP) had submitted this project for Board’s approval, said a news release.
The Indian board member attempted to reject Pakistan’s proposal but the other 23 Board Members, who considered the project fit for approval, out rightly rejected these claims and approved the project. Pakistan also holds an alternate seat at the board (with Saudi Arabia) and was able to effectively mitigate the false perceptions that were being propagated by the Indian member.
The approved project will impact the lives of thousands of people who are living in constant danger of periodic glacial outbursts in the Northern Pakistan. The project will address climate change impacts and Glacial Lake Outbursts Floods (GLOF) risks by preventing loss of lives and community infrastructure based on a holistic approach in all 7 districts of Gilgit-Baltistan and 5 districts in Khyber Pakhtunkhwa province, thus, contributing to a climate-resilient sustainable development in the long-term.
The proposed project will benefit approximately 700,000 people on average directly (5 districts in KP and 7 in GB) and about 30 million indirect beneficiaries, of whom half are women and girls.
The project, thus, benefits about 15% of the total population of Pakistan, estimated at 185 million as at 2014 (World Bank data). The project outcome will strengthen adaptive capacity and reduce exposure to climate risks posed by climate change impacts and GLOF risks through the increased technical capacity of provincial and line departments to integrate CC and GLOF risks into development plans, tools and budgets and by expanding the Pakistan Meteorological Department’s Early Warning System (EWS) based on hydrological modeling and flood scenarios.—APP