Toggle Offcanvas
...
Global Government Tenders

Most trusted source for Tendering Opportunities and Business Intelligence since 2002

Building A Model For Classifying Domestic Solid Waste In Communes And Supporting Equipment For Classifying Domestic Solid Waste In Nam Nhun Town, Nam Nhun District In 2024

Phong Tai nguyen va Moi trường huyện Nậm Nhùn tỉnh Lai Chau Vietnam has Released a tender for Building A Model For Classifying Domestic Solid Waste In Communes And Supporting Equipment For Classifying Domestic Solid Waste In Nam Nhun Town, Nam Nhun District In 2024 in Environment and Pollution. The tender was released on Nov 20, 2024.

Country - Vietnam

Summary - Building A Model For Classifying Domestic Solid Waste In Communes And Supporting Equipment For Classifying Domestic Solid Waste In Nam Nhun Town, Nam Nhun District In 2024

Deadline - Dec 05, 2024

GT reference number - 97950536

Product classification - Sewage, refuse, cleaning and environmental services

Organization Details:

  Address - Vietnam

  Contact details - 565656565

  Tender notice no. - 76454545

  GT Ref Id - 97950536

  Document Type - Tender Notices

Notice Details and Documents:

Description - notice_title: Building A Model For Classifying Domestic Solid Waste In Communes And Supporting Equipment For Classifying Domestic Solid Waste In Nam Nhun Town, Nam Nhun District In 2024local title:: Xây dựng mô hình phân loại chất thải r n sinh hoạt trên địa bàn các xã và hỗ trợ trang thiết bị phân loại chất thải rắn sinh hoạt trên địa bàn thị trấn Nậm Nhùn, huyện Nậm Nhùn năm 2024Contract Type: : ConsultancyNet Budget LC: : 1885945000.0 est_amount: 1885945000.0 lot_details: 1: Department of Natural Resources and Environment, Nam Nhun district, Lai Chau province, 2: Department of Natural Resources and Environment, Nam Nhun district

Gt Ref Id - 97950536

Deadline - Dec 05, 2024

Share share

Similar Tenders :

Create Account

Why Us

3,00,000 +

Users

190 +

Countries Covered

5,00,000 +

Agencies Tracked

50,000 +

Notices Daily

90 Million +

Database