Purchase Orders Over €20,000 Q4 2023

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2023	Boland Landscaping Ltd	Landscape Maintenance	Purchase Order	€56,163.15
31 Dec 2023	Boland Landscaping Ltd	Landscape Maintenance	Purchase Order	€26,449.94
31 Dec 2023	Beechill Bulbs Ltd	Plants Shrubs & Trees	Purchase Order	€41,135.24
31 Dec 2023	Ballyfin Construction Ltd	General Building Work (L.A.Housing)	Purchase Order	€20,895.35
31 Dec 2023	Axe Forestry Ltd	Capital Contract	Purchase Order	€123,519.78
31 Dec 2023	Austen Studio Ltd T/A Austin Associates	Landscape Consultancy	Purchase Order	€32,499.99
31 Dec 2023	Arkil Ltd	Road Surface Recycling	Purchase Order	€29,954.05
31 Dec 2023	Arkil Ltd	Road Surface Recycling	Purchase Order	€49,480.04
31 Dec 2023	Arkil Ltd	Road Surface Recycling	Purchase Order	€150,380.69
31 Dec 2023	AP Envecon Ltd t/a EnvEcon Decision Support	Economic - Marketing Consultancy	Purchase Order	€49,000.00
31 Dec 2023	An Taisce The National Trust for Irl	Training-Other	Purchase Order	€26,600.00
31 Dec 2023	An Post	Postage	Purchase Order	€136,429.74
31 Dec 2023	Absolute Landscaping Ltd	Landscape Maintenance	Purchase Order	€29,453.25
31 Dec 2023	Absolute Landscaping Ltd	Landscape Maintenance	Purchase Order	€26,774.65

^* Payment date may be the end of the reporting quarter when the entity does not publish an exact date.

How to read these figures

These are reported values from published purchase order and payment records — not verified cash paid, and not total spending by this organisation. A row may be a purchase order, a payment, or another reported transaction; the source files often do not say which.

Coverage and quality vary. Some fields are blank, supplier names are free text (the same firm can appear under many labels), and descriptions are inconsistent rather than a controlled taxonomy. An amount alone says nothing about value for money and it may or may not include VAT.

Records are retrieved from each organisation’s published files such as spreadsheets, PDFs, and other formats of uneven quality. Extraction techniques (including automated parsing) can introduce gaps, misreads, or incomplete rows when source layout or quality is poor. Treat the data as a starting point for investigation, not a definitive ledger.

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