Publications·November 30, 2024
This UNESCAP working paper takes stock of how the Philippines can use satellite and ground-based remote sensing to improve air-quality management. It lays out the country’s pollution burden and institutional landscape, scans existing EO (Earth Observation) use cases, documents the rollout and current status of Pandora spectrometers and the GEMS geostationary mission, and offers a practical action agenda to move from research pilots to operational, decision-ready products. Headline context: annual PM₂.₅ exposure ~19 µg/m³ in 2023 (≈3.8× WHO guideline); an estimated >32,000 deaths in 2019 and economic losses ≈ US$44.8 billion (2019, ~12% of GDP) underscore the stakes for data-driven mitigation.
Pollution sources, trends, and policy backbone
Urban pollution is dominated by transport and industry, with mobile sources contributing ~65% of urban air pollution. Diesel public utility jeepneys are singled out as major soot emitters—estimated at ~94% of urban soot mass—and coal-fired power remains a key SOₓ and PM source with sizable health costs. Long-range transport mixes biogenic, natural and anthropogenic aerosols into Metro Manila’s plume. The Philippines has advanced a broad policy stack: the Clean Air Act (RA 8749, 1999), Euro IV (and tighter) fuel/vehicle standards, emission-control and monitoring requirements, plus climate-aligned instruments (NCCAP, NDCs, NREP) that create co-benefits for air quality. UNEP’s scorecard credits the country with progress on 8 of 9 assessed air-quality policy targets (solid-waste burning remains only partially fulfilled).
Ground monitoring and research ecosystem
The DENR-EMB operates the most extensive regulatory network—~119 stations across manual and continuous monitors for criteria pollutants. Complementary capabilities include PNRI black-carbon monitors, AERONET at four sites, and the region’s first TCCON node for column greenhouse gases. Several field campaigns—notably MACE 2015 (vehicular aerosol characterisation in Metro Manila) and CAMP2Ex 2019 (NASA–Philippine partners)—have deepened understanding of aerosol processes and regional transport. Academia (UP Diliman, Manila Observatory, DLSU et al.) and city partners run additional PM networks and source-apportionment studies that provide valuable calibration/validation for satellite products.
Remote sensing that’s already in use
On the space side, analysts tap MODIS/VIIRS (fires, AOD), TROPOMI/OMI/GOME-2 (NO₂, SO₂, HCHO), Himawari-8/9 (high-cadence imagery), MERRA-2 (reanalyzed PM₂.₅), and CO₂ missions (GOSAT, OCO-2). Studies span AOD–PM mapping, burning & FRP relationships, NO₂/SO₂ time series, and health linkages (e.g., VIIRS fires + MERRA-2 PM₂.₅ vs respiratory morbidity). Global Forest Watch/FIRMS add near-real-time fire detection; 2022 saw ~62.9 kha burned and ~39.8 Mt CO₂ emissions from fires (with Palawan prominent), illustrating the value of EO for enforcement and prevention. PhilSA’s Space Data Dashboard already publishes AQ layers and hazard maps and plans the MULA EO satellite (launch targeted for 2025), which can enrich national feeds.
Knowledge gaps EO can close (and how)
Unmonitored areas. Build monthly/annual PM₂.₅ maps by fusing AOD (MODIS/MISR/SeaWiFS), CTMs (e.g., GEOS-Chem), and ground-bias correction (e.g., GWR/ML), validated with AQMN and AERONET. Early NCR attempts highlight the need for denser ground data and meteorology to improve model skill.
SLCPs & precursors. Operationalise NO₂, SO₂, HCHO, O₃ monitoring with TROPOMI/GEMS/Pandora to diagnose sources and chemistry (and to complement climate actions).
Long-term trends & policy evaluation. Use multi-year EO-ground blends to evaluate outcomes of vehicle/fuel standards, coal-plant controls, and waste-burning rules—nationally and for LGU plans (e.g., Quezon City AQMP).
Transboundary transport & airsheds. Combine trace-gas columns, AOD and trajectories to delineate airsheds, quantify cross-border episodes, and inform ASEAN/EANET/ESCAP cooperation. CALIOP-based analyses already show long-range aerosol transport into Metro Manila.
Vulnerability & equity. Merge high-resolution PM/trace-gas fields with socio-economic indicators to prioritise interventions for at-risk communities.
Agricultural/peat fires. Shift from hotspot counts to burn-area + FRP emissions (stratified by fuel/crop) to target prevention and evaluate policies.
Pandora & GEMS — where the Philippines stands now
Pandora (PGN/Pandora Asia Network). Four sites have been installed and as of 19 Dec 2024 all four are operational (Manila Observatory–Quezon City; University of San Carlos–Cebu; DENR-EMB PEMU–Puerto Princesa; MMSU–Batac). Current data availability focuses on tropospheric columns (NO₂, HCHO, H₂O, O₃); Direct-Sun total columns are not yet available and many records lack “assured high-quality” flags—so QA/QC routines and uptime stabilisation are the near-term priorities. Early diurnal analyses show the expected NO₂ morning/late-afternoon peaks (traffic) and midday O₃ and HCHO elevations (photochemistry), with Ilocos Norte behaving as a regional background site.
GEMS (geostationary). Trainings and case studies demonstrate good temporal coherence with TROPOMI NO₂ (improved with 2×2 binning); SO₂ plumes from Mt. Bulusan were captured; and gap-filling (2-D/3-D) improves O₃ fields. However, coarse GEMS pixels may miss micro-hotspots (e.g., localized burning), reinforcing the need for blends with Pandora/ground and ML/statistical bias-corrections. The roadmap includes systematic cal/val against AERONET & Pandora, error detection, kriging/distance-weighting harmonisation with ground sensors, and operational pipelines for near-real-time products (AOD/NO₂/SO₂/HCHO/O₃, UV index).
Municipal & governance lens
The Philippines’ decentralised LGU system (provinces → cities/municipalities → barangays) positions mayors as pivotal “last-mile” users of EO-ground intelligence for alerts, compliance targeting, and programme evaluation. Examples of LGU-led environmental planning (e.g., Santa Rosa’s multi-year programmes) show how city-level platforms could blend GEMS/Pandora with ground data to deliver public guidance and enforcement support. PhilSA–KOICA/NIER partnerships under PAPGAPI/Pandora Asia Network are already accelerating capacity and technology transfer.
Recommendations — a practical action agenda
Build the national EO–AQ platform. Automate ingest of GEMS/TROPOMI/OMI, AERONET, Pandora, AQMN, and MODIS/VIIRS fires; publish near-real-time maps, archives and open APIs with uncertainty metadata and bilingual documentation.
Harden Pandora operations. Standardise SOPs/QA-QC, ensure spares & tracker maintenance, and co-locate with reference PM₂.₅/NO₂/SO₂/O₃ at strategic sites.
Operationalise GEMS workflows. Bias-correct with Pandora/AERONET/ground, and stand up episode tools (fires, volcanic SO₂, local vs transported diagnostics) to support advisories and enforcement.
Invest in people. Recurring training for agencies and universities (EO ingest, ML bias-correction, WRF/CTM, nowcasting/forecasting); help-desk & shared code repositories.
Embed EO in policy cycles. Update national/LGU plans to name specific EO products and indicators; use EO-ground blends to evaluate Clean Air Act measures, fuel/vehicle standards, waste-burning controls, and power-sector actions; expand data sharing via EANET/ASEAN/ESCAP channels.
Public products that people use. Simple, reliable apps/dashboards for real-time AQ, with plain-language guidance and clear uncertainty, to drive awareness and protective behaviour.
Key words
Remote sensing; GEMS; Pandora (PGN); PM₂.₅ mapping; NO₂/SO₂/HCHO/O₃; AOD; fires & FRP/burn-area; airsheds & transboundary transport; QA/QC & SOPs; PhilSA/DENR-EMB/PNRI/Manila Observatory; LGUs & decision support.