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Santarém
City in Pará, Brazil
Overview
Santarém is a lively city in Pará, Brazil, set along the banks of the Tapajós and Amazon rivers. Known for its unique natural beauty, lively markets, and proximity to stunning beaches like Alter do Chão, it's a hub for eco-tourism and local culture.
Geographic Context
Jurisdiction
Brazil
State
Pará
Population
189,047
Time Zone
America/Sao_Paulo
Coordinates
-2.44°, -54.71°
Key Metrics
Safety Score · estimate
45
Female Safety
45
LGBTQ+ Safety
40
Traffic Safety
35
Food Safety
50
Monthly Cost · estimate
$775
Local Cost
$370
Local Income
$350
Cashless
40
English
15
Temperature
27.6°C
Summer Avg
27.5°C
Winter Avg
26.8°C
Record High
38.3°C
Record Low
22.9°C
Humidity
79%
Precipitation
1918 mm
Internet Speed
251 Mbps
Upload
264 Mbps
Latency
3 ms
City Vibrancy
59
Coworking
0
Cafes
0
Nightlife
7
Parks
52
Transport
0
Walk Score
0
Footways
—
Airport
STM
Distance
10 km
Explore
Data sources
Source-backed data
World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-06.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-05.
Estimates and unverified origins
Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-22.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 63/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.
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