Is it legal to scrape IQAir?

Scraping public air quality data for personal research or non-commercial analysis is generally permitted. However, users should respect the site's robots.txt and avoid high-frequency scraping that could disrupt their service or violate their Terms of Service.

Does IQAir have an official API?

Yes, IQAir offers the AirVisual API which provides structured access to global air quality data. They offer a free tier for community and development use, while higher volume and commercial access require a paid subscription.

How do I avoid getting blocked by IQAir?

The most effective way to avoid blocks is to use residential proxies and rotate your User-Agents. Additionally, implementing a human-like browsing speed with random delays between requests will reduce the likelihood of triggering anti-bot alarms.

How often does the data on IQAir update?

The data is typically updated once per hour, matching the reporting cycles of most global monitoring stations. For most use cases, scheduling your scraper to run hourly is the most efficient approach.

What format can I export IQAir data into?

Using tools like Automatio, you can export the data into structured formats like JSON, CSV, or XML. You can also automate the flow of data directly into Google Sheets or other cloud databases.

Can I scrape historical air quality data?

Yes, IQAir provides historical data for many cities on dedicated history pages. You can scrape these pages to build a timeline of pollution levels, though the depth of history available depends on the specific monitoring station.

Do I need a headless browser to scrape IQAir?

Yes, because the site relies on JavaScript to populate the air quality values, a headless browser like Playwright, Puppeteer, or a tool like Automatio is required to ensure the data is visible before extraction.

Which proxies work best for IQAir?

Residential proxies are highly recommended because they appear as legitimate home users. Static datacenter IPs are easily identified and blocked by the Cloudflare protection IQAir uses.

How to Scrape IQAir Air Quality Data

Learn how to scrape real-time air quality index (AQI), PM2.5, and weather data from IQAir to monitor pollution trends and build health-focused applications.

Start Scraping Free

iqair.comHard

Coverage:GlobalUnited StatesChinaIndiaEuropeSoutheast Asia

Available Data8 fields

TitleLocationDescriptionImagesSeller InfoPosting DateCategoriesAttributes

All Extractable Fields

City NameCountry/RegionAir Quality Index (AQI)Main Pollutant TypePM2.5 ConcentrationPM10 ConcentrationTemperatureHumidityWind SpeedBarometric Pressure7-Day Air Quality ForecastStation GPS CoordinatesHistorical Hourly AQIHealth RecommendationsFire/Smoke Map Data

Technical Requirements

JavaScript Required

No Login

Has Pagination

Official API Available

Anti-Bot Protection Detected

CloudflareBrowser FingerprintingRate LimitingIP BlockingJavaScript Challenges

View API Documentation

About IQAir

Learn what IQAir offers and what valuable data can be extracted from it.

Global Air Quality Monitoring

IQAir is a Swiss-based air quality technology company that operates the world's most comprehensive platform for tracking global air pollution. They aggregate data from over 30,000 monitoring stations, including official government sensors and their own proprietary AirVisual network, providing a real-time global map of air health.

Comprehensive Environmental Data

The platform provides detailed metrics including the US Air Quality Index (AQI), concentrations of specific pollutants like PM2.5, PM10, Ozone (O3), and nitrogen dioxide, alongside meteorological data such as temperature, humidity, and wind speed. It also features city-specific rankings and health recommendations based on current air conditions.

Value for Data Science and Research

Scraping this data is highly valuable for environmental researchers, urban planners, and health-tech developers. It allows for the analysis of long-term pollution trends, the impact of air quality on public health, and the correlation between environmental factors and economic indicators like real estate value or retail foot traffic.

Why Scrape IQAir?

Discover the business value and use cases for extracting data from IQAir.

Real-Time Health Alerts

Scraping allows you to build automated systems that notify sensitive populations when PM2.5 or Ozone levels exceed safe thresholds in specific cities.

Real Estate Market Analysis

Integrate air quality scores into property valuation models to determine how environmental health affects residential appeal and long-term pricing.

ESG and Corporate Compliance

Companies can monitor the air quality around their global office locations to ensure employee wellness and fulfill environmental reporting requirements.

Academic and Climate Research

Gathering historical pollution data across multiple regions helps researchers study long-term environmental trends and the efficacy of local policy changes.

Smart Home IoT Integration

Developers can use scraped AQI data to trigger smart HVAC systems or air purifiers to activate when external pollution levels rise.

Supply Chain Forecasting

Manufacturers of masks and air filters can correlate localized pollution spikes with sales data to optimize inventory distribution and marketing spend.

Scraping Challenges

Technical challenges you may encounter when scraping IQAir.

Advanced Cloudflare Protection

IQAir employs robust Cloudflare security layers that can detect and block non-browser traffic through fingerprinting and behavior analysis.

Dynamic Content Hydration

The website heavily uses JavaScript to render AQI values and interactive maps, meaning standard HTML parsers will often find empty data fields.

Regional Redirection Logic

The site often redirects users to localized subdomains based on their IP address, which can complicate attempts to scrape data for a different region.

High Data Volatility

Air quality numbers are updated hourly, requiring a highly reliable and performant infrastructure to capture temporal trends without missing data points.

Complex DOM Structure

The use of modern frameworks like React results in deeply nested and occasionally changing CSS selectors, which can break fragile scraping scripts.

Scrape IQAir with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

Describe What You Need

Tell the AI what data you want to extract from IQAir. Just type it in plain language — no coding or selectors needed.

AI Extracts the Data

Our artificial intelligence navigates IQAir, handles dynamic content, and extracts exactly what you asked for.

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Point-and-Click Visual Selection: Easily map data fields like AQI, temperature, and specific pollutants by simply clicking on them in the browser interface.

Bypasses Anti-Bot Layers: Automatio handles complex browser fingerprinting and JavaScript challenges natively, making it easier to navigate Cloudflare-protected pages.

Fully Managed Proxy Rotation: Automatic rotation between residential IPs prevents your scrapers from being rate-limited or blacklisted during large-scale data collection.

Cloud-Based Scheduling: Set your scraper to run at precise hourly intervals to match IQAir's update frequency without needing to manage your own servers.

Automated Data Pipelines: Instantly sync scraped air quality data with Google Sheets, webhooks, or external databases for real-time monitoring and analysis.

Start Scraping Free

No credit card requiredFree tier availableNo setup needed

No-Code Web Scrapers for IQAir

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape IQAir. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

Install browser extension or sign up for the platform

Navigate to the target website and open the tool

Point-and-click to select data elements you want to extract

Configure CSS selectors for each data field

Set up pagination rules to scrape multiple pages

Handle CAPTCHAs (often requires manual solving)

Configure scheduling for automated runs

Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Note: IQAir uses Cloudflare; simple requests may be blocked.
# This example demonstrates the structure if anti-bot is bypassed.
url = 'https://www.iqair.com/usa/new-york/new-york-city'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9'
}

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # City title is often in an h1
        city = soup.find('h1').text.strip() if soup.find('h1') else 'N/A'
        # AQI values are usually inside specific status classes
        print(f'City: {city}')
    else:
        print(f'Blocked by Cloudflare: {response.status_code}')
except Exception as e:
    print(f'Error: {e}')

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

●Fastest execution (no browser overhead)
●Lowest resource consumption
●Easy to parallelize with asyncio
●Great for APIs and static pages

Limitations

●Cannot execute JavaScript
●Fails on SPAs and dynamic content
●May struggle with complex anti-bot systems

from playwright.sync_api import sync_playwright

def scrape_iqair_live():
    with sync_playwright() as p:
        # Launching browser with stealth-like settings
        browser = p.chromium.launch(headless=True)
        context = browser.new_context(user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64)...')
        page = context.new_page()

        # Navigate to a specific city page
        page.goto('https://www.iqair.com/usa/new-york/new-york-city', wait_until='networkidle')

        # Wait for the dynamic AQI value element to appear
        page.wait_for_selector('.aqi-value__value')

        # Extract data from the DOM
        data = {
            'city': page.inner_text('h1'),
            'aqi': page.inner_text('.aqi-value__value'),
            'pollutant': page.inner_text('.pollutant-level-wrapper b'),
            'temp': page.inner_text('.weather__detail--temp')
        }

        print(data)
        browser.close()

if __name__ == '__main__':
    scrape_iqair_live()

When to Use

Use when content loads dynamically via JavaScript, or when you need to interact with the page (clicks, scrolls, form fills). Handles modern anti-bot detection better.

Advantages

●Executes JavaScript like a real browser
●Handles SPAs and dynamic content
●Better anti-bot evasion with stealth plugins
●Can take screenshots and PDFs

Limitations

●Slower than HTTP requests
●Higher memory/CPU usage
●More complex to set up

import scrapy

class IQAirRankingSpider(scrapy.Spider):
    name = 'iqair_spider'
    start_urls = ['https://www.iqair.com/world-air-quality-ranking']

    def parse(self, response):
        # Extract data from the global ranking table
        # Note: Scrapy usually needs a JS middleware like scrapy-playwright for this site
        for row in response.css('table.ranking__table tr'):
            yield {
                'rank': row.css('td.rank::text').get(),
                'city': row.css('a.city-name::text').get(),
                'aqi': row.css('td.aqi::text').get(),
                'country': row.css('span.country-name::text').get()
            }

When to Use

Ideal for large-scale crawling projects that need to scrape thousands of pages. Built-in support for rate limiting, retries, and data pipelines.

Advantages

●Built for scale (millions of pages)
●Automatic request throttling
●Built-in data export pipelines
●Middleware system for proxies/headers

Limitations

●Steeper learning curve
●Overkill for small projects
●No native JavaScript rendering

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  try {
    // Emulate a real user to avoid immediate blocking
    await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36...');
    await page.goto('https://www.iqair.com/usa/new-york/new-york-city', { waitUntil: 'networkidle2' });

    // Capture dynamic content
    const result = await page.evaluate(() => {
      return {
        city: document.querySelector('h1')?.innerText,
        aqi: document.querySelector('.aqi-value__value')?.innerText,
        main_pollutant: document.querySelector('.pollutant-level-wrapper b')?.innerText
      };
    });

    console.log(result);
  } catch (err) {
    console.error('Scraping failed:', err);
  } finally {
    await browser.close();
  }
})();

When to Use

Choose this if you're in a Node.js/JavaScript ecosystem or need tight integration with frontend tools. Similar capabilities to Playwright.

Advantages

●Native JavaScript/TypeScript support
●Chrome DevTools Protocol access
●Large ecosystem and community
●Good for JS-heavy projects

Limitations

●Chrome-only (vs Playwright's multi-browser)
●Similar overhead to Playwright
●Less mature stealth options

How to Scrape IQAir with Code

Python + Requests

import requests
from bs4 import BeautifulSoup

# Note: IQAir uses Cloudflare; simple requests may be blocked.
# This example demonstrates the structure if anti-bot is bypassed.
url = 'https://www.iqair.com/usa/new-york/new-york-city'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9'
}

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # City title is often in an h1
        city = soup.find('h1').text.strip() if soup.find('h1') else 'N/A'
        # AQI values are usually inside specific status classes
        print(f'City: {city}')
    else:
        print(f'Blocked by Cloudflare: {response.status_code}')
except Exception as e:
    print(f'Error: {e}')

Python + Playwright

from playwright.sync_api import sync_playwright

def scrape_iqair_live():
    with sync_playwright() as p:
        # Launching browser with stealth-like settings
        browser = p.chromium.launch(headless=True)
        context = browser.new_context(user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64)...')
        page = context.new_page()

        # Navigate to a specific city page
        page.goto('https://www.iqair.com/usa/new-york/new-york-city', wait_until='networkidle')

        # Wait for the dynamic AQI value element to appear
        page.wait_for_selector('.aqi-value__value')

        # Extract data from the DOM
        data = {
            'city': page.inner_text('h1'),
            'aqi': page.inner_text('.aqi-value__value'),
            'pollutant': page.inner_text('.pollutant-level-wrapper b'),
            'temp': page.inner_text('.weather__detail--temp')
        }

        print(data)
        browser.close()

if __name__ == '__main__':
    scrape_iqair_live()

Python + Scrapy

import scrapy

class IQAirRankingSpider(scrapy.Spider):
    name = 'iqair_spider'
    start_urls = ['https://www.iqair.com/world-air-quality-ranking']

    def parse(self, response):
        # Extract data from the global ranking table
        # Note: Scrapy usually needs a JS middleware like scrapy-playwright for this site
        for row in response.css('table.ranking__table tr'):
            yield {
                'rank': row.css('td.rank::text').get(),
                'city': row.css('a.city-name::text').get(),
                'aqi': row.css('td.aqi::text').get(),
                'country': row.css('span.country-name::text').get()
            }

Node.js + Puppeteer

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  try {
    // Emulate a real user to avoid immediate blocking
    await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36...');
    await page.goto('https://www.iqair.com/usa/new-york/new-york-city', { waitUntil: 'networkidle2' });

    // Capture dynamic content
    const result = await page.evaluate(() => {
      return {
        city: document.querySelector('h1')?.innerText,
        aqi: document.querySelector('.aqi-value__value')?.innerText,
        main_pollutant: document.querySelector('.pollutant-level-wrapper b')?.innerText
      };
    });

    console.log(result);
  } catch (err) {
    console.error('Scraping failed:', err);
  } finally {
    await browser.close();
  }
})();

What You Can Do With IQAir Data

Explore practical applications and insights from IQAir data.

Real Estate Health Scoring

Property platforms can use historical air quality data to provide health scores for specific neighborhoods.

How to implement:

1Scrape historical PM2.5 and AQI data for specific zip codes.
2Calculate the average number of 'Unhealthy' days per year.
3Integrate this score into property listing pages to inform buyers.
4Update the scores quarterly to reflect seasonal pollution changes.

Use Automatio to extract data from IQAir and build these applications without writing code.

More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents

Web Automation

Smart Workflows

Get Started Free

Pro Tips for Scraping IQAir

Expert advice for successfully extracting data from IQAir.

Use Residential Proxies

Datacenter IPs are frequently flagged; using residential proxies provides the highest success rate for bypassing IQAir's security filters.

Wait for Network Idle

Ensure your scraper waits for all network requests to finish before extracting data, as AQI values are often the last elements to load.

Differentiate AQI Standards

IQAir provides both US and Chinese AQI standards; make sure your scraper targets the specific element relevant to your analysis.

Capture the Timestamp

Always scrape the 'Last Updated' timestamp alongside the AQI to ensure your data is correctly aligned in time-series models.

Monitor Selector Stability

The site structure may shift during major updates; verify your selectors regularly to avoid capturing null values during pollution events.

Implement Exponential Backoff

If you encounter a 403 or 429 error, pause your scraper and increase the delay between requests to avoid a permanent IP block.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Mohammed Ibrahim

CEO, qannas.pro

Ben Bressington

CTO, AiChatSolutions

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About IQAir

Find answers to common questions about IQAir

How to Scrape IQAir Air Quality Data

About IQAir

Global Air Quality Monitoring

Comprehensive Environmental Data

Value for Data Science and Research

Why Scrape IQAir?

Real-Time Health Alerts

Real Estate Market Analysis

ESG and Corporate Compliance

Academic and Climate Research

Smart Home IoT Integration

Supply Chain Forecasting

Scraping Challenges

Advanced Cloudflare Protection

Dynamic Content Hydration

Regional Redirection Logic

High Data Volatility

Complex DOM Structure

Scrape IQAir with AI

How It Works

Why Use AI for Scraping

How to scrape with AI:

Why use AI for scraping:

No-Code Web Scrapers for IQAir

Typical Workflow with No-Code Tools

Common Challenges

No-Code Web Scrapers for IQAir

Typical Workflow with No-Code Tools

Common Challenges

Code Examples

How to Scrape IQAir with Code

Python + Requests

Python + Playwright

Python + Scrapy

Node.js + Puppeteer

What You Can Do With IQAir Data

Real Estate Health Scoring

Smart City IoT Integration

Healthcare Patient Monitoring

E-commerce Market Intelligence

What You Can Do With IQAir Data

Supercharge your workflow with AI Automation

Pro Tips for Scraping IQAir

Use Residential Proxies

Wait for Network Idle

Differentiate AQI Standards

Capture the Timestamp

Monitor Selector Stability

Implement Exponential Backoff

What Our Users Say

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Frequently Asked Questions About IQAir

Is it legal to scrape IQAir?

Does IQAir have an official API?

How do I avoid getting blocked by IQAir?

How often does the data on IQAir update?

What format can I export IQAir data into?

Can I scrape historical air quality data?

Do I need a headless browser to scrape IQAir?

Which proxies work best for IQAir?