<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.taxtmi.com/rss_sitemap/rss_feed_blog.xsl?v=1750492856"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Satellites can track CO2, methane in metros like Mumbai and Delhi: IIT Bombay researchers</title>
    <link>https://www.taxtmi.com/news?id=59201</link>
    <description>Satellite-derived remote sensing can provide actionable urban greenhouse gas measurements by identifying rising CO2 and methane concentrations and spatial hotspots; researchers used OCO 2 and Sentinel 5P data, validated against TCCON, applied specialised algorithms, and developed SARIMA forecasting for city specific projections to prioritise interventions. Limitations-episodic snapshots and distortion from clouds, dust, and smog-mean satellites should be integrated with ground monitoring; combining machine learning with physics based models and improved sensors can enhance regulatory utility and credibility of emission estimates.</description>
    <language>en-us</language>
    <pubDate>Fri, 17 Oct 2025 19:31:03 +0530</pubDate>
    <lastBuildDate>Fri, 17 Oct 2025 19:31:03 +0530</lastBuildDate>
    <generator>TaxTMI RSS Generator</generator>
    <atom:link href="https://www.taxtmi.com/rss_feed_blog?id=859295" rel="self" type="application/rss+xml"/>
    <item>
      <title>Satellites can track CO2, methane in metros like Mumbai and Delhi: IIT Bombay researchers</title>
      <link>https://www.taxtmi.com/news?id=59201</link>
      <description>Satellite-derived remote sensing can provide actionable urban greenhouse gas measurements by identifying rising CO2 and methane concentrations and spatial hotspots; researchers used OCO 2 and Sentinel 5P data, validated against TCCON, applied specialised algorithms, and developed SARIMA forecasting for city specific projections to prioritise interventions. Limitations-episodic snapshots and distortion from clouds, dust, and smog-mean satellites should be integrated with ground monitoring; combining machine learning with physics based models and improved sensors can enhance regulatory utility and credibility of emission estimates.</description>
      <category>News</category>
      <law>-</law>
      <pubDate>Fri, 17 Oct 2025 19:31:03 +0530</pubDate>
      <guid isPermaLink="true">https://www.taxtmi.com/news?id=59201</guid>
    </item>
  </channel>
</rss>