惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 司徒正美
Jina AI
Jina AI
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 三生石上(FineUI控件)
宝玉的分享
宝玉的分享
MyScale Blog
MyScale Blog
I
InfoQ
爱范儿
爱范儿
Microsoft Security Blog
Microsoft Security Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
Stack Overflow Blog
Stack Overflow Blog
T
Tailwind CSS Blog
D
DataBreaches.Net
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
T
The Blog of Author Tim Ferriss
B
Blog
阮一峰的网络日志
阮一峰的网络日志
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
月光博客
月光博客
雷峰网
雷峰网
Recent Announcements
Recent Announcements
量子位
B
Blog RSS Feed

Amazon Science homepage

Why don’t machine learning research agents overfit? Developing provably correct Rust code with Verus When LLM judges agree, should we believe them? SOP-Bench: A new benchmark for evaluating AI agents on real business procedures A decade of mathematical certainty: Reflections on the Automated Reasoning Group AWS Trainium Frontier competition: Co-design models and kernels on purpose-built AI chips 34 Amazon Research Awards Build on Trainium recipients announced How controllers from industrial machinery can coordinate multitask machine learning A new benchmark for evaluating patient-facing health AI agents Amazon is investing in the Lean Focused Research Organization Amazon and University of Michigan give robots a sense of touch Capturing token IDs during agentic interactions for better reinforcement learning The fuel of the future is already here: Why TRISO matters AWS Graviton5: How a new chiplet architecture delivers 25% better performance - Amazon Science How formal verification makes AWS Nitro the first formally verified cloud hypervisor - Amazon Science Four approaches to grounding AI agents in the physical world - Amazon Science Bridging intent and execution in agentic systems - Amazon Science Ground truth is a process, not a dataset - Amazon Science How flat is replacing fat in AWS data center networks - Amazon Science Amazon Research Awards recipients announced - Amazon Science Training LLMs to reason in oarallel: How global forking tokens improve accuracy - Amazon Science New scaling law connects LLM architecture to inference efficiency, boosting throughput up to 47% - Amazon Science Promptimus: Improving already good LLM prompts with zero manual engineering - Amazon Science How Amazon optimizes middle-mile delivery networks under uncertainty - Amazon Science How mechanism design theory helps optimize Amazon-vendor collaboration - Amazon Science Inside Amazon's responsible-AI pipeline - Amazon Science How to train AI on private data without exposing it - Amazon Science How catastrophic is your LLM? A statistical framework for certifying conversational risk - Amazon Science Isabelle/HOL: The proof assistant behind the Nitro Isolation Engine - Amazon Science Customized Amazon Nova models improve molecular-property prediction in drug discovery - Amazon Science
How Amazon tracks carbon intensity across its operations
https://www.amazon.science/author/kerry-constabile · 2026-07-01 · via Amazon Science homepage
EVs.meg.jpg

Amazon's investment in electric vehicles — like the ones shown here — is one of the ways it's reduced carbon emissions per unit shipped by 39% since 2019.

At Amazon, we believe that as our strategy to reach net-zero by 2040 evolves, we need to continue to raise the bar on what and how we measure. Measuring carbon emissions across our entire business is complex, and the tools and methodologies available are continuously improving.

Each year, we report on our carbon intensity, absolute emissions, and sustainability progress in our Sustainability Report, and we continue to adopt more-precise tools and methodologies to ensure our data is as meaningful and as representative of our decarbonization journey as possible.

Carbon intensity — the amount of emissions per unit of activity or production — is one of the most important tools for tracking decarbonization progress. But not all activities are the same. Across industries, some of the most meaningful intensity metrics are sector specific, tied to the actual activity being decarbonized, across buildings, energy, transportation, and products and beyond. Examples of metrics used by companies include carbon dioxide equivalent per megawatt-hour for electricity, per square foot for building decarbonization, and per kilometer for transport.

At Amazon, we apply the same principle: we are developing intensity metrics tailored to specific business activities, so we can measure what matters most.

Emissions per unit shipped

For Amazon's retail operations, we track carbon emissions per unit shipped. This metric matters because it directly reflects the efficiency of our delivery operations at scale. We’ve reduced emissions per unit shipped every year since 2019, resulting in a carbon intensity reduction of 39% at the end of 2025, relative to 2019. As we ship more packages, we're doing so with less carbon per unit, and our investments in carbon-free energy, smarter routing, lighter packaging, low-carbon fuels, alternative transportation methods (like rail versus road or air), and electric vehicles are all translating into real per-unit reductions. We also track carbon intensity at the regional and country level to understand geographic variation and target interventions accordingly. It's the clearest measure of whether we're decoupling delivery growth from emissions growth.

Why this is unique to Amazon

Amazon is more than a traditional logistics company: we're also a pharmacy, a grocery store, a cloud services company, a movie studio, a device manufacturer, a satellite business, and much more. As a result, our emissions span the entire value chain — from the manufacture of goods, long-haul shipping, and air freight to warehousing and distribution and middle-mile and last-mile delivery.

Amazon’s decarbonization efforts require strategies that can address significant portions of global transportation and supply chains simultaneously. That breadth creates complexity — and opportunity. Solutions that we develop together with our suppliers and partners don’t only stay within the four walls of Amazon; they have the potential to drive decarbonization across multiple industries at once. This is a responsibility we take seriously: we’re proud of our progress and want to share what we are learning along the way.

Simplifying our economic intensity metric

Part of sharing what we learn is being transparent about how we measure and what we change. One change that we’ve made recently is in our economic carbon intensity indicator. In our 2025 reporting, we updated this from grams of carbon dioxide equivalent per dollar of gross merchandise sales (gCO2e/$GMS) to grams of carbon dioxide equivalent per dollar of revenue (gCO2e/$Revenue). Revenue is publicly reported, widely understood, and aligns with how most companies disclose the carbon intensity of their operations— making our progress easier to compare with the rest of the industry’s. This update does not change our year-over-year trajectory.

Looking ahead

Climate science and carbon accounting are not static, and as the science and our own operations evolve, we'll continue to refine how we track and report our progress. We’re proud of our Climate Pledge goal to reach net-zero carbon by 2040. We’ll continue updating how we measure, so our data always reflects the most precise and meaningful picture of where we are and where we’re headed. To learn more about Amazon's carbon methodology, visit our Sustainability reporting website.

Kerry Constabile is the director of decarbonization strategy for Amazon's Sustainability organization.