5.0
3 条评分
★★★★★
2026年5月12日
2026年2月2日
更新内容
v1.3.4Removed generic loading animation and introduced a new branded one!
应用信息
- 开发者
- DreamLabsCA, LLC
- 分类
- Lifestyle
- 价格
- 免费
- 版本
- 1.3.4
- App ID
- 6754783507
简介
Turn Your Everyday Spending Into a Thriving Forest What if every coffee, every grocery run, every online order helped restore the planet? Grove makes it happen—automatically. How It Works Grove rounds up your everyday purchases to the nearest dollar and uses that spare change to plant real trees through verified reforestation partners. A $4.30 coffee generates a $0.70 contribution to your personal forest. No extra effort. No subscription fees. Just effortless climate action built into your daily life. Your Impact, Verified Every tree you plant is tracked and verified through our partnership with Veritree, a global leader in reforestation transparency. Watch your forest grow on an interactive map. See exactly where your trees are planted—from the Amazon Rainforest to the highlands of Kenya. Features Automatic round-ups on all your card purchases - Choose your reforestation project - Track trees planted, CO₂ sequestered, and acres restored - Verified impact through trusted reforestation partners - Bank-level security via Plaid - Pause anytime with one tap Real Results An average Grove user sequesters an estimated 540% more carbon than they produce each year. Setup takes just 3 minutes. Security You Can Trust Your financial data is protected with 256-bit encryption. We connect to your accounts through Plaid—the same service used by Venmo, Coinbase, and thousands of financial apps. Grove never stores your bank credentials or card numbers. Join the Movement Every tree planted with Grove contributes to the 1 Trillion Trees initiative, accelerating nature-based climate solutions alongside partners from 143 nations. Your spare change joins a global movement to restore the world's forests. Start your forest today. Download Grove and turn your everyday purchases into real environmental impact.
下载量预测
预估总下载量
50
低 / 月
74
预估 / 月
143
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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