PHD: PM2.5 Hindcast Databse for China, 2000-2016 PHD中国PM2.5浓度追算2000-2016数据库

About PHD 关于PHD

PHD (PM2.5 Hindcast Database) is a database that provides historical PM2.5 estimates across China, during 2000-2016. Using a machine learning approach, PHD assembled datasets from multiple sources, including MODIS satellite measurements of aerosol, CMAQ modeling outputs based on MEIC historical emission inventories and many other spatiotemporal variables, and hindcasted the daily PM2.5 concentrations from 2000 to 2016 in China. PHD is developed and maintained by a team from Tsinghua University, Beijing, China.

PHD(PM2.5 Hindcast Database)是2000-2016年中国PM2.5历史浓度数据库。该数据库基于MODIS卫星气溶胶观测,MEIC-CMAQ历史空气质量模式模拟,以及其它时空变量等多源数据,利用机器学习算法追算2000-2016年中国大陆PM2.5历史浓度数据。PHD数据库由清华大学主持开发和维护。

PHD v1.0 provides annual concentrations of PM2.5 and counts of polluted days in a regular grid of 0.1° × 0.1°, across the mainland of China, from 2000 to 2010, and other results derived from the product.

PHD v1.0数据库提供网格化的2000-2016年间,中国大陆PM2.5年均浓度及污染天数,空间分辨率为0.1° × 0.1°,以及其它衍生结果,包括人口加权的PM2.5时间序列数据。

For further details about PHD, please contact Professor Qiang Zhang(qiangzhang at tsinghua dot edu dot cn)or Dr. Tao Xue(xuetaogk_9032 at 126 dot com).

如果对PHD数据使用有任何问题,请联系张强教授(qiangzhang at tsinghua dot edu dot cn)或薛涛博士(xuetaogk_9032 at 126 dot com)。

Usage criteria 下载需知

  • PHD should not be utilized for commercial purposes.
  • For any published articles / materials or unpublished reports / products that related to PHD, please cite the following paper.
  • PHD数据库仅供非商业用途使用。
  • 在任何使用PHD数据库的论文、研究报告、产品中,必须完整引用PHD数据库的相关研究成果。

Download 数据下载

1. PHD v1.0 PM2.5 annual concentrations (μg/m3):

1.PHD v1.0 PM2.5年均浓度(μg/m3)

2. PHD v1.0 Polluted-and-above days (PM2.5 > 75 μg/m3, day):

2.PHD v1.0污染天数(PM2.5 > 75 μg/m3, 天):

3. PHD v1.0 Heavily-polluted-and-above days (PM2.5 > 150 μg/m3, day):

3.PHD v1.0重污染天数(PM2.5 > 150 μg/m3, day):

4.PHD v1.0 Population-weighted mean concentration of PM2.5 by month (μg/m3):

4. PHD v1.0 人口加权的PM2.5月均浓度(μg/m3):

Citation 文献引用

Xue T, Zheng Y, Tong D, Zheng B, Li X, Zhu T, Zhang Q. (2018). Spatiotemporal continuous estimates of PM2.5 concentrations in China, 2000-2016: a machine learning method with inputs from satellites, chemical transport model, and ground observations, Environment International. (Accepted).