In this post, I address an common problem in geoscience research: how to arrange the original geodata into pre-defined grid system. Sometimes, we need to unify the resolution of various dataset or summary the scatter data to raster one.

Specifically, this brief tutorial will look at two different original data, and allow you to creat gridded data in python. For better illustration, two practial cases with detailed code are shown:

• Creating an emission inventory based on the emissions from point sources (e.g., power plants, cement plants)
• Remapping a population density map to a coarser resolution

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I’m writing today about downloading, handling, and plotting satellite derived air pollution maps with cartopy and fiona using Python. One key task in this post is to clip a raster-like (2-d array) dataset with a polygon in pure Python environment (i.e., no need for ArcGIS or QGIS GUI-based software).

The satellite sensor can offer critical supplementary data of several atmospheric species, e.g., SO₂, NO₂, PM_2.5. Comparaing to ground-based monitoring which might be sparse in some areas (e.g., Africa, South America, oceans), the satellite observation offers a full picture for better understanding the spatiotemporal patterns of some air pollutants.

Below is an excerpt of a NO₂ column maps within Chengyu urabn agglomeration in China.

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In this post, I present some simple programs written in Python for post-processing the flexpart-wrf output.

It mainly contains several aspects, data merging, data processing and data visualization. I will also show some tips tp creat self-defined colormaps for nice plots.

PS: All th codes are also uploaded in my GitHub respority PyFlex

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FLEXPART is a Lagrangian particle dispersion model (LPDM) developed by Norwegian Institute of Air Research, Norway. It allows researchers to simulate the long-range transportation, diffusion, dry/wet deposition processes of atmospheric spcecies from their sources. It also can be utilized for backward calculation based on the observation of receptor to anaysis source-receptor relationships.

This model is coded following the Fortran 95 standard, and can be freely download from the page here. Flexpart 8.x/9.x is easy for compilation following the offical reference. I noticed that netCDF-format output (which would make the post-processing easier compared to the original binary output files) has been merged in the newer veision. Therefore, I tried to compile FLEXPART 10.0 beta version in the Linux system, while lots of issues appeared. My installing steps are listed as follows

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全国空气质量历史数据是大气环境研究的重要基础资料，而我国官方平台仅提供实时监测信息，而且还只支持IE浏览器(╮(╯_╰)╭)。

我曾尝试采用爬虫工具获取并存储逐时信息，但限于权限，未能在实验室服务器上连续长时间运行。互联网上直接提供数据或API端口的网站有很多，如环境云，PM25.in, 青悦开放环境数据中心等。其中，beijingair最具分享精神,提供了2013年至今的详尽历史数据，且完全免费。

由衷感谢@王_晓磊的出色工作和无私分享，极大地推动了我国环境数据的公开与透明。其数据格式为每日一份csv文件存储当日所有站点/城市的逐时信息。在长时间尺度的数据分析时，需逐一阅读各原始文件。此处，我考虑将全年数据文件整合为多维度数据存储格式(HDF5)文件，便于调用和处理。

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提要：此文介绍利用Python语言处理NASA MODIS火点数据（Global Monthly Fire Location Product，MCD14ML），可实现的基本功能包括：（1）特定时期的火点信息提取；（2）特定区域内的火点信息提取；（3）火点密度空间分布的计算与可视化表达

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实验室的服务器的四块硬盘全坏，而未进行备份，不得不将以前的内容全部重装一次。Python部分有Anaconda的分发包，比较容易。但常用的WRF模型却研究了好久。

之前，服务器采用的是ifort编译器。重装后，系统中只有gcc, 版本也比较旧(4.1.2)。 WRF编译失败，我认为原因可能是gcc太旧了。 因而，我考虑升级gcc的版本，同时由于本人不是root用户，也不能借助yum install gcc的简单办法，只得step by step地做。

本文记录了自gcc升级至WRF-Chem成功安装的全部流程，作为今后类似工作的参考。

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前沿

大气化学是一门关于大气中化学物质的排放、相互作用、物理及化学转化的综合性学科。同时，其对大气关键的物理过程亦会涉及。本计划所翻译的电子课本对大气化学领域近年来的研究进展(该课本编撰于2013年)进行陈述，如数学模型的并行计算研究，空气污染物对全球气候变化的影响等。原著作者期望本书的内容将为本科生与硕士生提供帮助，以之为专业课程的基础性参考资料。

第一章 大气层的结构和组成

大气层的总质量接近5.3x10¹⁸kg，而地球水圈(包括海洋、湖泊、河流、地下水以及冰雪)的总质量为1.4x10²¹kg，岩石圈总质量则为5.98x10²⁴kg。大气层的上边界没有严格的定义。大气层中的物质随高度的上升而急剧减少，并最终融入星际空间之中。包含着大量气体及颗粒组分的大气圈层围绕在地球的外部，随地球一同绕日旋转。

地球大气层的密度分布极不均匀。距离地面5.5 Km以下的空气占据着大气层一半的质量，而大气层约99%的质量分布在距地30 Km以内。地球大气层的范围和地球磁气圈的范围一致(图1.1)，这一形态由地球本体磁场与太阳风^[1]的相互作用而最终形成。

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