Multivariate air pollution prediction modeling with partial missingness

Air pollution prediction with statistical algorithms

Urban Air Pollution Modeling

All life form on this planet depends on clean air. Air quality not only affects human health but also components of environment such as water, soil, and forests, which are the vital resources for human development. Urbanization is a process of relative growth in a country’s urban population accompanied by an even faster increase in the economic, political, and cultural importance of cities rela...

Air pollution prediction via multi-label classification

A Bayesian network classifier can be used to estimate the probability of an air pollutant overcoming a certain threshold. Yet multiple predictions are typically required regarding variables which are stochastically dependent, such as ozone measured in multiple stations or assessed according to by different indicators. The common practice (independent approach) is to devise an independent classi...

Modeling heavy air pollution in Beijing

A modeling analysis of a heavy air pollution episode occurred in Beijing X. An, T. Zhu, Z. Wang, C. Li, and Y. Wang State Key Joint Laboratory of Environmental Simulation and Pollution Control, Center for Environmental Sciences, Peking University, Beijing 100871, China LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China Received: 17 July 2006 – Accepted: 2...

Modeling exposure to air pollution from the WTC disaster based on reports of perceived air pollution.

We examined the utility of a newly developed perceived air pollution (PAP) scale and of a modeled air pollution (MAP) scale derived from it for predicting previously observed birth outcomes of pregnant women enrolled following September 11, 2001. Women reported their home and work locations in the four weeks after September 11, 2001 and the PAP at each site on a four-point scale designed for th...