In his lively 2006 documentary Who Killed the Electric Car?, film-maker Chris Paine told the eye-opening story of the creation and destruction of the EV1, a prototype alternative to traditional, emission-spewing gas guzzlers that was recalled and crushed by its creators amid protests about oil company pressure.
In addition to the traditional anthropogenic precursor emissions associated with the industry, energy and transportation sectors, or biogenic emissions of precursors, Northern Eurasia experiences varied and complex sources of air pollution, including wildfires, crop residue burning, and dust.
Writing from Detroit (coincidentally, the capital of the traditional gas-guzzling, emission-spewing automobile), two New York Times reporters wrote that "the race by automakers and technology firms to develop self-driving cars has been fuelled by the belief that computers can operate a vehicle more safely than human drivers.
Compared to the much larger annual CO2 emissions, traditional industrial CO2 utilization can play only a minor role.
Traditional cement CO2 emissions are very high and, in some cases, can be more than 1 ton per 1 ton of cement production.
Those papers provide detailed definitions of three generations of exhaust emissions: Traditional Diesel Exhaust (TDE) pre-19899 engines), transitional diesel exhaust (1989 2006 engines), and New Technology Diesel Exhaust (NTDE) (2007 and later engines).
We employ three different classes of acoustic models: (1) traditional HMM/GMM, where the emission probabilities of the HMM states are modeled using GMMs; (2) hybrid HMM/DNN, where the emission probabilities of the HMM states are directly estimated using the DNN; and (3) BN-HMM/GMM, where a front-end (trained DNN) estimates BN features that are subsequently modeled by a HMM/GMM.
The traditional sources of atmospheric emissions (auto exhaust and industrial emissions) account for only about 20% of total exposure.
The results suggest variability and limitations associated with the present traditional approaches to gas emission prediction and design of gas management practices may be addressed using predictions derived from improved spatial datasets, and analysis techniques incorporating fundamental physical and energy related principles.
The traditional focus on annual emissions has masked the steady, and problematic, growth of committed emissions.
