Vehicular traffic is a hard problem in big cities. Internal combustion vehicles are the main fossil fuel consumers and frame the main source of urban air pollutants, such as particulate matter, nitrogen oxides, and vo...Vehicular traffic is a hard problem in big cities. Internal combustion vehicles are the main fossil fuel consumers and frame the main source of urban air pollutants, such as particulate matter, nitrogen oxides, and volatile organic compounds. Vehicular traffic is also a promoter of climate change due to its greenhouse gas emissions, such as CO and CO2. Awareness of the spatiotemporal distribution of urban traffic, including the velocity distribution, allows knowing the spatiotemporal distribution of the air pollutant vehicular emissions required to understand urban air pollution. Although no well-established traffic theory exists, some models and approaches, like cellular automata, have been proposed to study the main aspects of this phenomenon. In this paper, a simple approach for estimating the space-time distribution of the air pollutant emission rates in traffic cellular automata is proposed. It is discussed with the Fukui-Ishibashi (FI) and Nagel-Schreckenberg (NS) models for traffic flow of identical vehicles in a single lane. We obtained the steady-state emission rates of the FI and NS models, being larger those produced by the first one, with relative differences of up to 45% in hydrocarbons, 56% in carbon monoxide, and 77% in nitrogen oxides.展开更多
Ultrafine particles are associated with adverse health effects. Total Particle Number Concentration（TNC） of fine particles were measured during 2002 at the St. Louis — Midwest supersite. The time series showed over...Ultrafine particles are associated with adverse health effects. Total Particle Number Concentration（TNC） of fine particles were measured during 2002 at the St. Louis — Midwest supersite. The time series showed overall low level with frequent large peaks. The time series was analyzed alongside criteria pollutant measurements and meteorological observations. Multiple regression analysis was used to identify further contributing factors and to determine the association of different pollutants with TNC levels. This showed the strong contribution of sulfur dioxide（SO2） and nitrogen oxides（NO x） to high TNC levels. The analysis also suggested that increased dispersion resulting from faster winds and higher mixing heights led to higher TNC levels. Overall, the results show that there were intense particle nucleation events in a SO2 rich plume reaching the site which contributed around 29% of TNC. A further 40% was associated with primary emissions from mobile sources. By separating the remaining TNC by time of day and clear sky conditions,we suggest that most likely 8% of TNC are due to regional nucleation events and 23% are associated with the general urban background.展开更多
文摘Vehicular traffic is a hard problem in big cities. Internal combustion vehicles are the main fossil fuel consumers and frame the main source of urban air pollutants, such as particulate matter, nitrogen oxides, and volatile organic compounds. Vehicular traffic is also a promoter of climate change due to its greenhouse gas emissions, such as CO and CO2. Awareness of the spatiotemporal distribution of urban traffic, including the velocity distribution, allows knowing the spatiotemporal distribution of the air pollutant vehicular emissions required to understand urban air pollution. Although no well-established traffic theory exists, some models and approaches, like cellular automata, have been proposed to study the main aspects of this phenomenon. In this paper, a simple approach for estimating the space-time distribution of the air pollutant emission rates in traffic cellular automata is proposed. It is discussed with the Fukui-Ishibashi (FI) and Nagel-Schreckenberg (NS) models for traffic flow of identical vehicles in a single lane. We obtained the steady-state emission rates of the FI and NS models, being larger those produced by the first one, with relative differences of up to 45% in hydrocarbons, 56% in carbon monoxide, and 77% in nitrogen oxides.
基金funded the present analysis through grant number RD-83455701the original measurements through cooperative agreement R-82805901-0
文摘Ultrafine particles are associated with adverse health effects. Total Particle Number Concentration（TNC） of fine particles were measured during 2002 at the St. Louis — Midwest supersite. The time series showed overall low level with frequent large peaks. The time series was analyzed alongside criteria pollutant measurements and meteorological observations. Multiple regression analysis was used to identify further contributing factors and to determine the association of different pollutants with TNC levels. This showed the strong contribution of sulfur dioxide（SO2） and nitrogen oxides（NO x） to high TNC levels. The analysis also suggested that increased dispersion resulting from faster winds and higher mixing heights led to higher TNC levels. Overall, the results show that there were intense particle nucleation events in a SO2 rich plume reaching the site which contributed around 29% of TNC. A further 40% was associated with primary emissions from mobile sources. By separating the remaining TNC by time of day and clear sky conditions,we suggest that most likely 8% of TNC are due to regional nucleation events and 23% are associated with the general urban background.
