Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts

The structure of the atmospheric boundary layer (ABL) and its influence on regional air quality over the Pearl River Delta (PRD) were examined through two intensive observations in October 2004 and July 2006. Analytical results show the presence of two types of typical weather conditions associated with poor air quality over the PRD. The first is the warm period before a cold front (WPBCF) and the second is the subsidence period controlled by a tropical cyclone (SPCTC). Two typical low air quality situations, which are affected by WPBCF and SPCTC, and one high air quality situation were analysed in detail. Results showed that continuously low or calm ground winds resulted in the accumulation of pollutants, and sea-land breezes had an important role during low air quality conditions. Data on recirculation factors showed that recirculation was significant during low air quality conditions, and steady transportation occurred during high air quality conditions. The ventilation index and the 24 h average ventilation index during high air quality conditions were significantly higher than those during low air quality conditions. Deep and stable inversion layers inside the ABL remarkably affected low air quality. Surface and low-altitude inversions were usually observed during WPBCF, contrary to during SPCTC, during which only the low-altitude inversion appeared frequently.

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Observational studies of the meteorological characteristics associated with poor air quality over the Pearl River Delta in China

https://pubs.acs.org/doi/pdf/10.1021/ed051pA48.1

Practical fluorescence: theory, methods, and techniques

. A new multi-scale model of urban air pollution is presented. This model combines a chemistry–transport model (CTM) that includes a comprehensive treatment of atmospheric chemistry and transport on spatial scales down to 1 km and a street-network model that describes the atmospheric concentrations of pollutants in an urban street network. The street-network model is the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), which consists of two main components: a street-canyon component and a street-intersection component. MUNICH is coupled to the Polair3D CTM of the Polyphemus air quality modeling platform to constitute the Street-in-Grid (SinG) model. MUNICH is used to simulate the concentrations of the chemical species in the urban canopy, which is located in the lowest layer of Polair3D, and the simulation of pollutant concentrations above rooftops is performed with Polair3D. Interactions between MUNICH and Polair3D occur at roof level and depend on a vertical mass transfer coefficient that is a function of atmospheric turbulence. SinG is used to simulate the concentrations of nitrogen oxides (NOx) and ozone (O3) in a Paris suburb. Simulated concentrations are compared to NOx concentrations measured at two monitoring stations within a street canyon. SinG shows better performance than MUNICH for nitrogen dioxide (NO2) concentrations. However, both SinG and MUNICH underestimate NOx. For the case study considered, the model performance for NOx concentrations is not sensitive to using a complex chemistry model in MUNICH and the Leighton NO–NO2–O3 set of reactions is sufficient.

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Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1.0) by coupling MUNICH (v1.0) and Polair3D (v1.8.1)

The turbulent dispersion of a passive tracer emitted by a line source simulating vehicular traffic in an idealized urban canyon in neutral conditions is studied in the water channel by means of simultaneous measurements of velocity and concentration fields. The experiments are conducted for two geometrical arrangements of two-dimensional obstacles reproducing the skimming flow (AR = 1) and the wake-interference regime (AR = 2), where AR is the canyon aspect ratio. The results show a strict connection between the dynamics of the shear layer developing at the top of the canyon and the vorticity field. For AR = 1, it is found that the shear layer flaps upwards and downwards according to two different frequencies. The greatest of them matches the vortex shedding frequency as measured at the canyon top, while the lower is comparable to H/u∗ (H is the building height and u∗ a reference friction velocity). The shear layer flapping modulates in time the pollutant exchange rate between the canyon and the outer layer. The different characteristics of the shear layer found for the two flow regimes also explain the larger pollutant re-entrainment observed for AR = 1, which turns out to be greater than the emission rate at the source. Sweep and ejection modes are identified via quadrant analysis and used to quantify the weights of the factors involved in the turbulent exchanges of tracer and momentum between the canyon and the outer layer. It is found that the venting of polluted fluid at the canyon top increases substantially passing from AR = 1 to 2, while an opposite trend is observed for the entrainment of polluted fluid. The vertical flux of pollutant at the canyon top for AR = 2 is largely of turbulent nature, with the contribution of the mean flux being practically negligible. On the other hand, the latter becomes comparable or even exceeds the magnitude of the turbulent flux when AR = 1. The maps of the first three statistical moments of the pollutant concentration for the two geometrical arrangements are also reported and discussed.

Pollutant fluxes in two-dimensional street canyons

Estimating the height of the nocturnal urban boundary layer for dispersion applications

The ratio of effective building height to street width governs dispersion of local vehicle emissions

We formulate a Lagrangian model to supplement comprehensive Eulerian grid models such as CMAQ, to estimate concentrations of NO"x, NO"2, and O"3 averaged over a spatial scale of the order of a kilometer over a domain extending over hundreds of kilometers. The model can be used to estimate hourly concentrations of these species over time periods of years. It achieves the required computational efficiency by separating transport and chemistry using the concept of species age. The model computes concentrations by tracing the history of an air parcel reaching a receptor through back trajectories driven by surface winds. Chemical reactions within the parcel are modeled through the Generic Reaction Set (GRS) chemistry model, which approximates the photochemical processes that lead to the production of ozone. The model is evaluated with concentrations measured over two years, 2005 and 2007. Evaluation with data measured at 21 stations distributed over the California South Coast Air Basin (SoCAB) during 2007 indicates that the model provides an adequate description of the spatial and temporal variation of the concentrations of NO"2, and NO"x. Estimates of maximum hourly O"3 concentrations show little bias (less than 10%) compared to observations, and the scatter (s"g^2 @? 2.56-95% confidence interval of the ratio of predicted to observed concentrations) is comparable to those associated with more computationally demanding models. The model was also evaluated with data collected at monitors in the San Joaquin Valley Air Basin (SJVAB) in 2005, and it shows similar performance to that at SoCAB. The paper also illustrates the application of the model to 1) screening regions for attainment of statistically based air quality standards, such as that for the daily maximum 8-h average O"3, and 2) improving methods to interpolate observations.

A computationally efficient model for estimating background concentrations of NOx, NO2, and O3

A laboratory study was done to investigate dispersion of buoyant emissions from near surface sources in urban areas. Ground level concentrations under different surrounding building geometries were measured using a newly developed system based on laser induced fluorescence. In the presence of upstream buildings AERMOD (AMS/U.S. EPA regulatory dispersion model) is unable to explain concentrations close to the source. Plume visualisations and velocity measurements show that upstream buildings induce low velocity and a highly turbulent region near the stack, which increases the plume rise and induces rapid vertical mixing. Also, the urban canopy imposes a length scale on the horizontal turbulence, causing the plume to spread laterally with the square root of distance (~x1/2) rather than linearly as occurs in open terrain. A Gaussian-based dispersion model which accounts for these effects performs substantially better in predicting ground level concentrations associated with buoyant emissions from distributed power generators in urban areas.

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Si Tan

Papers

Estimating the height of the nocturnal urban boundary layer for dispersion applications

The ratio of effective building height to street width governs dispersion of local vehicle emissions

A computationally efficient model for estimating background concentrations of NOx, NO2, and O3

Dispersion of buoyant emissions from low level sources in urban areas: water channel modelling