Air quality forecasting using artificial neural networks with real time dynamic error correction in highly polluted regions.

Air pollution is an important issue, especially in megacities across the world. There are emission sources within and also in the regions around these cities, which cause fluctuations in air quality based on prevailing meteorological conditions. Short term air quality forecasting is used not to just possibly mitigate forthcoming high air pollution episodes, but also to plan for reduced exposures of residents. In this study, a model using Artificial Neural Networks (ANN) has been developed to forecast pollutant concentration of PM10, PM2.5, NO2, and O3 for the current day and subsequent 4 days in a highly polluted region (32 different locations in Delhi). The model has been trained using meteorological parameters and hourly pollution concentration data for the year 2018 and then used for generating air quality forecasts in real-time. It has also been equipped with Real Time Correction (RTC), to improve the quality of the forecasts by dynamically adjusting the forecasts based on the model performance during the past few days. The model without RTC performs decently, but with RTC the errors are further reduced in forecasted values. The utility of the model has been demonstrated in real-time and model validations were performed for the whole year of 2018 and also independently for 2019. The model shows very good performance for all the pollutants on several evaluation metrics. Coefficient of correlations for various pollutants varies from 0.79-0.88 to 0.49-0.68 between the Day0 to Day4 forecasts. Lowest deterioration of performance was observed for ozone over the four days of forecasts. Use of RTC further improves the model performance for all pollutants.

Health Impact Assessment of a Predicted Air Quality Change by Moving Traffic from an Urban Ring Road into a Tunnel. The Case of Antwerp, Belgium.

BACKGROUND: The Antwerp ring road has a traffic density of 300,000 vehicles per day and borders the city center. The 'Ringland project' aims to change the current 'open air ring road' into a 'filtered tunneled ring road', putting the entire urban ring road into a tunnel and thus filtering air pollution. We conducted a health impact assessment (HIA) to quantify the possible benefit of a 'filtered tunneled ring road', as compared to the 'open air ring road' scenario, on air quality and its long-term health effects. MATERIALS AND METHODS: We modeled the change in annual ambient PM2.5 and NO2 concentrations by covering 15 kilometers of the Antwerp ring road in high resolution grids using the RIO-IFDM street canyon model. The exposure-response coefficients used were derived from a literature review: all-cause mortality, life expectancy, cardiopulmonary diseases and childhood Forced Vital Capacity development (FVC). RESULTS: Our model predicts changes between -1.5 and +2 µg/m³ in PM2.5 within a 1,500 meter radius around the ring road, for the 'filtered tunneled ring road' scenario as compared to an 'open air ring road'. These estimated annual changes were plotted against the population exposed to these differences. The calculated change of PM2.5 is associated with an expected annual decrease of 21 deaths (95% CI 7 to 41). This corresponds with 11.5 deaths avoided per 100,000 inhabitants (95% CI 3.9-23) in the first 500 meters around the ring road every year. Of 356 schools in a 1,500 meter perimeter around the ring road changes between -10 NO2 and + 0.17 µg/m³ were found, corresponding to FVC improvement of between 3 and 64ml among school-age children. The predicted decline in lung cancer mortality and incidence of acute myocardial infarction were both only 0.1 per 100,000 inhabitants or less. CONCLUSION: The expected change in PM2,5 and NO2 by covering the entire urban ring road in Antwerp is associated with considerable health gains for the approximate 352,000 inhabitants living in a 1,500 meter perimeter around the current open air ring road.

Impact of trees on pollutant dispersion in street canyons: A numerical study of the annual average effects in Antwerp, Belgium.

Effects of vegetation on pollutant dispersion receive increased attention in attempts to reduce air pollutant concentration levels in the urban environment. In this study, we examine the influence of vegetation on the concentrations of traffic pollutants in urban street canyons using numerical simulations with the CFD code OpenFOAM. This CFD approach is validated against literature wind tunnel data of traffic pollutant dispersion in street canyons. The impact of trees is simulated for a variety of vegetation types and the full range of approaching wind directions at 15° interval. All these results are combined using meteo statistics, including effects of seasonal leaf loss, to determine the annual average effect of trees in street canyons. This analysis is performed for two pollutants, elemental carbon (EC) and PM10, using background concentrations and emission strengths for the city of Antwerp, Belgium. The results show that due to the presence of trees the annual average pollutant concentrations increase with about 8% (range of 1% to 13%) for EC and with about 1.4% (range of 0.2 to 2.6%) for PM10. The study indicates that this annual effect is considerably smaller than earlier estimates which are generally based on a specific set of governing conditions (1 wind direction, full leafed trees and peak hour traffic emissions).

Kinetics of O(1D) + H2O and O(1D) + H2: absolute rate coefficients and O(3P) yields between 227 and 453 K.

The rate coefficients for the crucial atmospheric reactions of O((1)D) with H(2)O and H(2), k(1) and k(2), were measured over a wide temperature range using O((1)D) detection based on the chemiluminescence reaction of O((1)D) with C(2)H. Analyzing the decays of the chemiluminescence intensities yielded a value for k(1)(T) of (1.70 x 10(-10)exp[36 K/T]) cm(3) s(-1). Multiplying or dividing k(1)(T) by a factor f(T) = 1.04 exp(5.59(|1 K/T- 1/287|)), gives the 95% confidence limits; our new determination, in good agreement with previous studies, further reduces the uncertainty in k(1). An extended study of k(2) yielded a temperature independent rate constant of (1.35 +/- 0.05) x 10(-10) cm(3) s(-1). This precise value, based on an extended set of determinations with very low scatter, is significantly larger than the current recommendations, as were two other recent k(2) determinations. Secondly, the fractions of O((1)D) quenched to O((3)P) by H(2)O and H(2), k(1b)/k(1) and k(2b)/k(2), were precisely determined from fits to chemiluminescence decays. A temperature-independent value for k(1b)/k(1) of 0.010 +/- 0.003 was found. For the quenching fraction k(2b)/k(2) a value of 0.007 +/- 0.007 was obtained at room temperature. Both determinations are significantly smaller than values and upper limits from previous studies.

A temperature dependence kinetic study of O(1D) + CH4: overall rate coefficient and product yields.

Using a recently-developed chemiluminescence technique for monitoring O(1D), the rate coefficient, k1, of the important atmospheric reaction O(1D) + CH4 --> products has been determined over a wide temperature range, 227 to 450 K. The rate coefficient was shown to be independent of temperature, having a value of (1.91 +/- 0.08) x 10(-10) cm3 s(-1); the quoted uncertainties are with 95% confidence. This highly precise value, based on an extended set of determinations with very low scatter, is significantly greater, 26%, than current recommended values. Secondly, the fraction of O(1D) quenched to O(3P) by CH4, k(1q)/k1, was precisely determined from chemiluminescence decays over the temperature range 236 to 340 K. A temperature independent value for k(1q)/k1 of 0.002 +/- 0.003 was found. Finally, LIF detection of OH has been applied to accurately determine the product branching fraction to OH of O(1D) + CH4 at room temperature. Our value, k(1a)/k1 = 0.76 +/- 0.08 (95% confidence), is in line with recent determinations by other groups.

CH(A2Delta) Formation in hydrocarbon combustion: the temperature dependence of the rate constant of the reaction C2H + O2--> CH(A2Delta) + CO2.

The temperature dependence of the rate constant of the chemiluminescence reaction C2H + O2 --> CH(A) + CO2, k1e, has been experimentally determined over the temperature range 316-837 K using pulsed laser photolysis techniques. The rate constant was found to have a pronounced positive temperature dependence given by k1e(T) = AT(4.4) exp(1150 +/- 150/T), where A = 1 x 10(-27) cm(3) s(-1). The preexponential factor for k1e, A, which is known only to within an order of magnitude, is based on a revised expression for the rate constant for the C2H + O(3P) --> CH(A) + CO reaction, k2b, of (1.0 +/- 0.5) x 10(-11) exp(-230 K/T) cm3 s(-1) [Devriendt, K.; Van Look, H.; Ceursters, B.; Peeters, J. Chem. Phys. Lett. 1996, 261, 450] and a k2b/k1e determination of this work of 1200 +/- 500 at 295 K. Using the temperature dependence of the rate constant k1e(T)/k1e(300 K), which is much more accurately and precisely determined than is A, we predict an increase in k(1e) of a factor 60 +/- 16 between 300 and 1500 K. The ratio of rate constants k2b/k1e is predicted to change from 1200 +/- 500 at 295 K to 40 +/- 25 at 1500 K. These results suggest that the reaction C2H + O2 --> CH(A) + CO2 contributes significantly to CH(A-->X) chemiluminescence in hot flames and especially under fuel-lean conditions where it probably dominates the reaction C2H + O(3P) --> CH(A) + CO.