Evaluation of water environment quality plays an important role in environment science. By analyzing the factors influencing multi-reach water quality, a RBF neural network model with water quality is developed using neural network theory and method. It is integrated into a software package using VB program. The software has a friend interactive interface, and someone not knowing artificial neural network can easily operate it. The development of software verifies that visual language VB is suitable to developing engineering softwares.
Based on the theory and method of neural network, and analysis of multi-reach water quality model, a model of RBF water quality model was presented, the model was trained and examined with the data of water quality of Fuyang river in Handan city. The results indicate that the model is more accurate than traditional model and is feasible for water quality simulation.
Abstract. The MM5-SMOKE-CMAQ model system, which was developed by the United States Environmental Protection Agency (US EPA) as the MODELS-3 system, has been used for daily air quality forecasts in the Beijing Municipal Environmental Monitoring Center (Beijing MEMC), as a part of the Ensemble air quality Modeling forecast System for Beijing (EMS-Beijing) since the 2008 Olympic Games. According to the daily forecast results for the entire duration of 2010, the model shows good performance in the PM10 forecast on most days but clearly underestimates PM10 concentration during some air pollution episodes. A typical air pollution episode from 11–20 January 2010 was chosen, in which the observed air pollution index of particulate matter (PM10-API) reached 180 while the forecast PM10-API was about 100. In this study, three numerical methods are used for model improvement: first, by enhancing the inner domain with 3 km resolution grids, and expanding the coverage from only Beijing to an area including Beijing and its surrounding cities; second, by adding more regional point source emissions located at Baoding, Landfang and Tangshan, to the south and east of Beijing; third, by updating the area source emissions, including the regional area source emissions in Baoding and Tangshan and the local village/town-level area source emissions in Beijing. The last two methods are combined as the updated emissions method. According to the model sensitivity testing results by the CMAQ model, the updated emissions method and expanded model domain method can both improve the model performance separately. But the expanded model domain method has better ability to capture the peak values of PM10 than the updated emissions method due to better reproduction of the pollution transport process in this episode. As a result, the hindcast results ("New(CMAQ)"), which are driven by the updated emissions in the expanded model domain, show a much better model performance in the national standard station-averaged PM10-API. The daily hindcast PM10-API reaches 180 and is much closer to the observed value, and has a high correlation coefficient of 0.93. The correlation coefficient of the PM10-API in all Beijing MEMC stations between the hindcast and observation is 0.82, clearly higher than the forecast 0.54. The FAC2 increases from 56% in the forecast to 84% in the hindcast, and the NMSE decreases from 0.886 to 0.196. The hindcast also has better model performance in PM10 hourly concentrations during the typical air pollution episode. The updated emissions method accompanied by a suitable domain in this study improved the model performance for the Beijing area significantly.
Abstract We have investigated the chemical and optical properties of aerosol particles during the 2014 Asia‐Pacific Economic Cooperation (APEC) summit in Beijing, China, using the highly time‐resolved measurements by a high‐resolution aerosol mass spectrometer and a cavity attenuated phase shift extinction monitor. The average (± σ ) extinction coefficient ( b ext ) and absorption coefficient ( b ap ) were 186.5 (±184.5) M m −1 and 23.3 (±21.9) M m −1 during APEC, which were decreased by 63% and 56%, respectively, compared to those before APEC primarily due to strict emission controls. The aerosol composition and size distributions showed substantial changes during APEC; as a response, the mass scattering efficiency (MSE) of PM 1 was decreased from 4.7 m 2 g −1 to 3.5 m 2 g −1 . Comparatively, the average single‐scattering albedo (SSA) remained relatively unchanged, illustrating the synchronous reductions of b ext and b ap during APEC. MSE and SSA were found to increase as function of the oxidation degree of organic aerosol (OA), indicating a change of aerosol optical properties during the aging processes. The empirical relationships between chemical composition and particle extinction were established using a multiple linear regression model. Our results showed the largest contribution of ammonium nitrate to particle extinction, accounting for 35.1% and 29.3% before and during APEC, respectively. This result highlights the important role of ammonium nitrate in the formation of severe haze pollution during this study period. We also observed very different optical properties of primary and secondary aerosol. Owing to emission controls in Beijing and surrounding regions and also partly the influences of meteorological changes, the average b ext of secondary aerosol during APEC was decreased by 71% from 372.3 M m −1 to 108.5 M m −1 , whereas that of primary aerosol mainly from cooking, traffic, and biomass burning emissions showed a smaller reduction from 136.7 M m −1 to 71.3 M m −1 . As a result, the contribution of primary aerosol to particle extinction increased from 26.8% to 39.6%, elucidating an enhanced role of local primary sources in visibility deterioration during APEC. Further analysis of chemically resolved particle extinction showed that the extinction contributions of aerosol species varied greatly between different air masses but generally with ammonium nitrate, ammonium sulfate, and secondary OA being the three major contributors.
Abstract In the context of China's clean air policy, the meteorological impacts on improved particulate matter (PM 2.5 ) air quality during 2016–2019 are investigated based on a four‐year high‐resolution atmospheric composition reanalysis data‐set, which has been produced by the Joint Data Assimilation System to resolve long‐term fine‐scale air quality variability over China. The reanalysis assimilates surface air quality observations using the Weather Research and Forecasting model coupled with Chemistry and an ensemble‐based assimilation algorithm, and simultaneous assimilations of meteorological observations, chemical initial conditions (ICs) and emissions are applied to help reduce the uncertainty in meteorology, ICs and the emissions inventory. Further, objective weather classification method is applied to quantitatively explore synoptic circulation pattern changes and associated PM 2.5 variability over North China by using this unique reanalysis data‐set. PM 2.5 reanalysis data are also investigated according to different circulation types, and results indicate that temporal and spatial variations of PM 2.5 are found to be closely connected with weather and circulation patterns. The northerly types correspond to the lower PM 2.5 levels, while the southerly and easterly types correspond to the higher PM 2.5 concentration due to favorable local meteorological conditions. According to the quantitative evaluation on circulation pattern changes, meteorological contribution have played a positive role in improving air quality in the context of China's clean air policy during 2016–2019. This study serves as a basis for future retrospective assessments of air pollutant variation and emissions regulation measures.
Particle formation in point source plumes is a typical sub-grid process not explicitly resolved in chemical transport models, and is an important contributor to atmospheric aerosols. The sub-grid particle formation (SGPF) is closely associated with the concentration of hydroxyl radical and condensation sinks in the plume, thus it has diurnal, seasonal and spatial variations. The impacts of SGPF in point source plumes on both aerosol mass and number concentrations were first investigated in China by a newly developed global nested chemical transport model with a SGPF parameterization scheme. Although a mean oxidation fraction of 2.5% sulfur dioxide for parameterizing the SGPF is suggested, the oxidation fraction and the particles formed in point source plumes have clear spatiotemporal variations based on the results of the SGPF scheme. The SGPF can enhance the annual mean concentration of sulfate by more than 1 μg m−3 (10–25%) over high emission areas (HEAs) in central-eastern China (CEC). In terms of particle number concentration, the SGPF contributes much more to nucleation mode particles with increasing number concentration, by 25–50% in HEAs, 10–25% in CEC, and 1–5% in northwestern China (NWC) compared with lower values (within ±5%) for the accumulation mode. This study reveals the significant impacts of SGPF over China and its strong dependence on meteorological and environmental factors. Physically-based SGPF scheme should be incorporated when studying the regional effects of point source plumes on air quality and climate.
We used simultaneous measurements of surface PM2.5 concentration and vertical profiles of aerosol concentration, temperature, and humidity, together with regional air quality model simulations, to study an episode of aerosol pollution in Beijing from 15 to 19 November 2016. The potential effects of easterly and southerly winds on the surface concentrations and vertical profiles of the PM2.5 pollution were investigated. Favorable easterly winds produced strong upward motion and were able to transport the PM2.5 pollution at the surface to the upper levels of the atmosphere. The amount of surface PM2.5 pollution transported by the easterly winds was determined by the strength and height of the upward motion produced by the easterly winds and the initial height of the upward wind. A greater amount of PM2.5 pollution was transported to upper levels of the atmosphere by upward winds with a lower initial height. The pollutants were diluted by easterly winds from clean ocean air masses. The inversion layer was destroyed by the easterly winds and the surface pollutants and warm air masses were then lifted to the upper levels of the atmosphere, where they re-established a multi-layer inversion. This region of inversion was strengthened by the southerly winds, increasing the severity of pollution. A vortex was produced by southerly winds that led to the convergence of air along the Taihang Mountains. Pollutants were transported from southern–central Hebei Province to Beijing in the boundary layer. Warm advection associated with the southerly winds intensified the inversion produced by the easterly winds and a more stable boundary layer was formed. The layer with high PM2.5 concentration became dee-per with persistent southerly winds of a certain depth. The polluted air masses then rose over the northern Taihang Mountains to the northern mountainous regions of Hebei Province.
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