Levels of PM2.5-bound species in Beijing, China: Spatio-temporal distributions and human health risks

High concentrations of PM2.5 and the corresponding health effect in Beijing, China have drawn attention worldwide. This study aims to assess the lifetime health risk of ambient PM2.5 bound elements and polycyclic aromatic hydrocarbons (PAHs) from 2013 to 2015 in Beijing. Risk assessment methods of US Environment Protection Agency (USEPA) were applied to the following PM2.5 components: six elemental components (Cr, Co, Ni, As, Cd, Pb) and sixteen EPA priority PAHs for cancer risks, and thirteen non- elemental components (Al, Ba, Cr, Mn, Ni, As, Cd, Pb, Co, V, P, Cl, Se) for non-cancer risks. Spatial and temporal variations of health risks were examined across Beijing. Source apportionment was applied to apportion the risks. The estimated lifetime cancer risk due to exposure to ambient PM2.5 in Beijing is 2.30E-02. This cancer risk level is two magnitudes higher than EPA upper threshold of 1.00E-04. Thus, remediation is desirable. Lifetime non-cancer hazard quotient in Beijing is 13.7, higher than EPA upper threshold of non-cancer hazard quotient (1.0), indicating that some non-cancer health impacts may also occur. Seasonal cancer risks range 7.47E-03 to 4.78E-03. Summer and winter have higher percentages of 31% and 26% respectively to the total lifetime risk, while lower in spring (23%), and autumn (20%). Seasonal non-cancer hazard quotients in Beijing range 4.5 to 26.2. Winter contributed approximate 52% of total non-cancer hazard quotient, followed by spring (21%), autumn (18%), and summer (9%). Lifetime cancer risk is higher in suburban area (3.53E-02) than in urban area (1.82E-02), while hazard quotient is higher in urban area (14.3) than suburban area (2.6). Overall, both lifetime cancer and non-cancer risks in Beijing are higher than the corresponding USEPA threshold. The health risks in Beijing are all higher than other cities in China, Windsor, and Mexico

Noise Source Identification and Noise Directivity Analysis of Bladeless Fans by Combined CFD and CAA Method

The bladeless fan is a new concept of fan that does not have visible impellers. It features low noise level, uniform airflow, and improved safety. It has been widely applied in household appliances. Since the customers are particularly sensitive to the noise generated by the fan, the aeroacoustics performance of the fan needs to be accurately characterized in the design stage. In this study, computational fluid dynamic (CFD) and computational aeroacoustics (CAA) are applied to investigate the aeroacoustics performance and identify the major noise source of the bladeless fan. A prototype of the bladeless fan, including a wind channel, a base cavity, a rotor and a stator inside the base, is set in a computational domain of 4m × 2m × 2m and the airflow through the fan is simulated. The hybrid mesh is generated, the unstructured mesh in the near field, and the structured at the far field. To compute the flow field, steady RANS simulation (standard k–ε turbulence model) and Large Eddy simulation (Smagorinsky-Lilly model) are carried out. Ffowcs Williams and Hawkings (FW-H) analogy is used to predict the acoustic field. Experiments, including air velocity measurement and sound pressure measurement, are conducted to validate simulation results. Sound pressure level results at the near-field receiver illustrate that the blade passage frequency can be captured by combined CFD and CAA method. Noise source analysis shows that the combination of the rotor and stator contributes most to the noise produced by the bladeless fan. The wind channel is the secondary source. Sound pressure level contours at different distances and different heights are generated to investigate the directivity pattern of the noise generated by the bladeless fan. At the near field, the produced noise at the front and the back of the bladeless fan are louder than those at left and right; at the far field, the noise at the front is much larger than the other three sides. In addition, at the near field, with the increase of the height, two separated hotspots appear over 2,500Hz and the sound pressure level at these two hotspots increases; at the far field, the noise distribution at different heights is similar and the peak near 3,000Hz can be estimated. A possible reason to cause this peak is vortex shedding at the trailing edge of the rotor’s blades. The aeroacoustics analysis is helpful to develop strategies to reduce noise and guide the improved design of the bladeless fan

Influence of Geometric Parameters on Aerodynamic and Acoustic Performances of Bladeless Fans

In recent years, the bladeless fan that does not have visible impellers have been widely applied in household appliances. Since the customers are particularly sensitive to noise and the strength of wind generated by the fan, the aerodynamic and acoustic performances of the fan need to be accurately characterized in the design stage. In this study, computational fluid dynamic (CFD) and computational aeroacoustics (CAA) are applied to investigate the performances of different designs of a bladeless fan model. The influence of four parameters, namely the airfoil selection for cross-section of the wind channel, the slit width, the height of cross-section and the location of the slit, is investigated. The results indicate the streamwise air velocity increases significantly by narrowing the outlet, but the noise level increases simultaneously. In addition, the generated noise increases while the height of fan cross-section increases, and a 4mm height of the cross section is optimal for aerodynamic performance. When the slit is closer to the location of maximum thickness, the performances of the bladeless fan increases. Moreover, the performance is not changed significantly by changing the cross-sectional profile. Finally, the optimal geometric parameters are identified to guide the future design of the bladeless fan

Event-Centric Query Expansion in Web Search

In search engines, query expansion (QE) is a crucial technique to improve search experience. Previous studies often rely on long-term search log mining, which leads to slow updates and is sub-optimal for time-sensitive news searches. In this work, we present Event-Centric Query Expansion (EQE), a novel QE system that addresses these issues by mining the best expansion from a significant amount of potential events rapidly and accurately. This system consists of four stages, i.e., event collection, event reformulation, semantic retrieval and online ranking. Specifically, we first collect and filter news headlines from websites. Then we propose a generation model that incorporates contrastive learning and prompt-tuning techniques to reformulate these headlines to concise candidates. Additionally, we fine-tune a dual-tower semantic model to function as an encoder for event retrieval and explore a two-stage contrastive training approach to enhance the accuracy of event retrieval. Finally, we rank the retrieved events and select the optimal one as QE, which is then used to improve the retrieval of event-related documents. Through offline analysis and online A/B testing, we observe that the EQE system significantly improves many metrics compared to the baseline. The system has been deployed in Tencent QQ Browser Search and served hundreds of millions of users. The dataset and baseline codes are available at https://open-event-hub.github.io/eqe .Comment: ACL 2023 Industry Trac

Graphene Oxide@Heavy Metal Ions (GO@M) Complex Simulated Waste as an Efficient Adsorbent for Removal of Cationic Methylene Blue Dye from Contaminated Water

Graphene oxide (GO) was heavily used in the adsorption process of various heavy metal ions (such as copper (Cu) and iron (Fe) ions), resulting in a huge waste quantity of graphene oxide@metal ions complex. In this research, the authors try to solve this issue. Herein, the GO surface was loaded with divalent (Cu2+) and trivalent (Fe3+) heavy metal ions as a simulated waste of the heavy metal in various removal processes to form GO@Cu and (GO@Fe) composites, respectively. After that, the previous nanocomposites were used to remove cationic methylene blue (MB) dye. The prepared composites were characterized with a scanning electron microscope (SEM), transition electron microscope (TEM), Fourier transmission infrared (FTIR), Raman, and energy-dispersive X-ray (EDS) before and after the adsorption process. Various adsorption factors of the two composites towards MB-dye were investigated. Based on the adsorption isotherm information, the adsorption process of MB-dye is highly fitted with the Langmuir model with maximum capacities (mg g−1) (384.62, GO@Cu) and (217.39, GO@Fe). According to the thermodynamic analysis, the adsorption reaction of MB-species over the GO@Cu is exothermic and, in the case of GO@Fe, is endothermic. Moreover, the two composites presented excellent selectivity of adsorption of the MB-dye from the MB/MO mixtur