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It has been proven that the future of energy demands for human society is related to clean energy sources such as solar energy. On the other hand, fuel cell technology converts the chemical energy of a fuel into electrical energy. Meanwhile, the polygeneration system based on (semi) renewable energy can be a viable alternative to conventional fuel-based systems. However, examining their performance for widespread implementation requires further and powerful studies. The aim of the present work is to evaluate the performance of the polygeneration energy system to produce electricity, heat, hydrogen and cool. The novel hybrid power system consists of the 10 kW el phosphoric acid fuel cell, linear Fresnel solar reflector (LFR), Organic Rankine Cycle (ORC) and Stirling engine (SE). In the novel energy conversion process proposed, the fuel cell generates electricity and heat, and its waste heat is used to generate additional electricity in the SE. The fuel and oxidant required by the fuel cell are supplied by an electrolyzer that is powered by an ORC system. A solar thermal collector provides the duty required by the evaporator of ORC system. The effect of key parameters such as current density, solar radiation and flow rate of hydrogen on the system energy and exergy performance is also investigated. To evaluate the performance of the LFR system the climatic conditions of Tehran (in Iran) and Beijing (in China) are considered. Results revealed that, the SE and ORC system separately generates 1.48 and 26.54 kW of electricity, respectively. Furthermore, the electrolyzer consumes 23.36 kW of electric power and 3.64 kW of cooling is produced by the chiller. In addition, the energy efficiency and total exergy destruction of the proposed system are 71.32 % and 57.94 kW, respectively. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) is a vital precursor of secondary aerosols, which play an important role in urban air pollution. The passive observation of NH 3 in the urban atmosphere showed higher concentrations than conventionally believed; however, the NH 3 dynamics remain limited due to the paucity of active measurements with fast response instruments. In this study, intensive online measurements of ambient NH 3 were conducted using cavity ring-down spectroscopy in late spring and early summer 2020 at the megacities of Beijing and Shanghai in northern and southern China. The results show that the average NH 3 concentration in Beijing (23.1 ± 10.3 ppb) was nearly double that in Shanghai (12.0 ± 5.0 ppb). This spatial difference was confirmed by satellite column observations and bottom-up emission patterns. In addition, there was a significant increase in NH 3 concentrations during the morning in our study. This special diurnal profile was a universal feature, with an occurrence frequency exceeding 50% in both cities. These frequent morning increases were mainly caused by motor vehicle emissions, with an additional contribution from the residual layer breakup for one-quarter of the days in the morning increase. On these days, the NH 3 concentration increased by approximately 20% due to the downward mixing of the residual layer rupture. The unique data observed here could be used to validate the chemistry and transport models at a higher time resolution and improve the understanding of the current status of NH 3 pollution in the urban atmosphere. [Display omitted] • 1 Hz NH 3 observations were conducted at megacities of Beijing and Shanghai. • Atmospheric NH 3 concentrations in urban Beijing were double that in Shanghai. • A morning pulse of NH 3 levels was a common feature at Beijing and Shanghai. • Highly frequent morning increases of NH 3 were mainly caused by vehicle emissions. • Boundary layer rupture further enhanced the rapid increase of NH 3 in the morning. [ABSTRACT FROM AUTHOR]

Abstract: Rainwater and airborne particles were sampled at five sites, including Beijing and Mazhuang Town in the northeast of China, Chongqing in the southwest of China, Shenzhen and Mangdang Mountain in the south of China. The pollution of airborne particles in winter at Chongqing and Beijing were the worst and the following was in summer at Mazhuang town and atmosphere quality in spring at Mangdang Mountain was the best. The ratios of fine particles to coarse particles were high among all the sampling sites. The contribution from soluble components to particulate mass was important and the main ions both on PM10 and PM2.5 were SO4 2 −, NO3 − and NH4 +. Both inorganic and organic soluble components on particles were mainly enriched on fine particles. The average pH values in rainwater at Beijing, Mazhuang Town, Shenzhen and Mangdang Mountain were 6.02, 5.97, 4.72 and 4.81 respectively. A new methodology to determine the neutralizing capacity of airborne particles was established in this study. The pH values and water-soluble ion concentrations in particulate matter extract were measured, then the ionization balance and charge conservation principle were adopted to determine the amount of acid-basic compositions on particle. The amount of H+ in rainwater neutralized by airborne particles per unit mass was used to denote the neutralizing capacity of particles. The neutralizing capacity of airborne particles was lower if both of the concentrations of particles and ratio of fine to coarse particles were higher. The neutralizing capacity of airborne particles was inverse proportion to the acidity of rainwater and the rain intensity. The neutralizing effect of particles accounted for 4%–28% of the reduction of rainwater acidity during wash-out process among different sites, and it was deduced that NH3 was the major neutralizing species especially for rainwater from sites in the northeast of China. [Copyright &y& Elsevier]

Background: Screening for Tuberculosis (TB) is a critical tactic for minimizing the prevalence of illness within schools. Tuberculosis Preventive Therapy (TPT), in turn, effectively staves off the development of TB from latent tuberculosis infection (LTBI). Unfortunately, there is limited research on LTBI and TPT among students. This study aimed to assess LTBI among freshmen in Changping District and advocate for the implementation of TPT. Methods: The prospective study collected data from 12 educational institutions within the Changping District of Beijing. The Kolmogorov − Smirnov test and other statistical methods were used for statistical analysis, x 2 was obtained using the formula x 2 = nΣA2/nRnC-1, df = (C-1) (R-1). We analyzed potential factors impacting the LTBI rate, and scrutinized the possible causes behind the low application of TPT and its efficacy for LTBI treatment, China. Results: Among 19,872 freshmen included in this study, 18 active TB cases (91 per 10,0000) and 2236 LTBI cases (11.6% of 19,223) were identified, respectively. Furthermore, of those with LTBI, 1045 (5.4% of 19,223) showed a strong positive for purified protein derivative (PPD), but only 312 opted for TB preventive treatment. There appeared to be no significant difference in the prevalence of LTBI and TPT rate between male and female students. Concurrently, 11 (71 per 100,000) and 7 (158 per 100,000) cases of active tuberculosis were identified in 6 universities and 6 higher vocational colleges, respectively. Interestingly, almost all freshmen who underwent TPT came from universities, suggesting a statistically significant disparity in TPT rate (χ2 = 139.829, P < 0.001) between these two types of educational institutions. Meanwhile, as for the age-wise distribution of latent infection among 17–20 years old freshmen, the LTBI rate exhibited 10.5%, 11.6%, 12.1% and 13.5%, respectively. Correlation between LTBI rate, the strong positive rate was statistically significant among different ages (χ2 = 34.559, P < 0.001). Over a follow-up period of 2 years, three students were diagnosed with active tuberculosis, one of which was resistant to rifampicin. All three students manifested a strong positive for PPD and declined preventive treatment during TB screening. Conclusions: The data indicates a high rate of LTBI amongst students in areas with a heavy TB burden, potentially leading to cross-regional TB transmission due to the migration of students. Education level might contribute to the limited uptake of TPT. Therefore, improving the implementation of TB preventive treatments is crucial in controlling and preventing TB across schools. [ABSTRACT FROM AUTHOR]

Background: Screening for Tuberculosis (TB) is a critical tactic for minimizing the prevalence of illness within schools. Tuberculosis Preventive Therapy (TPT), in turn, effectively staves off the development of TB from latent tuberculosis infection (LTBI). Unfortunately, there is limited research on LTBI and TPT among students. This study aimed to assess LTBI among freshmen in Changping District and advocate for the implementation of TPT. Methods: The prospective study collected data from 12 educational institutions within the Changping District of Beijing. The Kolmogorov − Smirnov test and other statistical methods were used for statistical analysis, x 2 was obtained using the formula x 2 = nΣA2/nRnC-1, df = (C-1) (R-1). We analyzed potential factors impacting the LTBI rate, and scrutinized the possible causes behind the low application of TPT and its efficacy for LTBI treatment, China. Results: Among 19,872 freshmen included in this study, 18 active TB cases (91 per 10,0000) and 2236 LTBI cases (11.6% of 19,223) were identified, respectively. Furthermore, of those with LTBI, 1045 (5.4% of 19,223) showed a strong positive for purified protein derivative (PPD), but only 312 opted for TB preventive treatment. There appeared to be no significant difference in the prevalence of LTBI and TPT rate between male and female students. Concurrently, 11 (71 per 100,000) and 7 (158 per 100,000) cases of active tuberculosis were identified in 6 universities and 6 higher vocational colleges, respectively. Interestingly, almost all freshmen who underwent TPT came from universities, suggesting a statistically significant disparity in TPT rate (χ2 = 139.829, P < 0.001) between these two types of educational institutions. Meanwhile, as for the age-wise distribution of latent infection among 17–20 years old freshmen, the LTBI rate exhibited 10.5%, 11.6%, 12.1% and 13.5%, respectively. Correlation between LTBI rate, the strong positive rate was statistically significant among different ages (χ2 = 34.559, P < 0.001). Over a follow-up period of 2 years, three students were diagnosed with active tuberculosis, one of which was resistant to rifampicin. All three students manifested a strong positive for PPD and declined preventive treatment during TB screening. Conclusions: The data indicates a high rate of LTBI amongst students in areas with a heavy TB burden, potentially leading to cross-regional TB transmission due to the migration of students. Education level might contribute to the limited uptake of TPT. Therefore, improving the implementation of TB preventive treatments is crucial in controlling and preventing TB across schools. [ABSTRACT FROM AUTHOR]

As for the problem that the traditional single depth prediction model has poor strain capacity to the prediction results of time series data when predicting lake eutrophication, this study takes the multi-factor water quality data affecting lake eutrophication as the main research object. A deep reinforcement learning model is proposed, which can realize the mutual conversion of water quality data prediction models at different times, select the optimal prediction strategy of lake eutrophication at the current time according to its own continuous learning, and improve the reinforcement learning algorithm. Firstly, the greedy factor, the fixed parameter of Agent learning training in reinforcement learning, is introduced into an arctangent function and the mean value reward factor is defined. On this basis, three Q estimates are introduced, and the weight parameters are obtained by calculating the realistic value of Q, taking the average value and the minimum value to update the final Q table, so as to get an Improved MIMO-DD-3Q Learning model. The preliminary prediction results of lake eutrophication are obtained, and the errors obtained are used as the secondary input to continue updating the Q table to build the final Improved MIMO-DD-3Q Learning model, so as to achieve the final prediction of water eutrophication. In this study, multi-factor water quality data of Yongding River in Beijing were selected from 0:00 on July 26, 2021 to 0:00 on September 5, 2021. Firstly, data smoothing and principal component analysis were carried out to confirm that there was a certain correlation between all factors in the occurrence of lake eutrophication. Then, the Improved MIMO-DD-3Q Learning prediction model was used for experimental verification. The results show that the Improved MIMO-DD-3Q Learning model has a good effect in the field of lake eutrophication prediction. [ABSTRACT FROM AUTHOR]

Size-resolved aerosol organic carbon (OC) and water-soluble OC (WSOC) was determined weekly in urban Beijing between 2013 and 2018. The results showed that in winter, the concentrations of WSOC and OC in fine (<2.1 μm) and coarse (>2.1 μm) mode were highest in 2013. During the following years, the concentrations of WSOC and OC were lower but an increasing trend was found from 2014 to 2016, which might be due to the increasing precursor concentrations. From summer 2013 to 2018, the concentrations of OC and WSOC in both fine and coarse mode decreased, which might be affected by decreasing emission intensity and photochemical oxidation. To characterize the seasonality of WSOC, two intensive field observations were further performed in winter 2013 and summer 2018. In winter of 2013, WSOC was mainly enriched in PM 1 (<1 μm) on clean days and lightly polluted days. In addition, the fine mode maximum shifted from 0.43-0.65 μm to 1.1–2.1 μm with the haze development due to the hygroscopic growth of particles. In summer of 2018, the WSOC was mainly concentrated in PM 1 , but in a few samples, the maximum size appeared in coarse mode. This difference might due to the different relative humidity and air mass sources. While the formation process of WSOC in winter was affected by photochemical oxidation below 2.1 μm, in 1.1–2.1 μm, it tended to change from photochemical oxidation to aqueous-phase oxidation. For the coarse mode WSOC formation in winter, however, it was mainly affected by heterogeneous processes. The findings advanced our understanding of the annual trends, size distribution and formation processes of WSOC, with significant implications for air pollution control in Beijing and surrounding regions. Image 1 • Carbonaceous species in both fine and coarse modes decreased from 2013 to 2018. • The size distribution of WSOC shifted from fine to coarse during haze episodes. • In summer, coarse mode WSOC was mainly condensed on sea salt. • In winter, WSOC formation was affected by secondary processes. [ABSTRACT FROM AUTHOR]