CHARACTERISTICS AND KINETICS OF BIOMASS PYLOLYSIS IN A MICRO FLUIDIZED BED REACTOR

A Micro Fluidized Bed Reactor (MFBR) was developed to enable on-line pulse feeding and isothermal differential reaction of particle reactant. Application of the MFBR to biomass pyrolysis demonstrated that the resulting globe kinetics parameters were 11.77 kJ/mol and 1.45 s-1 on the gas release characteristics, respectively

The simultaneous removal of NOx and SO2 from flue gas by direct injection of sorbents in furnace of waste incinerator

A effective pollution source control technology (called SDNS) has been developed to simultaneously remove NOx and SO2 from flue gas by direct injection of fine denitration (DeNO(x)) and desulfuration (DeSO(x)) agents (named DNS and DSS, respectively) into the furnace of 300 t.d(-1) waste incinerator. 75 % DeNO(x) efficiency and 95 % DeSO(x) efficiency could be acquired by simultaneous injection of 0.4 g.m(-3) DNS and 0.6 g.m(-3) DSS, and the SDNS system can run steadily with less than 80 mg.m 3 NOx and 10 mg.m(-3) SO2 left in flue gas, which can be comparable with the complex and expensive tail-end purification processes of flue gas. The interaction and interspersion between the active components and the polymer in DNS and DSS facilitate their high reactivity with NOx and SO2 at high temperatures, and the synergistic effect between DNS and DSS in furnace further decreases their consumption. The composition analysis of ash demonstrates that the majority of injected fine DNS and DSS particles flowed out with the flue gas, and only a fraction of them was left in furnace. In addition, the simple SDNS process can not only lower the sorbent consumption but also cut down two-thirds of the investment and operating costs compared with the traditional DeNO(x) and DeSO(x) process. The demonstrated technological and economic advantages of the SDNS process signify its promising application prospect for the source control of NOx and SO2 emissions from small and medium-sized waste incineration projects

The simultaneous removal of NOx and SO2 from flue gas by direct injection of sorbents in furnace of waste incinerator

A effective pollution source control technology (called SDNS) has been developed to simultaneously remove NOx and SO2 from flue gas by direct injection of fine denitration (DeNO(x)) and desulfuration (DeSO(x)) agents (named DNS and DSS, respectively) into the furnace of 300 t.d(-1) waste incinerator. 75 % DeNO(x) efficiency and 95 % DeSO(x) efficiency could be acquired by simultaneous injection of 0.4 g.m(-3) DNS and 0.6 g.m(-3) DSS, and the SDNS system can run steadily with less than 80 mg.m 3 NOx and 10 mg.m(-3) SO2 left in flue gas, which can be comparable with the complex and expensive tail-end purification processes of flue gas. The interaction and interspersion between the active components and the polymer in DNS and DSS facilitate their high reactivity with NOx and SO2 at high temperatures, and the synergistic effect between DNS and DSS in furnace further decreases their consumption. The composition analysis of ash demonstrates that the majority of injected fine DNS and DSS particles flowed out with the flue gas, and only a fraction of them was left in furnace. In addition, the simple SDNS process can not only lower the sorbent consumption but also cut down two-thirds of the investment and operating costs compared with the traditional DeNO(x) and DeSO(x) process. The demonstrated technological and economic advantages of the SDNS process signify its promising application prospect for the source control of NOx and SO2 emissions from small and medium-sized waste incineration projects

Chinese-style Plate Recognition Based on Artificial Neural Network and Statistics

AbstractIn this paper we propose an algorithm for the recognition of Chinese-style vehicle license plates. Because the resolution of videos is much lower than that of static images, the approaches designed for recognizing license plates in the static picture don’t yield satisfying results when processing videos. In addition, the traditional approaches only take a single snapshot per plate to recognize, which is insufficient to yield accurate recognition results for that plate. In order to solve this problem, our approach processes multiple frames and generates a series of results per plate. And it combines artificial neural network, which identifies characters in the snapshot, and a simple statistics which finds the most appealing results among the result sequences. The statistics analysis can confirm the accuracy of identification. Finally, this approach has been proved to be accurate and efficient by the experiment

Analysis of Influencing Factors of Thermal Coal Price

As the world’s largest coal consumer, China’s coal consumption in 2021 was 2934.4 million tons of standard coal. Thermal coal occupies an important position in the coal market and industry system, as an important raw material in the power industry, steel industry and other industries. The price of thermal coal in 2021 was at its highest level in a decade, and reached a historical level of about 2587.5 yuan per ton in October 2021. In the same month, the government intervened in the thermal coal price, which fell 51.9% by the end of the year under the influence of the policy. In previous studies, there has been little research on thermal coal and the impact of the variable “policy” on the thermal coal price. Thus, this paper analyzed the factors that affect the price fluctuation of thermal coal, and the impact of economic policy uncertainty on the thermal coal price. The cointegration test and forecast-error variance decomposition (FEVD) are adopted in this study. Our results show that the impact of policy uncertainty on the thermal coal price gradually increases over time, but the impact of policy uncertainty on price is negative and not as strong as expected. On the contrary, inventory and other energy prices have a greater positive impact on the price of thermal coal. The results of this study are of significance for the prediction of thermal coal prices in the future

Analysis of Influencing Factors of Thermal Coal Price

As the world’s largest coal consumer, China’s coal consumption in 2021 was 2934.4 million tons of standard coal. Thermal coal occupies an important position in the coal market and industry system, as an important raw material in the power industry, steel industry and other industries. The price of thermal coal in 2021 was at its highest level in a decade, and reached a historical level of about 2587.5 yuan per ton in October 2021. In the same month, the government intervened in the thermal coal price, which fell 51.9% by the end of the year under the influence of the policy. In previous studies, there has been little research on thermal coal and the impact of the variable “policy” on the thermal coal price. Thus, this paper analyzed the factors that affect the price fluctuation of thermal coal, and the impact of economic policy uncertainty on the thermal coal price. The cointegration test and forecast-error variance decomposition (FEVD) are adopted in this study. Our results show that the impact of policy uncertainty on the thermal coal price gradually increases over time, but the impact of policy uncertainty on price is negative and not as strong as expected. On the contrary, inventory and other energy prices have a greater positive impact on the price of thermal coal. The results of this study are of significance for the prediction of thermal coal prices in the future

Flotation Behaviors of Perovskite, Titanaugite, and Magnesium Aluminate Spinel Using Octyl Hydroxamic Acid as the Collector

The flotation behaviors of perovskite, titanaugite, and magnesium aluminate spinel (MA-spinel), using octyl hydroxamic acid (OHA) as the collector, were investigated using microflotation experiments, zeta-potential measurements, Fourier transform infrared (FT-IR) analyses, X-ray photoelectron spectroscopy (XPS) analyses, and flotation experiments on artificially mixed minerals. The microflotation experiments show that the floatability of perovskite is clearly better than titanaugite and MA-spinel at around pH 5.5, while titanaugite possesses certain floatability at pH 6.0–6.5, and MA-spinel displays good floatability at pH > 8.0. The results of the FT-IR and XPS analyses show that OHA mainly interacts with Ti, resulting in perovskite flotation, and that the Al on titanaugite, as well as the Mg and Al on the MA-spinel surface, chemically react with OHA under acidic conditions. However, OHA mainly reacts with the Ti and Ca on the perovskite surface, Ca and Mg on the titanaugite surface, and Mg and Al on the MA-spinel surface under alkaline conditions. The results of the artificially mixed mineral flotation experiment show that the concentrate of TiO2 grade increased from 19.73% to 30.18% at pH 5.4, which indicates that a weakly acidic solution is the appropriate condition for the flotation separation of perovskite from titanaugite and MA-spinel. The results of the modified slag flotation experiments show that the TiO2 grade of concentrate increased from 18.13% to 23.88% at pH 5.4, through the open circuit test of “one roughing and one cleaning”. OHA displays selectivity toward perovskite in the modified slag flotation, but the consumption of H2SO4 is very high. The CaSO4 precipitate covered on the mineral surfaces results in poor TiO2 grade and recovery

Clean air actions in China, PM2.5 exposure, and household medical expenditures: A quasi-experimental study.

BackgroundExposure to air pollution, a leading contributor to the global burden of disease, can cause economic losses. Driven by clean air policies, the air quality in China, one of the most polluted countries, has improved rapidly since 2013. This has enabled a unique, quasi-experiment to assess the economic impact of air pollution empirically.Methods and findingsUsing a series of nation-scale longitudinal surveys in 2011, 2013, and 2015, we first examined the questionnaire-based medical expenditure changes before and after the policy intervention for air pollution. Using a state-of-the-art estimator of the historical concentration of particulate matters with diameter less than 2.5 μm (particulate matter (PM)2.5), we further quantified the association between household medical expenditure and PM2.5 using mixed-effect models of the repeated measurements from 26,511 households in 126 cities. Regression models suggest a robust linear association between reduced PM2.5 and saved medical expenditures, since the association did not vary significantly across models with different covariate adjustments, subregions, or subpopulations. Each 10 μg/m3 reduction in PM2.5 was associated with a saving of 251.6 (95% CI: 30.8, 472.3; p-value = 0.026) Yuan in per capita annual medical expenditure. However, due to limitations in data quality (e.g., self-reported expenditures), and imperfect control for unmeasured confounders or impact from concurrent healthcare reform in China, the causality underlying our findings should be further confirmed or refuted.ConclusionIn this study, we observed that compared with the PM2.5 reduction in 2013, the PM2.5 reduction in 2017 was associated with a saving of 552 (95% CI: 68, 1036) Yuan / (person × year), or approximately 736 billion Yuan (equivalent to 111 billion US dollar) per year nationally, which is equivalent to approximately 1% of the national gross domestic product of China

Improving the Real-time Marine Forecasting of the Northern South China Sea by Assimilation of Glider-observed T/S Profiles

Prediction of marine conditions is notoriously challenging in the northern South China Sea (NSCS) due to inadequate observations in the region. The underwater gliders that were developed during the past decade may provide observing platforms that could produce required observations. During a field experiment, temperature/salinity (T/S) profiles from a set of underwater gliders were assimilated into a real-time marine forecasting system, along with the assimilation of climatological monthly mean Argo data to constrain the basin-wide model biases. The results show that, in addition to the reduction of the basin-wide model biases by the assimilation of the climatological monthly mean Argo data, the assimilation of glider-observed T/S profiles is efficient to reduce the local biases of the NSCS marine forecasting by as much as 28-31% (19-36%) in 24 h to 120 h forecasts for temperature (salinity) from sea surface to a depth of 1000 m. Our results imply that the real-time marine forecasting for the NSCS can largely benefit from a sustainable glider observing network of the NSCS in the future