Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Effect of nickel concentration on biohydrogen production: Organic solid waste vs. glucose

In recent years, alternative renewable energy generation sources have been investigated, highlighting the dark fermentation process due to it’s potential to obtain hydrogen-rich gas, which can be used as an energy source. Different trace metals intervene in this biological process. Nickel is one of the most important because it is a component of the [Ni–Fe] hydrogenase enzyme that catalyzes the oxidation of H₂ in numerous bacteria. The aim of this study was to evaluate the effect of nickel on biohydrogen production from organic solid waste (OSW). The experimental setup was carried out in batch tests using OSW as the substrate, glucose as a reference compound and the valuation of Ni²⁺ doses on the operation in a Sequencing Batch Reactor. The results of the batch tests showed that when using glucose as a substrate, 2 mg Ni²⁺/g VS_inoculum generated the highest hydrogen production (774 ± 7.3 mL H₂/L/d) and highest yield (55.8 ± 3.4 mL H₂/g of glucose), which was 34.4% higher than the control. Testing of different concentrations of nickel using OSW as a carbon source showed that the highest production was obtained without Ni²⁺ addition since the nickel concentration in the residue was 0.17 ± 0.06 mgNi/gVS; consequently, hydrogen production was not affected by the lack of Ni. The addition of 0.5 mg Ni²⁺/g VS_inoculum decreased acetate and butyrate production and increased caproate production.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Cladophora sp. as a sustainable feedstock for dark fermentative biohydrogen production

Macroalgae are rich in carbohydrates which can be used as a promising substrate for fermentative biohydrogen production. In this study, Cladophora sp. biomass was fermented for biohydrogen production at various inoculum/substrate (I/S) ratios against a control of inoculum without substrate in laboratory-scale batch reactors. The biohydrogen production yield ranged from 40.8 to 54.7 ml H₂/g-VS, with the I/S ratio ranging from 0.0625 to 4. The results indicated that low I/S ratios caused the overloaded accumulation of metabolic products and a significant pH decrease, which negatively affected hydrogen production bacteria's metabolic activity, thus leading to the decrease of hydrogen fermentation efficiency. The overall results demonstrated that Cladophora sp. biomass is an efficient fermentation feedstock for biohydrogen production.     

Deacylation of Calcium-Dependent Antibiotics from Streptomyces violaceoruber in Co-culture with Streptomyces sp. MG7-G1

When Streptomyces violaceoruber grows together with Streptomyces sp. MG7-G1, it reacts with strongly induced droplet production on its aerial mycelium. Initially the metabolite profile of droplets from S. violaceoruber in co-culture with Streptomyces sp. MG7-G1 was compared to samples from S. violaceoruber in single-culture by using high-performance liquid chromatography-mass spectrometry (HPLC-MS). Then, the exudate from agar plates of co-cultures and single cultures (after freezing and thawing) was also analysed. Several compounds were only observed when S. violaceoruber was grown in co-culture. Based on their high-resolution ESI mass spectra and their comparable retention times to the calcium-dependent antibiotics (CDAs) produced by S. violaceoruber, the new compounds were suspected to be deacylated calcium-dependent antibiotics (daCDAs), lacking the 2,3-epoxyhexanoyl residue of CDAs. This was verified by detailed analysis of the MS/MS spectra of the daCDAs in comparison to the CDAs. The major CDA compounds present in calcium ion-supplemented agar medium of co-cultures were daCDAs, thus suggesting that Streptomyces sp. MG7-G1 expresses a deacylase that degrades CDAs.