Extractive dividing-wall column (EDWC) was proved to be a promising energy-saving technique for the separation of multiple azeotropes or close-boiling mixtures; however, its controllability is very challenging due to its intensified structure with smaller physical space and strong interactions. Most studies on the EDWC control focused on evaluating the performance of temperature or composition control using proportional-integral (PI) control; nevertheless, significant steady-state offsets and overshoots are present in the control of two product purities of EDWC under different disturbances. In this paper, the performance of single temperature control (TC), temperature difference control (TDC) and double temperature control (DTDC) schemes for PI control of EDWC was first examined for the separation of toluene and 2-methoxyethanol using dimethyl sulfoxide as the entrainer. The results show that the steady-state offsets in product purities of TDC scheme are much smaller than those of TC and DTDC schemes. Subsequently, the offset-free model predictive control (MPC) based on temperature differences was proposed to improve the operation of EDWC. The results indicate that this MPC scheme can achieve much better control performance than PI control in terms of maximum transient deviation, amplitude of oscillations and setting time.

The development for high-efficiency noble-metal-free catalysts of electrochemical nitrogen reduction reaction (NRR) to ammonia under ambient conditions has great significance in fertilizer production and energy storage. Considering a major role...

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This tutorial and review of multi-objective optimization (MOO) gives a detailed explanation of the 5 steps to create, solve, and then select the optimum result. Unlike single-objective optimization, the fifth step of selection or ranking of solutions is often overlooked by the authors of papers dealing with MOO applications. It is necessary to undertake a multi-criteria analysis to choose the best solution. A review of the recent publications using MOO for chemical process engineering problems shows a doubling of publications between 2016 and 2019. MOO applications in the energy area have seen a steady increase of over 20% annually over the last 10 years. The three key methods for solving MOO problems are presented in detail, and an emerging area of surrogate-assisted MOO is also described. The objectives used in MOO trade off conflicting requirements of a chemical engineering problem; these include fundamental criteria such as reaction yield or selectivity; economics; energy requirements; environmental performance; and process control. Typical objective functions in these categories are described, selection/ranking techniques are outlined, and available software for MOO are listed. It is concluded that MOO is gaining popularity as an important tool and is having an increasing use and impact in chemical process engineering.

Abstract. Oxygenated organic molecules (OOMs) are crucial for atmospheric new particle formation and secondary organic aerosol (SOA) growth. Therefore, understanding their chemical composition, temporal behavior, and sources is of great importance. Previous studies on OOMs mainly focus on environments where biogenic sources are predominant, yet studies on sites with dominant anthropogenic emissions, such as megacities, have been lacking. Here, we conducted long-term measurements of OOMs, covering four seasons of the year 2019, in urban Beijing. The OOM concentration was found to be the highest in summer (1.6×108 cm−3), followed by autumn (7.9×107 cm−3), spring (5.7×107 cm−3) and winter (2.3×107 cm−3), suggesting that enhanced photo-oxidation together with the rise in temperature promote the formation of OOMs. Most OOMs contained 5 to 10 carbon atoms and 3 to 7 effective oxygen atoms (nOeff=nO-2×nN). The average nOeff increased with increasing atmospheric photo-oxidation capacity, which was the highest in summer and the lowest in winter and autumn. By performing a newly developed workflow, OOMs were classified into the following four types: aromatic OOMs, aliphatic OOMs, isoprene OOMs, and monoterpene OOMs. Among them, aromatic OOMs (29 %–41 %) and aliphatic OOMs (26 %–41 %) were the main contributors in all seasons, indicating that OOMs in Beijing were dominated by anthropogenic sources. The contribution of isoprene OOMs increased significantly in summer (33 %), which is much higher than those in the other three seasons (8 %–10 %). Concentrations of isoprene (0.2–5.3×107 cm−3) and monoterpene (1.1–8.4×106 cm−3) OOMs in Beijing were lower than those reported at other sites, and they possessed lower oxygen and higher nitrogen contents due to high NOx levels (9.5–38.3 ppbv – parts per billion by volume) in Beijing. With regard to the nitrogen content of the two anthropogenic OOMs, aromatic OOMs were mainly composed of CHO and CHON species, while aliphatic OOMs were dominated by CHON and CHON2 ones. Such prominent differences suggest varying formation pathways between these two OOMs. By combining the measurements and an aerosol dynamic model, we estimated that the SOA growth rate through OOM condensation could reach 0.64, 0.61, 0.41, and 0.30 µg m−3 h−1 in autumn, summer, spring, and winter, respectively. Despite the similar concentrations of aromatic and aliphatic OOMs, the former had lower volatilities and, therefore, showed higher contributions (46 %–62 %) to SOA than the latter (14 %–32 %). By contrast, monoterpene OOMs and isoprene OOMs, limited by low abundances or high volatilities, had low contributions of 8 %–12 % and 3 %–5 %, respectively. Overall, our results improve the understanding of the concentration, chemical composition, seasonal variation, and potential atmospheric impacts of OOMs, which can help formulate refined restriction policy specific to SOA control in urban areas.

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Abstract. Although the anthropogenic emissions of SO2 have decreased significantly in China, the decrease in SO42- in PM2.5 is much smaller than that of SO2. This implies an enhanced formation rate of SO42- in the ambient air, and the mechanism is still under debate. This work investigated the formation mechanism of particulate sulfate based on statistical analysis of long-term observations in Shijiazhuang and Beijing supported with flow tube experiments. Our main finding was that the sulfur oxidation ratio (SOR) was exponentially correlated with ambient RH in Shijiazhuang (SOR = 0.15+0.0032×exp⁡(RH/16.2)) and Beijing (SOR = -0.045+0.12×exp⁡(RH/37.8)). In Shijiazhuang, the SOR is linearly correlated with the ratio of aerosol water content (AWC) in PM2.5 (SOR = 0.15+0.40×AWC/PM2.5). Our results suggest that uptake of SO2 instead of oxidation of S(IV) in the particle phase is the rate-determining step for sulfate formation. NH4NO3 plays an important role in the AWC and the change of particle state, which is a crucial factor determining the uptake kinetics of SO2 and the enhanced SOR during haze days. Our results show that NH3 significantly promoted the uptake of SO2 and subsequently the SOR, while NO2 had little influence on SO2 uptake and SOR in the presence of NH3.

Abstract. Gaseous sulfuric acid (SA) has received a lot of attention for its crucial role in atmospheric new particle formation (NPF). And for this reason, studies until now have mainly focused on daytime SA when most NPF events occur. While daytime SA production is driven by SO2 oxidation of OH radicals of photochemical origin, the formation of SA during nighttime and its potential influence on particle formation remains poorly understood. Here we present evidence for significant nighttime SA production in urban Beijing during winter, yielding concentrations between 1.0 and 3.0 × 106 cm−3. We found a high frequency (∼ 30 %) of nighttime SA events, which are defined by the appearance of a distinct SA peak observed between 20:00 and 04:00 local time, with the maximum concentration exceeding 1.0 × 106 cm−3. These events mostly occurred during unpolluted nights with a low vapor condensation sink. Furthermore, we found that under very clean conditions (visibility > 16.0 km) with abundant ozone (concentration > 2.0 × 1011 cm−3, ∼ 7 ppb), the overall sink of SA was strongly correlated with the products of O3, alkenes and SO2 concentrations, suggesting that the ozonolysis of alkenes played a major role in nighttime SA formation under such conditions. This is in light of previous studies showing that the ozonolysis of alkenes can form OH radicals and stabilized Criegee intermediates (SCIs), both of which are able to oxidize SO2 and thus lead to SA formation. However, we also need to point out that there exist additional sources of SA under more polluted conditions, which are not investigated in this study. Moreover, there was a strong correlation between SA concentration and the number concentration of sub-3 nm particles on both clean and polluted nights. Different from forest environments, where oxidized biogenic vapors are the main driver of nighttime clustering, our study demonstrates that the formation of nighttime cluster mode particles in urban environments is mainly driven by nighttime SA production.