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Emerging contaminants (EC) distributed on surfaces in the environment can be oxidized by gas phase species (top-down) or by oxidants generated by the underlying substrate (bottom-up). One class of EC is the neonicotinoid (NN) pesticides that are widely distributed in air, water, and on plant and soil surfaces as well as on airborne dust and building materials. This study investigates the OH oxidation of the systemic NN pesticide acetamiprid (ACM) at room temperature. ACM on particles and as thin films on solid substrates were oxidized by OH radicals either from the gas phase or from an underlying TiO2 or NaNO2 substrate, and for comparison, in the aqueous phase. The site of OH attack is both the secondary >CH2 group as well as the primary -CH3 group attached to the tertiary amine nitrogen, with the latter dominating. In the case of top-down oxidation of ACM by gas phase OH radicals, addition to the -CN group also occurs. Major products are carbonyls and alcohols, but in the presence of sufficient water, their hydrolyzed products dominate. Kinetics measurements show ACM is more reactive toward gas phase OH radicals than other NN nitroguanidines, with an atmospheric lifetime of a few days. Bottom-up oxidation of ACM on TiO2 exposed to sunlight outdoors (temperatures were above 30 °C) was also shown to occur and is likely to be competitive with top-down oxidation. These findings highlight the different potential oxidation processes for EC and provide key data for assessing their environmental fates and toxicologies.

Hydroxyl radical (OH) is a key oxidant that triggers atmospheric oxidation chemistry in both gas and aqueous phases. The current understanding of its aqueous sources is mainly based on known bulk (photo)chemical processes, uptake from gaseous OH, or related to interfacial O3 and NO3 radical-driven chemistry. Here, we present experimental evidence that OH radicals are spontaneously produced at the air-water interface of aqueous droplets in the dark and the absence of known precursors, possibly due to the strong electric field that forms at such interfaces. The measured OH production rates in atmospherically relevant droplets are comparable to or significantly higher than those from known aqueous bulk sources, especially in the dark. As aqueous droplets are ubiquitous in the troposphere, this interfacial source of OH radicals should significantly impact atmospheric multiphase oxidation chemistry, with substantial implications on air quality, climate, and health.

While nitro and amino alkenes are common in pharmaceuticals, pesticides, and munitions, their environmental fates are not well known. Ozone is a ubiquitous atmospheric oxidant for alkenes, but the synergistic effects of nitrogen-containing groups on the reactions have not been measured. The kinetics and products of ozonolysis of a series of model compounds with different combinations of these functional groups have been measured in the condensed phase using stopped-flow and mass spectrometry methods. Rate constants span about six orders of magnitude with activation energies ranging from 4.3 to 28.2 kJ mol-1. Vinyl nitro groups substantially decrease the reactivity, while amino groups have the opposite effect. The site of the initial ozone attack is highly structure dependent, consistent with local ionization energy calculations. The reaction of the neonicotinoid pesticide nitenpyram, which forms toxic N-nitroso compounds, was consistent with model compounds, confirming the utility of model compounds for assessing environmental fates of these emerging contaminants.

Diffractive deep neural networks (D 2 NNs) have brought significant changes in many fields, motivating the development of diverse optical computing components. However, a crucial downside in the optical computing components is employing diffractive optical elements (DOEs) which were fabricated using commercial 3D printers. DOEs simultaneously suffer from the challenges posed by high-order diffraction and low spatial utilization since the size of individual neuron is comparable to the wavelength scale. Here, we present a design of D 2 NNs based on all-dielectric metasurfaces which substantially reduces the individual neuron size of net to scale significantly smaller than the wavelength. Metasurface-based optical computational elements can offer higher spatial neuron density while completely eliminate high-order diffraction. We numerically simulated an optical half-adder and experimentally verified it in the terahertz frequency. The optical half-adder employed a compact network with only two diffraction layers. Each layer has a size of 2 × 2 cm2 but integrated staggering 40,000 neurons. The metasurface-based D 2 NNs can further facilitate miniaturization and integration of all optical computing devices and will find applications in numerous fields such as terahertz 6G communication, photonics integrated circuits, and intelligent sensors.

Emerging contaminants are of concern due to their rapidly increasing numbers and potential ecological and human health effects. In this study, the synergistic effects of the presence of multifunctional nitro, amino and carbon-carbon double bond (C═C) groups on the gas phase ozonolysis in O2 or at the air/solid interface were investigated using five simple model compounds. The gas phase ozonolysis rate constants at 296 K were (3.5 ± 0.9) × 10-20 cm3 molecule-1 s-1 for 2-methyl-1-nitroprop-1-ene and (6.8 ± 0.8) × 10-19 cm3 molecule-1 s-1 for 4-methyl-4-nitro-1-pentene, with lifetimes of 134 and 7 days in the presence of 100 ppb ozone in the atmosphere, respectively. The rate constants for gas phase E-N,N-dimethyl-1-propenylamine and N,N-dimethylallylamine reactions with ozone were too fast (>10-18 cm3 molecule-1 s-1) to be measured, implying lifetimes of less than 5 days. A multiphase kinetics model (KM-GAP) was used to probe the gas-solid kinetics of 1-dimethylamino-2-nitroethylene, yielding a rate constant for the surface reaction of 1.8 × 10-9 cm2 molecule-1 s-1 and in the bulk 1× 10-16 cm3 molecule-1 s-1. These results show that a nitro group attached to the C═C lowers the gas phase rate constant by 2-3 orders of magnitude compared to the simple alkenes, while amino groups have the opposite effect. The presence of both groups provides counterbalancing effects. Products with deleterious health effects including dimethylformamide and formaldehyde were identified by FTIR. The identified products differentiate whether the initial site of ozone attack is C═C and/or the amino group. This study provides a basis for predicting the environmental fates of emerging contaminants and shows that both the toxicity of both the parent compounds and the products should be taken into account in assessing their environmental impacts.

Aiming at the problems of image edge blur and detail loss in most image denoising models, an image denoising model based on improved fractional calculus is proposed. Through the classification of image noise, the integer order PDE model is discussed. Based on the mathematical theory of fractional calculus, the fractional PDE model is discussed. The model is improved by combining texture detection operator, gray value detection operator, smoothing factor and fast algorithm. The simulation experiment of the model is carried out based on MATLAB simulation platform. The results show that the improved model is significantly better than other comparison models in image denoising effect, and the operation efficiency is higher.

Efficient energy data management forms a critical foundation for unlocking the carbon reduction potential of subway systems, holding significant importance in advancing urban processes towards lowcarbon and clean environments. Low-precision sampling is difficult to reflect the actual energy consumption of the station, and high-precision sampling has high requirements for the data storage and transmission capacity of the monitoring system. In order to determine the appropriate sampling accuracy, this study analyses the power load fluctuation characteristics of stations on a subway line in the North China Plain and optimizes the sampling granularity for achieving minimal data storage requirements while effectively capturing energy consumption fluctuation information. The findings indicate that a higher sampling granularity for power load monitoring is advisable during the summer to capture the frequent fluctuation characteristics of ventilation and air-conditioning system energy consumption. For a typical underground station, it is recommended to use a sampling interval of 5 min in summer and 15 min or longer in other seasons. For a typical elevated station, a sampling interval of 10 min is recommended in summer, and 20 min or longer in other seasons.