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Y. He, Y. He, X. Ding et al.

<p>Long-term data on PM<span class="inline-formula">_2.5</span> chemical composition provide essential information for evaluating the effectiveness of air pollution control measures and understanding the evolving mechanisms of secondary species formation in the real atmosphere. This study presented field measurements of PM<span class="inline-formula">_2.5</span> and its chemical composition at a regional background site in the Pearl River Delta (PRD) from 2007 to 2020. PM<span class="inline-formula">_2.5</span> concentration declined significantly from 87.1 <span class="inline-formula">±</span> 15.5 to 34.0 <span class="inline-formula">±</span> 11.3 <span class="inline-formula">µ</span>g m<span class="inline-formula">⁻³</span> (<span class="inline-formula">−</span>4.0 <span class="inline-formula">µ</span>g m<span class="inline-formula">⁻³</span> yr<span class="inline-formula">⁻¹</span>). The proportion of secondary species increased from 57 % to 73 % with the improvement in air quality. Among these species, sulfate (SO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M14" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="13pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="9e5c3b810d685753e2e31321de9aeed4"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-13729-2025-ie00001.svg" width="13pt" height="17pt" src="acp-25-13729-2025-ie00001.png"/></svg:svg></span></span>) showed a sharp decline, while nitrate (NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="9f81e901bf06635e082f559a787da68a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-13729-2025-ie00002.svg" width="9pt" height="16pt" src="acp-25-13729-2025-ie00002.png"/></svg:svg></span></span>) exhibited a moderate decrease. Consequently, the proportion of NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M16" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="06954914259a113e7faaa0d01a8ee756"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-13729-2025-ie00003.svg" width="9pt" height="16pt" src="acp-25-13729-2025-ie00003.png"/></svg:svg></span></span> in 2020 doubled relative to 2007. In addition, we further found that SO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M17" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="13pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="31655fb078684da776f2b5262b6b028b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-13729-2025-ie00004.svg" width="13pt" height="17pt" src="acp-25-13729-2025-ie00004.png"/></svg:svg></span></span> reduction (<span class="inline-formula">−</span>10 % yr<span class="inline-formula">⁻¹</span>) lagged behind SO<span class="inline-formula">₂</span> reduction (<span class="inline-formula">−</span>13 % yr<span class="inline-formula">⁻¹</span>), while NO<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M23" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="9pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="d4917cb251612ae03efebb0a66479930"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-25-13729-2025-ie00005.svg" width="9pt" height="16pt" src="acp-25-13729-2025-ie00005.png"/></svg:svg></span></span> reduction (<span class="inline-formula">−</span>6 % yr<span class="inline-formula">⁻¹</span>) outpaced that of NO<span class="inline-formula">₂</span> (<span class="inline-formula">−</span>3 % yr<span class="inline-formula">⁻¹</span>). These contrasting trends were associated with an increase in sulfur oxidation rate (SOR) and a decrease in nitrogen oxidation rate (NOR). Changes in PM<span class="inline-formula">_2.5</span> chemical composition also influenced aerosol physicochemical properties, such as aerosol pH (0.04 yr<span class="inline-formula">⁻¹</span>), aerosol liquid water content (ALWC, <span class="inline-formula">−</span>1.1 <span class="inline-formula">µ</span>g m<span class="inline-formula">⁻³</span> yr<span class="inline-formula">⁻¹</span>), and the light extinction coefficient (<span class="inline-formula">−</span>21.44 Mm<span class="inline-formula">⁻¹</span> yr<span class="inline-formula">⁻¹</span>). Given important roles of aerosol acidity and ALWC in the heterogeneous reactions, these changes may further inhibit the formation of secondary species in the atmosphere, particularly secondary organic aerosols.</p>

Song Jiang, Lu Wang, Shuo Wang et al.

Considering the implications for the environment and human health, oil-contaminated soil generated in the petroleum industry requires treatment. Chemical cleaning represents an effective treatment approach for oil-contaminated soil and has attracted considerable attention. In this study, sodium d-gluconate (C₆H₁₁NaO₇), trisodium citrate (C₆H₅Na₃O₇), and L-arginine (C₆H₁₄N₄O₂) were employed as detergents to remove oil from oily sludge. The impacts of sludge (solid) concentration (<i>C</i>_S), types of detergents, temperature (<i>T</i>), and pH value on the deoiling efficiency (<i>D</i>_e) were systematically investigated. The results indicated that at a given detergent concentration (<i>C</i>_DG) and <i>C</i>_S, <i>D</i>_e followed the order C₆H₁₁NaO₇ > C₆H₅Na₃O₇ > C₆H₁₄N₄O₂. When <i>C</i>_S was 3.86 g·L⁻¹ and <i>C</i>_DG was 10.0 g·L⁻¹, sodium d-gluconate achieved a maximum <i>D</i>_e of approximately 85%. Additionally, at a fixed <i>C</i>_S, <i>D</i>_e decreased as the pH value increased, while it increased with increasing temperature. Interestingly, during the deoiling equilibrium, an obvious “solid effect” (or <i>C</i>_S−effect) was observed. The “solid effect” refers to the phenomenon where the oil distribution coefficient (<i>K</i>_D) changes with an increase in <i>C</i>_S. The observed <i>C</i>_S effect was described using the surface component activity (SCA) model. The values of the intrinsic distribution coefficient (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>K</mi><mi>D</mi><mn>0</mn></msubsup></mrow></semantics></math></inline-formula>) and <i>C</i>_S−effect constant (<i>γ</i>), which are the model parameters of the SCA model, were derived from three detergent−sludge systems under different temperatures (<i>T</i>) and pH values. The strength of the <i>C</i>_S effect (or <i>γ</i> value) was found to be independent of detergent type and increased as <i>T</i> and pH value increased. This study broadens the application range of the SCA model and contributes to a deeper understanding of the adsorption and desorption behavior of oil droplets at the solid−liquid interface.

Ainur Berkinbayeva, Shynar Saulebekkyzy, Bagdaulet Kenzhaliyev et al.

Cyanide-containing effluents from hydrometallurgical gold extraction pose significant environmental risks due to their high toxicity. This study investigates the detoxification of cyanide-laden tailings from the Altyntau Kokshetau gold extraction facility (Kazakhstan) using sodium percarbonate in alkaline conditions. Employing response surface methodology (RSM) and central composite design (CCD), we optimized key parameters—pH (10–12), sodium percarbonate dosage (1.5–4.0 g), reaction time (10–40 min) and temperature (20–25 °C)—achieving 83.33% detoxification efficiency within 40 min and 99.99% after 8 h, reducing cyanide from 443.2 mg/L to 0.05 mg/L. The process follows biphasic pseudo-first-order kinetics ((k₁ = 0.0517) min^–1 initially, (k₂ = 0.01665) min^–1 subsequently), driven by HO^• radical-mediated oxidation of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>C</mi><mi>N</mi></mrow><mrow><mo>−</mo></mrow></msup></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>C</mi><mi>N</mi><mi>O</mi></mrow><mrow><mo>−</mo></mrow></msup></mrow></semantics></math></inline-formula>, as described by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msup><mrow><mi>C</mi><mi>N</mi></mrow><mrow><mo>−</mo></mrow></msup><mo>+</mo><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub><mo>→</mo><msup><mrow><mi>C</mi><mi>N</mi><mi>O</mi></mrow><mrow><mo>−</mo></mrow></msup><mo>+</mo><mo> </mo><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub><mi>O</mi></mrow></semantics></math></inline-formula>). pH emerged as the dominant factor, optimizing radical stability and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>C</mi><mi>N</mi></mrow><mrow><mo>−</mo></mrow></msup></mrow></semantics></math></inline-formula> protonation (pK_a ≈ 9.21) at pH 10. Infrared spectroscopy confirmed the presence of cyanide complexes (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>[</mo><mi>A</mi><mi>u</mi><msub><mrow><mo>(</mo><mi>C</mi><mi>N</mi><mo>)</mo></mrow><mrow><mn>2</mn></mrow></msub><msup><mrow><mo>]</mo></mrow><mrow><mo>−</mo></mrow></msup></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>[</mo><mi>F</mi><mi>e</mi><msub><mrow><mo>(</mo><mi>C</mi><mi>N</mi><mo>)</mo></mrow><mrow><mn>6</mn></mrow></msub><msup><mrow><mo>]</mo></mrow><mrow><mn>4</mn><mo>−</mo></mrow></msup></mrow></semantics></math></inline-formula>) in tailings, underscoring the need for effective treatment. The method ensures compliance with stringent environmental standards (e.g., ICMI limit of 0.2 mg/L), offering a scalable, eco-efficient solution for mitigating the environmental footprint of gold mining operations.

Frederik vom Ende

We present a simple, dimension-independent criterion which guarantees that some quantum channel $Φ$ is divisible, i.e. that there exists a non-trivial factorization $Φ=Φ_1Φ_2$. The idea is to first define an "elementary" channel $Φ_2$ and then to analyze when $ΦΦ_2^{-1}$ is completely positive. The sufficient criterion obtained this way -- which even yields an explicit factorization of $Φ$ -- is that one has to find orthogonal unit vectors $x,x^\perp$ such that $\langle x^\perp|\mathcal K_Φ\mathcal K_Φ^\perp|x\rangle=\langle x|\mathcal K_Φ\mathcal K_Φ^\perp|x\rangle=\{0\}$ where $\mathcal K_Φ$ is the Kraus subspace of $Φ$ and $\mathcal K_Φ^\perp$ is its orthogonal complement. Of course, using linearity this criterion can be reduced to finitely many equalities. Generically, this division even lowers the Kraus rank which is why repeated application -- if possible -- results in a factorization of $Φ$ into in some sense "simple" channels. Finally, be aware that our techniques are not limited to the particular elementary channel we chose.

Juexiu Li, Qixu Shi, Maiqi Sun et al.

The persulfate-based advanced oxidation process has been an effective method for refractory organic pollutants’ degradation in aqueous phase. Herein, α-MnO₂ with nanowire morphology was facially fabricated via a one-step hydrothermal method and successfully activated peroxymonosulfate (PMS) for Rhodamine B (RhB) degradation. Influencing factors, including the hydrothermal parameter, PMS concentration, α-MnO₂ dosage, RhB concentration, initial pH, and anions, were systematically investigated. The corresponding reaction kinetics were further fitted by the pseudo-first-order kinetic. The RhB degradation mechanism via α-MnO₂ activating PMS was proposed according to a series of quenching experiments and the UV-vis scanning spectrum. Results showed that α-MnO₂ could effectively activate PMS to degrade RhB and has good repeatability. The catalytic RhB degradation reaction was accelerated by increasing the catalyst dosage and the PMS concentration. The effective RhB degradation performance can be attributed to the high content of surface hydroxyl groups and the greater reducibility of α-MnO₂, and the contribution of different ROS (reactive oxygen species) was ¹O₂ > <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow><mrow><mo>·</mo><mo>−</mo></mrow></msubsup></mrow></semantics></math></inline-formula> > <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>SO</mi></mrow><mrow><mn>4</mn></mrow><mrow><mo>·</mo><mo>−</mo></mrow></msubsup></mrow></semantics></math></inline-formula> > ·OH.

Hao Jiang, Oskar K. G. Svensson, Ulf Ryde

We have calculated redox potentials of the two metal clusters in Mo-nitrogenase with quantum mechanical (QM) calculations. We employ an approach calibrated for iron–sulfur clusters with 1–4 Fe ions, involving QM-cluster calculations in continuum solvent and large QM systems (400–500 atoms), based on structures from combined QM and molecular mechanics (QM/MM) geometry optimisations. Calculations on the P-cluster show that we can reproduce the experimental redox potentials within 0.33 V. This is similar to the accuracy obtained for the smaller clusters, although two of the redox reactions involve also proton transfer. The calculated P¹⁺/P^N redox potential is nearly the same independently of whether P¹⁺ is protonated or deprotonated, explaining why redox titrations do not show any pH dependence. For the FeMo cluster, the calculations clearly show that the formal oxidation state of the cluster in the resting E₀ state is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>Mo</mi></mrow><mrow><mi>III</mi></mrow></msup><msubsup><mrow><mi>Fe</mi></mrow><mn>3</mn><mrow><mi>II</mi></mrow></msubsup><msubsup><mrow><mi>Fe</mi></mrow><mn>4</mn><mrow><mi>III</mi></mrow></msubsup></mrow></semantics></math></inline-formula> , in agreement with previous experimental studies and QM calculations. Moreover, the redox potentials of the first five E₀–E₄ states are nearly constant, as is expected if the electrons are delivered by the same site (the P-cluster). However, the redox potentials are insensitive to the formal oxidation states of the Fe ion (i.e., whether the added protons bind to sulfide or Fe ions). Finally, we show that the later (E₄–E₈) states of the reaction mechanism have redox potential that are more positive (i.e., more exothermic) than that of the E₀/E₁ couple.

M. Zhou, M. Zhou, G. Zheng et al.

<p>Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers is crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China, calculated with the ISORROPIA model based on observed gas and aerosol compositions. The implementation of the Air Pollution Prevention and Control Action Plan led to <span class="inline-formula">−35.8</span> %, <span class="inline-formula">−37.6</span> %, <span class="inline-formula">−9.6</span> %, <span class="inline-formula">−81.0</span> % and 1.2 % changes of PM<span class="inline-formula">_2.5</span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="a8455a3a3390243c17ea2f3ca419ac4e"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-13833-2022-ie00001.svg" width="29pt" height="17pt" src="acp-22-13833-2022-ie00001.png"/></svg:svg></span></span>, <span class="inline-formula">NH_<i>x</i></span>, non-volatile cations (NVCs) and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M8" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="8a872e45f44a0fc3c08e466e371cfb3a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-13833-2022-ie00002.svg" width="25pt" height="16pt" src="acp-22-13833-2022-ie00002.png"/></svg:svg></span></span> in the Yangtze River Delta (YRD) region during this period. Different from the drastic changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH showed a minor change of <span class="inline-formula">−0.24</span> over the 9 years. Besides the multiphase buffer effect, the opposite effects from the changes of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="8c898138530c760447165fe6cdc920bb"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-13833-2022-ie00003.svg" width="29pt" height="17pt" src="acp-22-13833-2022-ie00003.png"/></svg:svg></span></span> and non-volatile cations played key roles in determining this minor pH trend, contributing to a change of <span class="inline-formula">+0.3</span>8 and <span class="inline-formula">−0.35</span>, respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, <span class="inline-formula">SO₂</span>, <span class="inline-formula">NO_<i>x</i></span> and <span class="inline-formula">NH₃</span> emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by <span class="inline-formula">∼0.19</span>, resulting in 0.04 less <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M17" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="822fcc3376206f5298bc14405cca7022"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-13833-2022-ie00004.svg" width="25pt" height="16pt" src="acp-22-13833-2022-ie00004.png"/></svg:svg></span></span> and 0.12 less <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M18" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="7b888eb222795ca6a6dd2ceb535b59a0"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-13833-2022-ie00005.svg" width="24pt" height="15pt" src="acp-22-13833-2022-ie00005.png"/></svg:svg></span></span> partitioning ratios, which suggests that <span class="inline-formula">NH₃</span> and <span class="inline-formula">NO_<i>x</i></span> emission controls are effective in mitigating haze pollution in eastern China.</p>

N. J. Speetjens, G. Tanski, G. Tanski et al.

<p>Ongoing climate warming in the western Canadian Arctic is leading to thawing of permafrost soils and subsequent mobilization of its organic matter pool. Part of this mobilized terrestrial organic matter enters the aquatic system as dissolved organic matter (DOM) and is laterally transported from land to sea. Mobilized organic matter is an important source of nutrients for ecosystems, as it is available for microbial breakdown, and thus a source of greenhouse gases. We are beginning to understand spatial controls on the release of DOM as well as the quantities and fate of this material in large Arctic rivers. Yet, these processes remain systematically understudied in small, high-Arctic watersheds, despite the fact that these watersheds experience the strongest warming rates in comparison. Here, we sampled soil (active layer and permafrost) and water (porewater and stream water) from a small ice wedge polygon (IWP) catchment along the Yukon coast, Canada, during the summer of 2018. We assessed the organic carbon (OC) quantity (using dissolved (DOC) and particulate OC (POC) concentrations and soil OC content), quality (<span class="inline-formula"><i>δ</i>¹³C</span> DOC, optical properties and source apportionment) and bioavailability (incubations; optical indices such as slope ratio, <span class="inline-formula"><i>S</i>_r</span>; and humification index, HIX) along with stream water properties (temperature, <span class="inline-formula"><i>T</i></span>; pH; electrical conductivity, EC; and water isotopes). We classify and compare different landscape units and their soil horizons that differ in microtopography and hydrological connectivity, giving rise to differences in drainage capacity. Our results show that porewater DOC concentrations and yield reflect drainage patterns and waterlogged conditions in the watershed. DOC yield (in <span class="inline-formula">mg DOC g⁻¹ soil OC</span>) generally increases with depth but shows a large variability near the transition zone (around the permafrost table). Active-layer porewater DOC generally is more labile than permafrost DOC, due to various reasons (heterogeneity, presence of a paleo-active-layer and sampling strategies). Despite these differences, the very long transport times of porewater DOC indicate that substantial processing occurs in soils prior to release into streams. Within the stream, DOC strongly dominates over POC, illustrated by <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><mi mathvariant="normal">DOC</mi><mo>/</mo><mi mathvariant="normal">POC</mi></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="56pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="db336dddfee8670dea778afe75189a6a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-19-3073-2022-ie00001.svg" width="56pt" height="14pt" src="bg-19-3073-2022-ie00001.png"/></svg:svg></span></span> ratios around 50, yet storm events decrease that ratio to around 5. Source apportionment of stream DOC suggests a contribution of around 50 % from permafrost/deep-active-layer OC, which contrasts with patterns observed in large Arctic rivers (12 <span class="inline-formula">±</span> 8 %; Wild et al., 2019). Our 10 <span class="inline-formula">d</span> monitoring period demonstrated temporal DOC patterns on multiple scales (i.e., diurnal patterns, storm events and longer-term trends), underlining the need for high-resolution long-term monitoring. First estimates of Black Creek annual DOC (8.2 <span class="inline-formula">±</span> 6.4 <span class="inline-formula">t DOC yr⁻¹</span>) and POC (0.21 <span class="inline-formula">±</span> 0.20 <span class="inline-formula">t yr⁻¹</span>) export allowed us to make a rough upscaling towards the entire Yukon Coastal Plain (34.51 <span class="inline-formula">±</span> 2.7 <span class="inline-formula">kt DOC yr⁻¹</span> and 8.93 <span class="inline-formula">±</span> 8.5 <span class="inline-formula">kt POC yr⁻¹</span>). Rising Arctic temperatures, increases in runoff, soil organic matter (OM) leaching, permafrost thawing and primary production are likely to increase the net lateral OC flux. Consequently, altered lateral fluxes may have strong impacts on Arctic aquatic ecosystems and Arctic carbon cycling.</p>

Claudeth Hernández, Karo Michaelian

We have proposed that the abiogenesis of life around the beginning of the Archean may have been an example of “spontaneous” microscopic dissipative structuring of UV-C pigments under the prevailing surface ultraviolet solar spectrum. The thermodynamic function of these Archean pigments (the “fundamental molecules of life”), as for the visible pigments of today, was to dissipate the incident solar light into heat. We have previously described the non-equilibrium thermodynamics and the photochemical mechanisms which may have been involved in the dissipative structuring of the purines adenine and hypoxanthine from the common precursor molecules of hydrogen cyanide and water under this UV light. In this article, we extend our analysis to include the production of the other two important purines, guanine and xanthine. The photochemical reactions are presumed to occur within a fatty acid vesicle floating on a hot (∼80 °C) neutral pH ocean surface exposed to the prevailing UV-C light. Reaction–diffusion equations are resolved under different environmental conditions. Significant amounts of adenine (∼<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>5</mn></mrow></msup></semantics></math></inline-formula> M) and guanine (∼<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>6</mn></mrow></msup></semantics></math></inline-formula> M) are obtained within 60 Archean days, starting from realistic concentrations of the precursors hydrogen cyanide and cyanogen (∼<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>5</mn></mrow></msup></semantics></math></inline-formula> M).

Spencer S. Walse, Leonel R. Jimenez

Bean thrips (BT), <i>Caliothrips fasciatus</i> (Pergande), is a pest of concern to certain countries that import fresh citrus fruit from California, USA. A series of laboratory-scale exploratory fumigations with phosphine at 4.9 ± 0.3 °C (mean ± 2 SD; <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mi>x</mi><mo>¯</mo></mover><mo>±</mo><mn>2</mn><mi>s</mi></mrow></semantics></math></inline-formula>) were conducted to evaluate the postharvest control of adult BT. Models of the duration–mortality response predicted ca. 99% mortality of BT populations when headspace concentrations of phosphine, [PH₃], are maintained at levels ≥0.4 g m⁻³ (250 ppmv (µL L⁻¹)) and ≤1.5 g m⁻³ (1000 ppmv (µL L⁻¹)) for 12 h, with the duration representing the lower bound of the 95% confidence level (CL). Confirmatory fumigations, each lasting 12 h, were then conducted using BT-infested sweet oranges, <i>Citrus sinensis</i> (L.), at pulp temperature (<i>T</i>) ≤ 5 °C to corroborate the exploratory results. Three formulations of cylinderized phosphine were used: 1.6% phosphine by volume in nitrogen, VAPORPH3OS^®, and ECOFUME^®, all applied at two levels, ca. 1.5 g m⁻³ (1000 ppmv (µL L⁻¹)), as well as 0.5 g m⁻³ (300 ppmv (µL L⁻¹)). Collectively, across the formulations, an applied dose of ca. 1.5 g m⁻³ (1000 ppmv (µL L⁻¹)) resulted in 0 survivors from 38,993 (probit 8.60, 95% CL; probit 9, 72% CL) treated BT, while an applied dose of 0.5 g m⁻³ (300 ppmv (µL L⁻¹)) resulted in 0 survivors from 31,204 (probit 8.56, 95% CL; probit 9, 70% CL) treated BT. Results were discussed in the context of commercial and operational features of quarantine and pre-shipment (QPS) uses of phosphine to treat fresh fruit and, specifically, the control of BT in fresh citrus exported from California, USA, to Australia.

Huda Ansaf, Bahaa Kazem Ansaf, Sanaa S. Al Samahi

This paper proposes a neuro-fuzzy system to model <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>β</mi></semantics></math></inline-formula>-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>β</mi></semantics></math></inline-formula>-glucosidase. Second, each input’s optimized membership functions from the ANFIS technique were embedded in a new fuzzy inference system to simultaneously encompass the impact of temperature and pH level on the activity of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>β</mi></semantics></math></inline-formula>-glucosidase. The required base rules for the developed fuzzy inference system were created to describe the antecedent (pH and temperature) implication to the consequent (enzyme activity), using the singleton Sugeno fuzzy inference technique. The simulation results from the developed models achieved high accuracy. The neuro-fuzzy approach performed very well in predicting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>β</mi></semantics></math></inline-formula>-glucosidase activity through comparative analysis. The proposed approach may be used to predict enzyme kinetics for several nonlinear biosynthetic processes.

Christian Fillafer, Yana S. Koll, Matthias F. Schneider

In cholinergic synapses, the neurotransmitter acetylcholine (ACh) is rapidly hydrolyzed by esterases to choline and acetic acid (AH). It is believed that this reaction serves the purpose of deactivating ACh once it has exerted its effect on a receptor protein (AChR). The protons liberated in this reaction, however, may by themselves excite the postsynaptic membrane. Herein, we investigated the response of cell membrane models made from phosphatidylcholine (PC), phosphatidylserine (PS) and phosphatidic acid (PA) to ACh in the presence and absence of acetylcholinesterase (AChE). Without a catalyst, there were no significant effects of ACh on the membrane state (lateral pressure change <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>≤</mo><mn>0.5</mn></mrow></semantics></math></inline-formula> mN/m). In contrast, strong responses were observed in membranes made from PS and PA when ACh was applied in presence of AChE (>5 mN/m). Control experiments demonstrated that this effect was due to the protonation of lipid headgroups, which is maximal at the pK (for PS: <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>pK</mi><mrow><mi>COOH</mi></mrow></msub><mo>≈</mo><mn>5.0</mn></mrow></semantics></math></inline-formula>; for PA: <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>pK</mi><mrow><msubsup><mi>HPO</mi><mrow><mn>4</mn></mrow><mo>−</mo></msubsup></mrow></msub><mo>≈</mo><mn>8.5</mn></mrow></semantics></math></inline-formula>). These findings are physiologically relevant, because both of these lipids are present in postsynaptic membranes. Furthermore, we discussed evidence which suggests that AChR assembles a lipid-protein interface that is proton-sensitive in the vicinity of pH <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>7.5</mn></mrow></semantics></math></inline-formula>. Such a membrane could be excited by hydrolysis of micromolar amounts of ACh. Based on these results, we proposed that cholinergic transmission is due to postsynaptic membrane protonation. Our model will be falsified if cholinergic membranes do not respond to acidification.

Siham S. Hassan, Ahmed S. El-Shafie, Nourhan Zaher et al.

Adsorptive removal of rose bengal (RB) from contaminated water samples was approached using pineapple leaves (PAL). Three adsorbents were utilized for that purpose; raw pineapple leaves (RPAL) and the thermally activated bio-waste leaves at 250 and 500 °C. Two measures were executed to evaluate the functionality of exploited biomasses; percentage removal (%R) and adsorption capacity (<inline-formula><math display="inline"><semantics><mrow><msub><mi>q</mi><mi>e</mi></msub></mrow></semantics></math></inline-formula>). Face-centered central composite design (FCCCD) was conducted to experiment the influence of variables on the %R. Dose of PAL as adsorbent (AD), concentration of RB (DC), pH and contact time (CT), were the inspected factors. Existence of functional groups and formation of activated carbon was instigated employing Fourier-transform infrared (FT-IR) and Raman spectroscopies. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) analyses were used to explore surface features. Thermal behavior of adsorbents was studied using thermogravimetric analysis (TGA). The surface area and other surface structural properties were established using the Brunauer Emmett-Teller (BET) analysis. An amount of 92.53% of RB could be removed with an adsorption capacity of 58.8 mg/g using a combination of pH 5.00 ± 0.20, RPAL dose of 0.05 mg/50 mL, and 10-ppm RB for 180 min. Equilibrium studies divulge a favorable adsorption that follows the Freundlich isotherm. Pseudo-second-order model explains the observed adsorption kinetics.

N. Yang, N. Yang, J. Zhang et al.

<p>Hydrochemical and isotopic techniques have been widely applied in hydrological sciences because isotopic tracers can identify water sources and hydrochemical tracers can discern runoff flow paths. To better understand the hydrological process, we combined hydrochemical and isotopic techniques under controlled experimental conditions to investigate hydrological process from rainfall to runoff in the Hydrohill experiment catchment, a typical artificial catchment in Chuzhou, China. Hydrochemical and isotopic data, i.e., pH, electric conductivity (EC), total dissolved solids (TDS), anions (<span class="inline-formula">Cl⁻</span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="4c315b3ea451cf26923ad12993612b33"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="piahs-383-99-2020-ie00001.svg" width="25pt" height="16pt" src="piahs-383-99-2020-ie00001.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="6060a0eb6022af681aa55d19b3180df9"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="piahs-383-99-2020-ie00002.svg" width="29pt" height="17pt" src="piahs-383-99-2020-ie00002.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M4" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">HCO</mi><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="33pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="2fbeb9b29341401f243f2ced851d27df"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="piahs-383-99-2020-ie00003.svg" width="33pt" height="16pt" src="piahs-383-99-2020-ie00003.png"/></svg:svg></span></span>), cations (<span class="inline-formula">K⁺</span>, <span class="inline-formula">Na⁺</span>, <span class="inline-formula">Ca²⁺</span> and <span class="inline-formula">Mg²⁺</span>) and dissolved Si, <span class="inline-formula">¹⁸O</span> and D in water samples were collected during a rainfall event in 2016, and used to determine the hydrochemical and isotopic characteristics of rainfall and runoff components. We applied EC, TDS, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="8c898138530c760447165fe6cdc920bb"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="piahs-383-99-2020-ie00004.svg" width="29pt" height="17pt" src="piahs-383-99-2020-ie00004.png"/></svg:svg></span></span>, <span class="inline-formula">Ca²⁺</span>, <span class="inline-formula">Mg²⁺</span>, <span class="inline-formula">¹⁸O</span> and D as tracers to investigate rainfall-runoff processes in the experimental catchment. Runoff flow paths could be well identified by the relationship between <span class="inline-formula">¹⁸O</span> and EC, TDS, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="213a54c118da389977337da1db9c4008"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="piahs-383-99-2020-ie00005.svg" width="29pt" height="17pt" src="piahs-383-99-2020-ie00005.png"/></svg:svg></span></span>, <span class="inline-formula">Ca²⁺</span> and <span class="inline-formula">Mg²⁺</span>. The quantity of flow flux and mass fluxes of main hydrochemical and isotopic tracers gauged at the catchment outlet shows applicable tracers (<span class="inline-formula">Ca²⁺</span>, <span class="inline-formula">Mg²⁺</span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M20" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="dd552c817eaa417e494d4c74f0a27efc"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="piahs-383-99-2020-ie00006.svg" width="29pt" height="17pt" src="piahs-383-99-2020-ie00006.png"/></svg:svg></span></span>, and <span class="inline-formula">¹⁸O</span>) are mainly from deep groundwater runoff (from soil layer of 60–100&thinsp;cm beneath ground surface). Contributions of the event water and pre-event water to the total runoff during the rainfall-runoff process are different. The quantitative results were very encouraging as a basis to develop hydrological models for further study.</p>

V. Shah, D. J. Jacob, D. J. Jacob et al.

<p>Cloud water acidity affects the atmospheric chemistry of sulfate and organic aerosol formation, halogen radical cycling, and trace metal speciation. Precipitation acidity including post-depositional inputs adversely affects soil and freshwater ecosystems. Here, we use the GEOS-Chem model of atmospheric chemistry to simulate the global distributions of cloud water and precipitation acidity as well as the total acid inputs to ecosystems from wet deposition. The model accounts for strong acids (<span class="inline-formula">H₂SO₄</span>, <span class="inline-formula">HNO₃</span>, and HCl), weak acids (HCOOH, <span class="inline-formula">CH₃COOH</span>, <span class="inline-formula">CO₂</span>, and <span class="inline-formula">SO₂</span>), and weak bases (<span class="inline-formula">NH₃</span> as well as dust and sea salt aerosol alkalinity). We compile a global data set of cloud water pH measurements for comparison with the model. The global mean observed cloud water pH is <span class="inline-formula">5.2±0.9</span>, compared to <span class="inline-formula">5.0±0.8</span> in the model, with a range from 3 to 8 depending on the region. The lowest values are over East Asia, and the highest values are over deserts. Cloud water pH over East Asia is low because of large acid inputs (<span class="inline-formula">H₂SO₄</span> and <span class="inline-formula">HNO₃</span>), despite <span class="inline-formula">NH₃</span> and dust neutralizing 70&thinsp;% of these inputs. Cloud water pH is typically 4–5 over the US and Europe. Carboxylic acids account for less than 25&thinsp;% of cloud water <span class="inline-formula">H⁺</span> in the Northern Hemisphere on an annual basis but 25&thinsp;%–50&thinsp;% in the Southern Hemisphere and over 50&thinsp;% in the southern tropical continents, where they push the cloud water pH below 4.5. Anthropogenic emissions of <span class="inline-formula">SO₂</span> and <span class="inline-formula">NO_<i>x</i></span> (precursors of <span class="inline-formula">H₂SO₄</span> and <span class="inline-formula">HNO₃</span>) are decreasing at northern midlatitudes, but the effect on cloud water pH is strongly buffered by <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M17" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="8b20487e53d7ab6a3bf592e9df90e3eb"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-12223-2020-ie00001.svg" width="24pt" height="15pt" src="acp-20-12223-2020-ie00001.png"/></svg:svg></span></span> and carboxylic acids. The global mean precipitation pH is 5.5 in GEOS-Chem, which is higher than the cloud water pH because of dilution and below-cloud scavenging of <span class="inline-formula">NH₃</span> and dust. GEOS-Chem successfully reproduces the annual mean precipitation pH observations in North America, Europe, and eastern Asia. Carboxylic acids, which are undetected in routine observations due to biodegradation, lower the annual mean precipitation pH in these areas by 0.2 units. The acid wet deposition flux to terrestrial ecosystems taking into account the acidifying potential of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M19" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="7248c728767abac31fc80ac33e5f4469"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-12223-2020-ie00002.svg" width="25pt" height="16pt" src="acp-20-12223-2020-ie00002.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M20" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="730c3bacbcf80f0a2c8df5dbccbd0cf0"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-12223-2020-ie00003.svg" width="24pt" height="15pt" src="acp-20-12223-2020-ie00003.png"/></svg:svg></span></span> in N-saturated ecosystems exceeds 50&thinsp;<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M21" display="inline" overflow="scroll" dspmath="mathml"><mrow class="unit"><mi mathvariant="normal">meq</mi><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">m</mi><mrow><mo>-</mo><mn mathvariant="normal">2</mn></mrow></msup><mspace width="0.125em" linebreak="nobreak"/><msup><mi mathvariant="normal">a</mi><mrow><mo>-</mo><mn mathvariant="normal">1</mn></mrow></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="62pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="1fd1a98175102c22120585552b52f977"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-12223-2020-ie00004.svg" width="62pt" height="15pt" src="acp-20-12223-2020-ie00004.png"/></svg:svg></span></span> in East Asia and the Americas, which would affect sensitive ecosystems. <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="44642da34e3da1fffc83c720c465c894"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-20-12223-2020-ie00005.svg" width="24pt" height="15pt" src="acp-20-12223-2020-ie00005.png"/></svg:svg></span></span> is the dominant acidifying species in wet deposition, contributing 41&thinsp;% of the global acid flux to continents under N-saturated conditions.</p>

Bin Gui

In recent work, Damiolini-Gibney-Tarasca showed that for a $C_2$-cofinite rational CFT-type vertex operator algebra $\mathbb V$, sheaves of conformal blocks are locally free and satisfy the factorization property. In this article, we use analytic methods to prove that sewing conformal blocks is convergent, solving a conjecture proposed by Zhu and Huang.

Hui Jiang, Weidong Xu, Quansheng Chen

The odor information produced in <i>Saccharomyces cerevisiae</i> culture is one of the important characteristics of yeast growth status. This work innovatively presents the quantitative monitoring of cell concentration during the yeast culture process using a homemade color sensor. First, a color sensor array, which could visually represent the odor changes produced during the yeast culture process, was developed using eleven porphyrins and one pH indicator. Second, odor information of the culture substrate was obtained during the process using the homemade color sensor. Next, color components, which came from different color sensitive spots, were extracted first and then optimized using the ant colony optimization (ACO) algorithm. Finally, the back propagation neural network (BPNN) model was developed using the optimized feature color components for quantitative monitoring of cell concentration. Results demonstrated that BPNN models, which were developed using two color components from FTPPFeCl (component B) and MTPPTE (component B), can obtain better results on the basis of both the comprehensive consideration of the model performance and the economic benefit. In the validation set, the average of determination coefficient <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi mathvariant="normal">R</mi> <mi mathvariant="normal">P</mi> <mn>2</mn> </msubsup> </mrow> </semantics> </math> </inline-formula> was 0.8837 and the variance was 0.0725, while the average of root mean square error of prediction (RMSEP) was 1.0033 and the variance was 0.1452. The overall results sufficiently demonstrate that the optimized sensor array can satisfy the monitoring accuracy and stability of the cell concentration in the process of yeast culture.

Carina Dargel, Ramsia Geisler, Yvonne Hannappel et al.

This work investigates the temperature-dependent micelle formation as well as the micellar structure of the saponin aescin. The critical micelle concentration (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>c</mi> <mi>m</mi> <mi>c</mi> </mrow> </semantics> </math> </inline-formula>) of aescin is determined from the concentration-dependent autofluorescence (AF) of aescin. Values between <inline-formula> <math display="inline"> <semantics> <mrow> <mi>c</mi> <mi>m</mi> <msub> <mi>c</mi> <mrow> <mi>aescin</mi> <mo>,</mo> <mi>AF</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>(10 <inline-formula> <math display="inline"> <semantics> <msup> <mrow></mrow> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>C) = 0.38 &#177; 0.09 mM and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>c</mi> <mi>m</mi> <msub> <mi>c</mi> <mrow> <mi>aescin</mi> <mo>,</mo> <mi>AF</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>(50 <inline-formula> <math display="inline"> <semantics> <msup> <mrow></mrow> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>C) = 0.32 &#177; 0.13 mM were obtained. The significance of this method is verified by tensiometry measurements. The value determined from this method is within the experimental error identical with values obtained from autofluorescence (<inline-formula> <math display="inline"> <semantics> <mrow> <mi>c</mi> <mi>m</mi> <msub> <mi>c</mi> <mrow> <mi>aescin</mi> <mo>,</mo> <mi mathvariant="normal">T</mi> <mo>(</mo> <mi>WP</mi> <mo>)</mo> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>(23 <inline-formula> <math display="inline"> <semantics> <msup> <mrow></mrow> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>C) = 0.33 &#177; 0.02 mM). The structure of the aescin micelles was investigated by small-angle X-ray scattering (SAXS) at 10 and 40 <inline-formula> <math display="inline"> <semantics> <msup> <mrow></mrow> <mo>∘</mo> </msup> </semantics> </math> </inline-formula>C. At low temperature, the aescin micelles are rod-like, whereas at high temperature the structure is ellipsoidal. The radii of gyration were determined to &#8776;31 &#197; (rods) and &#8776;21 &#197; (ellipsoid). The rod-like shape of the aescin micelles at low temperature was confirmed by transmission electron microscopy (TEM). All investigations were performed at a constant pH of 7.4, because the acidic aescin has the ability to lower the pH value in aqueous solution.

J. Ding, P. Zhao, J. Su et al.

<p>Aerosol acidity plays a key role in secondary aerosol formation. The high-temporal-resolution PM<span class="inline-formula">_2.5</span> pH and size-resolved aerosol pH in Beijing were calculated with ISORROPIA II. In 2016–2017, the mean PM<span class="inline-formula">_2.5</span> pH (at relative humidity (RH)&thinsp;&gt;&thinsp;30&thinsp;%) over four seasons was <span class="inline-formula">4.5±0.7</span> (winter)&thinsp;&gt;&thinsp;<span class="inline-formula">4.4±1.2</span> (spring)&thinsp;&gt;&thinsp;<span class="inline-formula">4.3±0.8</span> (autumn)&thinsp;&gt;&thinsp;<span class="inline-formula">3.8±1.2</span> (summer), showing moderate acidity. In coarse-mode aerosols, <span class="inline-formula">Ca²⁺</span> played an important role in aerosol pH. Under heavily polluted conditions, more secondary ions accumulated in the coarse mode, leading to the acidity of the coarse-mode aerosols shifting from neutral to weakly acidic. Sensitivity tests also demonstrated the significant contribution of crustal ions to PM<span class="inline-formula">_2.5</span> pH. In the North China Plain (NCP), the common driving factors affecting PM<span class="inline-formula">_2.5</span> pH variation in all four seasons were <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="8c898138530c760447165fe6cdc920bb"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-7939-2019-ie00001.svg" width="29pt" height="17pt" src="acp-19-7939-2019-ie00001.png"/></svg:svg></span></span>, <span class="inline-formula">TNH₃</span> (total ammonium (gas&thinsp;<span class="inline-formula">+</span>&thinsp;aerosol)), and temperature, while unique factors were <span class="inline-formula">Ca²⁺</span> in spring and RH in summer. The decreasing <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M14" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">SO</mi><mn mathvariant="normal">4</mn><mrow><mn mathvariant="normal">2</mn><mo>-</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="29pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="14485914c781d9e26f0da54782d5723d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-7939-2019-ie00002.svg" width="29pt" height="17pt" src="acp-19-7939-2019-ie00002.png"/></svg:svg></span></span> and increasing <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NO</mi><mn mathvariant="normal">3</mn><mo>-</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="25pt" height="16pt" class="svg-formula" dspmath="mathimg" md5hash="ecc3e6dd5af0ffb1da8bfbfcb16b8e8b"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-7939-2019-ie00003.svg" width="25pt" height="16pt" src="acp-19-7939-2019-ie00003.png"/></svg:svg></span></span> mass fractions in PM<span class="inline-formula">_2.5</span> as well as excessive <span class="inline-formula">NH₃</span> in the atmosphere in the NCP in recent years are the reasons why aerosol acidity in China is lower than that in Europe and the United States. The nonlinear relationship between PM<span class="inline-formula">_2.5</span> pH and <span class="inline-formula">TNH₃</span> indicated that although <span class="inline-formula">NH₃</span> in the NCP was abundant, the PM<span class="inline-formula">_2.5</span> pH was still acidic because of the thermodynamic equilibrium between <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="44642da34e3da1fffc83c720c465c894"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-7939-2019-ie00004.svg" width="24pt" height="15pt" src="acp-19-7939-2019-ie00004.png"/></svg:svg></span></span> and <span class="inline-formula">NH₃</span>. To reduce nitrate by controlling ammonia, the amount of ammonia must be greatly reduced below excessive quantities.</p>

J. M. Roberts, Y. Liu

<p>Condensed-phase uptake and reaction are important atmospheric removal processes for reduced nitrogen species, isocyanic acid (HNCO), methyl isocyanate (<span class="inline-formula">CH₃NCO</span>), and cyanogen halides (XCN, X&thinsp;<span class="inline-formula">=</span>&thinsp;Cl, Br, I); yet many of the fundamental quantities that govern this chemistry have not been measured or are not well studied. These nitrogen species are of emerging interest in the atmosphere as they have either biomass burning sources, i.e., HNCO and <span class="inline-formula">CH₃NCO</span>, or, like the XCN species, have the potential to be a significant condensed-phase source of <span class="inline-formula">NCO⁻</span> and therefore HNCO. Solubilities and the first-order reaction rate of these species were measured for a variety of solutions using a bubble flow reactor method with total reactive nitrogen (<span class="inline-formula">N_r</span>) detection. The aqueous solubility of HNCO was measured as a function of pH and had an intrinsic Henry's law solubility of 20 (<span class="inline-formula">±2</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> and a <span class="inline-formula"><i>K</i>_a</span> of 2.0 (<span class="inline-formula">±0.3</span>)&thinsp;<span class="inline-formula">×</span>&thinsp;10<span class="inline-formula">⁻⁴</span>&thinsp;M (<span class="inline-formula"><i>p</i><i>K</i>_a</span>&thinsp;<span class="inline-formula">=</span>&thinsp;<span class="inline-formula">3.7±0.1</span>) at 298&thinsp;K. The temperature dependence of HNCO solubility was very similar to other small nitrogen-containing compounds, such as HCN, acetonitrile (<span class="inline-formula">CH₃CN</span>), and nitromethane, and the dependence on salt concentration exhibited the “salting out” phenomenon. The rate constant of reaction of HNCO with 0.45&thinsp;M <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M16" display="inline" overflow="scroll" dspmath="mathml"><mrow class="chem"><msubsup><mi mathvariant="normal">NH</mi><mn mathvariant="normal">4</mn><mo>+</mo></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="24pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="97c709e7ff43e05afce356dc3f53b497"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-4419-2019-ie00001.svg" width="24pt" height="15pt" src="acp-19-4419-2019-ie00001.png"/></svg:svg></span></span>, as <span class="inline-formula">NH₄Cl</span>, was measured at pH&thinsp;<span class="inline-formula">=</span>&thinsp;3 and found to be 1.2 (<span class="inline-formula">±0.1</span>)&thinsp;<span class="inline-formula">×</span>&thinsp;10<span class="inline-formula">⁻³</span>&thinsp;M<span class="inline-formula">⁻¹</span>&thinsp;s<span class="inline-formula">⁻¹</span>, faster than the rate that would be estimated from rate measurements at much higher pHs. The solubilities of HNCO in the non-polar solvents <span class="inline-formula"><i>n</i></span>-octanol (<span class="inline-formula"><i>n</i></span>-<span class="inline-formula">C₈H₁₇OH</span>) and tridecane (<span class="inline-formula">C₁₃H₂₈</span>) were found to be higher than aqueous solution for <span class="inline-formula"><i>n</i></span>-octanol (<span class="inline-formula">87±9</span>&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> at 298&thinsp;K) and much lower than aqueous solution for tridecane (<span class="inline-formula">1.7±0.17</span>&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> at 298&thinsp;K), features that have implications for multi-phase and membrane transport of HNCO. The first-order loss rate of HNCO in <span class="inline-formula"><i>n</i></span>-octanol was determined to be relatively slow, 5.7 (<span class="inline-formula">±1.4</span>)&thinsp;<span class="inline-formula">×</span>&thinsp;10<span class="inline-formula">⁻⁵</span>&thinsp;s<span class="inline-formula">⁻¹</span>. The aqueous solubility of <span class="inline-formula">CH₃NCO</span> was found to be 1.3 (<span class="inline-formula">±0.13</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> independent of pH, and <span class="inline-formula">CH₃NCO</span> solubility in <span class="inline-formula"><i>n</i></span>-octanol was also determined at several temperatures and ranged from 4.0 (<span class="inline-formula">±0.5</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> at 298&thinsp;K to 2.8 (<span class="inline-formula">±0.3</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> at 310&thinsp;K. The aqueous hydrolysis of <span class="inline-formula">CH₃NCO</span> was observed to be slightly acid-catalyzed, in agreement with literature values, and reactions with <span class="inline-formula"><i>n</i></span>-octanol ranged from 2.5 (<span class="inline-formula">±0.5</span>) to 5.3 (<span class="inline-formula">±0.7</span>)&thinsp;<span class="inline-formula">×</span>&thinsp;10<span class="inline-formula">⁻³</span>&thinsp;s<span class="inline-formula">⁻¹</span> from 298 to 310&thinsp;K. The aqueous solubilities of XCN, determined at room temperature and neutral pH, were found to increase with halogen atom polarizability from 1.4 (<span class="inline-formula">±0.2</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> for ClCN and 8.2 (<span class="inline-formula">±0.8</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> for BrCN to 270 (<span class="inline-formula">±54</span>)&thinsp;M&thinsp;atm<span class="inline-formula">⁻¹</span> for ICN. Hydrolysis rates, where measurable, were in agreement with literature values. The atmospheric loss rates of HNCO, <span class="inline-formula">CH₃NCO</span>, and XCN due to heterogeneous processes are estimated from solubilities and reaction rates. Lifetimes of HNCO range from about 1 day against deposition to neutral pH surfaces in the boundary layer, but otherwise can be as long as several months in the middle troposphere. The loss of <span class="inline-formula">CH₃NCO</span> due to aqueous-phase processes is estimated to be slower than, or comparable to, the lifetime against OH reaction (3 months). The loss of XCNs due to aqueous uptake is estimated to range from being quite slow, with a lifetime of 2–6 months or more for ClCN and 1 week to 6 months for BrCN to 1 to 10 days for ICN. These characteristic times are shorter than photolysis lifetimes for ClCN and BrCN, implying that heterogeneous chemistry will be the controlling factor in their atmospheric removal. In contrast, the photolysis of ICN is estimated to be faster than heterogeneous loss for average midlatitude conditions.</p>