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This study presents a novel ammonia sensor using hydrothermally synthesized ZnO nanowires integrated with a mode-localized coupled resonator. The ZnO nanowires, with their high surface area, act as an efficient gas adsorption layer. The resonator’s driving mechanism was optimized using finite element method (FEM) simulations, revealing that a coupled resonator pair exhibited 45.52 times higher sensitivity than a single resonator. Out-of-phase modes showed greater sensitivity than in-phase modes. Resonators R1 and R2 driven together had the lowest sensitivity, while Resonator 1, with a zinc oxide layer and driven individually, demonstrated the highest sensitivity. Additionally, the sensitivity of the coupled resonator increased with the decrease in dc bias voltage. Comprehensive materials characterization of the ZnO nanowires was conducted using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) to confirm their structural and chemical properties. Fourier-transform infrared spectroscopy (FTIR) results showed that after ammonia adsorption, ZnO nanowires exhibited additional absorption bands at approximately 1430 cm $^{-{1}}$ , 1633 cm $^{-{1}}$ , and within the broad range of 3100 to 3550 cm $^{-{1}}$ . The sensor’s gas-sensing performance was evaluated with varying ammonia concentrations, achieving a very high sensitivity of 0.0026 ppm $^{-{1}}$ in the 25–100 ppm range at room temperature. This design highlights the potential of integrating ZnO nanowires with coupled resonators for highly sensitive, miniaturized, low-cost sensors for environmental monitoring and safety applications.

This review is a summary of the most up-to-date knowledge regarding assessment of atmospheric deposition of reactive nitrogen (Nr) pollutants across complex terrain in the UK. Progress in the understanding of the mechanisms and quantification of Nrdeposition in areas of complex topography is slow, as no concerted attempts to measure the components of Nrin complex terrain have been made in the last decade. This is likely due to the inherent complexity of the atmospheric processes and chemical interactions which contribute to deposition in these areas. More than 300 studies have been reviewed, and we have consulted with a panel of international experts which we assembled for that purpose. We report here on key findings and knowledge gaps identified regarding measurement and modelling techniques used to quantify deposition of Nracross complex terrain in the UK, which depending on definition, may represent up to 60% of land coverage across Great Britain. The large body of peer reviewed papers, reports and other items reviewed in this study has highlighted both the strengths and weaknesses in the tools available to scientists, regulators and policy makers. This review highlights that there is no coherent global research effort to constrain the uncertainties in Nrdeposition over complex terrain, despite the clearly identified risk of N deposition to ecosystems and water quality. All evidence identified that enhanced Nrdeposition across complex terrain occurs, and magnitude of the enhancement is not known; however, there are major uncertainties particularly in the differences between modelled and measured wet deposition in complex terrain and representing accurate surface interactions in models. Using simplified estimates for Nrdeposition, based on current understanding of current measurement and model approaches, an enhancement across UK complex terrain in the range of a factor of 1.4–2.5 (i.e.40–150% larger than current estimates) is likely over complex upland terrain. If at the upper limits of this, then significantly more ecosystems in the UK would be at a direct risk of degradation, and the potential for long-term non-remediable water quality issues increased.

Domestic solid fuel combustion is a major source of organic compounds to the atmosphere in gas and aerosol phases; however, large uncertainties exist in the current understanding of the gas-to-particle partitioning and the drivers of the reactivity of these emissions. This study developed comprehensive, model-ready organic emission profiles for domestic solid fuel combustion sources collected from Delhi, India. It also examined the organic species responsible for secondary organic aerosol (SOA) production potential and hydroxyl radical (OH) reactivity of these emissions. The profiles spanned the entire volatility range, including non-methane volatile organic compounds (NMVOCs, effective saturation concentration, C* = 3 × 106to 1011μg m−3), intermediate-volatility organic compounds (IVOCs, C* = 300 to 3 × 106μg m−3), semi-volatile organic compounds (SVOCs, C* = 0.3–300 μg m−3) as well as low- and extremely low-volatility organic compounds (L/ELVOCs, where LVOC C* ≤ 0.3 μg m−3). The profiles predicted that IVOCs would contribute significantly to SOA production and that the combustion of fuel wood and charcoal released some of the smallest proportions of SVOCs. A model was developed to examine SOA production from burning emissions which estimated that phenolics would contribute 10–70% of the SOA. Furanics were the most important reactive species, contributing 9–48% of the OH reactivity and 9–58% of the SOA. Different combustion sources were also compared, with emissions from fuel wood, crop residue, cow dung cake and municipal solid waste (MSW) burning shown to be 30, 90, 120 and 230 times more reactive with the OH radical than emissions from liquefied petroleum gas (LPG) fuel. This study also estimated 3–4 times more SOA from cow dung cake combustion and 6–7 more from MSW combustion than fuel wood under comparable combustion conditions. The results of this study suggest that emissions from the combustion of domestic solid fuel sources in Delhi have the potential to significantly degrade local and regional air quality. As a result, more effective mitigation strategies are required to limit the impacts of solid fuel combustion on human health in countries like India.

ABSTRACTAir pollution presents a major risk to human health, resulting in premature deaths and reduced quality of life. Quantifying the role of vegetation in reducing air pollution concentrations is an important contribution to urban natural capital accounting. However, most current methods to calculate pollution removal are static, and do not represent atmospheric transport of pollutants, or interactions among pollutants and meteorology. An additional challenge is defining urban extent in a way that captures the green and blue infrastructure providing the service in a consistent way. We developed a refined urban morphology layer which incorporates urban green and blue space. We then applied an atmospheric chemistry transport model (EMEP4UK) to calculate pollutant removal by urban natural capital for pollutants including PM2.5, NO2, SO2, O3. We calculated health benefits directly from the change in pollutant concentrations (i.e. exposure) rather than from tonnes of pollutant removed. Urban natural capital across Britain removes 28,700 tonnes of PM2.5, NO2, SO2, O3. The economic value of the health benefits are substantial: £136 million in 2015, resulting from 900 fewer respiratory hospital admissions, 220 fewer cardiovascular hospital admissions, 240 fewer deaths and 3600 fewer Life Years Lost.

Below‐cloud scavenging (BS) is often underestimated in chemical transport models (CTMs) due to inaccurate parameterizations of BS coefficient for fine particle (Λ) caused by a shortage of high‐time resolution field observations. Rainfall ions and related air pollutants were measured hourly in Central China (CC) during 2019. BS contributed to 37%–68% of wet deposition for SO42–${\text{SO}}_{4}^{2\mbox{--}}$, NO3–${\text{NO}}_{3}^{\mbox{--}}$, and NH4+${\text{NH}}_{4}^{+}$(SNA). By a bulk method coupled with brute‐force search, the Λ (10−2–10 hr−1) was parameterized for SNA in PM2.5, which was 1–3 orders of magnitudes higher than theoretical calculations in CTMs. These chemical‐specific Λ parameterizations were validated by EMEP model. Compared to baselines, updated simulations for annual SNA wet deposition increased by 3.3%–20.4% and for mean PM2.5SNA concentrations reduced by 1.2%–40%, capturing measurements better. The contributions of scavenged gases to wet deposition below cloud were calculated as 9%–73%, exhibiting discrepancies (2%–17% for HNO3and 19%–90% for SO2) with previous modeling results as different Λ schemes adopted in CTMs. The nonlinearity between Λ and precipitation intensity causes frequency exerting stronger impact on aerosol burden than intensity and duration. Periodic light rain with a precipitation amount of 1–10 mm per event can eliminate 60% of SNA in PM2.5and is suggested as a routine procedure to improve local air quality. Analyzing a typical washout process after a haze event in CC, BS could reduce PM2.5SNA concentrations by 44%–54% derived from improved parameterizations. The below‐cloud scavenging (BS) is a key process for removing atmospheric aerosols. An underestimation of BS for fine particle (PM2.5) is common in chemical transport models (CTMs) and biases simulations. A comprehensive observation was conducted for 1 year to improve parameterizations of BS coefficient for PM2.5compounds (Λ). These parameterizations were assessed with a CTM. The updates increased the modeled wet deposition fluxes and decreased aerosol concentrations. These results mimicked observations better than baselines. The diversity of BS parameterizations in CTMs enhanced uncertainties of numerical simulation evaluations. The nonlinearity pattern of Λ between precipitation intensity implies frequency imposing stronger impact on aerosol burden than intensity and duration. This principle determines periodic light rain more suitable for cleaning air pollutants routinely. Utilizing the observational parameterizations, the importance of washout on clearing haze was revealed. This work can improve numerical simulations and air pollution control policies. The parameterizations of below‐cloud scavenging coefficients for fine particle compounds were improvedThe reliability of chemical‐specific parameterizations was verified by a chemical transport modelThe implications of improved parameterizations for numerical simulations and air pollution control were elucidated The parameterizations of below‐cloud scavenging coefficients for fine particle compounds were improved The reliability of chemical‐specific parameterizations was verified by a chemical transport model The implications of improved parameterizations for numerical simulations and air pollution control were elucidated