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Knowledge of the partition mechanisms in the agrochemical environment is fundamental for understanding their behavior within an ecosystem and mitigating possible adverse effects of these products. In this review, the objective was to present the main transport mechanisms, physical-chemical properties, and atmospheric monitoring methodologies of the most diverse types of agrochemicals used in agriculture that can reach the atmosphere and affect different compartments. It has been verified that volatilization is one of more considerable significance of the various forms of transport since a significant part of the applied pesticides can volatilize in a few days. As for monitoring these compounds in the atmosphere, both passive and active sampling have their advantages and disadvantages. Passive samplers allow sampling in large quantities and at remote locations, in addition to making continuous measurements, while active samplers have the advantage of being able to detect low concentrations and continuously. Since a significant portion of the applied pesticides is directed to the atmosphere, monitoring makes it possible to understand some properties of the pesticides present in the air. This monitoring can be done from different existing methodologies based on adopted criteria and existing technical standards. Graphical abstract Graphical representation of mobility and environmental monitoring of atmospheric pollutants from pesticides.

● A system of environmental optical monitoring technology has been established. ● New optical monitoring techniques and stereoscopic system should be established. ● The focus on interdisciplinarity should be increased. ● Pay more attention on greenhouse gases monitoring and atmospheric chemistry. The achievement of the targets of coordinated control of PM 2.5 and O 3 and the carbon peaking and carbon neutrality depend on the development of pollution and greenhouse gas monitoring technologies. Optical monitoring technology, based on its technical characteristics of high scalability, high sensitivity and wide-targets detection, has obvious advantages in pollution/greenhouse gases monitoring and has become an important direction in the development of environmental monitoring technology. At present, a system of environmental optical monitoring technology with differential optical absorption spectroscopy (DOAS), cavity ring-down spectroscopy (CRDS), light detection and ranging (LIDAR), laser heterodyne spectroscopy (LHS), tunable diode laser absorption spectroscopy (TDLAS), fourier transform infrared spectroscopy (FTIR) and fluorescence assay by gas expansion (FAGE) as the main body has been established. However, with the promotion of \"reduction of pollution and carbon emissions\" strategy, there have been significant changes in the sources of pollution/greenhouse gases, emission components and emission concentrations, which have put forward new and higher requirements for the development of monitoring technologies. In the future, we should pay more attention to the development of new optical monitoring techniques and the construction of stereoscopic monitoring system, the interdisciplinarity (among mathematics, physics, chemistry and biology, etc.), and the monitoring of greenhouse gases and research on atmospheric chemistry.

The number of atmospheric mercury (Hg) monitoring stations is growing globally. However, there are still many regions and locations where Hg monitoring is limited or non-existent. Expansion of the atmospheric Hg monitoring network could be facilitated by the use of cost-effective monitoring methods. As such, biomonitoring and passive monitoring offer a unique alternative to well-established monitoring by active measurements, since they do not require a power supply and require minimal workload to operate. The use of biomonitoring (lichens and mosses) and passive air samplers (PASs) (various designs with synthetic materials) has been reported in the literature, and comparisons with active measurement methods have also been made. However, these studies compared either biomonitoring or PASs (not both) to only one type of active measurement. In our work, we used transplanted (7 sampling sites) and in situ lichens (8 sampling sites) for biomonitoring, two PASs from different producers (3 sampling sites), and two different active measurement types (continuous and discontinuous active measurements, 1 and 8 sampling sites, respectively) to evaluate their effectiveness as monitoring methods. In the 9-month sampling campaign, 3 sampling locations with different characteristics (unpolluted, vicinity of a cement plant, and vicinity of a former Hg mine) were used. The results obtained with lichens and PASs clearly distinguished between sampling locations with different Hg concentrations; using both PASs and lichens together increased the confidence of our observations. The present work shows that biomonitoring and passive sampling can be effectively used to identify areas with elevated atmospheric Hg concentrations. The same can be said for discontinuous active measurements; however, the discrepancy between atmospheric Hg concentrations derived from PASs and discontinuous active measurements should be further investigated in the future. Graphical Abstract

Explosions in underground mining due to methane gas have been the leading cause of incidents and fatalities in the mining industry. The main objective of this research is to develop a forecasting methodology for methane gas emissions based on time series analysis. Methane time series data were retrieved from atmospheric monitoring systems (AMS) of three underground coal mines in the United States. The AMS data were preprocessed and statistically evaluated to explore the potential autocorrelation of methane gas. It was concluded that the autoregressive integrated moving average (ARIMA) time series model used in the one-step-ahead forecasting mode provides accurate estimates that match the increase or decrease of the methane gas emission data.

Atmospheric conditions vary significantly in terms of the temporal and spatial scales. Therefore, it is critical to obtain atmospheric parameters synchronized with an image for atmospheric correction based on radiative transfer calculation methods. On 3 July 2020, the high resolution and multimode imaging satellite, Gao Fen Duo Mo (GFDM), which was the first civilian high-resolution remote sensing satellite equipped with the Synchronization Monitoring Atmospheric Corrector (SMAC), was launched. The SMAC is a multispectral and polarization detection device that is used to retrieve atmospheric parameters that are time-synchronized with the image sensor of GFDM in the same field-of-view. On the basis of the atmospheric parameters obtained from the SMAC, a synchronization atmospheric correction (Syn-AC) method is proposed to remove the influence of the atmosphere and the adjacency effects to retrieve the surface reflectance. The Syn-AC method was applied in the experiments of synchronous atmospheric correction for GFDM images, where the surface reflectance retrieved via the Syn-AC method was compared with the field-measured values. In addition, the classical correction method, the FLAASH, was applied in the experiments to compare its performance with that of the Syn-AC method. The results indicated that the image possessed better clarity and contrast with the blurring effect removed, and the multispectral reflectance was in agreement with the field-measured spectral reflectance. The deviations between the reflectance retrievals of Syn-AC and the field-measured values of the selected targets were within 0.0625, representing a higher precision than that of the FLAASH method (the max deviation was 0.2063). For the three sites, the mean relative error of Syn-AC was 19.3%, and the mean relative error of FLAASH was 76.6%. Atmospheric correction based on synchronous atmospheric parameters can improve the quantitative accuracy of remote sensing images, and it is meaningful for remote sensing applications.

Currently, ground-based global navigation satellite system (GNSS) techniques have become widely recognized as a reliable and effective tool for atmospheric monitoring, enabling the retrieval of zenith total delay (ZTD) and precipitable water vapor (PWV) for meteorological and climate research. The International GNSS Service analysis centers (ACs) have initiated their third reprocessing campaign, known as IGS Repro3. In this campaign, six ACs conducted a homogeneous reprocessing of the ZTD time series spanning the period from 1994 to 2022. This paper primarily focuses on ZTD products. First, the data processing strategies and station conditions of six ACs were compared and analyzed. Then, formal errors within the data were examined, followed by the implementation of quality control processes. Second, a combination method is proposed and applied to generate the final ZTD products. The resulting combined series was compared with the time series submitted by the six ACs, revealing a mean bias of 0.03 mm and a mean root mean square value of 3.02 mm. Finally, the time series submitted by the six ACs and the combined series were compared with VLBI data, radiosonde data, and ERA5 data. In comparison, the combined solution performs better than most individual analysis centers, demonstrating higher quality. Therefore, the advanced method proposed in this study and the generated high-quality dataset have considerable implications for further advancing GNSS atmospheric sensing and offer valuable insights for climate modeling and prediction.

The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis is the latest global reanalysis dataset of atmospheric composition produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), consisting of three-dimensional time-consistent atmospheric composition fields, including aerosols and chemical species. The dataset currently covers the period 2003–2016 and will be extended in the future by adding 1 year each year. A reanalysis for greenhouse gases is being produced separately. The CAMS reanalysis builds on the experience gained during the production of the earlier Monitoring Atmospheric Composition and Climate (MACC) reanalysis and CAMS interim reanalysis. Satellite retrievals of total column CO; tropospheric column NO2; aerosol optical depth (AOD); and total column, partial column and profile ozone retrievals were assimilated for the CAMS reanalysis with ECMWF's Integrated Forecasting System. The new reanalysis has an increased horizontal resolution of about 80 km and provides more chemical species at a better temporal resolution (3-hourly analysis fields, 3-hourly forecast fields and hourly surface forecast fields) than the previously produced CAMS interim reanalysis. The CAMS reanalysis has smaller biases compared with most of the independent ozone, carbon monoxide, nitrogen dioxide and aerosol optical depth observations used for validation in this paper than the previous two reanalyses and is much improved and more consistent in time, especially compared to the MACC reanalysis. The CAMS reanalysis is a dataset that can be used to compute climatologies, study trends, evaluate models, benchmark other reanalyses or serve as boundary conditions for regional models for past periods.

The atmospheric corrosion monitoring (ACM) technique has been widely employed to track the real-time corrosion behavior of metal materials. However, limited studies have applied ACM to the corrosion protection properties of organic coatings. This study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors, both applied on ACM sensors, to observe their corrosion protection properties over time. Coatings with artificial damage via scratches were exposed to immersion and alternating dry and wet environments, which allowed for monitoring galvanic corrosion currents in real-time. Throughout the corrosion tests, the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy coating. The trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface analysis. This alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic coatings. Compared with the blank epoxy coating, the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.

Continuous monitoring of carbon monoxide and other fire-related parameters by means of an atmospheric monitoring system (AMS) is used in the mining industry for early fire detection. Researchers at the U.S. National Institute for Occupational Safety and Health (NIOSH) have developed a direct method to calculate the fire heat release rate (HRR) when a mine fire is close to the AMS sensors, but this method is only applicable to the case where a fire occurs in AMSmonitored airways. This paper presents an improved method for determining the fire HRR using AMS sensor data at any location downstream of the fire. The method was validated using a full-scale diesel fire test conducted in the Safety Research Coal Mine at NIOSH's Pittsburgh Mining Research Division.

Numerical simulations are performed to determine the angular dependence of the MIe scattering cross-section intensities of pure water droplets and pollutants such as contaminated water droplets and black carbon as a function of the wavelength of the incident laser light, complex refractive index, and size of the scatterer. Our results show distinct scattering features when varying the various scattering parameters, thereby allowing the identification of the scattering particle with specific application to the identification of atmospheric pollutants including black carbon. Regardless of the type of scatterer, the scattering intensity is nearly uniform with a slight preference for forward scattering when the size of the particle is within 20% of the incident laser’s wavelength. The scattering patterns start to exhibit distinguishable features when the size parameter equals 1.77, corresponding to an incident laser wavelength of 0.355 μm and a particle radius of 0.1 μm. The patterns then become increasingly unique as the size parameter increases. Based on these calculations, we propose a time-gated lidar scheme consisting of multiple detectors that can rotate through a telescopic angle and be placed equidistantly around the scattering particles to collect the backscattered light and a commercially available Q-switched laser system emitting at tunable laser wavelengths. By using a pulsed laser with 10-ns pulse duration, our scheme could distinguish scattering centers that are at least 3 m apart. Our scheme called MIe Scattering Time-gated multi-Static LIDAR (MISTS–LIDAR) would be capable of identifying the type of atmospheric pollutant and mapping its location with a spatial resolution of a few meters.