Atmosphere

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ISSN / EISSN : 2073-4433 / 2073-4433
Published by: MDPI (10.3390)
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Published: 27 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101251

Abstract:
Due to the lack of long-term climate records, our understanding of paleoclimatic variability in the Tibetan Plateau (TP) is still limited. In this study, we developed a tree-ring width (TRW) chronology based on tree-ring cores collected from our study site, southeastern TP. This chronology responded well to the mean maximum temperatures of May–June and was thus used to reconstruct early summer (May–June) maximum temperature during the period 1541–2019. The reconstruction explained 33.6% of the climatic variance during the calibration period 1962–2019. There were 34 extremely warm years (7.2% of total years) and 36 extremely cold years (7.5% of total years) during the reconstruction period. The spatial correlation analysis and the comparison with other local temperature reconstructions confirmed the reliability and representativeness of our reconstruction. The results of the ensemble empirical mode decomposition (EEMD) analysis indicated quasi-oscillations of 2.9–4.2 years, 4.5–8.3 years, 11.1–15.4 years, 20–33.3 years, 50.4 years, 159.7 years, and 250 years in this temperature reconstruction which may be associated with ENSO cycles, solar activity, and PDO.
Published: 26 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101250

Abstract:
Structure–activity (SAR) methods are presented for estimating rate constants at 298 K and approximate temperature dependences for the reactions of organic compounds with OH, NO3, and Cl radicals and O3, and O(3P) in the lower atmosphere. These are needed for detailed mechanisms for the atmospheric reactions of organic compounds. Base rate constants are assigned for the various types of H-abstraction and addition reactions, with correction factors for substituents around the reaction site and in some cases for rings and molecule structure or size. Rate constant estimates are made for hydrocarbons and a wide variety of oxygenates, organic nitrates, amines, and monosubstituted halogen compounds. Rate constants for most hydrocarbons and monofunctional compounds can be estimated to within ±30%, though predictions are not as good for multifunctional compounds, and predictions for ~15% of the rate constants are off by more than a factor of 2. Estimates are more uncertain in the case of NO3 and O3 reactions. The results serve to demonstrate the capabilities and limitations of empirical methods for predicting rate constants for the full variety of organic compounds that may be of interest. Areas where future work is needed are discussed.
Published: 26 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101249

Abstract:
Droughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, the spatial stratified heterogeneity in different seasons was discussed. Moreover, the copula joint functions of characteristics and dominant factors of agricultural droughts were constructed. Based on the Soil Moisture Anomaly Percentage Index (SMAPI), the results demonstrate that the climate tendency rate of droughts in the summer and in spring in Subregion I shows an increasing trend, while it decreases in the autumn and winter. In Subregion II, the climate tendency rate of droughts in different seasons has no significant change. Through geographical detection, the single factor detection illustrates that temperature and Precipitation Conversion Efficiency (PCE) show the highest explanatory power in different subregions. The interactive detection also demonstrates the explanatory powers of the combination of the PCE and temperature, respectively. The t-copula function describes the correlation coefficients of the SMAPI with the PCE and temperature, with the optimal tail dependence. In short, agricultural droughts are most significantly affected by temperature and the PCE, and their balance has a significant impact on agricultural droughts.
Published: 26 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101248

Abstract:
Demand for water resources has increased dramatically due to the global increase in consumption of water, which has resulted in water depletion. Additionally, global climate change has further resulted as an impediment to human survival. Moreover, Pakistan is among the countries that have already crossed the water scarcity line, experiencing drought in the water-stressed Thar desert. Drought mitigation actions can be effectively achieved by forecasting techniques. This research describes the application of a linear stochastic model, i.e., Autoregressive Integrated Moving Average (ARIMA), to predict the drought pattern. The Standardized Precipitation Evapotranspiration Index (SPEI) is calculated to develop ARIMA models to forecast drought in a hyper-arid environment. In this study, drought forecast is demonstrated by results achieved from ARIMA models for various time periods. Result shows that the values of p, d, and q (non-seasonal model parameter) and P, D, and Q (seasonal model parameter) for the same SPEI period in the proposed models are analogous where “p” is the order of autoregressive lags, q is the order of moving average lags and d is the order of integration. Additionally, these parameters show the strong likeness for Moving Average (M.A) and Autoregressive (A.R) parameter values. From the various developed models for the Thar region, it has been concluded that the model (0,1,0)(1,0,2) is the best ARIMA model at 24 SPEI and could be considered as a generalized model. In the (0,1,0) model, the A.R term is 0, the difference/order of integration is 1 and the moving average is 0, and in the model (1,0,2) whose A.R has the 1st lag, the difference/order of integration is 0 and the moving average has 2 lags. Larger values for R2 greater than 0.9 and smaller values of Mean Error (ME), Mean Absolute Error (MAE), Mean Percentile Error (MPE), Mean Absolute Percentile Error (MAPE), and Mean Absolute Square Error (MASE) provide the acceptance of the generalized model. Consequently, this research suggests that drought forecasting can be effectively fulfilled by using ARIMA models, which can be assist policy planners of water resources to place safeguards keeping in view the future severity of the drought.
Published: 25 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101247

Abstract:
A high sensitivity wavelength modulated reinjection off-axis integrated cavity output spectroscopy (WM-RE-OA-ICOS) experimental setup was built at a 2 μm band. On the basis of an off-axis integrated output spectroscopy (OA-ICOS), combined with an optical reinjection (RE) approach to improve signal intensity, and wavelength modulation spectroscopy (WMS) to improve the signal-to-noise ratio (SNR) of the system, the experimental study of trace CO2 with high sensitivity was carried out using the setup. The performance was compared and evaluated, and the results show that: Compared with the OA-ICOS, the wavelength modulated reinjection OA-ICOS enhanced the signal intensity by 6.3 times, and the SNR increased 7.2 times from 179 to 1288. The Allan variance results showed that the detection limit of the system is 0.35 ppm when the average system time is 230 s. The setup was used to measure the indoor CO2 concentration for a long time (22 h), and the measured results were in line with the actual concentration change. The proposed method shows good performance enhancement for the OA-ICOS system in trace gas measurements.
Published: 24 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101244

Abstract:
With the deepening of urbanization and industrialization, as well as the exacerbation of energy consumption, China is facing a severe situation in which nitrogen oxide (NOx) emissions reduction is imperative. In this study, it is aimed to put forward countermeasures and suggestions to reduce NOx emissions by analyzing the impact and mechanism of new urbanization, the agglomeration of energy-intensive industries and mutual interactions on China’s NOx emissions. By analyzing the data of 30 provinces in China from 2006 to 2017, this paper adopted the system generalized method of moments (SYS-GMM) and intermediary effect model to introduce four variables, such as: energy efficiency, human capital, industrial structure and energy structure, which were for empirical analysis. From the results, it was shown that: (1) NOx emissions in China have an accumulated effect; (2) new urbanization inhibits NOx emissions, whilst the agglomeration of energy-intensive industries intensifies NOx emissions. New urbanization weakens the negative impact of the agglomeration of energy-intensive industries on NOx emissions reduction and, (3) among the impacts of new urbanization on NOx emissions, the energy efficiency and human capital reflect the intermediary effect mechanism. At the same time, in the impact of the agglomeration of energy-intensive industries on NOx emissions, the industrial structure and energy structure show the mechanisms of the intermediary effect and masking effect, respectively.
Published: 24 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101246

Abstract:
Significant portions of European cities’ population are still exposed to levels of air pollution deemed harmful by the World Health Organization. Given the high impact of air pollution both on human health and the economy, numerous low-cost electrochemical sensor monitoring systems are being installed. The market is forced to develop new air quality monitoring systems to meet the needs of providing forecasting services based on advanced technologies and protocols that utilize certain characteristics such as high accuracy, real-time monitoring, daily and yearly statistics, data access from both experts and simple users with the use of low-cost equipment. In this study, conducted in Athens, Greece, a comparison is attempted between the findings from a low-cost electrochemical sensor device and those of a static, fixed site measurement monitoring station; this comparison is based on the data quality and Air Quality Index (AQI) concerning data accuracy and quality on adverse health effects due to air pollution. With regard to the prediction of different AQI intervals, TPR ranges from 35.2% up to 100.0%, FPR from 0.0% up to 36.1% and FNR from 0.0% up to 38.1%. The outcome of this study reveals flexible and affordable alternatives adopted during the evaluation and calibration of low-cost gas sensors for monitoring.
Published: 24 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101245

Abstract:
Understanding rainfall in arid and water-scarce regions is central to the efficient use of water resources in agriculture, irrigation, and domestic food security. This work presents a new dataset with which to study precipitation processes in arid regions, utilising two years (2018–2020) of ceilometer observations made at Al Ain International Airport in the desert region of Al Ain, United Arab Emirates (UAE), where the annual rainfall is 76 mm. Ceilometer data provide a novel method by which to study both the evolution of water droplets from the cloud base down to the surface and the local circumstances required for rain to successfully reach the surface. In this work, we explore how successful precipitation depends on the initial size of the droplets and the thermodynamic profile below the cloud. For 64 of the 105 rain events, the droplet diameters ranged from 0.60 to 3.75 mm, with a mean of 1.84 mm. We find that smaller droplets, higher cloud bases, reduced cloud depths, and colder cloud bases all act to prevent successful precipitation, instead yielding virga (28 out of the 105 rain generating events). We identify how these multiple regional factors combine—specifically, we identify clouds deeper than 2.9 km, droplet diameters greater than 2 mm, and a midpoint below-cloud RH profile greater than 50%—to give successful rainfall, which may ultimately lead to more efficient rainfall enhancing measures, such as cloud seeding.
Published: 23 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101241

Abstract:
The residual levels of 16 priority polycyclic aromatic hydrocarbons (PAHs) in environment media and freshwater fish were collected and measured from Lake Chaohu by using Gas chromatography-mass spectrometry. Potential atmospheric sources were identified by molecular diagnostic ratios and the positive matrix factorization (PMF) method. PAH exposure doses through inhalation, intake of water and freshwater fish ingestion were estimated by the assessment model recommended by US EPA. The carcinogenic risks of PAH exposure were evaluated by probabilistic risk assessment and Monte Carlo simulation. The following results were obtained: (1) The PAH16 levels in gaseous, particulate phase, water and fish muscles were 59.4 ng·m−3, 14.2 ng·m−3, 170 ng·L−1 and 114 ng·g−1, respectively. No significant urban-rural difference was found between two sampling sites except gaseous BaPeq. The relationship between gaseous PAHs and PAH in water was detected by the application of Spearman correlation analysis. (2) Three potential sources were identified by the PMF model. The sources from biomass combustions, coal combustion and vehicle emission accounted for 43.6%, 30.6% and 25.8% of the total PAHs, respectively. (3) Fish intake has the highest lifetime average daily dose (LADD) of 3.01 × 10−6 mg·kg−1·d−1, followed by the particle inhalation with LADD of 2.94 × 10−6 mg·kg−1·d−1. (4) As a result of probabilistic cancer risk assessment, the median ILCRs were 3.1 × 10−5 to 3.3 × 10−5 in urban and rural residents, which were lower than the suggested serious level but higher than the acceptable level. In summary, the result suggests that potential carcinogenic risk exists among residents around Lake Chaohu. Fish ingestion and inhalation are two major PAH exposure pathways.
Published: 23 September 2021
by MDPI
Atmosphere, Volume 12; https://doi.org/10.3390/atmos12101240

Abstract:
We investigated the seasonal and diurnal characteristics of volatile organic compound (VOC) concentrations in Shenyang, China, using the whole-year hourly data of 52 types of VOC at three sites over the year 2019. The photochemical reactivities of VOCs were also studied by analyzing the influence of VOCs on ozone and secondary organic aerosol (SOA) formation potential and the hydroxyl radical consumption rate. It is shown that the order of VOC concentrations from high to low is alkanes, alkynes, alkenes, and aromatic hydrocarbons. For various types of VOCs, the maximum appeared in the morning and at night, whereas the minimum appeared in the afternoon. The contributions of VOCs to ozone formation potential are highest for aromatic hydrocarbons with a value of 78%, followed by alkenes and alkanes, among which toluene and isoprene contributed the most. The contributions of VOCs to SOA formation potential are also highest for aromatic hydrocarbons with a value of 94%, followed by alkanes and alkenes, among which the contributions of toluene and benzene add up to over 70%. Being the most active type of VOCs in atmospheric chemical reactions, aromatic hydrocarbons are the dominant contributor to the formation of both ozone and SOA, and therefore being able to control of the use of a large number of solvents and vehicle exhaust emissions would be an effective way to regulate the formation of ozone and SOA in Shenyang.
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