Effects Of Meteorological Conditions Research Articles

One year of active moss biomonitoring in the identification of PAHs in an urbanized area-prospects and implications.

Classical monitoring of air pollution provides information on environmental quality but involves high costs. An alternative to this method is the use of bioindicators. The purpose of our work was to evaluate atmospheric aerosol pollution by selected polycyclic aromatic hydrocarbons conducted as part of annual active biomonitoring ("moss-bag" technique) with the use of three moss species: Pleurozium schreberi, Sphagnum fallax, and Dicranum polysetum. The gas chromatography-mass spectrometry (GC-MS) was utilized to determine certain 13 polycyclic aromatic hydrocarbons (PAHs). Three seasonal variations in PAH concentrations have been observed as a result of the study. A fire on the toilet paper plant caused an increase of five new compounds: benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), indeno(1.2.3)-cd_pyrene (IP), dibenzo(a.h)anthracene (Dah), and benzo(g.h.i)perylene (Bghi) in proximity after 8months of exposure compared to previous months. The effect of meteorological conditions on the deposition of PAHs (mainly wind direction) in mosses was confirmed by principal component analysis (PCA). Dicranum polysetum moss accumulated on average 26.5% more PAHs than the other species, which allows considering its broader use in active biomonitoring. The "moss-bag" technique demonstrates its feasibility in assessing the source of PAH air pollution in a long-term study. It is recommended to use this biological method as a valuable tool in air quality monitoring.

Uncovering the evolution of ozone pollution in China: A spatiotemporal characteristics reconstruction from 1980 to 2021

Ozone pollution emerged as a significant environmental concern in China in recent years. Given the enduring impact of anthropogenic activities on the atmosphere, understanding the long-term evolutionary patterns of ozone pollution is crucial for effective pollution mitigation strategies. However, there have been limited studies to reconstruct spatiotemporal continuity ozone concentrations in China since 1980. In this research, monthly and daily MDA8 ozone concentrations from 1980 to 2021 were first estimated by reproducing the numerical relations between ozone pollution and the atmospheric environment based on a machine learning approach. The verification results from temporal, spatial, and sample-based cross-validation methods demonstrated the model performance in simulating MDA8 ozone concentration spatiotemporally, with correlation coefficients (R) ranging from 0.76 to 0.79, mean square error (RMSE) ranging from 22.72 μg·m−3 to 24.28 μg·m−3, and mean absolute error (MAE) ranging from 17.06 μg·m−3 to 18.25 μg·m−3. The evolution of ozone pollution in China can be delineated into two phases, characterized by an increasing trend since 2001, coinciding with significant rises in average annual temperature and hot weather frequency over the past four decades. The 90th percentile of ozone concentration from 2001 to 2021 increased by 1.79% compared to the period from 1980 to 2001. Notably, ozone episodes have expanded beyond summer months, partly due to global warming and frequent extreme climate events, contributing to an annual temperature increase of 0.03 °C. Despite several pollutant emission restrictions since 2013, the ozone pollution in China has persisted due to the increased emissions of VOCs. Spatially, severe ozone pollution hotspots are evident in Xinjiang province, the Jing-Jin-Ji urban agglomeration, and Northeast China, with notable increases observed in Tibet and the Guangdong-Hong Kong-Macao Greater Bay Area over the past six years. Moreover, the influence factors were identified by the average reduction of node impurity calculation. The evolution of ozone pollution was inextricably linked to solar radiation and atmospheric temperature, which played pivotal positive roles in ozone formation. Whilst, there is significant heterogeneity in the effect of meteorological conditions on ozone concentrations due to the disparity between land and oceanic climates.

Effects of Meteorological Factors on Asthma Hospital Visits in Haikou City, China

The effects of meteorological conditions on asthma in Haikou, a tropical city in China, are still unclear. This study aimed to determine the relationships between meteorological factors and the number of asthma hospital visits in Haikou. A Poisson generalized additive model combined with a distributed lag nonlinear model is used to model the nonlinear exposure–response relationship between the daily mean temperature and asthma hospital visits. The daily mean pressure and air quality are used as covariates and simultaneously control the mixed effects of holiday effects, weekend effects, and long-term trends. The results indicate that there is a significant statistical relationship between the daily mean temperature and asthma hospital visits, which shows an inverted J-shaped relationship. When the daily mean temperature is below the reference value (29.3 °C), the number of asthma patients increases considerably, and there is a marked lag in the prevalence of asthma. The longest lag is 9 days, and the most pronounced impact of the daily mean temperature on the number of asthma hospital visits can be found when the lag time is 1–4 days. When the daily mean temperature is 10 °C, the cumulative effect of the relative risk of asthma is 2.204, an increase of 120.4% (95% CI 1.294–3.755). If the daily mean temperature is below the 2.5th percentile value (14.8 °C), the relative risk significantly increases by more than 5.3% (95% CI 1.000–1.110), and the longest lasting impact time is 5 days. This indicates that increases in asthma hospital visits in Haikou, China, are significantly correlated with low-temperature weather. We suggest that preventive measures for asthma should take low-temperature weather into account. Additionally, we also found that extremely high temperatures have a certain impact on the increase in asthma hospital visits, but that the correlation is not significant.

Processes governing the surface ozone over a tropical hill station in the Western Ghats

Tropospheric ozone (O3) plays predominant role in atmospheric chemistry, exacerbates the air quality, and contributes to the climate change. Near the Earth's surface, O3 levels exhibit large heterogeneity due to diverse emissions of precursors and effects of meteorological conditions. Nevertheless, the understanding of key dynamical and photochemical processes governing O3 remains limited in the Western Ghats, a tropical region of immense significance in context of the geosphere-biosphere processes. In this regard, we combined surface O3 measurements at Ponmudi (8.758° N, 77.114° E, ∼1 km above mean sea level–amsl), a high-altitude site in the Western Ghats, with ground- and balloon-borne O3 measurements at western coast of India (Thumba: 8.542° N, 76.858° E, ∼3 m amsl) and photochemical box model simulations. O3 diurnal variation exhibits a small amplitude (3–9 ppbv) with lower values during the daytime, in contrast to substantial urban O3 build-up (25–37 ppbv) at Thumba. The influence of regional pollution from the urban boundary layer, downdraft of O3-rich air during night, and dry deposition processes are suggested to govern the O3 diurnal pattern over Ponmudi. Lower O3/CO and O3/NO2 ratios indicating lower O3 production efficiency, and dominant role of dynamics are consistently seen over the study region. O3 variability between Ponmudi and Thumba are found to be well correlated (r = 0.7–0.8) during pre-monsoon and post-monsoon seasons as the sea breeze circulation transport the airmass from coast to the Western Ghats during the daytime. Mean O3 levels at Ponmudi are typically lower than those above Thumba showing an effective O3 loss towards Ponmudi. Chemistry involving strong natural emissions (e.g., isoprene) as simulated by photochemical box model, and greater dry deposition tend to supress O3 build up over this densely vegetated tropical region. Unlike other high-altitude sites, O3 seasonal cycle at Ponmudi is associated closely with synoptic wind changes, and peaks during the winter owing to the transport from Indo Gangetic Plain/northern India. Our study highlights the roles of regional pollution as well as natural processes including biogenic emissions in governing the surface O3 variability over the Western Ghats.

Effects of meteorological conditions on the mixing height of Nitrogen dioxide in China using new-generation geostationary satellite measurements and machine learning

Nitrogen dioxide (NO2) plays a critical role in terms of air quality, human health, ecosystems, and its impact on climate change. While the crucial roles of the vertical structure of NO2 have been acknowledged for some time, there is currently limited knowledge about this aspect in China. The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first geostationary satellite instrument capable of measuring the hourly columnar amount of NO2. The study presented here introduces the use of mixing height for NO2 in the atmosphere. A thorough examination of spatiotemporal variations in the mixing height of NO2 was conducted using data from both the GEMS and ground-based air quality monitoring networks. A random forest model based on machine learning techniques was utilized to examine how meteorological parameters affect the mixing height of NO2. The results of our study reveal a notable seasonal fluctuation in the mixing height of NO2, with the highest values observed during the summer and the lowest values during the winter. Additionally, there was an increasing diurnal trend from early morning to mid-afternoon. Moreover, the study discovered elevated NO2 mixing heights in the dry regions of northern China. The results also indicated a positive correlation between the mixing height of NO2 and temperature and wind speed, while negative associations were found with relative humidity and air pressure. The machine learning model's predicted NO2 mixing heights were in good agreement with the measurement-based outcomes, as evidenced by a coefficient of determination (R2) value of 0.96 (0.84 for the 10-fold cross-validation). These findings emphasize the noteworthy influence of meteorological variables on the vertical distribution of NO2 in the atmosphere and enhance our comprehension of the three-dimensional variations in NO2.

Background Characteristics and Influence Analysis of Greenhouse Gases at Jinsha Atmospheric Background Station in China

Central China has been acting as a major convergence zone for sources and sinks in China, such that the climate change studies of Central China have taken on critical significance. The Jinsha atmospheric background station refers to the sole background monitoring site in Central China. It is noteworthy that the greenhouse gas attributes of the Jinsha atmospheric background station represent the greenhouse gas conditions of Central China. The seasonal and daily variations in CO2, CH4, and CO in the scope of time between October 2019 to April 2021 at the station were examined in this study. The effect of meteorological conditions on greenhouse gas concentrations at the site was evaluated. Furthermore, the primary transmission origins affecting the station were identified using the backward trajectory through potential source contribution function analysis. As indicated by the results, the background concentrations at the Jinsha station in 2020 for CO2, CH4, and CO reached 424.1 ± 0.1 ppm, 2046.2 ± 0.6 ppb, and 324.1 ± 1.1 ppb, respectively. CO2 varied on a daily basis with higher nighttime levels, which was affected by the boundary layer elevation, photosynthesis, and human activities. In autumn, CH4 levels peaked under the effect of agricultural activities in Central China. However, CO2 and CO concentrations reached the maximum in winter, majorly affected by the transmissions from the Beijing–Tianjin–Hebei region and Hubei. Under China’s comprehensive carbon neutrality, more attention should be paid to the emissions from winter heating and industrial activities in the Beijing–Tianjin–Hebei region, and effects exerted by transport in the monitoring process should be differentiated in depth.

The influence of agricultural land on the level of airborne Alternaria spores

Aim of the research was to investigate the impact of agricultural activity on the concentration of Alternaria spores.
 Materials and methods. The study was carried out at the Department of Medical Biology, Parasitology and Genetics of the ZSMPhU. Samples were collected using a 7-day volumetric sampler of the Hirst type, using the volumetric method. Samples were identified under a light microscope, and spore identification and counting were limited to genus levels. The relationship between seasonal Alternaria spore levels and harvest rates was analysed using Pearson's correlation method. The effect of meteorological conditions and agricultural activity on the daily concentration of Alternaria was analysed using stepwise correlation based on logarithmically transformed daily average spore counts. Classical leave-one-out cross-validation (LOOCV) was used to estimate the mean square error (MSE), associated with this model and Bayesian information criterion (BIC) was used to assess its accuracy.
 Results. Seasonal characteristics of Alternaria spores and agricultural activity in Zaporizhzhia and Dnipro regions were analysed. The connection of some seasonal and daily indicators with harvesting rates and meteorological conditions was determined. Two models with 5 and 9 parameters were found that best explain the dynamics of Alternaria spores.
 Conclusions. The most significant parameters positively correlated with Alternaria spore levels were temperature, pressure, westerly wind and wheat yield; relative humidity was negatively correlated

Assessing the Impacts of Birmingham’s Clean Air Zone on Air Quality: Estimates from a Machine Learning and Synthetic Control Approach

We apply a two-step data driven approach to determine the causal impact of the clean air zone (CAZ) policy on air quality in Birmingham, UK. Levels of NO2, NOx and PM2.5 before and after CAZ implementation were collected from automatic air quality monitoring sites both within and outside the CAZ. We apply a unique combination of two recent methods: (1) a random forest machine learning method to strip out the effects of meteorological conditions on air pollution levels, and then (2) the Augmented Synthetic Control Method (ASCM) on the de-weathered air pollution data to isolate the causal effect of the CAZ. We find that, during the first year following the formal policy implementation, the CAZ led to significant but modest reductions of NO2 and NOX levels measured at the roadside within (up to 3.4% and 5.4% of NO2 and NOX, respectively) and outside (up to 6.6% and 11.9%) the zone, with no detectable changes at the urban background site outside the CAZ. No significant impacts of the CAZ were found on concentrations of fine particulates (PM2.5). Our analysis demonstrates the short-term effectiveness of CAZ in reducing concentrations of NO2 and NOX.

Effects of meteorological conditions on brood care in cooperatively breeding carrion crow and consequences on reproductive success

Meteorological stressors (e.g., temperature and rain shortage) constrain brood provisioning in some bird species, but the consequences on reproductive success have been rarely quantified. Here we show, in a cooperatively breeding population of carrion crow Corvus corone in Spain, that individual feeding rates decreased significantly with rising air temperatures both in breeders and helpers, while lack of rain was associated with a significant reduction in the effort of the male helpers as compared to the other social categories. Group coordination, measured as the degree of alternation of nest visits by carers, was also negatively affected by rising temperature. Furthermore, we found that the body condition of the nestlings worsened when temperatures were high during the rearing period. Interestingly, the analysis of a long-term data set on crow reproduction showed that nestling body condition steadily deteriorated over the last 26-years. Although many factors may concur in causing population changes, our data suggest a possible causal link between global warming, brood caring behaviour and the decline of carrion crow population in the Mediterranean climatic region of Spain.

Effect of Meteorological Conditions on Pollutants Removal and Enhancing Approaches During Photovoltaic Energy Direct Application: Electrokinetic Remediation of Soil Containing Cr(VI) as an Example

Effect of Meteorological Conditions on Pollutants Removal and Enhancing Approaches During Photovoltaic Energy Direct Application: Electrokinetic Remediation of Soil Containing Cr(VI) as an Example

Concentrations of PM0.1 and PM2.5 at high polluting event days in Ha Noi and the effects of meteorological conditions

. High levels of fine (PM2.5) and ultrafine (PM0.1) particles in the atmosphere can cause adverse effects on the environment and human health. This study aims at determining the mass concentrations of PM and meteorological influencing factors in high pollution event days in Hanoi. Daily samples of PM2.5 and PM0.1 were collected at a mixed site in Hanoi, Vietnam, from the middle of October to December 2020. High pollution events were determined based on PM2.5 concentrations and analyzed for its average concentration and intensity (number of days). The regression analysis and correlation matrix were determined by R software, version 4.04. Seven high pollution events were recorded for 2.5 sampling months. The daily PM2.5 concentrations were in the range of 19 - 147 µg/m3. Those of PM0.1 varied from 2 to 13 µg/m3 with an average of 6 µg/m3. The investigated meteorological factors can explain 70% PM2.5 variation but only 47% of PM0.1 variations.

Effect of meteorological conditions on PM10 concentrations in the middle reaches of the Yarlung Zangbo River, Tibet Plateau

Effect of meteorological conditions on PM10 concentrations in the middle reaches of the Yarlung Zangbo River, Tibet Plateau

Effect of Meteorological Conditions and Long-Range Air Mass Transport on Surface Aerosol Composition in Winter Moscow

Effect of Meteorological Conditions and Long-Range Air Mass Transport on Surface Aerosol Composition in Winter Moscow

Quantification of meteorological conditions for rockfall triggers in Germany

Abstract. A rockfall dataset for Germany is analysed with the objective of identifying the meteorological and hydrological (pre-)conditions that change the probability for such events in central Europe. The factors investigated in the analysis are precipitation amount and intensity, freeze–thaw cycles, and subsurface moisture. As there is no suitable observational dataset for all relevant subsurface moisture types (e.g. water in rock pores and cleft water) available, simulated soil moisture and a proxy for pore water are tested as substitutes. The potential triggering factors were analysed both for the day of the event and for the days leading up to it. A logistic regression model was built, which considers individual potential triggering factors and their interactions. It is found that the most important factor influencing rockfall probability in the research area is the precipitation amount at the day of the event, but the water content of the ground on that day and freeze–thaw cycles in the days prior to the event also influence the hazard probability. Comparing simulated soil moisture and the pore-water proxy as predictors for rockfall reveals that the proxy, calculated as accumulated precipitation minus potential evaporation, performs slightly better in the statistical model. Using the statistical model, the effects of meteorological conditions on rockfall probability in German low mountain ranges can be quantified. The model suggests that precipitation is most efficient when the pore-water content of the ground is high. An increase in daily precipitation from its local 50th percentile to its 90th percentile approximately doubles the probability for a rockfall event under median pore-water conditions. When the pore-water proxy is at its 95th percentile, the same increase in precipitation leads to a 4-fold increase in rockfall probability. The occurrence of a freeze–thaw cycle in the preceding days increases the rockfall hazard by about 50 %. The most critical combination can therefore be expected in winter and at the beginning of spring after a freeze–thaw transition, which is followed by a day with high precipitation amounts and takes place in a region preconditioned by a high level of subsurface moisture.

Effect of meteorological conditions on leisure walking: a time series analysis and the application of outdoor thermal comfort indexes.

Leisure walking is affected by meteorological conditions. However, it is still not clear what scales of meteorological conditions and thermal status affect the number of people who choose to leisure walk. Using a time series regression, this study examines the heat-leisure walking relationship by analyzing the effect of the seasons, weather, microclimate, and outdoor thermal comfort on walking count. Eight thermal indexes were selected to estimate the pedestrians' thermal comfort, and their predictive capacities in walking count were evaluated. Particular consideration was given to identifying heat thresholds of walking that determined the tolerance range of pedestrian heat stress. Four years of hourly daytime walking counts and publicly available ASOS meteorological data at Seoul-lo 7017, a pedestrian bridge in Seoul, were used for the analysis. Our findings indicate that walking count is correlated with seasonal climatic variations, with the highest number of pedestrians observed in fall and the lowest in summer. Moreover, air temperature played a vital role, showing that a 5.0°C rise in temperature was associated with a 1.34% rise in the square root of the walking count. Its impact becomes greater when combined with intense solar radiation and higher absolute humidity. The heat threshold for walking was between 23.8°C and 26.2°C. Empirical model indexes showed the highest predictive capacity in walking count at approximately 30.0%, which was followed by rational model indexes at 28.0%.

Seasonality and long-term trends of NDVI values in different land use types in the eastern part of the Baltic Sea basin

This study analyses changes in Normalized Difference Vegetation Index (NDVI) values in the eastern Baltic region. The main aim of the work is to evaluate changes in growing season indicators (onset, end time, time of maximum greenness and duration) and their relationship with meteorological conditions (air temperature and precipitation) in 1982–2015. NDVI seasonality and long-term trends were analysed for different types of land use: arable land, pastures, wetlands, mixed and coniferous forests. In the southwestern part of the study area, the growing season lasts longest, while in the northeast, the growing season is shorter on average by 10 weeks than in the other parts of the analysed territory. The air temperature in February and March is the most important factor determining the start of the growing season and the air temperature in September and October determines the end date of the growing season. Precipitation has a much smaller effect, especially at the beginning of the growing season. The effect of meteorological conditions on peak greenness is weak and, in most cases, statistically insignificant. At the end of the analysed period (1982–2015), the growing season started earlier and ended later (in both cases the changes were 3–4 weeks) than at the beginning of the study period. All these changes are statistically significant. The duration of the growing season increased by 6–7 weeks.

The effect of meteorological conditions on the spread of COVID-19 cases in six major cities in Saudi Arabia

The effect of meteorological conditions on the spread of COVID-19 cases in six major cities in Saudi Arabia

Nonlinear Response Relationship Between Ozone and Precursor Emissions in the Pearl River Delta Region Under Different Transmission Channels

With the rapid development of urbanization, ozone (O3) pollution is an ongoing occurrence in the Pearl River Delta (PRD) region in China. The effective control of O3 pollution is a great challenge owing to the nonlinear relationship between O3 and precursor emissions and the effect of meteorological conditions. Based on the regional air quality model CAMx-OSAT (ozone source apportionment technology), O3 formation regimes were determined, and inter-city transportation across PRD was quantified under different transmission channels. The results showed that spatial differences were observed for the O3 formation regimes under different transmission channels. The VOCs-sensitive regime was mainly located in the central areas of the PRD region, and the NOx-sensitive regime was distributed in the suburban areas of the PRD regions under calm wind conditions. When the northeast wind was prevailing, the polluted air mass of the urban agglomeration was transmitted southwesterly downward, resulting in the downwind areas being transformed to VOCs-sensitive; the upwind areas were still NOx-sensitive. Under the southeast wind, the VOCs-sensitive regime had a banding distribution along the southeast-northwest direction, and the remaining areas were NOx-sensitive. With the influence of transmission channels, downwind cities were significantly affected by the transmission of upwind urban agglomerations (41%-87%), whereas the local formation was the main contributor under the calm wind conditions (60%-87%). To explore the relationship between O3 and precursor emissions, a series of sensitivity tests were designed. The results showed that maximized areas (20%-36%) with reductions in O3 can be achieved by reducing VOCs and NOx in the corresponding sensitive regimes, and the maximized level with the reduction in O3 can be fulfilled by reducing VOCs in the VOCs-sensitive regime. For the typical city Jiangmen, the area that met the standard increased the most under the calm wind (11%) and southeast wind (8%) conditions when VOCs and NOx were reduced in the corresponding sensitive regimes. Additionally, under northeast wind conditions, reducing VOCs in the VOCs-sensitive regime can more effectively control O3, as the area up to the standard increased by 140%.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX=NO2+O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX=NO2+O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Effect of Meteorological Conditions on Tectonic Deformations in Hourly Period Range

Effect of Meteorological Conditions on Tectonic Deformations in Hourly Period Range