Effects Of Atmospheric Pollution Research Articles

Effects of atmospheric pollutants on human health and deterioration of medieval historical architecture (North Africa, Tunisia)

Air pollution is a factor of concern on a global scale, accelerating the deterioration of historic medieval architecture and having harmful effects on human health. The general objective of this study is to understand the risks of atmospheric contamination that contribute to the degradation of the medieval historical heritage of (1) Bab El Bhar, (2) the Tunis Train Station and (3) the Bardo National Museum, in the City of Tunis, capital of Tunisia, located in North Africa. Sequentially, 64 samples were collected in SMPSs and 64 of dust particles in sites 1, 2 and 3, from 2015 to 2019. Field Emission Scanning Electron Microscopy (FE-SEM) was utilized together with High Resolution Transmission Electron Microscopy (HR-TEM) and the coupled with an Energy Dispersive X-ray (EDS), which allowed a better characterization and identification of NPs in images, using Energy Dispersive X-ray (EDS). The Bab El Bhar SMPS samples yielded a higher proportion of ultrafine and organic particles. Sedimented dusts showed high proportions of organometallic particles (Al, As, Ba, Ca, Cd, Co, Cr, Fe, K, Mg, Mn, Mo, Na, Ni, Pb, S, Sb, Se, Si, Sn, Ti, V and Zn). The need to create public policies to protect both human health and physical historic infrastructure is noted, as this study identified dangerous elements harmful to human health in ultrafine particles, easily suspended by the wind and highly corrosive to historical buildings from the medieval period in the air of a busy metropolitan tourist site.

Synergistic effects of air pollutants on meteorological fields at the junction of the Loess Plateau, Mongolian Plateau and Tibetan Plateau over Northwest China during summer

The synergistic effects of various air pollutants on meteorological fields have not yet been widely studied and fully understood, especially at the junction of the Loess Plateau, Mongolian Plateau and Tibetan Plateau. Two experiments were carried out with and without the incorporation of air pollutants to explore the synergistic effects using the Weather Research and Forecasting (WRF) model and WRF model coupled with chemistry (WRF-Chem) at the junction of the above three plateaus. The incorporation of air pollutants led to negative and positive variation patterns of meteorological fields and improved the simulation accuracy of meteorological factors to some extent. The negative variation pattern was caused by the direct absorption and scattering of solar radiation by air pollutants, and the positive variation pattern was driven by the evaporation of clouds due to the synergistic semidirect effects of air pollutants, which was more significant in this region. In the positive variation pattern, the solar radiation flux reaching the ground and the outgoing longwave radiation at the top of the atmosphere were increased by approximately 2–8% and 1–4%, respectively, the surface was warmed by 0.2–0.6 K, planetary boundary layer height (PBLH) increased by 3–12%, and relative humidity (RH) decreased by 1–4%. Moreover, the change in wind speed was approximately −0.3–0.3 m/s in the region. Furthermore, the correlation of conventional air pollutants with changes in meteorological factors indicated that there were not simple linear effects of atmospheric pollutants on meteorological fields and that considering a single pollutant cannot reflect the synergistic effects of various air pollutants on meteorological fields. This study quantifies the synergistic effects of various air pollutants on meteorological fields, which is a key issue that cannot be ignored in the modelling of meteorological fields and in the exploration of the interactions between air pollutants and synoptic weather.

Anthropogenic and technogenic air pollution: case study of Bratsk

In the Russian Federation, the problem of atmospheric air pollution is relevant for most regions. Based on the dispersion calculations, the risk to the Bratsk population’s health from the chemicals that pollute the air was assessed. It was found that short-term effects of atmospheric pollution cause non-carcinogenic risks to the respiratory system, the immune and blood systems, systemic disorders and damage developmental processes. More than 95% of the contribution to the aggregate level of acute risks are made by dust, nitrogen dioxide, sulfur dioxide, gaseous fluorides, and benzene. Chronic exposure increases the level of the carcinogenic risk, causes the non-carcinogenic risk to the respiratory system, the skeletal system, blood damage and developmental disorders. More than 95% of the contribution are made by nitrogen oxides, sulfur dioxide, gaseous and poorly soluble fluorides, benzene, benzo (a) pyrene, carbon, hexavalent chromium and dust. A list of 13 priority pollutants that should be regularly monitored in Bratsk was compiled.

Good Agreement Between Modeled and Measured Sulfur and Nitrogen Deposition in Europe, in Spite of Marked Differences in Some Sites

Atmospheric nitrogen and sulfur deposition is an important effect of atmospheric pollution and may affect forest ecosystems positively, for example enhancing tree growth, or negatively, for example causing acidification, eutrophication, cation depletion in soil or nutritional imbalances in trees. To assess and design measures to reduce the negative impacts of deposition, a good estimate of the deposition amount is needed, either by direct measurement or by modeling. In order to evaluate the precision of both approaches and to identify possible improvements, we compared the deposition estimates obtained using an Eulerian model with the measurements performed by two large independent networks covering most of Europe. The results are in good agreement (bias <25%) for sulfate and nitrate open field deposition, while larger differences are more evident for ammonium deposition, likely due to the greater influence of local ammonia sources. Modeled sulfur total deposition compares well with throughfall deposition measured in forest plots, while the estimate of nitrogen deposition is affected by the tree canopy. The geographical distribution of pollutant deposition and of outlier sites where model and measurements show larger differences are discussed.

Micro and Macroelements in Honey and Atmospheric Pollution (NW and Central Poland)

Urban vegetation is generally exposed to high levels of air pollution in airborne particles, with the greatest exposure in the EU being seen in Poland. With the continuing growth of urban populations, there is a need to confirm whether honey produced from urban areas is of similar high quality to that from rural areas. A total of 27 honey samples were collected from urban and rural apiaries and tested for the concentrations of 19 elements by ICP-OES. The results were compared with data on honey produced in old and new EU countries (metadata). Our evaluation used a novel approach to determine threshold values in the identification of the bioproduct contamination index. The analysed urban honey samples demonstrated higher concentrations of K, Sr, Ba, Ni, and Co, and lower levels of Mn and B than rural honey samples. Contamination by PM10 particles and the toxic elements contained in them proved to be a poor predictor of the content of these elements in honey, in contrast to the effect of atmospheric pollution measured during firework shows, which demonstrated higher concentrations of Ba, Pb, Ca, Cu, and Mg. The non-carcinogenic risk assessment indicated that the analysed honey samples are of good quality and are comparable or of even better quality than honey products from other EU countries.

Impact of vehicular emissions on anatomical and morphological characteristics of vascular plants: A comparative study

Abbottabad is a famous tourist destination due to its greenery and location. However, rapid increase in population and unplanned urbanization cause various environmental problems. Among different environmental stress, vehicular emission is the major issue for the survival and sustainability of plant species. This study aimed to investigate the effects of atmospheric pollution (caused by vehicular emission) on the anatomical, biochemical and morphological aspects of plant species present alongside the roads of Abbottabad, Pakistan. The plants were also collected from control sites (away from road-sites) for comparison. The results showed that various morphological characteristics of plant species including petiole length, vein-to-vein difference between leaves and length to breadth ratio of leaves were adversely affected by air pollution. The stomatal index varies in plant species because of variations in the numbers of epidermal cells. The air pollution tolerance index (APTI) of plant leaves from contaminated areas was reported to be higher as compared to control (non-contaminated) areas. Consequently, the findings from this study confirmed that plant species growing alongside of Abbottabad roads has greater tolerance than plant species growing in solitude areas away from road sites (control sites). Among different studied plants, Juglans regia, Morus nigra, Xanthium strumarium, Prunus armenica, Diospterus lotus and Populus ciliata have highest APTI and found to be more suitable for plantation in Abbottabad.

The Adverse Impact of Air Pollution on China’s Economic Growth

This study empirically evaluates the impact of air pollution on China’s economic growth, based on a province-level sample for the period 2002–2017. Air pollution is measured by the concentration of fine particulate matter (PM2.5), and economic growth is measured by the annual growth rate of gross domestic product (GDP) per capita. A panel data fixed-effects regression model is built, and the instrumental variables estimation method is utilized for quantitative analyses. The study reports a significant negative impact of air pollution on the macroeconomic growth of China. According to our instrumental variables estimation, holding other factors constant, if the concentration of PM2.5 increases by 1%, then the GDP per capita growth rate will decline by 0.05818 percentage points. In addition, it is found that the adverse effect of atmospheric pollution is heterogeneous across different regions. The effect is stronger in the eastern region and in provinces with smaller state-owned enterprise shares, fewer governmental expenditures for public health services, and fewer medical resources. The study results reveal that air pollution poses a substantial threat to the sustainable economic growth of China. Taking actions to abate air pollution will generate great economic benefits, especially for those regions which are heavily damaged by pollution.

Ambient Air Quality, Pollutant Behavior, and Distribution Pattern in Rabigh City Using an Air Dispersion Model

The rise in industrial development and modern technology is one of the major causes of atmospheric pollution, which negatively affects human health. In this study, meteorological conditions and atmospheric pollution dispersion in Rabigh city and its catchments were analyzed using measured data and an air quality dispersion model. The Hybrid Single-Particle Lagrangian Integrated Trajectory model was used to simulate the dispersion of atmospheric pollutants. A dataset from 2018 was analyzed to clarify the seasonal distributions of atmospheric pollutant concentrations in Rabigh and other areas (Thuwal and Khulais). A significant variation in atmospheric pollutants was recorded across the seasons, which may be caused by changes in meteorological conditions. Variations in other anthropogenic sources related to high population density or heavy traffic in the nearby road may also be involved in these fluctuations. Predictions indicated that pollutants would impact the Thuwal area (>50 μg m−3) and Khulais (>35 μg m−3) during the winter season and affect Thuwal (>20 μg m−3) and Rabigh (>20 μg m−3) during the fall season. The concentrations of pollutants were mostly negatively correlated with wind speed, except for carbon monoxide. We established variations in the seasonal concentration of pollutants and the effect of meteorological conditions on atmospheric pollutants for the year 2018 in the study area. Policymakers and stakeholders must provide solutions to mitigate the environmental effect of atmospheric pollution in Rabigh city, Thuwal, and Khulais for the health of inhabitants.

Influences of the optimized air curtain at subway entrance to reduce the ingress of outdoor airborne particles

It is of great significance to control the air quality of underground metro stations, especially considering their poorly ventilated environments. Existing literature mainly focuses on the removal and control of underground pollutants and seldom pay attention to the ingress effects of atmospheric pollutants (e.g., from the burning of fossil fuels, exhaust gas of vehicles, etc.) diffusion through the entrances/exits. In this study, we aim to study the reducing effects of integrated air curtain and exhaust systems on atmospheric airborne particles entering into the metro stations. Validated turbulent models were adopted for numerical simulations. The associated effects of air curtain velocity, exhaust velocity, and atmospheric wind speed were investigated. Four different installation locations of the air curtain were considered. Subsequently, monitoring, Artificial Neural Network, and air purification methods were proposed for the optimal design of integrated air curtain and exhaust system. It is concluded that an integrated air curtain and exhaust system can improve the interception efficiency on particles around 40% compared with no measure taken at the subway entrance, or it can be increased about 20% compared with only using an air curtain system (no exhaust vent) at the entrance.

Long-term effects of atmospheric deposition on British plant species richness

The effects of atmospheric pollution on plant species richness (nsp) are of widespread concern. We carried out a modelling exercise to estimate how nsp in British semi-natural ecosystems responded to atmospheric deposition of nitrogen (Ndep) and sulphur (Sdep) between 1800 and 2010. We derived a simple four-parameter equation relating nsp to measured soil pH, and to net primary productivity (NPP), calculated with the N14CP ecosystem model. Parameters were estimated from a large data set (n = 1156) of species richness in four vegetation classes, unimproved grassland, dwarf shrub heath, peatland, and broadleaved woodland, obtained in 2007. The equation performed reasonably well in comparisons with independent observations of nsp. We used the equation, in combination with modelled estimates of NPP (from N14CP) and soil pH (from the CHUM-AM hydrochemical model), to calculate changes in average nsp over time at seven sites across Britain, assuming that variations in nsp were due only to variations in atmospheric deposition. At two of the sites, two vegetation classes were present, making a total of nine site/vegetation combinations. In four cases, nsp was affected about equally by pH and NPP, while in another four the effect of pH was dominant. The ninth site, a chalk grassland, was affected only by NPP, since soil pH was assumed constant. Our analysis suggests that the combination of increased NPP, due to fertilization by Ndep, and decreased soil pH, primarily due to Sdep, caused an average species loss of 39% (range 23–100%) between 1800 and the late 20th Century. The modelling suggests that in recent years nsp has begun to increase, almost entirely due to reductions in Sdep and consequent increases in soil pH, but there are also indications of recent slight recovery from the eutrophying effects of Ndep.

Ambient air pollutants and hospital visits for pneumonia: a case-crossover study in Qingdao, China

BackgroundPneumonia is one of the principal reasons for incidence and death in the world. The former research mainly concentrated on specific sources of patients. Besides, due to the heterogeneity among regions, there are inconsistencies in the outcome of these surveys. To explore the relationship between atmospheric pollution and hospital visits for pneumonia under the climate and pollution conditions in Qingdao, we carried out this study.MethodsThe medical records of pneumonia patients were gathered from the affiliated hospital of Qingdao University during Jan 1st, 2014, and Dec 31st,2018. Daily concentrations of PM2.5, PM10, SO2, NO2, as well as CO, were collected from the national air quality monitoring stations in Qingdao. Case-crossover study design and conditional logistic regression model were used to estimate the associations. Daily temperature, relative humidity, and atmospheric pressure were adjusted as the covariates in all models. A principal component analysis was used to solve the multicollinearity between atmospheric pollutants and investigate the relationship between various air pollutants and pneumonia occurs.ResultsIn the single pollutant model, with interquartile range increment of the density of PM2.5, PM10, NO2 and SO2 at the lag2 days, the odds ratio of hospital visits for pneumonia patients increased by 6.4% (95%CI, 2.3–10.7%), 7.7% (95%CI, 3.2–12.4%), 6.7% (95%CI, 1.0–12.7%), and 7.2% (95%CI, 1.1–13.5%). Stratified analysis showed that pollutants were more significant in the cold period. Besides, the impact of atmospheric particulates on different ages mainly occurs in the young child (0 to 3-year-old). The odds ratio was 1.042 (95%CI, 1.012–1.072) when the principal components of atmospheric pollutants were included in the conditional logistic model.ConclusionsOur study found a significant relationship between short-term uncovering to PM2.5, PM10, NO2, SO2, and hospital visits for pneumonia in Qingdao. The effect of atmospheric pollutants mainly arose in a cold period. The particulate matter might be the principal reason in inducing hospital visits for pneumonia.

Setting tasks for constructing an integrated decision support and control system according to minimize losses from harmful effects of atmospheric pollutants

Abstract Integrated decision support systems are widespread in solving problems for reducing the harmful effects of air pollutants from industry and vehicles. Authors have developed new tasks for these systems to minimize damage caused by atmospheric emissions. Researchers have proposed a general approach to their solution, which allows to reduce the search time solutions. Authors have compiled a list of tasks that are part of a typical integrated decision support and management system based on the criterion of minimum losses from air pollutants harmful effects. We have determined the harmful substances contained in air pollutants of vehicles, ferrous metallurgy, chemical, machine-building and metal-working industry enterprises, as well as in the atmospheric emissions from thermal power plants, which must be taken into account in the process of solving the tasks for reducing the damage caused by atmospheric emissions from industrial enterprises and vehicles. We have designed new meaningful and formalized problem statements of integrated intelligent system functional structure synthesis for minimizing damage caused by air pollutions. Authors have solved the task of coordinating the integrated intelligent decision support system functional structure which allowed us to obtain an economic effect. As a result, authors developed a standard functional structure of an intelligent information system for environmental monitoring and management. This system reduces the losses from air pollution from industrial emissions. This will make it possible to implement this type of systems more effectively.

景观生态学在大气污染研究中的应用

快速城市化和工业化进程造成了一系列大气污染问题，亟需在宏观尺度上解析大气污染时空分布规律。景观生态学关注格局与过程耦合，景观"源汇"理论可对应解析大气污染物的源与汇效应，将景观生态学的理论与方法引入大气污染研究中已成为解决当前区域发展与大气污染权衡的有效途径。从景观生态学视角辨识了景观与大气污染物的源汇关系，系统梳理了景观格局与大气污染的定量关系，指出当前景观格局指标仍需进一步完善以表征大气污染时空分布特征，而高质量大气污染物时空数据的缺乏是限制景观格局与大气污染过程耦合分析的重要因素，拓展应用景观"源汇"理论，定量解析景观格局对大气污染的源汇效应，同时进一步研发遥感反演技术，实现大气污染物分布格局的精细刻画，将为区域景观规划提供重要支撑。强化大气污染研究中的景观生态学分析途径，将有助于深化景观生态学格局与过程耦合研究体系，也将为景观可持续管理提供有力的科学支撑。;Rapid urbanization and industrialization process have caused a series of atmospheric pollution problems, and it's necessary to explore the spatio-temporal distributions of atmospheric pollution at macro scale. Landscape ecology focuses on landscape pattern and process coupling. The source-sink theory of landscape ecology can be applied to analyze the source and sink effects of atmospheric pollutants. Introducing the theory and method of landscape ecology to air pollution research has become an effective way to solve the problem on the tradeoff between current development and atmospheric pollution. From the perspective of landscape ecology, the relationships between landscape and source and sink of atmospheric pollutants were identified. The quantitative effects of landscape pattern on atmospheric pollution were also reviewed. We found that the current landscape pattern index should be improved to characterize the spatial and temporal distribution characteristics of atmospheric pollution, and the lack of high-quality spatio-temporal air pollutants data limited coupling analysis of landscape pattern and the atmospheric pollution process. Expanding the application of landscape source-sink theory, quantitatively analyzing source and sink effects of atmospheric pollutants, and developing remote sensing techniques to characterize atmospheric pollutants distribution pattern would provide important support for regional landscape planning. Strengthening the approach of landscape ecology analysis in air pollution research will extend the landscape ecology system on pattern and process coupling and will provide scientific supports for sustainable management of landscape.

Short-Term Effects of Atmospheric Pollution on Daily Mortality and Their Modification by Increased Temperatures Associated with a Climatic Change Scenario in Northern Mexico.

Short-term effects of air pollution on the health of residents in the Metropolitan Area of Monterrey, Mexico were assessed from 2012–2015 using a time-series approach. Guadalupe had the highest mean concentrations for SO2, CO and O3; whereas Santa Catarina showed the highest NO2 concentrations. Escobedo and Garcia registered the highest levels for PM10. Only PM10 and O3 exceeded the maximum permissible values established in the Mexican official standards. Most of pollutants and municipalities showed a great number of associations between an increase of 10% in their current concentrations and mortality, especially for people >60 years. Different scenarios resulting from climatic change were built (increases of 5–25% in daily mean temperature), but only the increase of 25% (5 °C) showed a significant association with air pollutant concentrations and mortality. All pollutants and municipalities showed significant increases in relative risk indexes (RRI) resulting from an increase of 5 °C when people >60 years was considered. Results were comparable to those reported by other authors around the world. The RRI were low but significant, and thus are of public concern. This study demonstrated that the elderly is strongly threatened not only by atmospheric pollution but also by climatic change scenarios in warm and semiarid places.

The Effect of Atmospheric Pollution on Building Materials in the Urban Environment

Nowadays atmospheric pollution affects not only the urban environment in general, but building materials, which leads to their corrosion, in particular. The article discusses the regularities of the adhesion process of particulate matter (dust) on the vertical surfaces of buildings and structures, which are made of various building materials. On the basis of experimental studies, regression dependences of the adhesion of urban dust on different vertical surfaces from random determining factors were obtained. Thus, by studying the regularities of pollution of urban environment objects, made of various building materials, it is possible to achieve their preservation, since they demonstrate the architectural and design features of various historical periods of the country's development.

Moss (Hypnum amabile) as biomonitor of genotoxic damage and as bioaccumulator of atmospheric pollutants at five different sites of Mexico City and metropolitan area.

Mexico City has been classified as one megacity, its altitude, thermal inversions, and high seasonal radiation are factors that prevent dispersion of pollutants, which effects are detrimental to health. Therefore, it is important to have an organism that allows evaluate the damage caused by such exposure, as is the case of mosses that obtain nutrients from the atmosphere; this property makes them excellent biomonitors to evaluate genotoxic damage caused by exposure to pollutants, in addition to its large accumulation capacity. For these reasons and to relate the effects of atmospheric pollution with a biological response, we propose to use the moss Hypnum amabile as a bioaccumulator of atmospheric pollutants and biomonitor of the genotoxic effect that the air pollution can induce it through the comet assay. Mosses were placed in five localities of Mexico City and the metropolitan area on the first days of each month of the dry (cold and warm) and rainy seasons, with a 30-day exposure, after which they were changed for a new sample (for 8 months). Each month, the moss exposed was collected and nuclei were isolated to perform comet assay. To demonstrate heavy metal bioaccumulation capacity, samples were observed in a transmission electron microscope and qualitative microanalysis by scanning electron microscopy was carried out parallel. The chemical analysis detected 14 heavy metals by mass spectrometry method with inductively coupled plasma source. Additionally, 22 polycyclic aromatic hydrocarbons were also determined by gas chromatography-mass spectrometry. Analysis of variance and Kruskal-Wallis test were performed to compare DNA damage of each station against control, which was maintained in the laboratory in a chamber with filtered air. This is the first study on the genotoxicity of mosses exposed to the atmosphere of Mexico City and metropolitan area that in addition to proving their accumulation capacity shows their ability to respond to atmospheric pollutants.

Assessment of the effects of atmospheric pollutants using the animal model Caenorhabditis elegans

Air pollution is recognized as the world's largest environmental health risk. In this work we evaluated in vivo the effects of three relevant components of atmospheric dusts (brake dust, wood pellet ash and Saharan dust) employing the animal model Caenorhabditis elegans. Main endpoints of C. elegans such as life span, brood size and oxidative stress were addressed by exposing the nematodes to different dust concentrations. Brake dust and pellet ash affected the life span and increased significantly the oxidative stress of exposed nematodes, while Saharan dust showed no effects. Water soluble and insoluble fractions of these dusts were used to investigate the impact of the single fraction on C. elegans. The two fractions of brake dust and pellet ash exerted different effects on C. elegans endpoints in terms of life span and oxidative stress response. These fractions acted in different ways on the worm susceptibility to infection of two human pathogens (Staphylococcus aureus and Pseudomonas aeruginosa) affecting the sek-1 gene expression. In conclusion, our study showed that C. elegans is a valuable tool to investigate in vivo possible effects of atmospheric dusts.

Mathematical model of determining a risk to the human health along with the detection of hazardous states of urban atmosphere pollution based on measuring the current concentrations of pollutants

A mathematical model of joint determining the risk to human health and the identification of hazardous states of the polluted urban atmosphere based on the measurement of current concentrations of pollutants was developed. The structure of the model includes two structural units. The input data for structural units are the results of measuring current concentrations of atmospheric pollutants at a checkpoint. The current risk to human health is calculated in the first unit, and recurrent states of atmosphere for early detection of dangerous pollution levels are determined in the second unit. A distinctive feature of the model is the use of only measurements of current concentrations of pollutants in the atmosphere at a control point. Meteorological or other information is not used. That is why the developed model is universal and can be used in any weather conditions and peculiarities of the urban infrastructure. The operation efficiency of the proposed model was tested experimentally using the example of measuring current concentrations of formaldehyde, nitrogen dioxide, and ammonia in the atmosphere of the typical urban infrastructure. It was established that the developed model makes it possible to determine the risk of immediate toxic effects and chronic intoxication for humans, caused by atmospheric pollution. It was proved experimentally that the proposed model makes it possible, together with the identification of relevant risks to human health, to detect hazardous states of the polluted atmosphere, in which pollutants are usually accumulated. It was established that determining the current probability of recurrent conditions of the polluted atmosphere makes it possible with various reliability degrees to detect the possible occurrence of negative effects of atmospheric pollution on human health 6–12 hours beforehand

Long‐term vegetation changes in Nardus grasslands indicate eutrophication, recovery from acidification, and management change as the main drivers

AbstractQuestionsWhich trends and patterns of community change occurred in Nardus grasslands over recent decades in parts of the Continental biogeographic region of Germany? Are patterns and trends consistent across two study regions? Do impacts of environmental changes on Nardus grasslands in Central Europe correspond to those identified in the European Atlantic biogeographic region?LocationEast Hesse Highlands, Germany.MethodsIn 2012–2015, we re‐surveyed quasi‐permanent plots that had been initially surveyed between 1971 and 1987, and re‐measured soil parameters. We tested for differences in species frequency and cover, mean Ellenberg indicator values, species richness, and soil variables. Nitrogen and sulphur deposition data were analysed to evaluate possible effects of atmospheric pollutants. We used regression and redundancy analyses to identify environmental drivers responsible for changes in species composition.ResultsAcross regions, we found significant increases in soil pH, Ellenberg R and N indicator values, plant nutrient indicators, forbs, species of agricultural grasslands and of fallows. By contrast, the C:N ratio, Nardus grassland specialists, low‐nutrient indicators, and graminoids declined. Changes in species composition were related to changes in pH and management. There was a strong decrease in sulphur and a moderate increase in nitrogen deposition, whose local‐scale pattern did not correlate with changes in soil parameters. However, there was an effect of local NHy changes on species composition.ConclusionsThe findings indicate significant overall eutrophication, a trend towards less acidic conditions and insufficient management, which are widely consistent across our study regions and correspond to recent reports of vegetation changes and recovery from acidification in the Atlantic biogeographic region. We assume the reduced sulphur deposition during recent decades to be a major driver of these changes, combined with increased nitrogen deposition and reduced management intensity. This suggests a large‐scale validity of processes that influenced changes in Nardus grasslands of Western and Central Europe.

Hybrid Deep Learning Algorithm with Open Innovation Perspective: A Prediction Model of Asthmatic Occurrence

Due to recent advancements in industrialization, climate change and overpopulation, air pollution has become an issue of global concern and air quality is being highlighted as a social issue. Public interest and concern over respiratory health are increasing in terms of a high reliability of a healthy life or the social sustainability of human beings. Air pollution can have various adverse or deleterious effects on human health. Respiratory diseases such as asthma, the subject of this study, are especially regarded as ‘directly affected’ by air pollution. Since such pollution is derived from the combined effects of atmospheric pollutants and meteorological environmental factors, and it is not easy to estimate its influence on feasible respiratory diseases in various atmospheric environments. Previous studies have used clinical and cohort data based on relatively a small number of samples to determine how atmospheric pollutants affect diseases such as asthma. This has significant limitations in that each sample of the collections is likely to produce inconsistent results and it is difficult to attempt the experiments and studies other than by those in the medical profession. This study mainly focuses on predicting the actual asthmatic occurrence while utilizing and analyzing the data on both the atmospheric and meteorological environment officially released by the government. We used one of the advanced analytic models, often referred to as the vector autoregressive model (VAR), which traditionally has an advantage in multivariate time-series analysis to verify that each variable has a significant causal effect on the asthmatic occurrence. Next, the VAR model was applied to a deep learning algorithm to find a prediction model optimized for the prediction of asthmatic occurrence. The average error rate of the hybrid deep neural network (DNN) model was numerically verified to be about 8.17%, indicating better performance than other time-series algorithms. The proposed model can help streamline the national health and medical insurance system and health budget management in South Korea much more effectively. It can also provide efficiency in the deployment and management of the supply and demand of medical personnel in hospitals. In addition, it can contribute to the promotion of national health, enabling advance alerts of the risk of outbreaks by the atmospheric environment for chronic asthma patients. Furthermore, the theoretical methodologies, experimental results and implications of this study will be able to contribute to our current issues of global change and development in that the meteorological and environmental data-driven, deep-learning prediction model proposed hereby would put forward a macroscopic directionality which leads to sustainable public health and sustainability science.