ARIMA forecasting of ambient air pollutants (O3, NO, NO2 and CO)

In the present study, a stationary stochastic ARMA/ARIMA [Autoregressive Moving (Integrated) Average] modelling approach has been adapted to forecast daily mean ambient air pollutants (O₃, CO, NO and NO₂) concentration at an urban traffic site (ITO) of Delhi, India. Suitable variance stabilizing transformation has been applied to each time series in order to make them covariance stationary in a consistent way. A combination of different information-criterions, namely, AIC (Akaike Information Criterion), HIC (Hannon–Quinn Information Criterion), BIC (Bayesian Information criterion), and FPE (Final Prediction Error) in addition to ACF (autocorrelation function) and PACF (partial autocorrelation function) inspection, has been tried out to obtain suitable orders of autoregressive (p) and moving average (q) parameters for the ARMA(p,q)/ARIMA(p,d,q) models. Forecasting performance of the selected ARMA(p,q)/ARIMA(p,d,q) models has been evaluated on the basis of MAPE (mean absolute percentage error), MAE (mean absolute error) and RMSE (root mean square error) indicators. For 20 out of sample forecasts, one step (i.e., one day) ahead MAPE for CO, NO₂, NO and O₃, have been found to be 13.6, 12.1, 21.8 and 24.1%, respectively. Given the stochastic nature of air pollutants data and in the light of earlier reported studies regarding air pollutants forecasts, the forecasting performance of the present approach is satisfactory and the suggested forecasting procedure can be effectively utilized for short term air quality forewarning purposes.     

Irregularity analysis of CO,NO2 and O3 concentrations at traffic,commercial and low activity sites in Delhi

The irregularity analysis of exceedance time series of gaseous pollutants CO, NO₂ and O₃ is carried out using Shannon entropy and Fisher information measure. The data observed during 2007–2010 at three sites with different land-use activities in Delhi are analyzed. CO and NO₂ showed irregular behavior at both, low anthropogenic activity and commercial activity sites, whereas at traffic site both the pollutant concentrations showed regular behavior. The irregularity is attributed to the multiplicity in emission sources at low activity and commercial site and regular behavior is observed due to the uniformity and well defined source characteristics at the traffic site. O₃ at three sites showed irregular behavior owing to its secondary nature. Fisher–Shannon information plane showed the grouping of three pollutants except CO and NO₂ at traffic and O₃ at low activity site suggesting the similar temporal characteristics of the pollutants even at the sites with different land-use activities.     

Investigating Correlations and Variations of Air Pollutant Concentrations under Conditions of Rapid Industrialization – Kocaeli (1987–2009)

In this study, it was aimed to characterize temporal variations of air pollutants for determining contribution to pollution episodes and to obtain correlations between these pollutants. With this aim we used data analysis for measured sulfur dioxide (SO₂), particulate matter (PM, black fume and PM10), nitrogen oxides (NO_x), ozone (O₃), carbon monoxide (CO), methane (CH₄), and non‐methane hydrocarbons (NMHC) recorded in Kocaeli, one of the most industrilizated cities of Turkey. Pollutant concentrations were the results of continuous and semi‐automatic measurements. Semi‐automatic measurements of SO₂ and PM (black fume) were enclosing period from 1987 to 2008 whereas continuous monitoring of all pollutants included years of 2007–2009. In the first stage of the study daily, monthly, annual, and seasonal variations of pollution were researched. Annual average concentrations were compared with limits set by Air Quality Protection Regulation (AQPR), Air Quality Evaluation and Management Regulation (AQEMR), World Health Organization (WHO), European Union (EU), and National Ambient Air Quality Standards (USEPA). In the following stage relationships between pollutants such as NO₂–O₃, NO_x–CO, NO_x–NMHC, and NO_x–SO₂ were investigated and correlation coefficients were determined as 0.87, 0.56, 0.51, and 0.69, respectively. R² values of regression models developed from these correlations were 0.78, 0.56, 0.34, and 0.72, respectively. Vehicle density of the traffic was evaluated with NO_x–O₃ emissions and decrease was seen in NO_x emissions due to decreasing vehicle density at weekends whereas O₃ concentrations increased. These correlations enable prediction of the parameters that cannot be measured which is important for providing improvement in early warning systems.     

Time series analysis and forecasting for air pollution in small urban area: an SARIMA and factor analysis approach

Despite the existing public and government measures for monitoring and control of air quality in Bulgaria, in many regions, including typical and most numerous small towns, air quality is not satisfactory. In this paper, factor analysis and Box–Jenkins methodology are applied to examine concentrations of primary air pollutants such as NO, NO₂, NO_x, PM10, SO₂ and ground level O₃ in the town of Blagoevgrad, Bulgaria within a 1 year period from 1st September 2011 to 31st August 2012, based on hourly measurements. By using factor analysis with PCA and Promax rotation, a high multicollinearity between the six pollutants has been detected. The pollutants were grouped in three factors and the degree of contribution of the factors to the overall pollution was determined. This was interpreted as the presence of common sources of pollution. The main part of the study involves the performance of time series analysis and the development of univariate stochastic seasonal autoregressive integrated moving average (ARIMA) models with recording on a hourly basis as seasonality. The study also incorporates the Yeo–Johnson power transformation for variance stabilizing of the data and model selection by using Bayersian information criterion. The obtained SARIMA models demonstrated very good fitting performance with regard to the observed air pollutants and short-term predictions for 72 h ahead, in particular in the case of ozone and particulate matter PM10. The presented statistical approaches allow the building of non-complex models, effective for short-term air pollution forecasting and useful for advance warning purposes in urban areas.     

Part Load Performance and Emission Improvement of Direct Injection Diesel Engine through Porous Medium Combustion Technique

Diesel engines are being extensively used in the transport sector owing to their excellent fuel efficiency, low emissions of carbon dioxide, unburned hydrocarbons and carbon monoxide. However, high emissions of nitrogen oxides (NO_x) and particulate matter (PM) place diesel engines on the down side. It is extremely complex to reduce both emissions at the same time, because of the trade‐off between NO_x and PM emissions. Even though the implementation of high pressure injection and common rail system could reduce both NO_x and PM emissions together, the cost involved would be high and unaffordable for many engine producers and consumers. In this research work, a new combustion technique termed, porous medium combustion, has been proven to be a proficient technique in reducing both NO_x and PM emissions from the direct injection diesel engines. However, the NO_x and PM emissions were found to be higher than the conventional engine at low range of part loads.     

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi-Natural Experiment

In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM₁₀ (27%), PM_2.5 (19%), NO₂ (74%), SO₂ (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m⁻³ in PM₁₀, 23 µg m⁻³ in PM_2.5, 14 µg m⁻³ in NO₂, 2 µg m⁻³ in SO₂, and 0.7 mg m⁻³ in CO can be achieved.     

Interannual variability of tropospheric NO2 column over central Europe — observations from SCIAMACHY and GEM-AQ model simulations

Spatial and temporal variability of NO₂ tropospheric column over Europe was analyzed for a 3 year period (2008–2010) based on monthly average observations from SCIAMACHY and the GEM-AQ model results. The GEM-AQ model was run in a global variable configuration with a resolution of ～15 km over Central Europe. Spatial averaged time series were calculated for two selected regions in Western and Central Europe in order to assess the seasonal and interannual variability of the tropospheric NO₂. The spatial pattern is similar near large emission sources for consecutive years. However, in remote regions there are differences due to interannual variability of meteorological conditions. Highest tropospheric NO₂ column values (over 150 × 10¹⁵ molecules/cm²) were persistent over the Benelux and over most of the European agglomerations. The general agreement between modelled and observed NO₂ column is good. In the remote areas, the modelled NO₂ column shows weaker gradients than the observed field.     

Analysis of particulate matter concentrations in mazovia region, central poland, based on 2007–2010 data

Measurement results of PM10 (particulate matter with diameters below 10 μm) concentrations performed at four stations in central Poland (2007–2010) were analyzed in terms of levels and distributions of concentrations, the number of exceedances of the limit values and the causes of these exceedances. PM10 levels were similar at suburban and rural stations, except of one station located in the vicinity of a busy street. The median of PM10 concentration ranged from 26 μg/m³ at suburban station to 44 μg/m³ at Warsaw Kerb station. Seasonal variability analysis of PM10 concentration revealed an additional maximum beyond the usual autumn-winter one. This maximum occurred in April at all stations, and corresponded to seasonal wildfires activity and dust activation in Eastern Europe. Cluster analysis of back-trajectories revealed that PM10 concentrations depend on the direction of advection of the incoming air; the highest values are registered for air of regional and southern origins, while the lowest are for the airmasses coming from the north and northwest direction.     

Simulating the global transport of nitrogen oxides emissions from aircraft

With the atmosphere general circulation model ECHAM the passive transport of NO_x emitted from global subsonic air traffic and the NO_x concentration change due to these emissions are investigated. The source of NO_x is prescribed according to an aircraft emission data base. The sink of NO_x is parameterized as an exponential decay process with globally constant lifetime. Simulations in perpetual January and July modes are performed. Both the resulting mean and the standard deviation of the NO_x mass mixing ratio are analysed. In January horizontal dispersion is more pronounced and vertical mixing is smaller than in July. In both cases the resulting quasi-stationary fields of the mass mixing ratio display a pronounced zonal asymmetry. The variability accounts up to 30% of the mean field.     

Wheat straw burning and its associated impacts on Beijing air quality

Based on MODIS images, large-scale flow field charts and environmental monitoring data, we thor- oughly analyzed the spatial distribution of wheat straw burning in North China, with focus on its envi- ronmental impacts on the air quality of Beijing and pollution transport paths. And we anatomized changes of air quality in Beijing under the impacts of pollution generated by wheat straw burning around. The results indicate that: (1) The North China Plain, a winter-wheat growing area, is the main source of pollutants induced by wheat straw burning in Beijing. The direction of south-west is the dominant heavy pollution transport path. (2) Impacts of wheat straw burning on air quality are mainly manifested by significantly increasing CO concentration. (3) Precursors of O3 generated by wheat straw burning, combining with favorable meteorological conditions, can induce increasing O3 concentration greatly. NO concentration will be greatly increased due to decreasing O3 concentration at night. (4) Atmospheric particles, especially the fine ones, from wheat straw burning exert considerable influ- ence on Beijing air quality. (5) Different contributions of wheat straw burning to pollutants are identified. Ratios of PM10/SO2, CO/SO2, etc., can be applied to indicate pollution extent of wheat straw burning. High ratios of PM10/SO2 and CO/SO2 show that the air quality was heavily impacted by wheat straw burning and these ratios can be employed as indicators of contribution of wheat straw burning to the degradation of Beijing air quality. (6) Randomness of wheat straw burning activities renders random outbreak of air pollution of this type. Regional and extensive wheat straw burning activities can cause serious air pollution event.     

Estimation of PM<Subscript>10</Subscript> concentration from air quality data in the vicinity of a major steelworks site in the metropolitan area of Avilés (Northern Spain) using machine learning techniques

Atmospheric particulate matter (PM) is one of the pollutants that may have a significant impact on human health. Data collected over 7 years from the air quality monitoring station at the LD-III steelworks, belonging to the Arcelor-Mittal Steel Company, located in the metropolitan area of Avilés (Principality of Asturias, Northern Spain), is analyzed using four different mathematical models: vector autoregressive moving-average, autoregressive integrated moving-average (ARIMA), multilayer perceptron neural networks and support vector machines with regression. Measured monthly, the average concentration of pollutants (SO₂, NO and NO₂) and PM₁₀ (particles with a diameter less than ?10 μm) is used as input to forecast the monthly average concentration of PM₁₀ from one to 7 months ahead. Simulations showed that the ARIMA model performs better than the other models when forecasting 1 month ahead, while in the forecast from one to 9 months ahead the best performance is given by the support vector regression.     

Assessment of the Kraków inhabitants’ health risk caused by the exposure to inhalation of outdoor air contaminants

Health risk associated with the exposure to the polluted atmospheric air inhalation was estimated for the residents of Kraków, Poland. The air pollution concentration data were obtained from the air-quality monitoring system of the city in 2007–2016. The carcinogenic risk of the studied subpopulations was not acceptable under the formula of C₆H₆ > BaP > As(PM10) > Cd(PM10) > Pb(PM10) > Ni(PM10). The total carcinogenic risk (Rt) amounted to 3.04E?04 for children, 2.22E?04 for infants, 1.45E?04 for women, and 1.22E?04 for men. The same risk was calculated for the top three locations of the monitoring stations in this respect, within the city of Kraków: Kurdwanów Housing Estate, Nowa Huta district, and Krasińskiego Av. Non-carcinogenic risk in the case of all six monitoring stations and in respect of all the studied subpopulations, resulting from the exposure to PM10 and for NO₂ for all stations in case of children and infants, as well as, for adults at Krasińskiego Av. and Dietla Str. stations was rated medium. For C₆H₆ in the case of adults, children, and infants the risk was rated low. The total risk (HI) of non-carcinogenic pollution was rated medium and ranged as follows: 6.53 for children, 4.70 for infants, 3.19 for women, and 2.67 for men. That type of risk was decreasing at the station locations as follows: Krasińskiego Av. > Dietla Str. > Nowa Huta district > Kurdwanów Housing Estate > Z?oty Róg Str. > Piastów Housing Estate.     

Evaluation and potential improvements of WRF/CMAQ in simulating multi-levels air pollution in megacity Shanghai,China

The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO₂ (from 2 to 14%) and for PM₁₀ (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO₂ in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO₂ and 19% for NO₂ decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future.     

An empirical analysis of the impact of a bus rapid transit system on the concentration of secondary pollutants in the roadside areas of the TransJakarta corridors

A bus rapid transit (BRT) system began operation in Jakarta City, Indonesia, in January 2004 and led to a modal shift from private to public modes of transport. This modal shift from car and motorcycle to BRT reduced the emission intensity of primary pollutants, such as NO_x and CO. We applied a combined structural equation model and an artificial neural network to evaluate the impact of the BRT system on the concentration of secondary pollutants in the roadside areas in the BRT corridors. An empirical analysis was carried out using data collected at five continuous ambient air quality monitoring stations located near to the BRT TransJakarta corridors in 2005. The establishment of our structural equation model gives a better understanding of the cause–effect relationship among the factors influencing roadside ambient air pollution, and was useful in simplifying the complexity of our artificial neural network model for predicting the modal shift’s impact on the PM₁₀ values and concentration of O₃. The introduction of the BRT system, and the modal shift it produced, had a greater influence on rapidly decaying pollutants, such as PM₁₀, than on O₃ because of the exposure to near-source microenvironments, such as the roadside of the TransJakarta corridors.     

Role of Nitrogen Oxides,Black Carbon,and Meteorological Parameters on the Variation of Surface Ozone Levels at a Tropical Urban Site – Hyderabad,India

In this study, temporal variations of surface ozone (O₃) were investigated at tropical urban site of Hyderabad during the year 2009. O₃, oxides of nitrogen (NO_x = NO + NO₂), black carbon (BC), and meteorological parameters were continuously monitored at the established air monitoring station. Results revealed the production of surface O₃ from NO₂ through photochemical oxidation. Averaged datasets illustrated the variations in ground‐level concentrations of these air pollutants along different time scales. Maximum mean concentrations of O₃ (56.75 ppbv) and NO_x (8.9 ppbv) were observed in summer. Diurnal‐seasonal changes in surface O₃ and NO_x concentrations were explicated with complex atmospheric chemistry, boundary layer dynamics, and local meteorology. In addition, nocturnal chemistry of NO_x played a decisive role in the formation of O₃ during day time. Mean BC mass concentration in winter (10.92 µg m^?3) was high during morning hours. Heterogeneous chemistry of BC on O₃ destruction and NO_x formation was elucidated. Apart from these local observations, long‐range transport of trace gases and BC aerosols were evidenced from air mass back trajectories. Further, statistical modeling was performed to predict O₃ using multi‐linear regression method, which resulted in 91% of the overall variance.     

Studies of the vertical distribution of atmospheric ozone in association with western disturbances over India

A series of ozone soundings were made at New Delhi (77°E 28°N) from 21 to 30 January 1969 and 10 to 22 February 1972 to study the changes in the vertical distribution of atmospheric ozone associated with western disturbances. The sonde used was the Indian ozonesonde made in the Instruments Laboratories at Poona.In February 1972, two western disturbances moved eastwards in quick succession across the western Himalayas, the first between the 11th and 13th and the second between the 13th and 15th. Associated with the first tropospheric trough was a high-speed jet stream with wind speeds reaching 180 knots, when the tropopause descended to 304 mb over Delhi. The second trough had no high-speed jet associated with it and the tropopause was at 227 mb. Ozone maxima were observed at 350, 180 and 125 mb in addition to the main peak at 35 mb in association with the upper tropospheric troughs over Delhi and its neighbourhood. A similar lowering of the tropopause and the influx of ozone in shallow layers was observed during the passage of two upper air troughs in January 1969. The study shows that with the approach of upper tropospheric troughs and the simultaneous lowering of the tropopause there is an increased influx in shallow layers of middle latitude ozone-rich air through breaks in the tropopause, replacing the subropical ozone-poor air over the station.     

Dependence of air pollution on meteorological conditions based on magnetic susceptibility measurements: a case study from Warsaw

This study reports systematic analysis of air pollution concentration by particulate matter (PM) in relation to annual changes of metrological conditions. The concentration of PM collected on filters was evaluated by magnetic properties. Long series of filters collected during 1977, 1980, 1981 and 1985 in Warsaw have been used for measurement. Such long time series allowed a better determination of correlation between seasonal susceptibility changes and meteorological conditions and to verify the repeatability of annual behavior. The magnetic susceptibility normalized by mass (??) has been used as a proxy of pollution. Monthly variations of ?? (??_m) demonstrated slow and small seasonal changes disturbed by quick, high peaks. The filters with high susceptibilities contain a mixture of magnetic single and multidomain grains which is characteristic for anthropogenic pollution, with the frequency-dependent susceptibility ??_fd being less than 4%. The low susceptibility samples are characterized by admixture of small amount of pseudo-single domain (PSD) and possible small amount of superparamagnetic (SP) grains. Detailed analysis of reduced mean monthly susceptibility ??_R revealed that temperature and absolute humidity correlate positively in cold period of year and negatively in warm months. The linear correlation coefficients range from 0.7 to 0.9 and from 0.3 to 0.4 for negative and positive linear correlation, respectively. The dispersion of pollutants in a city depends on the way of ventilation. The big cities like Warsaw are urban heat islands which act the most effective way for the warm period and for the cold time. The correlation of ??_R with absolute humidity is similar to that for temperature but for different reasons. The presence of big amount of water vapor particles in the atmosphere can favor the adhesion of smaller ferromagnetic grains to their surface which can accelerate the process of falling down of such agglomerates. Such a process can take place during wintertime. We do not observe clear correlation between ??_R and precipitation.     

Ozone and temperature changes in the lower stratosphere

The vertical profiles of ozone and temperature from a series of balloon soundings at Delhi (28°N), Poona (18°N) and Trivandrum (8°N) were studied with synoptic meteorological data. While both ozone and temperature profiles show similar variations over all three stations, ozone maxima being always associated with thermally stable layers, the variations are most pronounced over Delhi, particularly in winter and in early spring when a series of western disturbances pass over north India. Both ozone and temperature profiles over Delhi show a layer structure characterized by a series of maxima and minima in both the vertical distribution of ozone and temperature and these are most pronounced in the lower stratosphere. These variations are associated with the influx of ozone-rich middle latitude stratospheric air over Delhi replacing subtropical air.     

Spatial character of the gaseous and particulate state compound correlation of urban atmospheric pollution in winter and summer

The spatial/temporal variation information of atmospheric dynamic-chemical processes at observation site points of the "canopy" boundary of Beijing urban building ensemble and over urban area "surface", as well as the seasonal correlation structure of the gaseous and particulate states of urban atmospheric pollution (UAP) and its seasonal conversion feature at observation points are investigated, using the comprehensive observation data of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter and summer 2003 with a "point-surface" combined research approach. By using "one dimension spatial empirical orthogonal function (EOF)" principal component analysis (PCA) mode, the seasonal change of gaseous and particulate states of atmospheric aerosols and the association feature of pollutant species under the background of the complicated structure of urban boundary layer (UBL) are analyzed. The comprehensive analyses of the principal components of particle concentrations,gaseous pollutant species, and meteorological conditions reveal the seasonal changes of the complex constituent and structure features of the gaseous and particulate states of UAP to further trace the impact feature of urban aerosol pollution surface sources and the seasonal difference of the component structure of UAP. Research results suggest that in the temporal evolution of the gaseous and particulate states of winter/summer UAP, NOx, CO, and SO2 showed an "in-phase" evolution feature, however, O3 showed an "inverse-phase" relation with other species,all possessing distinctive dependent feature. On the whole, summer concentrations of gaseous pollutants CO, SO2, and NOx were obviously lower than winter ones, especially, the reduction in CO concentration was most distinctive, and ones in SO2 and NOx were next. However, the summer O3 concentration was more than twice winter one. Winter/summer differences in PM10and PM2.5 particle concentrations were relatively not obvious, which indicates that responses of PM10 and PM2.5 particle concentrations to the difference of winter/summer heating period emission sources are far less distinctive than those of NOx, SO2, and CO. The correlation feature of winter/summer gaseous and particulate states depicts that both PM10 and PM2.5 particles were significantly correlated with NOx, and their correlations with NOx are more significant than those with other pollutants. Through PCA, it is found that there was a distinctive difference in the principal component combination structure of winter/summer PM10 and PM2.5 particles: SO2 and NOx dominated in the principal component of winter PM10 and PM2.5 particles; while CO and NOx played the major role in the principal component of summer PM10 and PM2.5 particles. For winter/summer PM10 and PM2.5 particles, there might exist the gaseous and particulate states correlation structures of different "combinations" of such dependent pollutant species. Research results also uncover that the interaction processes of gaseous and particulate states were also related with the vertical structure of UBL, that is to say, the low value layer of UBL O3 concentration was associated with the collocation of atmospheric vertical structures of the low level inversion,inverse humidity, and small wind, which depicts summer boundary layer atmospheric character, i.e.the compound impact of the dependent factor "combination" of wind, temperature, and humidity elements and their collocation structure on the variations of different gaseous pollutant concentrations. Such a depth structure of the extremely low value of O3 concentration in the UBL accords with its "inverse-phase" relation with other gaseous pollutant species. The PCA of meteorological factors associated with PM10 and PM2.5 concentrations also reveals the sensitivity of PM10 and PM2.5 concentration to the combinatory feature of local meteorological conditions.     

Observations on the Abiotic Factors and Planktonic Periodicity in a Shallow Pond of the Highlands of Shillong (India)

The pond, situated at an altitude of 4862 m, shows an annual variation of temperature between 15 and 27 °C in a close correlation with the air temperature. In the case of a weakly acidic reaction of water an inverse relation exists between pH and conductivity and between free CO₂ and alkalinity. The nutrient content of 0.05 mg/l PO₄-P and NO₃-N each is low, the phosphorus concentration being maintained by re-solution from the sediment. Chlorophyceae and diatoms are dominant in the phytoplankton alternately, and rotatoria and copepoda are dominant in the zoo-plankton in winter and in summer, respectively. The pronounced changes in the composition of plankton do not show any definite dependence on the physico-chemical factors, particularly since a significant share of the nutrient metabolism and the oxygen balance in the pond investigated is determined by macrophytes.