scholarly journals On the Estimation of Trends in Annual Rainfall Using Paired Gauge Observations

2008 ◽  
Vol 47 (6) ◽  
pp. 1814-1818 ◽  
Author(s):  
Nathan Paldor
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Opposite Sign ◽  
Annual Rainfall ◽  
Trend Line ◽  
Rainfall Variation ◽  
Natural Rainfall ◽  
High Degree ◽  
The Impact ◽  
Best Fit

Abstract A method was recently proposed for evaluating the impact of a perturbation, such as air pollution or urbanization, on the precipitation at a location by calculating the ratio between the precipitation at the perturbed location and that at a location believed to be unperturbed. However, this method may be inappropriate because of the high degree of variability of precipitation at each of the stations. To explore the validity of this approach, noisy annual rainfall records are generated numerically in an upwind, unperturbed station and in a downwind, perturbed station, and the time series of ratio between the annual rainfalls in the two stations is analyzed. The noisy rainfall records are 50 yr long, and the imposed trend for the downwind, perturbed station is −2 mm yr−1 while at the upwind station the variations in annual rainfall are purely noisy. Many pairs of noisy rainfall records are numerically generated (each pair constitutes an experiment), and in every experiment the slope of the linear best fit to the rainfall ratio yields an estimate of the trend of rainfall at the perturbed station. In the absence of noise, the trend of the rainfall ratio is explicitly related to the trend of rainfall at the perturbed station, but the natural rainfall variation at the stations completely masks this explicit relationship. The results show that in some experiments the trend line of the rainfall ratio has the opposite sign to the imposed trend and that in only about one-half of the experiments does the ratio’s trend line lie within ±75% of the imposed trend. Trend estimates within ±25% of the imposed trend are obtained in less than one-quarter of the experiments. This result casts doubt on the generality and validity of using trends of rainfall ratio between two stations to estimate trends of precipitation in one of these stations.

scholarly journals THE IMPACT OF COVID-19 QUARANTINE MEASURES ON THE LEVEL OF AIR POLLUTION IN THE SHCHUCHINSK-BOROVSKAYA RESORT AREA

2021 ◽  
Author(s):  
Maikanov Balgabay ◽  
Auteleeva Laura
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Sulfur Dioxide ◽  
Maximum Permissible Concentration ◽  
Atmospheric Air ◽  
Standard Index ◽  
High Degree ◽  
The Impact ◽  
Very High

In this study, changes in air quality were quantified before and during the introduction of COVID-19 quarantine measures in the Shchuchinsk-Borovskaya resort area. During 2020, there were only 49 resolutions "On strengthening restrictive quarantine measures in the territory of the Akmola region"on the territory of the resort zone. The maximum permissible concentration of sulfur dioxide in the atmospheric air has been exceeded. We have revealed that in the entire territory of the resort area for 2018-2019. atmospheric air pollution, according to the standard index, was elevated and high (3.38 to 6.4), according to the highest frequency (16.6 to 100%), there was a very high degree of pollution, and in 2020, the indicators of the standard index and the highest frequency were within the norm.

scholarly journals Statistical analysis of rainfall and streamflow time series in the Lake Tana Basin, Ethiopia

2018 ◽  
Vol 11 (1) ◽  
pp. 258-273 ◽  
Author(s):  
Tibebe B. Tigabu ◽  
Georg Hörmann ◽  
Paul D. Wagner ◽  
Nicola Fohrer
Keyword(s):  
Time Series ◽  
Water Level ◽  
Lake Water ◽  
Land Use Changes ◽  
Annual Rainfall ◽  
Lake Tana ◽  
Agricultural Water Management ◽  
Lake Water Level ◽  
Rainfall Variation ◽  
Sample Data

Abstract This research focuses on the statistical analyses of hydrometeorological time series in the basin of Lake Tana, the largest freshwater lake in Ethiopia. We used autocorrelation, cross-correlation, Mann–Kendall, and Tukey multiple mean comparison tests to understand the spatiotemporal variation of the hydrometeorological data in the period from 1960 to 2015. Our results show that mean annual streamflow and the lake water level are varying significantly from decade to decade, whereas the mean annual rainfall variation is not significant. The decadal mean of the lake outflow and the lake water level decreased between the 1990s and 2000s by 11.34 m3/s and 0.35 m, respectively. The autocorrelation for both rainfall and streamflow were significantly different from zero, indicating that the sample data are non-random. Changes in streamflow and lake water level are linked to land use changes. Improvements in agricultural water management could contribute to mitigate the decreasing trends.

scholarly journals Time Series Modeling of Air Pollution and Its Association with Season and Climate Variables in Istanbul, Turkey

2020 ◽  
Author(s):  
hazem al-najjar ◽  
Nadia Al-Rousan ◽  
Ismail A. Elhaty
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Feature Selection ◽  
Wind Speed ◽  
Air Pollutants ◽  
Time Series Modeling ◽  
Climate Variables ◽  
Different Seasons ◽  
The Impact

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using NARX method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

scholarly journals Trend analysis of rainfall using Mann-Kendall, Sen’s slope, moving average and least square techniques for Ahmednagar district of Maharashtra

2021 ◽  
Vol 17 (1) ◽  
pp. 19-25
Author(s):  
Virendra N. Barai ◽  
Rohini M. Kalunge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Moving Average ◽  
Rainfall Variability ◽  
Least Square ◽  
Annual Rainfall ◽  
Series Data ◽  
Sen’S Slope ◽  
Increasing Trend ◽  
The Impact

The long-term behaviour of rainfall is necessary to study over space with different time series viz., annual, monthly and weekly as it is one of the most significant climatic variables. Rainfall trend is an important tool which assesses the impact of climate change and provides direction to cope up with its adverse effects on the agriculture. Several studies have been performed to establish the pattern of rainfall over various time periods for different areas that can be used for better agricultural planning, water supply management, etc. Consequently, the present report, entitled “Trend analysis of rainfall in Ahmednagar district of Maharashtra,” was carried out. 13 tahsils of the district of Ahmednagar were selected to carry out trend analysis. The daily rainfall data of 33 years (1980- 2012) of all stations has been processed out study the rainfall variability. The Mann Kendall (MK) Test, Sen’s slope method, moving average method and least square method were used for analysis. The statistical analysis of whole reference time series data highlighted that July and August month contributes highest amount of rainfall at all tahsils. Regarding trend in annual rainfall, these four methods showed increasing trend at most of the tahsils whereas a decreasing trend only at Shrigonda tahsil. For monthly trend analysis, Kopargaon, Newasa, Shevgaon and Shrirampur tahsils showed an increasing trend during July. During August and September month, most of the tahsils i.e. Kopargaon, Nagar, Parner and Sangamner showed increasing trends, whereas in June, only Shrigonda tahsil showed decreasing trend.

scholarly journals Can the Target Responsibility System of Air Pollution Control Achieve a Win-Win Situation of Pollution Reduction and Efficiency Enhancement?

2022 ◽  
Vol 9 ◽  
Author(s):  
Jie Wang ◽  
Hao Xu ◽  
Jingxuan Xu
Keyword(s):  
Air Pollution ◽  
Pollution Control ◽  
Environmental Law ◽  
Pollutant Emissions ◽  
Air Pollution Control ◽  
Sample Interval ◽  
The Difference ◽  
High Degree ◽  
The Impact ◽  
Responsibility System

Whether the environmental target responsibility system, a typical mandatory environmental regulation, can realize the coordinated development of environmental protection and economic growth has attracted widespread attention. With the difference-in-differences (DID) method, this paper utilizes a policy, “China’s Key Cities for Air Pollution Control to Meet the Standards within the Time Limit (APCMS),” as a quasi-natural experiment to empirically examine the target responsibility system of air pollution control’s effect on both firms’ pollutant emissions and their total factor productivity (TFP). The corresponding mechanisms are also investigated. The results show: 1) The policy not only significantly decreases firms’ pollutant emissions, but also improves their TFP. The results are robust to the exclusion of the impact of other policies in the same period, propensity score matching DID (PSM-DID) test, the adoption of alternative dependent variables, and altering sample interval; 2) The dynamic analysis shows that the policy effect on reducing pollutant emissions has increased over years after a lag of 2 years; 3) The policy reduces pollutant emissions mainly through stimulating the internal innovation rather than end-pipe treatment or production cuts. 4) Capital-intensive and private firms and firms in regions with a high degree of marketization or strong environmental law enforcement are found more responsive to the environmental target responsibility system.

scholarly journals Effect of socioeconomic status on the association between air pollution and mortality in Bogota, Colombia

2014 ◽  
Vol 56 (4) ◽  
pp. 371 ◽  
Author(s):  
Luis Camilo Blanco-Becerra ◽  
Víctor Miranda-Soberanis ◽  
Albino Barraza-Villarreal ◽  
Washington Junger ◽  
Magali Hurtado-Díaz ◽  
...  
Keyword(s):  
Air Pollution ◽  
Socioeconomic Status ◽  
Time Series ◽  
Particulate Matter ◽  
Ecological Study ◽  
Aerodynamic Diameter ◽  
Components Analysis ◽  
The Impact ◽  
The Relationship ◽  
Respiratory Causes

Objective. To evaluate the modification effect of socioeconomic status (SES) on the association between acute exposure to particulate matter less than 10 microns in aerodynamic diameter (PM10) and mortality in Bogota, Colombia. Materials and methods. A time-series ecological study was conducted (1998-2006). The localities of the cities were stratified using principal components analysis, creating three levels of aggregation that allowed for the evaluation of the impact of SES on the relationship between mortality and air pollution. Results. For all ages, the change in the mortality risk for all causes was 0.76% (95%CI 0.27-1.26) for SES I (low), 0.58% (95%CI 0.16-1.00) for SES II (mid) and -0.29% (95%CI -1.16-0.57) for SES III (high) per 10µg/m3 increment in the daily average of PM10 on day of death. Conclusions. The results suggest that SES significantly modifies the effect of environmental exposure to PM10 on mortality from all causes and respiratory causes.

scholarly journals Time series modeling of air pollution and its association with season and climate variables in istanbul, turkey

2020 ◽  
Author(s):  
hazem al-najjar ◽  
Nadia Al-Rousan ◽  
Ismail A. Elhaty
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Feature Selection ◽  
Air Pollutants ◽  
Time Series Modeling ◽  
Climate Variables ◽  
Different Seasons ◽  
The Impact ◽  
Nonlinear Autoregressive

Abstract Air pollution depends on seasons, wind speed, temperature, wind direction and air pressure. The effect of different seasons on air pollution is not fully addressed in the reported works. The current study investigated the impact of season on air pollutants including SO2, PM10, NO, NOX, and O3 using Nonlinear AutoregRessive network with eXogenous inputs (NARX) method. In the applied methodology, a feature selection was used with each pollutant to find the most important season(s). Afterward, six models are designed based on the feature selection to show the impact of seasons in finding the concentration of pollutants. A case study is conducted on Esenyurt which is one of the most populated and industrialized places in Istanbul to validate the proposed framework. The performance of using all of the designed models with different pollutants showed that using season effect led to improving the performance of predictor and generating high R2 and low error functions.

scholarly journals Impact of market anomalies on stock exchange: a comparative study of KSE and PSX

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Sadia Anjum
Keyword(s):  
Time Series ◽  
Serial Correlation ◽  
Stock Exchange ◽  
Weekend Effect ◽  
Market Anomalies ◽  
The Past ◽  
Lm Test ◽  
Day Of The Week ◽  
The Impact ◽  
Best Fit

AbstractThis paper serves the purpose of empirically investigating the impact of three market anomalies: day-of-the-week effect, weekend effect and monthly effect (January and July effects) on Pakistan stock market prior and after the establishment of PSX. The paper constructed multiple regression analysis employing dummy variables using least squares, ARCH and EGARCH-in-mean models. Breusch–Godfrey serial correlation LM test is used to check the serial correlation in the return series and Wald coefficient restriction test to evaluate joint significance of the dummy coefficients. However, Box–Jenkins (ARIMA) technique is used to evaluate the best fit of time series model to the past values of that time series. The results of the study reveal the highest Friday mean returns and lowest, but not negative Monday mean returns. Furthermore, the study indicates that December mean returns are high in Karachi Stock Exchange and March returns are high in the case of Pakistan Stock Exchange. This is the first study to evaluate the impact of three market anomalies prior and after the establishment of Pakistan Stock Exchange.

scholarly journals Modeling the integral risk assessment for air pollution in the areas of highways by probabilistic methods

2021 ◽  
Vol 2134 (1) ◽  
pp. 012001
Author(s):  
A.R. Shagidullin ◽  
Yu.A. Tunakova ◽  
S.V. Novikova ◽  
V.S. Valiev
Keyword(s):  
Experimental Data ◽  
Air Pollution ◽  
Road Transport ◽  
Multiple Regression Model ◽  
Probabilistic Methods ◽  
Risk Levels ◽  
The Road ◽  
Transport Component ◽  
High Degree ◽  
The Impact

Abstract A methodology for calculating the integral risk of atmospheric pollution using Bayes’s theorem is proposed to take into account the action of mobile and stationary emission sources in the influence zones of highways, the response to the impact in the form of accumulation of emission components in depositing media and biological media of the population. At the first stage, the clustering of experimental data arrays was carried out, homogeneous road sections (clusters) were identified. The integral risk was calculated for the selected clusters. The risks of contamination of the investigated media have been calculated. A multiple regression model has been built to assess the level of integral risk with a high degree of reliability when compared with experimental data. The significance of the aerogenic factor in the formation of the level of integral risk is shown. A reduced model for assessing the integral risk by the level of risk of atmospheric air pollution is proposed. Grades of risk levels are given according to the degree of acceptability. It is possible to determine the contribution of the road transport component to the level of integral risk based on the obtained values of the final risk.

Sign in / Sign up

Export Citation Format

Share Document