Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.

The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w

يتنامى يوما بعد يوم استخدام السيارات وتتعاضم اعدادها ، فهذا هو عصر السرعة، وخاصة في مجال النقل والمواصلات، والتي تتحقق باستخدام وسائل النقل المختلفة ومن بينها السيارات، وبالتالي اصبحت هذه الوسيلة ضرورية لتحقيق هذه السرعة ومن ضرورات الحياة في انجاز الاعمال.

وتتبارى مصانع السيارات فيما بينها لانتاج انواع السيارات بمواصفات عالية من المتانة والامان والراحة، وفي ذات الوقت اصبحت هندسة الطرق

      Air pollution means the release of pollutants into the atmosphere, which are harmful to human health and the planet as a whole. Almost all air pollutants come from production and energy use. In the present work, an assessment of some heavy metals, natural radioactivity and the quantity of dust fallen in three sites (Tessen, Rahemawa, and Laylan) in Kirkuk Governorate, northern Iraq. Three dust samples were collected from three locations (residential, commercial and industrial areas). The collected samples were analyzed for Cd, Cr, Cu, Ni, Pb, Zn, and radioactivity (Gamma rays). The studied heavy metals (Fe, Ni, Pb, and Zn) exceeded their limits in the atmosphere due to the increase in the number of automobiles, which

The Present study investigated the drought in Iraq, by using the rainfall data which obtained from 39 meteorological stations for the past 30 years (1980-2010). The drought coefficient calculated on basis of the standard precipitation index (SPI) and then characteristics of drought magnitude, duration and intensity were analyzed. The correlation and regression between magnitude and duration of drought were obtained according the (SPI) index. The result shows that drought magnitude values were greater in the northeast region of Iraq. 

The analysis of COVID-19 data in Iraq is carried out. Data includes daily cases and deaths since the outbreak of the pandemic in Iraq on February 2020 until the 28th of June 2022. This is done by fitting some distributions to the data in order to find out the most appropriate distribution fit to both daily cases and deaths due to the COVID-19 pandemic. The statistical analysis includes estimation of the parameters, the goodness of fit tests and illustrative probability plots. It was found that the generalized extreme value and the generalized Pareto distributions may provide a good fit for the data for both daily cases and deaths. However, they were rejected by the goodness of fit test statistics due to the high variability of the data.<

Abstract :                                                                                                            

In light of the trend of the countries of t

In this research ,we will study the phenomenon of dust storms for all types
(Suspended dust , rising dust , dust storm) , and its relationship with some climate
variables (Temperature , rainfall ,wind speed , Relative humidity ) through
regression models to three different locations ( Kirkuk , Rutba , Diwaniya ) almost
covering Iraq area for the period (1981 – 2012) . Time series has been addressing the
phenomenon of storms and climate variables for the time period under study to
attain the best models for long range forcast to the dust storms.

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system