meteorological variables

The study explores the complex relationship between meteorological variables, air quality, and Coronavirus-19 pandemic events in Jakarta, emphasizing the global concern over air pollution's detrimental effects on both health and the economy. It emphasizes the correlation between climate change and exacerbating air pollution by changing weather patterns and meteorological conditions, leading to elevated levels of pollution. Additionally, the study underscores the impact of the Coronavirus-19 pandemic on air quality, with lockdowns temporarily reducing emissions but also revealing the complex interplay between climate change, agricultural practices, and air pollution spikes. The ongoing challenges in improving air quality persist despite the government's efforts, highlighting the need for a thorough understanding of the situation to inform effective policy interventions and strategies for reducing emissions.

The study analyzed key pollutants from five monitoring stations in Jakarta including particulate matter 2.5 from a Swiss air quality technology company. Meteorological data (temperature, rainfall, wind speed, humidity, and sunshine hours) were sourced from the Indonesian Agency for Meteorology, Climatology, and Geophysics for the period 2018-2021. The restriction measures and case data pertaining to the Coronavirus disease-19 were acquired from Health Office in Jakarta. Data analysis utilized Microsoft excel and statistical package for the social sciences software, with spearman correlation tests due to non-normal distribution. This empirical approach investigated the associations among air pollutants, meteorological factors, and occurrences of Coronavirus disease-19 in Jakarta, Indonesia.

Positive linear elationships were identified between the concentrations of particulate matter 10, particulate matter 2.5, carbon monoxide, and nitrogen dioxide. Conversely, a negative linear correlation was observed between carbon monoxide and ozone levels. Nonlinear correlations also existed between various pollutants. During the pandemic, carbon monoxide, nitrogen monoxide and sulphur dioxide concentrations increased, whereas particulate matter 2.5 and ozone levels decreased. Air quality parameters were generally higher in the dry season. Throughout the pandemic, the temperature and wind speed exhibited a consistent pattern, remaining stable. However, it is noteworthy that the levels of humidity and intensity of rainfall experienced a noticeable increase during this period. Particulate matter exhibited a negative correlation with both humidity and rainfall, whereas temperature displayed positive correlations. Despite improved air quality during the pandemic, the link between air pollutants, meteorological factors, and Coronavirus disease-19 transmission was unclear, with only weak correlations between air quality parameters and Coronavirus-19 related deaths. Moderate correlations were observed between specific levels of pollutants prior to and amidst the pandemic.

Based on the findings, there was a weak correlation between confirmed deaths because of Coronavirus-19 and all air quality parameters.  Nevertheless, the study showcased a more distinct association between confirmed cases of Coronavirus-19 and particular pollutants. Coronavirus-19 This study identified several key meteorological variables, including wind speed, direction, temperature, humidity, and rainfall, as significant drivers of particulate matter and sulphur dioxide concentrations. It is essential to comprehend the intricate connections among meteorological factors, air quality indicators, and occurrences of Coronavirus disease-19 in order to formulate efficient public health measures and environmental regulations aimed at safeguarding communities from the impacts of air pollution and infectious diseases.

The time series model has been exploited to estimate the relationship between meteorological variables and air in Mashhad with respiratory mortality. For this purpose, data on respiratory mortality was based on data recorded on March 2014 to 2015. In order to investigate the effect of meteorological variables and air pollution values on respiratory mortality, the Box- Jenkins time series model has been utilized. Moreover, the effect of age and seasons on the number of respiratory deaths was assessed by the linear regression and ANOVA test. The fit of the final model to determining the monthly relationship between meteorological variables and air pollutants with the number of respiratory mortalities is a (1,0,2) ARIMA. In the monthly survey, temperature and rainfall have the inverse relationship and pressure has the direct relationship with the average of 7.4, 3.2, and 17.42 on the respiratory mortality. It was also found direct relationship between the mortality from respiratory diseases and CO and O3 and inverse relationship with SO2, NO2 and PM2.5 pollutants with an average of 67.40, 17.42, 17.89, 6.83, and 0.68, respectively. Also, the results of this study indicate that older people are more likely to be affected by the inappropriate status of air quality by 0.37%. The results showed a significant difference between respiratory mortality in different seasons of the year, and the highest number of deaths occurred in the winter.