Highly-resolved spatial-temporal variations of air pollutants from Chinese industrial boilers

2021 ◽  
pp. 117931
Author(s):  
Yali Tong ◽  
Jiajia Gao ◽  
Kun Wang ◽  
Hong Jing ◽  
Chenlong Wang ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Temporal Variations ◽  
Industrial Boilers

scholarly journals Analysis of Temporal Variations of Air Pollutant Concentrations in Ogoni Area, Niger Delta Region, Nigeria

2021 ◽  
pp. 63-73
Author(s):  
B. Yorkor ◽  
T. G. Leton ◽  
J. N. Ugbebor
Keyword(s):  
Air Pollution ◽  
Temporal Variability ◽  
Niger Delta ◽  
Air Pollutants ◽  
Temporal Variations ◽  
Time Of Day ◽  
Air Pollutant ◽  
Pollutant Concentrations ◽  
Hourly Data ◽  
Air Pollutant Concentrations

This study investigated the temporal variations of air pollutant concentrations in Ogoni area, Niger Delta, Nigeria. The study used hourly data measured over 8 hours for 12 months at selected locations within the area. The analyses were based on time series and time variations techniques in Openair packages of R programming software. The variations of air pollutant concentrations by time of day and days of week were simulated. Hours of the day, days of the week and monthly variations were graphically simulated. Variations in the mean concentrations of air pollutants by time were determined at 95 % confidence intervals. Sulphur dioxide (SO2), Nitrogen dioxide (NO2), ground level Ozone (O3) and fine particulate matter (PM2.5) concentrations exceeded permissible standards. Air pollutant concentrations showed increase in January, February, November and December compared to other months. Simulation showed that air pollutants varied significantly by hours-of-the-day and days-of-the-week and months-of-the-year. Analysis of temporal variability revealed that air pollutant concentrations increased during weekdays and decreased during weekends. The temporal variability of air pollutants in Ogoni area showed that anthropogenic activities were the main sources of air pollution in the area, therefore further studies are required to determine air pollutant dispersion pattern and evaluation the potential sources of air pollution in the area.

scholarly journals Spatial–Temporal Variations in Atmospheric Factors Contribute to SARS-CoV-2 Outbreak

Viruses ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 588 ◽  
Author(s):  
Raffaele Fronza ◽  
Marina Lusic ◽  
Manfred Schmidt ◽  
Bojana Lucic
Keyword(s):  
Air Pollutants ◽  
Fast Rate ◽  
Temporal Variations ◽  
Surrogate Markers ◽  
Infection Frequency ◽  
The Difference ◽  
Atmospheric Factors ◽  
Particulate Matter 2.5 ◽  
Near Future ◽  
Testing Policies

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing coronavirus disease 2019 (COVID-19) has reached over five million confirmed cases worldwide, and numbers are still growing at a fast rate. Despite the wide outbreak of the infection, a remarkable asymmetry is observed in the number of cases and in the distribution of the severity of the COVID-19 symptoms in patients with respect to the countries/regions. In the early stages of a new pathogen outbreak, it is critical to understand the dynamics of the infection transmission, in order to follow contagion over time and project the epidemiological situation in the near future. While it is possible to reason that observed variation in the number and severity of cases stems from the initial number of infected individuals, the difference in the testing policies and social aspects of community transmissions, the factors that could explain high discrepancy in areas with a similar level of healthcare still remain unknown. Here, we introduce a binary classifier based on an artificial neural network that can help in explaining those differences and that can be used to support the design of containment policies. We found that SARS-CoV-2 infection frequency positively correlates with particulate air pollutants, and specifically with particulate matter 2.5 (PM2.5), while ozone gas is oppositely related with the number of infected individuals. We propose that atmospheric air pollutants could thus serve as surrogate markers to complement the infection outbreak anticipation.

scholarly journals Spatial Distribution of BTEX and Inorganic Pollutants During Summer Season in Yalova, Turkey

2017 ◽  
Vol 24 (4) ◽  
pp. 565-581
Author(s):  
Lokman Hakan Tecer ◽  
Sermin Tagil ◽  
Osman Ulukaya ◽  
Merve Ficici
Keyword(s):  
Spatial Distribution ◽  
Rural Areas ◽  
Air Pollutants ◽  
Passive Sampling ◽  
Temporal Variations ◽  
Average Concentration ◽  
Geographical Information ◽  
Moran’S I ◽  
Moran's I ◽  
Industrial Sites

Abstract The objective of this research is to determine the atmospheric concentrations and spatial distribution of benzene (B), toluene (T), ethylbenzene (E) and xylenes (X) (BTEX) and inorganic air pollutants (O3, NO2 and SO2) in the Yalova atmosphere during summer 2015. In this study, a combination of passive sampling and Geographical Information System-based geo-statistics are used with spatial statistics of autocorrelation to characterise the spatial pattern of the quality of air based on concentrations of these pollutants in Yalova. The spatial temporal variations of pollutants in the air with five types of land-use, residence, rural, highway, side road and industrial areas were investigated at 40 stations in Yalova between 7th August 2015 and 26th August 2015 using passive sampling. An inverse distance weighting interpolation technique was used to estimate variables at an unmeasured location from observed values at nearby locations. The spatial autocorrelation of air pollutants in the city was investigated using the statistical methods of Moran’s I in addition to the Getis Ord Gi. During the summer, highway and industrial sites had higher levels of BTEX then rural areas. The average concentration of toluene was measured to be 5.83 μg/m3 and this is the highest pollutant concentration. Average concentrations of NO2, O3 and SO2 are 35.64, 84.23 and 3.95 μg/m3, respectively. According to the global results of Moran’s I; NO2 and BTEX had positive correlations on a global space at a significant rate. Moreover, the autocorrelation analysis on the local space demonstrated significant hot spots on industrial sites and along the main roads.

scholarly journals Seasonal and Temporal Variations of Criteria Air Pollutants and the Influence of Meteorological Parameters on the Concentration of Pollutants in Ambient Air in Lahore, Pakistan

2016 ◽  
Vol 59 (1) ◽  
pp. 34-42
Author(s):  
Amtul Bari Tabinda ◽  
Saleha Munir ◽  
Abdullah Yasar ◽  
Asad Ilyas
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Negative Correlation ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Ambient Air ◽  
Temporal Variations ◽  
Criteria Air Pollutants ◽  
Summer Minimum ◽  
One Year

Criteria air pollutants have their significance for causing health threats and damage to theenvironment. The study was conducted to assess the seasonal and temporal variations of criteria air pollutantsand evaluating the correlations of criteria air pollutants with meteorological parameters in the city ofLahore, Pakistan for a period of one year from April 2010 to March 2011. The concentrations of criteriaair pollutants were determined at fixed monitoring stations equipped with HORIBA analyzers. The annualaverage concentrations (µg/m3) of PM2.5, O3, SO2, CO and NOx (NO+NO2) for this study period were118.94±57.46, 46.0±24.2, 39.9±8.9, 1940±1300 and 130.9±81.0 (61.8±46.2+57.3±22.19), respectively.PM2.5, SO2, CO and NOx had maximum concentrations during winter whereas O3 had maximum concentrationduring summer. Minimum concentrations of PM2.5, SO2 and NOx were found during monsoon as comparedto other seasons due to rainfall which scavenged these pollutants. The O3 showed positive correlation withtemperature and solar radiation but negative correlation with wind speed. All other criteria air pollutantsshowed negative correlation with wind speed, temperature and solar radiation. A significant (P<0.01)correlation was found between NOx and CO (r = 0.779) which showed that NOx and CO arise from commonsource that could be the vehicular emission. PM2.5 was significantly correlated (P<0.01) with NOx (r = 0.524)and CO (r = 0.519), respectively. High traffic intensity and traffic jams were responsible for increased airpollutants level especially the PM2.5, NOx and CO.

scholarly journals ANALYSIS OF NO<sub>2</sub> TROPOSPHERIC COLUMN AMOUNT AT AIRPORTS IN MALAYSIA BEFORE AND DURING COVID-19 PANDEMIC USING SENTINEL-5P TROPOMI DATA

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 399-403
Author(s):  
K. D. Kanniah ◽  
N. A. F. Kamarul Zaman ◽  
K. Perumal
Keyword(s):  
Climate Change ◽  
Human Health ◽  
Urban Areas ◽  
Air Pollutants ◽  
Temporal Variations ◽  
Data Availability ◽  
Spatial And Temporal Patterns ◽  
Movement Restriction ◽  
Motorized Vehicles ◽  
The Impact

Abstract. Air pollution is a serious environmental and health issue in Malaysia due to the recent urbanization processes. The main sources of air pollutants are motorized vehicles in urban areas and airports and industrial activities. At the airports, NO2 is the main pollutant of concern besides aerosols particles, yet gap in data availability prevent studies to describe their patterns and quantify their effects on human health and climate change. In this study NO2 data from TROPOMI sensor on board Sentinel 5-P satellite was used to characterize the spatial and temporal patterns of NO2 tropospheric column amounts at major airports in Malaysia. The results demonstrate that NO2 amounts from aircrafts and ground traffic activities are generally higher and/or similar to the amounts found in urban areas. Total tropospheric column amounts of NO2 during the movement restriction imposed due to Covid-19 pandemic between March and April 2020 was approximately 50% lower the total emission during the same period in 2019 (representing a business as usual period). Assessing the spatial pattern and temporal variations in NO2 (both surface and total vertical profile) is important for monitoring the impact of air pollutants on climate change and human health in Malaysia.

scholarly journals Impact of non-ideality on reconstructing spatial and temporal variations of aerosol acidity with multiphase buffer theory

2021 ◽  
Author(s):  
Guangjie Zheng ◽  
Hang Su ◽  
Siwen Wang ◽  
Andrea Pozzer ◽  
Yafang Cheng
Keyword(s):  
Air Pollutants ◽  
Molar Fraction ◽  
Temporal Variations ◽  
Spatial Variations ◽  
Acid Dissociation ◽  
Acid Dissociation Constant ◽  
Aerosol Acidity ◽  
Long Term Trends ◽  
Key Parameter

Abstract. Aerosol acidity is a key parameter in atmospheric aqueous chemistry and strongly influence the interactions of air pollutants and ecosystem. The recently proposed multiphase buffer theory provides a framework to reconstruct long-term trends and spatial variations of aerosol pH based on the effective acid dissociation constant of ammonia (Ka,NH3*). However, non-ideality in aerosol droplets is a major challenge limiting its broad applications. Here, we introduced a non-ideality correction factor (cni) and investigated its governing factors. We found that besides relative humidity (RH) and temperature, cni is mainly determined by the molar fraction of NO3− in aqueous-phase anions, due to different NH4+ activity coefficients between (NH4)2SO4− and NH4NO3-dominated aerosols. A parameterization method is thus proposed to estimate cni at given RH, temperature and NO3− fraction, and is validated against long-term observations and global simulations. In the ammonia-buffered regime, with cni correction the buffer theory can well reproduce the Ka,NH3* predicted by comprehensive thermodynamic models, with root-mean-square deviation ~0.1 and correlation coefficient ~1. Note that, while cni is needed to predict Ka,NH3* levels, it is usually not the dominant contributor to its variations, as ~90 % of the temporal or spatial variations in Ka,NH3* is due to variations in aerosol water and temperature.

scholarly journals Impact of non-ideality on reconstructing spatial and temporal variations in aerosol acidity with multiphase buffer theory

2022 ◽  
Vol 22 (1) ◽  
pp. 47-63
Author(s):  
Guangjie Zheng ◽  
Hang Su ◽  
Siwen Wang ◽  
Andrea Pozzer ◽  
Yafang Cheng
Keyword(s):  
Air Pollutants ◽  
Molar Fraction ◽  
Temporal Variations ◽  
Spatial Variations ◽  
Acid Dissociation ◽  
Acid Dissociation Constant ◽  
Aerosol Acidity ◽  
Long Term Trends ◽  
Key Parameter

Abstract. Aerosol acidity is a key parameter in atmospheric aqueous chemistry and strongly influences the interactions of air pollutants and the ecosystem. The recently proposed multiphase buffer theory provides a framework to reconstruct long-term trends and spatial variations in aerosol pH based on the effective acid dissociation constant of ammonia (Ka,NH3∗). However, non-ideality in aerosol droplets is a major challenge limiting its broad applications. Here, we introduced a non-ideality correction factor (cni) and investigated its governing factors. We found that besides relative humidity (RH) and temperature, cni is mainly determined by the molar fraction of NO3- in aqueous-phase anions, due to different NH4+ activity coefficients between (NH4)2SO4- and NH4NO3-dominated aerosols. A parameterization method is thus proposed to estimate cni at a given RH, temperature and NO3- fraction, and it is validated against long-term observations and global simulations. In the ammonia-buffered regime, with cni correction, the buffer theory can reproduce well the Ka,NH3∗ predicted by comprehensive thermodynamic models, with a root-mean-square deviation ∼ 0.1 and a correlation coefficient ∼ 1. Note that, while cni is needed to predict Ka,NH3∗ levels, it is usually not the dominant contributor to its variations, as ∼ 90 % of the temporal or spatial variations in Ka,NH3∗ are due to variations in aerosol water and temperature.

scholarly journals Temporal analysis of air pollutants in the most affected monsoon region

2021 ◽  
Vol 23 (1) ◽  
pp. 229
Author(s):  
Omar Kairan ◽  
Nur Nasehah Zainudin ◽  
Nurul Hasya Mohd Hanafiah ◽  
Nur Emylia Arissa Mohd Jafri ◽  
Fukayhah Fatiha @Suhami ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Air Pollutants ◽  
Monsoon Season ◽  
Secondary Data ◽  
Ambient Air ◽  
Temporal Analysis ◽  
Quality Standard ◽  
Temporal Variations ◽  
Air Pollutant

Air pollution has become an issue at all rates in the world. In Malaysia, there is a system is known as air quality index (API) used to indicate the overall air quality in the country where the air pollutants include or the new ambient air quality standard are sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particulate matter with size less than 10 (PM10). The concentration levels of the air pollutants were said to be affected by the monsoon changes. Therefore, this study is conducted to examine the existence of temporal variations of each air pollutant then identify the differences of each air pollutants concentration in temporal variations. This study uses secondary data where data that has been retrieved from the Department of Environment (DOE) where it is data of air pollution specifically for Kota Bharu, kelantan records. Hierarchical agglomerative cluster analysis was conducted to group monthly air quality. As a conclusion, the study can conclude that the five air pollutants grouped into several different monthly clusters mostly representing the two main monsoon seasons. Mostly air pollutant varied accordingly towards the monsoon season. During the southwestern monsoon, air pollutant concentration tends to higher compare to the northeastern monsoon with mostly due to meteorological factors.

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