Regional Air Pollution Research Articles

The nexus between electronic commerce and environmental pollution: The roles of energy efficiency and resource consumption

AbstractThe platform economy is growing fast in the world. Its expansion, exemplified by industry giants like Amazon, Airbnb, and Uber, is reshaping societal lifestyles and commercial businesses. However, its environmental impacts are uncertain. Currently, the relationship between electronic commerce (e‐commerce) activities and environmental pollution has attracted a lot of attention. This paper attempts to construct a comprehensive theoretical model to investigate the nexus between e‐commerce and regional environmental pollution, with a particular focus on the effects of air pollution and waste pollution. Fixed effect models and China's provincial data during the period from 2008 to 2018 are employed to examine the roles of energy efficiency and resource consumption in such a nexus. The findings suggest that the development of e‐commerce is linked to a reduction in regional air pollution through the channel of improving transportation energy efficiency. The results also show that e‐commerce is associated with an increase in regional waste pollution due to the mechanism of resource consumption in the express packaging industry. As a result, the relationship between e‐commerce and environmental pollution is quite complex at the regional level, transcending a binary distinction of solely positive or negative impacts. This paper contributes to a better understanding of the complex environmental impacts of e‐commerce and helps governments design more efficient and targeted policies to reduce regional pollution.

Assessing vulnerability of densely populated areas to air pollution using Sentinel-5P imageries: a case study of the Nile Delta, Egypt

Air pollution represents one of the major environmental stressors with serious implications on human health and ecosystem health. Recently remote sensing imageries; as an alternative cost and time-effective method compared with regular monitoring techniques, were used for provision of appropriate data concerning air quality over large areas. In this context, Sentinel-5P satellite provides high-resolution images of atmospheric pollutants including nitrogen dioxide, ozone, carbon monoxide (CO) and particulate matter (PM). The current work aims to delineate vulnerability of densely populated areas in Northern-Egypt to air pollution through retrieving CO and PM2.5 from Sentinel-5P images and validate the retrieved data through simultaneous In-Situ measurements. For this purpose, our approach comprised four-step methodology; data acquisition on study area, data manipulation, validation of retrieved air quality data and mapping the vulnerability to air pollution. Based on the data retrieved from the imagery, a composite vulnerability index for each CO and PM2.5 value was developed delineating the most vulnerable areas to air pollution in the Northern Nile Delta region. Such results revealed that Sentinel-5P imagery can serve as a valuable tool for monitoring air quality and assessing vulnerability of densely populated areas to air pollution. Accordingly, it can be concluded that the applied Sentinel-5P based model can be applied effectively for other air pollutants and can be extrapolated to other areas with similar and/or different environmental settings.

Association of Short-Term Co-Exposure to Particulate Matter and Ozone with Mortality Risk.

A complex regional air pollution problem dominated by particulate matter (PM) and ozone (O3) needs drastic attention since the levels of O3 and PM are not decreasing in many parts of the world. Limited evidence is currently available regarding the association between co-exposure to PM and O3 and mortality. A multicounty time-series study was used to investigate the associations of short-term exposure to PM1, PM2.5, PM10, and O3 with daily mortality from different causes, which was based on data obtained from the Mortality Surveillance System managed by the Jiangsu Province Center for Disease Control and Prevention of China and analyzed via overdispersed generalized additive models with random-effects meta-analysis. We investigated the interactions of PM and O3 on daily mortality and calculated the mortality fractions attributable to PM and O3. Our results showed that PM1 is more strongly associated with daily mortality than PM2.5, PM10, and O3, and percent increases in daily all-cause nonaccidental, cardiovascular, and respiratory mortality were 1.37% (95% confidence interval (CI), 1.22-1.52%), 1.44% (95% CI, 1.25-1.63%), and 1.63% (95% CI, 1.25-2.01%), respectively, for a 10 μg/m3 increase in the 2 day average PM1 concentration. We found multiplicative and additive interactions of short-term co-exposure to PM and O3 on daily mortality. The risk of mortality was greatest among those with higher levels of exposure to both PM (especially PM1) and O3. Moreover, excess total and cardiovascular mortality due to PM1 exposure is highest in populations with higher O3 exposure levels. Our results highlight the importance of the collaborative governance of PM and O3, providing a scientific foundation for pertinent standards and regulatory interventions.

Spatio-temporal variation of O3 concentration and exposure risk assessment in key regions of China, 2015–2021

In recent years, the increasing Ozone (O3) concentration has become a significant concern for human life and health. In this study, O3 concentration data at 10 km resolution and population density data at 1 km resolution for China were utilized. Methods such as the Global Moran's I index, Getis-Ord Gi* index, and population exposure risk index, to analyze the spatial-temporal variation, meteorological influences, aggregation characteristics, exposure risk levels and health impact of O3 in China and six key regions from 2015 to 2021. The results revealed an increasing trend with a bimodal fluctuation pattern, peak in May and August. Only Pearl River Delta (PRD) showed the highest in autumn, five other key regions were highest O3 concentration in the summer. And the spatial autocorrelation in China is obvious among regions. Among the five meteorological factors, temperature and sunshine duration predominantly influenced O3 concentration in China. Relative humidity was the main factor affecting O3 concentration in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Sichuan Basin (SCB), while precipitation had the greatest impact on FenWei Plain (FWP) and Hexi Corridor (HXC) and exhibited a positive correlation. Wind speed in PRD showed a strong negative correlation with O3 concentration. The Ri exhibited significant differences between the eastern and western sides of the Hu Huanyong line, demonstrating a distribution pattern of "high in the east and low in the west". Through this research, we aim to provide valuable insights for public health policies and the prevention and control of regional air pollution.

The health and economic impacts of emergency measures to combat heavy air pollution

Emergency measures are effective measures that can be quickly taken in response to heavy air pollution. They not only have an obvious impact on slowing down the accumulation of particulate matter but also have a significant impact on public health and socio-economic development. Therefore, to analyze the effectiveness of emergency measures, one must assess their environmental, health and economic impacts. In this paper, we use exposure-response functions and a city-level computable general equilibrium (CGE) model to do so for China's Jing-Jin-Ji region. We find that the emergency measures implemented in 2019 significantly improve the region's air quality and enhance public health by reducing risk associated with acute bronchitis. Moreover, those emergency measures notably benefit the Jing-Jin-Ji region economically by expanding labor supply, most notably in Beijing and Tianjin. It seems Beijing and Tianjin should compensate industrial cities in Hebei, which enabled the Jing-Jin-Ji region's better air quality but encountered far fewer economic benefits. Handan, Baoding, and Cangzhou are among the cities in Hebei that are expanding employment in manufacturing and service sectors. These results can provide scientific guidance and policy suggestions for government while using emergency measures to combat regional heavy air pollution considering its health and economic benefits.

Impact of the COVID-19 outbreak on urban air, Land surface temperature and air pollution in cold climate zones

The objective of this study was to analyze air pollution and thermal environment in Turkey's cold region before, during, and after COVID-19 in 2019, 2020 and 2021. The CO, NO2, O3, PM10 and SO2 data from the state air quality stations, as well as ground air temperature data from six weather stations, and land satellite images from the USGS website using ArcGIS 10.4.1 software were collected in January, March, April and August of 2019, 2020 an 2021. In order to evaluate the impact of COVID-19 measures and restrictions on cold region cities, air pollution indicators, land surface temperature and air temperature as well as statistical data were analyzed. The results indicated that the CO, NO2, PM10 and SO2 emissions decreased by 14.9%, 14.3%, 47.1% and 28.5%, but O3 increased by 16.9%, respectively, during the COVID-19 lockdown in 2020 as compared to these of the pre-COVID-19 levels in 2019. A positive correlation between air temperature and O3 in 2019 (r2 = 0.80), and in 2020 and 2021 (r2 = 0.64) was obtained. Air temperature in 2020 and 2021 decreased due to lockdowns and quarantine measures that led to lower O3 emissions as compared to 2019. Negative correlations were also found between air temperature and NO2 (r2 = 0.60) and SO2 (r2 = 0.5). There was no correlation between air temperature and PM10. During the COVID-19 lockdown and intense restrictions in April 2020, the average LST and air temperature values dropped by 14.7 °C and 1.6 °C respectively, compared to April 2019. These findings may be beneficial for future urban planning, particularly in cold regions.

Spatial analysis of overweight prevalence in China: exploring the association with air pollution

BackgroundOverweight is a known risk factor for various chronic diseases and poses a significant threat to middle-aged and elderly adults. Previous studies have reported a strong association between overweight and air pollution. However, the spatial relationship between the two remains unclear due to the confounding effects of spatial heterogeneity.MethodsWe gathered height and weight data from the 2015 China Health and Retirement Long-term Survey (CHARLS), comprising 16,171 middle-aged and elderly individuals. We also collected regional air pollution data. We then analyzed the spatial pattern of overweight prevalence using Moran's I and Getis-Ord Gi* statistics. To quantify the explanatory power of distinct air pollutants for spatial differences in overweight prevalence across Southern and Northern China, as well as across different age groups, we utilized Geodetector's q-statistic.ResultsThe average prevalence of overweight among middle-aged and elderly individuals in each city was 67.27% and 57.39%, respectively. In general, the q-statistic in southern China was higher than that in northern China. In the north, the prevalence was significantly higher at 54.86% compared to the prevalence of 38.75% in the south. SO2 exhibited a relatively higher q-statistic in middle-aged individuals in both the north and south, while for the elderly in the south, NO2 was the most crucial factor (q = 0.24, p < 0.01). Moreover, fine particulate matter (PM2.5 and PM10) also demonstrated an important effect on overweight. Furthermore, we found that the pairwise interaction between various risk factors improved the explanatory power of the prevalence of overweight, with different effects for different age groups and regions. In northern China, the strongest interaction was found between NO2 and SO2 (q = 0.55) for middle-aged individuals and PM2.5 and SO2 (q = 0.27) for the elderly. Conversely, in southern China, middle-aged individuals demonstrated the strongest interaction between SO2 and PM10 (q = 0.60), while the elderly showed the highest interaction between NO2 and O3 (q = 0.42).ConclusionSignificant spatial heterogeneity was observed in the effects of air pollution on overweight. Specifically, air pollution in southern China was found to have a greater impact on overweight than that in northern China. And, the impact of air pollution on middle-aged individuals was more pronounced than on the elderly, with distinct pollutants demonstrating significant variation in their impact. Moreover, we found that SO2 had a greater impact on overweight prevalence among middle-aged individuals, while NO2 had a greater impact on the elderly. Additionally, we identified significant statistically interactions between O3 and other pollutants.

Quantification of Ozone Pollution Transport Based on Four-dimensional Flux Method in Foshan, China

Quantifying the contribution of transport processes to air pollution events has been a prominent challenge and an important need in regional air pollution prevention and control. The WRF-Chem model was used to simulate a typical regional ozone (O3) pollution event in Foshan, and the four-dimensional flux method was applied to quantify the transport fluxes of ozone and its precursors from the surrounding areas to Foshan and to clarify the contributions of the direct transport of ozone and transport of precursors. The average ozone flux from the surrounding areas to Foshan was 120.3 t·h-1, the volatile organic compound (VOCs) flux was 30.2 t·h-1, and the corresponding ozone formation potential (OFP) was 114.8 t·h-1. By counting the transport fluxes of each ozone pollution event, it was found that the city with the largest ozone flux into Foshan during the pollution period was Guangzhou (contributed 44%); the city with the largest input VOCs flux was Zhaoqing (contributed 48%). The analysis of ozone generation potential due to transported VOCs emissions found that oxygenated volatile organic compounds (OVOCs) contributed the most to OFP, accounting for 47% of the "maximum input events." OVOCs and aromatic hydrocarbons such as formaldehyde, xylenes, aldehydes, acetone, and phenols were the top five species contributing to the OFP, contributing more than 50% of the total OFP, mainly from industrial solvent sources.

Impacts of air pollution and meteorological conditions on dry eye disease among residents in a northeastern Chinese metropolis: a six-year crossover study in a cold region

The purpose of this study is to explore the associations among dry eye disease (DED), air pollution, and meteorological conditions in the cold region of a northeastern Chinese metropolis (i.e., Changchun). Data on ambient air pollutants and meteorological parameters as well as diagnosed DED outpatients during 2015–2021 were collected. The associations between DED and environmental factors were analysed at multiple time scales using various statistical methods (i.e., correlation, regression and machine learning). Among the 10,809 DED patients (21,617 eyes) studied, 64.60% were female and 35.40% were male. A higher frequency of DED was observed in March and April, followed by January, August and October. Individual and multiple factor models showed the positive importance of particles with aerodynamic diameters <10 μm (PM10), carbon monoxide (CO), and ozone (O3) among normal air pollutants and air pressure (AP), air temperature (AT) and wind speed (WS) among normal meteorological parameters. Air pollutants (PM10, nitrogen dioxide: NO2) and meteorological parameters (AT, AP) have combined impacts on DED occurrence. For the first time, we further explored the associations of detailed components of atmospheric particles and DED, suggesting potential emission sources, including spring dust from bare soil and roads and precursor pollutants of summer O3 formation from vehicles and industry in Northeast China. Our results revealed the quantitative associations among air pollutants, meteorological conditions and DED outpatients in cold regions, highlighting the importance of coordinated policies in air pollution control and climate change mitigation.

Abrupt exacerbation in air quality over Europe after the outbreak of Russia-Ukraine war

Much attention has been paid to the world economy and social situations in response to the outbreak of war between Russia and Ukraine in the context of COVID-19. However, much less attention has been paid to the detrimental effect of war on the atmospheric environment. Here, we used an extended deweathered-detrended technique to quantitatively evaluate changes in ambient NO2, O3, and PM2.5 AQI levels arising from emission changes (due to pandemic-driven lockdowns and war-related activities) in European cities. Results show pandemic-induced lockdowns mitigated regional air pollution in Europe, but the war activities led to an average increase of approximately 9.78% in PM2.5 and 10.07% in NO2, along with an average decrease of about 7.93% in O3 levels in cities near the war zones. Moreover, the regional air pollution exacerbated by the war activities has offset the improvements in air quality observed during the COVID-19 pandemic. The potential mechanism analysis show that the increase in atmospheric pollutant emissions driven by the war activities led to the complexity of chemical reactions in the mixed atmospheric system, which posed a huge challenge to the alleviation of air pollution in the region. This study highlights the urgent need for a ceasefire from an environmental perspective.

Seasonal and regional variations of atmospheric ammonia across the South Korean Peninsula

This study aimed to identify the factors causing NH3 emissions in the South Korean Peninsula and West Sea region. To analyze the trends of NH3 and other air pollutants, such as NOx, CO, and NR-PM1, we collected samples from six supersites across the peninsula, a roadside in Seoul, and the West Sea over different sampling periods, ranging from 1 month to 1 year. The highest NH3 concentrations were found at rural areas, ascribed to agricultural activities, particularly NH4NO3 decomposition at high summer temperatures. Areas with low population densities recorded the lowest NH3 concentrations, attributed to the lack of anthropogenic activities. A roadside field experiment confirmed the close link between ambient NH3 and vehicle emissions in urban regions by showing a strong correlation between CO and NOx concentrations and that of NH3. Moreover, we examined oceanic emissions near the eastern coast of South Korea in the West Sea. Long-range transportation studies confirmed that most of the pollutants (NH3, CO, and PM1) were transported by wind from the northeastern region of China. A maritime origin study showed that oceanic emissions and NH4NO3 decomposition in the atmosphere owing to high temperatures were the causing NH3 pollution. These findings provided valuable insights into the emission sources of NH3 in primary air pollutants in South Korea, highlighting the contributions of land-based and oceanic sources. Our study can help inform policymakers and stakeholders for developing effective regional air pollution control strategies.

Optical and Physical Characteristics of Aerosol Layers in Australia Based on CALIPSO

Atmospheric aerosols have important impacts on global radiative forcing, air pollution, and human health. This study investigated the optical and physical properties of aerosol layers over Australia from 2007 to 2019 using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 aerosol products. Australia was divided into three sub-regions (western highlands, central plains, and eastern ranges). Interannual and seasonal optical property variations in aerosol layers in the three sub-regions were analyzed and compared. Results showed that annual mean values of AODL (lowest aerosol layer AOD) and AODT (total AOD of all aerosol layers) were always higher in the eastern ranges region than the other two regions from 2007 to 2019. The reason could be that Australian population was predominantly located in the eastern ranges region, where more human activities could bring significant aerosol loadings. BL (base height of the lowest aerosol layer), HL (top height of the lowest aerosol layer), and HH (top height of the highest aerosol layer) all showed trends of “western highlands &gt; eastern mountains &gt; central plains”, indicating that the higher the elevation, the higher the BL, HL, and HH. TL (thickness of the lowest aerosol layer) was higher during the day than at night, which might account for increased diurnal atmospheric convection and nocturnal aerosol deposition. DRL (depolarization ratio of the lowest aerosol layer) was higher in the western highlands and central plains than the eastern mountains, probably because these two regions have large deserts with more irregularly shaped dust aerosols. CRL (color ratio of the lowest aerosol layer) had slightly higher values in the eastern ranges than the other two regions, probably due to the wet climate of the eastern ranges, where aerosols were more hygroscopic and had larger particle sizes. This study can provide technical support for the control and management of regional air pollutants.

Unveiling Air Pollution in Crimean Mountain Rivers: Analysis of Sentinel-5 Satellite Images Using Google Earth Engine (GEE)

This article presents an assessment of atmospheric pollutant concentrations based on state-of-the-art geoinformation research methods that utilize Sentinel-5 satellite imagery, the cloud computing platform Google Earth Engine (GEE), and ArcGIS 10.8 software. The spatial distributions of some pollutants (nitrogen dioxide, sulfur dioxide, formaldehyde, carbon monoxide, methane) in the atmosphere are analyzed on the example of the basins of the Zapadnyy Bulganak, Alma, Kacha, Belbek, and Chernaya rivers on the north-western slope of the Crimean Mountains. The concentrations of the average annual and average monthly values of pollutants for each catchment area are compared. The GEE (Google Earth Engine) platform is used for extracting annual and monthly average rasters of pollutant substances, while ArcGIS is utilized for enhanced data visualization and in-depth analytical processing. Background concentrations of pollutants within protected natural areas are calculated. By comparing the spatial and temporal distribution of pollutant values with the background concentrations within these protected areas, a complex index of atmospheric pollution is constructed. The spatial and temporal variability of nitrogen dioxide (NO2) concentrations has been thoroughly examined. Based on the regression analysis (R &gt; 0.85), the field of values of the total amount of emissions (which are analyzed for only six points in the study area and in the surrounding areas) was restored on the basis of the spatial and temporal heterogeneity of the field of distribution of nitrogen dioxide values (NO2). Since air pollution can have negative consequences, both for human health and for the ecosystem as a whole, this study is of great importance for assessing the ecological situation within the river basins of the north-western slope of the Crimean Mountains. This work also contributes to a general understanding of the problem of gas emissions, whose study is becoming increasingly relevant. The aim of this research is to assess the potential application of Sentinel-5 satellite imagery for air quality assessment and pollution analysis within the river basins of the north-western slopes of the Crimean Mountains. The significance of this study lies in the innovative use of Sentinel-5 satellite imagery to investigate air pollution in extensive regions where a regular network of observation points is lacking.

O-213 Breathing New Life into Air Pollution Research: Examining the Link Between Air Pollution and Adverse Birth Outcomes in the Eastern Mediterranean Region (EMR)

Abstract Study question What is the current understanding of the relationship between air pollution and perinatal health in the EMR? Summary answer The literature on exposure to air pollutants and perinatal health in the EMR is scarce, limited in scope, and using simply study designs and methods. What is known already Air pollution is a significant public health concern in the Eastern Mediterranean Region, due to many factors such as the arid nature of the region, rapid urbanization, oil production, and the emissions from the transportation, energy productions, and other practices. Not only can the degradation in air quality put the health of infants in jeopardy but it can also increase the risk of adverse pregnancy outcomes. Studies on air pollution and birth outcomes and early life development have been conducted in other parts of the world, but only a small number have been conducted in the EMR. Study design, size, duration The authors conducted a comprehensive search of various databases to identify relevant studies and publications on the topic. The findings were then critically evaluated and discussed in relation to the current understanding of the relationship between air pollution and perinatal health in the EMR. The study does not include any new data collection or primary research. The authors used a narrative approach to synthesize the existing literature on the topic. Participants/materials, setting, methods Not applicable Main results and the role of chance The existing literature is concentrated in specific geographic locations out of the 22 countries and territories that comprise the region, and it is focused on a limited number of exposures and outcomes, namely secondhand smoking and criteria air pollutants. The main gaps include the inconsistent and poorly funded air quality monitoring, inappropriate study designs, imprecise and/or unreliable assessments of exposures and outcomes, and the focus on traditional air pollutants rather than new emerging and increasingly concerning air pollutants. Moreover, even though the studies establish associations between air pollutants and adverse birth outcomes, the mechanisms through which these processes take place are yet to be fully understood. An area of research that holds great potential in explaining these processes is epigenetics; however, due to limited funding, expertise and health and environmental data, epigenetic research on the impact of air pollution in the EMR is still in its infancy. Limitations, reasons for caution The review is based on a narrative approach, which is subjective and may not be as rigorous as a systematic review. The reviewed studies also have their own limitations, such as inconsistent air quality monitoring and imprecise assessments of exposures and outcomes. Studies focused on epigenetics in EMR are scarce. Wider implications of the findings The review highlights the need for future research examining the epigenetic processes that underlie the adverse birth outcomes, to better understand them and to develop effective recommendations and intervention strategies. Trial registration number Not applicable

Air pollution in marmara region before and during the COVID-19 outbreak.

The lockdowns and curfews during the COVID-19 pandemic have halted economic and transportation activities across the world. This study aims to investigate air pollution levels in the Marmara region, particularly in Istanbul, before and during the COVID-19 pandemic. The study used real data provided by the General Directorate of Meteorology and applied three machine learning algorithms (ANN, RBFreg, and SMOreg) to analyze air pollution data. In addition, a one-sample t-test was performed to compare air pollution levels before and during the COVID-19 pandemic in the Marmara region and Istanbul. The results of the study showed a significant reduction in the particulate matter (PM) value, which indicates the degree of air pollution, in both the Marmara region and Istanbul during the COVID-19 pandemic. The one-sample t-test results showed that the reduction in air pollution levels was statistically significant in both areas (t = 11.45, p < .001 for the Marmara region, and t = 3.188, p < .001 for Istanbul). These findings have important practical implications for decision-makers planning for a more sustainable environment. Overall, the study provides valuable insights into the impact of the COVID-19 pandemic on air pollution levels in the Marmara region, particularly in Istanbul. The application of machine learning algorithms and statistical analysis provides a rigorous approach to the investigation of this important issue by comparing before and during the COVID-19 outbreak.

A study on the analysis of dynamical transmission behavior and mining key monitoring stations in PM and O3 networks in the Beijing-Tianjin-Hebei region of China

To investigate the dynamical transmission behavior of pollutants and explore the roles played by monitoring stations in regional air pollutants transportation, we constructed a new model for the dynamical transmission index by adopting a statistics model that employs complex network analysis along with terrain data, meteorological variables, and air quality data. The study is conducted in Beijing-Tianjin-Hebei region with 70 stations in 13 cities. The findings indicated that the regional dynamical transmission networks were characterized by the participation of 67 out of 70 stations, as determined by node number. Among the model characteristics, the average path length and the average clustering coefficient, within the ranges of 2.08–2.32 and 0.26–0.51, respectively, maintained reasonable small-world characteristic. For the seasonal transmission features, the networks for PM2.5, PM10 in winter, and O3 in summer shared similar modeling characteristics with those of yearly networks. This suggested that the networks for these two seasons could represent the yearly transmission features. By employing the entropy weight method, the key monitoring stations numbered 1011 A, 1026 A, and 1010 A, which are located in Tianjin, Shijiazhuang, and Beijing, exerted significant impacts on air pollution transmission path in cities. The novel model has demonstrated its soundness and effectiveness in terms of capturing the behavior of transmission as well as the distinguishing roles of these crucial monitoring stations. This methodology could be employed for the construction of additional monitoring stations, identification of possible pollution sources, and prioritization of key pollution areas, thus providing valuable insights for environmental protection and management.

Analysis of air pollution in Fenwei Plain in China based on functional spatial autoregressive combined model.

The Fenwei Plain is listed as one of the most serious air pollution regions in China, along with Beijing-Tianjin-Hebei and Yangtze River Delta regions. This paper proposed a functional data analysis method to study the environmental pollution problem in the Fenwei Plain of China. Functional spatial autoregressive combined (FSAC) model with spatial autocorrelation of both the response variable and error term is developed. The model takes the SO2 concentration of Fenwei Plain as the dependent variable and the dew point temperature as the independent variable and realizes the maximum likelihood estimation using functional principal component analysis to obtain the asymptotic properties of parameter estimation and the confidence interval of the slope function. According to the findings of the empirical analysis of the Fenwei Plain, the SO2 concentration has significant seasonal characteristics and has decreased year over year for three years in a row. Winter is the season with the highest concentration on the Fenwei Plain, followed by spring and autumn, while summer is the season with the lowest concentration. Winter also has a high spatial autocorrelation. The FSAC model is more effective at fitting the concentration and dew point temperature of the Fenwei Plain in China because its mean square error (MSE) is significantly lower than that of the other models. As a result, this paper can more thoroughly study the pollution problem on the Fenwei Plain and offer guidance for prevention and control.

SPATIAL DISTRIBUTION OF ATMOSPHERIC POLLUTION IN DUHOK URBAN AREA BY USING GIS TOOLS

Air pollution is becoming a serious challenge in thickly populated areas in the world. The air pollution in Kurdistan region is clearly noticed, especially in areas where pollution sources and human population are concentrated. Urbanization and economic growth are proceeding at a rapid pace, accompanied by increasing emissions of a mixture of greenhouse gases especially from transporting sector, that positively contribute to accelerate climate change around the globe, and also have impacts on public health and vegetation. In order to decrease the effects that caused by atmospheric pollution, suitable monitoring systems are urgently needed that can rapidly and reliably detect and quantify polluting sources and concentration for monitoring by local authorities in order to restrain more damage of the current pollution levels. In this study, GIS with portable gas detector (K-60 IV) KELISAIKE safety equipment, China, have been used to assess the status of NOx, VOCs and noise pollution at 54 randomly selected urban locations of Duhok city. The measurements were taken during the week and weekend days started from 9 am until 4 pm. The results showed that there is a variation in the values of the three variables NOx, VOCs and noise, where the highest values recorded during working days in the locations distributed along the highway and the city center with heavy traffic load and dense human population in comparison to lowest values obtained during weekend days in locations distributed outskirt of the city with lower population and traffic loads. Therefore, likely such connections exist between the urban traffic density and low air pollution quality within urban locations around Duhok city.

Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle.

The online version contains supplementary material available at 10.1007/s11270-023-06279-8.

Remote sensing supported analysis of the effect of wind erosion on local air pollution in arid regions: a case study from Iğdır province in eastern Türkiye

PM pollution is one of the most important environmental problems worldwide. One of the sources of PM pollution, which has a negative impact on human health, is dust that enters the atmosphere, especially in arid regions. Iğdır Province, located in the east of Anatolia, has an arid climate character and was selected as the most polluted province in Europe in 2021 and 2022 (in terms of PM2.5 pollution). In this study, the effect of wind erosion-induced dust on air pollution in Iğdır province was investigated. We think that local wind erosion during the summer season (May–September) in the province is effective on PM pollution. Because there are no industrial activities, vehicular traffic, fuel consumption and volcanic activities that cause PM pollution in the summer season around Iğdır. On the other hand, Türkiye’s second largest wind erosion area and the other two wind erosion areas are located here, and dust storms are quite frequent. The causes of local wind erosion, which is one of the main factors in air pollution in the summer period, were investigated from a geographical perspective and various data sets were utilized. Then, wind erosion sites were examined and their regional distributions were indicated. Research findings on wind erosion sites were supported by remote sensing techniques (quartz index, aerosol density, etc.). All the data obtained support the idea that wind erosion is a dominant factor in the high level of PM pollution during the summer season in this area. Because the number of days with strong winds during this period is quite high and EU, WHO and national PM limit values are exceeded almost every day.