Average Concentrations Of SO2 Research Articles

Indoor microbiome, air pollutants and asthma, rhinitis and eczema in preschool children - A repeated cross-sectional study.

Indoor microbiome exposure is associated with asthma, rhinitis and eczema. However, no studies report the interactions between environmental characteristics, indoor microbiome and health effects in a repeated cross-sectional framework. 1,279 and 1,121 preschool children in an industrial city (Taiyuan) of China were assessed for asthma, rhinitis and eczema symptoms in 2012 and 2019 by self-administered questionnaires, respectively. Bacteria and fungi in classroom vacuum dust were characterized by culture-independent amplicon sequencing. Multi-level logistic/linear regression was performed in two cross-sectional and two combined models to assess the associations. The number of observed species in bacterial and fungal communities in classrooms increased significantly from 2012 to 2019, and the compositions of the microbial communities were drastically changed (p<0.001). The temporal microbiome variation was significantly larger than the spatial variation within the city (p<0.001). Annual average outdoor SO2 concentration decreased by 60.7%, whereas NO2 and PM10 concentrations increased by 63.3% and 40.0% from 2012 to 2019, which were both associated with indoor microbiome variation (PERMANOVA p<0.001). The prevalence of asthma (2.0% to 3.3%, p=0.06) and rhinitis (28.0% to 25.3%, p=0.13) were not significantly changed, but the prevalence of eczema was increased (3.6% to 7.0%; p<0.001). Aspergillus subversicolor, Collinsella and Cutibacterium were positively associated with asthma, rhinitis and eczema, respectively (p<0.01). Prevotella, Lactobacillus iners and Dolosigranulum were protectively (negatively) associated with rhinitis (p<0.01), consistent with previous studies in the human respiratory tract. NO2 and PM10 concentrations were negatively associated with rhinitis in a bivariate model, but a multivariate mediation analysis revealed that Prevotella fully mediated the health effects. This is the first study to report the interactions between environmental characteristics, indoor microbiome and health in a repeated cross-sectional framework. The mediating effects of indoor microorganisms suggest incorporating biological with chemical exposure for a comprehensive exposure assessment.

On-line analysis of free-tropospheric water-soluble acidic gases and particulate anions on the summit of Mt. Fuji, Japan

Atmospheric gaseous and particulate pollutants emitted from local or regional sources cause transboundary air pollution. To better understand this environmental issue, it is useful to monitor the free troposphere, reflecting the global air quality, with high temporal resolution. During the summer of 2016, we operated an original on-line monitor on the summit of Mt. Fuji, Japan (3776 m a.s.l.) to measure water-soluble acidic gases and particulate anions in the free troposphere. Mt. Fuji is a free-standing mountain and, therefore, hardly affected by air pollutants emitted from the local region. The lab-made gas/particle collector coupled ion chromatograph successfully provided meaningful data on an hourly basis. The average concentrations of HNO3, SO2, NO3−, and SO42− (n = 64 each) were, respectively 1.8 ± 0.9, 2.3 ± 2.5, 0.22 ± 0.16, and 3.9 ± 2.6 nmol m−3. The gaseous HNO3 was the predominant form compared to particulate NO3−. For the sulfur component, the percentage of particulate form was higher than that of the gaseous one. The high time-resolution monitoring enabled us to classify the observed data based on the air parcel inflow direction to the sampling point even when it changed dramatically. As a result, the oxidation of SO2 to SO42− in atmospheric transport can be discussed for each air parcel. It was suggested that the SO2 oxidation was enhanced in the air parcels that passed over the Asian Continent.

Estimation of short-lived climate forced sulfur dioxide in Tehran, Iran, using machine learning analysis

This paper presents a time-series analysis of SO2 air concentration and the effects of particulates (either PM2.5 and PM10) concentrations and meteorological conditions (relative humidity and wind speed) on SO2 trend in Tehran for the period from 2011 to 2020. The source data were obtained from 21 monitoring stations of Air Quality Control Company and meteorological stations in Tehran. To predict the status of future concentration of SO2, PM2.5 and PM10, a Box–Jenkins ARIMA approach was used to model the monthly time series. Considering the whole period of ten years, a somewhat downward trend was noted for SO2 air concentration, even though a slight rising trend was observed in 2020 year. Monthly sulfur dioxide concentrations showed the lowest value in June and the highest value in January. Seasonal concentrations were lowest in spring and highest in winter. Then, in the ArcGIS software, the IDW method was used to obtain air pollution zoning maps. As a result, the highest average concentration of SO2 occurred in the north and southwest of Tehran. In the last step, Relations between the SO2 concentration and particulate matters and relative humidity and wind speed were calculated statistically using the daily average data. We finally concluded that the combined effect of particulate matters and relative humidity with the increasing role of Sulfur dioxide overcomes the decreasing role of wind speed. This study can contribute to a better understanding of the SO2 air pollution in Tehran affected by meteorological conditions and the rapid urbanization and industrialization, followed by the possible combustion of fuel oil in power plants and health problems.

Application TAPM-AERMOD system model to study impacts of thermal power plants in SouthEast and SouthWest areas to the air quality of HCMC: current status and according to Vietnam power planning VII toward 2030

Vietnam’s urban areas have faced serious environmental pollution issues, including water pollution, municipal waste, and air pollution. Vietnam’s real gross domestic product (GDP) has been experiencing positive growth for the past five years since 2016. And in 2019, Vietnam’s real GDP increased by 7.02% compared to the previous year. To maintain the growth rate, there is a huge amount of electricity required, not accounting for the other sectors. Thermal power plants generate more than 50% of total electricity in Vietnam, therefore, it is said that coal-fired power plants have been the major sources of air emissions and caused a serious impact on the environment. Recently air pollution is a hot issue in Ho Chi Minh City (HCMC), the air quality is being polluted by PM2.5, O3, CO, NO2, and TSP. Despite that, the neighboring areas of the city will install more coal-fired power plants, threatening to degrade the quality of the environment. Therefore, the objectives of this study are (i) Modeling the impacts of thermal power plants in SouthEast and SouthWest areas on the air quality of HCMC for two scenarios (current status in 2019 and future according to Power planning VII (adjusted) toward 2030); And (ii) Develop interprovincial air quality protection solutions. The research applied the TAPM model for meteorological modeling and AERMOD model for air pollution dispersion. The annual average PM2.5 concentration in the study area was approximately 0.121 μg/m3 and the highest concentration at a location close to Vinh Tan thermal power center with 8.61 μg/m3. NO2 the annual average concentration from power plants in 2020 and 2030 blows to HCMC and contributes to HCMC’ air quality only 0.01 and 0.03 μg/m3, respectively. The 24 hours average concentration of SO2 from power plants in 2030 blows to HCMC and contributes to HCMC’ air quality of 10 μg/m3. The 24 hours average SO2 levels of HCMC in 2030 is 39.2 μg/m3, higher than WHO’s guideline (20 μg/m3). Currently, air pollution in HCMC is polluted by PM2.5, SO2, and NO2 and cause bad effect to public health. However, in the future with the contribution of 33 thermal power plants under intercity/provinces air pollution dispersion, air pollution HCMC will be worse and affect public health. Air pollution HCMC will be a huge impact on HCMC’s public health in the future due to the contribution of 33 thermal power plants under intercity/provinces air pollution dispersion. The paper developed 7 main mitigation measures to reduce the impacts of air pollution from the power plan and reduce the impacts of air pollution on HCM’s public health. The measures are focused on using clean fuel, advanced technology, and controlling trans-provincial air pollution.

Assessment of gaseous air pollutants motility in Khulna City of Bangladesh using direct sense probes

The atmosphere surrounding Bangladesh is being polluted day by day in short order due to harmful activities strongly related to air pollution. This study was carried out in Khulna City of Bangladesh located in the southern part of the country. Gaseous air pollutants concentrations at specific eight locations were measured and analysed using real-time monitoring equipment. Time series analysis, diurnal and seasonal variations in mass concentration and variation in total mass concentration of SO2, CO, and NOx were analysed. This study reveals the highest average concentrations of SO2, CO, and NOx as 224 μg/m3, 3,104 μg/m3, and 116 μg/m3 consecutively. Significant diurnal and seasonal variation of pollutants can be sanctioned by the adjustable working scenario of concerning locations. Air pollution controlling provisions can be directed considering this baseline study in Bangladesh and other similar Asian countries.

Effects of prenatal exposures to air sulfur dioxide/nitrogen dioxide on toddler neurodevelopment and effect modification by ambient temperature

Emerging evidence suggests that prenatal exposure to ambient SO2 or NO2 induces fetal brain-damage. However, effects of prenatal exposure to SO2 or NO2 on toddler neurodevelopment and the effect-modification by ambient temperature remain unclear. Therefore, a prospective birth-cohort study was conducted from 2010 to 2012 in Shanghai, and 225 mother-child pairs were followed-up from mid-to-late pregnancy until 24–36 months postpartum. During the whole pregnancy, daily SO2/NO2 and temperature levels were obtained for each woman. Gesell-Development-Schedule was used to assess toddler neurodevelopment in the domains of gross-motor, fine-motor, adaptive-behavior, language and social-behavior. Distributed-lag-nonlinear-models simultaneously accounting for exposure-response and lag-response associations were applied to assess the impacts of prenatal SO2/NO2 exposure on neurodevelopment. Each 10-μg/m3 increase in weekly average SO2 concentrations had adverse associations with gross-motor in gestational-weeks 1–6, with adaptive-behavior in weeks 26–30, and with language in weeks 30–36 (developmental-quotient changes: − 1.17% to − 0.12%, P-values < 0.05). Each 10-μg/m3 increase in weekly average NO2 concentrations had adverse associations with gross-motor in gestational-weeks 33–36, with fine-motor in weeks 26–36 and with social-behavior in weeks 31–36 (developmental-quotient changes: − 0.91% to − 0.20%, P-values < 0.05). The cumulative effects for the whole pregnancy showed that each 10-μg/m3 increase in SO2 induced significant deficits in gross-motor and adaptive-behavior (developmental-quotient changes: − 4.71% and − 4.06%, respectively, P < 0.05). We found prenatal cumulative SO2 exposure induced more deficits in low temperature in language and adaptive-behavior than in high/moderate temperature. Thus, prenatal ambient SO2/NO2 exposure in specific time-windows (1st and 3rd trimesters for SO2; 3rd trimester for NO2) could impair toddler neurodevelopment and low temperature may aggravate the SO2-induced neurotoxicity.

Spatio-Temporal Characteristics of SO2 across Weifang from 2008 to 2020

China has achieved good results in SO2 pollution control, but SO2 pollution still exists in some areas. Analyzing the spatio-temporal distribution of SO2 is critical for regional SO2 pollution prevention and control. Compared with existing air pollution studies that paid more attention to PM2.5, NO2 and O3, and focused on the macro scale, this study took the small-scale Weifang city as the research area, analyzed the temporal and spatial changes in SO2, discussed the migration trajectory of SO2 pollution and explored the impact of wind on SO2 pollution. The results show that the average annual concentration of SO2 in Weifang has exhibited a downward trend in the past 13 years, showing the basic characteristics of “highest in winter, lowest in summer and slightly higher in spring and autumn”, “highest on Sunday, lowest on Thursday and gradually decreasing from Monday to Thursday” and “highest at 9 a.m., lowest at 4 p.m. and gradually increasing from midnight to 9 a.m.”. SO2 concentration showed obvious spatial heterogeneity: higher in the north and lower in the south. In addition, Shouguang, Changyi and Gaomi were seriously polluted. The SO2 pollution shifted from south to northeast. The clean wind direction (southeast wind and northeast wind) of Weifang city accounted for about 41%, and the pollution wind direction (northwest wind and west wind) accounted for about 7%. Drawing from the multi-scale analysis, vegetation, precipitation, temperature, transport situation and human activity were the most relevant factors. Limited to data collection, more quantitative research is needed to gain insight into the influence mechanism in the future.

Indoor air quality in sports center: Assessment of gaseous pollutants

The aims of this study were to determine the concentrations of selected gaseous indoor air pollutants (CO2, VOC, NO2, SO2), evaluate the ventilation system efficiency, and identify the factors determining air quality in a typical Polish sports center. Measurements were conducted simultaneously inside and outside the building during the non-heating (05/18/2017–06/21/2017) and heating (10/16/2017–11/20/2017) seasons. CO2 concentrations were measured automatically (MultiRAE), while VOCs, NO2, and SO2 samples were collected by the passive method and determined using gas chromatography, spectrophotometry, and ion chromatography, respectively. The average concentrations of the tested pollutants, except for CO2 outside, were higher in the heating season. Average CO2 concentrations in both seasons were higher inside the building (761–815 ppm) than outside (521–525 ppm). The average VOC (129.4–193.3 μg/m3), NO2 (20.2–21.3 μg/m3), and SO2 (0.9–1.4 μg/m3) concentrations in both seasons were comparatively lower inside. CO2 concentrations were mainly related to physical activity and determined by the number of people exercising on a given day, while VOC, NO2, and SO2 concentrations were influenced mainly by outdoor sources (traffic emissions, combustion of fossil fuels). The presence of specific substances (e.g. propanol, ethanol derivatives) only in indoor air were influenced by specific indoor sources, such as cleaning activities, hall maintenance, and cosmetics. The results can be used to develop appropriate control strategies to improve indoor air quality in sports facilities and improve the safety of their users by minimize the adverse health effects due to exercise in conditions of poor air quality.

Research on the Temporal and Spatial Characteristics of Air Pollutants in Sichuan Basin

Sichuan Basin is one of the most densely populated areas in China and the world. Human activities have great impact on the air quality. In order to understand the characteristics of overall air pollutants in Sichuan Basin in recent years, we analyzed the concentrations of six air pollutants monitored in 22 cities during the period from January 2015 to December 2020. During the study period, the annual average concentrations of CO, NO2, SO2, PM2.5 and PM10 all showed a clear downward trend, while the ozone concentration was slowly increasing. The spatial patterns of CO and SO2 were similar. High-concentration areas were mainly located in the western plateau of Sichuan Basin, while the concentrations of NO2 and particulate matter were more prominent in the urban agglomerations inside the basin. During the study period, changes of the monthly average concentrations for pollutants (except for O3) conformed to the U-shaped pattern, with the highest in winter and the lowest in summer. In the southern cities of the basin, secondary sources had a higher contribution to the generation of fine particulate matter, while in large cities inside the basin, such as Chengdu and Chongqing, air pollution had a strong correlation with automobile exhaust emissions. The heavy pollution incidents observed in the winter of 2017 were mainly caused by the surrounding plateau terrain with typical stagnant weather conditions. This finding was also supported by the backward trajectory analysis, which showed that the air masses arrived in Chengdu were mainly from the western plateau area of the basin. The results of this study will provide a basis for the government to take measures to improve the air quality in Sichuan Basin.

Characteristics and Origin Analysis of Air Pollution During the Spring Festival in Linfen, Fenwei Plain

In recent years, frequent haze episodes have resulted in the deterioration of air quality of the Fenwei Plain during winter and holidays. Besides coal combustion and industrial emissions, the topography and climate of the Fenwei Plain were also the main causes of the haze. The samples were collected in Linfen of Fenwei Plain during the Spring Festival from February 2 to February 13, 2019. The 13 elements(Li, Be, Ti, Rb, Sc, Y, La, Ce, Zr, V, Tl, U, and Sn) in PM2.5 were determined by inductively coupled plasma mass spectrometry(ICP-MS). Combined with the meteorological data, the spatial and temporal distribution of pollutants and potential source analysis were evaluated by cluster analysis and backward trajectory. The average concentration of SO2 was 58.39 μg·m-3 during the sampling period, which exceeded the 24 h average mass concentration limit(50.00 μg·m-3) of national ambient air quality standard(GB 3095-2012). The average concentrations of O3, NO2, and CO was 52.15 μg·m-3, 29.02 μg·m-3, and 2.29 mg·m-3, respectively. The results showed that SO2 was the dominated pollutant. NO2 and CO were mainly affected by diffusion from urban areas. The backward trajectory analysis indicated that the basin topography of the Fenwei Plain may be the main cause of the haze. The analysis of potential source contribution function(PSCF) of soil sources showed that the potential dominated areas included Northern Shaanxi, southern Gansu and Southern Ningxia., which were mainly affected by the monsoon climate.

A comparison between national air quality index, india and composite air quality index for Ahmedabad, India

Ahmedabad is the 5th biggest city and 7th most populated city in India. It is the largest city in Gujarat. The city is spread over a further 450 sq. km. of area. The study report prepared by the World Health organization (WHO) in May 2014 reveals that Ahmedabad is the 9th most air polluted city in the world and 5th most air polluted city in India, based on the concentration of fine particulate matter (PM2.5). In this study, six different ambient air quality monitoring locations are selected in Ahmedabad. A sensor-based continuous ambient air quality monitoring instrument is used to monitor the ambient air quality of selected locations for the summer and winter seasons. The concentration of six pollutants is monitored: respirable suspended particulate matter (PM10), fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). The monitoring data shows that in the summer, the average concentration of all the pollutants at all selected locations is within National Ambient Air Quality Standards (NAAQS), 2009. In the winter, gaseous pollutants; an average hourly concentration of O3 and CO; and 24 hrs. the average concentration of SO2 and NO2 are within NAAQS, 2009 at all the selected locations. In the winter, the average concentration of particulate matter (PM10 and PM2.5) are exceeding the standards at four out of six selected locations during monitoring. So, pollutants concentration is more in winter as compared to summer, this may be due to meteorological parameters. The monitoring data also reveals that in Ahmedabad the major responsible pollutants are particulate matters (PM10 and PM2.5) rather than the gaseous pollutants.The monitoring data are used to determine the National Air Quality Index (NAQI), India, and the fuzzy-based Composite Air Quality Index (CAQI). The two indexing systems are compared. In this research article, determination methods of the National Air Quality Index and the Composite Air Quality Index are discussed. The comparison between the two-indexing system reveals that the CAQI estimates more efficiently the pollutants exposure to the population as compared to the NAQI. The CAQI shows the realistic situation, especially when two or more pollutants are exceeding the standards simultaneously. The composite air quality indexing tool is very useful to inform the citizens and to protect human well-being in an urban area. It can be used as a governmental and administrative tool to make abatement strategies and to take effective measures. The wider range of composite air quality indexes proves the superiority over the national air quality index, India.

PM2.5-bound silicon-containing secondary organic aerosols (Si-SOA) in Beijing ambient air

Volatile methyl siloxanes (VMS) have been widely used in personal care products and industrial applications, and are an important component of VOCs (volatile organic compounds) indoors. They have sufficiently long lifetimes to undergo long-range transport and to form secondary aerosols through atmospheric oxidation. To investigate these silicon-containing secondary organic aerosols (Si-SOA), we collected PM2.5 samples during 8th-21st August 2018 (summer) and 3rd-23rd January 2019 (winter) at an urban site of Beijing. As the oxidation of VMS mainly results in hydrophilic polar semi-volatile and non-volatile oxidation products, the differences between total water-soluble Si and total water-soluble inorganic Si were used to estimate water-soluble organic Si, considered to be secondary organic Si (SO–Si). The average concentrations of SO–Si during the summer and winter campaigns were 4.6 ± 3.7 and 13.2 ± 8.6 ng m−3, accounting for approximately 80.1 ± 10.1% and 80.2 ± 8.7% of the total water-soluble Si, and 1.2 ± 1.2% and 5.0 ± 6.9% of total Si in PM2.5, respectively. The estimated Si-SOA concentrations were 12.7 ± 10.2 ng m−3 and 36.6 ± 23.9 ng m−3 on average in summer and winter, which accounted for 0.06 ± 0.07% and 0.16 ± 0.22% of PM2.5 mass, but increased to 0.26% and 0.92% on certain days. We found that net solar radiation is positively correlated with SO–Si levels in the summer but not in winter, suggesting seasonally different formation mechanisms.

Incorporating gridded concentration data in air pollution back trajectories analysis for source identification

The identification of air pollution sources is a challenging task due to the confounding effects of local and transboundary emitters. While the Potential Source Contribution Function (PSCF) is a useful tool for trajectory analysis and source identification, it can overestimate the impact of less polluted areas in which a trajectory event passed through. In this work, we propose incorporating air pollutant concentration fields from reanalysis data to improve the PSCF method's performance that avoids the overcontribution of less polluted areas. We develop the 3D-PSCF-CONC based on an updated three-dimensional version of the PSCF method (3D-PSCF). We used as a test case the Metropolitan Area of São Paulo (MASP) in Brazil, one of the most polluted regions in the world, for comparing the results of the conventional and the new PSCF method. A monitoring station in Vitória - Espírito Santo, Brazil which has smaller local emissions than MASP was used as an auxiliary test case. Hourly carbon monoxide (CO) and sulfur dioxide (SO2) concentrations from 2015 to 2019 of monitoring stations were analyzed. The daily average concentrations of CO and SO2 were used as a threshold on the probability calculations. An overall of 1825 backward trajectories from HYSPLIT version 4 was processed using the three models. CO and SO2 surface concentrations from MERRA-2, with a resolution of 0.5° x 0.625° was incorporated in the 3D-PSCF-CONC to correct the potential contribution calculation based on the air pollutant concentration field. Our results revealed that the 3D-PSCF-CONC reached a more consistent identification of local and regional sources, rather than emphasizing mostly the regional sources as the other PSCF methods. The 3D-PSCF-CONC reduced the potential contribution of less polluted and high precipitation areas. The analysis suggests a contribution of vehicular sources close to the receptor site in MASP and long-range transport of industrial emissions and biomass burning from the land clearing of sugarcane production. This work presents an important tool for understanding the air pollution process and source identification.

Modification of the effects of nitrogen dioxide and sulfur dioxide on congenital limb defects by meteorological conditions.

Can meteorological conditions modify the associations between NO2 and SO2 exposure and congenital limb defects (CLDs) during the first trimester of pregnancy? Increases in NO2 and SO2 exposure were consistently associated with higher risks of CLDs during the first trimester of pregnancy; both low- and high-temperature exposure and high air humidity act synergistically with the two air pollutants on CLDs. Animal studies have indicated air pollutants are associated with CLDs, but corresponding epidemiological studies are limited with equivocal conclusions. Meteorological conditions are closely connected to the generation, diffusion, distribution and even chemical toxicity of air pollutants. This case-control study included 972 cases of CLDs and 9720 controls in Changsha, China during 2015-2018. Cases from the hospital based monitoring system for birth defects (including polydactyly, syndactyly, limb shortening, and clubfoot) and healthy controls from the electronic medical records system were studied. Complete data on daily average NO2 and SO2 concentrations and meteorological variables were obtained from local monitoring stations to estimate monthly individual exposures during the first trimester of pregnancy, using the nearest monitoring station approach for NO2 and SO2 concentrations, and the city-wide average approach for temperature and relative humidity, respectively. The 25th and 75th percentiles of daily mean temperature, as well as the 50th percentile of daily mean relative humidity during the study period were used to classify high- and low-temperature exposure, and high humidity exposure based on existing evidence and local climate characteristics. Multivariate logistic regression models were used to estimate the independent effects per 10 μg/m3 increase in NO2 and SO2 on CLDs, and the attribute proportions of interaction (API) were used to quantify the additive joint effects of air pollutants with meteorological conditions after including a cross product interaction term in the regression models. NO2 and SO2 exposures during the first trimester of pregnancy were consistently and positively associated with overall CLDs and subtypes, with adjusted odd ratios (aORs) ranging from 1.13 to 1.27 for NO2, and from 1.37 to 2.49 for SO2. The effect estimates were generally observed to be the strongest in the first month and then attenuated in the second and third months of pregnancy. Synergistic effects of both low and high temperature in combination with NO2 (with APIs ranging from 0.07 to 0.38) and SO2 (with APIs ranging from 0.18 to 0.51) appeared in the first trimester of pregnancy. Several significant modifying effects by high humidity were also observed, especially for SO2 (with APIs ranging from 0.13 to 0.38). Neither NO2 nor SO2 showed an interactive effect with season of conception. The methods used to estimate individual exposure levels of air pollutants and meteorological factors may lead to the misclassification bias because of the lack of information on maternal activity patterns and residential mobility during pregnancy. Moreover, we were unable to consider several potentially confounding factors, including socioeconomic status, maternal nutrient levels, alcohol use and smoking during early pregnancy due to unavailable data, although previous studies have suggested limited change to the results after when including these factors in the analysis. The findings are helpful for understanding the combined effects of air pollution and meteorological conditions on birth defects. Environmental policies and practices should be formulated and implemented to decrease air pollutant emissions and improve meteorological conditions to reduce their harmful effects on pregnancy. Additionally, pregnant women should be suggested to reduce outdoor time when the air quality is poor, especially when ambient temperature is higher or lower than what is comfortable, or when it is excessively humid. The study is funded by Major Scientific and Technological Projects for Collaborative Prevention and Control of Birth Defects in Hunan Province (2019SK1012), Major Research and Development Projects in Hunan Province (2018SK2060) and Scientific and Technological Department Projects in Hunan Province (2017SK50802). There are no competing interests. N/A.

The relationship between urban heat island and air pollutants and them with influencing factors in the Yangtze River Delta, China

The relationship between urban heat island (UHI) and air pollution is worth exploring. We used land surface temperature (LST) and air quality data investigated the spatio-temporal distribution of UHI intensity (UHII) and six air pollutants of carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particle matter (PM2.5), coarse particle matter (PM10) and sulfur dioxide (SO2) in the YRD during 2015–2019, and the correlation relationship between UHII and air pollutants concentration. Using regression analysis to analyze the influence of natural and human factors on the UHI and air pollutants. We found that: (1) Annual average daytime UHII was 1.20 ℃ and northern higher than southern cities. Nighttime UHII was 0.35 ℃ and southern higher than northern. Annual average CO, NO2, O3, PM2.5, PM10 and SO2 concentrations were 0.83 mg/m3, 35.41 ug/m3, 63.34 ug/m3, 44.16 ug/m3, 73.46 ug/m3, 13.86 ug/m3, respectively. Air pollution in inland cities were worse than coastal cities. (2) A significant positive correlation between daytime UHII and O3 concentration, and a negative correlation with other pollutants. (3) The influence of LST is the closest factors, followed by vegetation coverage, geographic location, elevation and economic development intensity on UHII and air pollution.

Effects of chronic exposure to ambient air pollutants, demographic, and socioeconomic factors on COVID-19 morbidity: The Israeli case study

BackgroundRecent studies conducted in several OECD countries have shown that chronic exposure to elevated levels of air pollutants (especially PM2.5, PM10 and NOx), might negatively impact COVID-19 morbidity and mortality rates. The aim of this study was to examine the association between chronic exposure to air pollution in Israeli cities and towns, their demographic and socioeconomic status, and COVID-19 morbidity, during the three local morbidity waves. MethodsWe examined the associations between: (a) annual average concentrations of NOx, CO, PM10, PM2.5 and SO2 in 2016–2019, and demographic and socioeconomic parameters, and (b) COVID-19 positive cases in 279 Israeli cities and towns, in the four state-wide morbidity peaks: 1st wave peak: March 31st, 2020; 2nd wave peaks: July 24th and September 27th, 2020, and the 3rd wave peak: January 17th, 2021, which occurred after the beginning of the nationwide vaccination campaign. These associations were calculated using both Spearman correlations and multivariate linear regressions. ResultsWe found statistically significant positive correlations between the concentrations of most pollutants in 2016–19 and COVID-19 morbidity rate at the first three timepoints but not the 4th (January 17th, 2021). Population density and city/town total population were also positively associated with the COVID-19 morbidity rates at these three timepoints, but not the 4th, in which socioeconomic parameters were more dominant - we found a statistically significant negative correlation between socioeconomic cluster and COVID-19 morbidity. In addition, all multivariate models including PM2.5 concentrations were statistically significant, and PM2.5 concentrations were positively associated with the COVID-19 morbidity rates in all models. ConclusionsWe found a nationwide association between population chronic exposure to five main air pollutants in Israeli cities and towns, and COVID-19 morbidity rates during two of the three morbidity waves experienced in Israel. The widespread morbidity that was related to socioeconomic factors during the 3rd wave, emphasizes the need for special attention to morbidity prevention in socioeconomically vulnerable populations and especially in large household communities. Nevertheless, this ecological study has several limitations, such as the inability to draw conclusions about causality or mechanisms of action. The growing body of evidence, regarding association between exacerbated COVID-19 morbidity and mortality rates and long-term chronic exposure to elevated concentrations of air pollutants should serve as a wake-up call to policy makers regarding the urgent need to reduce air pollution and its harmful effects.

Status of Air Pollution over the Last Three Decades in Thimphu City, Bhutan

With an increasing human population and vehicles, air pollution in Thimphu City is growing and causing a risk to human health, properties, and ecosystems. The population of Thimphu was 79,185 in 2005 but in 2017 it surged up to 114,551. An increase in the human population has also led to the rising demands for vehicles and thus increased the vehicular emissions in the area. Additionally, the use of traditional fuels, burning of waste and agriculture residues, forest fire, and transboundary pollutants are other sources resulting in poor air quality in Thimphu City. Air pollution data from journal articles, government documents, reports from national and international organizations, and books were reviewed. Concentrations of PM10, PM2.5, SO2, NO2 were increasing over the decades. The annual average PM10 recorded in Thimphu was 28 µg/m3 in 2005, 47 µg/m3 in 2010, 43 µg/m3 in 2014, and 42 µg/m3 in 2015. Winter months were found to have higher PM10 and PM2.5 concentrations. The 24-hourly average concentrations of SO2 ranged from 0.0 to 6.9 µg/m3 and NO2 8.2-26.6 µg/m3. There is a need for comprehensive studies to identify spatial and temporal variations in the ambient concentration of the pollutants in the area. Strict enforcement of the legal frameworks is essential for the mitigation of air pollution in Thimphu City.

Relationship between urban atmospheric environment and surrounding two-dimensional and three-dimensional landscape pattern in China.

Atmospheric environment in urban built-up area is severely influenced by the surrounding landscape pattern. Understanding the relationship between air pollution and surrounding landscape pattern at small scale has great significance for mitigating air pollution from the perspective of urban construction. The annual average concentrations of NO2, SO2, PM2.5 and PM10 from 266 air pollution monitoring stations in 30 provincial capitals of China in 2017 were chosen as dependent variables. Ten two-dimensional and three-dimensional landscape pattern indices (number of buildings, building aggregation, building density, impervious water ratio, quantitative density of catering, building footprint area, high building ratio, floor area ratio, total building area and building type Shannon diversity index) within the 3 km area around the monitoring stations were used as independent variables. The effects of landscape pattern on the concentration of four air pollutants were analyzed using the boosted regression trees model. The results showed that the concentration of four air pollutants in the central and northern cities were significantly higher than that in the southeast coastal cities and southwest cities. The most important factor affecting the concentrations of NO2, SO2, PM2.5 and PM10 was the impervious ratio, with relative contribution rates of 40.7%, 36.3%, 51.0% and 51.8% respectively. The results of sub-region analysis showed that the most important influencing factor differed in different regions, including the impervious ratio in the East and Central China; the number and density of buildings in South China; the impervious ratio and diversity of building types in North China; the impervious ratio and the number of buildings in Northeast China, the density of buildings in Northwest China. Such differences were mainly caused by climate, topography, urban planning, and other factors.

Spatiotemporal variation of atmospheric pollution and its plausible sources in an industrial populated city, Bay of Bengal, Paradip, India

This study examines the possible sources of ambient pollutants and seasonal variations within the nine selected stations, including the residential, commercial, and industrial sites from January 2016 to December 2018 in Paradip city. The particulate matter (PM) like PM10 and PM2.5 and gaseous pollutants like sulphur dioxide (SO2), nitrogen dioxide (NO2), and ammonia (NH3) samples were collected in four different seasons such as pre-monsoon, monsoon, post-monsoon, and winter. The seasonal average concentrations of PM10 and PM2.5 showed the highest levels in winter and the lowest in monsoon. The seasonal average concentrations of SO2, NO2, and NH3 were within the permissible limits at all the sites. The seasonal air quality index (AQI) shows that industrial sites were under the “severe air pollution” category in the winter season while all residential and commercial sites (except AG) under the “light air pollution” category in all seasons. The correlation such as, PM10 with PM2.5 and SO2 with NO2, showed a significant positive relation in all seasons. Principal component analysis (PCA) identified two major factors, with a total variance of 47.995% and 25.821%, respectively. Hierarchical cluster analysis (HCA) was used to explain the pollutants dispersion and spatial variations.

Impact of emissions from a single urban source on air quality estimated from mobile observation and WRF-STILT model simulations

For industrial cities, quantifying the influence of a given emission source on air quality is very important for making a detailed control strategy to the emissions. By taking use of the mobile observations and WRF-STILT model simulations, this study analyzes the air pollution characteristics and air quality influences from an industrial emission source in Xinji, China. During the study period, the hourly average concentrations of smoke, SO2, and NOx emitted from the industrial source are 1.01, 22.04, and 26.22 mg/m3, respectively. The mobile observations show that with the increase of distance from the emission source, the concentration of air pollutants increases first and then decreases. The peak values of PM2.5, SO2, and NOx appear at the distance of around 0–3 km away from the emission source, among which PM2.5 and SO2 increase first and then decrease before stabilizing, while NOx is interfered by emissions from the traffic along the roads. Within the distance of 3 km, the emission source has obvious influence on the air quality with contribution rate 10–48% at night time and 3–23% at day time. The simulation results of WRF-STILT also support the observed gradient change characteristics of air pollutants, suggesting that this industrial emission source is an important pollution source for regions around it. Our results further show that the meteorological conditions play an important role on the transport capacity of industrial emissions. The results of this study provide support for quantifying the scope of influence of fixed emission sources, especially in industrial cities.