Showing papers in "Air Quality, Atmosphere & Health in 2021"

The impact of COVID-19 lockdown on the air quality of Eastern Province, Saudi Arabia.

Abstract: Since the identification of the COVID-19 outbreak in Wuhan, China, in December 2019, the death toll from the direct infection by COVID-19 has exceeded 775,000, and more than 21 million cases have been reported to the World Health Organization (WHO) around the world. It is strongly believed that its impact might be worsened by poor outdoor and indoor air qualities, particularly on older adults. The nationwide lockdown measures were imposed between March 23 and June 20, 2020, to stop the spread of COVID-19 pandemic in the Kingdom of Saudi Arabia (KSA). In this work, the possible effects of the lockdown on the air quality were investigated using meteorological and air quality datasets obtained from eight monitoring stations covering the Eastern Province of the KSA. The studied air pollutants include carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and inhalable particulate matter (PM10). The NO2 was found to be the marker pollutant responding best to the lockdown measures since its concentrations decreased at all sites during- and post-lockdown periods and ranged between 12-86% and 14-81%, respectively. Compared with pre-lockdown period, the Eastern Province also experienced significant concentration reductions at varying rates for PM10 (21-70%), CO (5.8-55%), and SO2 (8.7-30%), while O3 concentrations showed increasing rates ranging between 6.3 and 45%. The consequences of these reductions were reflected in easing the outdoor air quality, which might reduce the impact of COVID-19 pandemic, especially on elderly and sensitive groups.

UK COVID-19 lockdown: 100 days of air pollution reduction?

Abstract: On the 23 March 2020, a country-wide COVID-19 lockdown was imposed on the UK. The following 100 days saw anthropogenic movements quickly halt, before slowly easing back to a “new” normality. In this short communication, we use data from official UK air-quality sensors (DEFRA AURN) and the UK Met Office stations to show how lockdown measures affected air quality in the UK. We compare the 100 days post-lockdown (23 March to 30 June 2020) with the same period from the previous 7 years. We find, as shown in numerous studies of other countries, the nitrogen oxides levels across the country dropped substantially (∼ 50%). However, we also find the ozone levels increased (∼ 10%), and the levels of sulphur dioxide more than doubled across the country. These changes, driven by a complex balance in the air chemistry near the surface, may reflect the influence of low humidity as suggested by Met Office data, and potentially, the reduction of nitrogen oxides and their interactions with multiple pollutants.

Microplastics as emerging atmospheric pollutants: a review and bibliometric analysis

Abstract: Microplastics are ubiquitously present in various environments; thus, they have become a noteworthy issue by researchers. The present study aimed to provide state-of-the-art on microplastic studies and in detail to review the researches on atmospheric microplastic pollution in terms of occurrence, distribution, sampling, analysis, sources, and transport. The results of the bibliometric analysis showed that the annual output in microplastic research has increased, especially during the last 5 years. The research hot spots in the microplastic topic are marine environment, surface water, freshwater, wastewater, toxic effects, and fate and transport of microplastics. The number of studies investigating atmospheric microplastic pollution is still so limited, although microplastics in the atmosphere became one of the notable subjects. Natural and synthetic fibers were mainly detected in the studies investigating microplastic pollution in the air. Textile clothes, anthropogenic activities, and fragmentation of large plastics were indicated as the main sources, while the wind was pointed out as the predominant transport mechanism of atmospheric microplastics. Detailed and comprehensive studies on the determination of the fate and transport of microplastics in the air as well as their health effects are needed.

Air quality improvement from COVID-19 lockdown: evidence from China.

Abstract: As we move through 2020, our world has been transformed by the spread of COVID-19 in many aspects. A large number of cities across the world entered "sleep mode" sequentially due to the stay-at-home or lockdown policies. This study exploits the impact of pandemic-induced human mobility restrictions, as the response to COVID-19 pandemic, on the urban air quality across China. Different from the "traditional" difference-in-differences analysis, a human mobility-based difference-in-differences method is used to quantify the effect of intracity mobility reductions on air quality across 325 cities in China. The model shows that the air quality index (AQI) experiences a 12.2% larger reduction in the cities with lockdown. Moreover, this reduction effect varies with different types of air pollutants (PM2.5, PM10, SO2, NO2, and CO decreased by 13.1%, 15.3%, 4%, 3.3%, and 3.3%, respectively). The heterogeneity analysis in terms of different types of cities shows that the effect is greater in northern, higher income, more industrialized cities, and more economically active cities. We also estimate the subsequent health benefits following such improvement, and the expected averted premature deaths due to air pollution declines are around 26,385 to 38,977 during the sample period. These findings illuminate a new light on the role of a policy intervention in the pollution emission, while also providing a roadmap for future research on the pollution effect of COVID-19 pandemic.

Impacts of nationwide lockdown due to COVID-19 outbreak on air quality in Bangladesh: a spatiotemporal analysis.

Abstract: In Bangladesh, a nationwide lockdown was imposed on 26 March 2020, due to the COVID-19 pandemic. Due to restricted emissions, it was hypothesized that the air quality has been improved during lockdown throughout the country. The study is intended to assess the impact of nationwide lockdown measures on air quality in Bangladesh. We analyzed satellite data for four different air pollutants (NO2, SO2, CO, and O3) to assess the changes in the atmospheric concentrations of pollutants in major cities as well as across the country. In this study, the concentrations of NO2, SO2, CO, and O3 from 1 February to 30 May of the year 2019 and 2020 were analyzed. The average SO2 and NO2 concentrations were decreased by 43 and 40%, respectively, while tropospheric O3 were found to be increased with a maximum of > 7%. Among the major cities, Dhaka, Gazipur, Chattogram, and Narayanganj were found to be more influenced by the restricted emissions. In Dhaka, NO2 and SO2 concentrations were decreased approximately by 69 and 67%, respectively. Our analysis reveals that NO2 concentrations are highly correlated with the regional COVID-19 cases (r = 0.74). The study concludes that the lockdown measures significantly reduced air pollution because of reduced vehicular and industrial emissions in Bangladesh.

The association between COVID-19 deaths and short-term ambient air pollution/meteorological condition exposure: a retrospective study from Wuhan, China.

Abstract: The emergence of coronavirus disease 2019 (COVID-19) has become a worldwide pandemic after its first outbreak in Wuhan, China. However, it remains unclear whether COVID-19 death is linked to ambient air pollutants or meteorological conditions. We collected the daily COVID-19 death number, air quality index (AQI), ambient air pollutant concentrations, and meteorological variables data of Wuhan between Jan 25 and April 7, 2020. The Pearson and Poisson regression models were used accordingly to understand the association between COVID-19 deaths and each risk factor. The daily COVID-19 deaths were positively correlated with AQI (slope = 0.4 ± 0.09, R 2 = 0.24, p < 0.01). Detailedly, PM2.5 was the only pollutant exhibiting a positive association (relative risk (RR) = 1.079, 95%CI 1.071-1.086, p < 0.01) with COVID-19 deaths. The PM10, SO2, and CO were all also significantly associated with COVID-19 deaths, but in negative pattern (p < 0.01). Among them, PM10 and CO had the highest and lowest RR, which equaled to 0.952 (95%CI 0.945-0.959) and 0.177 (95%CI 0.131-0.24), respectively. Additionally, temperature was inversely associated with COVID-19 deaths (RR = 0.861, 95%CI 0.851-0.872, p < 0.01). Contrarily, diurnal temperature range was positively associated with COVID-19 deaths (RR = 1.014, 95%CI 1.003-1.025, p < 0.05). The data suggested that PM2.5 and diurnal temperature range are tightly associated with increased COVID-19 deaths.

Inactivation times from 290 to 315 nm UVB in sunlight for SARS coronaviruses CoV and CoV-2 using OMI satellite data for the sunlit Earth.

Abstract: UVB in sunlight, 290–315 nm, can inactivate SARS CoV and SARS CoV-2 viruses on surfaces and in the air. Laboratory exposure to ultraviolet irradiance in the UVC range inactivates many viruses and bacteria in times less than 30 min. Estimated UVB inactivation doses from sunlight in J/m2 are obtained from UVC measurements and radiative transfer calculations, weighted by a virus inactivation action spectrum, using OMI satellite atmospheric data for ozone, clouds, and aerosols. For SARS CoV, using an assumed UVC dose near the mid-range of measured values, D90 = 40 J/m2, 90% inactivation times T90 are estimated for exposure to midday 10:00–14:00 direct plus diffuse sunlight and for nearby locations in the shade (diffuse UVB only). For the assumed D90 = 40 J/m2 model applicable to SARS CoV viruses, calculated estimates show that near noon 11:00–13:00 clear-sky direct sunlight gives values of T90 < 90 min for mid-latitude sites between March and September and less than 60 min for many equatorial sites for 12 months of the year. Recent direct measurements of UVB sunlight inactivation of the SARS CoV-2 virus that causes COVID-19 show shorter T90 inactivation times less than 10 min depending on latitude, season, and hour. The equivalent UVC 254 nm D90 dose for SARS CoV-2 is estimated as 3.2 ± 0.7 J/m2 for viruses on a steel mesh surface and 6.5 ± 1.4 J/m2 for viruses in a growth medium. For SARS CoV-2 clear-sky T90 on a surface ranges from 4 min in the equatorial zone to less than 30 min in a geographic area forming a near circle with solar zenith angle < 60O centered on the subsolar point for local solar times from 09:00 to 15:00 h.

Calculation of comfortable thermal conditions for Mersin urban city planning in Turkey

Abstract: Computer models that evaluate the formulas of these indices together with environmental factors and human characteristics have been created. Physiological equivalent temperature index and classification summer calculation model used for bioclimatic comfort calculations by obtaining monthly data of General Directorate of State Metrology Stations between 1972 and 2018 in Mersin city center. The results, comfortable monthly intervals, were determined and necessary suggestions were made for the people of Mersin city center in a month. In the calculations, the meteorological parameters such as surface-and-air temperature, wind speed, and relative humidity were taken into consideration. Monthly results show the bioclimatically comfortable area in September and May. There are conditions in Mersin that lead to comfortable perceptions in summer. During the cold period, different levels appear and warm and comfortable thermal conditions are observed. GIS analysis was used to determine the development of thermal perceptions over time. It was calculated between 1972 and 2018. According to these coefficients, there is a tendency to increase in PET values in the regions close to the water in Mersin and to decrease in Mersin, which is the station in rural areas, as a city station.

Emission reduction of black carbon and polycyclic aromatic hydrocarbons during COVID-19 pandemic lockdown.

Abstract: The global pandemic COVID-19 necessitated various responses throughout the world, including social distancing, use of mask, and complete lockdown. While these measures helped prevent the community spread of the virus, the resulting environmental benefits of lockdown remained mostly unnoticed. While many studies documented improvements in air quality index, very few have explored the reduction in black carbon (BC) aerosols and polycyclic aromatic hydrocarbons (PAHs) concentrations due to lockdown. In this study, we evaluated the changes in concentrations of BC, PAHs, and PM2.5 before and during the lockdown period. Our results show that lockdown resulted in a significant reduction in concentrations of these pollutants. The average mass concentration of BC, PAHs, and PM2.5 before the lockdown was 11.71 ± 3.33 μgm−3, 108.71 ± 27.77 ngm−3, and 147.65 ± 41.77 μgm−3, respectively. During the lockdown period, the concentration of BC, PAHs, and PM2.5 was 2.46 ± 0.95 μgm−3, 23.19 ± 11.21 ngm−3, and 50.31 ± 11.95 μgm−3, respectively. The diagnostic ratio analysis for source apportionment showed changes in the emission sources before and during the lockdown. The primary sources of PAHs emissions before the lockdown were biomass, coal combustion, and vehicular traffic, while during the lockdown, PAHs emissions were primarily from the combustion of biomass and coal. Similarly, before the lockdown, the BC mass concentrations came from fossil-fuel and wood-burning, while during the lockdown period, most of the BC mass concentration came from wood-burning. Human health risk assessment demonstrated a significant reduction in risk due to inhalation of PAHs and BC-contaminated air.

Temporal variability of atmospheric particulate-bound polycyclic aromatic hydrocarbons (PAHs) over central east India: sources and carcinogenic risk assessment.

Abstract: Atmospheric polycyclic aromatic hydrocarbons (PAHs) are of significant interest owing to their high potential health effects, including mutagenicity and carcinogenicity. We report 16 PAHs measured in ambient PM2.5 from June 2018 to May 2019 over three different sites located in central east India. The annual average PM2.5 mass concentrations of 97.3 ± 18.1 µg m−3, 101.9 ± 19.4 µg m−3, and 93.9 ± 20.3 µg m−3 were measured at RCI (Ranchi), GHY (Gamharia), and BKR (Bokaro), respectively. The mass concentrations at all sampling sites are relatively higher than the annual average concentration of the National Ambient Air Quality Standard. Total annual PAH concentrations (ng m−3) are found to be comparable at BKR (797.9 ± 39.1 ng m−3) and RCI (887.7 ± 38.8 ng m−3); however, a relatively higher average is observed over GHY (1015.1 ± 42.7 ng m−3). Using PAH diagnostic ratios and principal component analysis (PCA), their major sources were attributed to coal and wood combustion as well as vehicular emission of diesel and gasoline at all sampling sites. Significant seasonal variability is observed for PAH composition and mainly attributed to change in emission sources. Summer and winter compositions were found to be impacted by the transport from Indo-Gangetic Plains (IGP). However, ambient level PAHs during the post-monsoon season were impacted by mixed sources from Indo-Gangetic Plain and eastern India. These observations are supported by the analysis of back-trajectory and fire count data. The excess life time cancer risk (ELCR) values estimated for the study sites are within acceptable limits suggesting acceptable risk levels at BKR, GHY, and RCI. This study highlights the significance of ambient aerosol concentration for health risks in the pre-COVID-19 scenario.

A study on variation of atmospheric pollutants over Bhubaneswar during imposition of nationwide lockdown in India for the COVID-19 pandemic.

Abstract: The nationwide lockdown in India to flatten the pandemic COVID-19 curve has resulted in the reduction of anthropogenic emission sources to a great extent. This study reports change in air quality and its impact on the environment during the unique lockdown scenario at Bhubaneswar, a coastal smart city in east India. The urban air shows a remarkable reduction in the mean pollutant levels influenced by traffic emission viz. NOx (~ 67 %) and BC (~ 47 %) during lockdown over the pre-lockdown. Comparatively, a lower reduction of CO (~ 14 %) is attributed to the dominance of natural atmospheric chemical regulation and biogenic sources in addition to anthropogenic contributions. In addition to the lockdown, frequent rain events due to depression in the Bay of Bengal (BoB) also had a significant role in the reduction of the primary pollutants over the study site. An enhancement of secondary pollutant viz. O3 (~ 3%) with a distinct diurnal pattern was observed during the first phase of lockdown over the pre-lockdown period. An anti-correlation between O3 and NOx during pre-lockdown points to a higher O3 production potential with decreasing NOx. While a reduction in the titration of O3 due to suppression of fresh NO emissions led to accumulation of O3 in the first phase of lockdown, inhibited photochemistry due to cloudy skies as well as reduction in precursors led to lower O3 values during the later phases of lockdown.

Impacts of the COVID-19 lockdown on air quality and its association with human mortality trends in megapolis Mexico City.

Abstract: Mexico City is the second most populated city in Latin America, and it went through two partial lockdowns between April 1 and May 31, 2020, for reducing the COVID-19 propagation. The present study assessed air quality and its association with human mortality rates during the lockdown by estimating changes observed in air pollutants (CO, NO2, O3, SO2, PM10 and PM2.5) between the lockdown (April 1–May 31) and prelockdown (January 1–March 31) periods, as well as by comparing the air quality data of lockdown period with the same interval of previous 5 years (2015–2019). Concentrations of NO2 (− 29%), SO2 (− 55%) and PM10 (− 11%) declined and the contents of CO (+ 1.1%), PM2.5 (+ 19%) and O3 (+ 63%) increased during the lockdown compared to the prelockdown period. This study also estimated that NO2, SO2, CO, PM10 and PM2.5 reduced by 19–36%, and O3 enhanced by 14% compared to the average of 2015–2019. Reduction in traffic as well as less emission from vehicle exhausts led to remarkable decline in NO2, SO2 and PM10. The significant positive associations of PM2.5, CO and O3 with the numbers of COVID-19 infections and deaths, however, underscored the necessity to enforce air pollution regulations to protect human health in one of the important cities of the northern hemisphere.

Impact of novel coronavirus (COVID-19) on daily routines and air environment: evidence from Turkey.

Abstract: Turkish people are facing several problems because of the novel coronavirus (COVID-19), as the pandemic has brought about drastic changes to their daily routines. This study mainly investigates the impact of this pandemic on the daily routines of Turkish. It also unveils how COVID-19 affects the air environment. The adopted methods for data collection are based on open-ended questions and Facebook interviews as per recommended by QSR-International (2012). The sample of this study comprises of Turkish students as well as professional workers. The findings of the research show that there are eighteen different results of COVID-19 that have been identified according to the Turkish people's daily routines. Results reveal that increasing unemployment, decrease in air contamination, high stress and depression, a slowdown in the economic growth, and the tourism industry are profoundly affected due to the COVID-19 in Turkey. Furthermore, on the one hand, the consequences of the pandemic are segregated into social problems and psychological issues in daily routines. On the other hand, they have shown a positive impact on the air environment. This study concludes that, amid the COVID-19 pandemic, the lives of the people in Turkey are subject to deterioration, while the air environment of Turkey is gradually improving.

Air quality change during the COVID-19 pandemic lockdown over the Auvergne-Rhône-Alpes region, France.

Abstract: Under the rapid spread of coronavirus diseases (COVID-19) worldwide, a complete lockdown was imposed in France from March 17th to May 11th, 2020 to limit the virus spread. This lockdown affected significantly the atmospheric pollution levels due to the restrictions of human activities. In the present study, we investigate the evolution of air quality in the Auvergne-Rhone-Alpes region, focusing on nine atmospheric pollutants (NO2, NO, PM10, PM2.5, O3, VOC, CO, SO2, and isoprene). In Lyon, center of the region, the results indicated that NO2, NO, and CO levels were reduced by 67%, 78%, and 62%, respectively, resulting in a decrease in road traffic by 80%. However, O3, PM10, and PM2.5 were increased by 105%, 23%, and 53%, respectively, during the lockdown. The increase in ozone is explained by the dropping in NO and other gases linked to human activity, which consume ozone. Thus, the increase of solar radiation, sunshine, temperature, and humidity promoted the O3 formation during the lockdown. Besides, rising temperature enhances the BVOC emissions such as isoprene. In addition, volatile organic component (VOC) and SO2 remain almost stable and oxidation of these species leads to the formation of ozone and organic aerosol, which also explains the increase in PM during the lockdown. This study shows the contribution of atmospheric photochemistry to air pollution.

Association of COVID-19 distribution with air quality, sociodemographic factors, and comorbidities: an ecological study of US states.

Abstract: This ecological study investigated the association between COVID-19 distribution and air quality index (AQI), comorbidities and sociodemographic factors in the USA. The AQI factors included in the study are total AQI, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide (NO2). Other demographic, socioeconomic, and geographic variables were included as covariates. The correlations of COVID-19 variables-proportion of cases and deaths in each population, as well as case fatality rate with independent variables were determined by Pearson and Spearman correlation and multiple linear regression analyses. The results revealed that AQI-NO2, population density, longitude, gross domestic product per capita, median age, total death of disease, and pneumonia per population were significantly associated with the COVID-19 variables (P < 0.05). Air pollutants, especially NO2 in the US case, could be addressed as an important factor linked with COVID-19 susceptibility and mortality.

Air quality data series estimation based on machine learning approaches for urban environments

Abstract: Air pollution is one of the main environmental problems in residential areas. In many cases, the effects of air pollution on human health can be prevented by forecasting the air quality in the next day. In order to predict the 1 day in advance air quality index (AQI) of Orumiyeh city, the hybrid single decomposition (HSD) and hybrid two-phase decomposition (HTPD) models were used. In the first step, the AQI data were decomposed by complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and was hybridized with general regression neural network (GRNN) and extreme learning machine (ELM) as HSD models. In the second step, using variational mode decomposition (VMD) technique the results of the first intrinsic mode functions (IMFs) of CEEMDAN model were decomposed into nine VMs and were predicted by GRNN and ELM models to obtain IMF1. Finally, in the third step, GRNN and ELM were used again to predict the IMFS as HTPD models. Results showed that in predicting AQI series data by HSD models both CEEMDAN-ELM and CEEMDAN-GRNN models were similarly accurate. Among all the models used, the accuracy of CEEMDAN-VMD-GRNN as the HTPD model was the highest in the training phase (R2 = 0.98, RMSE = 4.13 and MAE = 2.99) and in the testing phase (R2 = 0.74, RMSE = 5.45 and MAE = 3.87). It can be concluded that HTPD models have more accurate results to predict AQI data compared with HSD models.

Impact of COVID -19 pandemic lockdown on distribution of inorganic pollutants in selected cities of Nigeria.

Abstract: The COVID-19 global pandemic has necessitated some drastic measures to curb its spread. Several countries around the world instituted partial or total lockdown as part of the control measures for the pandemic. This presented a unique opportunity to study air pollution under reduced human activities. In this study, we investigated the impact of the lockdown on air pollution in three highly populated and industrious cities in Nigeria. Compared with historical mean values, NO2 levels increased marginally by 0.3% and 12% in Lagos and Kaduna respectively. However, the city of Port Harcourt saw a decrease of 1.1% and 215.5% in NO2 and SO2 levels respectively. Elevated levels of O3 were observed during the period of lockdown. Our result suggests that there are other sources of air pollution apart from transportation and industrial sources. Our findings showed that the COVID-19-induced lockdown was responsible for a decrease in NO2 levels in two of the locations studied. These results presents an opportunity for country wide policies to mitigate the impact of air pollution on the health of citizens.

A support vector machine model to forecast ground-level PM2.5 in a highly populated city with a complex terrain

Abstract: Physical models are essential to describe the behavior of pollutants especially in high latitudes, and they have been regarded as immensely precise. In the tropics, however, these models have lower accuracy due to the absence of a simple theoretical framework to describe tropical dynamics. Hence, the development of predictive nonlinear models with machine learning has increased, as they are able to quantify the different dynamic processes regarding air quality and to obtain accurate predictions in less computational time than their physical counterpart. This study constructs and evaluates a support vector machine (SVM) to forecast ground-level PM2.5 in a populated city with complex topography. The simulations were built for days with red Air Quality Index (AQI), to assess whether the model could represent the behavior of days with high values and data with fast and substantial changes in the PM2.5 tendency. The SVM is trained with an air quality monitoring network using the radial basis function kernel. A spatial interpolation is also conducted to determine and describe the behavior of the AQI in the city of Bogota. This work uses statistical scores (root mean square error (9.302 μg/m3), mean BIAS (1.405 μg/m3), index of agreement (0.732), and correlation coefficient (0.654)) to validate the capability of an SVM model of simulating, with high precision, the concentrations of PM2.5 in a city with complex terrain in the short term and also to demonstrate the potential of the SVM to be used as a forecast model in other tropical cities.

Effect of COVID-19 outbreak on urban health and environment.

Abstract: The WHO announced coronavirus disease a Public Health Emergency on 30 January 2020, and it spreads across the whole planet. Aftermath of outbreak of this disease at the global level is more frightening and panicking than anyone's worst nightmare. With more than 23 mln positive coronavirus cases and more than 800,000 causalities all over the world, the potential of this virus cannot be undermined. This pandemic has victimized all human beings residing on 209 countries and territories of the world. It emerged as an unbeatable global challenge that the world has never witnessed before. Consequently, the affected countries have sealed their borders and made populations reside in their homes until the pandemic is over. Thus, the victims of coronavirus are not only the ones who are exposed to it but also the ones who are affected by the lockdown imposed by the governments. The paper aims to evaluate the effect of COVID-19 on air pollution of various countries. Papers indicating the relationship between air pollution levels and lockdown measures are analyzed. The dramatic U-turn from environmental degradation is definitely a silver lining in these black clouds. This paper reviews the repercussions of the pandemic in some nations, while war-like preparations continue to fight it. COVID-19 has dramatically improved the quality of air. Also, it has greatly affected the economy of various countries due to lockdown.

Biological contaminants in the indoor air environment and their impacts on human health.

Abstract: Indoor air environment contains a complex mixture of biological contaminants such as bacteria, fungi, viruses, algae, insects, and their by-products such as endotoxins, mycotoxins, volatile organic compounds, etc. Biological contaminants have been categorized according to whether they are allergenic, infectious, capable of inducing toxic or inflammatory responses in human beings. At present, there is a lack of awareness about biological contamination in the indoor environment and their potential sources for the spreading of various infections. Therefore, this review article examines the association of biological contaminants with human health, and it will also provide in-depth knowledge of various biological contaminants present in different places such as residential areas, hospitals, offices, schools, etc. Moreover, qualitative and quantitative data of bio-contaminants in various indoor environments such as schools, hospitals, residential houses, etc. have also been derived from the recent literature survey.

Influence of lockdown caused by the COVID-19 pandemic on air pollution and carcinogenic content of particulate matter observed in Croatia.

Abstract: Due to the pandemic of SARS-CoV-2 in Croatia, all unnecessary activities were prohibited during the designated lockdown period (March–May 2020). With reduced human activity, levels of some air pollutants decreased. In this study, mass concentrations of the PM1 particle fraction (particulate matter with an equivalent aerodynamic diameter < 1 μm) and polycyclic aromatic hydrocarbons (PAHs) in PM1 and NO2 were measured and compared with concentrations measured in the same period the year before. Air pollutant concentrations were measured at two measuring sites: urban residential and urban traffic. Our results show a concentration decrease by 35% for NO2 and PM1 particles and by 26% for total PAHs at the traffic measuring site. At the residential measuring site, only concentrations of NO2 decreased slightly, but PM1 particles and PAHs were similar to the year before.

Systematics of atmospheric environment monitoring in China via satellite remote sensing

Abstract: Satellite remote sensing is increasingly applied in the field of environmental protection, especially in atmospheric monitoring. Here, a comprehensive review is provided on the development, limits, and prospects of remote sensing of the atmospheric environment in China. Firstly, the paper introduced the principle of detection of three types of atmospheric parameters and commonly used satellite data. Secondly, advances in retrieval methods, product validations, and applications in China were summarized. This included aerosol, particulate matter, haze, straw burning, dust storm, gaseous pollutant (sulfur dioxide, nitrogen dioxide, and ozone), greenhouse gas (carbon dioxide and methane), and air quality monitoring and control. Thirdly, products widely applied in monitoring the atmospheric environment in China were analyzed. Finally, the outlooks for future development were discussed. This included application of China’s satellite data, enhancement of the accuracy of air pollution monitoring, and services for environmental management.

Viral respiratory infections and air pollutants

Abstract: Air pollution is a public health issue of global importance and a risk factor for developing cardiorespiratory diseases. These contaminants induce reactive oxygen species (ROS) and increased pro-inflammatory cytokines such as IL-1β, IL-6, and IL-8, triggering the inflammatory response that alters cell and tissue homeostasis and facilitates the development of diseases. The effects of air pollutants such as ozone, particulate matter (PM10, PM2.5, and PM0.1), and indoor air pollutants on respiratory health have been widely reported. For instance, epidemiological and experimental studies have shown associations between hospital admissions for individual diseases and increased air pollutant levels. This review describes the association and relationships between exposure to air pollutants and respiratory viral infections, especially those caused by the respiratory syncytial virus and influenza virus. The evidence suggests that exposure to air contaminants induces inflammatory states, modulates the immune system, and increases molecules' expression that favors respiratory viruses' pathogenesis and affects the respiratory system. However, the mechanisms underlying these interactions have not yet been fully elucidated, so it is necessary to develop new studies to obtain information that will allow health and policy decisions to be made for the adequate control of respiratory infections, especially in the most vulnerable population, during periods of maximum air pollution.

Prediction of the concentrations of PM1, PM2.5, PM4, and PM10 by using the hybrid dragonfly-SVM algorithm

Abstract: This paper aims to model the daily evolution for particulate matter concentrations of less than 1 μm (PM1), 2.5 μm (PM2.5), 4 μm (PM4), 10 μm (PM10), and PM-Total, based on weather factors (WF), by using the hybrid dragonfly-SVMr algorithm. Hourly data on atmospheric concentrations of PMi and WF were recorded simultaneously at an automatic air quality check station located at an urban site in Algiers, using the fine dust measurement device, Fidas® 200. The number of data collected on PM was 540 measurements. In this study, the meta-heuristic dragonfly algorithm (DA) was used in order to select the optimal hyper-parameters of the Support Vector Machine model. For this, a MATLAB® program based on the dragonfly optimization algorithm coupled with the SVM regression algorithm has been written in order to correlate for the PMi concentrations. The obtained results show that the established model has good predictive performance, with a coefficient of determination R2 = 0.98 and root of the mean square error RMSE = 1.9261.

The impact of immigration on human capital and carbon dioxide emissions in the USA: an empirical investigation

Abstract: The phenomenon of migration is an essential component in designing sustainable development policies, and it is valuable to investigate the multidimensional effects of migration. While the current literature focuses more on the economic, social, and political impacts of migration, its impact on the environment is relatively less explored. This paper, which aims to overcome this shortcoming in the literature, examines the relationship between immigration, human capital, economic growth, financial development, energy, and environmental pollution in the USA with the STIRPAT model. We follow unit root and structural breaks co-integration tests, then parameter estimates and causality analysis. According to the results, while migration, financial development, and energy consumption have an increasing effect on environmental pollution, economic growth has a decreasing impact on pollution. There is no statistically significant relationship between human capital and the environment. On the other hand, immigration contributes to human capital accumulation in the long run.

Effects of COVID-19 pandemic control measures on air pollution in Lima metropolitan area, Peru in South America.

Abstract: The sanitary measures implemented to control and prevent an increase in infections due to the COVID-19 pandemic have produced an improvement in the air quality of many urban areas around the world. We assessed air quality during the COVID-19 pandemic for particulate matter (PM2.5 and PM10), NO2 and O3 in in metropolitan area of Lima, Peru between pre-lockdown period (February 1 and March 15 of 2020), historical period (March 16 to April 30 2017–2019) and lockdown period (March 16 to April 30, 2020). The complete national lockdown that was implemented in Peru produced statistically significant reductions in the in-air pollutant (PM10 (-40% and -58%), PM2.5 (-31% and -43%) and NO2 (-46% and -48%)), as recorded by the by the ground-based air quality monitoring network throughout the metropolitan area, compared with the corresponding concentrations for the previous weeks and over the same period for 2017–2019. Analysis of the spatial Distribution of satellite data also show decreases in the concentrations of PM10, PM2.5 and NO2 as a result of the containment measures and suspension of activities implemented by the Peruvian government. The concentrations of O3 significantly increased (11% and 170%) as a result of the decrease in the concentration of NO2, confirming that the study area is a hydrocarbon-limited system, as previously reported. The results obtained contribute to the assessment by the regulatory agencies of the possible strategies of control and monitoring of air pollution in the study area.

Particulate matter (PM 10 and PM 2.5 ) concentrations during a Saharan dust episode in Istanbul

Abstract: Istanbul, the biggest city of Turkey, is in a common route for air parcels. Air pollutants are carried over the city from Asian, African, and European continents. Sahara Desert, the largest dust source on earth, affects Turkey’s air qualities substantially due to millions of tons of mineral dust being transported from the African continent towards Turkey every year. Although the effect of Saharan dust transportation on PM10 concentrations in Turkey was examined many times, its effect on PM2.5 concentrations has not been studied yet sufficiently. In February 2015, Istanbul experienced a Saharan dust episode and during this event the concentrations of particulate matter rose to very high levels. This study focuses on particulate matter concentrations (PM10 and PM2.5) during this Saharan dust episode to better understand the effect of dust transportation on Istanbul’s air quality. HYSPLIT trajectory model, satellite products, and air quality monitoring data from ground observations were utilized. We show that the PM10 concentrations increased significantly during the dust episode while PM2.5 concentrations didn’t increase considerably. There was only a slight rise in the values of PM2.5. The significant increase for the PM10 values can be explained by the higher gravitational settling velocities of coarse particles in the atmosphere.

PM2.5 chemical composition and geographical origin of air masses in Cape Town, South Africa

Abstract: PM2.5 in the indoor and outdoor environment has been linked in epidemiology studies to the symptoms, hospital admissions and development of numerous health outcomes including death. The study was conducted during April 2017 and April 2018. PM2.5 samples were collected over 24 h and every third day. The mean PM2.5 level was 13.4 μg m−3 (range: 1.17–39.1 μg m−3). PM2.5 levels exceeded the daily World Health Organization air quality guideline (25 μg m−3) on 14 occasions. The mean soot level was 1.38 m−1 × 10−5 (range: 0 to 5.38 m−1 × 10−5). Cl−, NO3−, SO42−, Al, Ca, Fe, Mg, Na and Zn were detected in the PM2.5 samples. The geographical origin of air masses that passed Cape Town was estimated using the Hybrid Single Particle Lagrangian Integrated Trajectory software. Four air masses were identified in the cluster analysis: Atlantic-Ocean-WSW, Atlantic-Ocean-SW, Atlantic-Ocean-SSW and Indian-Ocean. The population of Cape Town may experience various health outcomes from the outdoor exposure to PM2.5 and the chemical composition of PM2.5.

Car restriction policies for better urban health: a low emission zone in Madrid, Spain

Abstract: The design of most cities prioritizes the use of motorized vehicles, having a negative effect on urban health. A major concern in the European Union (EU) is air pollution, especially nitrogen dioxide (NO2), which causes many inhabitants health problems and decreases the quality of life. A non-expensive way to reduce pollutants is implementing road restriction policies, as the creation of low emission zones. In this work, we analyze the case of Madrid Central, a low emission zone deployed in Madrid, Spain. We evaluate if it was effective to reduce air pollutants and if there were a side effect, as pollution displacement, during its application. Drawing on open data, we analyze air quality at different points of the city, before and during the application of this measure. Taking into account the EU directives in terms of what healthy air means, we consider three metrics: (a) the trend of NO2 concentration in the air in both periods, (b) the difference between the NO2 concentration during both periods, and (c) the percentage of time in which the population is exposed to air with NO2 concentration under a specific threshold (healthy air as defined by the EU). According to the results, Madrid Central significantly reduces the NO2 concentration in the air and does not produce pollution displacement. Thus, the population breathes healthy air during more time, and there is a positive effect on the whole city.

Particulate matter and foliar retention: current knowledge and implications for urban greening

Abstract: Suspended particulate matter (PM) constitutes a major problem in urban areas. Air purification of polluted cities is critical for protecting the increasing population. PM deposited on leaves can be an effective method of air quality amelioration. However, there are several factors involved, either favoring or hindering the PM capture. In this revision, we synthesized the current information about PM plant retention: plant features, consequences, and the relation with the urban environment. We also propose to use a knowledge-based planning framework to designate zones with similar characteristics across the city and to select the vegetation according to the necessities of each of these zones. Since available information regarding the best plant species to retain PM is sometimes contradictory, the application of a knowledge-based framework could be useful to focus future research on field conditions.