Understanding Of Air Pollution Research Articles

Analysis of the Impact of Meteorological Factors on Predicting Air Quality in South Tangerang City using Random Forest Method

Air pollution has become one of the most significant environmental problems in many cities throughout the world, which can endanger public health and the environment. Understanding the impact of meteorological conditions on air quality is very important to understanding air pollution patterns. This study investigates the influence of meteorological variables on air quality predictions in South Tangerang City, Indonesia, using the Random Forest method. Modeling is carried out by building two scenarios, namely predictions using meteorological variables and predictions without meteorological variables. Prediction performance analysis is measured using MAE, MSE, RMSE, R-square, and accuracy. The accuracy results of the research show that predictions without meteorological variables provide good prediction results with a value of 86.42%, but predictions with meteorological variables have better performance with a value reaching 98.99%. The largest error values from each model were 2.58 MAE, 71.82 MSE, and 8.4747 RMSE obtained in prediction modeling without meteorological variables, while the smallest error values were obtained in prediction modeling using meteorological variables, namely 0.00, 0.01, and 0.0219, respectively, for MAE, MSE, and RMSE. This research contributes to a better understanding of the relationship between meteorology and air pollution and air quality in urban areas and helps develop targeted mitigation strategies to improve air quality and public health, especially in South Tangerang City and the surrounding area.

Factors Affecting the Indoor Air Quality and Occupants’ Thermal Comfort in Urban Agglomeration Regions in the Hot and Humid Climate of Pakistan

The World Air Quality Index indicates that Pakistan ranks as the third most polluted country, regarding the average (Particulate Matter) PM2.5 concentration, which is 14.2 times higher than the World Health Organization’s annual air quality guideline. It is crucial to implement a program aimed at reducing PM2.5 levels in Pakistan’s urban areas. This review paper highlights the importance of indoor air pollution in urban regions such as Lahore, Faisalabad, Gujranwala, Rawalpindi, and Karachi, while also considering the effects of outdoor air temperature on occupants’ thermal comfort. The study aims to evaluate past methodological approaches to enhance indoor air quality in buildings. The main research question is to address whether there are statistical correlations between the PM2.5 and the operative air temperature and whether other indoor climatic variables have an impact on the thermal comfort assessment in densely built urban agglomeration regions in Pakistan. A systematic review analysis method was employed to investigate the effects of particulate matter (PM2.5), carbon oxides (COx), nitrogen oxides (NOx), sulfur oxides (SOx), and volatile organic compounds (VOCs) on residents’ health. The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) protocol guided the identification of key terms and the extraction of cited studies. The literature review incorporated a combination of descriptive research methods to inform the research context regarding both ambient and indoor air quality, providing a theoretical and methodological framework for understanding air pollution and its mitigation in various global contexts. The study found a marginally significant relationship between the PM2.5 operative air temperature and occupants’ overall temperature satisfaction, Ordinal Regression (OR) = 0.958 (95%—Confidence Interval (CI) [0.918, 1.000]), p = 0.050, Nagelkerke − Regression (R2) = 0.042. The study contributes to research on the development of an evidence-based thermal comfort assessment benchmark criteria for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database version 2.1.

Potential Early Effect Biomarkers for Ambient Air Pollution Related Mental Disorders.

Air pollution is one of the greatest environmental risks to health, with 99% of the world's population living where the World Health Organization's air quality guidelines were not met. In addition to the respiratory and cardiovascular systems, the brain is another potential target of air pollution. Population- and experiment-based studies have shown that air pollution may affect mental health through direct or indirect biological pathways. The evidence for mental hazards associated with air pollution has been well documented. However, previous reviews mainly focused on epidemiological associations of air pollution with some specific mental disorders or possible biological mechanisms. A systematic review is absent for early effect biomarkers for characterizing mental health hazards associated with ambient air pollution, which can be used for early warning of related mental disorders and identifying susceptible populations at high risk. This review summarizes possible biomarkers involved in oxidative stress, inflammation, and epigenetic changes linking air pollution and mental disorders, as well as genetic susceptibility biomarkers. These biomarkers may provide a better understanding of air pollution's adverse effects on mental disorders and provide future research direction in this arena.

Deep learning models for air quality forecasting based on spatiotemporal characteristics of data

The distribution of air-borne pollutants is governed by complex fluid dynamics processes involving convection and diffusion. The process is further affected by the characteristics of emission sources, meteorological parameters, socioeconomic factors, and land use patterns. Compared to deterministic and probabilistic air quality forecasting methods, data driven modeling of air quality parameters can address the large degree of freedom in air quality influencing parameters as well as offer interpretability and understanding of air pollutants' distribution at an increased spatial and temporal resolutions. This study focuses on the citywide prediction of air quality index (AQI) based on observations of pollutant concentrations, meteorological parameters, and spatiotemporal data. The study area includes Ansan city in South Korea, which has been observed as a hotspot for high concentrations of particulate matter. The air quality and meteorological were collected from 16 monitoring stations located in Ansan city. A detailed spatiotemporal analysis was performed to investigate the correlation between AQI records at the air quality monitoring stations. Based on strong spatiotemporal correlations observed between stations, several deep learning (DL) models were proposed, and their performance was investigated for different scenarios. It was observed that the selection of appropriate DL models should be based on (1) understanding of the underlying fluid dynamics process that control pollutant distribution and (2) spatiotemporal characteristics of data. Additionally, the complexity of DL models does not always guarantee the accuracy of the forecasts, and simple models can give good performance if the predictors are selected carefully to reflect the underlying physical process.

The development and application of a novel helicopter-based airborne platform for near-surface monitoring and sampling of atmospheric pollutants

This study presents a novel approach utilising helicopters as platforms for real-time monitoring of air pollutants and routine canister sampling to enhance our understanding of air pollution in the Greater Bay Area (GBA). By employing this method, local spatial and vertical distribution of various air pollutants (including CO, NO, NO2, O3, PM2.5 and VOCs) in Hong Kong could be obtained within hours for fast snapshots of air pollution.The investigation involved hovering ascent and descent operations above Tap Mun Island, revealing no indication of self-contamination from engine exhaust during the hovering process. The analysis of air pollutant spatial distribution in and around Hong Kong through multiple trips showed higher concentrations of O3 and PM2.5 in the northern region on days with episodic pollution, while urban areas exhibited elevated levels of NO2 and CO concentration. In contrast, Tap Mun Island as the background area demonstrated relatively low pollutant concentrations. The vertical distribution of concentrations of VOC species with high ozone formation potential revealed minor variations at sampling altitudes of 500 ft and 1000 ft over the waters around Hong Kong. The novel monitoring protocol using helicopters as platforms proves to be an effective approach for pollution episode investigations, offering valuable insights in the formation mechanisms and transport pathways of O3. The findings of the heterogenous spatial distribution of O3 and its precursors underscore the significance of ongoing monitoring efforts and policy development to combat air pollution in the dynamic GBA and similar regions worldwide.

Geochemical characteristics and socioeconomic associations of carbonaceous aerosols in coal-fueled cities with significant seasonal pollution pattern

Carbonaceous aerosols, comprising organic carbon (OC) and elemental carbon (EC), are critical component of fine particulate matter (PM2.5), with diverse impacts on air quality and human health. This study investigated the concentrations and seasonal patterns of carbonaceous species in PM2.5 during both the heating season (January 2021) and non-heating season (July 2021) in three coal-fueled cities in northern China, as well as the differences in carbonaceous aerosols and their associations with socioeconomic parameters in cities situated on either side of the “Hu Line” in China. The results showed that, owing to intensified coal combustion and unfavorable meteorological conditions, levels of OC, EC, and OC/EC ratios were higher in winter compared to summer. Moreover, the presence of dust (DU) and light pollution (LP) days resulted in elevated OC levels but decreased EC levels. The Char-EC/Soot-EC ratios were highest during LP, followed by CL and DU. A source apportionment analysis demonstrated that coal burning, vehicle exhaust, road dust, and biomass burning were the primary contributors to carbonaceous aerosols, as confirmed by diagnostic ratios, Char-EC/Soot-EC ratios, and PCA analysis. Furthermore, our study found that carbonaceous aerosols concentrations and source apportionment primarily varied with diurnal and seasonal trends and different pollution types. Additionally, at the national scale, population density and urban green space exhibited a positive correlation with OC/EC ratios (p < 0.05), while energy consumption per unit of GDP showed a negative correlation (p < 0.05). The observation that OC/EC ratios were lower in coal-fueled cities than in economy-based cities suggests a more severe pollution scenario. These findings highlight the importance of comprehending of the seasonal variation and chemical characteristics of carbonaceous aerosol for understanding air pollution sources and characteristics, which is essential for both air quality management and human health.

Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the “dual carbon” goal

ABSTRACT Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a “seesaw” phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a “U-shaped”, and O3 showed an inverted “U-shaped” seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve “double control and double reduction” of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research. Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the “14th Five-Year Plan”, the construction of the “Cheng-Yu Dual-City Economic Circle” and the “Dual-Carbon” goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward. Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve “double control and double reduction” of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality. In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.

Secondary aerosol formation in incense burning particles by O3 and OH oxidation via single particle mixing state analysis

Incense burning is a common religious activity that emits abundant gaseous and particulate pollutants into the atmosphere. During their atmospheric lifetime, these gases and particles are subjected to oxidation, leading to the formation of secondary pollutants. We examined the oxidation of incense burning plumes under O3 exposure and dark condition using an oxidation flow reactor connected to a single particle aerosol mass spectrometer (SPAMS). Nitrate formation was observed in incense burning particles, mainly attributable to the ozonolysis of nitrogen-containing organic compounds. With UV on, nitrate formation was significantly enhanced, likely due to HNO3/HNO2/NOx uptake triggered by OH chemistry, which is more effective than ozone oxidation. The extent of nitrate formation is insensitive to O3 and OH exposure, possibly due to the diffusion limitation on interfacial uptake. The O3-UV-aged particles are more oxygenated and functionalized than O3-Dark-aged particles. Oxalate and malonate, two typical secondary organic aerosol (SOA) components, were found in O3-UV-aged particles. Our work reveals that nitrate, accompanied by SOA, can rapidly form in incense-burning particles upon photochemical oxidation in the atmosphere, which could deepen our understanding of air pollution caused by religious activities.

An integrated view of correlated emissions of greenhouse gases and air pollutants in China

BackgroundAir pollution in China has raised great concerns due to its adverse effects on air quality, human health, and climate. Emissions of air pollutants (APs) are inherently linked with CO2 emissions through fossil-energy consumption. Knowledge of the characteristics of APs and CO2 emissions and their relationships is fundamentally important in the pursuit of co-benefits in addressing air quality and climate issues in China. However, the linkages and interactions between APs and CO2 in China are not well understood.ResultsHere, we conducted an ensemble study of six bottom-up inventories to identify the underlying drivers of APs and CO2 emissions growth and to explore their linkages in China. The results showed that, during 1980–2015, the power and industry sectors contributed 61–79% to China’s overall emissions of CO2, NOx, and SO2. In addition, the residential and industrial sectors were large emitters (77–85%) of PM10, PM2.5, CO, BC, and OC. The emissions of CH4, N2O and NH3 were dominated by the agriculture sector (46–82%) during 1980–2015, while the share of CH4 emissions in the energy sector increased since 2010. During 1980–2015, APs and greenhouse gases (GHGs) emissions from residential sources generally decreased over time, while the transportation sector increased its impact on recent emissions, particularly for NOx and NMVOC. Since implementation of stringent pollution control measures and accompanying technological improvements in 2013, China has effectively limited pollution emissions (e.g., growth rates of –10% per year for PM and –20% for SO2) and slowed down the increasing trend of carbon emissions from the power and industrial sectors. We also found that areas with high emissions of CO, NOx, NMVOC, and SO2 also emitted large amounts of CO2, which demonstrates the possible common sources of APs and GHGs. Moreover, we found significant correlations between CO2 and APs (e.g., NOx, CO, SO2, and PM) emissions in the top 5% high-emitting grid cells, with more than 60% common grid cells during 2010–2015.ConclusionsWe found significant correlation in spatial and temporal aspects for CO2, and NOx, CO, SO2, and PM emissions in China. We targeted sectorial and spatial APs and GHGs emission hot-spots, which help for management and policy-making of collaborative reductions of them. This comprehensive analysis over 6 datasets improves our understanding of APs and GHGs emissions in China during the period of rapid industrialization from 1980 to 2015. This study helps elucidate the linkages between APs and CO2 from an integrated perspective, and provides insights for future synergistic emissions reduction.

An assessment of seasonal, monthly and diurnal variations of ambient air quality in the Gurugram city (Haryana)

Gurugram is emerging as one of India's most advanced cities. The combined impact of industrial and vehicular emissions makes the environment toxic. Recently, Gurugram has experienced severe air quality. In the present work, an assessment of seasonal, monthly, and diurnal variations of ambient air quality was carried out in Gurugram during the period of March 2021 to 2022 February. Seasonal and monthly concentrations of key air pollutants like particulate matter (PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO) and ozone (O3) were examined at Vikas sadan, Gwal Pahari and Teri Gram in Gurugram city to study the most polluted seasons and months. Significantly higher mean concentrations of Particulate matter PM2.5 (406.94 μgm−3) and NO2 (353.96ppb) were seen during the colder months and seasons. O3 showed a consistent trend with variations during the year, with the highest concentration in winter (106.35µg/m3). PM2.5 and NO2 concentrations during the night were greater for all seasons when compared to diurnal values. O3 concentrations displayed diurnal tendencies that were the opposite of those of NO2 concentrations. The highest concentrations of ambient PM2.5, NO2, and CO were observed at the Vikas Sadan Monitoring Station. While the NISE Gwal Pahari station showed greater O3 values. The findings highlight the necessity of efficient air pollution control in Gurugram. To prevent public exposure to air pollutants, preventive measures like green spaces, using public transport, etc. must be adopted. The study contributes to a better understanding of air pollution by seasonal, monthly and diurnal assessment in the city of Gurugram.

The effects of meteorology and biomass burning on urban air quality: The case of Bangkok

Bangkok, one of the biggest metropolitan cities in Asia, has been experiencing poor (PM10 > 50 μg/m3 annual average) air quality for decades. Major sources of air pollution are traffic emissions, biomass burning, and non-combustible sources. In this study, the impact of meteorology and biomass burning on the concentration of particulate matter was assessed. Data from three monitoring stations and remotely sensed fire count between 2017 and 2020 was used to investigate the association. Moreover, the spatiotemporal pattern of aerosol optical depth (AOD) and fire count derived from remotely sensed data were investigated to observe their association. This study found that temperature, relative humidity, rainfall, wind speed, and wind direction have a significant negative relationship with particulate matter concentration. In contrast, atmospheric pressure and fire count have a significant positive correlation with particulate matter concentration. Moreover, the pollution rose diagram for particulate matter indicated that the northeasterly wind is the prevailing wind direction that carries the most pollutants. Furthermore, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and AOD indicated that biomass burning in neighboring regions significantly (p < 0.05) affected the particulate matter concentration in Bangkok. Multiple linear regression (MLR) analysis established that atmospheric pressure has the highest negative impact on the city air quality, followed by biomass burning, while heavy rainstorms were the most substantial parameter that reduced particulate matter concentration. Taken together, these findings highlight the importance of meteorological factors in understanding air pollution mechanisms in Bangkok. Equally important, the insights gained from this study may assist in addressing the long-range transport of air pollutants from biomass burning, which requires a coordinated engagement with neighboring countries.

Estimation of Ground-Level PM2.5 Concentration at Night in Beijing-Tianjin-Hebei Region with NPP/VIIRS Day/Night Band

Reliable measures of nighttime atmospheric fine particulate matter (PM2.5) concentrations are essential for monitoring their continuous diurnal variation. Here, we proposed a night PM2.5 concentration estimation (NightPMES) model based on the random forest model. This model integrates the radiance of the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB), moon phase angle, and meteorological data. We collected 13486 samples from the Beijing Tianjin–Hebei (BTH) region. The determination coefficient (R2) of the NightPMES model was 0.82, the root mean square error (RMSE) was 16.67 µg/m3, and the mean absolute error (MAE) was 10.20 µg/m3. The applicability analysis of the moon phase angles indicated that the amount of data available increased by 60% while the accuracy remained relatively unchanged. In the seasonal model, the meteorological factors and DNB radiance were found to be the primary factors affecting the PM2.5 concentration in different seasons. In conclusion, this study provided a method for estimating nighttime PM2.5 concentration that will improve our understanding of air pollution and associated trends in PM2.5 variation.

Characterization of fine particulate matter from indoor cooking with solid biomass fuels.

Household burning of solid biomass fuels emits pollution particles that are a huge health risk factor, especially in low-income countries (LICs) such as those in Sub-Saharan Africa. In epidemiological studies, indoor exposure is often more challenging to assess than outdoor exposure. Laboratory studies of solid biomass fuels, performed under real-life conditions, are an important path toward improved exposure assessments. Using on- and offline measurement techniques, particulate matter (PM) from the most commonly used solid biomass fuels (charcoal, wood, dung, and crops residue) was characterized in laboratory settings using a way of burning the fuels and an air exchange rate that is representative of real-world settings in low-income countries. All the fuels generated emissions that resulted in concentrations which by far exceed both the annual and the 24-hour-average WHO guidelines for healthy air. Fuels with lower energy density, such as dung, emitted orders of magnitude more than, for example, charcoal. The vast majority of the emitted particles were smaller than 300 nm, indicating high deposition in the alveoli tract. The chemical composition of the indoor pollution changes over time, with organic particle emissions often peaking early in the stove operation. The chemical composition of the emitted PM is different for different biomass fuels, which is important to consider both in toxicological studies and in source apportionment efforts. For example, dung and wood yield higher organic aerosol emissions, and for dung, nitrogen content in the organic PM fraction is higher than for the other fuels. We show that aerosol mass spectrometry can be used to differentiate stove-related emissions from fuel, accelerant, and incense. We argue that further emission studies, targeting, for example, vehicles relevant for LICs and trash burning, coupled with field observations of chemical composition, would advance our understanding of air pollution in LIC. We believe this to be a necessary step for improved air quality policy.

The association between air pollutants, meteorological factors and tuberculosis cases in Beijing, China: A seven-year time series study

BackgroundTuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing. ObjectiveThe purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB. MethodsData on the daily case of TB in Beijing during 2014–2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM10, PM2.5, SO2, NO2, CO and O3, were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing. ResultsIn the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 μg/m3 increase in NO2 in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 μg/m3 increase in O3 in lag 1 week (ER: −1.2%; 95% CI: −1.8%, −0.5%), every 5 °C increase in average temperature (ER: −1.7%; 95% CI: −2.9%, −0.4%) and every 10% increase in average relative humidity (ER: −0.4%; 95% CI: −0.8%, −0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO2, O3, average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM2.5, SO2, sunshine duration and TB cases. ConclusionOur findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.

Tropical modulation of East Asia air pollution

Understanding air pollution in East Asia is of great importance given its high population density and serious air pollution problems during winter. Here, we show that the day-to-day variability of East Asia air pollution, during the recent 21-year winters, is remotely influenced by the Madden–Julian Oscillation (MJO), a dominant mode of subseasonal variability in the tropics. In particular, the concentration of particulate matter with aerodynamic diameter less than 10 micron (PM10) becomes significantly high when the tropical convections are suppressed over the Indian Ocean (MJO phase 5–6), and becomes significantly low when those convections are enhanced (MJO phase 1–2). The station-averaged PM10 difference between these two MJO phases reaches up to 15% of daily PM10 variability, indicating that MJO is partly responsible for wintertime PM10 variability in East Asia. This finding helps to better understanding the wintertime PM10 variability in East Asia and monitoring high PM10 days.

Challenges Associated with Air Pollution in Sustainable City Development: Case of New Delhi and New York

Urbanization has advanced many lives but at the same time, it has degraded the natural environment in many layers be it air, water, or land. One such consequence has been air pollution. Air pollution has plagued the cities and has been one of the biggest obstacles to sustainability. Hence, it is crucial to understand, manage and mitigate the challenges associated with air Pollution in the development of sustainable cities. The study will begin by understanding air pollution, the correlation between the environment and sustainable development, and the current scenario of air pollution in India and the world. Further, it shall dig deeper into the challenges associated with air pollution along with Resource Planning and Mitigation and comprehend the case studies of New Delhi and New York. The paper shall later present the modes to improve the present and future scenarios of air pollution and conclude via an equitable solution for battling air pollution in India which shall involve both government reforms and the living style of people. This study stands valuable in perceiving the adversities of air pollution which affect sustainable city planning and development and will be helpful in suggesting mitigation strategies by the researchers.

Airborne Nanoparticles (PM0.1) in Southeast Asian Cities: A Review

PM0.1 (particles with a diameter ≤ 0.1 µm), nanoparticles (NPs), or ultrafine particles (UFPs) were interchangeably used in the scientific communities. PM0.1 originated from both natural and human sources; however, PM0.1 and its effects on the environment, visibility, and human health to understanding air pollution levels, sources, and impacts in Southeast Asia (SEA) countries continue to be challenging. The concentrations of PM0.1 in most SEA countries are much worse than in western countries’ environments. A further motivation of this reviewed article is to provide a critical synthesis of the current knowledge and study of ambient PM0.1 in SEA cities. The primary influence of characteristics of PM0.1 appears to be local sources, including biomass burning and motor vehicles. Continuous monitoring of PM0.1 in mass and number concentration should be further understood. A critical review is of great importance to facilitating air pollution control policies and predicting the behavior of PM0.1 in SEA.

Urban air pollution characteristics and associations with pre-school children respiratory health in four cities of Central China

The focus of this study was on the associations between air pollution, outdoor activities and symptoms of wheeze and rhinitis for pre-school children over Wuhan and surrounding cities. Air pollutants had downward trends over the study region from 2015 to 2020. Sulfur dioxide (SO2) content decreased significantly. Particulate matter was concentrated on the north side of the study area and nitrogen dioxide (NO2) was concentrated near Wuhan urban, while the distribution of ozone (O3) was relatively uniform. Odds Ratio (OR) showed that an increase in NO2 was associated with a high incidence of rhinitis, with an OR of 1.043 (1.025, 1.062 95% confidence interval). Reduction of O3 was associated with remissions of rhinitis symptoms in spring and autumn. The living environment is an important factor. Living near lakes was associated with the incidence of wheeze and living near roads was associated with the incidence of wheeze rhinitis, respectively. Additionally, appropriate outdoor activities showed association with a low incidence of wheeze and rhinitis symptoms in this region. This research improved our understanding of air pollution, outdoor activities and pre-school children's respiratory health. It was also a guide on the design of outdoor activities and outdoor courses for pre-school children during the process of urban construction.

Enhancements in Ammonia and Methane from Agricultural Sources in the Northeastern Colorado Front Range Using Observations from a Small Research Aircraft.

Quantifying ammonia (NH3) to methane (CH4) enhancement ratios from agricultural sources is important for understanding air pollution and nitrogen deposition. The northeastern Colorado Front Range is home to concentrated animal feeding operations (CAFOs) that produce large emissions of NH3 and CH4. Isolating enhancements of NH3 and CH4 in this region due to agriculture is complicated because CAFOs are often located within regions of oil and natural gas (O&NG) extraction that are a major source of CH4 and other alkanes. Here, we utilize a small research aircraft to collect in situ 1 Hz measurements of gas-phase NH3, CH4, and ethane (C2H6) downwind of CAFOs during three flights conducted in November 2019. Enhancements in NH3 and CH4 are distinguishable up to 10 km downwind of CAFOs with the most concentrated portions of the plumes typically below 0.25 km AGL. We demonstrate that NH3 and C2H6 can be jointly used to separate near-source enhancements in CH4 from agriculture and O&NG. Molar enhancement ratios of NH3 to CH4 are quantified for individual CAFOs in this region, and they range from 0.8 to 2.7 ppbv ppbv-1. A multivariate regression model produces enhancement ratios and quantitative regional source contributions that are consistent with prior studies.

The importance of understanding air pollution in nursing practice

Heather Henry explains how this environmental threat is affecting the nation's health