Role In PM2 Research Articles

Insights into multidimensional transport flux from vertical observation and numerical simulation in two cities in North China

This study represents the first quantitative evaluation of pollution transport budget within the boundary layer of typical cities in the Beijing-Tianjin-Hebei (BTH) region from the perspective of horizontal and vertical exchanges and further discusses the impact of the atmospheric boundary layer (ABL)-free troposphere (FT) exchange on concentration of fine particulate matter (PM2.5) within the ABL during heavy pollution. From the perspective of the transport flux balance relationship, differences in pollution transport characteristics between the two cities is mainly reflected in the ABL-FT exchange effect. The FT mainly flowed into the ABL in BJ, while in SJZ, the outflow from the ABL to the FT was more intense. Combined with an analysis of vertical wind profile distribution, BJ was found to be more susceptible to the influence of northwest cold high prevailing in winter, while sinking of strong cold air allowed the FT flowing into the ABL influence the vertical exchange over BJ. In addition, we selected a typical pollution event for targeted analysis to understand mechanistic details of the influence of ABL-FT exchange on the pollution event. These results showed that ABL-FT interaction played an important role in PM2.5 concentration within the ABL during heavy pollution. Especially in the early stage of heavy pollution, FT transport contributed as much as 82.74% of PM2.5 within the ABL. These findings are significant for improving our understanding of pollution transport characteristics within the boundary layer and the effect of ABL-FT exchange on air quality.

Mechanistic study of PM2.5 reduction by kaolin-limestone compound additive in pulverized coal combustion

A novel compound additive prepared from kaolin and limestone shows promising prospects for in-furnace abatement of combustion PM2.5 (particulate matter with aerodynamic diameters equal to or less than 2.5 μm). However, the mechanisms need further clarification. These were investigated by combustion of a low-alkali coal on a high-temperature drop tube furnace (DTF). Combustion experiments with the kaolin-limestone additive were carried out at 1300 °C and in simulated air. Baseline tests of individual additives (i.e., kaolin and limestone) were also performed for comparison. Particulate samples were collected and classified by a Dekati low pressure impactor (DLPI). Heat-treated additive samples were also collected by DLPI and filter. They were characterized by various techniques such as laser diffraction particle sizing, X-ray diffraction (XRD), and field emission scanning electron microscopy equipped with energy dispersive spectrometry (FESEM-EDS). The results show that the addition of kaolin or limestone suppresses the emission of aerosols between 0.3 and 2.5 μm (PM0.3-2.5), but unexpectedly increases that of ultrafine aerosols less than 0.3 μm (PM0.3). The latter is primarily attributed to the carryover of ultrafine additive particles. Due to different effects on the two particle size fractions, the individual additives are found to have overall insignificant effects on PM2.5 emission. In striking contrast, the addition of the kaolin-limestone additive leads to an apparent reduction of both PM0.3 (∼46%) and PM0.3-2.5 (∼37%). As a result, a significantly high reduction of PM2.5 by ∼ 40% is achieved. The superior performance of the compound additive, compared with the individual additives, is accounted for by enhanced interactions between kaolin-limestone, additive-vapor, and additive-ash. These mechanisms, together with the collision-induced particle capture mechanism proposed previously, are believed to play key roles in PM2.5 abatement in real boilers when the compound additive and fuel are premixed.

PM2.5 aggravates airway inflammation in asthmatic mice: activating NF-κB via MyD88 signaling pathway

ABSTRACT The role of PM2.5 in the bronchial asthma remains unclear. In this study, the deficient mice of TLR4-/-, TLR2-/- and MyD88 -/- were used to establish asthma model. The effects of PM2.5 on the inflammatory response in lung tissue of these mice were observed. PM2.5 increased alveolar macrophages and neutrophils, up-regulated the IL-12 and KC expression in WT mice, but down-regulated their levels in TLR2 -/-, TLR4 -/- and MyD88 -/- mice. OVA+PM2.5 stimulated neutrophil count in WT mice, but it decreased in TLR2 -/- and TLR4 -/- mice. OVA+PM2.5 also increased the Eotaxin, IL-5, IL-13 and MCP-3 expression levels, and OVA specific IgE and IgG1 in serum also increased in WT group. PM2.5 may activate NF-κB through the TLR2/TLR4/MyD88 signaling pathway and aggravate allergic inflammation of lung in asthmatic mice. The microelements in PM2.5 granules, such as lipopolysaccharide, may be an important factor in the high incidence of asthma.

The impacts of VOCs on PM2.5 increasing via their chemical losses estimates: A case study in a typical industrial city of China

Volatile organic compounds (VOCs) have been explicitly required to be controlled by national or local governments to tackle heavy PM2.5 pollution in China. However, the role of VOCs chemistry in PM2.5 is still far away from being fully understood. In this study, we selected a typically industrialized city of China, conducted VOCs online measurements in July and December of 2020, estimated VOCs chemical losses, and explored their impacts on PM2.5 in the real atmosphere. Our measurements totally detected the mixing ratios of 53 VOCs species, sum of which reaching 20.8 ± 9.1 ppb and 45.5 ± 19.8 ppb in July and December respectively. Based on the change in the relative abundance of various VOCs species with different reactivity, daily OH exposure and daily O3 exposure (molecules·s·cm−3) were estimated, respectively with the mean value of 11.0 × 1010 and 5.2 × 1015 in July, 5.9 × 1010 and 3.1 × 1015 in December. Thus, there were about 6.7 ± 3.2 ppb and 11.1 ± 5.0 ppb VOCs chemically lost in July and December, with the average loss ratio of 29.7% and 19.3% in respective. In July, PM2.5 in the range of 20–60 μg m−3 positively responded to VOCs loss ratios, and high PM2.5 values were always accompanied by higher VOCs losses instead of high CO levels; but their relationship became negative in December when PM2.5 in the range of 40–150 μg m−3, and extremely high PM2.5 values happened in high CO conditions instead of high VOCs losses conditions. Moreover, PM2.5 measurements in this city also showed an apparent upward trend in OC/EC with PM2.5 in summer, but a slight downward trend in winter. These all indicated that in the conditions of stronger solar radiations (summer) and low-middle aerosol loads, VOCs chemistry played the important role in PM2.5 increasing through contributing SOA; but in the conditions of lower solar radiations (winter) and heavy aerosol loads, VOCs chemistry was greatly weakened and had the minor impact on PM2.5 increasing. The measure involving VOCs reduction to alleviate PM2.5 pollution in winter needs to be cautiously considered and examined.

Contributions of Ammonia to High Concentrations of PM2.5 in an Urban Area

Atmospheric ammonia (NH3) plays a critical role in PM2.5 pollution. Data on atmospheric NH3 are scanty; thus, the role of NH3 in the formation of ammonium ions (NH4+) in various environments is understudied. Herein, we measured concentrations of NH3, PM2.5, and its water-soluble SO42−, NO3−, and NH4+ ions (SNA) at an urban site in Jeonju, South Korea from May 2019 to April 2020. During the measurement period, the average concentrations of NH3 and PM2.5 were 10.5 ± 4.8 ppb and 24.0 ± 12.8 μg/m3, respectively, and SNA amounted to 4.3 ± 3.1, 4.4 ± 4.9, and 1.6 ± 1.8 μg/m3, respectively. A three-dimensional photochemical model analysis revealed that a major portion of NH3, more than 88%, originated from Korea. The enhancement of the ammonium-to-total ratio of NH3, NHX (NHR = [NH4+]/[NH4+] + [NH3]) was observed up to ~0.61 during the increase of PM2.5 concentration (PM2.5 ≥ 25 μg/m3) under low temperature and high relative humidity conditions, particularly in winter. The PM2.5 and SNA concentrations increased exponentially as NHR increased, indicating that NH3 contributed significantly to SNA formation by gas-to-particle conversion. Our study provided experimental evidence that atmospheric NH3 in the urban area significantly contributed to SNA formation through gas-to-particle conversion during PM2.5 pollution episodes.

Impacts of Emission Reduction Technological Changes on China’s City-Level PM2.5 Concentration Based on Sustainable Development

As an important field for human activities, cities play a critical role in PM2.5 reductions. Among the determinants for PM2.5 concentration, technological progress is considered to exhibit significant inhibitory effects. Although most extant research has focused on energy technologies or total factor productivity, due to limitations in data and methods, few scholars have focused on emission reduction technological changes at a city-level scale. Therefore, based on the combination of k-means clustering and the log-mean Divisia index method, this study estimates and explores the impact of PM2.5 emission reduction technology (PME) on the temporal changes and spatial differences of 262 Chinese cities’ PM2.5 concentration during 2003–2017. The findings show the following: (1) although the results based on econometric methods indicate that emission reduction technological changes decreased China’s city-level PM2.5 concentration, there were turning points in the yearly impacts, indicating that the improvements to emission reduction efficiency were not stable; (2) compared with PME, energy intensity played a more stable role in PM2.5 emissions reductions, implying that the improvement of energy efficiency was still very important in controlling PM2.5 concentrations; (3) based on the classified groups after clustering, most cities’ PME contributed to negative differences, but the PME of a small number of cities was very weak to largely lower the average level of their group; and (4) distributions of the spatial decomposition of the three classified groups were stable in the period of 2003–2017, implying that the catch-up and transcendence effects of PME within the group were limited. Thus, policymakers should focus on the impact of different policies on PME differences between cities.

COVID-19 mortality and exposure to airborne PM2.5: A lag time correlation

COVID-19 has escalated into one of the most serious crises in the 21st Century. Given the rapid spread of SARS-CoV-2 and its high mortality rate, here we investigate the impact and relationship of airborne PM2.5 to COVID-19 mortality. Previous studies have indicated that PM2.5 has a positive relationship with the spread of COVID-19. To gain insights into the delayed effect of PM2.5 concentration (μgm−3) on mortality, we focused on the role of PM2.5 in Wuhan City in China and COVID-19 during the period December 27, 2019 to April 7, 2020. We also considered the possible impact of various meteorological factors such as temperature, precipitation, wind speed, atmospheric pressure and precipitation on pollutant levels. The results from the Pearson's correlation coefficient analyses reveal that the population exposed to higher levels of PM2.5 pollution are susceptible to COVID-19 mortality with a lag time of >18 days. By establishing a generalized additive model, the delayed effect of PM2.5 on the death toll of COVID-19 was verified. A negative correction was identified between temperature and number of COVID-19 deaths, whereas atmospheric pressure exhibits a positive correlation with deaths, both with a significant lag effect. The results from our study suggest that these epidemiological relationships may contribute to the understanding of the COVID-19 pandemic and provide insights for public health strategies.

The risk of admission acute heart failure in ST-elevation myocardial infarction patients and air pollution with PM2.5

Abstract Introduction Air pollution, in particular exposure to particulate matter fine particles of less than 2.5 microns in diameter (PM2.5), increases the risk of cardiovascular events. Short-term exposure (hours to few days prior) to increased PM2.5 levels even may help trigger ST-elevation myocardial infarction (STEMI) and heart failure exacerbation in susceptible individuals. The risk of vascular events is increased even in exposures below the current European air quality limit values (mean annual levels for PM2.5 less than 10μg/m3, 24-hour mean level less than 25μg/m3). Purpose To evaluate predictive role of PM2.5 levels ≥20 μg/m3 one day prior to hospital admission for the risk of admission acute heart failure (AAHF) in STEMI patients. Methods In 290 STEMI patients (100 women, 190 men, mean age 65.5±12.9 years), treated by primary percutaneous coronary intervention (PPCI) in 2018, we retrospectively registered the AAHF, defined as classes II-IV by Killip Kimbal classification. Additionally, we registered admission clinical data, potentially contributing to AAHF in STEMI patients such as gender, age ≥65 years, prior resuscitation, admission cTnI ≥5 μg/L (normal levels up to 0.045 μg/L), comorbidities, time to PPCI, and mean daily levels of PM2.5 ≥20 μg/m3 one day before admission. Mean daily, freely available, levels of PM2.5 were measured and registered by Chemical analytic laboratory of Environmental agency of Republic Slovenia. We evaluated the predictive role of admission data for admission AHF in STEMI patients. Results AAHF was observed in 34.5% of STEMI patients with the mean daily PM2.5 level 15.7±10.9 μg/m3 on the day before admission. PPCI was performed in 92.1% of all STEMI patients, in AAHF in 87.1% and in non-AAHF patients in 94.7% (p=0.037). AAHF in comparison to non-AAHF was associated significantly with female gender (50.5% vs 25.9%, p<0.001), age over 65 years (71.3% vs 45%, p<0.001), prior diabetes (33.7% vs 14.8%, p<0.001), left bundle branch block (LBBB) (10.9% vs 0.5%, <0.001), admission cTnI ≥5 μg/L (46.7% vs 25.9%, p<0.001) and mean daily levels of PM2.5 ≥20 μg/m3 one day before admission (31.7% vs 19%, p=0.020), but nonsignificantly with arterial hypertension, prior myocardial infarction, anterior STEMI and time to PPCI. Logistic regression demonstrated that significant independent predictors of AAHF were age over 65 years (OR 3.349, 95% CI 1.787 to 6.277, p<0.001), prior diabetes (OR 2.934, 95% CI 1.478 to 5.821, p=0.002), admission LBBB (OR 10.526, 95% CI 1.181 to 93.787, p=0.03), prior resuscitation (OR 3.221, 95% CI 1.336 to 7.761, p=0.009), admission cTnI ≥5μg/l (OR 2.984, 95% CI 1.618 to 5.502, p<0.001) and mean daily levels of PM2.5 ≥20 μg/m3 (OR 2.096, 95% CI 1.045 to 4.218, p=0.038) one day before admission. Conclusion Mean daily levels of PM2.5 ≥20μg/m3 one day before admission were among significant independent predictors of AAHF in STEMI patients. Funding Acknowledgement Type of funding sources: None.

A machine learning model to estimate ambient PM2.5 concentrations in industrialized highveld region of South Africa

Exposure to fine particulate matter (PM2.5) has been linked to a substantial disease burden globally, yet little has been done to estimate the population health risks of PM2.5 in South Africa due to the lack of high-resolution PM2.5 exposure estimates. We developed a random forest model to estimate daily PM2.5 concentrations at 1 km2 resolution in and around industrialized Gauteng Province, South Africa, by combining satellite aerosol optical depth (AOD), meteorology, land use, and socioeconomic data. We then compared PM2.5 concentrations in the study domain before and after the implementation of the new national air quality standards. We aimed to test whether machine learning models are suitable for regions with sparse ground observations such as South Africa and which predictors played important roles in PM2.5 modeling. The cross-validation R2 and Root Mean Square Error of our model was 0.80 and 9.40 μg/m3, respectively. Satellite AOD, seasonal indicator, total precipitation, and population were among the most important predictors. Model-estimated PM2.5 levels successfully captured the temporal pattern recorded by ground observations. Spatially, the highest annual PM2.5 concentration appeared in central and northern Gauteng, including northern Johannesburg and the city of Tshwane. Since the 2016 changes in national PM2.5 standards, PM2.5 concentrations have decreased in most of our study region, although levels in Johannesburg and its surrounding areas have remained relatively constant. This is anadvanced PM2.5 model for South Africa with high prediction accuracy at the daily level and at a relatively high spatial resolution. Our study provided a reference for predictor selection, and our results can be used for a variety of purposes, including epidemiological research, burden of disease assessments, and policy evaluation.

S-adenosylmethionine decarboxylase 1 and its related spermidine synthesis mediate PM2.5 exposure-induced neuronal apoptosis

PM2.5 exposure is considered harmful to central nerve system, while the specific biochemical mechanism underlying is still unrevealed. Neuronal apoptosis is believed the crucial event in pathogenesis of neurodegenerative diseases, but evidence supporting neuronal apoptosis as the mechanism for PM2.5 exposure induced neuronal injury is insufficient. S-adenosylmethionine decarboxylase 1 (AMD1) and its related spermidine synthesis have been shown to associate with cellular apoptosis, but its role in PM2.5 exposure induced neuronal apoptosis was rarely reported. The current study was aimed to better understand contribution of AMD1 activity and spermidine in PM2.5 exposure induced neuronal apoptosis. Sixteen C57BL/6 male mice were randomly divided and kept into ambient PM2.5 chamber or filtered air chamber for 6 months to establish the mouse model of whole-body ambient PM2.5 chronic exposure. In parallel, PC12 cells and primary hippocampal neurons were applied for various concentrations of PM2.5 treatment (0, 25, 50, 100, 200, and 400 μg/mL) to explore the possible cellular and molecular mechanism which may be critically involved in the process. Results showed that PM2.5 exposure triggered neuronal apoptosis with increased expression of Bax/Bcl-2 and cleaved caspase-3. PM2.5 exposure reduced AMD1 expression and spermidine synthesis. AMD1 inhibition could mimic PM2.5 exposure induced neuronal apoptosis. Spermidine supplementation rescued against neurotoxicity and inhibited PM2.5 induced apoptosis via impaired depolarization of mitochondrial membrane potential and reduced mitochondrial apoptosis related proteins. In summary, our work demonstrated that exposure to PM2.5 led to neuronal apoptosis, which may be the key event in the process of air pollution induced neurodegenerative diseases. AMD1 and spermidine associated with neuronal apoptosis induced by PM2.5 exposure, which was at least partially dependent on mitochondria mediated pathway.

Chemical characterization and source identification of PM2.5 in Luoyang after the clean air actions

Luoyang is a typical heavy industrial city in China, with a coal-dominated energy structure and serious air pollution. Following the implementation of the clean air actions, the physicochemical characteristics and sources of PM2.5 have changed. A comprehensive study of PM2.5 was conducted from October 16, 2019 to January 23, 2020 to evaluate the effectiveness of previous control measures and further to provide theory basis for more effective policies in the future. Results showed that the aerosol pollution in Luoyang in autumn and winter is still serious with the average concentration of 91.1 μg/m3, although a large reduction (46.9%) since 2014. With the contribution of nitrate increased from 12.5% to 25.1% and sulfate decreased from 16.7% to 11.2%, aerosol pollution has changed from sulfate-dominate to nitrate-dominate. High NO3−/SO42− ratio and the increasing of NO3−/SO42− ratio with the aggravation of pollution indicating vehicle exhaust playing an increasingly important role in PM2.5 pollution in Luoyang, especially in the haze processes. Secondary inorganic ions contributed significantly to the enhancement of PM2.5 during the pollution period. The high value of Cl−/Na+ and EC concentration indicate coal combustion in Luoyang is still serious. The top three contributor sources were secondary inorganic aerosols (33.3%), coal combustion (13.6%), and industrial emissions (13.4%). Close-range transport from the western and northeastern directions were more important factors in air pollution in Luoyang during the sampling period. It is necessary to strengthen the control of coal combustion and reduce vehicle emissions in future policies.

Transcriptome-wide profiling discover: PM2.5 aggravates airway dysfunction through epithelial barrier damage regulated by Stanniocalcin 2 in an OVA-induced model

BackgroundEpidemiologic evidence suggests that PM2.5 exposure aggravates asthma, but the molecular mechanisms are not fully discovered. MethodsOvalbumin (OVA)-induced mice exposed to PM2.5 were constructed. Pathological staining and immunofluorescence were performed in in vivo study. Gene set enrichment analysis (GSEA) was performed to identify the pathway involved in asthma severity by using U-BIOPRED data (human bronchial biopsies) and RNA-seq data (Beas-2B cells treated with PM2.5). Lentiviruses transfection, Real-time qPCR, immunofluorescence staining and trans-epithelial electrical resistance (TEER) measurement were performed for mechanism exploration in vitro. ResultsPM2.5 exposure aggravated airway inflammation and mucus secretion in OVA-induced mice. Based on transcriptome analysis of mild-to-severe asthma from human bronchial biopsies, gene set enrichment analysis (GSEA) showed that up-regulated reactive oxygen species (ROS) pathway gene set and down-regulated apical junction gene set correlated with asthma severity. Consistent with the analysis of mild-to-severe asthma, after PM2.5 exposure, the ROS pathway in Beas-2B cells was up-regulated with the down-regulation of apical junction. The expression levels of genes involved in the specific gene sets were validated by using qPCR. The mRNA levels of junction genes, ZO-1, E-cadherin and Occludin, were significantly decreased in cells exposed to PM2.5. Moreover, it confirmed that inhibition of ROS recovered the expression levels of E-cadherin, Occludin and ZO-1, and ameliorated inflammation and mucus secretion in airway in OVA-induced mice exposed to PM2.5. Meanwhile, ROS level was elevated by PM2.5. By checking trans-epithelial electrical resistance (TEER) value, we also found that epithelial barrier was damaged after PM2.5 exposure. Importantly, Stanniocalcin 2 (STC2) was identified as a key gene in regulation of epithelial barrier. It showed that STC2 expression was up-regulated by PM2.5, which was recovered by NAC as well. Over-expression of STC2 could decrease the expression levels of ZO-1, Occludin and E-cadherin. Contrarily, suppression of STC2 could increase the expression levels of ZO-1, Occludin and E-cadherin reduced by PM2.5. ConclusionsBy using transcriptome analysis, we revealed that STC2 played a key role in PM2.5 aggravated airway dysfunction through regulation of epithelial barrier in OVA-induced mice.

Study on the Influence of Socio-economic Activities on PM2.5 in Henan Province Based on Principal Component Regression Analysis

In the context of increasingly serious haze pollution in Henan Province, which is harmful to human health, it is important to clarify the impact of socio-economic activities on PM2.5, the key indicator of haze. Here, based on the analysis of the spatio-temporal variation characteristics of PM2.5 concentration in Henan Province during 2015-2018, this paper combined the data of ten socio-economic indicators and adopted the principal component regression (PCR) analysis method to explore the influence of socio-economic activities on PM2.5 concentration. The results showed that the annual average concentration of PM2.5 during 2015-2018 ranged from 59.0 μg/m3 to 83.8 μg/m3, with a decreasing rate of -5.955 μg/(m3·a). Spatial distribution of PM2.5 showed “high in the north and low in the south”, and the PM2.5 concentration in Anyang, Zhengzhou, Jiaozuo and Xinxiang were more than 75μg/m3, indicating a slightly polluted state. Among all the socio-economic indicators, gross domestic product (GDP), population density (PD), industrial value-added (IVA) and actual utilization of foreign capital (AUFC) played main positive roles in PM2.5 from 2015 to 2018 but with a diminishing trend, and afforestation area (AA) played a negative role in PM2.5. In addition, the effect of the sown area of major crops (SAMC) on PM2.5 was negative with enhanced before 2018 and reversed in 2018. Our findings can provide a basis for the government to formulate PM2.5 control policies.

Fine particulate matter induces airway inflammation bydisturbing the balance between Th1/Th2 and regulation of GATA3 and Runx3 expression in BALB/c mice.

The present study aimed to examine the effects of 2.5 µm particulate matter (PM2.5) on airway inflammation and to investigate the possible underlying mechanism. Specifically, the focus was on the imbalance of T helper (Th)1/Th2 cells and the dysregulated expression of transcription factors, including trans-acting T cell-specific transcription factor 3 (GATA3), runt-related transcription factor 3 (Runx3) and T-box transcription factor TBX21 (T-bet). In this study, ambient PM2.5 was collected and analyzed, male BALB/c mice were sensitized and treated with PBS, ovalbumin (OVA), PM2.5 or OVA + PM2.5. The effects of PM2.5 alone or PM2.5 + OVA on immunopathological changes, the expression of transcription factors GATA3, Runx3 and T-bet, and the imbalance of Th1/Th2 were investigated. It was found that PM2.5 + OVA co-exposure significantly enhanced inflammatory cell infiltration, increased higher tracheal secretions in lung tissue and upregulated respiratory resistance response to acetylcholine compared with PM2.5 or OVA single exposure and control groups. In addition, higher protein and mRNA expression levels of Th2 inflammatory mediators interleukin (IL)-4, IL-5 and IL-13 in bronchoalveolar lavage fluid were observed in PM2.5 + OVA treated mice, whereas the expression levels of GATA3 and STAT6 were exhibited in mice exposed to OVA + PM2.5 compared with the OVA and PM2.5 groups. By contrast, PM2.5 exposure decreased the protein and mRNA expression levels of Th1 cytokine interferon-γ and transcription factors Runx3 and T-bet, especially among asthmatic mice, different from OVA group, PM2.5 exposure only failed to influence the expression of T-bet. To conclude, PM2.5 exposure evoked the allergic airway inflammation response, especially in the asthmatic mouse model and led to Th1/Th2 imbalance. These effects worked mainly by upregulating GATA3 and downregulating Runx3. These data suggested that Runx3 may play an important role in PM2.5-aggravated asthma in BALB/c mice.

New Normal Role in PM2.5 Reduction in Bangkok

The world has been exposed to the Coronavirus Disease 2019 (COVID-19) since late 2019. A global pandemic has shifted health concerns from air pollution effects to novel coronavirus disease, similarly to those in Bangkok. Although Bangkokians have experienced severe PM2.5 conditions since the last quarter of 2017, the related agencies have failed to elucidate the crisis. This has been because the fundamental air quality management is focused on controlling emissions. The Thai government has sluggishly determined the situations that lead to the inability to clean up its air. How are air pollution and disease linked? This article points to the importance of source management. The lockdown measures revealed reduced traffic rate and PM2.5 concentrations. Such a close relationship has shed insights of the consequences of working from home (WFH). The link between disease and air pollution includes (i) WFH regulation is one specific way to prevent the transmission of disease, (ii) this guideline decreases traffic congestion in an urban city which is one path of diminished pollution discharge and (iii) then noticeably followed by PM2.5 reductions. Again, the magnitude of source control is crucial. Reducing pollutions from traffic by means of WFH has illustrated this accomplishment. In the midst of this crisis, moving to a new normal role supports remaining protected from both air pollution and the pandemic. Nevertheless, the sustainability of transportation control in an overcrowded city like Bangkok should be considered as a vital pathway to tackle air pollution.

Urban and air pollution: a multi-city study of long-term effects of urban landscape patterns on air quality trends

Most air pollution research has focused on assessing the urban landscape effects of pollutants in megacities, little is known about their associations in small- to mid-sized cities. Considering that the biggest urban growth is projected to occur in these smaller-scale cities, this empirical study identifies the key urban form determinants of decadal-long fine particulate matter (PM2.5) trends in all 626 Chinese cities at the county level and above. As the first study of its kind, this study comprehensively examines the urban form effects on air quality in cities of different population sizes, at different development levels, and in different spatial-autocorrelation positions. Results demonstrate that the urban form evolution has long-term effects on PM2.5 level, but the dominant factors shift over the urbanization stages: area metrics play a role in PM2.5 trends of small-sized cities at the early urban development stage, whereas aggregation metrics determine such trends mostly in mid-sized cities. For large cities exhibiting a higher degree of urbanization, the spatial connectedness of urban patches is positively associated with long-term PM2.5 level increases. We suggest that, depending on the city’s developmental stage, different aspects of the urban form should be emphasized to achieve long-term clean air goals.

Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.

Investigating the Impacts of Urbanization on PM2.5 Pollution in the Yangtze River Delta of China: A Spatial Panel Data Approach

Urbanization is a key determinant of fine particulate matter (PM2.5) pollution variability. However, there is a limited understanding of different urbanization factors’ roles in PM2.5 pollution. Using satellite-derived PM2.5 data from 2002 to 2017, we investigated the spatiotemporal evolution and the spatial autocorrelation of PM2.5 pollution in the Yangtze River Delta (YRD) region. Afterwards, the impacts of three urbanization factors (population urbanization, land urbanization and economic urbanization) on PM2.5 pollution were estimated by a spatial Durbin panel data model (SDM). Obtained results showed that: (i) PM2.5 pollution was larger in the north than in the south of YRD; (ii) Lianyungang and Yancheng cities had significant increasing trends in PM2.5 pollution from 2002 to 2017; (iii) the regional median center of PM2.5 pollution was observed in the Nanjing city, with gradual shifting to the northwest during the 16-year period; (iv) PM2.5 pollution showed significant and positive spatial autocorrelation and spillover effect; (v) population urbanization contributed more to the increase in PM2.5 pollution than land urbanization, while economic urbanization had no significant impact. The present study highlights the impacts of three urbanization factors on PM2.5 pollution which represent valuable and relevant information for air pollution control and urban planning.

Chemical and Biological Compositions Associated with Ambient Respirable Particulate Matter: a Review

Particulate matter (PM) is defined as a mixture of solid and/or liquid particles that remain separately dispersed in air. PM is not a pollutant by itself but a complex and dynamic combination of compound particles with biological and chemical origins. However, fine PM (PM2.5) seems to be incriminated in the respiratory system and poses a severe threat to human health. Several reviews focused on chemistry segments because they mainly contribute to fine PM concentration. Biological elements in PM2.5 should also be considered because they cause multiple allergies and respiratory illnesses. This review has selected articles by following predefined criteria and demonstrated that the biological and chemical parts of fine particles play a significant role in PM2.5 concentration. In addition, justification on the origin or sources of biological and chemical compositions and their effects on health become a concern in this review. Lastly, this review can provide knowledge that can be a useful tool for researchers, designers, engineers and policymakers to consider for further action.

Exploring the cause of PM2.5 pollution episodes in a cold metropolis in China

Harbin, a cold metropolis of China, frequently endures fine particles (PM2.5) pollution during its long heating seasons, which has almost become the main environmental issue. To better understand pollution causes, multifaceted factors including the meteorology conditions, secondary transformation, source apportionment and regional transportation, were analyzed based on the definition of three pollution levels and eight pollution episodes. The results showed that chemical species varied dynamically and followed similar trends to PM2.5, and secondary organic carbon and nitrate played more significant driving roles in PM2.5 as the pollution level increased. Five sources were apportioned using the positive matrix factorization model, and the order of importance for the entire study period was as follows: secondary aerosol, traffic emissions, biomass burning, mineral dust, and coal combustion. The PM2.5 in Harbin is mainly affected by transportation in the Harbin-Changchun megalopolis and slightly affected by long-distance transmission from the northwestern region of Harbin. A pollution episode in the fall was quite significant, as it was characterized by long duration time and extremely high pollutant levels, and was most likely attributed to extensive emissions from biomass burning and enhanced secondary transformation. The pollution episodes in winter were characterized by enhanced heterogeneous reactions and weakened photochemical reactions, which were especially sensitive to synoptic variations, and most likely induced by high relative humidity (>60%), low wind speed (3 m/s), suppressed planetary boundary layer height (<200 m), and strengthened inversion layer under the control of high-pressure systems. Meanwhile, the episodes in spring were characterized by high proportions of mineral dust, chlorine, and potassium, which was mostly attributed to the prevailing dust events, stronger biomass burning activities, and favorable transportation under low-pressure systems.