Associating airborne particulates and human health: Exploring possibilities: Comment on: Kim, Ki-Hyun, Kabir, E. and Kabir, S. 2015. A review on the human health impact of airborne particulate matter. Environment International 74 (2015) 136-143

Development of an automatic measurement system using atmospheric pressure photoionization ultrahigh-resolution mass spectrometry and application for on-line analysis of particulate matter

On-line chemical characterization of atmospheric particulate matter (PM) with soft ionization technique and ultrahigh-resolution Mass Spectrometry (UHRMS) provides molecular information of organic constituents in real time. Here we describe the development and application of an automatic measurement system that incorporates PM2.5 sampling, thermal desorption, atmospheric pressure photoionization, and UHRMS analysis. Molecular formulas of detected organic compounds were deducted from the accurate (±10 ppm) molecular weights obtained at a mass resolution of 100,000, allowing the identification of small organic compounds in PM2.5. Detection efficiencies of 28 standard compounds were determined and we found a high sensitivity and selectivity towards organic amines with limits of detection below 10 pg. As a proof of principle, PM2.5 samples collected off-line in winter in the urban area of Beijing were analyzed using the Ionization Module and HRMS of the system. The automatic system was then applied to conduct on-line measurements during the summer time at a time resolution of 2 hr. The detected organic compounds comprised mainly CHON and CHN compounds below 350 m/z. Pronounced seasonal variations in elemental composition were observed with shorter carbon backbones and higher O/C ratios in summer than that in winter. This result is consistent with stronger photochemical reactions and thus a higher oxidation state of organics in summer. Diurnal variation in signal intensity of each formula provides crucial information to reveal its source and formation pathway. In summary, the automatic measurement system serves as an important tool for the on-line characterization and identification of organic species in PM2.5.

How diversification of products impact emissions in China: a provincial perspective

Currently, global warming and air pollution are the world's most urgent issues partly caused by carbon dioxide (CO2) and sulfur dioxide (SO2) emissions, and prompt actions are needed to address these global concerns. Sustainable development cannot be attained until we reverse the negative impact of economic factors on the quality of the environment. It is noteworthy to offer a new indication on whether and how the empirical liaison between product diversification and environmental degradation evolved in China from 2008 to 2019. Product diversification (PD) is a remedy for reducing environmental degradation (ED). It is a crucial component of energy demand, which a significant impact on reducing energy consumption and ED. The purpose of this study is to investigate the impact of PD on ED in China using the provincial panel dataset. Employing the fixed effects-Driscoll-Kraay standard errors (FE-DKSE) and feasible generalized least squares (FGLS) methods, we discover an inverted U-shaped link between PD and ED. The control variable urbanization (URB) and technological innovation (TI) reduce ED significantly. However, industry value added (IVA) and energy consumption (EC) promote ED. Our results are robust with the addition of various controls in all models. The policy implication from our findings is that, to achieve a target of carbon neutrality, countries should adopt the product diversification strategy.

Temporal variability, meteorological influences, and long-range transport of atmospheric aerosols over two contrasting environments Agartala and Patiala in India

The present study focused on the temporal variability, meteorological influences, potential sources, and long-range transport of atmospheric aerosols over two contrasting environments during 2011-2013. We have chosen Agartala (AGR) city in Northeast India as one of our sites representing the rural-continental environment and Patiala (PTA) as an urban site in Northwest India. The seasonal averaged equivalent black carbon (eBC) concentration in AGR ranges from 1.55 to 38.11 µg/m3 with an average value of 9.87 ± 8.17 µg/m3, whereas, at an urban location, PTA value ranges from 1.30 to 15.57 µg/m3 with an average value of 7.83 ± 3.51 µg/m3. The annual average eBC concentration over AGR was observed to be ~ 3 times higher than PTA. Two diurnal peaks (morning and evening) in eBC have been observed at both sites but were observed to be more prominent at AGR than at PTA. Spectral aerosol optical depth (AOD) has been observed to be in the range from 0.33 ± 0.09 (post-monsoon) to 0.85 ± 0.22 (winter) at AGR and 0.47 ± 0.04 (pre-monsoon) to 0.74 ± 0.09 (post-monsoon) at PTA. The concentration of eBC and its diurnal and seasonal variation indicates the primary sources of eBC as local sources, synoptic meteorology, planetary boundary layer (PBL) dynamics, and distant transportation of aerosols. The wintertime higher values of eBC at AGR than at PTA are linked with the transportation of eBC from the Indo-Gangetic Plain (IGP). Furthermore, it is evident that eBC aerosols are transported from local and regional sources, which is supported by concentration-weighted trajectory (CWT) analysis results.

Is there an EKC between economic growth and air pollutant emissions in SAARC countries? Evidence from disaggregated analysis

The manufacturing and construction (M&C) sector not only plays a vital role in promoting economic growth, but is also a significant contributor to global air pollution. Growing concerns regarding air pollutant emissions necessitate a more disaggregated (i.e., sectoral) investigation in order to identify the major contributors. This study employs aggregated and disaggregated data to determine the fundamental effects of economic growth (i.e., overall growth and sectoral growth) on air pollutant emissions (APE) (specifically, PM2.5 and PM10 released by the M&C sector) in SAARC economies between 1995 and 2018. It assesses the environmental Kuznets curve (i.e., inverted U-shaped and N-shaped) using the feasible generalized least squares (FGLS), panel-corrected standard errors (PCSE), and generalized method of moments (GMM) techniques. The sectoral analysis reveals the presence of an N-shaped EKC while the overall analysis indicates an inverted U-shaped EKC. Population, financial development (FD), and merchandise exports (MX) have no influence on the estimates. Population and FD increase APE in all models, whereas the effects of MX vary between models. As SAARC economies are capital-deficient, these economies can adopt unbalanced environmental protection policies. First, focus on major contributing sectors (e.g., M&C sector) to curb APE, then focus on less emitting sectors in turn. By implementing pollution reduction strategies on M&C sector activities, governments may reach their threshold (peak) points earlier than expected. A reduction in APE is impossible without rigorous monitoring and application. Being capital-deficient nations and given the collective nature of the problem, a Transboundary Haze/Pollution agreement is required to solve this issue.

Rapid classification of micro-particles using multi-angle dynamic light scatting and machine learning approach

The rapid classification of micro-particles has a vast range of applications in biomedical sciences and technology. In the given study, a prototype has been developed for the rapid detection of particle size using multi-angle dynamic light scattering and a machine learning approach by applying a support vector machine. The device consisted of three major parts: a laser light, an assembly of twelve sensors, and a data acquisition system. The laser light with a wavelength of 660 nm was directed towards the prepared sample. The twelve different photosensors were arranged symmetrically surrounding the testing sample to acquire the scattered light. The position of the photosensor was based on the Mie scattering theory to detect the maximum light scattering. In this study, three different spherical microparticles with sizes of 1, 2, and 4 μm were analyzed for the classification. The real-time light scattering signals were collected from each sample for 30 min. The power spectrum feature was evaluated from the acquired waveforms, and then recursive feature elimination was utilized to filter the features with the highest correlation. The machine learning classifiers were trained using the features with optimum conditions and the classification accuracies were evaluated. The results showed higher classification accuracies of 94.41%, 94.20%, and 96.12% for the particle sizes of 1, 2, and 4 μm, respectively. The given method depicted an overall classification accuracy of 95.38%. The acquired results showed that the developed system can detect microparticles within the range of 1-4 μm, with detection limit of 0.025 mg/ml. Therefore, the current study validated the performance of the device, and the given technique can be further applied in clinical applications for the detection of microbial particles.

Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China

The Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) algorithm was developed for aerosol retrieval on bright surfaces. Although the global validation accuracy of the DB product is satisfactory, there are still some regions found to have very low accuracy. To this end, DB has updated the surface database in the latest version of the Collection 6.1 (C6.1) algorithm. Some studies have shown that DB aerosol optical depth (AOD) of the old version Collection 6 (C6) has been seriously underestimated in Northwestern China. However, the status of the new version of the C6.1 product in this region is still unknown. This study aims to comprehensively evaluate the performance of the MODIS DB product in Northwestern China. The DB AOD with high quality (Quality Flag = 2 or 3) was selected to validate against the 23 sites from the China Aerosol Remote Sensing Network (CARSNET) and Aerosol Robotic Network (AERONET) during the period 2002–2014. By the overall analysis, the results indicate that both C6 and C6.1 show significant underestimation with a large fraction of more than 54% of collocations falling below the Expected Error (EE = ±(0.05 + 20% AODground)) envelope and with a large negative Mean Bias (MB) of less than −0.14. Furthermore, the new C6.1 products failed to achieve reasonable improvements in the region of Northwestern China. Besides, C6.1 has slightly fewer collocations than C6 due that some pixels with systematic biases have been removed from the new surface reflectance database. From the analysis of the site scale, the scatter plot of C6.1 is similar to that of C6 in most sites. Furthermore, a significant underestimation of DB AOD was observed at most sites, with the most severe underestimation at two sites located in the Taklimakan Desert region. Among 23 sites in Northwestern China, there are only two sites where C6.1 has largely improved the underestimation of C6. Furthermore, it is interesting to note that there are also two sites where the accuracy of the new C6.1 has declined. Moreover, it is surprising that there is one site where a large overestimation was observed in C6 and improved in C6.1. Additionally, we found a constant value of about 0.05 for both C6 and C6.1 at several sites with low aerosol loading, which is an obvious artifact. The significant improvements of C6.1 were observed in the Middle East and Central Asia but not in most sites of Northwestern China. The results of this study will be beneficial to further improvements in the MODIS DB algorithm.

Induction of neutrophil apoptosis by a Bcl-2 inhibitor reduces particulate matter-induced lung inflammation

Background. Environmental particulate matter exposure can cause various respiratory problems including aggravated asthma, decreased lung function and increased respiratory symptoms. However, the molecular mechanisms underlying PM-induced lung inflammation are incompletely understood. Effective therapeutic strategies are required.

Results. A mouse model of particulate matter-induced lung inflammation was used to identify the pathology and the molecular mechanisms for particulate matter-induced lung inflammation. The mouse model revealed that particulate matter induced neutrophil-dominated lung inflammation. Neutrophils derived from particulate matter-instilled mice showed decreased apoptosis and elevated Bcl-2 expression. Further studies in vav-Bcl-2 transgenic mice made it clear that Bcl-2 overexpression caused a marked increase in neutrophils in bronchoalveolar lavage fluid. Furthermore, we found that the Bcl-2 inhibitor ABT-199 reduced particulate matter-induced lung inflammation, and induced apoptosis of neutrophils in particulate matter-induced lung inflammation mice model.

Conclusions. Particulate matter-induced lung inflammation is mediated in part by inhibition of apoptosis of inflammatory cells. Bcl-2 is responsible for the reduced apoptosis of inflammatory cells in particulate matter-induced lung inflammation. The Bcl-2 selective inhibitor ABT-199 reduces particulate matter-induced lung inflammation by inducing the apoptosis of neutrophils and might be a promising drug for the treatment of particulate matter-induced lung inflammation.

Effects of environmental stressors on stem cells

Environmental toxicants are ubiquitous, and many are known to cause harmful health effects. However, much of what we know or think we know concerning the targets and long-term effects of exposure to environmental stressors is sadly lacking. Toxicant exposure may have health effects that are currently mischaracterized or at least mechanistically incompletely understood. While much of the recent excitement about stem cells (SCs) focuses on their potential as therapeutic agents, they also offer a valuable resource to give us insight into the mechanisms and risks of toxicant effects. Not only as a response to the increasing ethical pressure to reduce animal testing, SC studies allow us valuable insight into the true effects of human exposure to environmental stressors under controlled conditions. We present a review of the history of publications on the effects of environmental stressors on SCs, followed by a consolidation of the literature over the past five years on a subset of key environmental stressors of importance to human health and their effects on both embryonic and tissue SCs. The review will make constructive suggestions as to areas of toxicant research where further studies are needed, as well as making indications of the potential utility for advancing knowledge and directing research on environmental toxicology.

Cooking oil fume-derived PM2.5 induces apoptosis in A549 cells and MAPK/NF-кB/STAT1 pathway activation

Cooking oil fumes (COFs) are the major sources of indoor air pollution in Asia. It is well known that alveolar cells are key participants in the development of respiratory system; however, it still remains unknown whether alveolar cells are affected by COFs. Therefore, the present study investigated the effects of COFs on alveolar cells (A549 cells) and illuminated its apoptotic mechanism in response to COF-PM_2.5 exposure. When A549 cells were exposed to COF-PM_2.5, cell viability was substantially decreased, while the generation of ROS increased, and LDH levels and CCK-8 levels gradually changed within a dose-dependent manner. The nitrite concentration in the supernatants was augmented, while the SOD activity and GSH recycling were decreased upon COF-PM_2.5. Moreover, COF-PM_2.5 treatment increased mRNA levels of COX-2, inducible NO synthase, and TNF-α, and Elisa assay suggested that secretory proteins IL-6 and TNF-α were also increased. Furthermore, the Bax/Bcl-2 mRNA ratio was increased, and cleaved caspase-3 protein was activated in the A549 cells. Strikingly, COF-PM_2.5 induced the phosphorylation of STAT1 at Tyr701/Ser727 and activation of NF-кB and ERK1/2, p38, and JNK of the MAPK pathway. In short, our study suggested that COF-PM_2.5 resulted in inflammation, apoptosis, and cell damage in A549 cells, which might be modulated via the activation of MAPK/NF-кB/STAT1 pathway.

Airborne particulate in Varanasi over middle Indo-Gangetic Plain: variation in particulate types and meteorological influences

The variation in particulate mass and particulate types (PM_2.5 and PM₁₀) with respect to local/regional meteorology was analyzed from January to December 2014 (n = 104) for an urban location over the middle Indo-Gangetic Plain (IGP). Both coarser (mean ± SD; PM₁₀ 161.3 ± 110.4 μg m^-3, n = 104) and finer particulates (PM_2.5 81.78 ± 66.4 μg m^-3) revealed enormous mass loading with distinct seasonal effects (range: PM₁₀ 12-535 μg m^-3; PM_2.5 8-362 μg m^-3). Further, 56% (for PM_2.5) to 81% (for PM₁₀) of monitoring events revealed non-attainment national air quality standard especially during winter months. Particulate types (in terms of PM_2.5/PM₁₀ 0.49 ± 0.19) also exhibited temporal variations with high PM_2.5 loading particularly during winter (0.62) compared to summer months (0.38). Local meteorology has clear distinguishing trends in terms of dry summer (March to June), wet winter (December to February), and monsoon (July to September). Among all the meteorological variables (average temperature, rainfall, relative humidity (RH), wind speed (WS)), temperature was found to be inversely related with particulate loading (r_PM10 -0.79; r_PM2.5 -0.87) while RH only resulted a significant association with PM_2.5 during summer (r_PM10 0.07; r_PM2.5 0.55) and with PM₁₀ during winter (r_PM10 0.53; r_PM2.5 0.24). Temperature, atmospheric boundary layer (ABL), and RH were cumulatively recognized as the dominant factors regulating particulate concentration as days with high particulate loading (PM_2.5 >150 μg m^-3; PM₁₀ >260 μg m^-3) appeared to have lower ABL (mean 660 m), minimum temperature (<22.6 °C), and high RH (∼79%). The diurnal variations of particulate ratio were mostly insignificant except minor increases during night having a high wintertime ratio (0.58 ± 0.07) over monsoon (0.34 ± 0.05) and summer (0.30 ± 0.07). Across the region, atmospheric visibility appeared to be inversely associated with particulate (r_PM2.5 -0.84; r_PM10 -0.79) for all humid conditions, while at RH ≥80%, RH appeared as the most dominant factor in regulating visibility compared to particulate loading. The Lagrangian particle dispersion model was further used to identify possible regions contributing particulate loading through regional/transboundary movement.

Fine particulates over South Asia: Review and meta-analysis of PM2.5 source apportionment through receptor model

Fine particulates (PM_2.5) constitute dominant proportion of airborne particulates and have been often associated with human health disorders, changes in regional climate, hydrological cycle and more recently to food security. Intrinsic properties of particulates are direct function of sources. This initiates the necessity of conducting a comprehensive review on PM_2.5 sources over South Asia which in turn may be valuable to develop strategies for emission control. Particulate source apportionment (SA) through receptor models is one of the existing tool to quantify contribution of particulate sources. Review of 51 SA studies were performed of which 48 (94%) were appeared within a span of 2007-2016. Almost half of SA studies (55%) were found concentrated over few typical urban stations (Delhi, Dhaka, Mumbai, Agra and Lahore). Due to lack of local particulate source profile and emission inventory, positive matrix factorization and principal component analysis (62% of studies) were the primary choices, followed by chemical mass balance (CMB, 18%). Metallic species were most regularly used as source tracers while use of organic molecular markers and gas-to-particle conversion were minimum. Among all the SA sites, vehicular emissions (mean ± sd: 37 ± 20%) emerged as most dominating PM_2.5 source followed by industrial emissions (23 ± 16%), secondary aerosols (22 ± 12%) and natural sources (20 ± 15%). Vehicular emissions (39 ± 24%) also identified as dominating source for highly polluted sites (PM_2.5>100 μgm^-3, n = 15) while site specific influence of either or in combination of industrial, secondary aerosols and natural sources were recognized. Source specific trends were considerably varied in terms of region and seasonality. Both natural and industrial sources were most influential over Pakistan and Afghanistan while over Indo-Gangetic plain, vehicular, natural and industrial emissions appeared dominant. Influence of vehicular emission was found single dominating source over southern part while over Bangladesh, both vehicular, biomass burning and industrial sources were significant.

Airing 'clean air' in Clean India Mission

The submission explores the possibility of a policy revision for considering clean air quality in recently launched nationwide campaign, Clean India Mission (CIM). Despite of several efforts for improving availability of clean household energy and sanitation facilities, situation remain still depressing as almost half of global population lacks access to clean energy and proper sanitation. Globally, at least 2.5 billion people do not have access to basic sanitation facilities. There are also evidences of 7 million premature deaths by air pollution in year 2012. The situation is even more disastrous for India especially in rural areas. Although, India has reasonably progressed in developing sanitary facilities and disseminating clean fuel to its urban households, the situation in rural areas is still miserable and needs to be reviewed. Several policy interventions and campaigns were made to improve the scenario but outcomes were remarkably poor. Indian census revealed a mere 31% sanitation coverage (in 2011) compared to 22% in 2001 while 60% of population (700 million) still use solid biofuels and traditional cook stoves for household cooking. Further, last decade (2001-2011) witnessed the progress decelerating down with rural households without sanitation facilities increased by 8.3 million while minimum progress has been made in conversion of conventional to modern fuels. To revamp the sanitation coverage, an overambitious nationwide campaign CIM was initiated in 2014 and present submission explores the possibility of including 'clean air' considerations within it. The article draws evidence from literatures on scenarios of rural sanitation, energy practises, pollution induced mortality and climatic impacts of air pollution. This subsequently hypothesised with possible modification in available technologies, dissemination modes, financing and implementation for integration of CIM with 'clean air' so that access to both sanitation and clean household energy may be effectively addressed.

Trend and variability of atmospheric ozone over middle Indo-Gangetic Plain: impacts of seasonality and precursor gases

Ozone dynamics in two urban background atmospheres over middle Indo-Gangetic Plain (IGP) were studied in two contexts: total columnar and ground-level ozone. In terms of total columnar ozone (TCO), emphases were made to compare satellite-based retrieval with ground-based observation and existing trend in decadal and seasonal variation was also identified. Both satellite-retrieved (Aura Ozone Monitoring Instrument-Differential Optical Absorption Spectroscopy (OMI-DOAS)) and ground-based observations (IMD-O₃) revealed satisfying agreement with OMI-DOAS observation over predicting TCO with a positive bias of 7.24 % under all-sky conditions. Minor variation between daily daytime (r = 0.54; R ² = 29 %; n = 275) and satellite overpass time-averaged TCO (r = 0.58; R ² = 34 %; n = 208) was also recognized. A consistent and clear seasonal trend in columnar ozone (2005-2015) was noted with summertime (March-June) maxima (Varanasi, 290.9 ± 8.8; Lucknow, 295.6 ± 9.5 DU) and wintertime (December-February) minima (Varanasi, 257.4 ± 10.1; Lucknow, 258.8 ± 8.8 DU). Seasonal trend decomposition based on locally weighted regression smoothing technique identified marginally decreasing trend (Varanasi, 0.0084; Lucknow, 0.0096 DU year^-1) especially due to reduction in monsoon time minima and summertime maxima. In continuation to TCO, variation in ground-level ozone in terms of seasonality and precursor gases were also analysed from September 2014 to August 2015. Both stations registered similar pattern of variation with Lucknow representing slightly higher annual mean (44.3 ± 30.6; range, 1.5-309.1 μg/m³) over Varanasi (38.5 ± 17.7; range, 4.9-104.2 μg/m³). Variation in ground-level ozone was further explained in terms water vapour, atmospheric boundary layer height and solar radiation. Ambient water vapour content was found to associate negatively (r = -0.28, n = 284) with ground-level ozone with considerable seasonal variation in Varanasi. Implication of solar radiation on formation of ground-level ozone was overall positive (Varanasi, 0.60; Lucknow, 0.26), while season-specific association was recorded in case of atmospheric boundary layer.

Toxic airborne S, PAH, and trace element legacy of the superhigh-organic-sulphur Raša coal combustion: Cytotoxicity and genotoxicity assessment of soil and ash

This paper presents the levels of sulphur, polycyclic aromatic hydrocarbons (PAHs), and potentially toxic trace elements in soils surrounding the Plomin coal-fired power plant (Croatia). It used domestic superhigh-organic-sulphur Raša coal from 1970 until 2000. Raša coal was characterised by exceptionally high values of S, up to 14%, making the downwind southwest (SW) area surrounding the power plant a significant hotspot. The analytical results show that the SW soil locations are severely polluted with S (up to 4%), and PAHs (up to 13,535ng/g), while moderately with Se (up to 6.8mg/kg), and Cd (up to 4.7mg/kg). The composition and distribution pattern of PAHs in the polluted soils indicate that their main source could be airborne unburnt coal particles. The atmospheric dispersion processes of SO2 and ash particles have influenced the composition and distribution patterns of sulphur and potentially toxic trace elements in studied soils, respectively. A possible adverse impact of analysed soil on the local karstic environment was evaluated by cytotoxic and genotoxic methods. The cytotoxicity effects of soil and ash water extracts on the channel catfish ovary (CCO) cell line were found to be statistically significant in the case of the most polluted soil and ash samples. However, the primary DNA-damaging potential of the most polluted soil samples on the CCO cells was found to be within acceptable boundaries.