Atmospheric microplastic deposition associated with GDP and population growth: Insights from megacities in northern China.

Microplastic (MP) pollution is evolving into one of the most pressing environmental concerns worldwide. This study assessed the impact of economic activities on atmospheric MP pollution across 17 megacities in northern China, analyzing the correlation between the deposition flux of atmospheric MPs and variables such as city population, gross domestic product (GDP), and industrial structure. The results have shown that the MP pollution is obviously impacted by human activities related to increased GDP, population, as well as tertiary service sector, in which the MP pollution shows most close relationship with the GDP growth. Polypropylene, polyamide, polyurethane, and polyethylene were identified as the primary components of atmospheric MPs. The average particle size of MPs in atmospheric dustfall is 78.3 µm, and the frequency of MP particles increases as the particle size decreases. The findings highlight the complex relationship between socio-economic development and atmospheric MP accumulation, providing essential insights for the formulation of targeted emission reduction strategies.

A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023.

Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.

A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China.

Air pollutants, notably ozone (O3) and fine particulate matter (PM2.5) give rise to evident adverse impacts on public health and the ecotope, prompting extensive global apprehension. Though PM2.5 has been effectively mitigated in China, O3 has been emerging as a primary pollutant, especially in summer. Currently, alleviating PM2.5 and O3 synergistically faces huge challenges. The synergistic prevention and control (SPC) regions of PM2.5 and O3 and their spatiotemporal patterns were still unclear. To address the above issues, this study utilized ground monitoring station data, meteorological data, and auxiliary data to predict the China High-Resolution O3 Dataset (CHROD) via a two-stage model. Furthermore, SPC regions were identified based on a spatial overlay analysis using a Geographic Information System (GIS). The standard deviation ellipse was employed to investigate the spatiotemporal dynamic characteristics of SPC regions. Some outcomes were obtained. The two-stage model significantly improved the accuracy of O3 concentration prediction with acceptable R2 (0.86), and our CHROD presented higher spatiotemporal resolution compared with existing products. SPC regions exhibited significant spatiotemporal variations during the Blue Sky Protection Campaign (BSPC) in China. SPC regions were dominant in spring and autumn, and O3-controlled and PM2.5-dominated zones were detected in summer and winter, respectively. SPC regions were primarily located in the northwest, north, east, and central regions of China, specifically in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Shanxi, Shaanxi, Shandong, Henan, Jiangsu, Xinjiang, and Anhui provinces. The gravity center of SPC regions was distributed in the BTH in winter, and in Xinjiang during spring, summer, and autumn. This study can supply scientific references for the collaborative management of PM2.5 and O3.

Comparative study on physicochemical characteristics of atmospheric microplastics in winter in inland and coastal megacities: A case of Beijing and Shanghai, China.

Atmospheric microplastics (MPs) have received global attention across various sectors of society due to their potential negative impacts. This study aims to understand the physicochemical characteristics of MPs in inland and coastal megacities for raising awareness about the urgent need to reduce plastic pollution. Laser Direct Infrared Imaging (LDIR) and Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray Spectroscopy (EDX) techniques were employed to characterize atmospheric MPs in megacities (inland megacity Beijing and coastal megacity Shanghai) in China, focusing on their physicochemical characteristics, including compositional types, number concentration, morphology, size, possible sources, and potential health risks. The LDIR analysis identified sixteen different types of MPs present in the atmospheres of Beijing and Shanghai. The number concentration of atmospheric MPs in Beijing (3.0 items/m3) is 1.8 times that of Shanghai (1.7 items/m3). The study found that the variations in MP pollution between Beijing and Shanghai are influenced by the urban industrial structure and geographical location. Morphological analysis indicates that fragment MPs have the highest relative abundance in Beijing, while fibrous MPs dominate the atmosphere of Shanghai. Additionally, the study assessed the potential health risks of atmospheric MPs to urban residents. The results suggest that residents of Beijing face more severe health risks from atmospheric MPs compared to those in Shanghai. These findings underscore the urgency to address the issue of atmospheric MPs and provide crucial evidence for the formulation of relevant environmental and health policies.

Rasterizing CO2 emissions and characterizing their trends via an enhanced population-light index at multiple scales in China during 2013-2019.

Climate change caused by CO2 emissions (CE) has received widespread global concerns. Obtaining precision CE data is necessary for achieving carbon peak and carbon neutrality. Significant deficiencies of existing CE datasets such as coarse spatial resolution and low precision can hardly meet the actual requirements. An enhanced population-light index (RPNTL) was developed in this study, which integrates the Nighttime Light Digital Number (DN) Value from the National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and population density to improve CE estimation accuracy. The CE from the Carbon Emission Accounts & Datasets (CEADS) was divided into three sectors, namely urban, industrial, and rural, to differentiate the heterogeneity of CE in each sector. The ordinary least square (OLS), geographically weighted regression (GWR), temporally weighted regression (TWR), and geographically and temporally weighted regression (GTWR) models were employed to establish the quantitative relationship between RPNTL and CE for each sector. The optimal model was determined through model comparison and precision evaluation and was utilized to rasterize CE for urban, industrial, and rural areas. Additionally, hot spot analysis, trend analysis, and standard deviation ellipses were introduced to demonstrate the spatiotemporal dynamic characteristics of CE at multiple scales. The performance of the GTWR outperformed other methods in estimating CE. The enhanced RPNTL demonstrated a higher coefficient of determination (R2 = 0.95) than the NTL (R2 = 0.92) in predicting CE, particularly in rural regions where the R2 value increased from 0.76 to 0.81. From 2013 to 2019, high CE was observed in eastern and northern China, while a decreasing trend was detected in northeastern China and Chengdu-Chongqing. Conversely, the Yangtze River Delta, Pearl River Delta, Fenwei Plain, and Henan Province showed an increasing trend. The center of gravity for industrial and rural CE is shifting towards western regions, whereas that for urban CE is moving northward. This study provides valuable insights for decision-making on CE control.

MATR3-antisense LINE1 RNA meshwork scaffolds higher-order chromatin organization.

Long interspersed nuclear elements (LINEs) play essential roles in shaping chromatin states, while the factors that cooperate with LINEs and their roles in higher-order chromatin organization remain poorly understood. Here, we show that MATR3, a nuclear matrix protein, interplays with antisense LINE1 (AS L1) RNAs to form a meshwork via phase separation, providing a dynamic platform for chromatin spatial organization. MATR3 and AS L1 RNAs affect the nuclear localization of each other. After MATR3 depletion, the chromatin, particularly H3K27me3-modified chromatin, redistributes in the cell nuclei. Topologically associating domains (TADs) that highly transcribe MATR3-associated AS L1 RNAs show decreased intra-TAD interactions in both AML12 and ES cells. MATR3 depletion increases the accessibility of H3K27me3 domains adjacent to MATR3-associated AS L1, without affecting H3K27me3 modifications. Furthermore, amyotrophic lateral sclerosis (ALS)-associated MATR3 mutants alter biophysical features of the MATR3-AS L1 RNA meshwork and cause an abnormal H3K27me3 staining. Collectively, we reveal a role of the meshwork formed by MATR3 and AS L1 RNAs in gathering chromatin in the nucleus.

PfSET2 Is Involved in Genome Organization of Var Gene Family in Plasmodium falciparum.

The three-dimensional (3D) genome structure of human malaria parasite Plasmodium falciparum is highly organized and plays important roles in regulating coordinated expression patterns of specific genes such as virulence genes which are involved in antigenic variation and immune escape. However, the molecular mechanisms that control 3D genome of the parasite remain elusive. Here, by analyzing genome organization of P. falciparum, we identify high-interacting regions (HIRs) with strong chromatin interactions at telomeres and virulence genes loci. Specifically, HIRs are highly enriched with repressive histone marks (H3K36me3 and H3K9me3) and form the transcriptional repressive center. Deletion of PfSET2, which controls H3K36me3 level, results in marked reduction of both intrachromosomal and interchromosomal interactions for HIRs. Importantly, such chromatin reorganization coordinates with dynamic changes in epigenetic feature in HIRs and transcriptional activation of var genes. Additionally, different cluster of var genes based on the pattern of chromatin interactions show distinct transcriptional activation potential after deletion of PfSET2. Our results uncover a fundamental mechanism that the epigenetic factor PfSET2 controls the 3D organization of heterochromatin to regulate the transcription activities of var genes family in P. falciparum. IMPORTANCE PfSET2 has been reported to play key role in silencing var genes in Plasmodium falciparum, while the underlying molecular mechanisms remain unclear. Here, we provide evidence that PfSET2 is essential to maintain 3D genome organization of heterochromatin region to keep var genes in transcription repressive state. These findings can contribute better understanding of the regulation of high-order chromatin structure in P. falciparum.

The influence of socioeconomic and environmental determinants on acute myocardial infarction (AMI) mortality from the spatial epidemiological perspective.

Plenty of epidemiological approaches have been explored to detect the effects of environmental and socioeconomic factors on acute myocardial infarction (AMI) mortality. Whereas, identifying the influence of potential affecting factors on AMI mortality based on a spatial epidemiological perspective was strongly desired. Moreover, the interaction effects of two potential factors on the diseases were always neglected previously. Here, the Geodetector and geographically & temporally weighted regression model (GTWR) combined with multi-source spatiotemporal datasets were introduced to quantitatively determine the relationship between AMI mortality and potential influencing factors across Xi'an during 2014-2016. Besides, Moran's I was adopted to diagnose the spatial autocorrelation of AMI mortality. Some findings were achieved. The number of AMI mortality cases increased from 5075 in 2014 to 6774 in 2016. Air pollutants, meteorological factors, economic status, and topography factors exhibited a significant effect on AMI mortality. The AMI mortality demonstrated an obvious spatial autocorrelation feature during 2014-2016. POP and PE represented the most obvious impact on AMI mortality, respectively. Moreover, the interaction of any two factors was larger than that of the single factor on AMI mortality, and the factors with the strongest interaction vary according to lag groups and ages. The effects of factors on AMI mortality were POP (- 628.925) > PE (140.102) > RD (79.145) > O3 (- 58.438) > E_NH3 (42.370) for male, and POP (- 751.206) > RD (132.935) > E_NH3 (58.758) > PE (- 45.434) > O3 (- 21.256) for female, respectively. This work reminds the local government to continuously control air pollution, strengthen urban planning, and improve the health care of the rural areas for alleviating AMI mortality. Meanwhile, the scheme of the current study supplies a scientific reference for examining the effects of potential impact factors on related diseases using the spatial epidemiological perspective.

Pollution characteristics and sources of environmentally persistent free radicals and oxidation potential in fine particulate matter related to city lockdown (CLD) in Xi'an, China.

The impact of COVID-19 control on air quality have been prevalent for the past two years, however few studies have explored the toxicity of atmospheric particulate matter during the epidemic control. Therefore, this research highlights the characteristics and sources of oxidative potential (OP) and the new health risk substances environmentally persistent free radicals (EPFRs) in comparison to city lockdown (CLD) with early days of 2019-2020. Daily particulate matter (PM2.5) samples were collected from January 14 to February 3, 2020, with the same period during 2019 in Xi'an city. The results indicated that the average concentration of PM2.5 decreased by 48% during CLD. Concentrations of other air pollutants and components, such as PM10, NO2, SO2, WSIs, OC and EC were also decreased by 22%, 19%, 2%, 17%, 6%, and 4% respectively during the CLD, compared to the same period in 2019. Whereas only O3 increased by 30% during CLD. The concentrations of EPFRs in PM2.5 was considerably lower than in 2019, which decreased by 12% during CLD. However, the OP level was increased slightly during CLD. Moreover, both EPFRs/PM and DTTv/PM did not decrease or even increase significantly, manifesting that the toxicity of particulate matter has not been reduced by more gains during the CLD. Based on PMF analysis, during the epidemic period, the contribution of traffic emission is significantly reduced, while EPFRs and DTTv increased, which consist of significant O3 and secondary aerosols. This research leads to able future research on human health effect of EPFRs and oxidative potential and can be also used to formulate the majors to control EPFRs and OP emissions, suggest the need for further studies on the secondary processing of EPFRs and OP during the lockdown period in Xi'an. .The COVID-19 lockdown had a significant impact on both social and economic aspects. The city lockdown, however, had a positive impact on the environment and improved air quality, however, no significant health benefits were observed in Xi'an, China.

Development of transferable neighborhood land use regression models for predicting intra-urban ambient nitrogen dioxide (NO2) spatial variations.

Land use regression (LUR) models have been extensively used to predict air pollution exposure in epidemiological and environmental studies. The lack of dense routine monitoring networks in big cities places increased emphasis on the need for LUR models to be developed using purpose-designed neighborhood-scale monitoring data. However, the unsatisfactory model transferability limits these neighborhood LUR models to be then applied to other intra-urban areas in predicting air pollution exposure. In this study, we tackled this issue by proposing a method to develop transferable neighborhood NO2 LUR models with comparable predictive power based on only micro-scale predictor variables for modeling intra-urban ambient air pollution exposure. Taking Auckland metropolis, New Zealand, as a case study, the proposed method was applied to three neighborhoods (urban, central business district, and dominion road) and compared with the corresponding counterpart models developed using pools of (a) only macro-scale predictor variables and (b) a mixture of both micro- and macro-scale predictor variables (traditional method). The results showed that the models using only macro-scale variables achieved the lowest accuracy (R2: 0.388-0.484) and had the worst direct (R2: 0.0001-0.349) and indirect transferability (R2: 0.07-0.352). Those models using the traditional method had the highest model fitting R2 (0.629-0.966) with lower cross-validation R2 (0.495-0.941) and slightly better direct transferability (R2: 0.0003-0.386) but suffered poor model interpretability when indirectly transferred to new locations. Our proposed models had comparable model fitting R2 (0.601-0.966) and the best cross-validation R2 (0.514-0.941). They also had the strongest direct transferability (R2: 0.006-0.590) and moderate-to-good indirect transferability (R2: 0.072-0.850) with much better model interpretability. This study advances our knowledge of developing transferable LUR models for the very first time from the perspective of the scale of the predictor variables used in the model development and will significantly benefit the wider application of LUR approaches in epidemiological and environmental studies.

Ocular Dominance and Functional Asymmetry in Visual Attention Networks.

Purpose: The dorsal attention network (DAN) and the ventral attention network (VAN) are known to support visual attention, but the influences of ocular dominance on the attention networks are unclear. We aimed to explore how visual cortical asymmetry of the attention networks correlate with neurophysiological oscillation and connectivity markers of attentional processes. Methods: An oddball task with concentric circle stimuli of three different sizes (i.e., spot size of 5°, 20°, or 30° of visual angle) was used to vary task difficulty. Event-related oscillations and interareal communication were tested with an electroencephalogram-based visual evoked components as a function of ocular dominance in 30 healthy subjects. Results: Accuracy rates were higher in the dominant eyes compared with the nondominant eyes. Compared with the nondominant eyes, the dominant eyes had higher theta, low-alpha, and low-beta powers and lower high-alpha powers within the nodes of VAN and DAN. Furthermore, visual information processed by the dominant and nondominant eye had different fates, that is, the dominant eyes mainly relied on theta and low-alpha connectivity within both the VAN and the DAN, whereas the nondominant eyes mainly relied on theta connectivity within the VAN and high-alpha connectivity within the DAN. The difference in accuracy rate between the two eyes was correlated with the low-alpha oscillations in the anterior DAN area and low-alpha connectivity of the left DAN. Conclusions: The ocular dominance processing and interareal communication reveal a cortical asymmetry underlying attention, and this reflects a two-way modulatory mechanism within attention networks in the human brain.

Cognitive deficits and rehabilitation mechanisms in mild traumatic brain injury patients revealed by EEG connectivity markers.

OBJECTIVE: To explore the multiple specific biomarkers and cognitive compensatory mechanisms of mild traumatic brain injury (mTBI) patients at recovery stage. METHODS: The experiment was performed in two sections. In Section I, using event-related potential, event-related oscillation and spatial phase-synchronization, we explored neural dynamics in 24 volunteered healthy controls (HC) and 38 patients at least 6 months post-mTBI (19 with epidural hematoma, EDH; 19 with subdural hematoma, SDH) during a Go/NoGo task. In Section II, according to the neuropsychological scales, patients were divided into sub-groups to assess these electroencephalography (EEG) indicators in identifying different rehabilitation outcomes of mTBI. RESULTS: In Section I, mean amplitudes of NoGo-P3 and P3d were decreased in mTBI patients relative to HC, and NoGo-theta power in the non-injured hemisphere was decreased in SDH patients only. In Section II, patients with chronic neuropsychological defects exhibited more serious impairments of intra-hemispheric connectivity, whereas inter-hemispheric centro-parietal and frontal connectivity were enhanced in response to lesions. CONCLUSIONS: EEG distinguished mTBI patients from healthy controls, and estimated different rehabilitation outcomes of mTBI. The centro-parietal and frontal connectivity are the main compensatory mechanism for the recovery of mTBI patients. SIGNIFICANCE: EEG measurements and network connectivity can track recovery process and mechanism of mTBI.

Deletion of ferritin H in neurons counteracts the protective effect of melatonin against traumatic brain injury-induced ferroptosis.

Accumulating evidence demonstrates that ferroptosis may be important in the pathophysiological process of traumatic brain injury (TBI). As a major hormone of the pineal gland, melatonin exerts many beneficial effects on TBI, but there is no information regarding the effects of melatonin on ferroptosis after TBI. As expected, TBI resulted in the time-course changes of ferroptosis-related molecules expression and iron accumulation in the ipsilateral cortex. Importantly, we found that treating with melatonin potently rescued TBI induced the changes mentioned above and improved functional deficits versus vehicle. Similar results were obtained with a ferroptosis inhibitor, liproxstatin-1. Moreover, the protective effect of melatonin is likely dependent on melatonin receptor 1B (MT2). Although ferritin plays a vital role in iron metabolism by storing excess cellular iron, its precise function in the brain, and whether it involves melatonin's neuroprotection remain unexplored. Considering ferritin H (Fth) is expressed predominantly in the neurons and global loss of Fth in mice induces early embryonic lethality, we then generated neuron-specific Fth conditional knockout (Fth-KO) mice, which are viable and fertile but have altered iron metabolism. In addition, Fth-KO mice were more susceptible to ferroptosis after TBI, and the neuroprotection by melatonin was largely abolished in Fth-KO mice. In vitro siFth experiments further confirmed the results mentioned above. Taken together, these data indicate that melatonin produces cerebroprotection, at least partly by inhibiting neuronal Fth-mediated ferroptosis following TBI, supporting the notion that melatonin is an excellent ferroptosis inhibitor and its anti-ferroptosis provides a potential therapeutic target for treating TBI.

Evaluating the Effect of Ambient Concentrations, Route Choices, and Environmental (in)Justice on Students' Dose of Ambient NO2 While Walking to School at Population Scales.

The commuting microenvironment accounts for a large part of students' diurnal exposure to air pollution, especially in cities in developed countries where air pollution is caused predominantly by vehicle traffic. Accurate quantification of students' exposure and pollution dose during their commute from home to school requires their home addresses and details of the schools they attend. Such details are usually inaccessible or difficult to obtain at population scales due to privacy issues. Therefore, estimates of students' exposure to, and dose of, air pollution at population scales have to rely on simulated origins and destinations, which may bias the results. This contribution overcomes this limitation by quantifying students' terrain-based dosage of ambient nitrogen dioxide (NO2) during their commute from home to school while walking along (a) the shortest-distance routes and (b) an alternative lowest-dose route. This is determined at population scales for students in Auckland, New Zealand using a rich dataset of observed home addresses and schools attended for 14,091 walking students. This study also determines the bias introduced when using simulated addresses (as opposed to observed data) to calculate the same result. Finally, we examine exposure inequalities among students of different socioeconomic backgrounds at school, at home, and during walking commutes. Results show that only 17.48% of students in the whole of Auckland can find alternative lowest-dose routes. The portion is higher (26%) in central Auckland because of its better road network connectivity. The trade-off analysis identifies that for only about 30% of students, a 1% increase in route length is associated with a >1% reduction in dosage if using the alternative lowest-dose route. Greater benefits were observed in suburban Auckland (a less-polluted area) than in central Auckland, which highlights the importance of taking an alternative lowest-dose route, especially for students whose shortest-distance routes overlap with or run parallel to an arterial road. The use of simulated addresses resulted in underestimates of both the length and reduced dosage of the alternative routes by up to a quarter in comparison with the results derived from the observed data. Limited evidence of exposure inequality based on commuter exposure was found, but patterns in the central city were opposite to those in the suburbs.

Assessing schoolchildren's exposure to air pollution during the daily commute - A systematic review.

Air pollution is mostly caused by emissions from human activities, and exposure to air pollution is linked with numerous adverse human health outcomes. Recent studies have identified that although people only spend a small proportion of time on their daily commutes, the commuter microenvironment is a significant contributor to their total daily air pollution exposure. Schoolchildren are a particularly vulnerable cohort of the population, and their exposure to air pollution at home or school has been documented in a number of case studies. A few studies have identified that schoolchildren's exposure during commutes is linked with adverse cognitive outcomes and severe wheeze in asthmatic children. However, the determinants of total exposure, such as route choice and commute mode, and their subsequent health impacts on schoolchildren are still not well-understood. The aim of this paper is to review and synthesize recent studies on assessing schoolchildren's exposure to various air pollutants during the daily commute. Through reviewing 31 relevant studies published between 2004 and 2020, we tried to identify consistent patterns, trends, and underlying causal factors in the results. These studies were carried out across 10 commute modes and 12 different air pollutants. Air pollution in cities is highly heterogeneous in time and space, and commuting schoolchildren move through the urban area in complex ways. Measurements from fixed monitoring stations (FMSs), personal monitoring, and air quality modeling are the three most common approaches to determining exposure to ambient air pollutant concentrations. The time-activity diary (TAD), GPS tracker, online route collection app, and GIS-based route simulation are four widely used methods to determine schoolchildren's daily commuting routes. We found that route choices exerted a determining impact on schoolchildren's exposure. It is challenging to rank commute modes in order of exposure, as each scenario has numerous uncontrollable determinants, and there are notable research gaps. We suggest that future studies should concentrate on examining exposure patterns of schoolchildren in developing countries, exposure in the subway and trains, investigating the reliability of current simulation methods, exploring the environmental justice issue, and identifying the health impacts during commuting. It is recommended that three promising tools of smartphones, data fusion, and GIS should be widely used to overcome the challenges encountered in scaling up commuter exposure studies to population scales.

A site-optimised multi-scale GIS based land use regression model for simulating local scale patterns in air pollution.

Standard Land Use Regression (LUR) models rely on one universal equation for the entire city or study area. Since this approach cannot represent the heterogeneous controls on pollutant dispersion in central, urban and suburban areas effectively the models are not transferable. Further, if different land use types are not adequately sampled in the measurement campaign, model estimates of local-scale pollutant concentrations may be poor. In this study, this deficiency is overcome with a site-optimised multi-scale GIS based LUR modelling approach developed. This approach is used to simulate nitrogen dioxide (NO2) concentrations in Auckland at three scales (central business district (CBD), urban, and suburban). The simulated NO2 distribution clearly shows a higher concentration of pollution along arterial roads and motorways as expected. Areas of limited dispersion (such as among high-rise buildings of the CBD) are also identified as high pollution areas. Predictor variables vary between scales; no single variable is common to all the scales. The leave-one-out cross validation (LOOCV) revealed that the multi-scale LUR model achieved an R2 of 0.62, 0.86 and 0.73, respectively, at the CBD, urban, and suburban scales. The corresponding LOOCV root-mean-square-errors (RMSE) were 5.58, 3.53 and 4.41 µg·m-3 respectively. Based on these statistical measures the multi-scale LUR model performs slightly better than the universal kriging (UK) model and the standard LUR model, and significantly better than the inverse distance weighting (IDW) and ordinary kriging (OK) models. When evaluated against external observations at eight fixed regulatory monitoring stations, the multi-scale LUR model out-performed all four of the other models considered and achieved an R2 value of 0.85 with the lowest RMSE (8.48 µg·m-3). This approach offers a robust alternative for modelling and mapping spatial concentrations of NO2 pollutants at multi-scales in large study areas with distinct urban design and configurations.

36% Enhanced Efficiency of Ternary Organic Solar Cells by Doping a NT-Based Polymer as an Electron-Cascade Donor.

In recent years, ternary organic photovoltaic cells (OPVs) have been dedicated to improving power conversion efficiency (PCE) by broadening optical absorption spectra. Ternary OPVs with different poly[thieno[3,2-b]thiophene-2,5-diyl-alt-4,9-bis(4-(2-decyltetradecyl)thien-2-yl)naphtho[1,2-c:5,6-c']bis[1,2,5]thiadiazole-5,5'-diyl] (PTT-DTNT-DT) doping concentrations were designed and the effect of PTT-DTNT-DT as a complementary electron donor on the performance of OPVs was investigated. The optimized PCE of OPVs was increased from 3.42% to 4.66% by doping 20 wt % PTT-DTNT-DT. The remarkable improvement in the performance of the ternary device is mainly attributed to the sharp increase in the short-circuit current density and fill-factor. The major reasons have been systematically studied from atomic force microscopy, electrochemical impedance spectroscopy, surface energy, space charge limited current and photocurrent behavior. It has been found that the separation of excitons and the transportation of charge are enhanced while light absorption is increased, and the charge recombination also decreases due to the optimization of the cascade energy level and the morphology of the ternary active layer. The results show that it is feasible to improve the performance of ternary OPVs by their complementary absorption.