Protease-independent control of parthanatos by HtrA2/Omi.

HtrA2/Omi is a mitochondrial serine protease with ascribed pro-apoptotic as well as pro-necroptotic functions. Here, we establish that HtrA2/Omi also controls parthanatos, a third modality of regulated cell death. Deletion of HtrA2/Omi protects cells from parthanatos while reconstitution with the protease restores the parthanatic death response. The effects of HtrA2/Omi on parthanatos are specific and cannot be recapitulated by manipulating other mitochondrial proteases such as PARL, LONP1 or PMPCA. HtrA2/Omi controls parthanatos in a manner mechanistically distinct from its action in apoptosis or necroptosis, i.e., not by cleaving cytosolic IAP proteins but rather exerting its effects without exiting mitochondria, and downstream of PARP-1, the first component of the parthanatic signaling cascade. Also, previously identified or candidate substrates of HtrA2/Omi such as PDXDC1, VPS4B or moesin are not cleaved and dispensable for parthanatos, whereas DBC-1 and stathmin are cleaved, and thus represent potential parthanatic downstream mediators of HtrA2/Omi. Moreover, mass-spectrometric screening for novel parthanatic substrates of HtrA2/Omi revealed that the induction of parthanatos does not cause a substantial proteolytic cleavage or major alterations in the abundance of mitochondrial proteins. Resolving these findings, reconstitution of HtrA2/Omi-deficient cells with a catalytically inactive HtrA2/Omi mutant restored their sensitivity against parthanatos to the same level as the protease-active HtrA2/Omi protein. Additionally, an inhibitor of HtrA2/Omi's protease activity did not confer protection against parthanatic cell death. Our results demonstrate that HtrA2/Omi controls parthanatos in a protease-independent manner, likely via novel, unanticipated functions as a scaffolding protein and an interaction with so far unknown mitochondrial proteins.

HTRA2/OMI-Mediated Mitochondrial Quality Control Alters Macrophage Polarization Affecting Systemic Chronic Inflammation.

Systemic chronic inflammation (SCI) due to intrinsic immune over-activation is an important factor in the development of many noninfectious chronic diseases, such as neurodegenerative diseases and diabetes mellitus. Among these immune responses, macrophages are extensively involved in the regulation of inflammatory responses by virtue of their polarization plasticity; thus, dysregulation of macrophage polarization direction is one of the potential causes of the generation and maintenance of SCI. High-temperature demand protein A2 (HtrA2/Omi) is an important regulator of mitochondrial quality control, not only participating in the degradation of mis-accumulated proteins in the mitochondrial unfolded protein response (UPRmt) to maintain normal mitochondrial function through its enzymatic activity, but also participating in the regulation of mitochondrial dynamics-related protein interactions to maintain mitochondrial morphology. Recent studies have also reported the involvement of HtrA2/Omi as a novel inflammatory mediator in the regulation of the inflammatory response. HtrA2/Omi regulates the inflammatory response in BMDM by controlling TRAF2 stabilization in a collagen-induced arthritis mouse model; the lack of HtrA2 ameliorates pro-inflammatory cytokine expression in macrophages. In this review, we summarize the mechanisms by which HtrA2/Omi proteins are involved in macrophage polarization remodeling by influencing macrophage energy metabolism reprogramming through the regulation of inflammatory signaling pathways and mitochondrial quality control, elucidating the roles played by HtrA2/Omi proteins in inflammatory responses. In conclusion, interfering with HtrA2/Omi may become an important entry point for regulating macrophage polarization, providing new research space for developing HtrA2/Omi-based therapies for SCI.

Assessment of spatiotemporal variability of ultraviolet index (UVI) over Kerala, India, using satellite remote sensing (OMI/AURA) data.

The spatial and temporal dynamics of daily ultraviolet index (UVI) for a period of 18 years (2004-2022) over the Indian state of Kerala were statistically characterised in the study. The UVI measurements used for the study were derived from the ultraviolet-B (UVB) irradiance measured by the Ozone Monitoring Instrument (OMI) of the AURA satellite and classified into different severity levels for analysis. Basic statistics of daily, monthly and seasonal UVI as well as Mann-Kendall (MK) statistical trend characteristics and the rate of change of daily UVI using Theil-Sen's slope test were also evaluated. A higher variability of UVI characteristics was observed in the Kerala region, and more than 79% of the measurements fell into the categories of very high and extreme UVI values, which suggests the need of implementation of appropriate measures to reduce health risks. Although the UVI measured during the study period shows a slight decrease, most of the data show a seasonal variation with undulating low and peak values. Higher UVI are observed during the months of March, April and September. The region also has higher UVI during the southwest monsoon (SWM) and summer seasons. Although Kerala region as a single whole unit, UVI show a non-significant decreasing trend (-0.83), the MK test revealed the increasing and decreasing trends of UVI ranging from -1.96 to 0.41 facilitated the delineation of areas (domains) where UVI are increasing or decreasing. The domain of UVI increase occupies the central and southern (S) parts, and the domains of decrease cover the northern (N) and S parts of the Kerala region. The rate of change of daily UVI in domain of increase and decrease shows an average rate of 0.34 × 10-5 day-1 and -2 × 10-5 day-1, respectively. The parameters (rainfall, air temperature, cloud optical depth (COD) and solar zenith angle (SZA)) that affect the strength of UV rays reaching the surface indicate that a cloud-free atmosphere or low thickness clouds prevails in the Kerala region. Overall, the study results indicate the need for regular monitoring of UVI in the study area and also suggest appropriate campaigns to disseminate information and precautions for prolonged UVI exposure to reduce the adverse health effects, since the study area has a high population density.

OMI-based emission source classification in East China and its spatial redistribution in view of pollution control measures.

This study aims to generate a satellite-based qualitative emission source characterization for the heavily polluted eastern part of China in the 2010-2016 time period. The applied source identification technique relies on satellite-based NOx and SO2 emission estimates by OMI, their SO2:NOx ratio, and the MIX anthropogenic emission inventory to distinguish emissions from different emission categories (urban, industrial, natural) and characterize the dominant source per 0.25° × 0.25° grid cell in East China. Overall, we find good agreement between the satellite- and emission inventory-based spatiotemporal distribution and characterization of the dominant emission sources in East China in 2010-2016. In 2010, the satellite measurements suggest an emission distribution less dominated by industrial areas, a somewhat larger role for urban/transportation areas and agricultural activities, and more natural emissions in the southern part compared to the bottom-up emission categorization. In 2016, more than half of the classified emission categories over East China have remained the same. At the same time, there is a notable increase of agricultural lands and decrease of areas dominated by industry/transportation in 2016, suggestive of an overall decrease in heavy air pollution in East China over the course of 7 years. This is likely attributed to the sustained efforts of the Chinese government to drastically improve the air quality, especially since 2013 when the National Air Pollution Prevention and Control Action Plan was enacted. However, signs of urban expansion (urbanization) and rural-urban migration ("Go West" motion) stemmed from China's rapid economic growth and labour demand are evident; escalating industrialization (even with cleaner means) and the urban population growth in East China resulted in stronger emissions from sources representing consumption and transportation which are strongly related to NO2 and PM10 pollution (rather than SO2) and are directly influenced by the population size. This resulted to a shift of the emissions from the east mainly to the north and northwest of East China. Overall, although the effectiveness of the Chinese environmental control policies has been successful, the air pollution problem remains an important concern.

Evaluation of Uncertainties in the Anthropogenic SO2 Emissions in the USA from the OMI Point Source Catalog.

Satellite remote sensing is a promising method of monitoring emissions that may be missing in inventories, but the accuracy of these estimates is often not clear. We demonstrate here a comprehensive evaluation of errors in anthropogenic sulfur dioxide (SO2) emission estimates from NASA's OMI point source catalog for the contiguous US by comparing emissions from the catalog with high-quality emission inventory data over different dimensions including size of individual sources, aggregate vs individual source errors, and potential bias in individual source estimates over time. For sources that are included in the catalog, we find that errors in aggregate (sum of error for all included sources) are relatively low. Errors for individual sources in any given year can be substantial, however, with over- or underestimates in terms of total error ranging from -80 to 110 kt (roughly 10-90th percentile). We find that these errors are not necessarily random over time and that there can be consistently positive or negative biases for individual sources. We did not find any overall statistical relationship between the degree of isolation of a source and bias, either at a 40 or 70 km scales. For a sub-set of sources where inventory emissions over a radius of 70 km around an OMI detection are larger than twice the emissions within 40 km, the OMI value is consistently overestimated. We find, as expected, that emission sources not included in the catalog are the largest aggregate source of difference between the satellite estimates and inventories, especially in more recent years where source emission magnitudes have been decreasing and note that trends in satellite detections do not necessarily track trends in total emissions. We find that the OMI-based SO2 emissions are accurate in aggregate, when summed over a number of sources, but must be interpreted more cautiously at the individual source level. Similar analyses would be valuable for other satellite emission estimates; however, in many cases, the appropriate high-quality reference data may need to be generated.

Climatology and landscape determinants of AOD, SO2 and NO2 over Indo-Gangetic Plain.

Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO2 and SO2, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO2 and SO2 over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005-2019. IGP experienced an overall increment in AOD (R2 = 0.63) and SO2 (R2 = 0.67) values, with LIGP (AOD, R2 = 0.8 & SO2, R2 = 0.8) experiencing the largest rate of enhancement. The levels of NO2 (R2 = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R2 = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO2 value (3.82 ± 0.98 × 1015 molecules/cm2) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO2 (3.8 ± 1.4 × 1015 molecules/cm2) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO2 level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO2 and NO2, implying no pollution abatement effect on SO2 and NO2 pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.

FOCUS may detect wall motion abnormalities in patients with ACS.

BACKGROUND: Chest pain is a common presentation to the Emergency Department (ED) with roughly 6 million visits a year. The primary diagnostic modality for the identification of acute coronary syndrome (ACS) is the electrocardiogram (ECG), which is used to screen for electrocardiographic findings representing acute coronary occlusion. It is known that the ischemia generated by an acutely occluded coronary vessel generates a wall motion abnormality which can be visualized by echocardiogram; however, emergency physician-performed focused cardiac ultrasound (FOCUS) currently does not have a formal role in the diagnosis of OMI within the emergency department. PURPOSE: We sought to define the characteristics of FOCUS performed by emergency physicians of variable training levels in the identification of RWMA in patients presenting to the emergency department with high suspicion for ACS before undergoing cardiac catheterization or formal echocardiography. We also explored whether RWMA was associated with OMI in these patients. METHODS: We performed a structured, retrospective review of adult patients presenting to a large, academic, tertiary care center with suspected ACS from July 1st, 2019, and October 24th, 2020. Patients were included if they underwent FOCUS in the ED during the time-period above for suspected ACS looking for RWMA and FOCUS images were stored and reviewable in our middleware software. The primary outcome was the accuracy, sensitivity, and specificity of FOCUS compared to formal echocardiography for the detection of RWMA. Secondary outcomes were sensitivity of FOCUS compared to formal echocardiography for detection of RWMA in patients with and without cardiac catheterization proven OMI and sensitivity and specificity of FOCUS operators based on training. RESULTS: FOCUS for RWMA performed by emergency physicians had a sensitivity of 94% (95% CI, 82-98), specificity 35% (95% CI, 15-61), and overall accuracy of 78% (95% CI, 66-87). Of all subjects, 82% underwent urgent or emergency coronary angiography, of which 71% had OMI at the time of coronary angiography of the procedure. FOCUS identified RWMA in 87% of patients with coronary angiography proven OMI. Residents (PGY-1 - PGY-3) (n = 31) were able to detect RWMA with a sensitivity of 86% (95% CI, 64-96), a specificity of 56% (95% CI, 23-85%), and an accuracy of 77 (95% CI, 58-90%). Emergency ultrasound fellows and attendings (n = 34) were able to detect RWMA with a sensitivity of 85% (95% CI, 64-95%), a specificity of 75% (95% CI, 36-96%), and an accuracy of 82% (95% CI, 65-93%). CONCLUSIONS: Our retrospective study concludes FOCUS performed by emergency physicians may be used to detect RWMA in patients with high concern for acute coronary syndrome. This may have its greatest utility in patients presenting without STEMI where the ECG is felt to be equivocal, but the clinician has high concern for OMI, in which the presence of RWMA might result in emergent cath lab activation, though this requires further study. The presence of RWMA in such cases may help to rule in OMI as a cause; however, the absence of RWMA should exclude OMI. Further research is necessary to confirm these findings.

Spatial variability of trace gases (NO2, O3 and CO) over Indian region during 2020 and 2021 COVID-19 lockdowns.

COVID-19 lockdown has given us an opportunity to investigate the pollutant concentrations in response to the restricted anthropogenic activities. The atmospheric concentration levels of nitrogen dioxide (NO2), carbon monoxide (CO) and ozone (O3) have been analysed for the periods during the first wave of COVID-19 lockdown in 2020 (25th March-31st May 2020) and during the partial lockdowns due to second wave in 2021 (25th March-15th June 2021) across India. The trace gas measurements from Ozone Monitoring Instrument (OMI) and Atmosphere InfraRed Sounder (AIRS) satellites have been used. An overall decrease in the concentration of O3 (5-10%) and NO2 (20-40%) have been observed during the 2020 lockdown when compared with business as usual (BAU) period in 2019, 2018 and 2017. However, the CO concentration increased up to 10-25% especially in the central-west region. O3 and NO2 slightly increased or had no change in 2021 lockdown when compared with the BAU period, but CO showed a mixed variation prominently influenced by the biomass burning/forest fire activities. The changes in trace gas levels during 2020 lockdown have been predominantly due to the reduction in the anthropogenic activities, whereas in 2021, the changes have been mostly due to natural factors like meteorology and long-range transport, as the emission levels have been similar to that of BAU. Later phases of 2021 lockdown saw the dominant effect of rainfall events resulting in washout of pollutants. This study reveals that partial or local lockdowns have very less impact on reducing pollution levels on a regional scale as natural factors like atmospheric long-range transport and meteorology play deciding roles on their concentration levels.

Validations of satellite ozone profiles in austral spring using ozonesonde measurements in the Jang Bogo station, Antarctica.

Using ozonesonde measurements from 2015 to 2018 at the Jang Bogo station located in the southeastern Antarctic region, we evaluate ozone profiles retrieved from the three satellite measurements that are widely used: Ozone Monitoring Instrument (OMI), Microwave Limb Sounder (MLS), and Ozone Mapping Profiler Suite (OMPS) data. For the fair validation, ozonesonde profiles are smoothed using the weighting function of each satellite retrieval algorithm (i.e., convolution process). Compared with limb-viewing MLS and OMPS ozone profiles, the OMI ozone profiles are relatively less qualified: coarser vertical resolution and larger inter-annual variation. Nevertheless, our validation reveals that the quality of all three satellite ozone profiles looks comparable; In general, difference from ozonesonde profile is ∼1 ppm absolutely, and -20 to 30% relatively at maximum. This quantitative range well corresponds to previous work, meaning that our new validation confirms the reliability of satellite ozone profiles in the southeastern Antarctic region where the measurement data for the validation were not enough. Another interesting feature is the role of a priori ozone profile; Nadir-viewing OMI satellite can have qualified ozone profiles by a proper assumption of a priori ozone profile. Since the performance of limb-viewing ozone profiles is better, however, the careful usage of nadir-viewing ozone profile is still required. We think that the simultaneous usage of multiple satellite ozone profiles can contribute to better understanding of Antarctic ozone characteristics.

Mapping hydroxyl variability throughout the global remote troposphere via synthesis of airborne and satellite formaldehyde observations.

The hydroxyl radical (OH) fuels tropospheric ozone production and governs the lifetime of methane and many other gases. Existing methods to quantify global OH are limited to annual and global-to-hemispheric averages. Finer resolution is essential for isolating model deficiencies and building process-level understanding. In situ observations from the Atmospheric Tomography (ATom) mission demonstrate that remote tropospheric OH is tightly coupled to the production and loss of formaldehyde (HCHO), a major hydrocarbon oxidation product. Synthesis of this relationship with satellite-based HCHO retrievals and model-derived HCHO loss frequencies yields a map of total-column OH abundance throughout the remote troposphere (up to 70% of tropospheric mass) over the first two ATom missions (August 2016 and February 2017). This dataset offers unique insights on near-global oxidizing capacity. OH exhibits significant seasonality within individual hemispheres, but the domain mean concentration is nearly identical for both seasons (1.03 ± 0.25 × 106 cm-3), and the biseasonal average North/South Hemisphere ratio is 0.89 ± 0.06, consistent with a balance of OH sources and sinks across the remote troposphere. Regional phenomena are also highlighted, such as a 10-fold OH depression in the Tropical West Pacific and enhancements in the East Pacific and South Atlantic. This method is complementary to budget-based global OH constraints and can help elucidate the spatial and temporal variability of OH production and methane loss.

Spatiotemporal Dynamics of Surface Ozone and Its Relationship with Meteorological Factors over the Beijing-Tianjin-Tangshan Region, China, from 2016 to 2019.

In recent years, ozone pollution has been increasing in some parts of the world. In this study, we used the Beijing-Tianjin-Tangshan (BJ-TJ-TS) urban agglomeration region as a case study and used satellite remotely sensed inversion data and hourly ground monitoring observations of surface ozone concentrations, meteorological data, and other factors from 2016 to 2019 to explore the spatiotemporal dynamic characteristics of surface ozone concentration and its pollution levels. We also investigated their coupling relationships with meteorological factors, including temperature, pressure, relative humidity, wind velocity, and sunshine duration, in order to support the development of effective control measures for regional ozone pollution. The results revealed that the surface ozone concentration throughout the BJ-TJ-TS region from 2016 to 2019 exhibited an overall pattern of high values in the northwest and low values in the southeast, as well as an obvious difference between built-up and non-built-up areas (especially in Beijing). Meanwhile, a notable increasing trend of ozone levels was discovered in the BJ and TJ areas from 2016 to 2019, whereas this upward trend was not evident in the TS area. In all three areas, the highest monthly average ozone values occurred in the summer month of June, while the lowest monthly average levels occurred in the winter month of December. Their diurnal variation values reached a maximum value at approximately 3:00-4:00 p.m. and a minimum value at approximately 7:00 a.m. It is clear that high temperature, long sunshine duration, low atmospheric pressure, and weak wind velocity conditions, as well as certain relative humidity levels, readily led to high-concentration ozone pollution. Meanwhile, the daily average values of the five meteorological factors on days with Grade I and Grade II ozone pollution displayed different characteristics.

Changes in the ozone chemical regime over the contiguous United States inferred by the inversion of NOx and VOC emissions using satellite observation.

To investigate changes in the ozone (O3) chemical production regime over the contiguous United States (CONUS) with accurate knowledge of concentrations of its precursors, we applied an inverse modeling technique with Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) and total formaldehyde (HCHO) retrieval products in the summers of 2011, 2014, and 2017, years in which United States National Emission Inventory were based. The inclusion of dynamic chemical lateral boundary conditions and lightning-induced nitric oxide emissions significantly account for the contribution of background sources in the free troposphere. Satellite-constrained nitrogen oxide (NOx) and non-methane volatile organic compounds (NMVOCs) emissions mitigate the discrepancy between satellite and modeled columns: the inversion suggested 2.33-2.84 (1.07-1.34) times higher NOx over the CONUS (over urban regions) and 0.28-0.81 times fewer NMVOCs emissions over the southeastern United States. The model-derived HCHO/NO2 column ratio shows gradual spatial changes in the O3 production regime near urban cores relative to previously defined threshold values representing NOx and VOC sensitive conditions. We also found apparent shifts from the NOx-saturated regime to the transition regime (or the transition regime to the NOx-limited regime) over the major cities in the western United States. In contrast, rural areas, especially in the east-southeastern United States, exhibit a decreased HCHO/NO2 column ratio by -1.30 ± 1.71 with a reduction in HCHO column primarily driven by meteorology, becoming sensitive to VOC emissions. Results show that incorporating satellite observations into numerical modeling could help policymakers implement appropriate emission control policies for O3 pollution.

Inhibition of High-Temperature Requirement Protein A2 Protease Activity Represses Myogenic Differentiation via UPRmt.

Skeletal muscles require muscle satellite cell (MuSC) differentiation to facilitate the replenishment and repair of muscle fibers. A key step in this process is called myogenic differentiation. The differentiation ability of MuSCs decreases with age and can result in sarcopenia. Although mitochondria have been reported to be involved in myogenic differentiation by promoting a bioenergetic remodeling, little is known about the interplay of mitochondrial proteostasis and myogenic differentiation. High-temperature-requirement protein A2 (HtrA2/Omi) is a protease that regulates proteostasis in the mitochondrial intermembrane space (IMS). Mice deficient in HtrA2 protease activity show a distinct phenotype of sarcopenia. To investigate the role of IMS proteostasis during myogenic differentiation, we treated C2C12 myoblasts with UCF101, a specific inhibitor of HtrA2 during differentiation process. A key step in this process is called myogenic differentiation. The differentiation ability of MuSCs decreases with age and can result in sarcopenia. Further, CHOP, p-eIF2α, and other mitochondrial unfolded protein response (UPRmt)-related proteins are upregulated. Therefore, we suggest that imbalance of mitochondrial IMS proteostasis acts via a retrograde signaling pathway to inhibit myogenic differentiation via the UPRmt pathway. These novel mechanistic insights may have implications for the development of new strategies for the treatment of sarcopenia.

Time series analysis and spatial distribution map of aggregate risk index due to tropospheric NO2 and O3 based on satellite observation.

A high increase in human activities has led to more emission of air pollutants in metropolises and industrial areas. Recently, remotely sensed data of tropospheric pollutants is used for environmental management and decision-making on large scale. The purpose of this study was a time series analysis of nitrogen dioxide Vertical Column Density (NO2 VCD) and Ozone (O3) using Ozone Monitoring Instrument (OMI) from 2005 to 2016 by Mann-Kendall test. Also, the aggregate risk index (ARI) was calculated to estimate the overall impact of exposure to tropospheric NO2 and O3 concentrations at the national scale in 2016. To estimate the surface NO2 related drivers, The Radial Basis Function (RBF) neural network modeling was performed for different months of 2016. Results of Mann-Kendall test showed that tropospheric ozone concentration had an increasing trend in all parts of Iran and this increasing trend was significantly higher in the southern region of Iran and lower in the northern parts of Iran. NO2 VCD in most parts of Iran had a significant increasing trend. The result of sensitivity analysis showed that NO2 VCD (1.25), the distance to the industrial area, (1.20) and wind speed (1.07) were the most important variables for the estimation of surface NO2 concentration. Spatial ARI with the highest risks is mainly located in the Northern half of Iran, especially in Tehran, Alborz, and Khorasan-e- Razavi provinces, where NO2 and O3 concentrations are very severe. In northern Iran and central cities, the ARI values are calculated from 1.5 to 2.08, indicating the highest human health risks in these regions. The human health risks based on OMI observation were obtained higher in comparison to AQM data because the satellite data coverage is larger than AQM station and monitors transmitted air pollution by the wind in addition to local pollution. Based on this research, using satellite observation for air quality monitoring is a suitable tool for environmental management on a national scale.

Analysis of atmospheric ozone in Fenwei Plain based on remote sensing monitoring.

This study uses the daily product data of the concentration of ozone in the atmospheric column (ozone column concentration) collected by the Aura satellite's Ozone Monitoring Instrument (OMI), to evaluate the ozone pollution status of the Fenwei Plain in east-central China, by employing pixel-based spatial analysis, an θslope trend index, a Hurst index, and grey correlation. The following results were found. (1) The spatial distribution of ozone in the atmosphere of the Fenwei Plain was higher in the north and lower in the south, with high values appearing in Jinzhong, Lvliang, and other cities. (2) The changes in ozone column concentration periodically and seasonally in the Fenwei Plain. Seasonally, the ozone column concentration was highest in spring, followed by summer, winter, and autumn. (3) The pixel-based trend change of the ozone slope (θslope) indicated that the ozone concentration in the region was in a downward trend, while the long-term correlation of the time series trend Hurst index found that the region should expect to see a weak rebound in the ozone column concentration in the future, so that routine monitoring should be strengthened. (4) The present study on the factors influencing the ozone concentration found that the concentration is relatively closely related to temperature, air pressure, humidity, grain sowing area, highway mileage, and secondary industry.

Modeling of spatial and temporal variations of ozone-NOx-VOC sensitivity based on photochemical indicators in China.

Comprehensive air quality model with extensions (CAMx)-decoupled direct method (DDM) was used to simulate ozone-NOx-VOCs sensitivity of for May-November in 2016-2018 in China. Based on the relationship between the simulated ozone (O3) sensitivity values and the ratio of formaldehyde (HCHO) to NO2 (FNR) and the ratio of production rate of hydrogen peroxide (H2O2) to production rate of nitric acid (HNO3) ( [Formula: see text] ), the localized range of FNR and [Formula: see text] thresholds in different regions in China were obtained. The overall simulated FNR values are about 1.640-2.520, and [Formula: see text] values are about 0.540-0.830 for the transition regime. Model simulated O3 sensitivities or region specific FNR or [Formula: see text] thresholds should be applied to ensure the accurate local O3 sensitivity regimes. Using the tropospheric column FNR values from ozone monitoring instrument (OMI) satellite data as an indicator with the simulated threshold values, the spatial distributions of O3 formation regimes in China are determined. The O3 sensitivity regimes from eastern to central China are gradually from VOC-limited, transition to NOx-limited spatially, and moving toward to transition or NOx-limited regime from 2005 to 2019 temporally.

Intramitochondrial proteostasis is directly coupled to α-synuclein and amyloid ß1-42 pathologies.

Mitochondrial dysfunction has long been implicated in the neurodegenerative disorder Parkinson's disease (PD); however, it is unclear how mitochondrial impairment and α-synuclein pathology are coupled. Using specific mitochondrial inhibitors, EM analysis, and biochemical assays, we report here that intramitochondrial protein homeostasis plays a major role in α-synuclein aggregation. We found that interference with intramitochondrial proteases, such as HtrA2 and Lon protease, and mitochondrial protein import significantly aggravates α-synuclein seeding. In contrast, direct inhibition of mitochondrial complex I, an increase in intracellular calcium concentration, or formation of reactive oxygen species, all of which have been associated with mitochondrial stress, did not affect α-synuclein pathology. We further demonstrate that similar mechanisms are involved in amyloid-ß 1-42 (Aß42) aggregation. Our results suggest that, in addition to other protein quality control pathways, such as the ubiquitin-proteasome system, mitochondria per se can influence protein homeostasis of cytosolic aggregation-prone proteins. We propose that approaches that seek to maintain mitochondrial fitness, rather than target downstream mitochondrial dysfunction, may aid in the search for therapeutic strategies to manage PD and related neuropathologies.

Revisiting the levels of Aerosol Optical Depth in south-southeast Asia, Europe and USA amid the COVID-19 pandemic using satellite observations.

The countries around the world are dealing with air quality issues for decades due to their mode of production and energy usages. The outbreak of COVID-19 as a pandemic and consequent global economic shutdown, for the first time, provided a base for the real-time experiment of the effect of reduced emissions across the globe in abetting the air pollution issue. The present study dealt with the changes in Aerosol Optical Depth (AOD), a marker of air pollution, because of global economic shutdown due to the coronavirus pandemic. The study considered the countries in south and south-east Asia (SSEA), Europe and the USA for their extended period of lockdown due to coronavirus pandemic. Daily Aerosol Optical Depth (AOD) from Moderate-resolution imaging spectroradiometer (MODIS) and tropospheric column density of NO2 and SO2 from Ozone monitoring instrument (OMI) sensors, including meteorological data such as wind speed (WS) and relative humidity (RH) were analyzed during the pre-lockdown (2017-2019) and lockdown periods (2020). The average AOD, NO2 and SO2 during the lockdown period were statistically compared with their pre-lockdown average using Wilcoxon-signed-paired-rank test. The accuracy of the MODIS-derived AOD, including the changing pattern of AOD due to lockdown was estimated using AERONET data. The weekly anomaly of AOD, NO2 and SO2 was used for analyzing the space-time variation of aerosol load as restrictions were imposed by the concerned countries at the different points of time. Additionally, a random forest-based regression (RF) model was used to examine the effects of meteorological and emission parameters on the spatial variation of AOD. A significant reduction of AOD (-20%) was obtained for majority of the areas in SSEA, Europe and USA during the lockdown period. Yet, the clusters of increased AOD (30-60%) was obtained in the south-east part of SSEA, the western part of Europe and US regions. NO2 reductions were measured up to 20-40%, while SO2 emission increased up to 30% for a majority of areas in these regions. A notable space-time variation was observed in weekly anomaly. We found the evidence of the formation of new particles for causing high AOD under high RH and low WS, aided by the downward vertical wind flow. The RF model showed a distinguishable relative importance of emission and meteorological factors among these regions to account for the spatial variability of AOD. Our findings suggest that the continued lockdown might provide a temporary solution to air pollution; however, to combat persistent air quality issues, it needs switching over to the cleaner mode of production and energy. The findings of this study, thus, advocated for alternative energy policy at the global scale.

Simulation of average monthly ozone exposure concentrations in China: A temporal and spatial estimation method.

BACKGROUND: Ozone has adverse effects on human health, it is necessary to obtain the refined ozone exposure concentration. At present, most of existing ozone exposure research is based on ground air quality monitoring station (MS) which gather urban area information only. It is diffcult to estimate the ozone in the areas where MSs are scarce. OBJECTIVE: By combining accurate but uneven data of outdoor ozone exposure concentrations based on MSs and unbiased coverage data based on RS in China, we can improve the accuracy of simulation of average monthly ozone exposure concentrations in monitor-free area. Since ozone concentrations are usually low at night, ozone exposure is assessed during the day (e.g., 10:00-18:00). METHODS: We proposed a space-time geostatistical kriging interpolation based on the composite space/time mean trend model (CSTM) to predict ozone exposure in mainland China, having obtained a refined ozone exposure concentration interpolation map from an MS. We verified the accuracy of the interpolation results and remote sensing (RS) data, while simultaneously determining the distance threshold (according to the data accuracy) to improve the accuracy of the hybrid map. RESULTS: We used a refined smoothing filter to reduce the influence of spatial and seasonal trends on ozone concentration. We found a cutoff separation distance of 175 km at which the two data showed an equal estimation accuracy, and the estimation result was fused with RS data through the distance threshold. Finally, The multi-source data with the best accuracy were fused to obtain the refined map. In China, ozone exposure concentration mainly gathers in the northern and eastern regions as well as part of the central mainland. CONCLUSIONS: RS data can be used to characterize ground ozone exposure concentrations when 24th-layer data and MS data for monitoring ozone exposure concentrations are combined to estimate temporal and spatial ozone exposure in China. Ozone exposure in China can be explored further to provide suggestions for human health and regional economic development.

Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO2 variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations.

The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO2 due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO2 concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO2 VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO2 concentrations. The daily variations of atmospheric NO2 during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24-30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO2 reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO2 reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO2 concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.