Search

The association between short-term ambient air pollution (AAP) exposure and blood lipids is inconsistent across populations. This study aimed to investigate the modifying effects of fasting blood glucose (FBG) levels on the associations between short-term AAP exposure and blood lipids in 110,637 male participants from Beijing, China. The results showed that FBG modified the association between short-term AAP exposure and blood lipids, especially low-density lipoprotein cholesterol (LDL-C). In the hyperglycemia group, a 10-μg/m3 increase in particles with diameters ≤ 2.5 μm (PM2.5), particles with diameters ≤ 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), or a 1-mg/m3 increase in carbon monoxide (CO) was associated with a 0.454%, 0.305%, 1.507%, 0.872%, or 3.961% increase in LDL-C, respectively. In the nonhyperglycemic group, short-term increases in air pollutants were even associated with small decreases in LDL-C. The findings demonstrate that lipids in hyperglycemic individuals are more vulnerable to short-term AAP exposure than those in normal populations. [ABSTRACT FROM AUTHOR]

The impact of contextual bias has been demonstrated repeatedly across forensic domains; however, research on this topic in forensic toxicology is very limited. In our previous study, experimental data from only one context version were compared with the actual forensic biasing casework. As a follow‐up, this controlled experiment with 159 forensic toxicology practitioners was conducted, to test whether knowledge of different contextual information influenced their forensic decision‐making. Participants in different context groups were tasked to identify testing strategies for carbon monoxide and opiate drugs. The results of chi‐squared tests for their selections and two context groups exhibited statistically significant differences (p < 0.05 or p < 0.01). These findings show contextual information can bias forensic toxicology decisions about testing strategies, despite it is a relatively objective domain in forensic science. [ABSTRACT FROM AUTHOR]

Constructing a highly resolved comprehensive emission dataset for China is challenging due to limited availability of refined information for parameters in a unified bottom-up framework. Here, by developing an integrated modeling framework, we harmonized multi-source heterogeneous data, including several up-to-date emission inventories at national and regional scales and for key species and sources in China to generate a 0.1° resolution inventory for 2017. By source mapping, species mapping, temporal disaggregation, spatial allocation, and spatial–temporal coupling, different emission inventories are normalized in terms of source categories, chemical species, and spatiotemporal resolutions. This achieves the coupling of multi-scale, high-resolution emission inventories with the Multi-resolution Emission Inventory for China (MEIC), forming the high-resolution INTegrated emission inventory of Air pollutants for China (INTAC). We find that INTAC provides more accurate representations for emission magnitudes and spatiotemporal patterns. In 2017, China's emissions of sulfur dioxide (SO2), nitrous oxides (NOx), carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs), ammonia (NH3), PM10 and PM2.5 (particulate matter), black carbon (BC), and organic carbon (OC) were 12.3, 24.5, 141.0, 27.9, 9.2, 11.1, 8.4, 1.3, and 2.2 Tg , respectively. The proportion of point source emissions for SO2 , PM10 , NOx , and PM2.5 increases from 7 %–19 % in MEIC to 48 %–66 % in INTAC, resulting in improved spatial accuracy, especially mitigating overestimations in densely populated areas. Compared with MEIC, INTAC reduces mean biases in simulated concentrations of major air pollutants by 2–14 µgm-3 across 74 cities, compared against ground observations. The enhanced model performance by INTAC is particularly evident at finer-grid resolutions. Our new dataset is accessible at http://meicmodel.org.cn/intac (last access: 15 April 2024) and 10.5281/zenodo.10459198 (Wu et al., 2024), and it will provide a solid data foundation for fine-scale atmospheric research and air-quality improvement. [ABSTRACT FROM AUTHOR]

Events of stratospheric intrusions to the surface (SITS) can lead to severe ozone (O3) pollution. Still, to what extent SITS events impact surface O3 on a national scale over years remains a long-lasting question, mainly due to difficulty of resolving three key SITS metrics: frequency, duration and intensity. Here, we identify 27,616 SITS events over China during 2015-2022 based on spatiotemporally dense surface measurements of O3 and carbon monoxide, two effective indicators of SITS. An overview of the three metrics is presented, illustrating large influences of SITS on surface O3 in China. We find that SITS events occur preferentially in high-elevation regions, while those in plain regions are more intense. SITS enhances surface O3 by 20 ppbv on average, contributing to 30-45% of O3 during SITS periods. Nationally, SITS-induced O3 peaks in spring and autumn, while over 70% of SITS events during the warm months exacerbate O3 pollution. Over 2015-2022, SITS-induced O3 shows a declining trend. Our observation-based results can have implications for O3 mitigation policies in short and long terms. The authors analyze the frequency, duration and intensity of stratospheric intrusions to the surface in China over 2015-2022 and find that such intrusions enhance surface ozone pollution, especially in spring and autumn, followed by summer. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) is one of the six major pollutants and mainly comes from anthropogenic emissions. CO has active chemical properties, and its concentrations vary distinctly in the atmosphere, thus creating great uncertainty in forecasts. In this study, we conducted a data assimilation forecast system, i.e., CO-FCST, by coupling the proper orthogonal decomposition (POD) technique with an atmosphere transport model, i.e., CMAQ (Community Multiscale Air Quality model). The CO-FCST was then used in two districts, i.e., Shangdianzi (SDZ, located 40 km northeast of Beijing) and Waliguan (WLG, located in Qinghai Province, China), in China for CO concentration forecasts with a couple of continuous hourly surface CO observation datasets. The results show that after optimization by the CO-FCST system, CO concentrations had significant improvements in forecasting in both areas. In addition, the two posteriors were much higher than the two priors, i.e., 31.7% higher in SDZ and 62.3% higher in WLG. [ABSTRACT FROM AUTHOR]

The number of cars is increasing every year and the environmental aspects of transport are becoming a hot topic. The spatial and temporal patterns of motor vehicle carbon monoxide (CO) emissions are still unclear due to the unbalanced economic development and heterogeneous geographic conditions of China. With the objective of realizing a reduction in motor vehicle CO emissions, his study explores the transport carbon emission reduction pathways of China from motor vehicle CO emission. Firstly, the entropy method is adopted to comprehensively evaluate the CO emissions from motor vehicles in each province; secondly, the development of a Geographically and Temporally Weighted Regression (GTWR) model facilitates the examination of the spatiotemporal dynamics pertaining to the influencing factors of motor vehicle CO emissions within each province.; finally, the characteristics of motor vehicle CO emissions in ETS pilot areas and non-ETS pilot areas are compared. The results show that: (1) After the completion of the six ETS pilot areas in 2011, the CO emission from motor vehicles is reduced by 18% compared with 2010.(2)The entropy method shows that the largest CO emissions from motor vehicles are from Beijing, Shanghai, Guangdong and other provinces with high economic levels.(3) The results of the GTWR model show that the positive effects of economic level, population size, road mileage intensity and motor vehicle intensity on motor vehicle CO emissions are decreasing year by year. The negative effect of metro line intensity on CO emission decreases year by year. This study can help decision makers to identify the high emission areas, understand the influencing factors, and formulate emission reduction measures to achieve the purpose of carbon emission reduction in transport. [ABSTRACT FROM AUTHOR]

Accurately estimating the concentration of carbon monoxide (CO) with high spatiotemporal resolution is crucial for assessing its meteorological-environmental-health impacts. Although machine learning models have high predictive ability in environmental research, there are relatively few explanations for model outputs. Utilizing the top-of-atmosphere radiation data of China's new generation geostationary satellites (FY-4A and FY-4B) and interpretable machine learning models, the 24-hour near-surface CO concentrations in China was conducted (resolution: 1 hour, 0.04°). The model improved by 6.6% when using the all-sky dataset (cloud-contained model, R2 = 0.759) compared to the clear-sky dataset (cloud-removed model). The interpretability analysis of the CO estimation model used two methods, namely ante-hoc (model feature importance) and post-hoc (SHapley Additive exPlanations). The importance of daytime meteorological factors increased by 51% compared to nighttime. Combining partial dependency plots, the impact of key meteorological factors on CO was elucidated to gain a deeper understanding of the spatiotemporal variations of CO. [ABSTRACT FROM AUTHOR]

The high altitude in mountainous regions results in lower atmospheric pressure, oxygen concentration and temperature, leading to lower combustion efficiency in motor vehicles. Therefore, there may be differences in carbon dioxide (CO2), carbon monoxide (CO), and nitrogen oxides (NOx) emissions characteristics at different altitudes. In this study, a portable emission measurement system was used to investigate the effects of varying elevations on the emission factors of CO2, CO, and NOx on diesel and gasoline-powered vehicles at altitudes ranging from 2270 to 4540 m in the Qinghai–Tibet Plateau of China. Additionally, the influencing factors of CO2, CO, and NOx emissions were studied. Results showed that the CO2, CO, and NOx emission factors for diesel vehicles varied in the range of 161.83–195.54, 0.59–0.77, and 4.61–6.58 g/km; the population means with 90% confidence intervals were 178.54, 0.68, and 5.60 g/km, respectively. For gasoline vehicles, the CO2, CO, and NOx emission factors varied in the range of 161.66–181.98, 0.95–1.06, and 0.12–0.25 g/km; the population means with 90% confidence intervals were 171.82, 1.01, and 0.19 g/km, respectively. Overall, the emission factors of diesel vehicles were higher than those of gasoline vehicles, and the emissions increased with increasing altitude. Atmospheric pressure was identified as the primary environmental factor affecting CO2, CO, and NOx emissions. As the speed of motor vehicles increased, the emission of CO2 also increased, while there was a quadratic relationship with acceleration. This study provides a reference and guidance for vehicle pollution control in high-altitude regions. [ABSTRACT FROM AUTHOR]

Top-down observational constraints on emissions flux estimates from satellite observations of chemical composition are subject to biases and errors stemming from transport, chemistry and prior emissions estimates. In this context, we developed an ensemble data assimilation system to optimize the initial conditions for carbon monoxide (CO) and aerosols, while also quantifying the respective emission fluxes with a distinct attribution of anthropogenic and wildfire sources. We present the separate assimilation of CO profile v9 retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument and Aerosol Optical Depth (AOD), collection 6.1, from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. This assimilation system is built on the Data Assimilation Research Testbed (DART) and includes a meteorological ensemble to assimilate weather observations within the online Community Atmosphere Model with Chemistry (CAM-chem). Inversions indicate an underestimation of CO emissions in CAMS-GLOB-ANT_v5.1 in China for 2015 and an overestimation of CO emissions in the Fire INventory from NCAR (FINN) version 2.2, especially in the tropics. These emissions increments are consistent between the MODIS AOD and the MOPITT CO-based inversions. Additional simulations and comparison with in situ observations from the NASA Atmospheric Tomography Mission (ATom) show that biases in hydroxyl radical (OH) chemistry dominate the CO errors. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to assess the association between solid fuel use for cooking or heating and the risk of hypertension among individuals older than 45 years. Methods: Baseline questionnaires were used to collect self-reported primary cooking and heating fuel usage. Outcomes were defined as the time of first diagnosis of hypertension. Data were analyzed using Cox proportional hazards models. Results: Solid fuel use for cooking was associated with a higher risk of hypertension. The association between solid fuel for cooking and hypertension remained significant among residents in north China, individuals aged 45 to 65 years, urban residents, and nonsmokers. Solid fuel for heating was associated with a higher risk of hypertension only in South China. Conclusions: Solid fuel use may result in an increased risk of hypertension. Our findings further emphasize the health hazards of solid fuel for cooking and heating. [ABSTRACT FROM AUTHOR]

China's annual metallurgical by-product gas production exceeds 1400 billion Nm3, the calorific equivalent of ∼266 million tonnes of coal. The widely-studied blast furnace gas used in hydrogen-enriched carbonic oxide recycling oxygenate furnaces ensures carbon-reduction. Converter gas contains abundant heat resources, equivalent to ∼6.5 million tonnes of coal. Using high-temperature by-product gas online reforming methods to convert thermal energy into chemical energy and combining it with power generation and other industries imparts physical heat recovery exceeding 60%. China's annual coke oven gas (COG) production could support more than 100 million tonnes of direct reduced iron production, thus reducing CO 2 emissions by more than 150 million tonnes (nearly 10% of China's steel industry CO 2 emissions). We summarise the characteristics, availability, and steel-chemical co-production utilisation of three by-product gases, and discuss the application of COG in direct reduced iron production and development of metallurgical by-product gas utilisation for carbon reduction in China. • Development direction of metallurgical by-product gas. • The utilisation of by-product gas in steel-chemical co-production. • Coke oven gas for direct reduction ironmaking. • Online reforming method to convert thermal energy into chemical energy. • Blast furnace gas for hydrogen-enriched carbonic oxide recycling oxygenate furnace. [ABSTRACT FROM AUTHOR]

Exhaust emissions from ships have garnered significant attention because of their impact on global climate change, deterioration of air quality, and potential risks to human health. Consequently, it is necessary and urgent to quantify the gaseous and particulate emission factors (EFs) of ships in a local area. In order to supplement native EF profile data, an inland cargo ship in China was selected for measuring gaseous and particle pollutants under real-world operation modes. The fuel-based EFs of carbon dioxide, carbon monoxide (CO), nitrogen oxides, and hydrocarbons (THC) were 2965–3144 g/kg, 8.04–83.53 g/kg, 64.51–126.20 g/kg, and 3.90–23.35 g/kg, respectively. The maximum values of CO EF and THC EF were achieved under idling mode, which were 10.4 and 5.3 times those observed under cruising (500 rpm) mode, as extremely poor engine loads under idling mode can result in low temperature, low pressure, and uneven mixture of air and fuel. Organic carbon and element carbon were identified as the most abundant compositions of particulate matter (PM). Ions and elements were primarily dominated by SO42− and S, which can be attributed to the utilization of fuels with high sulfur content. Additionally, hopanes (dominated by 17α(H),21β(H)-Hopane and 17α(H),21β(H)-29-Norhopane) and fatty acids (dominated by n-Hexadecanoic acid and n-Octadecanoic acid) have the potential to serve as tracers for ship exhaust emissions. Pyrene and fluoranthene, two EPA priority polycyclic aromatic hydrocarbons (PAHs), were identified as the major constituents of PAHs and accounted for 50% of total PAHs. This finding also provides an explanation for the significant contribution of four-ring PAHs to the total PAHs mass. [ABSTRACT FROM AUTHOR]

This study aims to analyse the spatial and temporal characteristics of the transfer of pollutants, including carbon monoxide (CO), ammonia (NH3), non‐methane volatile organic compounds (NMVOCs), sulphur dioxide (SO2), nitrogen oxide (NOX), and particulate matter with particle size below 10 microns (PM10), which are embodied in the bilateral trade between China and India, and the transfer paths between various industries. A multiregional input–output model (MRIO) is constructed based on the EORA Database to track the economic connections and the effects of specific products across regional supply chains. The empirical results indicate the following significant findings. China is a net exporter of embodied pollutants in bilateral trade, and India is a net importer. CO accounted for the most significant amount of pollutants emitted by the bilateral trade between China and India. The energy intensity has mainly adverse effects on emissions of six pollutants, while the consumption scale has overall positive effects. Metal products and mining and quarrying are the top two industries producing the highest emissions at the export ends. The emissions of certain pollutants, such as SO2, are also particularly pronounced in individual sectors. Construction and electrical and machinery are the highest CO‐importing sectors of China and India. [ABSTRACT FROM AUTHOR]

Background: The impact of exposure to ambient pollutants on influenza transmissibility is poorly understood. We aim to examine the associations of six ambient pollutants with influenza transmissibility in China and assess the effect of the depletion of susceptibles. Methods: Provincial‐level surveillance data on weekly influenza‐like illness (ILI) incidence and viral activity were utilized to estimate the instantaneous reproduction number (Rt) using spline functions. Log‐linear regression and the distributed lag non‐linear model (DLNM) were employed to investigate the effects of ambient pollutants—ozone (O3), particulate matter ≤2.5 μm (PM2.5), particulate matter ≤10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)—on influenza transmissibility across 30 Chinese provinces from 2014 to 2019. Additionally, the potential effects of the depletion of susceptibles and regional characteristics were explored. Results: There is a significantly positive correlation between influenza transmissibility and five distinct ambient pollutants: PM2.5, PM10, SO2, CO, and NO2. On average, these ambient pollutants explained percentages of the variance in Rt: 0.8%, 0.8%, 1.9%, 1.3%, and 1.4%, respectively. Conversely, O3 was found to be negatively associated with Rt, explaining 1.5% of the variance in Rt. When controlling for the effect of susceptibles depletion, the effects of all pollutants were more pronounced. The effects of PM2.5, PM10, CO, and SO2 were higher in the eastern and southern regions. Conclusions: Most ambient pollutants may potentially contribute to the facilitation of human‐to‐human influenza virus transmission in China. This observed association was maintained even after adjusting for variation in the susceptible population. [ABSTRACT FROM AUTHOR]

Many studies in China investigated how the lockdown following the coronavirus disease 2019 substantially affected air quality; however, few were conducted in Northeastern China. Here, the changes in six criteria air pollutants, including particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3), were investigated in Shenyang from January to May 2015-2020. Compared with the pre-lockdown, the mass concentrations of PM2.5, PM10, SO2, NO2, and CO during the lockdown decreased by 40.3% to 48.6%, indicating a positive impact of lockdown policies on reducing pollutant emissions. The responses of PM2.5, PM10, and CO to the lockdown measures in downtown areas were more sensitive than in the suburbs. However, the O3 concentration showed the opposite trend, attributed to the drop in NOx and particulate matters. Compared to the same period in 2015-2019, the proportion of days with good air quality increased from 63.2% to 77.2% during the lockdown and Shenyang experienced no severe pollution. Our results suggest that reducing human activities can improve air quality; however, coordinated control policies of O3, PM2.5, and NO2 are imperative. [ABSTRACT FROM AUTHOR]

Below-cloud wet scavenging is an important pathway to remove atmospheric aerosols. The below-cloud wet-scavenging coefficient (BWSC) is the value to describe the ability of rainfall to remove aerosols. The reported BWSCs obtained from the field measurements are much higher than the theory, but the reason for this remains unclear. Based on the long-term field measurements in the Yangtze River Delta of eastern China, we find that 28 % of the rainfall events are high-BWSC events. The high-BWSC events show the sudden decrease in the particle number concentration in all size bins near the end of rainfall. By investigating the simultaneously observed changes in carbon monoxide and aerosol chemical compositions during rainfall events, the circulation patterns, and backward trajectories, we find the cause of the high-BWSC events is the air mass changing but not the wet scavenging. The change in air masses is always followed by the rainfall processes and cannot be screened out by the traditional meteorological criteria, which would cause the overestimation of BWSC. After excluding the high-BWSC events, the observed BWSC is close to the theory and is correlated with the rainfall intensity and particle number concentrations prior to rainfall. This study highlights that the discrepancy between the observed BWSC and the theoretical value may not be as large as is currently believed. To obtain reasonable BWSCs and parameterization from field measurements, the effect of air mass changing during rainfall needs to be carefully considered. [ABSTRACT FROM AUTHOR]

Surface ozone increased unexpectedly over northern China during the COVID-19 lockdown (CLD) period (23 January–29 February 2020), which was characterized by vigorous emission reduction. The reasons for this ozone enhancement have been speculated from perspectives of chemical responses to the emissions and meteorology. As known, the processes of natural stratospheric ozone injecting to the troposphere are most active in winter and spring. Yet, little attention was paid to stratospheric influences on this ozone enhancement. Here we report a stratospheric intrusion (SI) that reached the surface over northern China on 15–17 February during the CLD. The coevolution of enhanced ozone and sharply declined carbon monoxide and relative humidity (RH) was indicative of the SI occurrence. We show that the SI was facilitated by a cutoff low system that led to abnormally high surface ozone in most part of northern China. We estimate that over the SI period, the injected stratospheric ozone constituted up to 40–45% of the surface ozone over northern China. If the stratospheric ozone inputs were scaled over the entire CLD period, these inputs would account for 4–8% of the surface ozone. In view of the unexpected ozone increase during the CLD, this SI event could explain up to 18% of the ozone increase in some cities, and average 5–10% over larger areas that were affected. Hence, the nonnegligible stratospheric influences urge extra consideration of natural ozone sources in disentangling the role of emission reduction and meteorological conditions during the CLD in China and elsewhere in the world. [ABSTRACT FROM AUTHOR]

The effect of environmental and socioeconomic conditions on the global pandemic of COVID-19 had been widely studied, yet their influence during the early outbreak remains less explored. Unraveling these relationships represents a key knowledge to prevent potential outbreaks of similar pathogens in the future. This study aims to determine the influence of socioeconomic, infrastructure, air pollution, and weather variables on the relative risk of infection in the initial phase of the COVID-19 pandemic in China. A spatio-temporal Bayesian zero-inflated Poisson model is used to test for the effect of 13 socioeconomic, urban infrastructure, air pollution, and weather variables on the relative risk of COVID-19 disease in 122 cities of China. The results show that socioeconomic and urban infrastructure variables did not have a significant effect on the relative risk of COVID-19. Meanwhile, COVID-19 relative risk was negatively associated with temperature, wind speed, and carbon monoxide, while nitrous dioxide and the human modification index presented a positive effect. Pollution gases presented a marked variability during the study period, showing a decrease of CO. These findings suggest that controlling and monitoring urban emissions of pollutant gases is a key factor for the reduction of risk derived from COVID-19. [ABSTRACT FROM AUTHOR]

Exposure to air pollution is one of the greatest environmental risks for human health. Air pollution level is significantly driven by anthropogenic emissions and meteorological conditions. To protect people from air pollutants, China has implemented clean air actions to reduce anthropogenic emissions, which has led to rapid improvement in air quality over China. Here, we evaluated the impact of anthropogenic emissions and meteorological conditions on trends in air pollutants in a coastal city (Lianyungang) in eastern China from 2015 to 2022 based on a random forest model. The annual mean concentration of observed air pollutants, including fine particles, inhalable particles, sulfur dioxide, nitrogen dioxide, and carbon monoxide, presented significant decreasing trends during 2015–2022, with dominant contributions (55–75%) by anthropogenic emission reduction. An increasing trend in ozone was observed with an important contribution (28%) by anthropogenic emissions. The impact of meteorological conditions on air pollution showed significant seasonality. For instance, the negative impact on aerosol pollution occurred during cold months, while the positive impact was in warm months. Health-risk-based air quality decreased by approximately 40% in 8 years, for which anthropogenic emission made a major contribution (93%). [ABSTRACT FROM AUTHOR]

The atmospheric oxidation capacity (AOC) characterizes the ability of the atmosphere to scavenge air pollutants. However, it is not well understood in China, where anthropogenic emissions have changed dramatically in the past decade. A detailed analysis of different parameters that determine the AOC in China is presented on the basis of numerical simulations performed with the regional chemical-meteorological model WRF-Chem. The model results, with the aerosol effects of extinction and heterogeneous processes taken into account, show that the presence of aerosols leads to a decrease in surface ozone of approximately 8–10 ppbv in NOx-limited rural areas and an increase of 5–10 ppbv in VOC-limited urban areas. The ozone reduction in NOx-sensitive regions is due to the combined effect of nitrogen dioxide and peroxy radical uptake on particles and of the light extinction by aerosols, which affects the photodissociation rates. The ozone increase in VOC-sensitive areas is attributed to the uptake of NO2 by aerosols, which is offset by the reduced ozone formation associated with HO2 uptake and with the aerosol extinction. Our study concludes that more than 90 % of the daytime AOC is due to the reaction of the hydroxyl radical with VOCs and carbon monoxide. In urban areas, during summertime, the main contributions to daytime AOC are the reactions of OH with alkene (30–50 %), oxidized volatile organic compounds (OVOCs) (33–45 %), and carbon monoxide (20–45 %). In rural areas, the largest contribution results from the reaction of OH with alkenes (60 %). Nocturnal AOC is dominantly attributed to the nitrate radical (50–70 %). Our results shed light on the contribution of aerosol-related NOx loss and the high reactivity of alkenes for photochemical pollution. With the reduction of aerosols and anthropogenic ozone precursors, the chemistry of nitrogen and temperature-sensitive VOCs will become increasingly important. More attention needs to be paid to the role of photodegradable OVOCs and nocturnal oxidants in the formation of secondary pollutants. [ABSTRACT FROM AUTHOR]

Few studies have examined the link between short-term exposure to air pollutants and atrial fibrillation (AF) episodes. This study aims to examine the association of hourly criteria air pollutants with AF episodes. We employ a smart device-based photoplethysmography technology to screen AF from 2018 to 2021. Hourly concentrations of six criteria air pollutants are matched to the onset hour of AF for each participant. We adopt a time-stratified case-crossover design to capture the acute effects of air pollutants on AF episodes, using conditional logistic regression models. Subgroup analyses are conducted by age, gender, and season. A total of 11,906 episodes of AF are identified in 2976 participants from 288 Chinese cities. Generally, the strongest associations of air pollutants are present at lag 18–24 h, with positive and linear exposure-response relationships. For an interquartile range increase in inhalable particles, fine particles, nitrogen dioxide, and carbon monoxide, the odds ratio (OR) of AF is 1.19 [95% confidential interval (CI): 1.03, 1.37], 1.38 (95%CI: 1.14, 1.67), 1.60 (95%CI: 1.16, 2.20) and 1.48 (95%CI: 1.19, 1.84), respectively. The estimates are robust to the adjustment of co-pollutants, and they are larger in females, older people, and in cold seasons. There are insignificant associations for sulfur dioxide and ozone. This nationwide case-crossover study demonstrates robust evidence of significant associations between hourly exposure to air pollutants and the onset of AF episodes, which underscores the importance of ongoing efforts to further improve air quality as an effective target for AF prevention. [ABSTRACT FROM AUTHOR]

Copyright of Industrial Minerals & Processing / Huagong Kuangwu yu Jiagong is the property of Industrial Minerals & Processing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. Over‐dispersed generalized additive model was adopted to quantity the associations between CO and COPD with T2DM or hypertension. Based on principal diagnosis, COPD cases were identified according to the International Classification of Diseases (J44), and a history of T2DM and hypertension was coded as E12 and I10‐15, O10‐15, P29, respectively. A total of 459,258 COPD cases were recorded from 2014 to 2019. Each interquartile range uptick in CO at lag 03 corresponded to 0.21% (95%CI: 0.08%–0.34%), 0.39% (95%CI: 0.13%–0.65%), 0.29% (95%CI: 0.13%–0.45%) and 0.27% (95%CI: 0.12%–0.43%) increment in admissions for COPD, COPD with T2DM, COPD with hypertension and COPD with both T2DM and hypertension, respectively. The effects of CO on COPD with T2DM (Z = 0.77, P = 0.444), COPD with hypertension (Z = 0.19, P = 0.234) and COPD with T2DM and hypertension (Z = 0.61, P = 0.543) were insignificantly higher than that on COPD. Stratification analysis showed that females were more vulnerable than males except for T2DM group (COPD: Z = 3.49, P < 0.001; COPD with T2DM: Z = 0.176, P = 0.079; COPD with hypertension: Z = 2.48, P = 0.013; COPD with both T2DM and hypertension: Z = 2.44, P = 0.014); No statistically significant difference could be found between age groups (COPD: Z = 1.63, P = 0.104; COPD with T2DM: Z = 0.23, P = 0.821; COPD with hypertension: Z = 0.53, P = 0.595; COPD with both T2DM and hypertension: Z = 0.71, P = 0.476); Higher effects appeared in cold seasons than warm seasons on COPD (Z = 0.320, P < 0.001). This study demonstrated an increased risk of COPD with comorbidities related to CO exposure in Beijing. We further provided important information on lag patterns, susceptible subgroups, and sensitive seasons, as well as the characteristics of the exposure‐response curves. Plain Language Summary: The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. The aim of this study was to investigate the acute adverse effect of CO on admission of COPD, and COPD with T2DM or hypertension in Beijing, China. Our findings revealed that short‐term exposure to CO significantly increased the risk of COPD and COPD comorbidities admissions. Females were more vulnerable to CO exposure among COPD with comorbidities (expect T2DM group). We found higher effects appeared in cold season than warm season among COPD group. The exposure response relationship showed that there was no significant threshold effect between CO and COPD admission. Key Points: Exposure to CO was associated with an increased risk of chronic obstructive pulmonary disease (COPD) with comorbiditiesFemales were more vulnerable to CO exposure among COPD with comorbiditiesHigher effect appeared in cold season than warm season among COPD group [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO), acetylene (C 2 H 2), ethane (C 2 H 6), formaldehyde (H 2 CO), and hydrogen cyanide (HCN) are important trace gases in the atmosphere. They are highly related to biomass burning, fossil fuel combustion, and biogenic emissions globally, affecting air quality and climate change. However, the variations and correlations among these species are not well known in northern China due to limited measurements. In June 2018, we installed a new ground-based Fourier transform infrared (FTIR) spectrometer (Bruker IFS 125HR) recording mid-infrared high spectral resolution solar-absorption spectra at Xianghe (39.75 ∘ N, 116.96 ∘ E), China. In this study, we use the latest SFIT4 code, together with advanced a priori profiling and spectroscopy, to retrieve these five species from the FTIR spectra measured between June 2018 and November 2021. The retrieval strategies, retrieval information and retrieval uncertainties are presented and discussed. For the first time, the time series, variations, and correlations of these five species are analyzed at a typical polluted site in northern China. The seasonal variations in C 2 H 2 and C 2 H 6 total columns show a maximum in winter–spring and a minimum in autumn, whereas the seasonal variations in H 2 CO and HCN show a maximum in summer and a minimum in winter. Unlike the other four species, the FTIR measurements show that there is almost no seasonal variation in the CO column. The correlation coefficients (R) between the synoptic variations in CO and the other four species (C 2 H 2 , C 2 H 6 , H 2 CO, and HCN) are between 0.68 and 0.80, indicating that they are affected by common sources. Using the FLEXPART model backward simulations and satellite fire measurements, we find that the variations in CO, C 2 H 2 , C 2 H 6 , and H 2 CO columns are mainly dominated by the local anthropogenic emissions, while HCN column observed at Xianghe is a good tracer to identify fire emissions. [ABSTRACT FROM AUTHOR]

Since its launch on 13 October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) mission has been measuring the solar radiation backscattered by Earth's atmosphere and surface. In this study, we evaluate the TROPOMI operational methane (CH4) and carbon monoxide (CO) products' performance results covering about 3 years using the only two global Total Carbon Column Observing Network (TCCON) sites in China, i.e., the Hefei site and the Xianghe site. These two sites have recently joined the TCCON, and this study uses the both sites simultaneously to validate the TROPOMI products over China for the first time. We found that the systematic bias with rescaling between the TROPOMI CO products and the Hefei site is on average 1.78 ± 6.35 ppb or 1.18 ± 5.35%. The systematic bias with rescaling between the TROPOMI CO products and the Xianghe site is on average 5.33 ± 14.24 ppb or 3.85 ± 10.30%. Both the stations show a correlation above 0.9. The TROPOMI CO data are systematically higher than the two TCCON sites measurements in China. We found that the systematic bias with rescaling between the TROPOMI CH4 products and the Hefei site is on average −4.13 ± 11.65 ppb or −0.22 ± 0.62%. The systematic bias between the TROPOMI CH4 products and Xianghe site is on average −7.25 ± 10.72 ppb or −0.39 ± 0.57%. Both the stations show a correlation above 0.9. The TROPOMI CH4 data are systematically lower than the two TCCON sites measurements in China. We found that the bias between the TROPOMI and the two sites' data as a function of the coincident radius around the two sites is mostly affected by localized emissions for both CO and CH4. We also observe a CO decreasing trend and a CH4 increasing trend in the year-to-year relative changes from 2019 to 2021. Validating against reference from Hefei and Xianghe TCCON site demonstrates the high quality of TROPOMI CO and CH4 data over China. [ABSTRACT FROM AUTHOR]

Summary: We hypothesized that air pollution could cause oxidative damage and inflammation in the human body, which was linked to bone loss. Our result showed that long-term exposure to air pollution might decrease bone mineral density (BMD) T-score and increase the prevalence of osteoporosis in Hubei province. Introduction: Osteoporosis is becoming an increasingly serious public health problem with the advent of global aging. Long-term exposure to air pollution has been linked to multitudinous adverse health outcomes, but evidence is still relatively limited and inconsistent for BMD T-score and osteoporosis. This study aimed at exploring the associations between long-term exposure to air pollution and BMD T-score and osteoporosis. Methods: The Hubei part of the China Osteoporosis Prevalence Study was extracted. Data on air pollutants were collected by the national air quality real-time release platform of China Environmental Monitoring Station. Linear mixed models and multilevel logistic regression analyses were performed to assess the associations between air pollution and BMD T-score and osteoporosis, respectively. Subgroup analyses were conducted to identify vulnerable populations. Results: A total of 1845 participants were included in this cross-section study. Per 10 ug/m3 increase in PM2.5 and SO2 were associated with 0.20 (95% CI: 0.04, 0.36) and 0.31 (95% CI: 0.11, 0.51) decrease in BMD T-score of the neck of femur, respectively. Per 10 ug/m3 increase in CO was linked with 0.03 (95% CI: 0.02, 0.05) decrease in BMD T-score of the total hip. Per 1 ug/m3 increase in PM2.5 was associated with 5% increase in the prevalence of osteoporosis in all participants. In general, the higher concentrations of PM2.5 with the more adverse effect on osteoporosis (P for trend = 0.01). The impact of PM2.5 on osteoporosis in males was higher than that in females [1.29, 95% CI (1.11, 1.50) vs 1.01, 95% CI (0.95, 1.07)]. Per 1 ug/m3 increase in PM10 corresponded with 4% elevation in the risks of osteoporosis in rural population. The ORs (95% CI) for the association of osteoporosis and NO2 in ever/current smoking and drinking population were 1.07 (1.01, 1.13) and 1.05 (1.00, 1.09), respectively. SO2 had a statistically significant positive effect on people with comorbidity [OR = 1.10, (95% CI: 1.00 to 1.21)], while none in people without comorbidity [OR = 0.96, (95% CI: 0.88 to 1.05)]. Conclusion: Our study provided evidence that long-term exposure to PM2.5 was linked with the decreased BMD T-score and increased risk of osteoporosis among all participants. The adverse impacts of PM2.5, PM10, and NO2 were larger in males than in females. People having comorbidity, living in rural areas, and current/ever smoking or drinking were more vulnerable to air pollution. Public health departments should consider air pollution to formulate better preventive measures for osteoporosis. [ABSTRACT FROM AUTHOR]

Evidence on the relationship between prenatal exposure to NO2 and CO and spontaneous abortion (SAB) is insufficient. We investigated whether there is an association between maternal exposure to nitrogen dioxide (NO2) and carbon monoxide (CO) before and during pregnancy and SAB. We conducted a case-control study using medical records of 2445 pregnant women who admitted for abortion prior to 20 weeks of gestational age from January 2014 to December 2019 at a tertiary-care hospital in Shanghai, China. Of the 2445 participants, 1075 were SAB cases and 1370 were healthy controls (underwent elective abortions). Maternal exposure to NO2 and CO before and during pregnancy was estimated using daily air pollution concentration data. Multivariable logistic regression models were constructed to quantify the relationships between maternal exposure to NO2 or CO and the risk of SAB while controlling for potential confounders. NO2 exposure levels during pregnancy were significantly higher in SAB cases than in healthy controls (42.26 vs. 40.67, p <.01). NO2 exposure during pregnancy was positively associated with the risk of SAB. An interquartile range (16 μg/m3) increase in NO2 exposure was associated with 68% increase in the odds of SAB (OR = 1.68, 95% CI, 1.28, 2.21). Analyses of associations by quartile of NO2 exposure showed that elevated NO2 exposure during pregnancy was associated with increased odds of SAB in linear dose–response manners. Compared with the lowest quartile of NO2 exposure, the odds of SAB in the fourth quartile of NO2 exposure increased 61% (OR = 1.61, 95% CI, 1.03–2.53). No associations of CO exposure with SAB risk were observed. Our study suggested that exposure to NO2 during early pregnancy was associated with increased risk of SAB. Further studies are needed to confirm our results and explore the potential biological mechanism underlying these associations. [ABSTRACT FROM AUTHOR]

Air pollution is widely acknowledged as a significant risk factor for human health, especially reproductive health. Nevertheless, many studies have disregarded the potentially mixed effects of air pollutants on reproductive outcomes. We performed a retrospective cohort study involving 8048 women with 9445 cycles undergoing In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) in China, from 2017 to 2021. A land-use random forest model was applied to estimate daily residential exposure to air pollutants, including sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO), ozone (O 3), and fine particulate matter (PM 2.5). Individual and joint associations between air pollutants and oocyte-related outcomes of ART were evaluated. In 90 days prior to oocyte pick-up to oocyte pick-up (period A), NO 2 , O 3 and CO was negatively associated with total oocyte yield. In the 90 days prior to oocyte pick-up to start of gonadotropin medication (Gn start, period B), there was a negative dose-dependent association of exposure to five air pollutants with total oocyte yield and mature oocyte yield. In Qgcomp analysis, increasing the multiple air pollutants mixtures by one quartile was related to reducing the number of oocyte pick-ups by −2.00 % (95 %CI: −2.78 %, −1.22 %) in period A, −2.62 % (95 %CI: −3.40 %, −1.84 %) in period B, and −0.98 % (95 %CI: −1.75 %, −0.21 %) in period C. During period B, a 1-unit increase in the WQS index of multiple air pollutants exposure was associated with fewer number of total oocyte (−1.27 %, 95 %CI: −2.16 %, −0.36 %) and mature oocyte (−1.42 %, 95 %CI: −2.41 %, −0.43 %). O 3 and NO 2 were major contributors with adverse effects on the mixed associations. Additionally, period B appears to be the susceptible window. Our study implies that exposure to air pollution adversely affects oocyte-related outcomes, which raises concerns about the potential adverse impact of air pollution on women's reproductive health. [Display omitted] • A LURF model was used to evaluate air pollution among women underwent ART. • The mixture effect of air pollutants on early ART outcomes was assessed. • The higher exposure level of air pollutants, fewer number of oocytes retrieved. [ABSTRACT FROM AUTHOR]

Carbon emission is not just a threat to the environment but also an economic burden. Faced with the growing pollutant emission, the purpose of financial institutions is more crucial. To address this issue, this research employs difference-in-differences to assess the role of China's green financing policy in renewable energy deployment for emission reduction. The findings demonstrate that the green finance strategy in renewable energy can reduce the general situation of emission reduction. The results show that the policy was effective in lower three contaminants, including Sulfur dioxide, Nitrogen dioxides, and PM 2.5, but are inadequate in reducing Carbon monoxide, Ozone, and PM 10. Besides, the control impacts of green finance policy are via local enterprises' economic activities. Compared with the financially advanced areas, the reducing emissions impacts of green financing policies in the financially undeveloped areas are greater. These results give recommendations for controlling air quality financial advantage from the standpoint of micro practice. • Carbon emission is an economic burden. • We assessed China's green finance policy on renewable energy and emission reduction. • The policy reduced Sulfur dioxide, Nitrogen dioxides, and PM2.5. • It is inadequate to reduce Carbon monoxide, Ozone, and PM10. • Emission reduction impacts in the financially undeveloped areas of China are greater. [ABSTRACT FROM AUTHOR]

The long-range transport of biomass burning pollutants from Southeast Asia has a significant impact on air quality in China. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) fire data and aerosol optical depth (AOD) products and the Tropospheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data were used to analyze the impact of air pollution caused by biomass burning in Southeast Asia on southern China. Results showed that Yunnan, Guangdong and Guangxi were deeply affected by biomass burning emissions from March to April during 2016–2020. Comparing the data for fires on the Indochinese Peninsula and southern provinces of China, it is obvious that the contribution of pollutants emitted by local biomass burning in China to air pollution is only a small possibility. The distribution of CO showed that the overall emissions increased greatly from March to April, and there was an obvious transmission process. In addition, the MODIS AOD in areas close to the national boundary of China is at a high level (>0.6), and the AOD in the southwest of Guangxi province and the southeast of Yunnan Province is above 0.8. Combined with a typical air pollution event in southern China, the UVAI combined with wind direction and other meteorological data showed that the pollutants were transferred from the Indochinese Peninsula to southern China under the southwest monsoon. The PM2.5 data from ground-based measurements and backward tracking were used to verify the pollutant source of the pollution event, and it was concluded that the degree of pollution in Yunnan, Guangxi and Guangdong provinces was related to the distance from the Indochinese Peninsula. Results indicate that it is necessary to carry out in-depth research on the impact of cross-border air pollution transport on domestic air quality as soon as possible and to actively cooperate with foreign countries to carry out pollution source research and control. [ABSTRACT FROM AUTHOR]

In the past decade, ozone (O 3) pollution has become a severe environmental problem in China's major cities. Here, based on available observational records, we investigated the long-term trend of O 3 pollution in China during 2014–2020. The O 3 concentrations were slightly higher in urban areas than in non-urban areas. During these 7 years, the highest O 3 concentrations primarily occurred during summer in northern China, and during autumn or spring in southern China. Although O 3 precursors, including nitrogen oxides (NO x) and carbon monoxide (CO), continuously decreased, O 3 concentrations generally increased throughout the 7 years with a slower increasing rate after 2017. The long-term trend of O 3 concentrations differed across seasons, especially from 2019 to 2020, when O 3 concentrations decreased in summer and increased in winter. To analyse the causes of this observed trend, a photochemical box model was used to investigate the change in the O 3 sensitivity regime in two representative cities – Beijing and Shanghai. Our model simulations suggest that the summertime O 3 sensitivity regime in urban areas of China has changed from a VOC-limited regime to a transition regime during 2014–2020. By 2020, the urban photochemistry was in a transition regime in summer but in a VOC-limited regime in winter. This study helps to understand the distinct trends of O 3 in China and provides insights into efficient future O 3 control strategies in different regions and seasons. [ABSTRACT FROM AUTHOR]

Satellite and surface carbon monoxide (CO) observations have been widely used to investigate the sources and variabilities of atmospheric CO. However, comparative analyses to explore the effects of satellite and surface measurements on atmospheric CO assimilations are still lacking. Here we investigate the assimilated atmospheric CO over East Asia in 2015–2020, via assimilating CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) instrument and Ministry of Ecology and Environment of China (MEE) monitoring network. We find noticeable inconsistencies in the assimilations: the adjusted CO columns (Xco) are about 162, 173 and 172 ppb by assimilating surface CO measurements, in contrast to 138–144, 149–155 and 144–151 ppb by assimilating MOPITT CO observations over East China, the North China Plain (NCP), and the Yangtze River Delta (YRD), respectively. These inconsistencies could be associated with possible representation errors due to differences between urban and regional CO backgrounds. Furthermore, the adjusted surface CO concentrations are about 631, 806, and 657 ppb by assimilating surface CO measurements, in contrast to 418–427, 627–639 and 500–509 ppb by assimilating MOPITT CO observations over East China, NCP, and YRD, respectively; assimilations of normalized surface CO measurements (to mitigate the influences of representation errors) indicate declines of CO columns by about 2.2, 2.1, and 1.8 ppb yr -1 , in contrast to 0.63–0.86, 0.97–1.29, and 1.0–1.27 ppb yr -1 by assimilating MOPITT CO measurements over East China, South Korea, and Japan, respectively. These discrepancies reflect the different vertical sensitivities of satellite and surface observations in the lower and free troposphere. This work demonstrates the importance of integrating information from satellite and surface measurements to provide a more accurate evaluation of atmospheric CO changes. [ABSTRACT FROM AUTHOR]

Although a growing number of original epidemiological studies imply a link between ambient pollution exposure and mortality risk, the findings associated with carbon monoxide (CO) exposure are inconsistent. Thus, we conducted a systematic review and meta-analysis of epidemiological studies to evaluate the correlations between ambient CO and non-accidental, cardiovascular, and respiratory mortality in China. Eight databases were searched from inception to 15 May 2021. A random-effect model was used to calculate the pooled relative risks (RRs) and 95% confidence intervals (CIs). Subgroup analyses as well as sensitivity analyses were performed. The I square value (I2) was used to assess heterogeneity among different studies. The assessment of publication bias on included studies was examined by funnel plot and Egger's test. The influence of a potential publication bias on findings was explored by using the trim-and-fill procedure. Ultimately, a total of 19 studies were included in our analysis. The pooled relative risk for each 1 mg/m3 increase of ambient carbon monoxide was 1.0220 (95%CI: 1.0102–1.0339) for non-accidental mortality, 1.0304 (95%CI:1.0154–1.0457) for cardiovascular mortality, and 1.0318 (95%CI:1.0132–1.0506) for respiratory mortality. None of subgroup analyses could explain the source of heterogeneity. Exclusion of any single study did not materially alter the pooled effect estimates. Although it was suggestive of publication bias, findings were generally similar with principal findings when we explored the influence of a potential publication bias using the trim-and-fill method. Our meta-analysis demonstrated that exposure to ambient CO was positive with risk of deaths from all non-accidental causes, total cardiovascular, and respiratory diseases. Based on these findings, tougher intervention policies and initiatives to reduce the health effects of CO exposure should be established. [ABSTRACT FROM AUTHOR]

As compared to conventional diesel heavy-duty vehicles, natural gas vehicles have been proved to be more eco-friendly due to their lower production of greenhouse gas and pollutant emissions, which are causing enormous adverse effects on global warming and air pollution. However, natural gas vehicles were rarely studied before, especially through on-road measurements. In this study, a portable emission measurement system (PEMS) was employed to investigate the real-world emissions of nitrogen oxides (NOx) (nitrogen monoxide (NO), nitrogen dioxide (NO 2)), total hydrocarbons (THC), carbon monoxide (CO), and carbon dioxide (CO 2) from two liquified natural gas (LNG) China V heavy-duty cleaning sanitation trucks with different weight. Associated with the more aggressive driving behaviors, the vehicle with lower weight exhibited higher CO 2 (3%) but lower NOx (48.3%) (NO 2 (78.2%) and NO (29.4%)), CO (44.8%), and THC (3.7%) emission factors. Aggressive driving behaviors were also favorable to the production of THC, especially those in the medium-speed range but significantly negative to the production of CO and NO 2 , especially those in the low-speed range with high engine load. In particular, the emission rate ratio of NO 2 /NO decreased with the increase of speed/scaled tractive power in different speed ranges. [Display omitted] Average speed-bin and the boxplot of gaseous emission factors of CO, THC, NO, NO 2 , and CO 2 for both tested vehicles. [ABSTRACT FROM AUTHOR]

The conventional Ensemble Kalman filter (EnKF), which is now widely used to calibrate emission inventories and to improve air quality simulations, is susceptible to simulation errors of meteorological inputs, making accurate updates of high temporal-resolution emission inventories challenging. In this study, we developed a novel meteorologically adjusted inversion method (MAEInv) based on the EnKF to improve daily emission estimations. The new method combines sensitivity analysis and bias correction to alleviate the inversion biases caused by errors of meteorological inputs. For demonstration, we used the MAEInv to inverse daily carbon monoxide (CO) emissions in the Pearl River Delta (PRD) region, China. In the case study, 60% of the total CO simulation biases were associated with sensitive meteorological inputs, which would lead to the overestimation of daily variations of posterior emissions. Using the new inversion method, daily variations of emissions shrank dramatically, with the percentage change decreased by 30%. Also, the total amount of posterior CO emissions estimated by the MAEInv decreased by 14%, indicating that posterior CO emissions might be overestimated using the conventional EnKF. Model evaluations using independent observations revealed that daily CO emissions estimated by MAEInv better reproduce the magnitude and temporal patterns of ambient CO concentration, with a higher correlation coefficient (R , +37.0%) and lower normalized mean bias (NMB, -17.9%). Since errors of meteorological inputs are major sources of simulation biases for both low-reactive and reactive pollutants, the MAEInv is also applicable to improve the daily emission inversions of reactive pollutants. [Display omitted] [ABSTRACT FROM AUTHOR]

Irregular industrial Carbon monoxide (CO) emissions not only deteriorate global atmospheric environment but also add a large uncertainty to CO emission inventory. This work demonstrates the potentiality of the Tropospheric Monitoring Instrument (TROPOMI) data product to derive CO emissions from facility‐level industrial sources. We have demonstrated CO emission estimates of 14 randomly selected facility‐level industrial sources over China with uncertainties of 10%–35% from TROPOMI archive between 2017 and 2020. We found that most of the plumes reveal significantly larger emissions than the registered inventory values. The simplicity of the demonstrated plume quantification method makes it easily applicable everywhere around the globe. This study suggests that future CO satellite constellation can routinely observe point source CO emissions to support environment policy. Plain Language Summary: Irregular Carbon monoxide (CO) emissions from industrial sources add a large uncertainty to CO emission inventory. Some irregular CO emission events from industrial point sources in China may be not recorded properly by in situ monitoring system since enterprises may turn down the reporting values manually before discharging excessive pollutants to escape punishment. It is also expensive to carry out frequent airborne or ground‐based surveys across the entire industrial area to monitor such irregular CO emission events. This work demonstrates the potentiality of the Tropospheric Monitoring Instrument (TROPOMI) data product to derive CO emissions from facility‐level industrial sources. We have demonstrated CO emission estimates of 14 randomly selected facility‐level industrial sources over China with uncertainties of 10%–35% from TROPOMI archive between 2017 and 2020. We found that most of the plumes reveal significantly larger emissions than the registered inventory values. The simplicity of the demonstrated plume quantification method makes it easily applicable everywhere around the globe. This study suggests that future satellite constellation should monitor CO and co‐emitted gases with high spatial‐temporal resolutions and coverage, which can monitor routinely CO emissions to support environment policy. Key Points: Tropospheric Monitoring Instrument observations reveal a large Carbon monoxide (CO) emission discrepancy from industrial point sources over ChinaRegional emission inventory probably underestimated CO emissions of certain industrial point sources over ChinaFuture CO satellite constellation together with monitoring local emissions could support environment policy [ABSTRACT FROM AUTHOR]

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and Qinghai (QH)) of northwest China (NWC) from January 2015 to December 2018. For this purpose, surface-level aerosol pollutants, including particulate matter (PMx, x = 2.5 and 10) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were obtained from China National Environmental Monitoring Center (CNEMC). The results showed that fine particulate matter (PM2.5), coarse particulate matter (PM10), SO2, NO2, and CO decreased by 28.2%, 32.7%, 41.9%, 6.2%, and 27.3%, respectively, while O3 increased by 3.96% in NWC during 2018 as compared with 2015. The particulate matter (PM2.5 and PM10) levels exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II standards as well as the WHO recommended Air Quality Guidelines, while SO2 and NO2 complied with the CAAQS Grade II standards in NWC. In addition, the average air quality index (AQI), calculated from ground-based data, improved by 21.3%, the proportion of air quality Class I (0–50) improved by 114.1%, and the number of pollution days decreased by 61.8% in NWC. All the pollutants' (except ozone) AQI and PM2.5/PM10 ratios showed the highest pollution levels in winter and lowest in summer. AQI was strongly positively correlated with PM2.5, PM10, SO2, NO2, and CO, while negatively correlated with O3. PM10 was the primary pollutant, followed by O3, PM2.5, NO2, CO, and SO2, with different spatial and temporal variations. The proportion of days with PM2.5, PM10, SO2, and CO as the primary pollutants decreased but increased for NO2 and O3. This study provides useful information and a valuable reference for future research on air quality in northwest China. [ABSTRACT FROM AUTHOR]

Agricultural machinery has increasingly become a significant source of air pollution in China, more in-depth research is needed regarding the emissions. Given the seasonal and regional characteristics with agricultural machinery usage, it is necessary to accurately estimate the emission intensity and spatio-temporal distribution. This study using Beijing as the case study area, evaluated agricultural tractors emissions using remote monitoring and emission tests during 2020. The results show that tractors in Beijing emitted 80 t of carbon monoxide (CO), 21 t of hydrocarbons (HC), 104 t of nitrogen oxides (NO x), and 10 t of particulate matter (PM), totalling 215 t in 2020 and that the emissions were unevenly distributed with the districts and counties of Beijing. Shunyi District contributed the most (31.546%) whilst Haidian District contributed the least, less than 1% of the total. The spatio-temporal variation of NO x and PM emissions showed that the higher emissions occurred in Spring and Autumn because of agricultural activities. Using the annual utilisation hours determined by remote monitoring throughout the year, the emission factors for tractors obtained from emission tests and the estimated emission inventory could supplement the emission database from agricultural machinery in the different regions of China to assist environmental pollution research and policy making. • Remote monitoring system of agricultural tractors was established. • 71 agricultural tractors were monitored all the year round in Beijing. • Gaseous and PM emission rates of 14 tractors were measured using PEMS. • The spatio-temporal distribution analysis of emissions was established. [ABSTRACT FROM AUTHOR]

As China's economic development enters a transitional stage, the government has put forward higher requirements for efficient air pollution control. Different from the traditional environmental regulation methods, China's carbon market pilots (CMP) can use market mechanism to achieve carbon emission reduction policy goals while also providing more efficient control methods for air pollution. Using the unique daily air pollution data of 324 prefecture-level and above cities in China from December 1, 2013, to December 18, 2017, and matching them with the daily data of carbon allowance trading in each CMP, we employ the time-varying difference-in-differences (DID) method to explore the casual relationship between CMP and air pollution, and its influence mechanism. Our results show that (1) the establishment of CMP can reduce air pollution by at least 4.9%, especially on sulfur dioxide, inhalable particulate matter, fine particles, and carbon monoxide. This conclusion is still robust after we use the instrumental variable (IV) method to deal with endogeneity. (2) Mechanism analysis shows that the reducing effect of CMP on air pollution is achieved mainly through three channels, including energy consumption reducing, technological progressing, and industrial structure upgrading. (3) Since CMP have just been established, government regulation plays a stronger role than the market mechanism in the process of CMP affecting air pollution. However, with the continuous improvement of CMP, the market mechanism has also played an increasingly important dynamic effect. [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) poisoning is a common cause of death, leading to morbidity and mortality worldwide. Features of the CO poisoning with low carboxyhemoglobin (COHb) levels remain to be characterized. This study collected a total of 307 CO poisoning cases from Shanghai Public Security Bureau, an official organization that handles the most complicated and life-threatening cases across Shanghai municipality in China, and regrouped these cases into three categories: group 1, 10% < COHb% < 30% (n = 58); group 2, 30% ≤ COHb% < 50% (n = 79); group 3, COHb% ≥ 50% (n = 170). Epidemiological, demographic, and forensic aspects of the CO poisoning cases, particularly those with low COHb levels, were analyzed. Our results showed that group 2 and 3 were mostly observed in younger victims (≤ 30 years), while group 1 equally distributed to all age groups (p = 0.03). All the CO poisoning from group 2 and 3 occurred in enclosed spaces, whereas cases from group 1 died additionally in outdoor spaces (p = 0.01). 81.03% of group 1 cases died in fire circumstances, while only 45.57% from group 2 and 30.59% from group 3 were fire-related (p = 0.00). Accordingly, group 1 was mostly related with fire burns, while group 2 or 3 were largely associated with gas leakage (p = 0.00). A combination with alcohol, but not other psychotropic drugs, associated with significant higher levels of blood COHb% in fire-unrelated (p = 0.021) but not fire-related cases (p = 0.23). Five extremely low COHb% (< 30%)-related poisoning deaths were negative of any cardiopulmonary pathology and psychoactive substances. In conclusion, CO poisoning with low COHb% significantly associates with fire circumstances and outdoor spaces and has no age preference. Further diagnostic markers mandates to be identified in order to avoid disputes in cases of extremely low COHb%-related poisoning. [ABSTRACT FROM AUTHOR]

After stagnating in the early 2000s, the atmospheric methane growth rate has been positive since 2007 with a significant acceleration starting in 2014. While the causes for previous growth rate variations are still not well determined, this recent increase can be studied with dense surface and satellite observations. Here, we use an ensemble of six multi-species atmospheric inversions that have the capacity to assimilate observations of the main species in the methane oxidation chain – namely, methane, formaldehyde, and carbon monoxide – to simultaneously optimize both the methane sources and sinks at each model grid. We show that the surge of the atmospheric growth rate between 2010–2013 and 2014–2017 is most likely explained by an increase of global CH 4 emissions by 17.5±1.5 Tg yr -1 (mean ± 1σ), while variations in the hydroxyl radicals (OH) remained small. The inferred emission increase is consistently supported by both surface and satellite observations, with leading contributions from the tropical wetlands (∼ 35 %) and anthropogenic emissions in China (∼ 20 %). Such a high consecutive atmospheric growth rate has not been observed since the 1980s and corresponds to unprecedented global total CH 4 emissions. [ABSTRACT FROM AUTHOR]

Photochemical smog characterized by high concentrations of ozone (O3) is a serious air pollution issue in the North China Plain (NCP) region, especially in summer and autumn. For this study, measurements of O3, nitrogen oxides (NOx), volatile organic compounds (VOCs), carbon monoxide (CO), nitrous acid (HONO), and a number of key physical parameters were taken at a suburban site, Xianghe, in the NCP region during the summer of 2018 in order to better understand the photochemical processes leading to O3 formation and find an optimal way to control O3 pollution. Here, the radical chemistry and O3 photochemical budget based on measurement data from 1–23 July using a chemical box model is investigated. The daytime (0600–1800 LST) average production rate of the primary radicals referred to as ROx (OH + HO2 + RO2) is 3.9 ppbv h−1. HONO photolysis is the largest primary ROx source (41%). Reaction of NO2 + OH is the largest contributor to radical termination (41%), followed by reactions of RO2 + NO2 (26%). The average diurnal maximum O3 production and loss rates are 32.9 ppbv h−1 and 4.3 ppbv h−1, respectively. Sensitivity tests without the HONO constraint lead to decreases in daytime average primary ROx production by 55% and O3 photochemical production by 42%, highlighting the importance of accurate HONO measurements when quantifying the ROx budget and O3 photochemical production. Considering heterogeneous reactions of trace gases and radicals on aerosols, aerosol uptake of HO2 contributes 11% to ROx sink, and the daytime average O3 photochemical production decreases by 14%. The O3-NOx-VOCs sensitivity shows that the O3 production at Xianghe during the investigation period is mainly controlled by VOCs. [ABSTRACT FROM AUTHOR]

Background: To investigate the effects of short-term exposure to sulfur dioxide (SO2) and carbon monoxide (CO) in the central and southern China areas on ischemic heart disease (IHD) and non-accidental deaths. Method: We investigated the associations between short-term exposure to SO2 and CO in a city in south-central China and IHD and non-accidental death using a time-series design and generalized additive models with up to a 5-day lag adjusting for day of the week, temperature, air pressure, wind speed, and relative humidity. The relative risks of IHD and non-accidental death per 10-unit increase in SO2 and CO were derived from zero to five days in single-pollutant models. Results: Between 2016 and 2018, a total of 10,507 IHD and 44,070 non-accidental deaths were identified. The largest significant relative risk for IHD death was lag 02 for both SO2 (1.080; 95% confidence interval: 1.075–1.084) and CO (5.297; 95% confidence interval: 5.177–5.418) in single-pollutants models. A significant association was shown at all lag multiple-day moving averages. Two-pollutant models identified an association between SO2 and mortality when adjusting for CO. In stratified analyses, SO2 exhibited a stronger association with death during the cold season, while CO exhibited a stronger association with mortality from IHD during the warm season. The risk of death was more robust in the elderly for both pollutants, but was greater in men for CO and in women for SO2. Conclusions: Overall, we found an association between short-term exposure to low-level SO2 and CO and the risk of IHD and non-accidental death. [ABSTRACT FROM AUTHOR]

Objective： To systematically evaluate the efficacy of butylphthalide in the treatment of carbon monoxide poisoning encephalopathy. Methods: Related studies published from January 2009 to August 2020 were retrived from Wanfang Data-Digitalization Journals, China National Knowledge Infrastructure (CNKI), VIP China Science and Technology Journal Data base, PubMed, EMBase and ClinicalKey databases. The efficacy of butylpht halide in the prevention and treatment of carbon monoxide delayed encephalopathy was investigated. The RevMan 5.3 software was used for meta analysis of various effect indexes. Results: A total of 13 studies involving 1140 patients were included in the study. Meta analysis showed that butylphthalide could significantly reduce the incidence of delayed encephalopathy in the patients with carbon monoxide poisoning [95% CI (0. 10, 0. 42), 001], improve the mini-mental state examination scores (MMSE) [95% CI(2. 91, 6. 02), P

Ambient air pollutants exposures may lead to aggravated Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD). However, there is still a scarcity of empirical studies that have rigorously estimated this association, especially in regions where air pollution is severe. To fill in the literature gap, we conducted a cross-sectional study involving 2711,207 adults living in five regions of southern Xinjiang Uyghur Autonomous Region in 2021. Using a Space-Time Extra-Trees model, we assessed the four-year (2017–2020) average concentrations of particulate matter with aerodynamic diameter ≤1 µm (PM 1), particulate matter with aerodynamic diameter ≤2.5 µm (PM 2.5), particulate matter with aerodynamic diameter ≤10 µm (PM 10), ozone (O 3), sulfur dioxide (SO 2), and carbon monoxide (CO), and then assigned these values to the participants. Generalized linear mixed models were employed to examine the relationships between air pollutants and the prevalence of MAFLD, with adjustment for multiple confounding factors. The odds ratios and 95% confidence intervals of MAFLD were 2.002 (1.826–2.195), 1.133 (1.108–1.157), 1.034 (1.027–1.040), 1.077 (1.023–1.134), 2.703 (2.322–3.146) and 1.033 (1.029–1.036) per 10 µg/m3 increase in the 4-year average PM 1 , PM 2.5 , PM 10 , O 3 , SO 2 and CO exposures, respectively. The robustness of the findings was confirmed by a series of sensitivities. In summary, long-term exposure to ambient air pollutants was associated with increased odds of MAFLD, particularly in males and individuals with unhealthy lifestyles. • Evidence concerning ambient air pollution and MAFLD is limited. • Exposure to air pollutants was related to higher odds of MAFLD. • The association between gaseous pollutants and MAFLD is more pronounced in males. • A healthy lifestyle may mitigate the adverse effects of air pollution on MAFLD. [ABSTRACT FROM AUTHOR]

Schematic diagram of the dual-gas sensor system, which includes a gas pretreatment part, an optical part and an electrical part. [Display omitted] • A SPGC and a MPGC were developed for achieving wide measurement ranges. • The developed sensor system is intrinsically safe and explosion-proof. • The developed gas pretreatment module can remove moisture and aerosols. • Use temperature compensation algorithm to adapt to changes in ambient temperature. • The sensor system can operate normally in the laboratory and field deployment. To effectively monitor gas explosion and coal spontaneous combustion in coal mine, an intrinsically safe and explosion-proof dual-gas sensor system was developed for methane (CH 4) and carbon monoxide (CO) measurement. A distributed feedback (DFB) laser was used to scan two adjacent absorption lines (CH 4 : 4284.51 cm−1, CO: 4285.01 cm−1). Two measurement ranges of 0–500 parts per million by volume (ppmv) and 0–300,000 ppmv for CH 4 and 0–100 ppmv and 0–4000 ppmv for CO were realized using a ∼25 cm single-pass gas cell (SPGC) and a ∼25 m multi-pass gas cell (MPGC), respectively. A gas pre-treatment module was used to remove moisture and aerosols from gas samples. A temperature compensation algorithm was adopted to deal with ambient temperature change. Based on the Allan deviation analysis, the limit of detection (LoD) of CH 4 is 0.19 ppmv and the LoD of CO is 0.12 ppmv, respectively, at an averaging time of 0.5 s. A continuous two-day CH 4 measurement was performed to demonstrate the long-term stability and environmental monitoring capability. The sensor system was successfully deployed in coal mine gas analysis at Longjiapu, Changchun City, China. [ABSTRACT FROM AUTHOR]

Photochemical air quality models (AQMs) are a vital tool for atmospheric pollution research and have been widely used in various applications, such as air quality prediction and evaluation of pollution control strategies. Before using these models for further studies, it is essential to thoroughly evaluate their reliability and accuracy. While previous guidelines and benchmarks have primarily focused on fine particulate matter (PM 2.5) and ozone (O 3), there is still a lack of benchmarks for evaluating the model performance on primary criteria pollutants such as sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM 10). The use of air quality models in China has increased significantly in the past decades. However, there is still a lack of standardized benchmarks for the performance evaluation of these models. Building upon our previous work on PM 2.5 and its chemical species, we propose a set of benchmarks for evaluating the performance of the aforementioned four air pollutants. Initially, we identified a total of 475 papers published during 2007–2019 that utilized at least one of the five commonly used AQMs in China. From these papers, we selected 164 articles that provided model performance evaluation (MPE) results of the four primary air pollutants. The three most frequently used Model Performance Evaluation (MPE) metrics were selected to analyse the impact of different model configurations on the reported statistics, including modelling region, season, and emission inventory. Lastly, three commonly used statistical indicators, including normalized mean bias (NMB), normalized mean error (NME), and correlation coefficient (R), were proposed for the validation of simulated NO 2 , SO 2 , CO, and PM 10. Two sets of benchmarks are given, including the "goal" and "criteria". The "goal" represents the best range of performance that a model can be expected to achieve, and the "criteria" represents performance that the majority of studies have achieved. We recommend R values above 0.50, 0.35, 0.45, and 0.40 for NO 2 , SO 2 , PM 10 , and CO, respectively, in order to meet the "criteria" benchmark. If the "goal" benchmark is to be achieved, the corresponding R values are 0.60, 0.55, 0.60, and 0.60. The "goal" benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are within ±20%, ±25%, ±20%, and ±25%, respectively; while the "goal" benchmarks of NME for the four pollutants are less than 40%, 45%, 45%, and 60%, respectively. These benchmarks supplement our previous benchmarks for PM 2.5 and its components and provide a more comprehensive guideline for the air quality modelling community in China. • A set of benchmarks for evaluation of the NO 2 , SO 2 , CO and PM 10 simulation over China are proposed. • Three commonly used statistical indicators (NMB, NME, and R) were proposed for the validation of the four pollutants. • The goal benchmarks of NMB for NO 2 , SO 2 , PM 10 , and CO are <20%, <25%, <20% and <25%, respectively. [ABSTRACT FROM AUTHOR]

Limited evidence exists regarding the link between air pollution exposure and cognitive function in developing countries, particularly in areas with abundant natural sources of particulate matter. To investigate this association in a large representative sample of the elderly in northwestern China. We performed a cross-sectional study among 176,345 participants aged 60–100 years in northwestern China in 2020. A satellite-based spatiotemporal model was applied to assess three-year annual averages of particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM 2.5), ≤ 10 µm (PM 10), sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbon monoxide (CO), and ozone (O 3) at residential address. Poor cognitive function was assessed using the Mini-Mental State Examination (MMSE). Generalized linear mixed models were used to assess associations. Compared with participants with the lowest quartiles of PM 2.5 , PM 10 , and O 3 levels, those with the second, third, and highest quartiles of air pollutants consistently showed increased odds of poor cognitive function and decreased MMSE scores. The odds ratios of poor cognitive function associated with a 10 μg/m3 increment in PM 2.5 , PM 10 , and O 3 were 1.26 (95 % confidence interval [CI]: 1.17, 1.36), 1.06 (95 %CI: 1.04, 1.08), and 2.76 (95 %CI: 2.11, 3.62), respectively. Subgroup analyses suggested stronger associations between air pollution exposures and poor cognitive function among participants who were younger, were non-Uyghur and were physically active. Long-term exposures to PM 2.5 , PM 10 and O 3 were associated with poor cognitive function in elders. Our results suggest that reducing air pollution may alleviate the burden of poor cognitive function in the elderly. • The first study explored the link of air pollution and cognition in northwest China. • A total of 176,345 older adults were included. • Long-term exposures to PM 2.5 , PM 10 , and O 3 were related to poor cognitive function. • Participants who were younger, non-Uygur, and physically active were more sensitive. [ABSTRACT FROM AUTHOR]