RESUMEN

With the continuous control of anthropogenic emissions, China's air quality has improved significantly in recent years. Given this background, research on how the short-term exposure risks caused by air pollution in China have changed is insufficient. This study utilized hourly concentration data from ground observation stations and the official air quality guidelines of the Ministry of Ecology and Environment of China and the World Health Organization as standards to systematically investigate the spatiotemporal characteristics and short-term exposure risks of air pollution in China from 2015 to 2022. The results indicate that various atmospheric pollutants except for ozone showed a decreasing trend yearly. Nationwide, both single pollutant air pollution days (SAPDs) and multiple pollutant air pollution days (MAPDs) showed varying degrees of reduction within 15 and 25 days, respectively. SAPD was dominated mainly by excessive PM2.5 and PM10 pollutants, while MAPD was dominated mainly by excessive pollutant combinations, including PM2.5 + PM10, CO + PM2.5 + PM10, and SO2 + PM2.5 + PM10. As the concentration of atmospheric pollutants decreased, the total excess risk (ER) decreased yearly from 2015 to 2022, but there were significant regional differences. Now, the ER is less than 0.25% in southern China, in the range of 0.25%-0.5% in the North China Plain and some cities in the northeast, and higher than 1% in the northwest. Particulate matter is currently the primary pollutant posing short-term exposure risk in China, especially due to the impact of sandstorm weather. This study indicates that China's atmospheric cleaning action is significantly beneficial for reducing health risks.

Asunto(s)

RESUMEN

The emission of heavy-duty vehicles has raised great concerns worldwide. The complex working and loading conditions, which may differ a lot from PEMS tests, raised new challenges to the supervision and control of emissions, especially during real-world applications. On-board diagnostics (OBD) technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles. This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals. Real-world NOx and CO2 emissions of China-6 heavy-duty vehicles have been examined. The results showed that city heavy-duty vehicles had higher NOx emission levels, which was mostly due to longer time of low SCR temperatures below 180°C. The application of novel methods based on 3B-MAW also found that heavy-duty diesel vehicles tended to have high NOx emissions at idle. Also, little difference had been found in work-based CO2 emissions, and this may be due to no major difference were found in occupancies of hot running.

Asunto(s)

RESUMEN

The toxicity of PM2.5 does not necessarily change synchronously with its mass concentration. In this study, the chemical composition (carbonaceous species, water-soluble ions, and metals) and oxidative potential (dithiothreitol assay, DTT) of PM2.5 were investigated in 2017/2018 and 2022 in Xiamen, China. The decrease rate of volume-normalized DTT (DTTv) (38%) was lower than that of PM2.5 (55%) between the two sampling periods. However, the mass-normalized DTT (DTTm) increased by 44%. Clear seasonal patterns with higher levels in winter were found for PM2.5, most chemical constituents and DTTv but not for DTTm. The large decrease in DTT activity (84%-92%) after the addition of EDTA suggested that water-soluble metals were the main contributors to DTT in Xiamen. The increased gap between the reconstructed and measured DTTv and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022 were observed. The decrease rates of the hazard index (32.5%) and lifetime cancer risk (9.1%) differed from those of PM2.5 and DTTv due to their different main contributors. The PMF-MLR model showed that the contributions (nmol/(min·m3)) of vehicle emission, coal + biomass burning, ship emission and secondary aerosol to DTTv in 2022 decreased by 63.0%, 65.2%, 66.5%, and 22.2%, respectively, compared to those in 2017/2018, which was consistent with the emission reduction of vehicle exhaust and coal consumption, the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC. However, the contributions of dust + sea salt and industrial emission increased.

Asunto(s)

RESUMEN

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta (YRD) region and its meteorology-related and emission-related have not been systematically analyzed. In this study, by using 8-year-long (2015-2022) surface ozone observation data, we attempted to reveal the variation of multiple timescale components using the Kolmogorov-Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables. The results showed that the short-term, seasonal, and long-term components accounted for daily maximum 8-hr average O3 (O3-8 hr) concentration, 46.4%, 45.9%, and 1.0%, respectively. The meteorological impacts account for an average of 71.8% of O3-8 hr, and the YRD's eastern and northern sections are meteorology-sensitive areas. Based on statistical analysis technology with empirical orthogonal function, the contribution of meteorology, local emission, and transport in the long-term component of O3-8 hr were 0.21%, 0.12%, and 0.6%, respectively. The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest, influenced by the monsoon and synoptic conditions. The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution. Among the cities studied, Shanghai, Anqing, and Xuancheng, located at similar latitudes, were significantly impacted by atmospheric transmission-the contribution of Shanghai, the maximum accounting for 3.6%.

Asunto(s)

RESUMEN

Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide. Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem. Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables. In this study, we propose a machine learning algorithm for carbon emissions, a Bayesian optimized XGboost regression model, using multi-year energy carbon emission data and nighttime lights (NTL) remote sensing data from Shaanxi Province, China. Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models, with an R2 of 0.906 and RMSE of 5.687. We observe an annual increase in carbon emissions, with high-emission counties primarily concentrated in northern and central Shaanxi Province, displaying a shift from discrete, sporadic points to contiguous, extended spatial distribution. Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns, with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering. Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissions more accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment. This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.

Asunto(s)

RESUMEN

To investigate the seasonal characteristics in air pollution in Chengdu, a single particle aerosol mass spectrometry was used to continuously observe atmospheric fine particulate matter during one-month periods in summer and winter, respectively. The results showed that, apart from O3, the concentrations of other pollutants (CO, NO2, SO2, PM2.5 and PM10) were significantly higher in winter than in summer. All single particle aerosols were divided into seven categories: biomass burning (BB), coal combustion (CC), Dust, vehicle emission (VE), K mixed with nitrate (K-NO3), K mixed with sulfate and nitrate (K-SN), and K mixed with sulfate (K-SO4) particles. The highest contributions in both seasons were VE particles (24%). The higher contributions of K-SO4 (16%) and K-NO3 (10%) particles occurred in summer and winter, respectively, as a result of their different formation mechanisms. S-containing (K-SO4 and K-SN), VE, and BB particles caused the evolution of pollution in both seasons, and they can be considered as targets for future pollution reduction. The mixing of primary sources particles (VE, Dust, CC, and BB) with secondary components was stronger in winter than in summer. In summer, as pollution worsens, the mixing of primary sources particles with 62 [NO3]- weakened, but the mixing with 97 [HSO4]- increased. However, in winter, the mixing state of particles did not exhibit an obvious evolution rules. The potential source areas in summer were mainly distributed in the southern region of Sichuan, while in winter, besides the southern region, the contribution of the western region cannot be ignored.

Asunto(s)

RESUMEN

Improving the accuracy of anthropogenic volatile organic compounds (VOCs) emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution. In this study, an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km × 3 km spatial resolution based on the emission factor method. The 2019 VOCs emission in Henan Province was 1003.5 Gg, while industrial process source (33.7%) was the highest emission source, Zhengzhou (17.9%) was the city with highest emission and April and August were the months with the more emissions. High VOCs emission regions were concentrated in downtown areas and industrial parks. Alkanes and aromatic hydrocarbons were the main VOCs contribution groups. The species composition, source contribution and spatial distribution were verified and evaluated through tracer ratio method (TR), Positive Matrix Factorization Model (PMF) and remote sensing inversion (RSI). Results show that both the emission results by emission inventory (EI) (15.7 Gg) and by TR method (13.6 Gg) and source contribution by EI and PMF are familiar. The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73. The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.

Asunto(s)

RESUMEN

VOCs (Volatile organic compounds) exert a vital role in ozone and secondary organic aerosol production, necessitating investigations into their concentration, chemical characteristics, and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution. From July to October 2020, online monitoring was conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity. Additionally, the PMF (positive matrix factorization) method was utilized to identify the VOCs sources. Results indicated that the TVOCs (total VOCs) concentration was (96.7 ± 63.4 µg/m3), with alkanes exhibiting the highest concentration of (36.1 ± 26.4 µg/m3), followed by OVOCs (16.4 ± 14.4 µg/m3). The key active components were alkenes and aromatics, among which xylene, propylene, toluene, propionaldehyde, acetaldehyde, ethylene, and styrene played crucial roles as reactive species. The sources derived from PMF analysis encompassed vehicle emissions, solvent and coating sources, combustion sources, industrial emissions sources, as well as plant sources, the contribution of which were 37.80%, 27.93%, 16.57%, 15.24%, and 2.46%, respectively. Hence, reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.

Asunto(s)

RESUMEN

Severe ground-level ozone (O3) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on human health and the sustainability of society. This study explored the spatiotemporal distribution characteristics of ground-level O3 and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021. Then, a high-performance convolutional neural network (CNN) model was established by expanding the moment and the concentration variations to general factors. Finally, the response mechanism of O3 to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables. The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern. When the wind direction (WD) ranges from east to southwest and the wind speed (WS) ranges between 2 and 3 m/sec, higher O3 concentration prone to occur. At different temperatures (T), the O3 concentration showed a trend of first increasing and subsequently decreasing with increasing NO2 concentration, peaks at the NO2 concentration around 0.02 mg/m3. The sensitivity of NO2 to O3 formation is not easily affected by temperature, barometric pressure and dew point temperature. Additionally, there is a minimum [Formula: see text] at each temperature when the NO2 concentration is 0.03 mg/m3, and this minimum [Formula: see text] decreases with increasing temperature. The study explores the response mechanism of O3 with the change of driving variables, which can provide a scientific foundation and methodological support for the targeted management of O3 pollution.

Asunto(s)

RESUMEN

Polychlorinated naphthalenes (PCNs) are detrimental to human health and the environment. With the commercial production of PCNs banned, unintentional releases have emerged as a significant environmental source. However, relevant information is still scarce. In this study, provincial emissions for eight PCNs homologues from 37 sources in the Chinese mainland during the period of 1960-2019 were estimated based on a source-specific and time-varying emission factor database. The results showed that the total PCNs emissions in 2019 reached 757.0 kg with Hebei ranked at the top among all the provinces and iron & steel industry as the biggest source. Low-chlorinated PCNs comprised 90% of emissions by mass, while highly chlorinated PCNs dominated in terms of toxicity, highlighting divergent priorities for mitigating emissions and safeguarding human health. The emissions showed an overall upward trend from 1960 to 2019 driven by emission increase from iron & steel industry in terms of source, and from North China and East China in terms of geographic area. Per-capita emissions followed an inverted U-shaped environmental Kuznets curve while emission intensities decreased with increasing per-capita Gross Domestic Product (GDP) following a nearly linear pattern when log-transformed.

Asunto(s)

RESUMEN

Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns (SWPs), however, the consistency of different classification methods is rarely examined. In this study, we apply two widely-used objective methods, the self-organizing map (SOM) and K-means clustering analysis, to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022. We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities. In the case of classifying six SWPs, the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods, and the difference in the mean frequency of each SWP is less than 7%. The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature, lower cloud cover, relative humidity, and wind speed, and stronger subsidence compared to climatology mean. We find that during 2015-2022, the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 day/year, faster than the increases in the ozone exceedance days (3.0 day/year). The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6. In particular, the significant increase in ozone-favorable SWPs in 2022, especially the Subtropical High type which typically occurs in September, is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022. Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.

Asunto(s)

RESUMEN

To explore air contamination resulting from special biomass combustion and suspended dust in Lhasa, the present study focused on the size distribution and chemical characteristics of particulate matter (PM) emission resulting from 7 types of non-fossil pollution sources. We investigated the concentration and size distribution of trace elements from 7 pollution sources collected in Lhasa. Combining Lhasa's atmospheric particulate matter data, enrichment factors (EFs) have been calculated to examine the potential impact of those pollution sources on the atmosphere quality of Lhasa. The highest mass concentration of total elements of biomass combustion appeared at PM0.4, and the second highest concentration existed in the size fraction 0.4-1 µm; the higher proportion (12 %) of toxic metals was produced by biomass combustion. The elemental composition of suspended dust and atmospheric particulate matter was close (except for As and Cd); the highest concentration of elements was all noted in PM2.5-10 (PM3-10). Potassium was found to be one of the main biomass markers. The proportion of Cu in suspended dust is significantly lower than that of atmospheric particulate matter (0.53 % and 3.75 %), which indicates that there are other anthropogenic sources. The EFs analysis showed that the Cr, Cu, Zn, and Pb produced by biomass combustion were highly enriched (EFs > 100) in all particle sizes. The EFs of most trace elements increased with decreasing particle size, indicating the greater influence of humanfactors on smaller particles.

Asunto(s)

RESUMEN

China is the most important steel producer in the world, and its steel industry is one of the most carbon-intensive industries in China. Consequently, research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals. We constructed a carbon dioxide (CO2) emission model for China's iron and steel industry from a life cycle perspective, conducted an empirical analysis based on data from 2019, and calculated the CO2 emissions of the industry throughout its life cycle. Key emission reduction factors were identified using sensitivity analysis. The results demonstrated that the CO2 emission intensity of the steel industry was 2.33 ton CO2/ton, and the production and manufacturing stages were the main sources of CO2 emissions, accounting for 89.84% of the total steel life-cycle emissions. Notably, fossil fuel combustion had the highest sensitivity to steel CO2 emissions, with a sensitivity coefficient of 0.68, reducing the amount of fossil fuel combustion by 20% and carbon emissions by 13.60%. The sensitivities of power structure optimization and scrap consumption were similar, while that of the transportation structure adjustment was the lowest, with a sensitivity coefficient of less than 0.1. Given the current strategic goals of peak carbon and carbon neutrality, it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies, increase the ratio of scrap steel to steelmaking, and build a new power system.

Asunto(s)

RESUMEN

Chinese diesel trucks are the main contributors to NOx and particulate matter (PM) vehicle emissions. An increase in diesel trucks could aggravate air pollution and damage human health. The Chinese government has recently implemented a series of emission control technologies and measures for air quality improvement. This paper summarizes recent control technologies and measures for diesel truck emissions in China and introduces the comprehensive application of control technologies and measures in Beijing-Tianjin-Hebei and surrounding regions. Remote online monitoring technology has been adopted according to the China VI standard for heavy-duty diesel trucks, and control measures such as transportation structure adjustment and heavy pollution enterprise classification control continue to support the battle action plan for pollution control. Perspectives and suggestions are provided for promoting pollution control and supervision of diesel truck emissions: adhere to the concept of overall management and control, vigorously promote the application of systematic and technological means in emission monitoring, continuously facilitate cargo transportation structure adjustment and promote new energy freight vehicles. This paper aims to accelerate the implementation of control technologies and measures throughout China. China is endeavouring to control diesel truck exhaust pollution. China is willing to cooperate with the world to protect the global ecological environment.

Asunto(s)

RESUMEN

BACKGROUND: Ambient air pollution, including particulate matter (such as PM10 and PM2·5) and nitrogen dioxide (NO2), has been linked to increases in mortality. Whether populations' vulnerability to these pollutants has changed over time is unclear, and studies on this topic do not include multicountry analysis. We evaluated whether changes in exposure to air pollutants were associated with changes in mortality effect estimates over time. METHODS: We extracted cause-specific mortality and air pollution data collected between 1995 and 2016 from the Multi-Country Multi-City (MCC) Collaborative Research Network database. We applied a two-stage approach to analyse the short-term effects of NO2, PM10, and PM2·5 on cause-specific mortality using city-specific time series regression analyses and multilevel random-effects meta-analysis. We assessed changes over time using a longitudinal meta-regression with time as a linear fixed term and explored potential sources of heterogeneity and two-pollutant models. FINDINGS: Over 21·6 million cardiovascular and 7·7 million respiratory deaths in 380 cities across 24 countries over the study period were included in the analysis. All three air pollutants showed decreasing concentrations over time. The pooled results suggested no significant temporal change in the effect estimates per unit exposure of PM10, PM2·5, or NO2 and mortality. However, the risk of cardiovascular mortality increased from 0·37% (95% CI -0·05 to 0·80) in 1998 to 0·85% (0·55 to 1·16) in 2012 with a 10 µg/m3 increase in PM2·5. Two-pollutant models generally showed similar results to single-pollutant models for PM fractions and indicated temporal differences for NO2. INTERPRETATION: Although air pollution levels decreased during the study period, the effect sizes per unit increase in air pollution concentration have not changed. This observation might be due to the composition, toxicity, and sources of air pollution, as well as other factors, such as socioeconomic determinants or changes in population distribution and susceptibility. FUNDING: None.

Asunto(s)

RESUMEN

Although it is well documented that exposure to fine particulate matter (PM2.5) increases the risk of several adverse health outcomes, less is known about its relationship with economic opportunity. Previous studies have relied on regression modeling, which implied strict assumptions regarding confounding adjustments and did not explore geographical heterogeneity. We obtained data for 63,165 US census tracts (86% of all census tracts in the United States) on absolute upward mobility (AUM) defined as the mean income rank in adulthood of children born to families in the 25th percentile of the national income distribution. We applied and compared several state-of-the-art confounding adjustment methods to estimate the overall and county-specific associations of childhood exposure to PM2.5 and AUM controlling for many census tract-level confounders. We estimate that census tracts with a 1 µg/m3 higher PM2.5 concentrations in 1982 are associated with a statistically significant 1.146% (95% CI: 0.834, 1.458) lower AUM in 2015, on average. We also showed evidence that this relationship varies spatially between counties, exhibiting a more pronounced negative relationship in the Midwest and the South.

Asunto(s)

Asunto(s)

RESUMEN

Although there is substantial evidence on the harmful effects of air pollution on human health, these are scarcely considered in the general clinical practice and also in the context of cardiovascular disease prevention. In light of the numerous epidemiological and basic research studies that have demonstrated the unfavorable impact of air pollution on the cardiovascular system, this review aims to bring this aspect to the attention of clinicians. This work describes the main air polluting components that can contribute to the onset and progression of cardiovascular diseases. The pathophysiological mechanisms underlying the impact of pollutants on the cardiovascular system and the available evidence regarding their effect on cardiovascular risk factors are reported. This article also examines the evidence relating to the correlation between environmental pollutants and some specific cardiovascular diseases, including acute coronary syndromes, cerebrovascular diseases, heart failure, and arrhythmias. Finally, the possible strategies to be implemented to limit pollution-induced cardiovascular damage are analyzed.

Asunto(s)

RESUMEN

Plants could effectively adsorb and remove particulate matter from the air, while could be suffered from the adverse effects. Therefore, exploring the interaction between plants and atmospheric particulate matter is crucial for profound understanding of ecological balance, microenvironmental climate, and environmental quality improvement. Few systematic literature have elaborated the adsorption and response mechanisms of atmospheric particulate matter by plants. We summarized the causes and composition of atmospheric particulate matter, as well as the adsorption methods and factors of plants on atmospheric particulate matter. Moreover, we elaborated the impact of atmospheric particulate matter stress on phenotypic and physiological characteristics, as well as molecular mechanisms. For the future researches, we proposed 1) to select plant species with strong adaptability and high dust retention capacity. Subsequently, there should be a universal green dust retention plan on account of comprehensive factors such as plant community structure, street morphology, and planting space; 2) to extend the research from urban areas to agricultural and pastoral areas, with a systematic analysis of the comprehensive dust retention capacity of communities with different plant configuration; 3) to effectively combine the dust retention capacity of plants with their own resistance. Subsequently, we should explore the physiological and molecular mechanisms of plants responding to atmospheric particulate matter stress and establish a comprehensive evaluation system and criteria; 4) to develop in situ labeling detection technology, which would be a valuable tool for accurately tracing and quanti-fying the dynamics of atmospheric particulate matter within plant at the cellular level.

Asunto(s)

RESUMEN

Emergency ambulance dispatches (EAD) have been proven to be associated with ambient particulate matter with diameter < 2.5 µm (PM2.5) concentration, but the associations of circulatory EAD remained inconclusive, especially in heavily polluted areas. In this time series conducted in Shenyang City, Northeastern China, we explored the associations between circulatory EAD and ambient PM2.5 and its constituents. Data including 113,508 circulatory EAD records, five types of PM2.5 constituents, and meteorological information spanning from 2014 to 2019 were retrieved. Using generalized additive models (GAMs), we explored the association between circulatory EAD and calculated excess risks induced by a 10 µg/m3 increase (ERR10) in PM2.5 mass and its constituents. ERR by percentage change (ERRpc) to compare among the different constituents were also calculated. Positive associations between circulatory EAD and PM2.5 mass, sulfates, organic matters, and black carbon, were found particularly at lag0 and lag0-5, with the ERR10 of 3.8% (3.2%-4.4%), 6.5% (2.2%-10.8%), 4.2% (1.7%-6.6%), and 30.2% (17.2%-43.4%) at lag0-5, respectively. Similar associations were observed for cardiovascular EAD, while cerebrovascular EAD suggested a positive association with O3 rather than PM2.5 or its constituents. Notably, PM2.5 mass exhibited the largest ERRpc for circulatory and cardiovascular EAD, followed by sulfates and black carbon. Moreover, the risks were enhanced for circulatory and cardiovascular EAD in males compared to females and during warmer seasons compared to colder seasons. Our findings contribute new evidence on PM2.5 exposure and circulatory EAD in relatively polluted areas.

Asunto(s)