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To mitigate the societal impact of the COVID-19 pandemic, China implemented long-term restrictive measures. The sudden liberalization at the end of 2022 disrupted residents' daily routines, making it scientifically intriguing to explore its effect on air quality. Taking Chongqing City in Southwest China as an example, we examined the impact of restriction liberalization on air quality, identified potential sources of pollutants, simulated the effects of abrupt anthropogenic control relaxation using a Random Forest Model, and applied an optimized model to predict the post-liberalization pollutant concentrations. The results showed increases in PM 2.5 (72.3%), PM 10 (67.7%), and NO 2 (21.9%) concentrations, while O 3 concentration decreased by 20.5%. Although potential pollution source areas contracted, pollution levels intensified with northeastern Sichuan, interior Chongqing, and northern Guizhou being major contributors to pollutant emissions. Anthropogenic emissions accounted for 26.7 ~ 33% changes in PM 2.5 and PM 10 concentrations while meteorological conditions contributed to 40.2 ~ 43.3% variations observed during the period. The optimized model demonstrated a correlation between predicted and observed values with R 2 ranging from 0.70 to 0.89, enabling accurate prediction of post-liberalization pollutant concentrations. This study can enhance our understanding regarding the impact of sudden social lockdown relaxation events on air quality while providing support for urban air pollution prevention., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The complex air pollution driven by both Ozone (O 3 ) and fine particulate matter (PM 2.5 ) significantly influences the air quality in the Sichuan Basin (SCB). Understanding the O 3 formation during autumn and winter is necessary to understand the atmospheric oxidative capacity. Therefore, continuous in-site field observations were carried out during the late summer, early autumn and winter of 2020 in a rural area of Chongqing. The total volatile organic compounds (VOCs) concentration reported by a Proton-Transfer-Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS) were 13.66 ± 9.75 ppb, 5.50 ± 2.64 ppb, and 9.41 ± 5.11 ppb in late summer, early autumn and winter, respectively. The anthropogenic VOCs (AVOCs) and biogenic VOCs (BVOCs) were 8.48 ± 7.92 ppb and 5.18 ± 2.99 ppb in late summer, 3.31 ± 1.89 ppb and 2.19 ± 0.93 ppb in autumn, and 6.22 ± 3.99 ppb and 3.20 ± 1.27 ppb in winter. A zero-dimensional atmospheric box model was employed to investigate the sensitivity of O 3 -precursors by relative incremental reactivity (RIR). The RIR values of AVOCs, BVOCs, carbon monoxide (CO), and nitrogen oxides (NO x ) were 0.31, 0.71, 0.09, and -0.36 for late summer, 0.24, 0.59, 0.22, and -0.38 for early autumn, and 0.30, 0.64, 0.33 and -0.70 for winter, and the results showed that the O 3 formation of sampling area was in the VOC-limited region, and O 3 was most sensitive to BVOCs (with highest RIR values, > 0.6). This study can be helpful in understanding O 3 formation and interpreting the secondary formation of aerosols in the winter., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

The ozone (O 3 ) pollution in China drew lots of attention in recent years, and the Sichuan Basin (SCB) was one of the regions confronting worsening O 3 pollution problem. Many previous studies have shown that regional transport is an important contributor to O 3 pollution. However, very few features of the O 3 profile during transport have been reported, especially in the border regions between different administrative divisions. In this study, we conducted tethered balloon soundings in SCB during the summer of 2020 and captured a nocturnal O 3 transport event during the campaign. Vertically, the O 3 transport occurred in the bottom of the residual layer, between 200 and 500 m above ground level. Horizontally, the transport pathway was directed from southeast to northwest based on the analysis of the wind field and air mass trajectories. The effect of transport in the residual layer on the surface O 3 concentration was related to the spatial distribution of O 3 . For cities with high O 3 concentrations in the upwind region, the transport process would bring clean air masses and abate pollution. For downwind lightly polluted cities, the transport process would slow down the decreasing or even increase the surface O 3 concentration during the night. We provided observational facts on the profile features of a transboundary O 3 transport event between two provincial administrative divisions, which implicated the importance of joint prevention and control measures. However, the sounding parameters were limited and the quantitative analysis was preliminary, more integrated, and thorough studies of this topic were called for in the future., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Forty-six percent of the world's population resides in rural areas, the majority of whom belong to vulnerable groups. They mainly use cheap solid fuels for cooking and heating, which release a large amount of PM 2.5 and cause adverse effects to human health. PM 2.5 exhibits urban-rural differences in its health risk to the respiratory system. However, the majority of research on this issue has focused on respiratory diseases induced by atmospheric PM 2.5 in urban areas, while rural areas have been ignored for a long time, especially the pathogenesis of respiratory diseases. This is not helpful for promoting environmental equity to aid vulnerable groups under PM 2.5 pollution. Thus, this study focuses on rural atmospheric PM 2.5 in terms of its chemical components, toxicological effects, respiratory disease types, and pathogenesis, represented by PM 2.5 from rural areas in the Sichuan Basin, China (Rural SC-PM 2.5 ). In this study, organic carbon is the most significant component of Rural SC-PM 2.5 . Rural SC-PM 2.5 significantly induces cytotoxicity, oxidative stress, and inflammatory response. Based on multiomics, bioinformatics, and molecular biology, Rural SC-PM 2.5 inhibits ribonucleotide reductase regulatory subunit M2 (RRM2) to disrupt the cell cycle, impede DNA replication, and ultimately inhibit lung cell proliferation. Furthermore, this study supplements and supports the epidemic investigation. Through an analysis of the transcriptome and human disease database, it is found that Rural SC-PM 2.5 may mainly involve pulmonary hypertension, sarcoidosis, and interstitial lung diseases; in particular, congenital diseases may be ignored by epidemiological surveys in rural areas, including tracheoesophageal fistula, submucous cleft of the hard palate, and congenital hypoplasia of the lung. This study contributes to a greater scientific understanding of the health risks posed by rural PM 2.5 , elucidates the pathogenesis of respiratory diseases, clarifies the types of respiratory diseases, and promotes environmental equity., Competing Interests: Declaration of competing interest The authors confirm that they have no known competing financial interests or personal relationships which might have influenced the work presented in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Terrain effect is challenging for understanding atmospheric environment changes under complex topography. This study targets the Sichuan Basin (SCB), a deep basin isolated by plateaus and mountains in Southwest China, by employing WRF-Chem with integrated process rates (IPR) analysis to characterize the terrain-driven seasonal variations of tropospheric ozone (O 3 ) with atmospheric physical and chemical processes. Results show that the basin terrain exerts reversed impacts on regional air quality changes by aggravating summertime and alleviating wintertime near-surface O 3 with the relative contributions oscillating seasonally between -40% and 40% in SCB. Similarly, a seasonal shift of vertical O 3 structures is dominated by summertime positive and wintertime negative changes in the lower troposphere induced by basin terrain. The key contributions of atmospheric process to near-surface O 3 are identified with vertical and horizontal transport, which is dominated by basin terrain with intensifying seasonal and diurnal variations. With the existence of basin, the daytime O 3 productions at the near-surface layer are elevated in months of warm seasons (April and July) but inhibited in the cold seasons (October and January), presenting a seasonal transition of primary factor from meteorology to aerosol-radiation forcing on photochemical reactions. Driven by plateau-basin thermodynamic forcing, horizontal O 3 transport between the SCB and eastern TP is enhanced by mountain-plains solenoid (MPS), and even nocturnal O 3 -rich layers contribute to the impacts of vertical exchange on near-surface O 3 levels. The terrain effects of deep basin under the interaction of Asian monsoons and westerlies could jointly change atmospheric physical and chemical processes to construct the seasonal and diurnal O 3 evolution patterns over the SCB region., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Maternal PM 2.5 exposure has been identified as a potential risk factor for preterm birth, yet the inconsistent findings on the susceptible exposure windows may be partially due to the influence of gaseous pollutants. This study aims to examine the association between PM 2.5 exposure and preterm birth during different susceptible exposure windows after adjusting for exposure to gaseous pollutants. We collected 2,294,188 records of singleton live births from 30 provinces of China from 2013 to 2019, and the gridded daily concentrations of air pollutants (including PM 2.5 , O 3 , NO 2 , SO 2 , and CO) were derived by using machine learning models for assessing individual exposure. We employed logistic regression to develop single-pollutant models (including PM 2.5 only) and co-pollutant models (including PM 2.5 and a gaseous pollutant) to estimate the odds ratio for preterm birth and its subtypes, with adjustment for maternal age, neonatal sex, parity, meteorological conditions, and other potential confounders. In the single-pollutant models, PM 2.5 exposure in each trimester was significantly associated with preterm birth, and the third trimester exposure showed a stronger association with very preterm birth than that with moderate to late preterm birth. The co-pollutant models revealed that preterm birth might be significantly associated only with maternal exposure to PM 2.5 in the third trimester, and not with exposure in the first or second trimester. The observed significant associations between preterm birth and maternal PM 2.5 exposure in the first and second trimesters in single-pollutant models might primarily be influenced by exposure to gaseous pollutants. Our study provides evidence that the third trimester may be the susceptible window for maternal PM 2.5 exposure and preterm birth. The association between PM 2.5 exposure and preterm birth could be influenced by gaseous pollutants, which should be taken into consideration when evaluating the impact of PM 2.5 exposure on maternal and fetal health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

PM 2.5 seriously endangers human health, and its mutagenicity is considered an important pathogenic mechanism. However, the mutagenicity of PM 2.5 is mainly determined by traditional bioassays, which are limited in the large-scale identification of mutation sites. Single nucleoside polymorphisms (SNPs) can be used for the large-scale analysis of DNA mutation sites but have not yet been used on the mutagenicity of PM 2.5 . The Chengdu-Chongqing Economic Circle is one of China's four major economic circles and five major urban agglomerations, and the relationship between the mutagenicity of PM 2.5 and ethnic susceptibility in this circle remains unclear. In this study, the representative samples are PM 2.5 from Chengdu in summer (CDSUM), Chengdu in winter (CDWIN), Chongqing in summer (CQSUM) and Chongqing in winter (CQWIN) respectively. PM 2.5 from CDWIN, CDSUM and CQSUM induce the highest levels of mutation in the regions of exon/5'Utr, upstream/splice site and downstream/3'Utr respectively. PM 2.5 from CQWIN, CDWIN and CDSUM induce the highest ratio of missense, nonsense and synonymous mutation respectively. PM 2.5 from CQWIN and CDWIN induce the highest transition and transversion mutations respectively. The ability of PM 2.5 from the four groups to induce disruptive mutation effects is similar. For ethnic susceptibility, PM 2.5 in this economic circle is more likely to induce DNA mutation in Chinese Dai from Xishuangbanna among Chinese ethnic groups. PM 2.5 from CDSUM, CDWIN, CQSUM and CQWIN may particularly tend to induce Southern Han Chinese, Dai in Xishuangbanna, Dai in Xishuangbanna and Southern Han Chinese respectively. These findings may assist in the development of a new method for analyzing the mutagenicity of PM 2.5 . Moreover, this study not only promotes attention to ethnic susceptibility to PM 2.5 , but also introduces public protection policies for the susceptible population., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

In recent years, the annual mean concentration of PM 2.5 has decreased in Chengdu, China; however, atmospheric visibility has not improved accordingly. Low-visibility events occurred even when the PM 2.5 mass concentrations were below the national ambient air quality secondary standard (daily mean concentration, 75 μg/m 3 ). In this study, the non-linear relationship between PM 2.5 and visibility was analyzed under different NO 3 - mass fractions in PM 2.5 based on 2-year field observation data. The results indicated that NO 3 - formation contributed to particulate pollution events and reduced atmospheric visibility. Multiple linear regression was used to propose a localized reconstruction equation for the light-scattering coefficient. According to the maximum likelihood estimation method and log-transformed residuals, the mass scattering coefficients (MSEs) of organic matter (OM), NH 4 NO 3 , and (NH 4 ) 2 SO 4 in Chengdu were 7.42, 3.83, and 3.80, respectively. OM and NH 4 NO 3 contributed to more than 50% of the light-extinction coefficient (b ext ). NH 4 NO 3 was the main pollutant causing the substantial increase in b ext . Chengdu has a high relative humidity (annual mean 70%), and under such conditions, the contribution of NH 4 NO 3 to b ext was considerably enhanced through hygroscopic growth and heterogeneous reactions. This study estimated the localized MSEs of OM, NH 4 NO 3 , and (NH 4 ) 2 SO 4 in Chengdu and emphasized that effective control measures to reduce nitrate and its precursors could simultaneously ameliorate air quality and visibility in humid regions with poor atmospheric visibility., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Air pollutants suspended in the atmosphere have a large impact on air quality, climate, and human health. As one of the important populated and industrialized regions in China, the Sichuan Basin (SCB) has confronted severe air pollution in recent years. Previous studies have shown that regional transport played a significant role in the formation of regional pollution in the SCB, particularly in the southern basin. Using Yibin and Zigong as representative receptor cities, we further identified the transport channels affecting the southern basin by conducting gridded dispersion simulations. A total of seven channels were identified, including three for cyclonic transport, three through the mountainous areas between the Longquan Mountain and the Huaying Mountain, and one along the Yangtze River. Varying seasonal distributions of their occurrence frequencies were observed. Furthermore, observational evidence for several universal channels was presented during a typical transport case. The transport pathways identified in this study can guide the planning of regional distribution of emission sources and the measures for regional joint prevention and control of air pollution.

Chengdu-Chongqing Economic Circle (CD-CQ Economic Circle) is one of China's four major economic circles and five major urban agglomerations located in Southwest China's Sichuan Basin. The CD-CQ Economic Circle, with its strong economic development and dense population, suffers from severe PM 2.5 pollution, which is known to cause chronic and acute respiratory ailments. This study examined the lung disease-related hub genes, functions, and pathways that are affected by PM 2.5 in summer and winter in the two central megacities of Chengdu and Chongqing. PM 2.5 frequently activates lung disease-associated hub genes, most notably the transcription factor TP53. TP53 interacts with the majority of lung disease-related genes and regulates important and commonly occurring biological functions and pathways, including gland development, aging, reactive oxygen species metabolic process, the response to oxygen levels, and fluid shear stress, among others. Thus, PM 2.5 has been shown to target TP53 for regulating lung disease genes/functions/pathways, thereby influencing the occurrence and progression of lung illnesses. Notably, PM 2.5 may be associated with small cell carcinoma of the lung due to the high number of lung disease genes, hub genes, critical functions, and pathways enriched in this kind of cancer. These findings shed fresh light on the molecular pathophysiology of PM 2.5 pollution on the respiratory system in the CD-CQ Economic Circle and aid in the development of novel techniques for mitigating PM 2.5 pollution-associated respiratory illness., (Copyright © 2022. Published by Elsevier Ltd.)

Until recently, Northern China was one of the most SO 2 polluted regions in the world. The lack of long-term and spatially resolved surface SO 2 data hinders retrospective evaluation of relevant environmental policies and human health effects. This study aims to derive the spatiotemporal distribution of surface SO 2 across Northern China during 2005-2019. As "concept drift" causes substantial estimation bias in back-extrapolation, we propose a new approach named the robust back-extrapolation via data augmentation approach (RBE-DA) to model the long-term surface SO 2 . The results show that the population-weighted regional SO 2 ([SO 2 ] pw ) increased from 2005 to 2007 and decreased steadily afterwards. The [SO 2 ] pw decreased by 80.4% from 74.2 ± 28.4 μg/m 3 in 2007 to 14.6 ± 4.8 μg/m 3 in 2019. The predicted spatial distributions for each year show that the SO 2 pollution was severe (more than 20 μg/m 3 ) in most areas of Northern China until 2017. By using model interpretation methods, we visually reveal the mechanism of estimation bias in the back-extrapolation. Specifically, the training data is severely imbalanced with respect to the satellite-retrieved SO 2 column densities (i.e., it is short on high-value samples), so the benchmark model is unable to extrapolate the effects of this important predictor. This study provides long-term surface SO 2 data for post hoc evaluation and human exposure assessment in Northern China, while demonstrating that the interpretable machine learning approach is critical for model diagnostics and refinement. Leveraging satellite retrievals, the RBE-DA approach can be applied worldwide to back-extrapolate various measures of air quality., Competing Interests: Declaration of competing interest The authors declare no competing interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Long-term surface NO 2 data are essential for retrospective policy evaluation and chronic human exposure assessment. In the absence of NO 2 observations for Mainland China before 2013, training a model with 2013-2018 data to make predictions for 2005-2012 (back-extrapolation) could cause substantial estimation bias due to concept drift., Objective: This study aims to correct the estimation bias in order to reconstruct the spatiotemporal distribution of daily surface NO 2 levels across China during 2005-2018., Methods: On the basis of ground- and satellite-based data, we proposed the robust back-extrapolation with a random forest (RBE-RF) to simulate the surface NO 2 through intermediate modeling of the scaling factors. For comparison purposes, we also employed a random forest (Base-RF), as a representative of the commonly used approach, to directly model the surface NO 2 levels., Results: The validation against Taiwan's NO 2 observations during 2005-2012 showed that RBE-RF adequately corrected the substantial underestimation by Base-RF. The RMSE decreased from 10.1 to 8.2 µg/m 3 , 7.1 to 4.3 µg/m 3 , and 6.1 to 2.9 µg/m 3 in predicting daily, monthly, and annual levels, respectively. For North China with the most severe pollution, the population-weighted NO 2 ([NO 2 ] pw ) during 2005-2012 was estimated as 40.2 and 50.9 µg/m 3 by Base-RF and RBE-RF, respectively, i.e., 21.0% difference. While both models predicted that the national annual [NO 2 ] pw increased during 2005-2011 and then decreased, the interannual trends were underestimated by >50.2% by Base-RF relative to RBE-RF. During 2005-2018, the nationwide population that lived in the areas with NO 2  > 40 µg/m 3 were estimated as 259 and 460 million by Base-RF and RBE-RF, respectively., Conclusion: With RBE-RF, we corrected the estimation bias in back-extrapolation and obtained a full-coverage dataset of daily surface NO 2 across China during 2005-2018, which is valuable for environmental management and epidemiological research., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The association between maternal exposure to gaseous air pollutants and congenital heart defects (CHD) remains unclear. The concentration-response relationship and the time windows of susceptibility to gaseous pollutants may vary by pollutant species and CHD subtypes., Objective: We aimed to examine the relationship between maternal exposures to four species of gaseous pollutants (NO 2 , O 3 , SO 2 , and CO) and atrial septal defect (ASD), which is a common subtype of CHD, and to determine the critical time windows of susceptibility for each gaseous pollutant., Methods: Among 1,253,633 infants born between October 1, 2013 and December 31, 2016 in China, 1937 newborns were diagnosed with isolated ASD, a prevalence of 1.55‰. Maternal exposures to the gaseous pollutants were estimated by matching the geocoded maternal addresses with the gridded ambient concentrations. The adjusted odds ratios (aOR) between exposures and ASD were quantified by using mixed-effects logistic regression models., Results: We found significantly positive associations between ASD and maternal exposures to NO 2 , O 3 , SO 2 , and CO during entire pregnancy, first-, second-, and third-trimester. However, no statistically significant association was found between maternal exposure to PM 2.5 , PM 2.5-10 and ASD risk (P > 0.05). In the fully adjusted model with respect to average exposure over entire pregnancy, the adjusted odds ratios (aOR) for each 10 μg/m 3 increment of NO 2 , O 3 , SO 2 were 1.33 (95% CI: 1.22-1.45), 1.13 (95% CI: 1.10-1.16), 1.28 (95% CI: 1.20-1.35), respectively; the aOR for each 100 μg/m 3 increment of CO was 1.10 (95% CI: 1.06-1.15). The observed concentration-response relationships varied by exposure periods and pollutants, with the strongest association for NO 2 during the 1st-8th embryology weeks, for O 3 during the third trimester, for SO 2 during the second trimester, and for CO without obvious variation., Conclusions: The findings suggest an increased risk of ASD in association with maternal exposures to four common gaseous pollutants. From the perspective of birth defects prevention and ASD risk mitigation, it is critical to reduce maternal exposure to gaseous pollutants especially during the most susceptible time windows., (Copyright © 2021 Elsevier Inc. All rights reserved.)

China has been performing nationwide social lockdown by releasing the Level 1 response to major public health emergencies (RMPHE) to struggle against the COVID-19 (SARS-CoV-2) outbreak since late January 2020. During the Level 1 RMPHE, social production and public transport were maintained at minimal levels, and residents stayed in and worked from home. The universal impact of anthropogenic activities on air pollution can be evaluated by comparing it with air quality under such extreme conditions. We investigated the concentration of both gaseous and particulate pollutants and aerosol light absorption at different levels of (RMPHE) in an urban area of southwestern China. During the lockdown, PM 2.5 , PM 10 , SO 2 , NO x , and BC decreased by 30-50%, compared to the pre-Level 1 RMPHE period. Meanwhile, the decrease of NO x caused the rise of O 3 by up to 2.3 times due to the volatile organic compounds (VOCs) limitation. The aerosol light absorption coefficient at multiple wavelengths decreased by 50%, and AAE decreased by 20% during the Level 1 RMPHE. BrC played essential roles in light absorption after the RMPHE was announced, accounting for 54.0% of the aerosol absorption coefficient at 370 nm. Moreover, the lockdown down-weighted the fraction of fossil fuel in BC concentrations to 0.43 (minima). This study characterizes air pollution at the most basic level and can provide policymakers with references for the "baseline.", Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

While accumulating evidence shows that air pollution exposure is an important risk factor to influenza prevalence, their association has been inadequately investigated in mountainous regions with dense populations and high humidity. We aim to estimate the association and exposure-outcome effects between exposure to nitrogen dioxide (NO 2 ) and influenza prevalence in a mountainous region with a dense population and high humidity. We investigated 14,993 patients with confirmed influenza cases from January 2013 to December 2017 in Chongqing, a mountainous city in southwest China. We developed distributed lag non-linear models with quasi-Poisson link to take into account the lag and non-linear effects of NO 2 exposure on influenza prevalence. We estimated that the cumulative effect of a 10 μg/m 3 increase in NO 2 with seven-day lag (i.e., summing all the contributions up to seven days) corresponded to relative risk of 1.24 (95% CI: 1.17-1.31) in daily influenza prevalence. Comparing to annual mean of the World Health Organization air quality guidelines of 40 μg/m 3 for NO 2 , we estimated that 14.01% (95% CI: 10.69-17.08%) of the influenza cases were attributable to excessive NO 2 exposure. Our results suggest that NO 2 exposure could worsen the risk of influenza infection in this mountainous city, filling the gap of relevant researches in densely populated and mountainous cities. Our findings provide evidence for developing influenza surveillance and early warning systems., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The Three Gorges Dam's construction and industrial transfer have resulted in a new air pollution pattern with the potential to threaten the reservoir eco-environment. To assess the impact of socioeconomic factors on the pattern of air quality vairation and economical risks, concentrations of SO 2 , NO 2 , and PM 10 , industry genres, and meteorological conditions were selected in the Three Gorges Reservoir of Chongqing (TGRC) during 2006-2015. Results showed that air quality had improved to some extent, but atmospheric NO 2 showed an increased trend during 2011-2015. Spatially, higher atmospheric NO 2 extended to the surrounding area. The primary industry, especially for agriculture, had shown to be responsible for the remarkable increase of atmospheric NO 2 (p < 0.01) due to the direct burning of agricultural straws and the emission of livestock breeding. The improvement of regional industrial structure and industrialization benefited air pollutant reductions, but construction industries had inhibited the improvement of regional air quality. In the tertiary industry, the cargo industry at ports had significantly decreased atmospheric NO 2 as a result of eliminating the obsoleted small ships. Contrarily, the highway transportation had brought more air pollutants. The relative humidity was shown to be the main meteorological factor, which had an extremely remarkable relation with atmospheric SO 2 (p < 0.01) and a significant correlation with atmospheric NO 2 (p < 0.05), respectively. In the future, the development of agriculture and livestock breeding would make regional air quality improvement difficult, and atmospheric SO 2 , NO 2 , and PM 10 deposition would aggravate regional soil and water acidification and reactivate heavy metal in soil and sediment, further to pose a high level of ecological risk in the TGRC and other countries with reservoirs in the world.

There is a paucity of prospective cohort studies investigating the impact of environmental factors on the development of cardiometabolic (CM) disorders like type II diabetes (T2DM). The objective of the Air-Pollution and Cardiometabolic Diseases (AIRCMD) study is to investigate the impact of personal level air pollution measures [personal black carbon (BC)/sulfate measures] and ambient fine particulate matter [(PM2.5)/NO2] levels on propensity to type II diabetes in Beijing, China. Subjects with metabolic syndrome will undergo four repeated study visits within each season over a one year period following an initial screening visit. At each study visit, subjects will be monitored for sub-acute exposure to personal and ambient measures of air-pollution exposure and will undergo a series of functional CM outcomes. The primary endpoints include independent associations between integrated 5-day mean exposure to PM2.5 and BC and homeostasis model assessment of insulin resistance (HOMA-IR) measures, 24-hour mean diastolic and mean arterial pressure and endothelial-dependent vasodilatation. The secondary endpoints will explore the mechanistic explanation for a causal relationship between exposures and propensity for type II diabetes and will include additional functional outcomes such as arterial compliance, heart rate variability and plasma adipokines. The novel aspects of the study include the launch of infrastructure for future translational investigations in highly polluted urbanized environments and the creation of novel methodologies for linking personalized exposure measurements with functional CM outcomes. We believe that AIRCMD will allow for unprecedented new investigations into the association between environmental risk factors and CM disorders., (Copyright © 2012 Elsevier B.V. All rights reserved.)