By analyzing the data of urban air pollutant measurements from 2013 to 2015 in Nanjing, East China, we found that the correlation coefficients between major atmospheric compound pollutants PM 2.5 and O 3 were respectively 0.40 in hot season (June, July and August) and −0.16 in cold season (December, January and February) with both passing the confidence level of 99%. This provides evidence for the inverse relations of ambient PM 2.5 and O 3 between cold and hot seasons in an urban area of East China. To understand the interaction of PM 2.5 and O 3 in air compound pollution, the underlying mechanisms on the inversion relations between cold and hot seasons were investigated from the seasonal variations in atmospheric oxidation and radiative forcing of PM 2.5 based on three-year environmental and meteorological data. The analyses showed that the augmentation of atmospheric oxidation could strengthen the production of secondary particles with the contribution up to 26.76% to ambient PM 2.5 levels. High O 3 concentrations in a strong oxidative air condition during hot season promoted the formation of secondary particles, which could result in a positive correlation between PM 2.5 and O 3 in hot season. In cold season with weak atmospheric oxidation, the enhanced PM 2.5 levels suppressed surface solar radiation, which could weaken O 3 production for decreasing ambient O 3 level with the low diurnal peaks. Under the high PM 2.5 level exceeding 115 µg·m −3 , the surface O 3 concentration dropped to 12.7 µg·m −3 at noon with a significant inhibitory effect, leading to a negative correlation between PM 2.5 and O 3 in cold season. This observational study revealed the interaction of PM 2.5 and O 3 in air compound pollution for understanding the seasonal change of atmospheric environment.

Abstract. Nitrous acid (HONO) is a significant precursor of atmospheric “detergent” OH radicals and plays a vital role in tropospheric chemistry. The current knowledge about daytime HONO sources is incomplete, and its impact on the tropospheric radical chemistry has not been fully quantified. Existing observational studies of HONO were mostly conducted at the surface, with few efforts focusing on the high-elevation atmosphere. In order to better understand the characteristics and sources of HONO in the upper boundary layer and lower free troposphere, two intensive field observations were carried out at the summit of Mt. Tai (1534 m a.s.l.), the peak of the North China Plain (NCP), in winter 2017 and spring 2018. HONO showed moderate concentration levels (average ± standard deviation: 0.15±0.15 and 0.13±0.15 ppbv), with maximum values of 1.14 and 3.23 ppbv in winter and spring, respectively. Diurnal variation patterns with broad noontime maxima and lower nighttime concentrations were observed during both campaigns, which is distinct from most of the previous studies at the ground level. The Lagrangian particle dispersion model (LPDM, WRF-FLEXPART v3.3) simulations indicated the combined effects of the planetary boundary layer evolution and valley breeze on the daytime HONO peak. A photostationary state (PSS) analysis suggested a strong unknown daytime HONO source with production rates of 0.45±0.25 ppb h−1 in winter and 0.64±0.49 ppb h−1 in spring. Correlation analysis supported the important role of photo-enhanced heterogeneous conversion of NO2 to HONO on the aerosol surface at this high-elevation site. HONO photolysis is the predominant primary source of OH radical and plays a major role in the radical chemistry at Mt. Tai. The model only considering a homogenous HONO source predicted much lower levels of the HOx radicals and atmospheric oxidation capacity than the model constrained with measured HONO data. This study sheds light on the characteristics, sources, chemistry, and impacts of HONO in the upper boundary layer and lower free troposphere in the NCP region.

Abstract. A global gridded net ecosystem exchange (NEE) of CO2 dataset is vital in global and regional carbon cycle studies. Top-down atmospheric inversion is one of the major methods to estimate the global NEE; however, the existing global NEE datasets generated through inversion from conventional CO2 observations have large uncertainties in places where observational data are sparse. Here, by assimilating the GOSAT ACOS v9 XCO2 product, we generate a 10-year (2010–2019) global monthly terrestrial NEE dataset using the Global Carbon Assimilation System, version 2 (GCASv2), which is named GCAS2021. It includes gridded (1∘×1∘), globally, latitudinally, and regionally aggregated prior and posterior NEE and ocean (OCN) fluxes and prescribed wildfire (FIRE) and fossil fuel and cement (FFC) carbon emissions. Globally, the decadal mean NEE is -3.73±0.52 PgC yr−1, with an interannual amplitude of 2.73 PgC yr−1. Combining the OCN flux and FIRE and FFC emissions, the net biosphere flux (NBE) and atmospheric growth rate (AGR) as well as their inter-annual variabilities (IAVs) agree well with the estimates of the Global Carbon Budget 2020. Regionally, our dataset shows that eastern North America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia are carbon sinks, while the western United States, African grasslands, Brazilian plateaus, and parts of South Asia are carbon sources. In the TRANSCOM land regions, the NBEs of temperate N. America, northern Africa, and boreal Asia are between the estimates of CMS-Flux NBE 2020 and CT2019B, and those in temperate Asia, Europe, and Southeast Asia are consistent with CMS-Flux NBE 2020 but significantly different from CT2019B. In the RECCAP2 regions, except for Africa and South Asia, the NBEs are comparable with the latest bottom-up estimate of Ciais et al. (2021). Compared with previous studies, the IAVs and seasonal cycles of NEE of this dataset could clearly reflect the impacts of extreme climates and large-scale climate anomalies on the carbon flux. The evaluations also show that the posterior CO2 concentrations at remote sites and on a regional scale, as well as on vertical CO2 profiles in the Asia-Pacific region, are all consistent with independent CO2 measurements from surface flask and aircraft CO2 observations, indicating that this dataset captures surface carbon fluxes well. We believe that this dataset can contribute to regional- or national-scale carbon cycle and carbon neutrality assessment and carbon dynamics research. The dataset can be accessed at https://doi.org/10.5281/zenodo.5829774 (Jiang, 2022).

Acrolein (ACR) is a highly reactive α, β-unsaturated aldehyde that plays a key role in the pathogenesis of human diseases, such as atherosclerosis and pulmonary, cardiovascular, and neurodegenerative disorders. We...

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To evaluate the relationship between smoking and both antithyroperoxidase antibody (TPOAb) and antithyroglobulin antibody (TgAb) positivity in subjects from Panshan, Zhangwu, and Huanghua with mildly deficient, more than adequate, and excessive iodine intake, respectively. Smoking-related data were collected by questionnaire, and laboratory measurements of TPOAb, TgAb, and thyrotropin (TSH) were determined at baseline and follow-up. (1) A 1.48-fold increased risk of TPOAb positivity was found in smokers than in non-smokers after adjusting for confounders (age, sex, and areas) (OR[95% CI] = 1.48[1.12-1.95], p = 0.01). (2) Among female subjects, the prevalence of thyroid autoantibodies in smokers was increased than that in non-smokers in Panshan, Zhangwu, and Huanghua (TPOAb): 16.79 vs. 8.89%, 14.14 vs. 11.09%, 19.53 vs. 9.57%; TgAb 15.32 vs. 9.29%, 12.79 vs. 11.94%, 17.19 vs. 10.55%, respectively). The difference was significant in Panshan after adjusting for age. (3) Female long-term smokers (> 20 years) had an increased frequency of thyroid autoantibody positivity than non-smokers after adjusting for confounders (TPOAb OR[95% CI] = 1.60[1.10-2.34]; TgAb OR[95% CI] = 1.31[0.88-1.94]). (4) There was no difference in the incidence of thyroid autoantibodies among non-smokers, new smokers, and long-term smokers at follow-up. (5) TSH was greater in TPOAb-positive subjects than in seronegative smokers (1.56 vs. 1.20 mU/L, p < 0.001) and non-smokers (1.97 vs. 1.58 mU/L, p < 0.001). However, TSH was also greater in non-smokers than in smokers, regardless of whether subjects were positive (1.97 vs. 1.56 mU/L, p = 0.04) or negative (1.58 vs. 1.20 mU/L, p < 0.001) for TPOAb. Long-term smoking could increase the prevalence of thyroid autoantibodies in a population with mildly deficient iodine intake. TSH levels were lesser in smokers than in non-smokers and greater in subjects with thyroid autoantibody positivity than in seronegative subjects. The influence of smoking on TSH levels was independent of thyroid autoantibody levels.

At the end of 2019, confirmed cases of Coronavirus Disease 2019 (COVID-19) caused by a novel virus, named SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) later, appeared in Wuhan, a megacity in central China. The disease spread abruptly throughout the whole country in the following months (He et al.