Progress in Dust Modelling, Global Dust Budgets, and Soil Organic Carbon Dynamics

Soil and water pollution and cardiovascular disease

Healthy, uncontaminated soils and clean water support all life on Earth and are essential for human health. Chemical pollution of soil, water, air and food is a major environmental threat, leading to an estimated 9 million premature deaths worldwide. The Global Burden of Disease study estimated that pollution was responsible for 5.5 million deaths related to cardiovascular disease (CVD) in 2019. Robust evidence has linked multiple pollutants, including heavy metals, pesticides, dioxins and toxic synthetic chemicals, with increased risk of CVD, and some reports suggest an association between microplastic and nanoplastic particles and CVD. Pollutants in soil diminish its capacity to produce food, leading to crop impurities, malnutrition and disease, and they can seep into rivers, worsening water pollution. Deforestation, wildfires and climate change exacerbate pollution by triggering soil erosion and releasing sequestered pollutants into the air and water. Despite their varied chemical makeup, pollutants induce CVD through common pathophysiological mechanisms involving oxidative stress and inflammation. In this Review, we provide an overview of the relationship between soil and water pollution and human health and pathology, and discuss the prevalence of soil and water pollutants and how they contribute to adverse health effects, focusing on CVD.

Spatiotemporal variations and driving factors for potential wind erosion on the Mongolian Plateau

Wind erosion can cause desertification and sandstorms in arid and semiarid areas. However, quantitative studies of the dynamic changes in wind erosion over long time periods are relatively rare, and this knowledge gap hinders our understanding of desertification under the conditions of a changing climate. Here, we selected the Mongolian Plateau as the study area. Using the revised wind erosion equation (RWEQ) model, we assessed the spatial and temporal dynamics of wind erosion on the Mongolian Plateau from 1982 to 2018. Our results showed that the wind erosion intensity on the Mongolian Plateau increased from northeast to southwest. The annual mean wind erosion modulus was 46.5 t·ha^-1 in 1982-2008, with a significant decline at a rate of -5.1 t·ha^-1·10 yr^-1. The intensity of wind erosion was the strongest in spring, followed by autumn and summer, and was weakest in winter. During 1982-2018, wind erosion showed a significant decreasing trend in all seasons except winter. The wind erosion contribution of spring to the total annual wind erosion significantly increased, while that of summer significantly decreased. These results can help decision-makers identify high-risk areas of soil erosion on the Mongolian Plateau and take effective measures to adapt to climate change.

Contribution of local and surrounding area anthropogenic emissions to a high ozone episode in Zhengzhou, China

This study analyzed an ozone pollution episode that occurred in the summer of 2020 in Zhengzhou, the provincial capital of Henan, China, and quantified the contribution of local and surrounding area anthropogenic emissions to this episode based on the Weather Research and Forecasting with Chemistry (WRF/Chem) model. Simulation results showed that the WRF/Chem model is well suited to simulate the ozone concentrations in this area. In addition, four simulation scenarios (removing the emissions from the northern Zhengzhou, southwestern Zhengzhou, Zhengzhou local and southeastern Zhengzhou) were conducted to explore the specific contributions of local emissions and emissions from surrounding areas within Henan to this ozone pollution episode. We found that contributions from the northern, local, southwestern, and southeastern regions were 6.1%, 5.9%, 1.7%, and 1.5%, respectively. The northern and local emissions of Zhengzhou (only emissions from Zhengzhou) were prominent contributors within the simulation areas. In other words, during this episode, most of the ozone pollution in Zhengzhou appeared to be transported in from regions outside Henan Province.

Full-Coverage PM2.5 Mapping and Variation Assessment during the Three-Year Blue-Sky Action Plan Based on a Daily Adaptive Modeling Approach

Owing to a series of air pollution prevention and control policies, China’s PM2.5 pollution has greatly improved; however, the long-term spatial contiguous products that facilitate the analysis of the distribution and variation of PM2.5 pollution are insufficient. Due to the limitations of missing values in aerosol optical depth (AOD) products, the reconstruction of full-coverage PM2.5 concentration remains challenging. In this study, we present a two-stage daily adaptive modeling framework, based on machine learning, to solve this problem. We built the annual models in the first stage, then daily models were constructed in the second stage based on the output of the annual models, which incorporated the parameter and feature adaptive tuning strategy. Within this study, PM2.5 concentrations were adaptively modeled and reconstructed daily based on the multi-angle implementation of atmospheric correction (MAIAC) AOD products and other ancillary data, such as meteorological factors, population, and elevation. Our model validation showed excellent performance with an overall R2 = 0.91 and RMSE = 9.91 μg/m3 for the daily models, along with the site-based cross-validation R2s and RMSEs of 0.86–0.87 and 12–12.33 μg/m3; these results indicated the reliability and feasibility of the proposed approach. The daily full-coverage PM2.5 concentrations at 1 km resolution across China during the Three-Year Blue-Sky Action Plan were reconstructed in this study. We analyzed the distribution and variations of reconstructed PM2.5 at three different time scales. Overall, national PM2.5 pollution has significantly improved with the annual average concentration dropping from 33.67–28.03 μg/m3, which demonstrated that air pollution control policies are effective and beneficial. However, some areas still have severe PM2.5 pollution problems that cannot be ignored. In conclusion, the approach proposed in this study can accurately present daily full-coverage PM2.5 concentrations and the research outcomes could provide a reference for subsequent air pollution prevention and control decision-making.

Spatiotemporal PM2.5 estimations in China from 2015 to 2020 using an improved gradient boosting decision tree

Fine particulate matter (PM_2.5) with spatiotemporal continuity can provide important basis for the assessment of adverse effects on human health. In recent years, researchers have done a lot of work on the surface PM_2.5 simulation. However, due to the limitations of data and models, it is difficult to accurately evaluate the spatial and temporal PM_2.5 variations on a fine scale. In this study, we adopted the multi-angle implementation of atmospheric correction (MAIAC) aerosol products, and proposed a spatiotemporal model based on the gradient boosting decision tree (GBDT) algorithm to retrieve PM_2.5 concentration across China from 2015 to 2020 at 1-km resolution. Our model achieved excellent performance, with overall CV-R² of 0.92, and annual CV-R² of 0.90-0.93. In addition, the model can also be used for evaluation on different time scales. Compared with previous studies, the model developed in our study performed better and more stable, which showed the highest accuracies in PM_2.5 estimation works at 1-km resolution. During the study period, the overall national PM_2.5 pollution showed a downward trend, with the annual mean concentration dropping from 42.42 μg/m³ to 27.91 μg/m³. The largest decrease occurred in Beijing-Tianjin-Hebei (BTH), with a trend of -5.17 μg/m³/yr, while it remains the most polluted region. The area meeting the secondary national air quality standard (<35 μg/m³) increased from ∼34% to ∼79%. These results indicate that the atmospheric environment has improved significantly. Moreover, different regions have different time nodes for the start of the continuous standard-met day during the year, and the duration is different as well. Overall, this study can provide reliable large-scale PM_2.5 estimations.

Metal(loid)s Spatial Distribution, Accumulation, and Potential Health Risk Assessment in Soil-Wheat Systems near a Pb/Zn Smelter in Henan Province, Central China

To understand the influence of Pb/Zn smelter on surrounding environment, 110 soil and 62 wheat grain samples (62 paired samples) were collected nearby a Pb/Zn smelter in Jiaozuo City, Henan Province, China. The content and spatial distribution of metal(loid)s in the soil-wheat system, and the potential health risk via consumption of wheat grains were determined. Results showed that the average content of Pb, Cd, As, Cu, Zn, and Ni in soil were 129.16, 4.28, 17.95, 20.43, 79.36, and 9.42 mg/kg, respectively. The content of Cd in almost all soil samples (99.1%) exceeded the national limitation of China (0.6 mg/kg). Spatial distribution analysis indicated that atmospheric deposition might be the main pollution source of Pb, Cd, As, and Zn in soil. In addition, the average content of Pb, Cd, As, Cu, Zn, and Ni in wheat grain were 0.62, 0.35, 0.10, 3.7, 35.77, and 0.15 mg/kg, respectively, with the average Pb and Cd content exceeding the national limitation of China. The average bioaccumulation factor of these metal(loid)s followed the following order: Zn (0.507) > Cu (0.239) > Cd (0.134) > Ni (0.024) > Pb (0.007) > As (0.006). Health risk assessment indicated that the average noncarcinogenic risk of children (6.78) was much higher than that of adults (2.83), and the carcinogenic risk of almost all wheat grain is higher than the acceptable range, with an average value of 2.43 × 10−2. These results indicated that humans who regularly consume these wheat grains might have a serious risk of noncarcinogenic and carcinogenic diseases.

Exploring the Ecological Climate Effects Based on Five Land Use Types: A Case Study of the Huang-Huai-Hai River Basin in China

As one of the main driving forces for the change in surface energy balance, land use and cover change affects the ecological climate through different levels of biogeochemical and physical processes. However, many studies on the surface energy balance are conducted from the perspective of biogeochemistry, ignoring biogeochemical processes. By using core methods such as the surface energy balance algorithm and Mann-Kendall trend test, we analyzed the surface energy balance mechanism and ecological climate effects of five land use types in the Huang-Huai-Hai Basin in China. The results showed that: (1) the net radiation and latent heat flux in the five land use types increased significantly, and their highest values were located in cropland areas and urban expansion areas, respectively. (2) The influence of net radiation on surface energy absorption was greater than latent heat flux. This relationship was more obvious in land use types that were greatly influenced by human activities. (3) The net surface energy intake in the Huang-Huai-Hai River Basin showed a decreasing trend and decreased with the increase in human influence intensity, indicating that human activities weakened the positive trend in net surface energy intake and increased the warming effect. This study reveals the difference in energy budgets of different land use types under the influence of human activities. It is helpful for understanding how to formulate sustainable land management strategies, and it also provides a theoretical basis for judging the climate change trends and urban heat island effects in the Huang-Huai-Hai River Basin from a biogeophysical perspective.