Temporal-spatial characteristics and sources of heavy metals in bulk deposition across China.

With the rapid development of industries, agriculture, and urbanization (including transportation and population growth), there has been a significant alteration in the emission and atmospheric deposition of heavy metal pollutants. This has consequently given rise to a range of ecological and environmental health issues. In this study, we conducted a comprehensive two-year investigation on the temporal and spatial distribution characteristics of heavy metals in atmospheric deposition across China based on the Nationwide Nitrogen Deposition Monitoring Network (NNDMN). The atmospheric bulk deposition of Lead (Pb), Arsenic (As), Nickel (Ni), Selenium (Se), Chromium (Cr) and Cadmium (Cd) were 6.32 ± 1.59, 4.49 ± 0.57, 1.31 ± 0.21, 1.05 ± 0.16, 0.60 ± 0.06 and 0.21 ± 0.03 mg m-2 yr-1, respectively, with a large variation among the different regions of China. The order for atmospheric deposition flux was Southwest China > Southeast China > North China > Northeast China > Qinghai-Tibet Plateau and rural area > urban area > background area. The concentrations of heavy metals in bulk deposition exhibit seasonal variation with higher levels observed during winter compared to summer and spring, which are closely associated with anthropogenic activities. The Positive Matrix Factorization (PMF) results indicated that combustion, industrial emissions and traffic are the primary contributors to atmospheric deposition of heavy metals. The single factor pollution index (Pi) of heavy metals is consistently below 1, and the composite pollution index (Ni) is 0.16 across China, indicating that atmospheric heavy metal deposition is at a pollution-free level. The comprehensive potential ecological risk index of heavy metals is 11.8, with Cd exhibiting the highest single factor potential ecological risk index at 7.09, suggesting that more attention should be paid to Cd deposition in China. The present study reveals the spatial-temporal distribution pattern of atmospheric heavy metals deposition in China, identifying regional source characteristics and providing a theoretical foundation and strategies for reducing emissions of atmospheric pollutants.

Effects of intercropping on soil greenhouse gas emissions - A global meta-analysis.

Diversified cropping systems, such as intercropping, have shown multifunctionality in agronomic productivity promotion, pest control, and soil health improvement. However, the intense interaction between crop species stimulates soil carbon and nitrogen turnover, and intercropping systems cause inexplicit effects on soil greenhouse gas emissions (GHG). Therefore, a comprehensive meta-analysis using 52 published articles (531 paired observations) was conducted to elucidate the effects of intercropping on soil N2O, CO2, and CH4 emissions under different environmental conditions and field practices to identify the primary driving factors, such as climate, soil and field practices. The results showed that intercropping treatment had a non-significant impact on the three GHG emissions on average. However, using a cereal-legume intercropping regime, adopting moderate N application rate or intercropping in alkaline soils could significantly mitigate soil N2O emission. Additionally, intercropping in soils with high soil organic carbon reduce soil CH4 emission. On the contrary, increasing intercropping duration, or adopted in soils with moderate soil total N tended to stimulate CO2 emission. The mixed-effect model selection indicated that initial soil pH, MAP, MAT, tillage regime, and intercropping duration and type were significant moderators in regulating soil GHG emissions. Our findings explicitly elucidated soil GHG responses to intercropping practice. Further studies are warranted on the evaluation of long-term intercropping effects to improve the comprehensive understanding of C and N balance and global warming potential under intercropping.

Suitable biochar application practices simultaneously alleviate N2O and NH3 emissions from arable soils: A meta-analysis study.

Nitrogen (N) fertilization profoundly improves crop agronomic yield but triggers reactive N (Nr) loss into the environment. Nitrous (N2O) and ammonia (NH3) emissions are the main Nr species that affect climate change and eco-environmental health. Biochar is considered a promising soil amendment, and its efficacy on individual Nr gas emission reduction has been widely reported. However, the interactions and trade-offs between these two Nr species after biochar addition have not been comprehensively analysed. The influencing factors, such as biochar characteristics, environmental conditions, and management measures, remain uncertain. Therefore, 35 publications (145 paired observations) were selected for a meta-analysis to explore the simultaneous mitigation potential of biochar on N2O and NH3 emissions after its application on arable soil. The results showed that biochar application significantly reduced N2O emission by 7.09% while having no significant effect on NH3 volatilisation. Using biochar with a low pH, moderate BET, or pyrolyzed under moderate temperatures could jointly mitigate N2O and NH3 emissions. Additionally, applying biochar to soils with moderate soil organic carbon, high soil total nitrogen, or low cation exchange capacity showed similar responses. The machine-learning model suggested that biochar pH is a dominating moderator of its efficacy in mitigating N2O and NH3 emissions simultaneously. The findings of this study have major implications for biochar application management and aid the further realisation of the multifunctionality of biochar application in agriculture, which could boost agronomic production while lowering environmental costs.

The application of machine learning to air pollution research: A bibliometric analysis.

Machine learning (ML) is an advanced computer algorithm that simulates the human learning process to solve problems. With an explosion of monitoring data and the increasing demand for fast and accurate prediction, ML models have been rapidly developed and applied in air pollution research. In order to explore the status of ML applications in air pollution research, a bibliometric analysis was made based on 2962 articles published from 1990 to 2021. The number of publications increased sharply after 2017, comprising approximately 75% of the total. Institutions in China and United States contributed half of all publications with most research being conducted by individual groups rather than global collaborations. Cluster analysis revealed four main research topics for the application of ML: chemical characterization of pollutants, short-term forecasting, detection improvement and optimizing emission control. The rapid development of ML algorithms has increased the capability to explore the chemical characteristics of multiple pollutants, analyze chemical reactions and their driving factors, and simulate scenarios. Combined with multi-field data, ML models are a powerful tool for analyzing atmospheric chemical processes and evaluating the management of air quality and deserve greater attention in future.

Crop-specific ammonia volatilization rates and key influencing factors in the upland of China - A data synthesis.

Ammonia (NH3) is an important alkaline reactive nitrogen (Nr) species which is involved in global nitrogen (N) biogeochemical cycling, but which has negative impacts on the environment and human health. In order to better understand and control the NH3 loss potential in soil-upland crop systems in China, an integrated data analysis including 1302 observations from 236 published articles between 1980 and 2021 was conducted. The typical NH3 volatilization rate (AVR) and the main factors influencing AVR in the major Chinese upland crops (maize, wheat, openfield vegetables and greenhouse vegetables and others) were estimated and analyzed. The mean AVR for maize, wheat, openfield vegetables and greenhouse vegetables were 7.8%, 5.3%, 8.4% and 1.8%. The most important influencing factors were fertilizer placement, meteorological conditions (especially temperature and rainfall) and soil properties (especially SOM). Subsurface N application produced a significantly lower AVR compared to surface application. High N recovery efficiency and N agronomic efficiency were generally associated with low AVRs. In conclusion, high N application rates, inefficient application methods and the use of loss-prone N fertilizer types are the main factors responsible for high AVRs in major Chinese croplands.

Reactive N emissions from cropland and their mitigation in the North China Plain.

Excessive application of chemical nitrogen (N) fertilizer and inefficient N management are still common in the North China Plain, leading to large reactive N (Nr) losses and pollution, threatening environmental security and public health. Three improved N management practices (33% reduction in N applied (OU), OU combined with partial organic fertilizer substitution (UOM) and the urea in UOM amended with a urease inhibitor (ULOM)) together with no N application (CK) and farmers' conventional practice (CU) were tested on a maize-wheat rotation at Quzhou, Hebei, North China Plain (NCP). Nr emissions were related to WFPS (Water Filled Pore Space), soil mineral N (NH4+-N and NO3--N) and soil temperature. Nr emissions and yield-scaled Nr emissions were significantly reduced by partial substitution of organic fertilizer for chemical fertilizer: NH3 emissions were reduced by 55.8-62.4%. Using a urease inhibitor (Limus®), further reduced NH3 emissions by 40.2-64.5%. Yield-scaled NH3 emissions were, on average, reduced by 60.0% and 55.2% in the maize and wheat growing season, respectively, relative to the UOM treatment. Long-term application of organic fertilizer had a significant positive effect on N use efficiency (NUE). Overall, the study shows that appropriated N management such as reducing the N application rate, partial substitution of chemical N by organic N and using a urease inhibitor can reduce Nr emissions and promote NUE in the North China Plain. The methods corresponding to the ULOM and UOM treatments were the most and second most effective, respectively, with high net economic benefits.

Environmental drivers of the leaf nitrogen and phosphorus stoichiometry characteristics of critically endangered Acer catalpifolium.

Acer catalpifolium is a perennial deciduous broad-leaved woody plant, listed in the second-class protection program in China mainly distributed on the northwest edge of Chengdu plain. However, extensive anthropogenic disturbances and pollutants emissions (such as SO2, NH3 and NOX) in this area have created a heterogeneous habitat for this species and its impacts have not been systematically studied. In this study, we investigated the leaf nitrogen (N) and phosphorus (P) content of A. catalpifolium in the natural distribution areas, and a series of simulation experiments (e.g., various water and light supply regimes, different acid and N deposition levels, reintroduction management) were conducted to analyze responses of N and P stoichiometric characteristics to environmental changes. The results showed that leaf nitrogen content (LNC) was 14.49 ~ 25.44 mg g-1, leaf phosphorus content (LPC) was 1.29~3.81 mg g-1 and the N/P ratio of the leaf (L-N/P) was 4.87~13.93. As per the simulation experiments, LNC of A. catalpifolium is found to be relatively high at strong light conditions (80% of full light), high N deposition (100 and 150 kg N ha-1), low acidity rainwater, reintroduction to understory area or N fertilizer applications. A high level of LPC was found when applied with 80% of full light and moderate N deposition (100 kg N ha-1). L-N/P was high under severe shade (8% of full light), severe N deposition (200 kg N ha-1), and reintroduction to gap and undergrowth habitat; however, low L-N/P was observed at low acidity rainwater or P fertilizer application. The nutrient supply facilitates corresponding elements uptake, shade tends to induce P limitation and soil acidification shows N limitation. Our results provide theoretical guidance for field management and nutrient supply regimes for future protection, population rejuvenation of this species and provide guidelines for conservation and nutrient management strategies for the endangered species.

Improved soil-crop system management aids in NH3 emission mitigation in China.

High ammonia (NH3) emissions from fertilized soil in China have led to various concerns regarding environmental safety and public health. In response to China's blue skies protection campaign, effective NH3 reduction measures need to consider both mitigation efficiency and food security. In this context, we conducted a meta-analysis (including 2980 observations from 447 studies) to select effective measures based on absolute (AV) and yield-scaled (YSAV) NH3 volatilization reduction potential, with the aim of establishing a comprehensive NH3 mitigation framework covering various crop production sectors, and offering a range of potential solutions. The results showed that manipulating crop density, using an intermittent irrigation regime for paddy field rice, applying N as split applications or partially substituting inorganic fertilizer N with organic N sources could achieve reductions in AV and YSAV reduction of 10-20 %; adopting drip irrigation regimes, adding water surface barrier films to paddy fields, or using double inhibitor (urease and nitrification), slow-release or biofertilizers could achieve 20-40 % mitigation; plastic film mulching, applying fertilizer by irrigation or using controlled-release fertilizers could yield 40-60 % reduction; use of a urease inhibitor, fully substituting fertilizer N with organic N, or applying fertilizer by deep placement could decrease AV and YSAV by over 60 %. In addition, use of soil amendments, applying suitable inorganic N sources, or adopting crop rotation, intercropping or a rice-fish production model all had significant benefits to control AV. The adoption of any particular strategy should consider local accessibility and affordability, direct intervention by local/government authorities and demonstration to encourage the uptake of technologies and practices, particularly in NH3 pollution hotspot areas. Together, this could ensure food security and environmental sustainability.

Response of ammonia volatilization to biochar addition: A meta-analysis.

There has been increasing interest in and use of biochar as a soil amendment. However, the effects of biochar addition on ammonia volatilization (AV) appeared contradictory from the many reported studies and the main influencing factors remain unclear. Here, we conducted a comprehensive meta-analysis of 41 published articles with 144 observations to reveal the effects of biochar addition on AV and used a boosted regression tree modelling approach to further interpret the contribution of biochar characteristics, soil properties and experimental conditions to this process. On average, biochar addition did not impact on AV, but this varied greatly under different soil, biochar and experimental conditions. The pH of soil and biochar were important factors impacting AV. Biochar application to acidic soil could stimulate AV, and addition of biochar with a high pH and at a low application rate also showed the same trend. In contrast, combining biochar with urea or organic fertilizer, or using wood-based or acidified biochar at appropriate rates had benefits in reducing AV. These findings have major implications for biochar management strategies in agricultural systems, where an important consideration is the mitigation of potentially detrimental environmental consequences.

Emergy assessment of three home courtyard agriculture production systems in Tibet Autonomous Region, China.

Home courtyard agriculture is an important model of agricultural production on the Tibetan plateau. Because of the sensitive and fragile plateau environment, it needs to have optimal performance characteristics, including high sustainability, low environmental pressure, and high economic benefit. Emergy analysis is a promising tool for evaluation of the environmental-economic performance of these production systems. In this study, emergy analysis was used to evaluate three courtyard agricultural production models: Raising Geese in Corn Fields (RGICF), Conventional Corn Planting (CCP), and Pea-Wheat Rotation (PWR). The results showed that the RGICF model produced greater economic benefits, and had higher sustainability, lower environmental pressure, and higher product safety than the CCP and PWR models. The emergy yield ratio (EYR) and emergy self-support ratio (ESR) of RGICF were 0.66 and 0.11, respectively, lower than those of the CCP production model, and 0.99 and 0.08, respectively, lower than those of the PWR production model. The impact of RGICF (1.45) on the environment was lower than that of CCP (2.26) and PWR (2.46). The emergy sustainable indices (ESIs) of RGICF were 1.07 and 1.02 times higher than those of CCP and PWR, respectively. With regard to the emergy index of product safety (EIPS), RGICF had a higher safety index than those of CCP and PWR. Overall, our results suggest that the RGICF model is advantageous and provides higher environmental benefits than the CCP and PWR systems.