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Background and objective: The area of mangroves is gradually decreasing globally, and mangroves are already one of the most threatened ecosystems. Despite net growth in the mangrove areas in China, the restoration potential of mangroves is still insufficient. This study proposed the Random forest model as an excellent data mining method to map the restoration potential based on the predicted probability of mangrove habitat suitability.Methods: We demonstrated the vital environmental variables influencing habitat suitability. The de-cisive advantages of RFM were parsimonious (variables selection), cost-effective (us-ing existing open-source data), accurate (training AUC was 0.89, testing AUC was 0.91), highly efficient (fast-training speed); and its results had high explanatory power. Here, we first mapped the conservation gaps using the RFM.Results: The results showed that temperature was the most important environmental factor influencing the habitat suit-ability of mangroves. The northern limit of suitable areas was around 24°44' N. The theoretical suitable habitat area for mangrove was 196,566.6 ha (the highly suitable area was 32,551.4 ha, the medium suitable area was 164,015.2 ha). The potential area for mangrove restoration was 176,264 ha (Guangdong with 104215.4 ha, Guangxi with 65957.5 ha).Conclusion: We proposed 24 sites with conservation gaps for mangrove forests restoration and nine potential sites as examples for the further restoration plan. We took one example site with high restoration potential for further explanation: how the key environmental factors influence the habitat suitability and how to use the infor-mation to guide the restoration strategies. RFM can be used as a data mining algo-rithm for the utmost use of the presence-only ecological data, objectively evaluating the suitability of species distribution, and providing scientifically technical data for species restoration planning.

Exploring the responses of greenhouse gas (GHG) emissions to land use conversion or reversion is significant for taking effective land use measures to alleviate global warming. A global meta-analysis was conducted to analyze the responses of carbon dioxide (CO

Feeding an increasingly affluent population is a huge challenge facing global agriculture. In contrast to “large-scale farming” in developed economies (e.g. Europe and the United States), developing countries are dominated by “smallholder farms” relying on traditional farming practices but increasingly with substantial nitrogen overuse leading to severe environmental degradation and adverse human health. Here, we explore the potential for better nitrogen use by synthesizing the global relationship between farm size and nitrogen use for 16 major crops, assess the impact of farm size on nitrogen flows, and link these with air quality modelling to produce an integrated assessment of nitrogen-related environmental and health outcomes related to farm size. We find that increasing farm size in developing countries can contribute to more efficient and sustainable farming practices, which could decrease nitrogen overuse, ammonia emissions and nitrogen deposition by 20-25%, increase nitrogen use efficiency by 2-8%, and save over 142,000 premature deaths per year related to PM2.5 air pollution. Although a large one-time investment is required for increasing farm size, there would be substantial progress towards achieving Sustainable Development Goals, associated with food security, a clean environment and improved human health.

Growing population and consumption pose unprecedented demands on food production. However, ammonia emissions mainly from food systems increase oceanic nitrogen deposition contributing to eutrophication. Here, we developed a long-term oceanic nitrogen deposition dataset (1970 to 2018) with updated ammonia emissions from food systems, evaluated the impact of ammonia emissions on oceanic nitrogen deposition patterns, and discussed the potential impact of nitrogen fertilizer overuse. Based on the chemical transport modeling approach, oceanic ammonia-related nitrogen deposition increased by 89% globally between 1970 and 2018, and now, it exceeds oxidized nitrogen deposition by over 20% in coastal regions including China Sea, India Coastal, and Northeastern Atlantic Shelves. Approximately 38% of agricultural nitrogen fertilizer was excessive, which corresponds to 15% of global oceanic ammonia-related nitrogen deposition. Policymakers and water quality managers need to pay increasingly more attention to ammonia associated with food production if the goal of reducing coastal nitrogen pollution is to be achieved for Sustainable Development Goals.

China experienced worsening ground-level ozone (O3) pollution from 2013 to 2019. In this study, meteorological parameters, including surface temperature (T2), solar radiation (SW), and wind speed (WS), were classified into two aspects, (1) Photochemical Reaction Condition (PRC = T2 × SW) and (2) Physical Dispersion Capacity (PDC = WS). In this way, a Meteorology Synthetic Index (MSI = PRC/PDC) was developed for the quantification of meteorology-induced ground-level O3 pollution. The positive linear relationship between the 90th percentile of MDA8 (maximum daily 8-h average) O3 concentration and MSI determined that the contribution of meteorological changes to ground-level O−3 varied on a latitudinal gradient, decreasing from ∼40% in southern China to 10%–20% in northern China. Favorable photochemical reaction conditions were more important for ground-level O3 pollution. This study proposes a universally applicable index for fast diagnosis of meteorological roles in ground-level O3 variability, which enables the assessment of the observed effects of precursor emissions reductions that can be used for designing future control policies. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s00376-021-1257-x.

Graphical abstract The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented public health, and social and economic challenges. It remains unclear whether seasonal changes in ambient temperature will alter spreading trajectory of the COVID-19 epidemic. The probable mechanism on this is still lacking. This review summarizes the most recent research data on the effect of ambient temperature on the COVID-19 epidemic characteristic. The available data suggest that (i) mesophilic traits of viruses are different due to their molecular composition; (ii) increasing ambient temperature decreases the persistence of some viruses in aquatic media; (iii) a 1°C increase in the average monthly minimum ambient temperatures (AMMAT) was related to a 0.72% fewer mammalian individuals that would be infected by coronavirus; (iv) proportion of zoonotic viruses of mammals including humans is probably related to their body temperature difference; (v) seasonal divergence between the northern and southern hemispheres may be a significant driver in determining a waved trajectory in the next 2 years. Further research is needed to understand its effects and mechanisms of global temperature change so that effective strategies can be adopted to curb its natural effects. This paper mainly explores possible scientific hypothesis and evidences that local communities and authorities should consider to find optimal solutions that can limit the transmission of SARS-CoV-2 virus. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-14625-8.

Significance Agricultural systems are already major forces of ammonia pollution and environmental degradation. How agricultural ammonia emissions affect the spatio-temporal patterns of nitrogen deposition and where to target future mitigation efforts, remains poorly understood. We develop a substantially complete and coherent agricultural ammonia emissions dataset in nearly recent four decades, and evaluate the relative role of reduced nitrogen in total nitrogen deposition in a spatially explicit way. Global reduced nitrogen deposition has grown rapidly, and will occupy a greater dominant position in total nitrogen deposition without future ammonia regulations. Recognition of agricultural ammonia emissions on nitrogen deposition is critical to formulate effective policies to address ammonia related environmental challenges and protect ecosystems from excessive nitrogen inputs.

A massive rise in atmospheric nitrogen deposition (ND) has threatened ecosystem health through accelerating soil nitrogen (N) cycling rates. While soil microbes serve a crucial function in soil N transformation, it remains poorly understood on how excess ND affects microbial functional populations regulating soil N transformation in tropical forests. To address this gap, we conducted 13-year N (as NH

The populous Pearl River Delta (PRD) region in China suffers from serious air arsenic (As) pollution. The objective of this study was to explore the pollution situation of atmospheric arsenic deposition in the PRD region, and to evaluate the associated multimedia daily intake in children. The average deposition flux was 3921.7 μg/m2/year during the 2016-2017, and the pollution situation was even worse than that in 2015. A continuously increasing trend of arsenic atmospheric deposition was found. The bioaccessibility of As in the settled dust was determined as about 22% by a physiologically based extraction test (PBET). After corrected with the bioaccessibilities of As in the settled dust and food items, the geometry means (GM) value of daily uptake through multimedia ingestion of produce (dust and diet) originated from arsenic atmospheric deposition was 0.23 μg/kg/day for 1- to 6-year-old children. The contribution of the non-dietary oral exposure (settled dust) was negligible and just accounted for only 0.01% of the daily uptake. This estimated value was much lower than those in the literatures, in which the bioaccessibility of As was not taken into account, concluding that the role of the settled dust in the total daily intake may have been overestimated previously. Milk, eggs and freshwater fish were the dominant pathways for children to intake the products derived from atmospheric arsenic deposition. There still be a concern about the high non-carcinogenic and carcinogenic risk by long-term multimedia ingestion. Special care should be considered toward the emission sources of air arsenic, including the coal combustion from industries and construction dust, etc., to reduce the negative effect of air arsenic in children.

Single particle aerosol mass spectrometers (SPAMS) have created significant interest among atmospheric scientists by virtue of their ability to provide real-time size-resolved information on the chemical composition of aerosols. The objective of this study is to evaluate the newly developed single particle analysis technique in terms of chemical characterization and source apportionment of ambient aerosols by comparing it with traditional filter-based methods. In this study, an air quality monitoring campaign was conducted over a period of 25 days at an urban area in Yulin city, southern China, by employing both SPAMS and traditional filter-based measurements to establish the performance of SPAMS. It was observed that the chemical characterization of particles based on SPAMS did not agree well with the filter-based analysis. Based on the filter analysis, sulfate was the most abundant component in PM2.5 (23.5%), followed by OC (18.1%), while for single particle analysis (number concentration), EC-containing particles showed the largest contribution to PM2.5 (>40%), followed by OC (15.7%). In terms of source apportionment via positive matrix factorization, six sources were identified by each of the two approaches. Both the approaches showed relatively good agreements for secondary species, traffic, and dust sources; however, discrepancies were noted for industry, fossil fuel, and biomass burning sources. Finally, investigation of diurnal profiles and two specific emission episodes monitored during the Chinese New Year and traffic activities demonstrated the relative advantage of single particle analysis over filter-based methods. Overall, single particle analysis can provide source apportionment with a high time resolution, which is helpful for policy makers to analyze and implement emergency control strategies during air pollution episodes. However, SPAMS performs quantification of number concentration rather than mass concentration and is limited to particles larger than 200 nm, which leads to discrepancies between the two methods. SPAMS measurements can therefore not simply replace traditional filter-based analyses, which needs to be carefully considered in the selection of the monitoring implementation.

The trends and variability of atmospheric nitrogen deposition in the Pearl River Delta (PRD) region for the period 2008-2017 were investigated by integrating ground- and satellite-based observations and a chemical transport model, in order to gauge the effects of emission reductions and meteorological variability. We show that dry deposition observation of oxidized nitrogen decreased at the rate of 2.4% yr

Metals can pose hazards to marine species and can adversely affect structures and functions of communities of marine species. However, little is known about how structural properties of metal atoms combined with current geographical and climatic conditions affect their toxic potencies. A mathematical model, based on quantitative structure-activity relationships and species sensitivity distributions (QSAR-SSD) was developed by use of acute toxicities of six metals (Cd, Cr, Cu, Hg, Ni, and Zn) to eight marine species and accessory environmental conditions. The model was then used to predict toxicities of 31 metals and metalloids and then to investigate relationships between acute water quality criteria (WQC) and environmental conditions in coastal marine environments. The model was also used to predict WQC in the coastal areas of different countries. Given global climate change, the QSAR-SSD model allows development of WQC for metals that will be protective of marine ecosystems under various conditions related to changes in global climate. This approach could be of enormous benefit in delivering an evidence-based approach to support regulatory decision making in management of metal and metalloids in marine waters.

Exposure to radionuclide thorium (Th) has generated widespread public concerns, mainly because of its radiological effects on human health. Activity levels of airborne 232 Th in total suspended particulate (TSP) were measured in the vicinity of the largest rare earth mine in China in August 2012 and March 2013. The mean activity concentrations of 232 Th in TSP ranged from 820 μBq m − 3 in a mining area in August 2012 to 39,720 μBq m − 3 in a smelting area in March 2013, much higher than the world reference of 0.5 μBq m − 3 . Multistatistical analysis and Kohonen's self-organizing maps suggested that 232 Th in TSP was mainly derived from rare earth mining and smelting practices. In addition, personal inhalation exposures to 232 Th associated with respirable particulate (PM 10 ) were also measured among local dwellers via personal monitoring. The mean dose values for different age groups in the smelting and mining areas ranged from 97.86 to 417 μSv year − 1 and from 101.03 to 430.83 μSv year − 1 , respectively. These results indicate that people living in the study areas are exposed to high levels of widespread 232 Th.

The fine particulate matter (PM2.5) pollution is one of the atmospheric environmental problems in densely populated areas of China. The secondary species contribution in PM2.5 is extensively studied but the comprehensive analysis on the long-term trend of the secondary species and the main drivers of this trend in the Pearl River Delta (PRD) have not been explored. Therefore, this study aimed to evaluate the long-term temporal variation of PM2.5 and its secondary species contribution in PRD for twenty years from 2000 to 2019. The results of the meta-analysis showed that the annual average concentration of PM2.5 in the PRD was 60.3 ± 16.8 μg/m3 and generally decreased by 3.9 μg/m3 per year from 2004 to 2019. Three significant transitions in secondary species percentage were observed during 2000–2019: first declined in 2000–2005 before rose in 2005–2008 and followed by a stable period in 2008–2019. The percentage of secondary species stabilized at around 80%, of which secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA, including SO42−, NO3−, and NH4+) had identical contributions to PM2.5 over the past decade. SOA was affected by the concentration of total oxidant (OX) and volatile organic compounds (VOCs) emissions. SO42− and SO2 have declined with significant reductions in SO2 emissions. NO3− and NH4+ were positively and negatively correlated with the atmospheric concentration of NO2 and NH3, respectively. In addition to the current efforts on SO2 and NOx controls, further measures are needed to control NH3 and VOCs emissions over a larger area for PRD to effectively improve the air quality.

The trends and variability of atmospheric nitrogen deposition in the Pearl River Delta (PRD) region for the period 2008-2017 were investigated by integrating ground- and satellite-based observations and a chemical transport model, in order to gauge the effects of emission reductions and meteorological variability. We show that dry deposition observation of oxidized nitrogen decreased at the rate of 2.4% yr-1 for a moderate reduction in NOx emissions by 27% in the past decade, while reduced nitrogen presented an increase at the rate of 2.3% yr-1 despite no regulated interventions for NH3 emissions, which is likely related to changes in atmospheric gas-particle partitioning of NH3 as reductions in SO2 and NOx emissions. These results coincide with the trends in ground-level concentrations of oxidized and reduced nitrogen compounds in the atmosphere during 2008-2017. The changes in annual deposition fluxes of total oxidized and reduced nitrogen are not statistically significant trends and largely related with the inter-annual variability in their corresponding wet depositions, which reflects combined effects of variability in precipitation amount, and changes in atmospheric nitrogen compounds which dominates wet deposition of the oxidized and reduced forms. The meteorological conditions can mask 34% and 25% decrease in total oxidized and reduced nitrogen deposition on the decadal timescale, respectively. We conclude that meteorology-driven variability probably have masked the full response of oxidized nitrogen deposition to NOx emissions reduction. Our results also imply that persistent and integrated emission control strategies on NOx and NH3 are needed to effectively reduce total nitrogen deposition fluxes towards the critical limit in the PRD region.

The temporal and spatial patterns of nitrogen wet deposition were investigated in the Pearl River Delta (PRD) under different weather types. The study was carried out in 27 monitoring sites with reliable meteorological data from 2010 to 2017. Large spatial variation data showed that both annual volume weighted mean (VWM) concentrations and fluxes were higher in the central PRD while lower in the outer area. The annual mean concentrations and fluxes were in the range of 0.8–1.3 mg N L−1 and 10.9–20.6 kg N ha−1 yr−1, respectively. The monthly mean concentrations and fluxes ranged from 0.1 to 0.2 mg N L−1 and 0.4 to 2.4 kg N ha−1, respectively. Further the study data revealed that the ratio of NH4+/NO3− was 1.1 which was much lower than the ratio reported in other regions like Northern China, Sichuan Basin, the US and Europe. The flux of NH4+ in urban sites was comparable to rural sites, implying that potential non-agricultural NH3 emissions were likely to be high in the PRD. The top three weather types were E, C and SE, with the total contribution of more than a half to the flux. Multiple linear regression was used to set up an equation to predict the variation of annual fluxes under the changes in weather conditions. The result hints that the variation on annual fluxes in the PRD tends to be stable in the next 30 years. Considering the increasing impact on the ecosystem, more effort should be exerted to reduce nitrogen wet deposition in the future.

Aerosol acidity is of great interest due to its effects on atmospheric chemical processes and impact on human health; however, the driving factors of aerosol acidity have only been scarcely investigated. This study characterized the aerosol acidity during the wet and dry seasons in Guangzhou, China, and systematically analyzed the seasonal variation and the corresponding driving factors of aerosol acidity followed by the discussion of their impact on gas-aerosol partitioning of NH3 and HNO3. It was demonstrated that the pH of PM2.5 was 0.08 unit lower (more acidic) during wet season than during the dry season and the aerosol acidity varied less in South China than that in North China. Additionally, our results showed that the meteorological parameters including temperature and relative humidity have larger effect on aerosol pH variation than chemical species. Particularly, the lower temperature during dry season had the positive influence (0.38 pH unit) on aerosol pH compared to the wet season; however, the negative effect due to relative humidity (RH) and chemical species resulted in a smaller seasonal variation of aerosol pH between these two seasons. The sensitivity analysis showed that the increase of temperature has negative impact (reducing pH) on aerosol pH with an almost linear relationship, while RH and chemical species represented a two-phase linear and nonlinear effect, respectively. Finally, the calculation of gas-aerosol partitioning indicated that the temperature had the largest influence on the seasonal variation of gas-aerosol partitioning for both HNO3 and NH3 followed by liquid water content and non-ideality, while aerosol acidity imposed the lowest impact, which suggests that all the parameters including meteorological and chemical species should be comprehensively evaluated to devise a PM2.5 control strategy.

The spatial-temporal pattern of N deposition has an important ecological impact on terrestrial ecosystems, providing a scientific background for the study of global changes. Based on the analysis method of spatial ellipse, we establish the standard deviation ellipse (SDE) center migration method to quantify the transport of regional deposition, and discuss the uncertainty of this method, which proves the feasibility of this method in characterizing the regional transport of nitrogen deposition. In October 2015, about 70% of the local emissions from the three regions in the Beijing-Tianjin-Hebei (BTH) region, the Yangtze River Delta (YRD) region and the Pearl River Delta (PRD) region are deposited to the ground (about 30% are located within the region and 40% are outside the region). The results show that native nitrogen from anthropogenic emissions in BTH area migrates to the southeast while there is a southwest migration relative to emission area in the YRD and PRD region. Compared with reduced nitrogen, oxidized nitrogen is more susceptible to transport. This phenomenon is mainly related to the strong atmospheric reactivity of ammonia in the atmosphere. The transport distance of nitrogen deposition in different areas is the BTH>YRD>PRD. The transmission impact from the BTH region is relatively bigger. It is pointed out that more attention should be paid to the control of oxidized nitrogen emerging from nitrogen deposition on the transport of external areas in China's core urban agglomeration. The government and relevant departments need to formulate corresponding measures to smooth the current situation of air pollution in China.

Southern China has experienced severe photochemical pollution events in recent years, and the tropospheric ozone has emerged as the major pollutant of concern. Despite some recent efforts, the role of natural factors in constraining long-term trends of ozone in this region is poorly understood. In this study, we addressed this issue using tropospheric column ozone (TCO) datasets (2005–2017) from the Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) and surface ozone datasets from 16 monitoring stations in Southern China (2006–2016). Consequently, we studied the influence of atmospheric dynamical factors, such as solar cycle, El-Nino Southern Oscillation (ENSO), Quasi-Biennial Oscillation (QBO), and Arctic Oscillation (AO), and local-scale meteorological factors, such as precipitation, surface temperature, planetary boundary layer height, and horizontal winds, on regional ozone trends. Stepwise multivariate regression analysis and harmonic function fitting were adopted to quantitatively simulate the influence of these natural drivers on ozone change. We found that within our research periods, both surface ozone and TCO in Southern China had a significant upward trend, with slopes of 0.97% y−1 (0.23 ppbv y−1) and 0.82% y−1 (0.28 DU y−1), respectively. Natural factors explained 44.4% of the TCO uptrend and 27.0% of the surface ozone uptrend. Among the natural factors, the solar cycle plays the most important role in tropospheric and surface ozone modulation. Its 11-year cycle had a large impact on TCO for 2–7 DU and on surface ozone for 3–8 ppbv. However, the ENSO, QBO, and AO indices did not affect tropospheric ozone trends significantly. In addition, we showed that precipitation and wind fields associated with the Asian summer monsoon played a critical role in lowering ozone levels over Southern China, accounting for 24.8% and 81.5% of summertime TCO and surface ozone variability, respectively. Finally, a significant fraction of TCO and surface ozone uptrends (55.6% and 73.0%, respectively) remained unexplained even after consideration of these natural factors in the periods 2005–2017 and 2006–2016, respectively. These unexplained factors are most likely related to anthropogenic emissions and should be studied further.

The atmospheric deposition of heavy metals poses serious risks to the ecological system and human health. To advance our knowledge of atmospheric dry/wet heavy metal deposition in the PRD region, monthly fluxes were examined based on soluble/insoluble fractions of five heavy metal elements (Cu, Pb, Cd, Cr and Zn) in samples collected from January 2014 to December 2015 at Guangzhou (urban) and Dinghushan (suburban) sites. The ratios of wet/dry deposition fluxes indicated that heavy metal deposition was governed by wet deposition rather than dry deposition in the PRD region. Affected by the shifting of the Asian monsoon, wet deposition fluxes exhibited significant seasonal variation between summer monsoon seasons (April to September) and winter monsoon seasons (October to February) in this region. Cd was classified as an extremely strong potential ecological risk based on solubility and the Hakanson ecological risk index. Source contributions to wet deposition were calculated by PMF, suggesting that dust, biomass burning, industries, vehicles, long-range transport and marine aerosol sources in Guangzhou, and Zn fertilizers, marine aerosol sources, agriculture, incense burning, biomass burning, vehicles and the ceramics industry in Dinghushan, were the potential sources of heavy metals.

Lead, a ubiquitous pollutant throughout the environment, is confirmed to be neurotoxic for children by pulmonary and oral routes. As preschool children in China continue to be exposed to lead, we analyzed the available biomonitoring data for preschool children in urban China collected in the period 2004-2014 through a literature review. To identify apportionment of lead exposure sources for urban children in China, we modified the IEUBK model with a Monte Carlo module to assess the uncertainty and variability of the model output based on limited available exposure data and compared the simulated blood lead levels with the observed ones obtained through literature review. Although children's blood lead levels in urban China decreased statistically over time for the included studies, changes in blood lead levels in three economic zones and seven age groups except for two age-specific groups were no longer significant. The GM-predicted BLLs and the GM-observed BLLs agreed within 1μg/dL for all fourteen cities. The 95% CIs for the predicted GMs and the observed distribution (GM±GSD) overlapped substantially. These results demonstrated the plausibility of blood lead prediction provided by the adapted IEUBK model. Lead exposure estimates for diet, soil/dust, air, and drinking water were 12.01±6.27μg/day, 2.69±0.89μg/day, 0.20±0.15μg/day, and 0.029±0.012μg/day, respectively. These findings showed that the reduction of lead concentrations in grains and vegetables would be beneficial to limit the risk of dietary lead exposure for a large proportion of preschool children in urban China.

An extensive soil survey was conducted to study pollution sources and delineate contamination of heavy metals in one of the metalliferous industrial bases, in the karst areas of southwest China. A total of 597 topsoil samples were collected and the concentrations of five heavy metals, namely Cd, As (metalloid), Pb, Hg and Cr were analyzed. Stochastic models including a conditional inference tree (CIT) and a finite mixture distribution model (FMDM) were applied to identify the sources and partition the contribution from natural and anthropogenic sources for heavy metal in topsoils of the study area. Regression trees for Cd, As, Pb and Hg were proved to depend mostly on indicators of anthropogenic activities such as industrial type and distance from urban area, while the regression tree for Cr was found to be mainly influenced by the geogenic characteristics. The FMDM analysis showed that the geometric means of modeled background values for Cd, As, Pb, Hg and Cr were close to their background values previously reported in the study area, while the contamination of Cd and Hg were widespread in the study area, imposing potentially detrimental effects on organisms through the food chain. Finally, the probabilities of single and multiple heavy metals exceeding the threshold values derived from the FMDM were estimated using indicator kriging (IK) and multivariate indicator kriging (MVIK). The high probabilities exceeding the thresholds of heavy metals were associated with metalliferous production and atmospheric deposition of heavy metals transported from the urban and industrial areas. Geostatistics coupled with stochastic models provide an effective way to delineate multiple heavy metal pollution to facilitate improved environmental management.

Eutrophication of lakes and reservoirs has become a worldwide environmental problem, and nitrogen (N) has been recognized as one of the key factors responsible for eutrophication. Nitrogen adsorbed on sediments may be released via chemical and biological processes under changing environmental conditions. Spatial distributions of concentrations of ammonia nitrogen (NH4 +–N), nitrate nitrogen (NO3 −–N) and total nitrogen (TN) were investigated in sediments and overlying water of Dongting Lake, the second largest freshwater lake in China. The concentration of TN in the sediments exhibited strong spatial variation with relatively high values in the eastern part and relatively low values in the southern part of the lake. The TN concentration in the water of different regions of Dongting Lake was affected by the internal load of sediment N. The vertical distribution of TN in sediment cores showed a decreasing trend with an increase in depth. Concentrations of NH4 +–N in the sediment cores decreased with the depth increase until 6–8 cm and then increased slowly. However, concentrations of NO3 −–N in the sediment cores showed an opposite trend from those of NH4 +–N. A kinetic release experiment of NH4 +–N showed that the maximum release rate occurred in the first 5 min and the amount of NH4 +–N release reached 77.93–86.34 % of the total amount in 0–10 min. The release of NH4 +–N in the surface sediments of Dongting Lake fits a first-order kinetics function.

Air pollution is an important public health problem in Europe and there is evidence that it exacerbates health inequities. This calls for effective strategies and targeted interventions. In this study, we conducted a systematic review to evaluate the effectiveness of strategies relating to air pollution control on public health and health equity in Europe. Three databases, Web of Science, PubMed, and Trials Register of Promoting Health Interventions (TRoPHI), were searched for scientific publications investigating the effectiveness of strategies on outdoor air pollution control, public health and health equity in Europe from 1995 to 2015. A total of 15 scientific papers were included in the review after screening 1626 articles. Four groups of strategy types, namely, general regulations on air quality control, road traffic related emission control interventions, energy generation related emission control interventions and greenhouse gas emission control interventions for climate change mitigation were identified. All of the strategies reviewed reported some improvement in air quality and subsequently in public health. The reduction of the air pollutant concentrations and the reported subsequent health benefits were more significant within the geographic areas affected by traffic related interventions. Among the various traffic related interventions, low emission zones appeared to be more effective in reducing ambient nitrogen dioxide (NO₂) and particulate matter levels. Only few studies considered implications for health equity, three out of 15, and no consistent results were found indicating that these strategies could reduce health inequity associated with air pollution. Particulate matter (particularly fine particulate matter) and NO₂ were the dominant outdoor air pollutants examined in the studies in Europe in recent years. Health benefits were gained either as a direct, intended objective or as a co-benefit from all of the strategies examined, but no consistent impact on health equity from the strategies was found. The strategy types aiming to control air pollution in Europe and the health impact assessment methodology were also discussed in this review.

Objects: In order to understand the lead concentration and distribution characteristics in the foods and daily intake of residents by diet in China, we collected the literatures published in last d...

The city of Jinan is the capital of Shandong province. The southern mountain of Jinan is a sensitive region of soil erosion. Severe soil erosion not only destroys the ecosystem environment roughly, affects the economic and social sustainable development, but also endangers its spring. Therefore, the assessment of soil erosion, as the basis of the comprehensive control and use planning on Jinan, must be done actively. But till now, there has been no unanimous conclusion on the quantitative assessment indexes and their thresholds for the small watershed on Jinan. The study area is the city of Jinan. With the principles of combination of qualitative and quantitative analysis, macroscopic and microscopic analysis, the assessment indexes of soil erosion are selected through a series processes such as analysis of relations between the influencing indexes and soil erosion. The soil erosion intensity of the whole watershed is assessed with the qualitative method of RS and GIS.

This paper presents an overview of agent-based models in land-use/cover change studies. This special class of LUCC models combines a cellular landscape model with agent-based representations of decision making, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors first explain the related concepts of agent based models. Then we briefly discuss recent studies that apply agent- based modeling to study land use/cover change for practical cases. Finally, we discuss limitations of agent-based methods in LUCC modeling. We find that agent-based models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers with the goal of creating fine-scale models of LUCC phenomena that focus on human-environment interactions.

In China, the protection of prime farmland is a national policy of eminent importance. From an analytical perspective, its central mission, designating qualified cultivated land as prime farmland, is a comprehensive multi-attribute ranking problem. The paper first analyzed the shortcomings of the existent methods, and then proposed a spatial clustering method for prime farmland designation. The main processes were as follows: (1) Building of index system of prime farmland delimiting; (2) Evaluation of index weights according to expert knowledge; (3) Partition of study area on account of the accuracy. Data of elliptical regions that was preprocessed was put into model of spatial clustering. (4) The land parcels in same cluster is combined into larger units, ranking the result units by holistic productivity level, and selecting the super units which meet the requirement of prime farmland, finally modulating the result according to the correlated policy. The final result can be acquired. Take Jiyang County, Shandong, as a study area, the research showed that the model of selecting cultivated land into prime farmland by GA-K means spatial clustering can effectively solve the existing problems. The prime farmlands were obviously more concentrative, the isolated land parcel fragments were removed effectively, and spatial gathering level was enhanced remarkably. All that makes it a scientifically sound and practically feasible tool to protect and manage prime farmland, and monitor the prime farmland, and realize the aim of scientific and scale management.

China has experienced a dramatic change in atmospheric reactive nitrogen (Nr) emissions over the past four decades. However, it remains unclear how nitrogen (N) deposition has responded to increases and/or decreases in Nr emissions. This study quantitatively assesses temporal and spatial variations in measurements of bulk and calculated dry N deposition in China from 1980 to 2018. A long-term database (1980–2018) shows that bulk N deposition peaked in around 2000, and had declined by 45% by 2016–2018. Recent bulk and dry N deposition (based on monitoring from 2011 to 2018) decreased from 2011 to 2018, with current average values of 19.4 ± 0.8 and 20.6 ± 0.4 kg N ha−1 yr−1, respectively. Oxidized N deposition, especially dry deposition, decreased after 2010 due to NOx emission controls. In contrast, reduced N deposition was approximately constant, with reductions in bulk NH4+-N deposition offset by a continuous increase in dry NH3 deposition. Elevated NH3 concentrations were found at nationwide monitoring sites even at urban sites, suggesting a strong influence of both agricultural and non-agricultural sources. Current emission controls are reducing Nr emissions and deposition but further mitigation measures are needed, especially of NH3, built on broader regional emission control strategies.