Journal of Environmental Management最新文献

Appropriate vegetation restoration measures are beneficial to ecosystem restoration and nutrient retention in ecologically fragile areas. However, the high water consumption of planted forests and the increasing frequency of drought events may reshape or complicate this ecological process. The effects of forest types and drought stress on nutrient limitation remain unclear. In this study, we selected five different vegetation restoration types on the Loess Plateau, China, and applied three drought levels to assess their effects on extracellular enzyme activity, soil microbial biomass, and soil nutrient limitations.We measured the activities of carbon-, nitrogen-, and phosphorus-acquiring enzymes and investigated the relationships among enzyme activity, microbial biomass, and nutrient limitations under drought conditions. Our results showed that vegetation types and drought significantly influenced soil enzymatic activity and stoichiometry. Mixed forests demonstrated higher enzyme activity and nutrient content compared to pure forests, indicating greater resilience under drought conditions. Short-term drought significantly reduced soil enzyme activity and microbial biomass, whereas mild drought stimulated enzyme activity, and moderate drought promoted microbial biomass. Drought markedly decreased microbial carbon and nitrogen content but increased the microbial carbon-to-nitrogen ratio. Furthermore, drought enhanced the correlation between microbial biomass carbon and carbon-acquiring enzymes, but there was no correlation between microbial biomass nitrogen and nitrogen-acquiring enzymes under drought. All vegetation types exhibited nitrogen limitation, and a negative correlation was observed between nitrogen and carbon limitations under drought conditions. Drought significantly exacerbated nitrogen limitation, while its impact on carbon limitation varied with drought severity and vegetation type. Overall, plant communities exhibited distinct nutrient acquisition strategies under drought stress, resulting in complex changes in soil enzyme activities and microbial biomass. This study advances our understanding of microbial nutrient limitations and enzymatic activities under varying vegetation restoration patterns and drought conditions, providing critical insights for enhancing soil resilience and nutrient cycling under climate change.

In the management of reservoirs, different forms of infrastructure (such as dams, hydropower units, information) are functionally interdependent and often managed by different types of actors to form a social-ecological-technological system. Such interdependence also occurs because institutions (understood as rules that guide and constrain actor behavior) exist to indicate how infrastructures should be managed. We apply institutional analysis and social network analysis to identify how functionally interdependent infrastructures and actors are connected by formal rules created to manage reservoir operations in Argentina (Ameghino Dam, Chubut) and the United States (Coyote Valley Dam, California). Using Exponential Random Graph Models and motif analysis we develop and test hypotheses about which types of patterns of rule-mediated interdependence are more likely to occur in the management of reservoir operations as well as how contextual features, such as the socio-political environment and the types of actors involved, influence rule-mediated interdependence in social-ecological-technological systems. We find that the type of actors involved and the socio-political context in which rules are designed shape the patterns of rule-mediated interdependencies. These findings shed light on and call for more attention to the role that formal rules play in shaping infrastructure management across socio-political contexts.

Reducing enteric methane emissions from livestock is a key environmental challenge, as methane is a major pollutant. The complexity of animal biology and diverse diet compositions make it difficult to develop strategy to control methane production. This study examined the use of plant phenolic extracts of Madhuca longifolia (ML-7) as a feed additive combined with various ruminant diets and dosages to find an effective supplement to reduce methane emissions. Seven feeds were assessed: two dry forages (wheat and oat straw), two green fodders (berseem and napier), and three mixed diets formulated with straw bases: wheat (Diet-1), oat (Diet-2) and sorghum (Diet-3), each combined with berseem and concentrate in a 2:1:1 ratio. The nutritive value of each feed was assessed, followed by measuring total gas, methane and in vitro fermentation after supplementing all feeds with ML-7 at different levels (0, 0.2, 0.6 and 1.0%). Diet-3 had the highest (18.98 Mj kg^-1) gross energy while oat straw had the lowest (18.25 Mj kg^-1). Berseem had the best nutritional profile. Supplementing feeds with ML-7 extract significantly reduced total gas and methane production across the tested feeds. However, DMD declined significantly in diet-3 and napier grass. ML-7 had no effect on short-chain fatty acid production in the tested diets, although SCFA production decreased significantly with 1.0% ML-7 supplementation in dry and green fodder. The methane reduction pattern was diet-1 > napier > berseem, diet-2, diet-3, wheat straw, and oat straw. Total volatile fatty acids decreased most in diet-3, followed by diet-2, diet-1, napier, berseem, and other dry roughages. ML-7 supplementation had minimal impact on total protozoa populations but significantly reduced holotrichs. Supplementing ML-7 extract to feeds at 0.6-1.0% levels shows potential for reducing methane emissions in ruminants without disrupting rumen fermentation, promoting sustainable livestock production and a climate-friendly environment by reducing methane emissions.

China is concurrently facing the dual challenges of air pollution and climate change. Here, we established a coupled modeling framework that integrated a chemical transport model with a health impact assessment model and the human capital method, to quantify the contributions of 150 emission sources (five sectors in 30 provinces) to the CO₂ emissions, and the mortality burdens attributed to O₃ and PM_2.5. We found that, in 2019, the estimated premature deaths in China attributed to PM_2.5 and O₃ pollution were 1,499,073 and 143,420, respectively. The social cost of air pollution was approximately 232 billion USD (PM_2.5: 212 billion USD, O₃: 20 billion USD), comparable to the social cost of CO₂ emissions at 246 billion USD. The social costs of air pollution and carbon emissions attributable to the 150 emission sources exhibited significant heterogeneity. We identified the control priorities and primary control targets for each emission source. Consequently, based on the social costs of air pollution and climate impact, we proposed a synergistic emission control policy that accounted for spatial distribution and sectoral categories. This policy aimed to harmonize the control strategies for PM_2.5 pollution, O₃ pollution, and CO₂ emissions, thereby enhancing the comprehensive benefits of mitigation measures. Our study sheds light on optimizing emission control policies, enhancing the realism of relevant policy-making for synergistic control of air pollution and carbon emissions.

Molybdenum (Mo) is an essential micronutrient for plants, yet it also poses potential environmental risks when present in excess. This study investigated the Mo speciation in soils with varying properties and their influences on Mo uptake by wheat (Triticum aestivum L.), a staple crop with significant implications for global food security. Mo K-edge X-ray absorption spectroscopy (XAS), combined with a sequential extraction method, was employed to analyze the chemical speciation and fractionation of Mo in the soils before and after wheat cultivation. The predominant Mo species identified were sorbed molybdate (Mo(VI)) and Ca- and Fe-Mo(VI) precipitates. After wheat cultivation, sorbed Mo(VI) and Ca-Mo(VI) decreased while Fe-Mo(VI) increased, with the most notable changes observed in the alkaline soil. These changes indicated that the desorption of sorbed Mo(VI) and dissolution of Ca-Mo(VI) contributed to soil Mo availability, while Fe-Mo(VI) precipitation restricted it. Bioaccumulation and translocation factors revealed efficient Mo uptake and transport within wheat plants, with shoots being the primary site of Mo accumulation. Elevated Mo concentrations in wheat grains raise potential human health concerns due to dietary exposure. These findings underscore the critical role of soil Mo speciation in controlling Mo dynamics in soil-wheat systems, providing valuable insights for managing Mo in agricultural soils to balance its nutritional benefits with the risks of excessive crop accumulation.

In farmland shelterbelt systems, the decomposition and/or apoptosis of forest fine root litter could affect farmland soil properties at the tree-crop interface, particularly the soil nitrogen (N) cycling. However, how fine root litter affect the ammonia (NH₃) and nitrous oxide (N₂O) losses from farmland soil and the crop production is little known. A soil column experiment covering a whole rice season was conducted to evaluate the dynamics aforesaid in response to fine root litter of Populus (RP) and Metasequoia glyptostroboides (RM) with 0 and 240 kg ha^-1 N fertilizer input. Both RP and RM had minimal impact on NH₃ and N₂O emissions from soils without N input. At 240 kg N ha^-1 input, RP significantly (p < 0.05) increased total NH₃ volatilization (including yield-scaled NH₃ volatilization and emission factor) by 37.1%, while RM significantly (p < 0.05) decreased it by 18.1%. Both fine root litter significantly (p < 0.05) reduced the N₂O emissions from paddy soil receiving 240 kg N ha^-1 by 22.7-27.1%. The reduction of N₂O emission in N240 + RM was primarily attributed to higher topsoil ammonium-N but lower nitrate-N contents that indicating a reduced nitrification rate during the mid-season drainage stage. In addition, the decreases in soil AOA amoA (-39.4%) and nirS (-23.7%) gene copies explained the mitigating effect of RP on N₂O emission. Regardless of N fertilizer application or not, there was no statistically significant difference in rice grain yield between treatments with and without fine root litter, although RM reduced grain yield by 11.2-14.9% compared to treatments without fine root litter. In conclusion, the impact of fine root litter on N emissions via NH₃ and N₂O depends on both N input rates and fine root types. RM simultaneously reduce reactive farmland soil N losses via NH₃ and N₂O in the tree-crop interface soils with N input.

Some research has studied the carbon footprints of the multinational enterprises (MNEs) in the global value chains (GVCs). However, currently there are few studies have studied the carbon footprints of the foreign invested firms (FIFs) distributed in different provinces in China's domestic value chains (DVCs). This paper has used China's inter-provincial input-output table distinguishing domestically owned enterprises (DEs), Hong Kong, Macao, and Taiwan (HMTs) invested enterprises and other foreign invested enterprises (FIEs) to study the carbon footprints of the FIFs in China's DVCs and further analyzed the driving factors of the carbon footprints change. The results show that: (1) In 2017, more than two-thirds of the carbon footprints came from FIEs and this proportion had decreased 5.6% compared with 2012. The FIFs located in coastal provinces or economically developed areas basically have the largest carbon footprints. (2) The production activity of the FIFs located in some developed provinces has mostly driven the carbon emissions of other provinces that have direct or indirect trade with them. While in some less affluent energy provinces, it has mainly driven the carbon emissions of the local DEs. (3) The biggest driving factor for reducing the carbon footprints of the FIFs is the carbon emissions intensity of the DEs, followed by the input-output relationship between DEs and FIFs. The final product production of the HMTs is the largest driving factor that promoting the increase of the FIFs' carbon footprints, followed by the final product production of the FIEs. However, different driving factors have different contributions in different provinces. The research results of this article have important research significance for reasonably introducing foreign investment and promoting the reduction of the FIFs' carbon footprints in various provinces in China.

Achieving the national climate target would depend on national actions. China has implemented important market mechanisms for a green and low-carbon energy transition, including the Renewable Portfolio Standard (RPS), the Tradable Green Certificate (TGC) market, the green power trading market, and so on. However, how to effectively integrate coupled TGC and green power trading to achieve a balance between maximizing economic benefits and environmental friendliness remains to be explored. Therefore, this study extends prior research by establishing a bi-level decision optimization model to explore market participants' decision making from the perspective of energy supply and economic value, and analyzes the impact of the RPS, TGC price, and the penetration of renewable energy (RE) in the electricity market, the green power market, and the trading strategy of market participants in a multi-market equilibrium state. The feasibility and effectiveness of the bi-level decision optimization model and algorithm are verified using the example of IEEE14 node and historical data of Elia Energy. The results show that: (1) Under the market equilibrium condition, the clearing price in the day-ahead RE market is equal to the clearing price in the day-ahead traditional energy market plus the TGC price. (2) When green power participates in the spot market, there is a complementary relationship between RE generation and traditional energy generation. (3) A shift from decreasing to increasing costs for electricity consumers when RE penetration is above a certain threshold (α>30%) and the TGC price is 100 CNY/MWh, and a decrease in the growth rate of RE generators' profits when RE penetration is above a certain threshold (α>35%). (4) Traditional energy generators with small installed capacities adopt riskier market behaviors to declare more electricity and try to obtain higher profit in market transactions. These insights can make up for the research gap of decision optimization in multi-timescale electricity market, achieve energy optimization allocation and environmental sustainability.

PM_2.5 is an important environmental risk factor for cardiovascular disease (CVD) and poses a threat to global health. This study combines bibliometric analysis, Mendelian randomization (MR), and Global Burden of Disease (GBD) data to comprehensively explore the relationship between PM_2.5 exposure and CVD. MR analyses provided strong evidence for causality, reinforcing findings from traditional observational studies. The estimated global burden of PM_2.5-related CVD indicated, that there exist significant impacts on the elderly, men, and populations in low and medium socio-demographic index (SDI) areas. This study further found that population growth and aging are the main drivers of this burden with large inequities, although medical advances have mitigated some of the effects. Overall, the opportunity to reduce the burden of CVD remains significant, particularly in medium SDI countries. Projections to 2045 suggested that the absolute burden will increase, while age-standardized rates will decline due to improvements in air quality and health care. These findings emphasized the urgent need for targeted interventions to mitigate the deleterious effects of PM_2.5 on global cardiovascular health and to address health inequalities between regions.

As the economy enters the "new normal" and the upgrading of consumption structure enters a critical period of acceleration, under the dual background of accelerating the upgrading of consumption structure and realizing carbon peaking and carbon neutrality goals, it is of great significance to explore the impacts of the upgrading of consumption structure on the carbon emissions of households and the internal mechanism, so as to clarify how to promote the carbon emission reduction of households from the consumption side. This study calculates the household carbon emissions of 10 provinces and 1 municipality in the Yangtze River Economic Belt from 2012 to 2021 from direct and indirect perspectives. Using panel data, a fixed effect and mediating effect model is constructed to explore the mechanism of consumption structure upgrading affecting household carbon emissions. The spatial and temporal evolution characteristics of household carbon emissions are further analyzed, and the spatial Dubin model is constructed to study the spatial spillover effect of consumption structure upgrading on household carbon emissions. The results show that: (1) The upgrading of consumption structure is conducive to reducing household carbon emissions and passes the robustness test. (2) According to the mediating effect analysis, the upgrading of consumption structure reduces household carbon emissions by promoting technological innovation, effectively improving energy efficiency. (3) There is a significant negative spatial spillover effect on household carbon emissions. The upgrading of consumption structure can not only reduce household carbon emissions in the region, but also have a significant inhibitory effect on household carbon emissions in the surrounding areas. In order to reduce household carbon emissions, this study proposes policies to promote upgrading of consumption structure and technological innovation in accordance with local conditions, which will serve as a reference for policy makers and contribute to the accounting and monitoring system of household carbon emissions, which will help to realize China's "dual-carbon goal".