Journal of Environmental Management最新文献

The water rights reform (WRR) is an important way to achieve market-oriented allocation of water resources. This article uses city-level panel data to analyze the economic effects of WRR in China. The results show that the WRR can increase overall value added by 4.40%. However, the average impact of WRR on agricultural value added is not significant, but it can significantly increase non-agricultural value added by 3.83%. Heterogeneity analysis shows that the WRR in cities with water rights conversion experience or in provincial capital or sub-provincial cities will have a smaller promotion effect on the overall economy than in other cities; in places with lower total water resources, the WRR will have a greater promoting effect on the overall economy. In areas where the total amount of water resources or sown area is small, the WRR can also promote the added value of agriculture. Cities participating in water rights conversion will achieve lower non-agricultural economic effects after the WRR, but in areas with higher population density, the non-agricultural economic effects the WRR can achieve will be greater. Further analysis shows that the WRR can promote the increase in the proportion of non-agricultural value added, and the increase in non-agricultural value added mainly comes from the industrial sector. Furthermore, the WRR does not threaten food security.

The primary approach to assessing monitored natural attenuation (MNA) is currently based on a conceptual model utilizing the total contaminant concentrations, assuming a single aqueous species. However, many contaminants, such as metals and radionuclide - including iodine, can exist in multiple species that behave chemically differently in the environment and can exist simultaneously. For example, radioiodine often occurs concurrently as three major aqueous species: iodide (I^-), iodate (IO₃^-), and organo-I, which undergo distinct attenuation pathways and exhibit markedly different mobility and geochemical behavior. Here, current literature is reviewed with the objective to: 1) demonstrate differences in iodine species' geochemical behavior and natural attenuation mechanisms; 2) show that a species-specific (or multi-species) approach provides greater details on contaminant migration and attenuation; and (3) discuss the logistics of a species-specific approach to developing conceptual models for assessing overall contaminant mobility. The species-specific approach results in a more accurate assessment of mass flux and maximum groundwater concentrations; and, therefore, a more defensible risk evaluation to support short- or long-term remediation and/or natural attenuation strategies. Although iodine is the focus of this paper, this methodology could be applied to other risk-driving contaminants such as mercury and uranium, which have even more complex aqueous speciation than iodine, or technetium and chromium, which have complex solid phase speciation and natural attenuation reaction networks. Accounting for species-specific geochemical behavior, while implementing MNA strategies can greatly reduce uncertainty, and, therefore, remedial costs required to ultimately achieve remediation regulatory objectives.

Biocrusts are the primary organic carbon reservoirs in desert areas, in which inorganic clays potentially playing significant roles; however, the specific details of these roles remain largely unclear. In this study, typical 1:1 type (kaolin) and 2:1 type (montmorillonite, MMT) clay minerals were added to artificial biocrusts to investigate their effect on the acquisition performance of soil organic carbon (SOC). After 84 days of cultivation, the enhancement effects of kaolin and MMT were significant, resulting in SOC increments that were 5.03 times and 4.08 times higher than those of the Algae group (without clay). Notably, the two types of clay exhibited different advantages in SOC accumulation. Due to its larger external specific surface area and higher cation exchange capacity, MMT contributes more effectively to SOC stability. Specifically, the mineralization quotient (qM), hot-water extractable organic carbon (HWEOC), and molecular structural stability of SOC in the MMT group were 0.3, 0.34, and 1.31 times those of the Algae group, respectively. In contrast, kaolin was more favorable for microbial growth and SOC formation due to its higher dissolved organic carbon (DOC) content. Microbial biomass carbon (MBC), chlorophyll-a (Chl-a), photosynthetic performance index (PI_ABS), and Shannon index in the kaolin group were 5.67, 2.44, 11.95, and 1.82 times those of the Algae group, respectively. These findings highlighted the synergistic effect for SOC accumulation of clay and cyanobacteria in artificial biocrust systems, clarified the specific roles of two typical clay minerals, and offered new insights for accelerating the restoration of nutrient-limited areas such as deserts.

Inland river runoff variability is pivotal for maintaining regional ecological stability. Daily flow forecasting in arid regions is crucial in understanding water body ecological processes and promoting healthy river ecology. Precise daily runoff forecasting serves as a cornerstone for ecological evaluation, management, and decision-making. With the advancement of artificial intelligence technology, data-driven models have exhibited promising capabilities in runoff prediction. Nevertheless, the arbitrary selection of boundaries between different flow patterns without considering temporal changes across seasons limits the accuracy of runoff simulation. This paper proposed an integrated modeling approach encompassing a dynamic classification method, an attention mechanism, and a bidirectional long short-term memory network (CA-BiLSTM) to enhance flow prediction performance while accommodating diverse flow patterns. The classification boundary was determined by the dynamic change interval value of relevant hydrological variables, facilitating a more comprehensive exploration of the relationships and information within hydrological data. The performance of the CA-BiLSTM model was compared against a traditional machine learning model lacking data classification, utilizing data from the West Bridge station of the Aksu River Basin (ARB). The results indicate that the CA-BiLSTM model outperforms traditional LSTM and BiLSTM models across all seasons. The CA-BiLSTM model demonstrates superior performance in arid zones. Compared to the single LSTM model, CA-BiLSTM exhibits reductions of 42.99%, 36.89%, and 49.73% in MAE, RMSE, and MAPE, respectively, while enhancing R² and KGE by 10.47% and 11.76%. The proposed hybrid model effectively reduces runoff prediction uncertainty, offering valuable insights for water resource management in arid zones.

Communities of arbuscular mycorrhizal fungi (AMF) in soil are influenced by various agricultural managements, which in turn affects crop productivity. However, the impacts of straw returning on AMF communities are sparsely understood. Here, a 7-year field experiment including three sets of straw managements - returning methods (CK: no-tillage without straw; RT-SR: rotary tillage with straw; DB-SR: ditch-buried tillage with straw), burial amount, burial depth - were applied to evaluate the influences of straw managements on AMF composition. With full amounts of straw return, AMF diversity was similar between DB-SR and CK at a depth of 20 cm, whilst it was 13% higher than that under RT-SR. This could be explained by the increased rhizodeposition under DB-SR may counterbalance the negative effect of tillage under RT-SR on AMF hyphal growth. DB-SR changed AMF composition and enhanced the abundance of Glomeraceae, as well as the amount of glomalin-related protein, as a consequence increased plant P uptake by 68% than RT-SR. DB-SR remained stable plant P uptake and wheat biomass at a burial depth of 40 cm, but it decreased AMF diversity and the abundance of Glomeraceae as compared to DB-SR at a burial of 20 cm. This indicated DB-SR at a burial depth of 40 cm may be not beneficial to crop growth. Our results suggest that ditch-buried straw return with a depth of 20 cm and full amounts of straws is promising to improve soil health (via regulating AMF community diversity and composition) and promote crop production (via increasing plant P uptake).

Globally, there are more than 17,000 cargo-handling ports that are expected to double in capacity by 2030. Overwater structures are common in ports and create permanently shaded environments that can produce ecological shifts from primary-producer to consumer dominated communities. Yet, the extent of these structures across ports and their impact on light conditions and associated communities in different areas beneath has not been quantified. Here we quantified the spatial extent of overwater structures in 17 major global ports and found a total estimated area of >13.96 km² of seabed to be shaded. We then surveyed in situ overwater structures in Sydney Harbour, Australia, to directly measure the impacts of these structures on light intensity and marine communities. We show that overwater structures can reduce light levels between 37 and 83% and shift ecological communities from mixed algal-invertebrate communities towards invertebrate dominance. This study provides critical evidence of the impacts of port structures on natural light regimes and ecological communities, and highlights the need for sustainable solutions (e.g. light penetrating surfaces, artificial light) to restore natural light regimes to global ports to maintain algal communities and associated ecosystem services in areas that are shaded by overwater structures.

Honey bees (Apis mellifera) play an important role in our agricultural systems. In recent years, beekeepers have reported high colony mortality rates in several parts of the world. Inadequate foraging landscapes are often cited as a major factor deterring honey bee colony health. Few studies, if any, have yet used large-scale datasets to assess the quality of landscapes encountered in commercial pollination activities. Here, we coupled a unique dataset comprising georeferenced reports on 17,743 colonies in the province of Quebec, Canada, with data derived from satellite remote sensing, to compute landscape metrics at each visited location. We ran a Cox and a random survival forests (RSF) model with time-weighted features to predict the lifespan of colonies in various landscape scenarios. Survival estimates from our RSF model indicate that colonies foraging primarily in forested areas exhibit higher survival rates, whereas those in cranberry- and maize-dominated landscapes may face lower survival probabilities. Our findings suggest that vegetation abundance could play a significant role in shaping outcomes. Additionally, landscape diversity within a 1 km radius seems to have a positive effect, with potentially greater benefits in areas where vegetation is sparse. While topography contributes valuable predictive insights, its effects are complex and challenging to fully interpret.

The changes in lake ice phenology (LIP) can intuitively reflect the climate evolution in the regions where lakes are located, serving as an important indicator of climate change. The Tianshan Mountains, situated at the southern edge of freezing lakes in the Northern Hemisphere, are a crucial water resource base in Xinjiang and support significant ecosystems closely related to human activities. In the context of intensified climate change, this study focuses on the geographical location, altitude, and water quality differences among large lake groups in the mid-latitude region of Xinjiang, aiming to explore the characteristics of LIP changes in these lakes and their responses to driving factors, thereby providing a basis for effective environmental management and protection. This research conducts a comparative analysis of the LIP changes and driving factors of three large lakes-Sayram Lake (SL), Bosten Lake (BL), and Ebnur Lake (EL)-using multi-source remote sensing data to reveal the response and adaptation mechanisms of lakes under global warming. It effectively captures the time series variations of ice formation and melting, as well as the common responses to environmental and climatic factors. The results indicate that SL has experienced significant climate change effects, with earlier freezing times and accelerated melting speeds; In contrast, EL and BL have shown relatively minor changes, suggesting that geographical and hydrological factors may buffer the impacts of climate. The study finds that all three lakes are jointly influenced by environmental factors such as temperature, wind speed, and precipitation; however, due to differences in altitude, lake surface area, and water transparency, their responses to these climatic factors vary significantly. For instance, SL's high altitude gives water transparency a dominant role in LIP, while BL's larger surface area enhances the impact of precipitation and thermal capacity on the melting process. This indicates that, despite facing similar climate pressures, local environmental conditions can lead to different trends in ice phenology changes. This study offers a novel and efficient monitoring method for LIP, providing valuable insights for future LIP research and water resource management.

In the context of global sustainability goals, it is imperative to examine the interplay between emerging financial technologies and environmental objectives, which in turn offers insights into the implications of such technologies on sustainable investments and environmental policy decisions. Accordingly, this study investigates the influence of Bitcoin's energy consumption (BEC), as a representative of the cryptocurrency market, on the regional green economy indices of the United States, Europe, and Asia. Utilizing both unfiltered and filtered data, we conduct empirical analyses from both static and dynamic perspectives to account for the causal relationships that emerged during critical market developments, employing novel algorithms including forward recursive, rolling windows, and recursive rolling. The results reveal that energy-related developments play a dominant role in shaping the causal link between BEC and the green economy performance. More specifically, events such as the COVID-19 pandemic, the Russia-Ukraine war, and China's ban on cryptocurrency mining appear to significantly drive casual effects. After filtering out the impacts of global equity markets and information technology developments, we observe even more pronounced impacts on these causal relationships. Our findings highlight the need for coordinated global actions to address the energy consumption of the cryptocurrency market, facilitating the transition to global sustainability.

Mountain regions of Central Asia are experiencing strong influences from climate change, with significant reductions in snow cover and glacial reserves. A comprehensive assessment of the potential consequences under the worst-case climate scenario is vital for adaptation measures throughout the region. Water balance analysis in the Naryn River basin was conducted for the baseline period of 1981-2000 including potential changes under the worst-case SSP5-8.5 scenario for 2077-2096 by combining high-resolution (5 km) regional climate projections with fully distributed glacio-hydrological (1 km) modeling. Results showed that with the complete degradation of glaciers and increase in evapotranspiration, the overall runoff will decrease by 16%, and in the upper basins, the reduction will exceed 40%. The maximum snow water equivalent (SWE) is projected to decrease by 17%, and the seasonal peak of SWE will occur one month earlier. The transition from snow to rain will significantly affect lower regions, increasing extremes in peak runoff and causing 10-year recurrence interval events to occur every 3-4 years. Moreover, extreme runoff in high mountainous areas will increase due to intensified snowmelt and increased rainfall extremes. Additionally, a gradient of surface soil temperature change of 0.1 °C per 100 m elevation gain was observed, suggesting a potential snow-albedo feedback effect that could further amplify the warming, especially at higher altitudes. This study provides a robust analytical framework to assess the complex responses of mountain ecosystems to the impacts of climate change, with the potential of widespread application for addressing the challenges facing these critical regions.