ALBERT

Description: In the process of continuously advancing urbanization, the energy efficiency of the construction industry, as a pillar industry of the national economy, has attracted much attention. The imbalance of regional economic development, the difference of regional resource endowment, and the incomplete energy infrastructure in some areas lead to the prominent problem of energy poverty in China. Based on the panel data of 30 provinces and cities from 2008 to 2017, this paper calculates the energy poverty index and the energy efficiency of the construction industry. Using OLS, Tobit, Probit, and other estimation methods, this paper analyzes the internal relationship between energy poverty and the energy efficiency of the construction industry, the mediating role of energy consumption structure, and the moderating effect of technological level and marketization degree. The results show the following: There is a negative correlation between energy poverty and the energy efficiency of the construction industry (Husnain, ENERG POLICY, 2021, 157). The energy consumption structure plays a partial mediating role in the impact of energy poverty on the energy efficiency of the construction industry (Li, CHEM ENG J, 2021, 408). It means that energy poverty inhibits the optimization of the energy consumption structure, and through this process, it also inhibits the improvement of the energy efficiency of the construction industry. The technological level and the degree of marketization play a moderating role in the main effect, which can weaken and strengthen the negative impact of energy poverty on the energy efficiency of the construction industry (Gajdzik, ENERGIES, 2021, 14).

Description: Small-scale natural gas liquefaction processes have several clear advantages, particularly in the exploitation of ‘unconventional’ natural gas (NG) from sources such as difficult-to-access and offshore gas fields. Moreover, conventional liquefaction processes have a number of disadvantages such as high energy consumption, large cooling loads required in the refrigeration cycle, and non-uniform matching of cold and hot flows in liquified natural gas (LNG) heat exchanger (HE). The main objective of this study was to optimize the most commonly used mixed refrigerant process. The liquefaction performance of the optimized process was analyzed and the influence of gas parameters on the power consumption, exergy loss, freezing mixture circulation, and cooling water load were investigated. The results show that compressor power consumption can be reduced by 29.8%, the cooling water load can be reduced by 21.3%, and the system exergy efficiency can be increased by 41% with the optimized process. Furthermore, throttling and compression of the freezing mixture were increased during the refrigeration stage. It can be concluded that reducing the feed gas temperature and increasing the feed gas pressure can reduce the total power consumption, exergy loss, freezing mixture circulation, and cooling water load, which can significantly improve liquefaction performance.

Description: Secondary organic aerosols (SOA) play an important role in global climate change and air quality, and SOA tracers can directly characterize the source and reaction mechanism of SOA. However, it is not well known that whether the tracers can be oxidized or how the instability of the tracers in the atmosphere. In this paper, in-situ FTIR was used to analyze the chemical structure changes of erythritol, analogue of 2-methyl erythritol (AME) that is, a tracer of isoprene SOA, and 2, 3-dihydroxy-4-oxopentanoic acid (DHOPA), a tracer of toluene SOA, when exposed to high concentration of ozone for short periods. Under the condition of 20 ppm ozone exposure for 30 min, the change rate of absorption area of AME at 3,480 and 1700 cm−1 was −0.0134 and 0.00117 int.abs/s, respectively, and the change rate of the absorption area of DHOPA at 1,640 and 3340cm−1 was −0.00191 and 0.00218 int.abs/s, respectively. The pseudo-first-order reaction rate constant kapp were 1.89 × 10−8 and 2.12 × 10−7 s−1, and the uptake coefficients of ozone on the surface of AME and DHOPA were (1.3 ± 0.8) × 10−8 and (4.5 ± 2.7) × 10−8, respectively. These results showed the oxidation processes of AME and DHOPA were slow in the presence of high concentrations of ozone, which implied that AME and DHOPA could be considered to be stable in the atmospheric environment with ozone as the main oxidant.

Description: This study attempts to analyze the time-varying pattern between the exchange rates, stock market return, temperature, and number of confirmed COVID-19 cases in G7 countries caused by the COVID-19 pandemic. We have implemented our analysis using wavelet coherence and partial wavelet coherence (PWC) on independent variables from January 4, 2021 to July 31, 2021. This paper contributes to the earlier work on the same subject by employing wavelet coherence to analyze the effect of the sudden upsurge of the COVID-19 pandemic on exchange rates, stock market returns, and temperature to sustain and improve previous results regarding correlation analysis between the above-mentioned variables. We arrived at the following results: 1) temperature levels and confirmed COVID-19 cases are cyclical indicating daily temperatures have a material bearing on propagating the novel coronavirus in G7 nations; 2) noteworthy correlations at truncated frequencies show that a material long-term impact has been observed on exchange rates and stock market returns of G7 and confirmed COVID-19 cases; 3) accounting for impact of temperature and equity market returns, a more robust co-movement is observed between the exchange rate returns of the respective nations and the surge in COVID-19 cases; and 4) accounting for the influence of temperature and exchange rate returns and the increase in the confirmed number of coronavirus-infected cases and equity returns, co-movements are more pronounced. Besides academic contributions, this paper offers insight for policymakers and investment managers alike in their attempt to navigate the impediments created by the coronavirus in their already arduous task of shaping the economy and predicting stock market patterns.

Description: The present paper discusses families of Interior Penalty Discontinuous Galerkin (IP) methods for solving heterogeneous and anisotropic diffusion problems. Specifically, we focus on distinctive schemes, namely the Hybridized-, Embedded-, and Weighted-IP schemes, leading to final matrixes of different sizes and sparsities. Both the Hybridized- and Embedded-IP schemes are eligible for static condensation, and their degrees of freedom are distributed on the mesh skeleton. In contrast, the unknowns are located inside the mesh elements for the Weighted-IP variant. For a given mesh, it is well-known that the number of degrees of freedom related to the standard Discontinuous Galerkin methods increases more rapidly than those of the skeletal approaches (Hybridized- and Embedded-IP). We then quantify the impact of the static condensation procedure on the computational performances of the different IP classes in terms of robustness, accuracy, and CPU time. To this aim, numerical experiments are investigated by considering strong heterogeneities and anisotropies. We analyze the fixed error tolerance versus the run time and mesh size to guide our performance criterion. We also outlined some relationships between these Interior Penalty schemes. Eventually, we confirm the superiority of the Hybridized- and Embedded-IP schemes, regardless of the mesh, the polynomial degree, and the physical properties (homogeneous, heterogeneous, and/or anisotropic).

Description: Stand-alone hybrid energy systems are an enticing option for electrification in remote areas in several aspects such as grid extension difficulty, economic feasibility and reliability. The use of existing micro-hydropower (MHP) with other renewable resources in rural areas has not been well studied. Moreover, it is challenging to use mathematical optimization algorithms for these kinds of real-world problems, so the derivative-free algorithm is highly sought. In this paper, a methodology has been proposed to perform the optimal sizing, financial and generation uncertainty analysis of solar photovoltaic (SPV) based on an MHP that is proposed to handle the intermittent power output of the SPV. The analysis is performed in two cases: using storage and without storage. The optimal sizing is performed using the least present value cost and reliability constraint using different derivative-free algorithms. The storage-based hybrid system has been found to generate reliable electricity at minimal cost than without a storage-based one. This study would be helpful to propose electrification and existing micro-hydro reinforcement policies to provide reliable electricity in rural areas.

Description: Urbanization and seasonality strongly influence the bacterial composition of the soil. However, aquatic environments such as rivers are understudied owing to their high dynamics and therefore rules relating to more static habitats such as lentic or terrestrial environments may be limited. Here, we compared the spatiotemporal patterns of bacterioplankton communities in the Zhangxi river along a gradient of urbanization using 16S ribosomal DNA identification. The alpha and beta diversity of bacterioplankton showed no significant response to watershed urbanization. A significant difference in predicted functional profiles of the bacterioplankton community was also revealed between the wet and dry seasons. The bacterioplankton community assembly was driven by both deterministic and stochastic processes. Stochasticity was one of the most vital processes affecting the bacterioplankton communities in both wet and dry seasons, explaining over 50% variation in the community by the null model analysis. Bacterioplankton co-occurrence patterns in the river changed with the seasons. More notably, the composition of bacterioplankton communities was inconsistent with alternations of the spatial distance offering meaningful implications for interactions between zero-radius operational taxonomic units and the dynamics of the bacterioplankton communities in surface water. In summary, we found clear patterns of seasonal variations in the bacterioplankton community structures.

Description: Sustainable development remains unattainable unless we move to reduce the negative impact of economic factors on environmental quality. It is noteworthy to provide new evidence on whether and how the empirical association between export diversification, agricultural value-addition, renewable energy, and regulatory quality with greenhouse gas (GHG) emissions evolved in Asian countries from 1996 to 2014. The study examines the relationships between these variables using current panel data techniques. The econometric procedure includes second-generation cointegration and unit root tests together with a novel Method of Movements Quantile Regression (MMQR). This approach offers an asymmetric relationship between the variables and is very robust to outliers compared to traditional quantile regression. The empirical outcomes show that export diversification, renewable energy, and regulatory quality are significantly and negatively associated with GHG emissions. In contrast, agricultural value-added in Asia has become a source of increased GHG emissions. Our findings are also robust with alternate specifications, including fully modified, dynamic and fixed effect regressions. This study will help policymakers for diversifying their export portfolio while ensuring a sustainable environment in Asia.

Description: In recent decades, degradation and loss of the world’s forest ecosystems have been key contributors to biodiversity loss and future climate change. This article analyzes plant diversity, biomass, carbon sequestration potential (CSP), and the net primary productivity (NPP) of four vegetation types viz., Dense mixed forest (DMF); Open mixed forest (OMF); Teak plantation (TP), and Sal mixed forest (SMF) in the dry tropical forest ecosystem of central India through remote sensing techniques together with physical ground observations during 2013–2018. The total C storage in trees varied from 16.02 to 47.15 Mg ha−1 in studied vegetation types with the highest in DMF and lowest in OMF. The total C storage in stem wood, branches, and foliage falls in the range of 52.93–78.30%, 9.49–22.99%, and 3.31–12.89% respectively. The total standing biomass varied from 83.77 to 111.21 Mg ha−1 and these variations are due to different vegetation types, with the highest in DMF followed by TP, SMF while the lowest was estimated in OMF. The net primary productivity (NPP) [aboveground (AG) + belowground (BG)] varied from 7.61 to 9.94 Mg ha−1 yr−1 with mean values of 8.74 Mg ha−1 yr−1 where AG shares a maximum contribution of 77.66%. The total biomass production was distributed from 64.09 to 82.91% in AG and 17.08–35.91% in BG components. The present study outlines that the studied forest ecosystem has the substantial potential of carbon sequestration and a great possibility of mitigating local and global climate change.

Description: Amino-thiol bifunctional polysilsesquioxane/carbon nanotubes (PSQ/CNTs) magnetic composites were prepared by sol-gel method with two types of functional siloxanes coating on carboxyl CNTs simultaneously. The composites were served as efficient adsorbents for removing Hg(II) in aqueous solution and the adsorption properties were investigated systematically. The optimal pH of bifunctional composites for Hg(II) removal is at pH 4.5. The thermodynamic fitting curves are more consistent with the Langmuir model and the adsorption capacities of the bifunctional composites for Hg(II) varied from 1.63 to 1.94 mmol g−1 at 25°C according to the Langmuir model. The kinetics curves are more fitted to the pseudo-second-order model and the composites could selectively adsorb Hg(II) in a series of binary metal ions solution. The elution regeneration tests showed that the adsorption rate could still reach 78% after repeat cycle three times. It is expected that the bifunctional PSQ/CNTs magnetic composites can be potentially applied to remove low concentration Hg(II) from waste water.

Description: Circular Economy (CE) has emerged as a potential strategy for developing business practices based on sustainability concerns, especially in the fashion industry, which presents high environmental and social impacts. Startups are responsible for introducing innovations in business conduction toward CE. As a current theme, research on Business Model Innovation for Circular Economy (BMI4CE) has increased. However, empirical research in the fashion industry and startups is still scarce. This paper aimed to identify the key elements of startups' BMI4CEs, using the fashion industry as the context of the study. We conducted an exploratory and descriptive multiple case study composed of ten early-stage fashion startups from Europe, North America, and Asia. The findings suggest that environmental and economic sustainability dimensions receive priority in the analyzed BMI4CEs. On business type, we found differences between product-based and service-based Business Models (BMs). The Business Models Innovations (BMIs) were based mainly on CE principles of closed-loop and reducing material use and consumption. BMs focus on CE strategies of product reuse and extend resource time by lowering consumption and material use. Findings also demonstrate the role of emerging and digital technologies (e.g., blockchain and artificial intelligence) for BMI4CEs effectiveness. We developed five propositions and a theoretical framework from a triple bottom line perspective. This research highlights new theoretical perspectives under an investigation area still little explored in the literature. Results enable fashion startup managers to understand better the functioning of BMI4CEs and the critical elements needed for their effectiveness.

Description: The United Nations' Development Goals (SDGs) have been criticized but are nonetheless seen by many as an important, if imperfect, international effort to address climate and environmental change, resource depletion and the unsustainability of contemporary life. Many of the Goals need to be implemented at the local level, yet sub-national governments have not been granted any enhanced status at the UN to facilitate this process. As a result, the role and effectiveness of local governments in localizing the SDGs is dependent on multi-level arrangements within respective national contexts. In this paper we present findings on the challenges facing local authorities in England, namely co-dependent ambivalence, partial holism and narrow practices of knowledge governance. We draw on work carried out collaboratively with local authorities and other stakeholders in Greater Manchester and Sheffield, and a UK-wide national workshop. These challenges explain the relatively low uptake and engagement with the SDGs in the context of wider political and economic concerns compared with international comparator cities. Against this background our research found that making the Goals real, relevant, relatable and relational offered a tactical route to localization for English local government.

Description: Antibiotics resistance genes (ARGs) are mainly caused by the extensive use and abuse of antibiotics and have become a global public health concern. Owing to the development of high-throughput sequencing, metagenomic sequencing has been widely applied to profile the composition of ARGs, investigate their distribution pattern, and track their sources in diverse environments. However, the lack of a detailed transmission mechanism of ARGs limits the management of its pollution. Hence, it’s essential to introduce how to utilize the metagenomic data to obtain an in-depth understanding of the distribution pattern and transmission of ARGs. This review provides an assessment of metagenomic data utilization in ARG studies and summarizes current bioinformatic tools and databases, including ARGs-OAP, ARG analyzer, DeepARG, CARD, and SARG, for profiling the composition of ARGs and tracking the source of ARGs. Several bioinformatic tools and databases were then benchmarked. Our results showed that although SARG is a good database, the application of two or more bioinformatic tools and databases could provide a comprehensive view of ARG profiles in diverse environmental samples. Finally, several perspectives were proposed for future studies to obtain an in-depth understanding of ARGs based on metagenomic data. Our review of the utilization of metagenomic data together with bioinformatic tools and databases in ARG studies could provide insights on exploring the profiles and transmission mechanism of ARG in different environments that mitigate the spread of ARGs and manage the ARGs pollution.

Description: Climate change and human activities are having increasing impacts on the global water cycle, particularly on streamflow. Current methods for quantifying these impacts are numerous and have their merits and limitations. There is a lack of a guide to help researchers select one or more appropriate methods for attribution analysis. In this study, hydrological modeling, statistical analysis, and conceptual approaches were used jointly to develop a methodological options framework consisting of three modules, to guide researchers in selecting appropriate methods and assessing climatic and anthropogenic contributions to streamflow changes. To evaluate its effectiveness, a case study in the Upper Yangtze River Basin (UYRB) of China was conducted. The results suggest that the SWAT-based method is the best approach to quantify the influences of climate change and human activities on streamflow in the UYRB. The comprehensive assessment indicates that climate change is the dominant cause of streamflow changes in the UYRB, and the contribution of climate change, indirect human activities, and direct human activities to streamflow changes is about 7:1:2. The proposed framework is efficient and valuable in assisting researchers to find appropriate methods for attribution analysis of streamflow changes, which can help to understand the water cycle in changing environments.

Description: The time and annealing temperature for the film crystallization in perovskite solar cells (PSCs) is critical and is at the stake of device optimization. It governs the crystallization process, the film’s morphorlogy and texture and the level of non-radiative defects, which in whole control the power conversion efficiency (PCE). However, deciphering each of these parameters in the device cell characteristics remains not totally clear. In this work, we led a holistic study considering temperature and time for the MAPbI3 crystallization as a free parameter to study how the latter is impacting on the film’s characteristics and how the device figure of merit is affected. The results suggest that the crystallinity level of the grains plays an important role in the photo-current value whereas the morphology and PbI2 impurities resulting from the onset of thermal decomposition of MAPbI3 penalizes the cell photovoltage and the fill factor values. Based on this study, it is highlighted that flash high temperature annealing is beneficial to limit out-of-plane substrate grain boundaries, resulting in a device exhibiting 18.8% power conversion efficiency compared to 18.0% when more standard post-annealing procedure is employed.

Description: Citizen science and informed citizens have become fundamental in providing the first records and accounts about the expansion of numerous non-indigenous species. However, implementing a successful citizen science campaign can be expensive and particularly difficult for aquatic species. Here, we demonstrate how a low-cost citizen science campaign and its outreach plan in social and traditional media enabled to track the expansion of the Atlantic blue crab Callinectes sapidus Rathbun, 1896 along the coast of Algarve (southern Portugal, Europe). We describe the outreach strategy and a cost-benefit analysis of the first year of the citizen science campaign. Social media platforms allowed us to reach a significant number of citizens (over 31,500 clicks in Facebook publications), while traditional media gave national visibility to the citizen science campaign and biological invasions. In only 1 year, we documented the spread of the invasive Atlantic blue crab across the entire 140 km of the Algarve coast with 166 valid observations referring to 1747 specimens, submitted by 62 citizen scientists. We spent 0 € on the citizen science campaign, but considering the time invested in the campaign the cost would have summed up to 3,751 €, while the total minimum cost for one scientist to go to the field and retrieve the equivalent information would have exceeded 11,000 €. We used free online tools of communication to obtain the records about the Atlantic blue crab, instead of a dedicated web platform or mobile app, and handled social media accounts ourselves, which saved us at least 18,815 €. The citizen science campaign revealed that the Atlantic blue crab is unequivocally established in southern Portugal and that females appear to exhibit summer migrations to coastal areas to spawn as in the native area. Overall, our low-cost citizen science campaign effectively documented the rapid spread of a marine invasive species while providing some insights into its ecology. Our strategy can be easily replicated and implemented elsewhere in the world to tackle the ever-growing problem of biological invasions while increasing the scientific literacy of local populations.

Description: An estimated 90% of the Swan Coastal Plain (SCP) wetlands, located in southwestern Australia, have been lost because of infilling or drainage. This loss continues despite the well-known causes, which include nutrient enrichment; the invasion of exotic flora and fauna; loss of fringing vegetation; and altered hydrological regimes caused by groundwater abstraction; urbanization; and a drying climate. Further loss is expected with climate change exacerbating the undesirable ecosystem changes of remaining wetlands. In this study, we consider these wetlands as examples of social-ecological systems (SES) which are characterized by a close interaction of the ecosystem with the social system. We take the theory of resilient SES as a starting point to identify the adaptive capacity and resilience of the wetlands. We argue that resilience provides a useful framework to analyze adaptation processes and to identify appropriate policy responses. We explore incremental adjustments and transformative action and demonstrate that policy responses arise across multiple scales and levels of jurisdiction and institution. By applying the theoretical framework of resilience to the SCP wetlands, we identified (un)desired ecosystem states of wetlands (hydrology and ecology) through different set of policy actions. Our results show that current wetland management is inadequate to maintain the ecosystem's functioning. We recommend cross-jurisdictional collaboration and the use of conceptual eco-hydrological models to depict gradual ecological change and types of regime shifts (thresholds, hysteresis, and irreversible changes). The different adaption options inform decision-makers to adequately adapt wetland management practices when uncertainty in ecosystem responses exist. Empirical data on how multiple jurisdictions operate and decide could help to further support decision-making. With this research we aim to narrow the science-policy interface which depends on corresponding cross-jurisdictional and institutional responses to coordinate wetland management policies and actions.

Description: In the domain of globalization, the global value chain (GVC) is formed across diverse economies. Owing to the expansion of economic globalization and the resultant global trade liberalization, the geographical isolation of production and consumption has resulted in the transfer of polluting emissions from advanced economies to developing states. Developing economies, falling in the middle and low end of the GVC, have to strive hard to expand their production in the GVC, while simultaneously addressing the consequent environmental damage and attending to the core environmental concerns of sustainable growth, energy preservation and drastic cuts in CO2. This paper addresses how manufacturing subsidiaries can improve their low-carbon innovation ability and help to achieve a sustainable competitive advantage through the embedded GVC. Data were gathered employing interview and survey methods, 31 manufacturing companies and 56 enterprise groups across 16 Chinese provinces were selected as the case study. A partial least square structural equation modelling was adopted to analyse the responses. The results indicate that the embedded GVC significantly enhances low-carbon innovation capability and promotes a sustainable competitive advantage. This study proposes that companies should continuously identify high-quality resources from the GVC and discover ways of integrating internal and external carbon innovation resources to form innovation capabilities.

Description: Spent carbon anode (SCA) is a dangerous solid waste that is continuously discharged from the aluminum electrolysis industry and has a large number of valuable resources and a high risk of environmental pollution. Its safe disposal and resource utilization have become a resource and environmental problem that must be solved urgently. Current methods for SCA disposal include flotation, vacuum metallurgy, physical activation, roasting, bubbling fluidized bed combustion, alkali fusion, alkali leaching, and chemical leaching combined with high temperature graphitization. In this paper, the material composition, resource properties, and environmental risks of SCA are discussed. Working principle, treatment process, advantages and disadvantages of the above methods are also briefly described and compared. Results showed that flotation is the safest disposal and comprehensive utilization technology that is suitable for characteristics of SCA raw materials and has the most large-scale application potential. In addition, characteristics of SCA recovery products are correlated to the recycling of aluminum reduction cells. This technology can alleviate the shortage of high-quality petroleum coke resources in China’s carbon material industry and the high cost of raw materials in aluminum electrolysis industry.

Description: This study develops an implementation framework for asset management strategic planning of water distribution networks to meet sustainable infrastructure, socio-political, and financial targets over the life cycle of the infrastructure. The proposed framework is comprised of three decision-making layers: (1) Visions and Values, (2) Function, and (3) Performance. The asset management strategy framework is implemented and validated by demonstrating functionality and value by using data from three water utilities in Canada. The Visions and Values layer is set to meet the needs of the water utilities' stakeholders. The Function layer uses an advanced system dynamics model to simulate and forecast the system's future behavior. The Performance layer benchmarks, compares, and graphically illustrates the situation and performance of water utilities against each other regardless of their size. Benchmarking results indicate that all three water utilities can sustainably meet the strategic targets established in the Visions and Values layer of the asset management strategy over the benchmarking period. The impact of the desired cash reserve on infrastructure and financial benchmarking performance indicators is also investigated to explore the “optimal” combination of allowable fee-hike and rehabilitation rates using the contour plots developed over the benchmarking period. The results indicate that the optimal combinations of allowable fee-hike of ~8% per year and rehabilitation rate of 1.3% per year along with a 1–4% cash reserve, depends on the network condition, will allow water utilities to have sufficient funds to meet their strategic targets. The performance modeling and simulation approach presented in this study represents a powerful tool for other utilities to develop optimal strategic and operational plans for their networks and thus better service to their stakeholders.

Description: The suitability of remediation systems using metallic iron (Fe0) has been extensively discussed during the past 3 decades. It has been established that aqueous Fe0 oxidative dissolution is not caused by the presence of any contaminant. Instead, the reductive transformation of contaminants is a consequence of Fe0 oxidation. Yet researchers are still maintaining that electrons from the metal body are involved in the process of contaminant reduction. According to the electron efficiency concept, electrons from Fe0 should be redistributed to: i) contaminants of concern (COCs), ii) natural reducing agents (e.g., H2O, O2), and/or iii) reducible co-contaminants (e.g. NO3-). The electron efficiency is defined as the fraction of electrons from Fe0 oxidation which is utilized for the reductive transformations of COCs. This concept is in frontal contradiction with the view that Fe0 is not directly involved in the process of contaminant reduction. This communication recalls the universality of the concept that reductive processes observed in remediation Fe0/H2O systems are mediated by primary (e.g., FeII, H/H2) and secondary (e.g., Fe3O4, green rusts) products of aqueous iron corrosion. The critical evaluation of the electron efficiency concept suggests that it should be abandoned. Instead, research efforts should be directed towards tackling the real challenges for the design of sustainable Fe0-based water treatment systems based on fundamental mechanisms of iron corrosion.

Description: Phytoplankton functional groups and their influence on water quality have been studied in various types of water bodies but have yet to be studied in agricultural irrigation ponds. Freshwater sources (e.g., lakes, rivers, and reservoirs) have been previously shown to exhibit high spatial and temporal variability in phytoplankton populations. Improvements in the monitoring of phytoplankton populations may be achieved if patterns of stable spatial variability can be found in the phytoplankton populations through time. The objective of this work was to determine if temporally stable spatial patterns in phytoplankton communities could be detected in agricultural irrigation ponds using a functional group approach. The study was performed at two working agricultural irrigation ponds located in Maryland, USA over two summer sampling campaigns in 2017 and 2018. Concentrations of four phytoplankton groups, along with sensor-based and fluorometer based water quality parameters were measured. Temporal stability was assessed using mean relative differences between measurements in each location and averaged measurements across ponds on each sampling date. Temporally stable spatial patterns of three phytoplankton functional groups were found for both ponds over the two sampling seasons. Both ponds had locations where specific phytoplankton functional group concentrations were consistently higher or lower than the pond's average concentration for each sampling date. Zones of consistently higher or lower than average concentrations were associated with flow conditions, pond morphology, and human activities. The existence of temporally stable patterns of phytoplankton functional group concentrations can affect the outcome of a water quality assessment and should be considered in water quality monitoring designs.