Supply-demand Mismatches Research Articles

Exploring the supply-demand match and drivers of blue-green spaces cooling in Wuhan Metropolis

This study explores the spatial evolution and driving factors of cooling supply and demand matching in blue-green spaces (BGSs) to alleviate urban heat island effects. Using Wuhan Metropolis as a case study, the cooling supply index (CSI) and cooling demand index (CDI) were utilized to assess the BGSs' cooling supply capacity and demand levels in 2014, 2018 and 2022. The relationship between them was then examined applying spatial gradient analysis and constraint effect analysis. Subsequently, the coupled coordination degree (CCD) of cooling supply-demand and its built environment-driven explanatory power was investigated. Ultimately, areas with supply-demand mismatches were identified, and tailored cooling strategies were devised to rectify these discrepancies. The results indicated that: (1) Wuhan Metropolis experienced a decline in BGSs' cooling supply capacity and an increase in cooling demand level between 2014 and 2022. (2) There is a significant correlation between the cooling supply capacity and demand level of BGSs in Wuhan Metropolis, with a spatial gradient effect and a constraint effect (CSI values = 0–0.2). (3) The CCD of cooling supply-demand in Wuhan Metropolis decreased from 2014 to 2022, with building density being the dominant built environment factors (q-value = 0.83–0.86). (4) The number of mismatched cooling supply-demand units significantly increased in Wuhan Metropolis from 2014 to 2022, indicating an imperative need to alleviate urban high temperatures. To address this issue, the study proposes a mismatch mechanism-based regulatory strategy aimed at mitigating the heat from residential, transportation, and industrial areas.

Two-agent proportionate flowshop scheduling with deadlines: polynomial-time optimization algorithms

AbstractVolatility in the supply chain of critical products, notably the vaccine shortage during the pandemic, influences livelihoods and may lead to significant delays and long waiting times. Considering the capital- and time-intensive nature of capacity expansion plans, strategic operational production decisions are required best to address the supply-demand mismatches given the limited production resources. This research article investigates the production scenarios where the demand of one agent must be completed within a specified due date, hereinafter referred to as the deadline, while minimizing the maximum or total completion time of another agent's demand. For this purpose, the Two-Agent Proportionate Flowshop Scheduling Problem with deadlines is introduced. Two polynomial-time optimization algorithms are developed to solve these optimization problems. This study will serve as a basis for further developing this practical yet understudied scheduling problem.

Managing the Supply–Demand Mismatches and Potential Flows of Ecosystem Services in Jilin Province, China, from a Regional Integration Perspective

Regional integration strategically reorganizes spatially heterogeneous resources to maximize the overall benefits. Ecosystem services (ESs) are promising targets for regional integration due to their inherent heterogeneity and mobility, yet research in this area remains limited. This study quantifies crop production (CP), water yield (WY), carbon storage (CS), and habitat quality (HQ) for the years 2000, 2010, and 2020 using the InVEST model and identifies four ES bundles through a K-means cluster analysis. A conceptual ecosystem service flow (ESF) network at the service cluster scale is constructed based on county-level ESF data. The results reveal the following: (1) there is an upward trend in the ES budget for all services from 2000 to 2020, coupled with spatial mismatches between supply and demand; (2) deficit nodes for CP and CS services are concentrated in densely populated districts, while deficits in WY and HQ services are mainly in western Jilin Province; (3) Bundles I and II act as “sources” of ES, Bundle IV serves as a “sink”, and Bundle III is the only cluster with a CP surplus, balancing CP services across the province. In addition, this study provides ecological perspectives for understanding regional integration by suggesting differentiated integrated management for different ecosystem bundles.

Risk-averse coordinated operation of hydrogen-integrated energy hubs with seasonal energy storage

Addressing seasonal fluctuations and supply–demand mismatches in renewable energy is vital for sustainable multi-energy hubs. Moreover, current research has limitations in achieving economic efficiency, flexibility, security, and sustainability simultaneously. Therefore, this study leverages hydrogen storage’s long-term flexibility, proposing an integrated operational strategy to manage these fluctuations and optimize green energy utilization. This novel tertiary hub hydrogen-based integrated energy system integrates producers, prosumers, and consumers, optimizing ecological and economic sustainability via demand response programs and carbon capture, utilization, and storage systems. Utilizing risk-averse stochastic optimization for day-ahead and real-time operations, it evaluates dispatch decisions’ impact on risk costs and coupling efficiency. This study’s mixed-integer linear programming model, solved using CPLEX in GAMS, ensures a globally optimal solution. Key findings include an 86.15% cost-saving return through multi-energy storage and hub coordination, along with a 5.27% decrease in operating expenses and an 8.13% drop in emissions. In addition, adjusting the risk level parameter by 10% leads to a 14.76% variance in risk cost, bolstering client confidence in the model’s efficacy and sustainability.

Management on Transfer Pricing of Farmland Based on the Supply–Demand Mismatches for Multifunction: A Case Study from China

Realizing the multifunctional value of farmland is essential for regulating the pricing of farmland transfers and stabilizing the rural land market. However, in China, the mismatch between supply and demand leads to improper resource allocation, weakens the explicit value of farmland, and causes unreasonable transfer pricing mechanisms that threaten agricultural production and food security. This study develops an analytical framework to examine the relationship between farmland multifunction and transfer pricing from a supply–demand perspective. An evaluation index system is constructed, considering the physical, value, and material quantities. This study uses the matching index method and bivariate spatial autocorrelation to analyze the supply–demand match of farmland multifunction from 2014 to 2021 and its relationship with transfer prices. Additionally, management methods and strategies for dynamic zoning-based pricing under multifunctional matching trade-offs are proposed. The results show that: (1) There is significant heterogeneity in the supply and demand matching degree of different farmland functions in both space and time. The production and ecological functions of farmland are oversupplied, while the living functions are undersupplied. (2) Different spatial autocorrelation relationships exist between the degree of supply and demand matching of farmland functions and farmland transfer prices. Specifically, the supply and demand matching degrees of the production and living functions show a significant negative spatial correlation with farmland transfer prices. In contrast, the ecological function shows a significant positive spatial correlation with farmland transfer prices, which are continuously strengthening over time. (3) Based on the supply and demand matching situation of different farmland functions and the spatial autocorrelation of farmland transfer prices, nine types of regions are delineated for farmland functions. Among them, the surplus-coordinated development areas have the most cities, accounting for about 40%, with a wide distribution range. This study proposes zoning-based pricing instruments and management strategies. This research provides valuable insights for developing countries seeking to alleviate conflicts in multifunctional land use, enhance the sustainable protection of land resources, and improve land resource assessment frameworks.

A control strategy considering buildings’ thermal characteristics to mitigate heat supply-demand mismatches in district heating systems

In district heating systems (DHS), periodic heat supply-demand mismatches (HSDM) exacerbate issues such as thermal imbalance and hydraulic instability. To mitigate these issues, this paper proposes a supply water temperature correction strategy for heating stations that considers building's thermal characteristics. Firstly, buildings are classified into energy-saving levels based on comprehensive thermal characteristic Bc and heat load index. Secondly, simulation models are developed for buildings with different thermal characteristics, and response of indoor temperature to supply-demand mismatch rates was analyzed. Then, after determining the regulation sequence and supply water temperature of heating stations, a balanced control strategy is formulated for HSDM conditions. Finally, the proposed strategy was applied to a practical combined heat and power system (CHPS) in severe cold regions. The results showed that the studied heating stations were classified into 4 types. After regulation of both insufficient and excessive heating conditions, the indoor temperature guarantee rate increased by over 20 %; the ranges of thermal imbalance degree and hydraulic imbalance degree were reduced by more than 0.09 and 0.22, respectively; the SD of supply water pressure and supply-return pressure difference were reduced by over 0.17 and 0.11, respectively. The strategy provides a reference for global balanced control of DHS under similar HSDM conditions.

Ecological risk assessment and influencing factors in the Wuhan Metropolitan Area based on supply and demand bundles of ecosystem services

In the context of rapid urbanization, metropolitan areas are facing the risk of supply-demand mismatches among ecosystem services. Investigating the patterns, relationships, and driving factors of multiple supply-demand risks is of great significance to support the efficient management of regional ecological risks. We quantified the single/comprehensive supply-demand risk rates of six ecosystem services in Wuhan Metropolitan Area at the township scale in 2000, 2010, and 2020. By applying the self-organizing feature map network and optimal parameter geo-detector, we identified supply-demand risks bundles of ecosystem services and influencing factors of comprehensive risks. The results showed significant spatial variations in the supply-demand risks of typical ecosystem services from 2000 to 2020. The supply-demand risk associated with grain production, water yield, carbon sequestration, and green space recreation increased, while soil conservation and water purification risks decreased. The comprehensive ecosystem services supply-demand risk increased from 0.41 to 0.45, indicating a 'core area increase and periphery decrease' trend. Throughout the study period, the area exhibited bundles of comprehensive extremely high-risk bundles (B1), comprehensive high-risk bundles (B2), water purification high-risk bundles (B3), and grain production-soil conservation risk bundles (B4). The transition of risk types from B3 to B2 and from B2 to B1 suggested an increase in the combination and intensity of supply-demand risk. Vegetation cover, nighttime light index, and population density were the main driving factors for spatial variations in comprehensive supply-demand risk. Ecologi-cal risk assessment based on ecosystem services supply-demand bundles could provide an effective and reliable way to regulate multiple regional risk issues.

Perioperative hyperoxia- impact on myocardial biomarkers, strain and outcome in high-risk patients undergoing non-cardiac surgery: Protocol for a prospective randomized controlled trial

BackgroundSupplemental oxygen is used during every general anesthesia. However, for the maintenance phase of a general anesthesia, in most cases the longest part of anesthesia, only scarce evidence of dosing supplemental oxygen exists. Oxygen is a well-known coronary vasoconstrictor and thus may contribute to cardiovascular complications especially in vulnerable high-risk patients with coronary artery disease undergoing major non-cardiac surgery. Myocardial biomarkers are early indicators of myocardial injury. Oxygen supply demand mismatches due to coronary artery disease aggravated by hyperoxia might be displayed by changes from the biomarker's baseline-values. This study is designed to detect changes in myocardial biomarkers levels associated with perioperative hyperoxia. MethodsThis prospective randomized controlled interventional trial investigates the impact of maintaining perioperative high oxygen supplementation in high-risk patients undergoing non-cardiac vascular surgery on cardiac biomarkers, myocardial strain and outcome in 110 patients. Patients are allocated to be supplemented with either 0.3 (normal) or 0.8 (high) fraction of inspired oxygen (FiO2) perioperatively. Included is a short crossover phase during which transesophageal echocardiography is used to evaluate myocardial function at FiO2 0.3 and 0.8 by strain analysis in each patient. Patients will be followed up for complications at 30 days and 1 year. ConclusionThe trial is designed to evaluate perioperative changes from baseline myocardial biomarkers associated with perioperative FiO2. Furthermore, exploration and correlation of changes in biomarkers, acute early changes in myocardial function and clinical outcomes induced by different FiO2 may be possible.

Urban green inequality and its mismatches with human demand across neighborhoods in New York, Amsterdam, and Beijing

ContextUrban green spaces (UGS) are not evenly distributed within cities, and some neighborhoods with high socio-environmental demands require more UGS than others. This raises two challenges: green inequality and demand-based inequity. However, comprehensive assessments of UGS inequality and inequity in cities worldwide are lacking.ObjectivesWe aim to develop a multi-level approach and supply-demand concept to assess UGS inequality and inequity across neighborhoods in international cities with contrasting geographical and socio-political contexts.MethodsWe measured multi-level green accessibility and human demands based on Earth Observation and statistical data. UGS inequality and supply-demand mismatches were assessed by Gini coefficients, spatial cluster analysis, and statistical models.ResultsWe found that: (1) UGS inequality is primarily reflected by the public park per capita in three cities. New York has larger UGS inequality than Beijing and Amsterdam. (2) Demand-based inequity in terms of low supply and high demand is mainly scattered around the city center in three cities. Tree coverage does not align with environmental pressures (LST/PM2.5) in New York and Beijing. (3) Relations between green supplies and human demands vary by cities and indicators. A shorter distance to the nearest large park is associated with a higher proportion of the elderly and children in New York and Amsterdam.ConclusionsOur findings can inform UGS allocations to improve landscape sustainability in the neighborhoods with low green supply and high human demand, and to prioritize specific green metrics based on demand-oriented equity.

Utilizing supply-demand bundles in Nature-based Recreation offers insights into specific strategies for sustainable tourism management

Balancing supply and demand in Nature-based Recreation (NbR) has the potential to yield co-benefits across multiple Ecosystem Services (ES), helping to make tourism activities more sustainable. However, a comprehensive understanding of supply-demand mismatches in NbR is challenging due to the complex interaction among various social, economic and ecological factors. This paper investigates mismatches in NbR supply and demand to provide insights for informing spatial and regional planning to achieve sustainable tourism. To this end, the paper uses a wide range of indicators such as biophysical attributes, accessibility and social indicators to map and assess NbR supply and demand, followed by the application of spatial statistics to analyse supply-demand mismatches. Cluster analysis was performed based on the supply-demand relationship to identify a typology of NbR ES across the study area in the north of Iran. The paper proposes an innovative application of recreation ES bundles with potential implications for sustainable tourism in a region marked as a hot spot for tourism. The analysis generated a typology of five bundles of NbR ES with differing recreational opportunities. Bundles 1 and 2, characterized by a supply surplus and substantial ecological value, are suitable for NbR activities such as camping, hiking, climbing, and birdwatching. In contrast, bundle 4 and 5 associated with urban centres, experience a supply deficit, making them less suitable for NbR. Bundle 3, characterized by a mixture of natural and productive lands, plays an important role in maintaining a balanced supply-demand state. This region holds potential for diverse forms of tourism, including rural and agricultural recreation such as farm tours and farm life experiences. Based on findings, the paper provides valuable insights for spatial and regional planning by proposing targeted strategies to sustainably manage tourism activities.

Advancing the optimization of urban–rural ecosystem service supply-demand mismatches and trade-offs

ContextIntensified human activities have disrupted landscape patterns, causing a reduction in the supply of ecosystem services (ESs) and an increase in demand, especially in urban agglomerations. This supply-demand imbalance will eventually lead to unsustainable landscapes and needs to be optimized.ObjectiveBased on ES supply-demand mismatch and trade-off relationships across urban–rural landscapes, this study explored which ESs need to be optimized and identified priority restoration regions of ESs that require optimization to promote landscape sustainability in Beijing-Tianjin-Hebei urban agglomeration.MethodsA methodological framework for ES supply-demand optimization in urban–rural landscapes was developed. urban–rural landscapes were identified using Iso cluster classification tool. ES supply was quantified using biophysical models and empirical formulas, and demand was quantified through consumption and expectations. Restoration Opportunities Optimization Tool was then adopted to identify priority regions.ResultsFrom 2000 to 2020, most of ES supply were lowest in urban areas and highest in rural areas, while demand exhibited the opposite. Although supply was increasing, it did not match demand. ES deficits were dominant in urban areas; both deficits and trade-offs were dominant in urban–rural fringe; and trade-offs were dominant in rural areas. There were 13,175 km2 of priority regions distributed in urban–rural landscapes, and their spatial heterogeneity was influenced by ES deficits and trade-offs.ConclusionDifferences in ESs supply-demand relationships affected the necessity of optimizing ESs zoning in urban–rural landscapes. Assigning weights reasonably according to trade-off curves to determine priority regions could facilitate both efficient use of resources and sustainable ES management for urban–rural regions.

Still waiting for the (data) revolution. Examining supply-demand mismatches in the production of SDG 4 metrics

In the context of the 2030 Agenda for Sustainable Development, high hopes were placed in the production of global metrics. Such expectations rest upon two main assumptions: first, that global data demands will lead to an increase in domestic data supply; and second, that global and domestic data needs are closely aligned. Having passed the halfway point of the SDGs, this paper critically examines each of these assumptions in relation to recent developments in the education field. In so doing, it highlights the need for greater reflection on the opportunity costs associated with the production of globally comparable data, and for an empirically-informed analysis of the necessary resources and conditions for strengthening education information systems and domestic statistical capacity.

Landscape management and planning as a spatial organization method connecting CES supply-demand assessment and sustainable tourism development

Evaluating the balance between the supply and demand of Cultural Ecosystem Service (CES) in space is the key to linking ecosystem services to human well-being. However, due to its invisibility, it is difficult to quantify and is often ignored in ecosystem service evaluation. Based on social media photos, by integrating multisource data and using a clustering algorithm and the MaxEnt model, this paper maps and evaluates the supply-demand balance of three CES of aesthetic, historical and cultural, and leisure services in Suzhou, China. The result shows a widespread imbalance between supply and demand in Suzhou, among which the cultural heritage CES imbalance area as high as 48.1% accounts for the largest proportion, and the aesthetic imbalance area accounts for 38.4%, while the recreation imbalance area accounts for 37%. Building upon the assessment of supply and demand balance at the urban scale, we further identified the supply-demand imbalance at the scenic area scale by integrating local tourism development policies in Suzhou and selecting a typical scenic area, Xishan Island. Based on the urban and scenic area supply-demand assessment results, this paper proposes a multiscale CES supply-demand allocation strategy. This comprehensive approach not only furnishes valuable guidance for local decision-making and management within the realm of sustainable tourism but also holds potential for wider applicability to diverse urban areas worldwide that share analogous contextual backgrounds. Management implicationsCES supply and demand assessment can help identify the CES supply-demand imbalance areas of tourist destinations. Landscape management and planning is a spatial organization method to balance CES supply-demand mismatches in tourist destinations. Optimizing landscape structure at multiple scales will be of instructional significance for the protection and development of tourist destinations. A ‘CES assessment and mapping – landscape management and planning – tourism protection and development’ system is beneficial to achieve the sustainable development of tourism.

Assessing the spatial pattern of supply-demand mismatches in ecosystem flood regulation service: A case study in Xiamen

Balancing the supply and demand of urban flood regulation services is crucial for refining flood management policies. Previous studies often employed coarse evaluation units and data limitations may constrained assessments of flood regulation service demand, while this study employs finer evaluation units and an integrated methodology using open data. Taking Xiamen as a case study, machine learning and a comprehensive multi-criteria evaluation model were used to assess flood regulation service demand, hydrological modeling was conducted to evaluate the service supply. Spatial supply-demand disparities were analyzed by the supply-demand ratio. Results reveal pronounced spatial mismatches between flood regulation service supply and demand in Xiamen, with supply deficient units primarily concentrated in intense constructed areas, specifically Jimei, Huli, and Siming districts. The transferability of the method is examined, the correlation between supply-demand relationships and land use is analyzed, demonstrating the applicability of the methods in supporting similar studies in poor-data areas. The methodology could thereby facilitate spatial planning optimization and policy adjustments.

Managing the supply-demand mismatches and potential flows of ecosystem services from the perspective of regional integration: A case study of Hangzhou, China

Regional integration is a development strategy that synergizes various components as a whole to maximize overall benefits. The natural heterogeneity and fluidity of ecosystem service (ES) make it a promising target for regional integration. However, the current focus on regional integration was more on the socio-economic factors rather than ecological resources, and the understanding of the supply-demand relationship and potential flow of ecosystem services was still limited. Therefore, we attempted to interpret ecological integration management by linking ES budgets, bundles, and flows in this study. The results showed that the spatial mismatches of ESs supply-demand were observed in all six selected ES types. Most of the ESs deficit regions were concentrated in urban centers, while ES surplus regions were scattered in surrounding rural areas. Multiple heterogeneous ES resources could ideally benefit an additional 0.13–4.84 million people in 9–70 townships through potential ES flows under ecological integration management. Therefore, we connected the service provisioning areas (SPAs) and service beneficiary areas (SBAs) with three types of ES flows and drew the potential provider-beneficiary relationship networks at the townships/bundles scale, demonstrating the interactive relationship of ecological integration within the region. On this basis, we also proposed the applicability matrix of governance tools for the first time according to the type of ES flows, and then put forward the corresponding governance opinions around the two aspects of “improving ES budges within clusters” and “strengthening ES flow among clusters”. This study provided an ecological perspective for understanding regional integration, and relevant conclusions can inform environmental policy priorities for sustainable decision-making in urbanized areas.

Framework for the application of ecosystem services based urban ecological carrying capacity assessment in the urban decision-making process

Urban Ecological Carrying Capacity (UECC) is widely studied as a comprehensive measure of urban ecology. Several tools, like an ecological footprint, comprehensive index system, system dynamic models, etc., are used to study UECC. In recent times, ecosystem services (ES) have been applied in analyzing carrying capacity to promote sustainable development. ES-based analysis helps study supply-demand mismatches, identify dependencies on natural systems, and understand trade-offs between strategic plans. The ES approach effectively scopes prioritized services, collects baseline data, makes choices between alternatives, and studies cumulative impacts. However, the lack of application-oriented frameworks hinders the mainstreaming of ES in urban planning. Therefore, the study proposes a framework for using ES-based UECC assessment in urban decision-making. It employs a two-stage methodology: first, a bibliometric analysis of UECC to identify knowledge gaps and trends, and second, the development of a framework for the application of ES based UECC in urban decision-making process based on the gaps identified from bibliometric analysis. The bibliometric results reveal that further research is needed to strengthen the link between ES and UECC. ES provides a comprehensive framework that includes cultural and social subsystems, enhancing the practicality and comprehensiveness of carrying capacity assessments. Based on the literature review Strategic Environmental Assessment (SEA) is identified as the tool that facilitates the entry of ES in the urban decision-making process. The main aim of the framework is to combine the ES cascade model, SEA, and carrying capacity to establish a comprehensive and practical approach to decision-making that promotes sustainable urban development. The proposed framework considers various aspects, including its environment, societal requirements, and resource constraints. The ES-based UECC concept can be extended to define limits to urban growth for ensuring the sustainable development of urban settlements.

Distributed rate control of smart solar arrays with batteries

Continued advances in technology have led to falling costs and a dramatic increase in the aggregate amount of solar capacity installed across the world. A drawback of increased solar penetration is the potential for supply-demand mismatches in the grid due to the intermittent nature of solar generation. While energy storage can be used to mask such problems, we argue that there is also a need to explicitly control the rate of solar generation of each solar array in order to achieve high penetration while also handling supply-demand mismatches. To address this issue, we present the notion of smart solar arrays that can actively modulate their solar output based on the notion of proportional fairness. We present a decentralized algorithm based on Lagrangian optimization that enables each smart solar array to make local decisions on its fair share of solar power it can inject into the grid and then present a sense-broadcast-respond protocol to implement our decentralized algorithm into smart solar arrays. We also study the benefits of using energy storage when we rate control solar. To do so, we present a decentralized algorithm to charge and discharge batteries for each smart solar. Our evaluation on a city-scale dataset shows that our approach enables 2.6× more solar penetration while causing smart arrays to reduce their output by as little as 12.4%. By employing an adaptive gradient approach, our decentralized algorithm has 3 to 30× faster convergence. Finally, we demonstrate energy storage can help netmeter more solar energy while ensuring fairness and grid constraints are met.

Understanding supply-demand mismatches in ecosystem services and interactive effects of drivers to support spatial planning in Tianjin metropolis, China

Metropolitan areas are being challenged by the disparity between growing societal needs and dwindling natural resource provision. Understanding the supply-demand mismatches of ecosystem services (ES) and their drivers is essential for landscape planning and decision-making. However, integrating such information into spatial planning remains challenging due to the complex nature of urban ecosystems and their intrinsic interactions. In this study, we first assessed and mapped the supply, demand, and mismatches of six typical ES in Tianjin, China. We then clustered numerous townships based on their corresponding spatial characteristic of ES supply-demand mismatches. We also used Random Forest regression to examine the relative importance of drivers and applied Partial Least Squares structural equation modelling to decouple their interactions. The results showed that, the distribution of ES supply and demand showed obvious spatial heterogeneity, with a common surplus of ES supply in highly natural mountainous region and an excess of demand in urban centre. Additionally, all towns were classified into four spatial clusters with homogeneous states of supply-demand mismatches, serving as basic units for spatial optimization. Moreover, the interactions between drivers affected ES supply-demand mismatches in a coupled manner, including the direct effects of the socioeconomic factor (−0.821) and landscape composition (0.234), as well as the indirect effects of the biophysical factor (0.151) and landscape configuration (0.082). Finally, we discussed the utility of analysing the spatial mismatches between ES supply and demand for integrated territorial planning and coordinated decision-making.

Identifying supply-demand mismatches in district heating system based on association rule mining

Supply-demand mismatches in district heating system (DHS) may affect system's safe and stable operation without reasonable regulation actions in time. The accurate identification of supply-demand matching states is the prerequisite for heat balance regulation. However, this job is quite difficult and time-consuming, as DHS is typically a large time delay system and operates under various conditions. This paper proposes an association rule mining-based method to identify supply-demand mismatch from DHS operation data. Considering DHS's thermal inertia and fault-tolerance, the supply-demand mismatch rate is firstly defined along with its quantitative evaluation model. Then the theoretical intervals of the heating parameters are obtained by establishing association rules and rules post-processing. And a reasonable error band is decided by comparing the occurrence times of mismatches to balance identification accuracy and sensitivity. The proposed method is tested and verified in a typical DHS. The rules between primary supply temperature and relevant operation parameters are mined. An error band of ±7.5% is determined by comparison with historical operation data. The supply-demand mismatch rate is calculated to be −10%–15%. The identification results are validated by analyzing the heat substations' operation data including supply and return temperature, flow rate, and valve opening.

Scale effects on the supply–demand mismatches of ecosystem services in Hubei Province, China

Understanding the patterns, relationships, and driving forces between ecosystem services (ESs) supply–demand at multiple spatial scales can facilitate sustainable hierarchical management. However, the scale effects of ESs supply–demand mismatches were typically ignored, resulting in inadequate targeted ecosystem promotion policies. This study identified the supply–demand mismatches of the key ESs (grain production, water yield, carbon sequestration, and soil conservation) using the ecological supply–demand ratio and bivariate Moran's I at three grid and county scales from 2000 to 2020 in Hubei Province, China. Then the spatial regression models were applied to explore the driving forces of these mismatches. The major results revealed that (1) Hubei Province and counties located away from urban areas were self-sufficient in the ESs supply–demand, but the numbers of these counties declined over the twenty years. The characteristics of ESs mismatches in some patches may be obscured at coarser scales. (2) The directions of socioecological drivers were robust, but their intensities changed significantly at the four scales. The normalized difference vegetation index was the primary positive driver at the fine scale, while population, economy, and proportion of construction land became dominant drivers at coarser scales. Factors influencing mismatches were more diverse at the fine scale compared to the coarse scale. (3) Efficient strategies were scale-dependent and place-based. Different management units should clarify their responsibilities and strengthen linkages between upper and lower levels to achieve sustainable ESs development. At the provincial level, strengthening interregional cooperation and allocating surplus grain and water resources from the southwest to urban regions contributes to balancing regional ESs. At the county level, adopting region-specific strategies based on delineating ESs management zones is crucial. At finer management levels, incorporating micro-scale mismatch locations and natural background information can provide valuable guidance for localized ecological protection and restoration projects. The findings underscore the strengths of conducting assessments of ESs supply–demand at multiple scales, enabling different government levels to enhance effective ecosystem management and prevent misinformation.