Consumption Patterns Research Articles

The Impact of Demographic Transition on Energy Poverty in China: Potential Challenges and Opportunities

Energy poverty is a serious concern and an influential global determinant of subjective well-being (SWB). This paper seeks to explore the impact of demographic transition on energy poverty. Data for the study was obtained through panel data from 30 provinces of China from 2010 to 2022. The old dependency ratio is selected to address the shift in the total population. The negative population growth is anticipated to increase further and may not be easy to reverse. Demographic shifts also cause the gap to widen and alter the patterns of energy consumption. The energy poverty concept is measured through a multidimensional energy poverty index (MEPI) established on five key indicators: electricity consumption, clean cooking fuel like natural gas, telecommunication, heating, and cooling appliances. A Generalized Method of Moments (GMM) estimation technique is used to analyze the impact of the old dependency ratio (ODR) on energy poverty and a fixed effects model is performed to confirm the stability of the results. The outcome reveals that ODR and the demographic transition strongly contribute to worsening energy poverty. Effective policy implications regarding regional disparities among the elderly can change these challenges into opportunities and enhance clean energy access and infrastructure development across all regions.

Parental Drinking Patterns and Adolescent Alcohol Consumption: Considering the Role of Sex and Developmental Stage.

Research indicates that parental behaviors shape adolescents' alcohol consumption, but it is unclear whether mothers or fathers have a more significant impact and how this relationship varies by sex and developmental stage. This study examines the effects of parental alcohol consumption patterns on adolescents in Russia using a large representative sample. The study employs pooled data from the Russia Longitudinal Monitoring Survey-Higher School of Economics (RLMS-HSE) from 2006 to 2019. The final sample included 25 611 cases of adolescents with the available data on their parents (20% male adolescents aged 14-17, 20% female adolescents aged 14-17, 28% male adolescents aged 18-22, and 32% female adolescents aged 18-22; M = 18.22, SD = 2.63). Logistic regression models were used to account for sex and developmental stages. Adolescent drinking was measured as a binary variable indicating drinking at least sometimes, while parental drinking was categorised into five levels, including moderate and excessive consumption. Maternal alcohol consumption patterns were associated with adolescent drinking. Sex differences were observed, with parental drinking patterns showing a greater association with alcohol use for female adolescents. For middle adolescents, a positive association with excessive alcohol consumption by their parents was found. The study emphasises the importance of considering both parents' alcohol consumption patterns when examining adolescent alcohol use, with findings indicating that maternal drinking played a more significant role than paternal drinking. It is crucial to explore this relationship separately for male and female adolescents, considering the stage of adolescence.

Discovering Sustainable Beyond the Food Festivals: A Case Study on the Keuken Food Festival in Bandung

Food festival waste has been a big challenge nowadays. Food festivals that support the culinary tourism industry should give special attention to sustainability and also the awareness of environmental impacts such as the number of foods consumed at the event. Ideally, effective food festival waste management should significantly prevent and reduce that and ensure as much as possible is prevented, reduced, and reused based on Sustainable Development Goals (SDGs). Keuken is one of the most popular food festivals in Bandung, West Java, Indonesia annually held the culinary festival 13 times from the year of 2011 until the 13th event in 2024. The novelty of this study is to discover the contribution and implementation of sustainability beyond the festivals. This study used a descriptive analysis method with a qualitative approach. The findings indicate and also provide valuable best practices and methods to implement Sustainable Development Goals (SDGs) on the food festivals, especially on the 12th goal “Ensure sustainable consumption and production patterns”.

Tangible consumption data landscapes of teenagers

Teenagers are increasingly concerned about clean energy and play a crucial role in driving energy transition. In this study, I investigate how teenagers understand energy consumption, how tangible data mapping through anthropological theories may increase their awareness, and what ideas they may have about how to change habits. I present an approach for designing new data physicalizations, shaping how to facilitate data interaction sessions, and analyzing data physicalization and interactions based on Ingoldian concepts such as the Life of Lines and Imagining for Real. The empirical material includes 1-h sessions in two secondary education schools with 30 teenagers and video-recorded explanations about their consumption habits. The teenagers completed a questionnaire, drew a layout drawing of their home, and built a physical model of their home with products and rooms representing their energy consumption. The data landscapes encouraged participants to explore the perceptual integrity of energy-consuming habits and identify ways to change them. The self-expressive sessions demonstrate that the three data-mapping techniques enable teenagers to recount their daily consumption patterns. In particular, the tangible mapping of Consumption Data Landscapes can open avenues for engagement to increase their awareness of energy consumption and spawn responsibility for a change of habits.

Greenhouse gas emissions (GHGE), water footprint and nitrogen loss associated with food consumption among adults: findings from the updated LEBANese natiONal food consumption survey (LEBANON-FCS)

BackgroundLebanon is grappling with numerous environmental challenges, including water scarcity, landfill waste, deforestation, and rising air pollution. Food choices significantly influence global greenhouse gas emissions and environmental impacts, making it crucial to evaluate the environmental footprints (EFPs) of Lebanon’s current dietary habits. This study aimed to assess food consumption patterns and their EFPs among a nationally representative sample of Lebanese adults.MethodsA cross-sectional survey was conducted from May to September 2022, involving 444 Lebanese adults aged 18 to 64 years. The sample was representative, and participants were distributed across the eight Lebanese governorates. Sociodemographic and medical data were collected via a questionnaire, food consumption was assessed through a validated Food Frequency Questionnaire (FFQ) and two non-consecutive 24-hour recalls, and anthropometric measurements were also taken. EFPs were derived from databases and repositories.ResultsThe typical EFPs of an average Lebanese adult included water usage of 2,862.39 ± 1,617.88 L/day, greenhouse gas emissions of 4.43 ± 2.29 kg CO2-eq/day, and nitrogen use of 12.72 ± 6.76 g/day. Animal products were the primary contributors to greenhouse gas emissions, while vegetable products had the highest water footprint and nitrogen loss impact on the environment. Grains and cereals, the most consumed food category, significantly influenced the water footprint and nitrogen loss. Additionally, meat consumption notably drove greenhouse gas emissions.ConclusionLebanon must address its environmental challenges and the impact of dietary choices on greenhouse gas emissions and EFPs. By evaluating and understanding the environmental consequences of current dietary patterns, Lebanon can take proactive steps towards promoting sustainable food practices and mitigating environmental degradation.

Impact of Direct Contact and Ingestion of Selected Insecticides on the Predator Harmonia axyridis of Citrus Psyllids

The Asian citrus psyllid, Diaphorina citri, serves as the primary vector for Huanglongbing (HLB) by transmitting Candidatus Liberibacter asiaticus. Lambda-cyhalothrin and thiamethoxam are commonly employed for the control of D. citri. The multicolored Asian lady beetle, or harlequin ladybird, Harmonia axyridis, is an important predator of D. citri in both greenhouse and field settings. The effectiveness of integrated pest management (IPM) relies on the judicious use of selective insecticides that minimize harm to natural enemies. However, the effects of these insecticides on H. axyridis’ predation of D. citri remain thoroughly unexplored. In this study, we assessed the toxicity of lambda-cyhalothrin and thiamethoxam to H. axyridis and examined their impact on the functional response of this predator to D. citri using direct contact exposure methods. We also evaluated the indirect effects on predator voracity through ingestion exposure. Our results demonstrated that exposure to both insecticides at LC50 concentrations significantly prolonged the developmental durations of H. axyridis larval stages. The type-II functional response model effectively described the prey consumption patterns of H. axyridis, revealing a significant reduction in predation capacity across all life stages, particularly among second instar larvae, which experienced reductions of 85.30% and 88.58% following lambda-cyhalothrin and thiamethoxam treatments, respectively. Furthermore, H. axyridis’ predation significantly declined when feeding on D. citri contaminated at LC50 concentrations. These findings indicate that lambda-cyhalothrin and thiamethoxam adversely affect the predation of H. axyridis, both via direct contact and ingestion. Evaluating the potential impacts of these insecticides on H. axyridis is critical for the development of effective IPM strategies targeting D. citri.

Cross-Sectional Analysis of Household Food Demand in Estuaire Gabon: A Near-Ideal Quadratic Demand System Approach

Gabon depends heavily on food imports to safeguard its food security; yet household food consumption patterns remain underexplored. This study investigates the structure of food demand in the Estuaire region, incorporating demographic determinants such as the age of the household head, household size, youth proportion, and residential distance from shopping centers. Using primary data collected from a randomized survey of 410 households, the analysis employs the Quadratic Almost Ideal Demand System (QUAIDS) model to estimate expenditure and price elasticities. The results indicate that expenditure elasticities are universally positive, with luxury items, including meat, eggs, and fish, exhibiting greater sensitivity compared to staple foods such as poultry, oil, rice, cassava, and bananas, which display inelastic demand. Price elasticities for meat, poultry, fish, eggs, and rice are negative, adhering to the law of demand. Demographic factors, including education, age, and residential location, significantly influence the consumption of meat, cassava, bananas, and oil. Household size, employment type, and youth composition also emerge as critical determinants of increased demand for poultry, fish, and rice. These findings offer policy-relevant insights to strengthen food security and address socioeconomic disparities.

Blood-based epigenome-wide association study and prediction of alcohol consumption

Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait. Here, we explore the epigenetic architecture of self-reported weekly units of alcohol consumption in the Generation Scotland study. We first create a blood-based epigenetic score (EpiScore) of alcohol consumption using elastic net penalized linear regression. We explore the effect of pre-filtering for CpG features ahead of elastic net, as well as differential patterns by sex and by units consumed in the last week relative to an average week. The final EpiScore was trained on 16,717 individuals and tested in four external cohorts: the Lothian Birth Cohorts (LBC) of 1921 and 1936, the Sister Study, and the Avon Longitudinal Study of Parents and Children (total N across studies > 10,000). The maximum Pearson correlation between the EpiScore and self-reported alcohol consumption within cohort ranged from 0.41 to 0.53. In LBC1936, higher EpiScore levels had significant associations with poorer global brain imaging metrics, whereas self-reported alcohol consumption did not. Finally, we identified two novel CpG loci via a Bayesian penalized regression epigenome-wide association study of alcohol consumption. Together, these findings show how DNAm can objectively characterize patterns of alcohol consumption that associate with brain health, unlike self-reported estimates.

Modeling and Prediction of Demand Response Based on Deep Quantum Neural Networks

Demand Response (DR) plays a crucial role in modern power networks, addressing the challenges posed by increasing renewable energy integration, grid modernization, and sustainability goals. By modifying electricity consumption patterns in response to signals such as price fluctuations or grid conditions, DR helps balance supply and demand on the grid, reduce peak demand, alleviate grid congestion, and integrate renewable energy resources more effectively. However, effective DR strategies require accurate modeling and prediction of DR behavior. In this research, a novel modeling and prediction strategy for DR that integrates deep learning and quantum computing principles is proposed. The approach involves two main phases: preprocessing and prediction. During preprocessing, input data undergo normalization using an improved Z-score technique. Subsequently, the normalized data are processed by the Modified Deep Quantum Neural Network (MDQNN) model during the prediction phase. MDQNN, an enhanced version of Deep Quantum Neural Networks (DQNN), employs angle encoding to enhance prediction accuracy by effectively identifying patterns. The efficacy of this strategy is demonstrated through comprehensive analyzes, highlighting its potential to enhance DR prediction accuracy and contribute to the advancement of power network optimization and sustainability objectives.

Business Intelligence and Artificial Intelligence for Sustainable Business Operations

In the modern business landscape, sustainability has become a fundamental goal for organizations, driven by growing environmental concerns, social responsibility, and the need for long-term profitability (Bocken et al., 2014). Companies are under increasing pressure to reduce their environmental footprint, optimize resources, and improve operational efficiency, all while maintaining competitiveness. Business Intelligence (BI) and Artificial Intelligence (AI) have emerged as key technologies in this transition, offering organizations the ability to make data-driven decisions that promote sustainability (Chen et al., 2020). BI encompasses tools and techniques that convert raw data into actionable insights, helping businesses optimize operations and minimize waste (Shollo & Galliers, 2016). On the other hand, AI, particularly machine learning and predictive analytics, enhances decision-making by forecasting trends, automating processes, and providing deeper insights into complex datasets (Jeble et al., 2020). This article explores the integration of BI and AI in driving sustainable business operations. It examines their individual contributions and the synergistic benefits they bring when combined. Key applications discussed include energy management, where BI helps track energy consumption patterns, and AI optimizes resource allocation to minimize waste (Kemp et al., 2021). In supply chain optimization, BI analyzes supplier performance and inventory levels, while AI forecasts demand and automates processes to reduce carbon footprints (Saghafian et al., 2020). Waste reduction efforts are enhanced through predictive analytics, which help anticipate production needs and reduce excess output (Karim et al., 2021). Environmental monitoring, powered by AI and IoT sensors, allows for real-time analysis of environmental conditions, ensuring compliance with sustainability standards (Khan et al., 2021). However, the implementation of these technologies also presents challenges. Data integration remains a significant barrier, as companies often face difficulties in harmonizing large datasets from disparate sources (Laudon & Laudon, 2019). The initial investment in BI and AI technologies can be high, making it difficult for small and medium-sized enterprises (SMEs) to adopt these solutions (Zhang et al., 2020). Additionally, a shortage of skilled professionals in data science and AI poses another challenge, limiting the effective use of these technologies (Brynjolfsson & McAfee, 2014). Despite these challenges, the potential of BI and AI to foster sustainable business operations is substantial, and overcoming these barriers will be key to unlocking their full potential. The article concludes by discussing strategies for successful implementation and the future outlook for BI and AI in sustainable business practices.

Energy Efficiency and Sustainable Energy Use in Chaff Cutters: A Comprehensive Review and Future Directions

The increasing need for agricultural equipment that has less environmental impact has led to energy efficiency and sustainable energy use becoming essential considerations in the design and operation of chaff cutters. Chaff cutters, which are mainly utilized within the agricultural industry for chopping straw, hay, and other plant material, can be highly energy-intensive. In this paper, we discuss the existing energy consumption patterns in conventional chaff cutters, emphasize the role of energy efficiency, and examine alternative and renewable energy sources for sustainable operation. We examine design enhancement, energy-saving innovations, and techniques for optimizing energy consumption. Additionally, we introduce models and strategies for boosting efficiency in chaff cutters, with an emphasis on practical applications for smallholder farmers and large-scale agriculture. ________________________________________ Key Words: energy, efficiency, chaff, design

Abnormality Detection Using Power Rising and Descending Signature (PRIDES)

This paper presents a new paradigm for abnormality detection using a novel power signature that characterizes the rising and descending patterns of energy consumption. The proposed methodology includes a low-overhead power signature generation circuit, computation-light analysis methods, and optimal generation of the golden signature used in the analysis. The proposed power signature generation circuit is designed using 90 nm CMOS technology, and its operation is validated via circuit simulations. The effectiveness of the proposed method in detecting the insertion of potentially malicious code is demonstrated with data obtained from hardware experiments and circuit simulations.

The synergies of air quality monitoring program: Information disclosure and pollution control.

To deal with the increasingly severe climate crisis and environmental pollution, China launched a nationwide real-time air quality monitoring program in three batches, a milestone moment in its environmental governance history. Using the time-varying difference-in-differences model, this study explores the synergies of this program across 284 cities from 2009 to 2019. The findings are as follows: (1) With environmental information disclosed, the national air quality monitoring program can reduce the outdoor fine particulate matter concentration by an overall effect of 3.31%, equivalent to an almost 1% reduction calculated by its average value. (2) This program can enhance public environmental attention and stimulate environmental practitioners' employment, thereby achieving a synergistic effect on air pollution reduction. (3) The pollution reduction effect is expected to be more pronounced in cities located in the southern and eastern regions, cities with higher population densities, and cities with favourable ventilation capabilities. (4) In response to air pollution problems, the public will adjust their daily consumption patterns to avoid potential health risks. As a result of the short-term behavioural changes, they will be more willing to pay for clean air by purchasing household air purifiers. This study highlights the considerable ecological and economic benefits of environmental information disclosure, thus further contributing to future eco-friendly and sustainable development.

Emotional priming for sustainable consumption? The effects of social media content on the valuation of chocolate

Abstract Current consumption patterns in the Global North are unsustainable across environmental, social, and economic dimensions. To promote more sustainable consumer behavior, emotional priming on social media has become an increasingly popular tool. In this paper, we mimic social media content to test the effectiveness of emotional priming in incentivizing sustainable consumption. Specifically, we examine whether emotionally primed information about sustainability aspects in cocoa production increases consumers’ valuation for sustainably produced products in the short and medium term. To achieve this, we conducted an online panel survey of 2,161 German consumers with random assignment to one of four different treatments (unprimed information or information with emotional prime) designed as social media posts (videos). We differentiate between environmental sustainability and social responsibility, and separate the products into sustainability certification, uncertified claims, and conventional chocolate. We find statistically significant positive effects of the emotional primes on consumers’ willingness-to-pay (WTP) for products with sustainability certifications and non-certified sustainability claims in the short term. These effects can be attributed to negative emotions triggered by the primes. Two weeks after the treatments, the WTP decreases for all groups. The difference in WTP between the primed and unprimed groups diminishes in the medium term. Primed participants value sustainability certifications and claims less than those who received unprimed information.

Household dietary diversity and associated factors in rural and peri-urban areas of Mbale District, Eastern Uganda

BackgroundGlobally, the importance of dietary diversity in addressing malnutrition and promoting overall health is increasingly being recognized. However, increasing urbanization has led to shifts in dietary preferences, food consumption patterns, and a greater reliance on less nutritious processed foods. Efforts to address these challenges have been futile, as nutrition in peri-urban areas often receives less attention, with food and nutrition insecurity typically seen as a rural issue. This study, therefore, examined dietary diversity (DD) and its socio-economic and demographic predictors in rural and peri-urban households.MethodsA cross-sectional study of 221 households in rural and peri-urban Eastern Uganda collected data on DD, socio-economic and demographic factors using the Household Dietary Diversity Score (HDDS) and structured questionnaires, respectively. The data were analyzed in SPSS using descriptive statistics, and independent sample t-tests compared mean DD scores between rural and peri-urban areas. Pearson Chi-square tested differences in food group consumption, while binary logistic regression in STATA identified socio-economic and demographic predictors of household dietary diversity.ResultsThere was no significant difference in dietary diversity (DD) between rural and peri-urban households, with mean DD scores of 6.64 ± 1.60 and 6.55 ± 1.30, respectively, indicating a medium level in both areas. However, significant differences were observed in the consumption of cereals and roots/tubers/plantains (p < 0.05), while intake of animal-source foods and fruits remained generally low across both settings. In rural areas, household DD was significantly influenced by the education levels of the household head (β: -1.276) and spouse (β: -1.123), as well as access to credit (β: 1.136), while in peri-urban areas, average monthly income (β: -0.801) was a significant predictor of household DD.ConclusionThe study showed that dietary diversity was similar and at a medium level in both rural and peri-urban households, and mainly consisted of plant-based foods, with limited consumption of fruits and animal-sourced foods. Socio-economic factors, including level of education, access to credit, and income, significantly influenced DD. These results highlight the role of socio-economic and demographic factors in shaping household diets and underscores the need for targeted interventions to improve dietary diversity and address nutritional gaps in the study area.

Optimalisasi DMA IAIN untuk Menurunkan Kehilangan Air pada di Perumda Air Minum Tirta Giri Nata Kota Cirebon

District Meter Area (DMA) of IAIN has not compliance the National Non Revenue Water (NRW) target of 25% from January-December 2023. The NRW of DMA IAIN in 2023 is 44.38%. This research aims to analyse the existing conditions, identify causes of NRW, and arrange recommendations for the optimize DMA to reduce water loss. The analysis is analysing the water consumption pattern, water balance, Infrastructure Leakage Index (ILI) and Strength Weakness Oportunity Threats (SWOT) method. This DMA has fulfilled ideal condition except the division of subDMAs, the implementation of hydraulic modelling, and the implementation of IoT. There is an indication of leakage in the pipeline based on the pressure-discharge graph. The water loss is 44.26%. The ILI is 0 or good category (A1). The ATR performance indicator is 501 L/connection/day or very bad category (D). The DMA optimisation strategies to reduce and control water loss are planning alternative financial support, forming subDMA, applying Epanet for hydraulic modelling, installing loggers and SCADA as implementation of IoT, revitalising pipes and customer meters that has &gt;10 years of technical age, finding active leaks such as executing step test, arranging water loss reduction and control SOP, ensuring the assets safety, and updating GIS data.

Abstract

In 2013 excavation works were undertaken at the location of the former Canongate Charity Poorhouse (or workhouse) on the New Waverley development site, at the junction of Calton Road and Old Tolbooth Wynd, Canongate, Edinburgh. The excavation revealed development of the site from the initial cultivation of the ‘backlands’ in the 12th/13th centuries to the construction of the Poorhouse in 1761. A sequence of buried garden soils/middens relating to pre-18th-century activity was recorded, in addition to the remains of a single burgage plot boundary and associated rig and furrow deposits. Substantial structural features related to the 18th-century Poorhouse were revealed, including sandstone walls with wooden plank and pinion foundation rafting. Seven burials of probable late 17th-/early 18th-century date associated with the Canongate Kirk were recorded along the site’s southern boundary (an eighth had been encountered in 1997). A rich artefact and ecofact assemblage was recovered from the soils and midden deposits, including imported fine glassware. The ceramic assemblage included Scottish White Gritty Ware (SWGW), Scottish Post-medieval Reduced Ware (SPMRW) and Scottish Post-medieval Oxidised Ware (SPMOW), together with high-status imported material such as a Spanish gaming piece and a rare German stove tile. Consumption patterns revealed by the artefact evidence appear to reflect the high status of the Canongate’s inhabitants prior to the greater development of the site during the 18th century. The creation of the Poorhouse stands in stark contrast to this, revealing the changing fortunes of this part of post-medieval Edinburgh.

Appendices

In 2013 excavation works were undertaken at the location of the former Canongate Charity Poorhouse (or workhouse) on the New Waverley development site, at the junction of Calton Road and Old Tolbooth Wynd, Canongate, Edinburgh. The excavation revealed development of the site from the initial cultivation of the ‘backlands’ in the 12th/13th centuries to the construction of the Poorhouse in 1761. A sequence of buried garden soils/middens relating to pre-18th-century activity was recorded, in addition to the remains of a single burgage plot boundary and associated rig and furrow deposits. Substantial structural features related to the 18th-century Poorhouse were revealed, including sandstone walls with wooden plank and pinion foundation rafting. Seven burials of probable late 17th-/early 18th-century date associated with the Canongate Kirk were recorded along the site’s southern boundary (an eighth had been encountered in 1997). A rich artefact and ecofact assemblage was recovered from the soils and midden deposits, including imported fine glassware. The ceramic assemblage included Scottish White Gritty Ware (SWGW), Scottish Post-medieval Reduced Ware (SPMRW) and Scottish Post-medieval Oxidised Ware (SPMOW), together with high-status imported material such as a Spanish gaming piece and a rare German stove tile. Consumption patterns revealed by the artefact evidence appear to reflect the high status of the Canongate’s inhabitants prior to the greater development of the site during the 18th century. The creation of the Poorhouse stands in stark contrast to this, revealing the changing fortunes of this part of post-medieval Edinburgh.

Acknowledgements

In 2013 excavation works were undertaken at the location of the former Canongate Charity Poorhouse (or workhouse) on the New Waverley development site, at the junction of Calton Road and Old Tolbooth Wynd, Canongate, Edinburgh. The excavation revealed development of the site from the initial cultivation of the ‘backlands’ in the 12th/13th centuries to the construction of the Poorhouse in 1761. A sequence of buried garden soils/middens relating to pre-18th-century activity was recorded, in addition to the remains of a single burgage plot boundary and associated rig and furrow deposits. Substantial structural features related to the 18th-century Poorhouse were revealed, including sandstone walls with wooden plank and pinion foundation rafting. Seven burials of probable late 17th-/early 18th-century date associated with the Canongate Kirk were recorded along the site’s southern boundary (an eighth had been encountered in 1997). A rich artefact and ecofact assemblage was recovered from the soils and midden deposits, including imported fine glassware. The ceramic assemblage included Scottish White Gritty Ware (SWGW), Scottish Post-medieval Reduced Ware (SPMRW) and Scottish Post-medieval Oxidised Ware (SPMOW), together with high-status imported material such as a Spanish gaming piece and a rare German stove tile. Consumption patterns revealed by the artefact evidence appear to reflect the high status of the Canongate’s inhabitants prior to the greater development of the site during the 18th century. The creation of the Poorhouse stands in stark contrast to this, revealing the changing fortunes of this part of post-medieval Edinburgh.

References

In 2013 excavation works were undertaken at the location of the former Canongate Charity Poorhouse (or workhouse) on the New Waverley development site, at the junction of Calton Road and Old Tolbooth Wynd, Canongate, Edinburgh. The excavation revealed development of the site from the initial cultivation of the ‘backlands’ in the 12th/13th centuries to the construction of the Poorhouse in 1761. A sequence of buried garden soils/middens relating to pre-18th-century activity was recorded, in addition to the remains of a single burgage plot boundary and associated rig and furrow deposits. Substantial structural features related to the 18th-century Poorhouse were revealed, including sandstone walls with wooden plank and pinion foundation rafting. Seven burials of probable late 17th-/early 18th-century date associated with the Canongate Kirk were recorded along the site’s southern boundary (an eighth had been encountered in 1997). A rich artefact and ecofact assemblage was recovered from the soils and midden deposits, including imported fine glassware. The ceramic assemblage included Scottish White Gritty Ware (SWGW), Scottish Post-medieval Reduced Ware (SPMRW) and Scottish Post-medieval Oxidised Ware (SPMOW), together with high-status imported material such as a Spanish gaming piece and a rare German stove tile. Consumption patterns revealed by the artefact evidence appear to reflect the high status of the Canongate’s inhabitants prior to the greater development of the site during the 18th century. The creation of the Poorhouse stands in stark contrast to this, revealing the changing fortunes of this part of post-medieval Edinburgh.