To support environmental management and differentiated green transformation in industrial parks, this study develops an evaluation framework that assesses eco-industrial development performance and identifies park-specific strengths and weaknesses. The framework contains 39 indicators across economic development, ecological environment, material circulation, resource potential, technological innovation, and policy and management. Weights are derived using the Attribute Hierarchical Model (AHM) and coefficient of variation method, integrated via the minimum-deviation principle, and applied through multi-level grey evaluation to four Chinese parks. Findings show that policy and management is weighted highest, followed by economic development and ecological environment; overall performance ranks Tianjin, Suzhou, Dalian, and Fushun. Critically, similar aggregate performance masks distinct weaknesses in environmental governance, resource circulation, technological innovation, and resource conditions. The framework therefore enables diagnosis of differentiated management priorities and supports park-specific pathways toward eco-industrial development.
To restore a stream to a more natural condition and still minimize flooding and erosion, the optimal longitudinal bed slope and meander sinuosity are needed. A straight channel can reduce flooding but cause excessive velocity and concomitant bed degradation, incision, and riverbank collapse. Conversely, a highly meandering channel will have slower velocity but higher flow depths that can lead to flooding. A meandering channel provides for the diversity of habitat needed for the ecosystem to be healthy. Balancing these needs can be difficult. To aid in the selection of bed slope and sinuosity, the optimal slope was found here using a multi-objective optimization formulation that minimizes both flooding and erosion. The Pareto front was established and the closest point to the origin of zero depth and velocity was the optimal combination of these two inversely proportional variables. It was found that, for a wide range of channel roughness, width, and flow values, a slope of approximately 0.0002-0.0004 was desirable.
Purpose-built student accommodation (PBSA) is characterised by prolonged residential occupancy, compact spatial arrangements and managed building systems. Yet comparatively little evidence addresses how residents understand indoor air quality (IAQ) determinants and prioritise monitoring and mitigation. This exploratory cross-sectional case study examined occupants’ perceptions of environmental and building-related IAQ determinants, awareness of IAQ monitoring technologies, endorsement of mitigation strategies, and overall self-rated IAQ in a near-road PBSA in Bolton, United Kingdom. Seventy-seven survey records were returned, with two respondents under 18 years who provided no substantive IAQ responses, leaving 75 complete cases. Composite scores showed satisfactory internal consistency for environmental-determinant recognition (α = .841), building-related determinant recognition (α = .708), monitoring awareness (α = .838) and mitigation-strategy endorsement (α = .950). Respondents generally recognised the listed determinants and supported the mitigation strategies, and monitoring-awareness scores were positively correlated with mitigation endorsement. In a multiple linear regression, the three predictors jointly explained 63.5% of the variance in mitigation-strategy endorsement (R² = .635; adjusted R² = .620). Residual diagnostics indicated heteroscedasticity, so HC3 robust inference was used. Monitoring awareness showed the strongest independent association with mitigation endorsement (standardised β = .434, p < .001), followed by building-related determinant recognition (β = .292, p = .004). The environmental-determinant association was positive but borderline under robust inference (β = .205, p = .053). Overall self-rated IAQ was analysed separately and was not the dependent variable in this regression. The study therefore contributes context-specific evidence on occupant IAQ awareness and management priorities. Future multi-site research should combine occupant surveys with direct environmental and ventilation measurements.
This study examines the prevalence of tobacco use in African countries in 2025. The study finds that Africa’s total population increased from 910.84 million in 2006 to 1.527 billion in 2025. The study finds that while tobacco use rates are relatively lower in African countries when compared with countries outside of Africa, the rates are relatively higher in Southern and Northern Africa. Of the 930.5 million people aged 15 and over in Africa in 2025, 86.1 million (9.3%) used tobacco. Of the 86.1 million people aged 15 and over who used tobacco in 2025, 31,795,580 (36.9%) were in Northern Africa; 23,244,942 (27%) were in Eastern Africa; 12,105,792 (14.1%) were in Western Africa; 9,923,250 (11.5%) were in Southern Africa; and 9,015,348 (10.5%) were in Middle Africa. Of the 295,297,616 people aged 15 and over in Eastern Africa in 2025, 23,244,942 (7.9%) used tobacco; 31,795,580 (17.4%) out of 182,349,569 in Northern Africa; 9,923,250 (19.6%) out of 50,665,515 in Southern Africa; 12,105,792 (4.4%) out of 276,301,670 in Western Africa; and 9,015,348 (7.2%) out of 125,839,154 in Middle Africa. The top 10 countries in Africa with the highest tobacco use rates are as follows: Egypt, 25.8%, Madagascar, 24.1%, Algeria, 21.4%, Lesotho, 22.8%, Seychelles, 20.5%, South Africa, 20.1%, Mauritius, 19.6%, Tunisia, 19%, Botswana, 17.1%, and the Republic of Congo, 15.8 percent. The factors presented in the study for the prevalence of tobacco use in Africa are as follows: sex/gender, age, population growth, increase in the GDP of African countries, increase in wealth, climate/weather, educational attainment, tourism, region, and religion/religiosity.
Brazil's ABC+ Plan sets, for each of ten low-carbon agricultural technologies, two parallel 2030 targets: a physical target (area, herd size, or adoption volume) and a climate target (Mg CO2 equivalent mitigated). Regional climate-target figures are official accounting estimates from predetermined emission factors applied to observed adoption, not independently measured outcomes. This study assesses the regional consistency and methodological robustness of this official accounting -- not the Plan's actual mitigation effectiveness -- by structuring official data on adoption, expansion, accounted mitigation, and financing across Brazil's five macro-regions (2020-2025), interpreted through a narrative literature review. Because technologies differ in physical unit, mitigation pathway, and time horizon, cross-technology comparisons are presented as descriptive accounting patterns, not a common performance metric; regional shares reflect distribution, not region-specific effectiveness. Results show systematic divergence between physical- and climate-target attainment within most technologies -- 3.3-fold for integrated crop-livestock-forestry and 4.3-fold for agroforestry systems, for example -- and that four biophysically distinct technologies share one fixed accounting coefficient (3.79 Mg CO2eq ha-1 yr-1). Rural credit shows no clearly expressed proportional relationship with accounted mitigation for any technology. We conclude the accounting would benefit from technology-specific emission factors, region-adjusted benchmarks, and greater transparency, and that validating these estimates against field-measured mitigation remains an open task.
