The objective of this research was to evaluate the unit generation rate of solid hospital waste at the Gustavo Lanatta Lujan Bagua Support Hospital (HAB). The calculations were based on the weights of hospital waste disposed periodically to the biosafety cell located 7 km from the city of Bagua since 2015. Nineteen services were identified and grouped into three areas: hospitalization area, emergency area and gynecology area, studied according to the group classification of Peruvian regulations. The results show that 92.77 kg/day-1 are generated, 62.26 % are biocontaminated waste, 26.45 % are common waste, 7.7 % are sharp-sharp waste and 3.6 % are special waste. It was also found that only 73.56 % is disposed of in the hospital's biosafety cell. In this sense, this study will contribute to promote the reduction of the entry of hazardous substances into the stream of an adequate waste management and save workers and the environment in the Amazon Region. Therefore, awareness should be raised at all levels of society through various means of communication and education, so that the risks of spreading health hazards can be minimized by improving hospital waste management. In addition, healthcare waste management should be implemented, taking into account the parameters to be monitored, the economic resources to be managed and the national plans for healthcare waste.

The objective of this research was to evaluate the unit rates of MSW generation in Cumba in the years 2016 and 2022. The calculations were based on the weights of the MSW disposed in the dump located 5 km from the city of Cumba since 2012. The GPC, physical composition, density, humidity were determined in the years 2016 and 2022, studied according to the methodology and group classification of Peruvian regulations. The results show that 5.45 Tn/day−1 are generated in 2016, 4.37 Tn/day−1 in 2022; according to its physical composition, 82% RO, 14% MICVC and 4% MISVC in 2016; 77% RO, 16% MICVC, 7% MISVC in 2022; density 137.90 kg/m−3 in 2016 and 172.69 kg/m−3 in 2022; humidity 67.67% in 2016 and 63.43% in 2022. It was also found that in 100.00% there is no solid waste treatment; Everything generated in homes, businesses and streets is evacuated to the final disposal site, which is a dump. In 2022, Cumba acquired 10 hectares to have adequate sanitary infrastructure and begin the closure and recovery of its current dump. This study will contribute to providing accurate data on MSW generation that allows the local government to promote the optimization of collection routes and schedules, resulting in cost savings and reduction of carbon emissions in the Amazon Region. Therefore, it is necessary to raise awareness at all levels of society through various means of communication and education, so that the risks of spreading health risks can be minimized by improving MSW management.

Tourism in biodiversity-rich regions was among the sectors most severely disrupted by the COVID-19 pandemic, which amplified existing socioeconomic vulnerabilities and placed cultural and natural heritage conservation at risk. In the Peruvian Amazon, Bagua Province illustrates this challenge, where experiential tourism is central to local livelihoods yet lacks adaptive management tools to support a sustainable recovery. To address this gap, this study introduces an integrated approach that combines artificial intelligence with biodiversity conservation through the application of multilayer perceptron (MLP) neural networks. By analyzing two decades of domestic visitor data (2003–2023), the research explores how predictive modeling can inform tourism governance in fragile ecosystems. Two scenarios were evaluated: one incorporating the complete dataset and another excluding the anomalous year 2020, heavily disrupted by the pandemic. The findings show that MLP models are capable of capturing visitor dynamics and forecasting demand fluctuations with notable accuracy. This predictive capacity allows for more adaptive planning of ecologically sensitive sites, such as the Tsunsuntsa Waterfall, where balancing visitor inflows with ecological thresholds is essential to preventing overtourism. Beyond technical accuracy, the study highlights the strategic potential of artificial intelligence as a governance tool that strengthens resilience in post-pandemic contexts, offering actionable insights for harmonizing socioeconomic recovery with biodiversity preservation. By positioning neural networks as vital instruments for sustainable destination management, this research contributes a reproducible model that can be adapted to other vulnerable regions worldwide. It underscores the value of integrating advanced computational methods into tourism governance frameworks, ultimately bridging technology and conservation to foster long-term sustainability.

Background Peru presents a paradigmatic case of hydrological asymmetry, where national water abundance (56,887 m 3 /capita/year) masks acute regional scarcity. The Pacific basin, hosting 66.4% of the population, possesses only 1.9% of renewable water resources (1,628 m 3 /capita/year), falling below the Falkenmark water stress threshold (1,700 m 3 /capita/year). Conversely, the Amazon basin holds 97.8% of resources for 30.4% of the population (183,142 m 3 /capita/year). This 112.5-fold asymmetry ratio exceeds comparable international cases (Egypt: 49.2; China: 8.0), yet Peru lacks systemic redistribution mechanisms. Policy and Implications Current governance frameworks under Law 29338 (2009) have failed to address territorial misalignment between supply, demand, and institutional capacity. Economic compensation mechanisms (S/205.5 million annually) paradoxically tax scarcity rather than value ecosystem services, with the Pacific basin contributing 61.7% of revenues despite extreme resource constraints. Groundwater extraction in coastal regions operates at 100% of renewable recharge limits, indicating unsustainable fossil aquifer mining. Climate projections indicate 30% runoff reduction in glacier-fed Pacific basins by 2100, exacerbating existing stress. Recommendations (1) Implement basin-scale demand management and irrigation efficiency programmes in the Pacific basin; (2) Strengthen groundwater monitoring and abstraction controls to prevent irreversible depletion; (3) Reform economic compensation mechanisms to incorporate ecosystem service valuation, redistributing revenues toward hydrologically strategic headwater regions; (4) Integrate indigenous water governance systems (comunidades campesinas, ayllus) into state planning frameworks; (5) Establish inter-basin transfer feasibility studies given the extreme asymmetry ratio. Conclusions Peru’s water challenge stems from governance asymmetry layered upon hydrological asymmetry, not absolute scarcity. Without institutional mechanisms reconciling hydrology, demography, and political economy, climatic variability will entrench coastal scarcity while Amazonian abundance remains underutilised. The integrated assessment framework presented provides transferable insights for water-rich yet spatially asymmetric nations facing increasing climatic variability.

Rapid urbanisation in Amazonian riverine cities poses persistent challenges for sustainable municipal solid waste (MSW) management, where hydrological connectivity amplifies environmental risks. This study establishes a baseline indicator framework for Bagua, Peru—a high-density city adjacent to the Utcubamba River—using stratified characterisation data (n=115 units, 920 observations) from March–April 2016, complemented by operational landfill data (2018–2023). The citywide MSW generation rate was 0.570±0.043 kg/capita/day, with pronounced organic waste dominance (64.9±4.1%). Spatial analysis identified marked service inequalities: collection coverage declined from 98.5% in the urban core to 45% in riverside informal settlements, with an estimated 3.11 tonnes/day of uncollected waste discharged directly to the Utcubamba River. Despite Peru's Circular Economy Law (DL 1501/2020), valorisation rates stagnated below 5% through 2023. By framing MSW characteristics as sustainability indicators conceptually aligned with SDG monitoring frameworks, this study provides a transferable analytical approach for decentralised circular economy strategies in riverine cities across the Global South.