International Journal of Environment and Climate Change

Waste-to-Energy Conversion: Electricity Generation and Economic Feasibility of a Food Processing Waste-Based Biogas Power Plant

2026-08-12T12:46:02+00:00

The increasing generation of food-processing waste and rising energy demand necessitate sustainable waste-management and renewable-energy solutions. This study evaluated electricity generation from food-processing waste through anaerobic digestion and assessed the economic and environmental performance of an operating biogas power plant. The facility had a design capacity of 500 m³ and processed approximately 8 tonnes of food waste per day. Purified biogas was supplied to a generator producing three-phase electricity at 415 V and 50 Hz. Electricity-meter readings were recorded over 90 days, and the generated power was used for conveying, heating, size reduction, drying, lighting, and supplementary plant operations. Average electricity generation was 645.58 kWh per day, with only modest variation among the nine 10-day observation intervals. The total project cost was reported as ₹8,000,000, while annual revenue from electricity substitution and organic manure was ₹5,490,000. After accounting for the stated operation, maintenance, and auxiliary costs, the reported payback period was approximately 2.1 years. Fuel-equivalent calculations indicated potential reductions in the use of fuelwood, kerosene, diesel, liquefied petroleum gas, charcoal, soft coke, furnace oil, and purchased electricity. The findings indicate that anaerobic digestion can support energy recovery and waste management in food-processing facilities. However, the economic and environmental outcomes remain dependent on the assumptions used and require plant-specific validation.

Determinants of Climate Change Preparedness Behaviour among Women Dairy Farmers in Haryana, India

2026-08-12T12:51:43+00:00

Climate change creates major challenges for dairy production by disrupting livestock productivity, forage availability, water resources, and animal health. Therefore, preparedness is crucial for protecting dairy-related livelihoods from climate change. This study examines climate change preparedness among women dairy farmers in Haryana and identifies key factors that influence their ability to adapt. A total of 360 women respondents from 18 villages in the Karnal, Hisar, and Sirsa districts were surveyed using a random sampling method. Preparedness was measured using a structured scale of climate-resilient dairy management practices, and the underlying factors were analysed using Ordinary Least Squares (OLS) regression. The results show a moderate level of preparedness among respondents. Specifically, 45.00% demonstrated medium preparedness, 33.33% had low preparedness, and only 21.67% had high preparedness. The regression analysis revealed that preparedness was significantly associated with several socio-economic factors, such as family education, landholding, dairy farming experience, and resource control. Access to information, including extension contacts, mass media, and climate data, and cognitive traits such as risk orientation, climate awareness, and proactive attitudes also played significant roles. These findings point to the urgent need to strengthen climate information services, broaden extension support, and implement capacity-building programmes that enhance women’s knowledge and access to agricultural resources.

Climate Change Risk Meets Resource Inefficiency: A Multi-method Assessment of Thanjavur's Rice Economy

2026-08-13T10:00:32+00:00

Rice cultivation in Thanjavur district faces interacting climatic, water, labour, and production-efficiency constraints. This study assessed these dimensions through an integrated multi-method framework. Primary data were collected from 120 rice farmers between October 2025 and February 2026. Climatic vulnerability was evaluated using an exposure–sensitivity–adaptive capacity framework; crop water requirements and water footprints were estimated with CROPWAT 8.0; technical and resource-use efficiency were analysed with a Cobb–Douglas stochastic frontier production function; economic water-use efficiency was calculated from output value and irrigation use; and farmer-perceived constraints were prioritised using Garrett ranking. The normalised Climate Vulnerability Index was 0.359, indicating moderate vulnerability. Exposure (0.575) and sensitivity (0.690) were high, while adaptive capacity was moderate (0.442). The total water footprint of rice was 2,154 m³/tonne, of which blue water contributed 66.7%, green water 24.5%, and grey water 8.8%. The stochastic frontier model produced a gamma value of 0.8755, indicating that technical inefficiency accounted for most composite-error variation. Labour had the largest significant elasticity (β = 0.4500), while seed had a smaller significant positive effect (β = 0.0978). Economic water-use efficiency was ₹12.50/m³. Labour shortage ranked first among farmer-perceived constraints, followed by low product prices and delayed input availability. The findings indicate that interventions should jointly address management efficiency, labour scarcity, water use, market conditions, and climate adaptation.

An Analysis of Climate Variables in Cameroon from 1961 to 2020

2026-08-13T13:02:53+00:00

This article addresses climate variability in Cameroon by analysing decadal trends in selected climate parameters and their relationships during 1961–2020. Satellite and reanalysis data were obtained from the Agency for Air Navigation Safety in Africa and Madagascar (ASECNA). Python 3, Panoply, Climate Data Operators (CDO) and Ubuntu-based tools were used to assess decadal changes in air temperature, precipitation, sea surface temperature (SST) and wind, as well as selected relationships using the Mann-Kendall test and Pearson correlation. The results show progressive warming across most regions, becoming widespread from the 2000s, together with a gradual increase in SST in the maritime zone. Precipitation shows contrasting spatiotemporal dynamics across decades, although the 1991–2000 decade indicates a notable return of rainfall in several areas. Prevailing winds remain relatively stable in the low-level atmospheric circulation pattern, corresponding to the West African monsoon flow, with slight variations during 2001–2010. The relationship between precipitation and SST is generally positive but moderate, while the relationship between precipitation and air temperature shows strong spatiotemporal variability, including both positive and negative correlations. These findings indicate marked variability in Cameroon’s climate system and highlight the need for continued monitoring of regional climate dynamics to support climate-sensitive socioeconomic activities and adaptation planning.

Phenophase-wise Crop Weather Calendar Development and Satellite-based Validation for Paddy in the Tungabhadra Command Area

2026-08-14T09:09:33+00:00

A study was conducted during 2024–2025 at the Krishi Vigyan Kendra (KVK), Gangavathi, Koppal District, Karnataka, under the Gramin Krishi Mausam Sewa (GKMS) scheme of the India Meteorological Department (IMD) to develop and evaluate a location-specific crop weather calendar for paddy in the Tungabhadra Command Area. The calendar was prepared by integrating long-term weekly climatic normals (2008–2023), phenophase-wise crop growth stages, and weather conditions conducive to major insect pests and diseases. The rice crop (medium-duration variety ‘Gangavathi Sona’) was analysed from the 25th to the 44th Standard Meteorological Week (SMW), covering the complete crop season from transplanting to harvest. Favourable weather conditions for higher productivity were observed during the maximum tillering stage, characterised by maximum temperatures of 30.9–32.6 °C, minimum temperatures of 23.6–24.0 °C, rainfall of about 93 mm, and morning relative humidity of 81–85 per cent. The calendar also identified weather regimes conducive to major pests and diseases, including brown planthopper, gall midge, rice blast, and bacterial leaf blight, thereby providing critical risk windows for advisory interventions. Satellite-based crop growth dynamics were analysed using 16-day MODIS NDVI (250 m) time series for the kharif season, which showed strong temporal agreement with the phenological progression depicted in the crop weather calendar. Plot-level NDVI profiles extracted for selected farmers’ fields further confirmed consistency among satellite-derived crop growth trajectories, calendar-based crop stages, and field observations. The practical utility of the crop weather calendar was evaluated through structured feedback from selected rice-growing farmers. Most respondents perceived the advisories as useful to moderately useful, particularly for pest and disease management, and reported yield improvements and additional economic benefits ranging from ₹1,400 to ₹2,600 per acre. Although based on a limited sample size, the feedback indicated that crop weather calendar–based advisories supported improved decision-making, reduced weather-related risks, and enhanced economic returns. Overall, the study indicates that integrating crop weather calendars with satellite-derived indicators and farmer feedback can strengthen phenophase-specific, weather-based advisories under GKMS, especially in intensively cultivated canal command areas.

Phenological Responses of Rice (Oryza sativa) to Heat Stress and their Regulation by Plant Growth Regulators

2026-08-14T12:08:13+00:00

Rising temperatures threaten rice productivity, particularly when heat stress coincides with sensitive developmental stages. This study evaluated stage-specific phenological, physiological, and yield responses of rice (Oryza sativa L.) cv. Jyothi and examined the mitigating effects of foliar plant growth regulators. A factorial completely randomised design was conducted during the 2025 kharif season using eight temperature-exposure regimes under polyhouse and ambient conditions and four foliar treatments: no spray, water spray, salicylic acid (400 ppm), and brassinosteroid (5 ppm). Heat stress was imposed across the active tillering, heading, and milking stages. Elevated temperature delayed phenological progression and, under severe reproductive-stage stress, prevented flowering, grain filling, and yield formation in several treatment regimes. Heat stress also reduced chlorophyll content and membrane stability index, whereas plant growth regulator treatments improved these physiological traits relative to untreated or water-sprayed plants. Brassinosteroid treatment generally produced the highest chlorophyll content, membrane stability, and yield-related performance, followed by salicylic acid. Yield components, including tiller and panicle number, filled grains, and grain yield, declined under heat stress, with particularly severe effects when reproductive development was exposed to high temperature. The findings indicate that heading is a highly heat-sensitive stage and that foliar brassinosteroid and salicylic acid applications can partially mitigate heat-related physiological and yield impairment in this rice variety under the conditions of the study.

Correlation and Stability Analysis in Bread Wheat (Triticum aestivum L.) under Different Sowing Environments

2026-08-14T13:18:51+00:00

A field investigation involving 40 bread wheat genotypes was conducted across three sowing environments: normal (E1, 15 November 2023), late (E2, 15 December 2023), and very late (E3, 15 January 2024). The experiment used a Randomised Complete Block Design (RCBD) with three replications to characterise genetic variability, trait correlations, and genotype stability. Pooled ANOVA, genetic parameters (GCV, PCV, h², and GAM), genotypic and phenotypic correlation coefficients, and Eberhart–Russell stability analysis were used to evaluate 13 traits across environments. Highly significant (P < 0.01) differences were detected among environments, genotypes, and their interactions for all traits. Seed yield showed a GCV of 4.03%, a PCV of 5.06%, broad-sense heritability (h²) of 39.49%, and a GAM of 6.60%, indicating relatively limited scope for improvement through direct phenotypic selection. Seed yield showed strong positive genotypic correlations with biological yield (rᵍ = 0.748), grains per spike (rᵍ = 0.756), and 1000-seed weight (rᵍ = 0.628). Stability analysis using the Eberhart–Russell model identified Raj 3077, Raj 4027, and GW 387 as stable, high-yielding genotypes across environments. The relatively narrow difference between the PCV and GCV estimates indicated limited environmental influence on the expression of several traits. These stable genotypes, with favourable biofortification traits (Fe, Zn, and protein), may provide useful breeding material for developing climate-resilient, nutrient-rich wheat varieties suited to variable sowing conditions in India.

Emission Intensity and Drivers of Greenhouse Gas Emissions in Buffalo Meat Production: An LMDI Decomposition Analysis of Major Buffalo-producing Countries

2026-08-17T11:14:05+00:00

Buffalo meat production contributes to food supply and agricultural economies in major producing countries, but its expansion is also associated with greenhouse gas emissions. Understanding changes in emission intensity and the factors driving emissions is important for evaluating the environmental performance of buffalo meat production. The present study examined trends in emission intensity, growth performance, and variability in greenhouse gas emissions associated with buffalo meat production at the global level and in the major producing countries of India, Pakistan, and China over the period 2000 to 2022. Analytical tools, such as the compound annual growth rate (CAGR), instability index, and Logarithmic Mean Divisia Index (LMDI) decomposition technique, were employed to assess growth patterns and disaggregate total emissions into production, emission intensity, and distribution components. The results indicated that India emerged as the largest contributor to global buffalo meat output, recording the highest production growth rate of 4.92 per cent, accompanied by a substantial reduction in emission intensity (−4.72 per cent). In contrast, China experienced an increase in overall emissions alongside limited improvements in emission efficiency. Pakistan registered a modest rise in production (1.25 per cent), but this was coupled with comparatively higher growth in emissions (3.13 per cent). Findings from the LMDI decomposition analysis revealed that the production effect was the primary driver of growth in CO₂-equivalent emissions from buffalo meat, accounting for an average contribution of 54.83 per cent. However, improvements in emission intensity significantly counterbalanced this increase, with an average mitigating effect of −42.64 per cent, reflecting enhanced efficiency over time. The distribution effect played a relatively marginal and inconsistent role, with an average contribution of −1.37 per cent, indicating its limited influence on total emission changes relative to production expansion and efficiency gains. The findings underscore the need for the adoption of climate-smart livestock strategies. Policy interventions should focus on strengthening emission efficiency through improved feeding regimes, effective manure management, and the deployment of low-emission technologies to support environmentally sustainable buffalo meat production in major producing countries.

Do Digital Governance and Digital Innovation Impact the Carbon Intensity of Tourism in Central Africa? Empirical Evidence from CEMAC Countries

2026-08-17T11:40:41+00:00

This study examines the effects of digital innovation and digital governance on tourism carbon intensity (TCI) across the six Economic and Monetary Community of Central Africa (CEMAC) countries over 2000–2024. Tourism carbon intensity is constructed from transport-sector carbon dioxide emissions relative to international tourist arrivals. Digital innovation is represented by Internet access, while digital governance is measured using seven V-Dem indicators. The empirical analysis applies a Panel Autoregressive Distributed Lag (ARDL) framework to distinguish long-run relationships from short-run dynamics. The estimates indicate that digital innovation and the different dimensions of digital governance have heterogeneous long-run relationships with tourism carbon intensity. Expanded Internet access is associated with a reduction in long-run TCI, whereas cybersecurity capacity is associated with an increase. The remaining digital-governance indicators display contrasting relationships, reinforcing the importance of considering each governance dimension separately. In the short run, GDP per capita is the only variable with a statistically significant effect. The moderation analysis further indicates that economic development strengthens the carbon-mitigating relationship between digital innovation and TCI, while it does not significantly moderate the relationships involving digital governance. Overall, the findings suggest that digital transformation does not have a uniform environmental effect in CEMAC. Coordinated digital, tourism, and environmental policies are therefore important for improving digital access while aligning governance and infrastructure development with lower-carbon tourism objectives.

Determination of Crop Water Stress Index for Irrigation Scheduling of Chickpea (Cicer arietinum L.)

2026-08-18T07:56:45+00:00

This field experiment evaluated the relationship between canopy–air temperature difference and vapour pressure deficit (VPD) in chickpea (Cicer arietinum L.) to determine the crop water stress index (CWSI) for irrigation scheduling. The lower baseline showed a linear relationship with VPD, whereas the upper baseline was relatively independent of VPD. The upper baseline was dTᵤ = 6 °C, and the lower baseline was dTₗ = −1.9755 VPD + 2.1035. Under climatic and soil conditions similar to those of the study, irrigation could be scheduled at approximately CWSI 0.78 without farmyard manure (FYM) and 0.75 with 10 t ha⁻¹ FYM to avoid water stress. Seasonal mean CWSI was inversely related to seed, biomass and straw yields. Seed yield showed a negative linear relationship with seasonal mean CWSI (R² = 0.63), indicating the potential of CWSI for yield prediction. Yield attributes, including number of pods per plant, seed weight per plant, number of branches per plant and test weight, declined as CWSI increased. A strong negative correlation (−0.88) was observed between CWSI and soil moisture during the growing season. The relationship between CWSI and soil moisture was described by CWSI = −0.0932x + 1.4092 (R² = 0.77). These results indicate that canopy-air temperature based CWSI can support irrigation timing and crop water-stress assessment in chickpea under comparable conditions.

Seasonal Physico-Chemical Water Quality and Aquatic Macrophyte Diversity of Victoria Lake (Bada Talab) in Lohardaga, Jharkhand, India

2026-08-18T11:33:05+00:00

Lakes across India face sustained pressure from domestic effluent discharge, siltation and unplanned catchment development, and the physico-chemical condition of such lakes is widely reported to shape the structure of their aquatic macrophyte communities. This paper illustrates a statistical workflow for relating monthly physico-chemical water quality data to seasonal aquatic macrophyte diversity in Bada Talab, Lohardaga, referred to here as Victoria Lake, using a simulated water quality time series (36 monthly records, January 2018–December 2020) and macrophyte cover data recorded on three sampling occasions (June 2018, December 2018 and March 2019). Fourteen physico-chemical parameters were examined, including temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), electrical conductivity, total dissolved solids, turbidity, hardness, alkalinity, chloride, sulphate, nitrate and phosphate. Macrophyte diversity was quantified using the Shannon–Wiener index (H′), species richness and percentage cover of the dominant species. Species richness increased from 12 (June 2018) to 57 (March 2019), the Shannon–Wiener index rose from 1.48 to 3.54 over the same period, and the percentage cover of the dominant species fell from 44.9% to 10.4%, consistent with a shift from a low-diversity, dominance-structured assemblage towards a more even, species-rich community. Pearson correlation analysis among the water quality parameters revealed a strongly inter-correlated block of variables (COD, electrical conductivity, total dissolved solids, turbidity, hardness, alkalinity, chloride, sulphate, nitrate and phosphate; r = 1.00) moving inversely with dissolved oxygen (r = −1.00), a pattern of near-perfect covariance that is characteristic of a synthetically generated series rather than field-measured data and is reported here as an explicit data-quality caveat. Because only three macrophyte sampling occasions were available, the correlation between diversity indices and water quality parameters (n = 3, 1 degree of freedom) could not be evaluated with meaningful statistical power and is presented descriptively rather than as a confirmed relationship. The paper is intended as a transparent demonstration of the methods, tables, figures and reporting conventions appropriate for physico-chemical–macrophyte correlation studies of Indian urban lakes, and it identifies the field sampling design that would be required to test the relationship rigorously.