Abstract

Purpose: The aim of the study was to examine contribution of livestock farming to environmental pollution in China. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that livestock farming in China significantly contributes to environmental pollution, posing substantial challenges to water, air, and soil quality. Intensive livestock operations, characterized by concentrated animal feeding operations (CAFOs), generate large quantities of animal waste containing nutrients and pathogens that contaminate water bodies. Additionally, livestock farming contributes to air pollution through emissions of ammonia and other pollutants, particularly in areas with intensive farming practices. Soil degradation and nutrient imbalance further exacerbate environmental degradation, with higher livestock densities associated with increased soil compaction and nutrient runoff. Unique Contribution to Theory, Practice and Policy: Tragedy of the Commons & Ecological Modernization Theory may be used to anchor future studies on contribution of livestock farming to environmental pollution in China. Promote the adoption of sustainable livestock management practices through capacity building, training, and extension services for farmers. Encourage the implementation of integrated farming systems that optimize resource use, minimize waste generation, and enhance environmental resilience. Strengthen regulatory frameworks and enforcement mechanisms to ensure compliance with environmental standards and promote responsible livestock production. Implement stringent measures to control water pollution from livestock waste, including mandatory wastewater treatment and monitoring programs.

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