## 1 Introduction  
The key success for underground mining projects is to increase production rates while lowering operating costs. Stope dilution and recovery are two of the parameters that directly affect financial results and operational efficiency [1, 2]. Dilution causes uneconomic material to mix with the run of the mine, which raises processing costs; lowers the quality of the ore; and, due to the increased number of truck cycles, impacts CO\({}_{2}\) emissions underground. Additionally, it causes delays in production schedules, which impacts short- and long-term planning targets. Dilution-related costs can make up 20-30%, and in some cases as much as 40%, of the total metal or concentrate costs, according to studies from different mines [3]. There is still a lack of useful modular tools for precisely monitoring and controlling stope dilution in the regular base at many underground mines. Conventional methods frequently miss out the relation of the results of dilution to their wider financial and environmental results, instead placing a strong emphasis on geotechnical design and stope geometry [4,5]. Also, mine planning usually does not differentiate between planned and unplanned dilution, even though they come from very different reasons: design choices versus unexpected operational issues [6]. This lack of information makes it hard to make accurate reserve estimates and efficient production planning. This lack of clarity makes it harder to plan production and figure out how much reserve you really have. Mineral resource estimation and creating a block model that includes the grade, block coordinates, density, and volume of each block are usually the first steps in the planning process [7]. After that, stope optimization is carried out using mine planning software, considering modifying factors, including equipment capacity, production targets, and geotechnical parameters [8]. The relationship between stope designs and their actual implementation is so critical, especially if loss and dilution are not dynamically monitored. Dilution has several consequences for underground production. In addition to this, operational costs increase especially when it comes to increasing CO\({}_{2}\) emissions. Extra cycles are needed to haul extra waste material to the surface, which increases the ventilation requirement and fuel consumption. According to recent studies, optimizing underground operations' energy efficiency, especially in ventilation and haulage, can decrease CO\({}_{2}\) emissions by as much as 24% [9]. As a result, controlling dilution management both environmentally and economically is the key factor for successful operation [10,11]. In order to track planned and unplanned dilution, as well as mining losses, this study presents D-Loss, a user-friendly interface created using MATLAB's academic license. D-Loss allows mine planners to evaluate the wider effects of their design and operational results by directly connecting the dilution result to the D-Loss financial and CO\({}_{2}\) emissions module. Using block model and stope design data, it enables quick evaluation of stope tonnage, recovery, and grade, offering both immediate flexibility and long-term planning advantages. Despite the growing awareness of dilution's impact on underground mining performance, current tools often fall short in integrating technical, economic, and environmental results into a single decision-making framework. While some software applications address stope reconciliation, they rarely provide analysis of how dilution levels affect both financial returns and CO\({}_{2}\) emissions. This study addresses that gap by presenting D-Loss, a MATLAB-based software tool designed to quantify planned and unplanned dilution, evaluate stope-level profitability, and estimate haulage-related CO\({}_{2}\) emissions. Unlike traditional tools, D-Loss allows for iterative comparisons and planning support based on user-defined scenarios.