India’s freight and logistics sector is a critical pillar of the economy, contributing 13-14% of the country’s GDP. However, as freight demand is projected to triple with economic growth, the sector’s heavy reliance on diesel is raising significant environmental concerns. Currently, freight contributes to 8% of global greenhouse gas emissions, with India’s transport sector being a major CO2 emitter, exacerbated by inefficient practices like overloading and empty runs.
India’s commitment to achieving net zero emissions by 2070 highlights the urgent need for greener freight transport solutions. However, the lack of city-level emissions data is a significant barrier to effective policymaking. A recent study by the Urban Lab Foundation, one of HVT’s Transport -Technology Research and Innovation for International Development (T-TRIID) projects, focuses on Ahmedabad’s walled city – a key commercial hub with significant freight movement – where a freight emission index (FEI) has been developed to monitor emission efficiency and provide strategies for emission reduction.
Freight emissions are influenced by several factors including vehicle attributes such as type, fuel, engine technology, and age, as well as operational factors like load efficiency and empty trips. Heavy-duty trucks and diesel engines are among the largest contributors to emissions, while alternative fuels like CNG and LNG can significantly reduce them. Regular maintenance and advancements in engine technology also play a vital role in minimizing emissions.
Operational efficiency is crucial for reducing emissions. The avoid-shift-improve framework is instrumental in this regard, emphasizing the reduction of unnecessary trips, the shift to less carbon-intensive modes, and the improvement of efficiency. Accurate measurement and management of emissions are supported by carbon accounting and standardized methods, such as the Global Logistics Emissions Council (GLEC) framework.
The study aimed to capture emission efficiency by integrating vehicular and operational characteristics for the index. Three key commodities – perishables, electronics, and textiles – were selected due to their significant impact on freight emissions. This selection was made using a framework that evaluated commodities based on market presence, kilometres travelled, trip frequency, and other criteria.
The methodology for developing the freight emission index (FEI) involved a hybrid approach, combining secondary research, data collection, and expert interviews. Detailed data collection was conducted through classified volume count (CVC) surveys, roadside interviews, and establishment surveys, supplemented by feedback from residents and drivers gathered during stakeholder interactions. Residents expressed concerns about air quality, with one noting: “The air has become so thick with pollution, it feels like we are living in a fog,” highlighting the urgent need for action to improve air quality and preserve the heritage of the walled city.
The index primarily focused on carbon monoxide (CO) density in the exhaust smoke, as it was captured in the pollution under control (PUC) certificates issued in the city. It was created using a combination of vehicle characteristics such as engine type, fuel type, and vehicle age, along with operational factors like load factor, empty runs, and time spent in congestion. The index combined these factors to understand the holistic emission efficiency of a vehicle.
The FEI was developed as a decision-making tool, providing localized insights and strategies for reducing freight emissions. Its final scores indicate the emission efficiency of each commodity’s markets. The score does not indicate the on-ground emissions produced by the freight vehicles of that commodity, but indicates the performance and operational characteristics of these vehicles. The index uses a scale of 1 to 100. A high score indicates good performance in terms of operational and vehicle characteristics. The results of the FEI for the walled city of Ahmedabad are as follows.
Perishable markets score the highest out of the three commodities, with a score of 84 out of 100, indicating good performance in terms of vehicle and operational characteristics. Second is the electronics market, with a score of 68, and third is the textile market with a score of 62.
Through emission calculations it was observed that vehicles in the perishable market are the most polluting in terms of their CO2 g emissions daily with 5342 CO2 g t/km, while textile and electronics commodities had 1306 g t/km and 158 g t/km respectively, but since perishables scores the highest on the index, it is also the most emission-efficient commodity. This is partly due to the fact that many perishable goods are transported in passenger three-wheelers which are CNG based, due to government mandates. This is not the case with textile and electronic markets where most vehicle are diesel-based three-wheeler freight vehicles. While textile and electronic market vehicles actually produce fewer emissions than perishable markets, their vehicles are less emission efficient.
The study recommends several strategies to enhance emission efficiency, including transitioning to cleaner fuels, implementing stricter regulations on older vehicles, and optimizing load factors. For the electronics market, specific measures are proposed, such as converting older diesel vehicles to CNG and reducing empty runs to improve the FEI score.
The research presents a comprehensive approach to reducing emissions in the freight sector, highlighting the importance of policy changes, regulatory frameworks, and technological innovations. The development of a scalable freight emission index (FEI) tailored for walled cities provides valuable insights that can be applied to other urban areas in India, helping to understand commodity-specific emission efficiency and design targeted emission reduction strategies. It also enables urban local bodies and city authorities to better understand emission efficiency, while freight operators can assess the efficiency of their fleet on a private level.
Looking ahead, the study recommends expanding research to include other greenhouse gases like NOx (refers to a group of nitrogen-based gases, primarily nitrogen dioxide (NO2) and nitric oxide (NO), that are produced during combustion processes, especially from vehicle engines, power plants and industrial processes) and PM2.5 (refers to fine particulate matter that is less than 2.5 micrometres in diameter. These tiny particles can penetrate deep into the lungs and even enter the bloodstream and is generated from various sources, including vehicle exhaust, industrial emissions, construction activities, and natural sources like wildfires), as well as incorporating real-time emissions data for more accurate results. The methodologies and strategies outlined in this study offer a blueprint for sustainable urban planning and support India’s emission reduction goals.