Objective To investigate current carbon footprint status of five hemodialysis centers regarding energy consumption of dialysis machine and patient commuting, so as to provide a scientific basis for quantification of carbon footprint in hemodialysis treatment.  Methods A cross-sectional survey approach was employed. Data collection was conducted from January to December 2024 in five hemodialysis centers in Beijing, Changsha, and Shanghai. Electricity consumption per hemodialysis session and per dialysis machine was measured by a plug-in energy meter. Resident distance and traffic mode of the patient were obtained via anonymous questionnaires. Emission factors for provincial electricity and transportation mode were used to calculate the carbon footprint.  Results  Carbon footprint of a hemodialysis session attributable to electricity consumption by a hemodialysis machine and patient’s commuting were 1.67±0.38 kg and 1.53±0.56 kg of carbon dioxide equivalents (CO2-eq), respectively. The coefficient of variation for carbon footprint of patients’ commuting was 37%. For the same type of dialysis machines, electricity consumption and carbon footprint for a hemodialysis session in northern centers were 25% and 30% higher than those in southern centers. Commuting distance analysis revealed that carbon footprint for commuting was statistically different among the groups of different resident distance (≤4 km, ＞4～8 km, ＞8～16 km, and＞16 km; H=320.662, P＜0.001), with the medium value of 0.00 (0.00, 0.06) kg CO2-eq in ≤4 km group to 7.55 (0.37, 9.74) kg CO2-eq in＞16 km group; commuting mode was also statistically different among groups (χ²=274.661, P＜0.001), with traffic mode from walking or bicycle (62.3%) to car or bus  (55.6%) along with the increase of resident distance.  Conclusion Carbon footprint for commuting of hemodialysis patients is lower in China than in foreign countries, probably due to the advanced system of public transportation in China. We recommend that commuting distance should also be considered in the management of hemodialysis patients, encouraging patients to use hemodialysis facilities in nearby community centers to reduce carbon consumption. Moreover, optimization of the operation environment for dialysis machines may reduce the electricity consumption due to geographic differences.