重型货运车承担了我国大宗货物运输的主要份额，随着其保有量的持续增长，单纯以机动车排放标准加严的管控措施已遇到瓶颈，无法有效遏制快速增长的公路货运排放，成为当前交通领域减污降碳协同治理的严峻挑战。近年来，货车监管平台大数据技术快速发展，为建立企业层面的高分辨率路网排放清单和大数据治理策略提供了坚实的数据基础。因此，将重型货运车的排放与工业行业相关联，开发基于货车轨迹大数据的企业货运排放靶向追踪方法，从而解决大宗货物相关重点企业货运排放增长带来的环境问题，这一研究方向具有重大意义。针对行业端公路货运排放，本研究识别并筛选出主要大宗货类及相关重点工业行业，构建并优化了一套基于物质流的重点大宗货物相关行业的公路货运污染物排放计算方法，核算了2020年大宗货物相关重点行业的货运排放清单。针对企业端公路货运排放，本研究构建了一套基于起讫点轨迹数据、兴趣点数据和重点大宗货物相关企业名单库的多源数据融合框架，使得货运车轨迹排放精准靶向追踪到具体企业。同时基于该靶向追踪方法，挑选京津冀的钢铁企业进行案例研究，精确到逐日、逐小时的排放变化特征，并从车辆注册地、排放标准、限行政策等角度开展分析，为企业级的大数据货运排放治理提供参考依据。研究结果显示：上游原材料货运量和货运排放量远远高于下游产品，其中砂石骨料和石灰石引发的公路货运NOx排放占上游总公路货运排放的85.3%，是需要重点关注的大宗货类。上游原材料道路排放强度呈现公路货运量和排放强度负相关的特征，其中道路NOx和CO2排放强度最高的分别是铁矿石、煤炭，需要重点关注钢铁行业的公路货运减排。2017年京津冀地区钢铁企业货运NOx、PM2.5排放量分别为21588.1吨、572.1吨，占京津冀地区总货运排放的20%左右。河北省注册货车NOx排放占比接近80%，国III、国IV车是主要货运车辆，NOx年排放分担率分别为35%、59%。货车限行政策会显著降低货运排放，NOx、PM2.5日均排放量分别下降约19.7%、19.9%。对于临港和远港城市来说，其钢铁企业货运路线以南北走向的短途路线和以东西走向的长途路线为主。货车在限行时间内会选择绕行路线，导致北京市一天时间内货运通道有较明显的排放动态迁移。经电动化治理后，金鼎重工和沧州中铁的货运NOx减排比例能达到29.6%和18.6%。

Heavy-duty trucks bear the main share of China‘s bulk cargo transportation. With the continuous growth of their ownership, strict control measures based solely on motor vehicle emission standards have encountered bottlenecks, which cannot effectively curb the rapidly growing emissions of highway freight transportation. This has become a serious challenge for the current coordinated governance of pollution reduction and carbon reduction in the transportation sector. In recent years, the big data technology of the truck supervision platform has developed rapidly, providing a solid data foundation for the establishment of a high-resolution road network emissions inventory and big data governance strategy at the enterprise level. Therefore, it is of great significance to associate the emissions of heavy freight vehicles with the industrial industry and develop a targeted tracking method for enterprise freight emissions based on truck trajectory big data, in order to solve the environmental problems caused by the growth of freight emissions from key enterprises related to bulk goods.This study identified and screened the main bulk cargo categories and related key industrial industries for industry end road freight emissions, constructed and optimized a set of calculation methods for road freight pollutant emissions in key bulk cargo related industries based on material flow, and calculated the freight emissions list of key bulk cargo related industries in 2020. This study constructed a multi-source data fusion framework based on origin and destination trajectory data, point of interest data, and a list of key bulk cargo related enterprises for enterprise side road freight emissions, enabling precise and targeted tracking of freight vehicle trajectory emissions to specific enterprises. At the same time, based on the targeted tracking method, select steel enterprises in the Beijing Tianjin Hebei region for case studies, accurately analyzed the emission changes on a daily and hourly basis, and from the perspectives of vehicle registration location, emission standards, and administrative policies, providing a reference basis for enterprise level large data freight emission control.The research results showed that the freight volume and emissions of upstream raw materials were much higher than those of downstream products, with the total road freight NOx emissions of sand and gravel aggregates and limestone causing 85.3% of the total road freight emissions in the upstream, making it a major commodity category that needs to be focused on. The intensity of upstream raw material road emissions showed a negative correlation between road freight volume and emission intensity, with iron ore and coal having the highest intensity of road NOx and CO2 emissions. It was necessary to focus on reducing road freight emissions in the steel industry. In 2017, the emissions of NOx and PM2.5 from freight transportation by steel enterprises in the Beijing Tianjin Hebei region were 21588.1 tons and 572.1 tons, respectively, accounting for about 20% of the total freight transportation emissions in the Beijing Tianjin Hebei region. Registered trucks in Hebei Province accounted for nearly 80% of NOx emissions, with National III and IV vehicles being the main freight vehicles, with annual NOx emission sharing rates of 35% and 59%, respectively. Truck travel restrictions could significantly reduce freight emissions, resulting in a decrease of approximately 19.7% and 19.9% in daily average NOx and PM2.5 emissions, respectively. For cities near and far from ports, their steel enterprise freight routes mainly consisted of short north-south routes and long-distance east-west routes. During the travel restictions, trucks would choose detours, resulting in significant dynamic emission migration in Beijing in the freight passage within a day. After electrification treatment, the NOx emission reduction ratios of Jinding Heavy Industry and Cangzhou China Railway for freight transportation could reach 29.6% and 18.6%, respectively.