Sustainable roadway construction data from Greenroads certified projects

Data was collected as part of the roadway construction certification offered by Greenroads International according to Greenroads Rating System v1.5. This dataset is the result of data collection efforts for 33 construction projects across the US and abroad. Data was initially collected by Greenroads International as part of its certification process and was later obtained by this dataset's contributors. Projects in pursuit of certification submit supporting documents as evidence for performing a roadway construction practice. For example, tracking the amount of water used in construction to earn points and satisfy a credit in Greenroads. We hypothesize this dataset is unique in that it contains information and statistics on roadway construction projects that are declared sustainable with numeric outcomes to act as performance benchmarks for future projects to follow. Construction documents were first used to collect data on 12 sustainable performance benchmarks explained in the dataset (see Performance Benchmarks and Project Properties and Landscape Plans files). Sustainable performance benchmarks are established using median values of quantitatively measurable project outcomes. These benchmarks are defined in such a way that any roadway construction project regardless of size or scope may use them as sustainability achievement goals. In that, these performance benchmarks are somehow normalized to an aspect of the project’s size such as its monetary value, length, or area. Except for the source documents used to produce sustainable performance benchmarks, the dataset contains numeric values obtained from digesting several digitally formatted documents or spreadsheets submitted by project teams. The other major construction document included in this dataset is the pay item list from 30 projects (three projects did not provide this data). Pay item lists contain all the items used in the bidding process of a project and include a short description of each item, a unit of measure, the unit price, and the total price (see Pay Item Lists for LCA and Construction Materials LCA files). Several other construction documents were used to reinforce projects’ pay item lists with enough information for environmental impact assessment. As a result, many other data attributes were added to the pay item list data for each project. These include but are not limited to material’s unit weights, breakdown of material constituents (e.g., how much cement is in a concrete item), transportation distances, etc. Finally, life cycle inventory (LCI) data for the primary construction materials (see Materials LCI file) were collected from publicly available sources and were embedded into the pay item list data for life cycle assessment of materials used to build roadways. We analyzed the resultant dataset to estimate the greenhouse gas emissions and energy consumption of projects. When necessary, each dataset contains a metadata worksheet that explains data attributes.

本数据集的数据采集依托国际绿道（Greenroads International）依据《绿道评级体系v1.5》（Greenroads Rating System v1.5）推出的道路施工认证项目开展。本次数据集涵盖美国及海外共计33个施工项目的数据采集成果。数据最初由国际绿道为其认证流程所采集，后由本数据集的贡献方获取。

申请认证的项目需提交支撑性文件，以证明其落实了相关道路施工实践。例如，通过追踪施工用水量以获取对应积分，满足《绿道评级体系》的某项信用要求。

我们认为本数据集具备独特性：其收录了已声明为可持续的道路施工项目的相关信息与统计数据，并附带可量化的成果指标，可作为后续项目参考的性能基准。

施工文件最初用于采集本数据集提及的12项可持续性能基准相关数据（详见《性能基准与项目属性及景观规划》（Performance Benchmarks and Project Properties and Landscape Plans）文件）。可持续性能基准通过可量化的项目成果的中位数确定，其定义兼顾项目规模与范围，可被任意道路施工项目用作可持续性达成目标。具体而言，这些性能基准会针对项目的某一规模维度（如工程造价、道路长度或占地面积）进行归一化处理。

除了用于生成可持续性能基准的源文件外，本数据集还包含从项目团队提交的多种数字化文档或电子表格中提取的数值型数据。本数据集包含的另一核心施工文件为30个项目的支付项清单（Pay Item Lists，另有3个项目未提供该数据）。支付项清单涵盖项目招投标过程中涉及的全部条目，包含每项的简短描述、计量单位、单价及总价（详见《生命周期评估与建筑材料生命周期评估支付项清单》（Pay Item Lists for LCA and Construction Materials LCA）文件）。

另有多项其他施工文件用于补充项目支付项清单的信息，以支撑环境影响评估工作，由此为每个项目的支付项清单数据新增了诸多数据属性，包括但不限于材料单位重量、材料组成拆解（如混凝土构件中的水泥占比）、运输距离等。

最终，我们从公开渠道采集了主要建筑材料的生命周期清单（life cycle inventory, LCI）数据（详见《材料生命周期清单》（Materials LCI）文件），并将其嵌入支付项清单数据中，用于开展道路建设所用材料的生命周期评估。我们对生成后的数据集进行了分析，以估算项目的温室气体排放量与能源消耗。必要时，每个数据集均包含元数据工作表，用于解释各数据属性的含义。