一、评价依据
This index follows the CPPPS proprietary evaluation-algorithm specification: it does not copy public rankings but computes its own rankings from underlying environmental data. The 'underlying data' of environmental performance is the true state of a country's natural and ecological systems and its transition actions, which can be grouped into four categories:
本指数遵循 CPPPS 自有评价算法规范：不摘抄公开榜单名次，用底层环境数据自算排名。环境绩效的"底层数据"即一个国家自然与生态系统的真实状态及其转型行动，可归为四类：
- 规模：国土面积、森林面积——决定生态承载空间与碳汇本底。
- 质量：空气质量（PM2.5 年均浓度）、水环境质量、森林覆盖率、生物多样性——反映环境健康与生态系统活力，是环境绩效的核心。
- 创新：可再生能源发电占比——反映能源结构的绿色转型进程。
- 贡献：年新增可再生能源装机、年新增造林（碳汇）、碳中和承诺力度、人均碳排放（反向）——反映一国对全球气候治理的增量贡献与排放现状（CPPPS 特色维度，国际榜单普遍以存量状态为主，忽视"新增贡献"）。
二、数学模型
Each indicator is first range-standardized (min-max) onto [0,1]; large-span scale indicators (land area, forest area, new installed capacity) are log-transformed before standardization to avoid head countries monopolizing the scores:
各指标先做极差标准化（min-max）映射到 [0,1]；规模类大跨度指标（国土面积、森林面积、新增装机）取对数后再标准化，避免头部国家垄断分值：
The weight logic: Quality is the essence of environmental performance (45%); Contribution reflects 'common but differentiated responsibilities' and incremental action (25%); Scale and Innovation are each 15%. Air quality (PM2.5) and per-capita carbon emissions are taken inversely (the lower the better), while all other indicators are taken positively.
权重逻辑：质量是环境绩效的本质（45%）；贡献体现"共同但有区别的责任"与增量行动（25%）；规模与创新各 15%。空气质量（PM2.5）与人均碳排放取反向（越低越好），其余指标均取正向。
三、指标与权重依据
| 指标 | 方向 | 权重 | 维度 | 依据 |
|---|
| 国土面积 | 对数 | 规模 0.50 | 规模 | 生态承载空间（取对数防垄断） |
| 森林面积 | 对数 | 规模 0.50 | 规模 | 碳汇与生态本底 |
| PM2.5 年均浓度 | 反向 | 质量 0.30 | 质量 | 环境健康核心指标 |
| 水环境质量 | 正向 | 质量 0.25 | 质量 | 水生态安全 |
| 森林覆盖率 | 正向 | 质量 0.25 | 质量 | 陆地生态系统活力 |
| 生物多样性 | 正向 | 质量 0.20 | 质量 | 物种与生态系统丰富度 |
| 可再生能源占比 | 正向 | 创新 1.00 | 创新 | 能源绿色转型进程 |
| 新增可再生能源装机 | 对数 | 贡献 0.35 | 贡献 | 绿色增量（CPPPS 特色） |
| 新增造林面积 | 正向 | 贡献 0.25 | 贡献 | 碳汇增量（CPPPS 特色） |
| 碳中和承诺与力度 | 正向 | 贡献 0.20 | 贡献 | 气候治理决心 |
| 人均 CO₂ 排放 | 反向 | 贡献 0.20 | 贡献 | 当前碳排放水平（越低越好） |
四、贡献维度（CPPPS 特色）
Traditional environmental rankings focus mainly on the stock state (current air, water, forest and emission levels), which naturally favors developed countries that 'started early, have high historical emissions and small current increments', while systematically underestimating developing countries that have 'a low base, a late start but huge increments'. CPPPS introduces a 'Contribution dimension' to correct this: it looks at both the stock (Quality) and the increment (Contribution)—annual newly installed renewable-energy capacity, annual new afforestation carbon sinks and the strength of carbon-neutrality commitments—and constrains high-emission stock with per-capita carbon emissions (inverse).
传统环境榜单多以存量状态（当前空气、水、森林、排放水平）为主，这使"起步早、历史排放高、当前增量小"的发达国家天然占优，而"基数低、起步晚、但增量巨大"的发展中国家被系统性低估。CPPPS 引入"贡献维度"加以修正：既看存量（质量），也看增量（贡献）——年新增可再生能源装机、年新增造林碳汇、碳中和承诺力度，并以人均碳排放（反向）约束高排放存量。
Taking China as an example: about 300 GW of newly installed renewable-energy capacity per year and about 4 million hectares of new afforestation per year, both the largest in the world, with incremental contributions far exceeding most countries; combined with the 'carbon peak and carbon neutrality' target commitment, China ranks first in the Contribution dimension. This dimension objectively presents the actual incremental contribution of developing countries in global climate governance, consistent with the 'common but differentiated responsibilities' principle of the Paris Agreement.
以中国为例：年新增可再生能源装机约 300 吉瓦、年新增造林约 400 万公顷，均为全球第一，增量贡献远超多数国家；叠加"碳达峰、碳中和"目标承诺，中国在贡献维度居首。这一维度客观呈现了发展中国家在全球气候治理中的实际增量贡献，与《巴黎协定》"共同但有区别的责任"原则一致。
五、数据来源与局限性
PM2.5 annual average concentration, water-environment quality, forest coverage, biodiversity, per-capita carbon emissions, share of renewable energy, new installed capacity, new afforestation and carbon-neutrality commitments are all public-knowledge approximations marked 'subject to official figures', sourced from public data of the United Nations Environment Programme (UNEP), the World Bank, the International Energy Agency (IEA), the International Renewable Energy Agency (IRENA), the Food and Agriculture Organization (FAO) and national statistical bulletins.
PM2.5 年均浓度、水环境质量、森林覆盖率、生物多样性、人均碳排放、可再生能源占比、新增装机、新增造林、碳中和承诺等均为公开常识近似值，标注"以官方为准"，来源包括联合国环境规划署（UNEP）、世界银行、国际能源署（IEA）、国际可再生能源署（IRENA）、联合国粮农组织（FAO）及各国统计公报的公开数据。
Limitations: (1) the approximations carry errors, and the ranking is for research and reference only; (2) the model centers on stock ecological assets (forests, biodiversity, clean electricity), so countries with outstanding forest and species endowments such as Brazil and Indonesia naturally score higher, while their deforestation problem is only partially reflected in the afforestation item (recorded as 0) of the Contribution dimension; (3) the Innovation dimension counts only the share of renewable energy, so countries such as France with 'high nuclear power and low carbon emissions' do not fully reflect their low-carbon advantage; (4) the biodiversity index is a composite approximation that is hard to quantify precisely; (5) indicators such as ozone, soil and marine pollution are not included. This model contains no subjective scoring and is permanently free and public.
局限性：①近似值存在误差，排名仅供研究与参考；②本模型以存量生态资产（森林、生物多样性、清洁电力）为核心，巴西、印度尼西亚等森林与物种禀赋突出的国家自然得分偏高，其毁林问题仅在贡献维度的造林项（记 0）部分体现；③创新维度仅统计可再生能源占比，法国等"高核电低碳排放"国家未充分体现其低碳优势；④生物多样性指数为综合近似，难以精确量化；⑤未纳入臭氧、土壤、海洋污染等指标。本模型不包含任何主观赋分，永久免费公开。
六、参考文献
- 蕾切尔·卡森：《寂静的春天》（1962）。
- 联合国：《人类环境宣言》（斯德哥尔摩，1972）。
- 联合国：《联合国气候变化框架公约》（里约，1992）与《巴黎协定》（2015）。
- 联合国：《变革我们的世界：2030 年可持续发展议程》（SDGs）。
- 耶鲁大学环境法律与政策中心：《Environmental Performance Index》（仅作方法论参照，未转载名次）。
- 世界银行：World Development Indicators（森林覆盖、可再生能源等）。
- 国际能源署（IEA）：World Energy Outlook。
- 国际可再生能源署（IRENA）：Renewable Capacity Statistics。
- 联合国粮农组织（FAO）：Global Forest Resources Assessment。
- 各国统计年鉴与环境公报（公开近似值，以官方为准）。