下载到 MS-PowerPointCite This: 引用:Environ. Sci. Technol. 环境。科学技术 2016, 50, 5, 2175-2182
Greening Industrial Production through Waste Recovery: “Comprehensive Utilization of Resources” in China
通过废物回收实现工业生产绿色化:中国“资源综合利用”
- Junming Zhu
朱 * † ‡ 俊明 - and
- Marian R. Chertow
玛丽安·切尔托(Marian R.Chertow * † )
Abstract 抽象
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0008.gif)
Using nonhazardous wastes as inputs to production creates environmental benefits by avoiding disposal impacts, mitigating manufacturing impacts, and conserving virgin resources. China has incentivized reuse since the 1980s through the “Comprehensive Utilization of Resources (CUR)” policy. To test whether and to what extent environmental benefits are generated, 862 instances in Jiangsu, China are analyzed, representing eight industrial sectors and 25 products that qualified for tax relief through CUR. Benefits are determined by comparing life cycle inventories for the same product from baseline and CUR-certified production, adjusted for any difference in the use phase. More than 50 million tonnes of solid wastes were reused, equivalent to 51% of the provincial industrial total. Benefits included reduction of 161 petajoules of energy, 23 million tonnes of CO2 equivalent, 75 000 tonnes of SO2 equivalent, 33 000 tonnes of NOX, and 28 000 tonnes of PM10 equivalent, which were 2.5%–7.3% of the provincial industrial consumption and emissions. The benefits vary substantially across industries, among products within the same industry, and when comparing alternative reuse processes for the same waste. This first assessment of CUR results shows that CUR has established a firm foundation for a circular economy, but also suggest additional opportunities to refine incentives under CUR to increase environmental gain.
使用无害废物作为生产投入,通过避免处置影响、减轻制造影响和保护原始资源来创造环境效益。自1980年代以来,中国通过“资源综合利用”政策鼓励再利用。为了测试是否以及在多大程度上产生了环境效益,分析了中国江苏的862个实例,代表了8个工业部门和25个产品,这些产品有资格通过CUR获得税收减免。收益是通过比较同一产品从基线和 CUR 认证生产开始的生命周期库存来确定的,并根据使用阶段的任何差异进行调整。固体废物再利用5000多万吨,相当于全省工业总量的51%。效益包括减少161拍焦耳的能源、2300万吨二氧化碳 2 当量、75000吨SO 2 当量、33000吨一氧化氮 X 和28000吨颗粒当 10 量,占全省工业消费和排放量的2.5%-7.3%。不同行业、不同行业的产品以及比较相同废物的替代再利用工艺时,其效益差异很大。对 CUR 结果的首次评估表明,CUR 已经为循环经济奠定了坚实的基础,但也提出了更多机会来完善 CUR 下的激励措施以增加环境收益。
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工业生产会产生大量的废水、固体材料、副产品和废气。非危险废物再利用的努力引起了越来越多的关注,这既源于作为当地工业共生实例的邻近公司之间的资源共享(1,2),也源于一个地区或国家之间更大规模的资源共享。(3, 4)再利用效益的量化表明,将废物作为原料重新投入工业生产,不仅可以抢占废物处理和原始资源开采,还可以使制造过程更清洁,降低能耗和排放。(3, 5-8)为了使再利用和回收可行,已经使用了各种政策工具,例如禁止填埋某些类型的废物、欧洲国家的垃圾填埋税和焚烧税 (9) 以及日本对回收项目的投资补贴。(10)
然而,从环境经济学的角度来看,如果侧重于促进回收和再利用的政策工具仅包括部分过程(例如在生命周期结束阶段),而忽略了废物再利用的生产阶段效益,则无法实现社会最优。虽然垃圾填埋场收费或资源税等工具可以阻止处置并鼓励再利用,但它们目前没有区分替代再利用过程,这意味着废物通常不会被引导到产生最大环境效益的过程。(11) 相反,我们建议应将废物投入生产视为一种清洁的替代品,并根据废物回收相对于基准生产量减轻污染的强度给予奖励。在许多情况下,至少在理论上,污染税和清洁替代品补贴的两部分工具是首选。(12, 13)然而,在实践中,不同工业过程的废物副产品使用程度是否得到承认以及在多大程度上得到承认,需要进一步完善,并应取决于再利用的效益与获取信息和执行政策的成本有关。换言之,如果差别废物再利用的额外收益能够弥补成本,那么改进政策设计和执行的额外成本将是合理的。
为了促进无害工业废物管理的讨论和政策制定,本文评估了受益于使用废物作为原料的各种行业和工艺。根据2011年中国江苏省755家企业和862个再利用流程的信息,收集了单个废物再利用活动的综合数据集。这些公司属于八个主要工业部门。由于它们使用废弃物投入,它们获得了政府和第三方机构在中国“资源综合利用”(CUR)政策下的税收减免认证。为了量化收益,选择了 25 种具有代表性的产品。对于每种产品,都会建立两个生命周期清单 (LCI),一个基于对基线生产流程的分析,另一个基于具有 CUR 认证输入的重复使用的流程。在调整了可能影响使用阶段库存的产品功能和质量的任何差异后,对同一产品的替代 LCI 进行了比较。
2011年,经CUR认证的废物再利用总量超过5000万吨(表1),相当于江苏省工业固体废物总量的51%。(14)节能减排总效益相当于江苏省整个工业部门能源消耗的2.5%、CO 2 排放量的3%、SO 2 排放量的7.3%、NO X 排放量的2.8%和颗粒物排放量的5.8%。仅节能一项就相当于全国非水可再生能源发电总量的40%,是同年江苏核能和可再生能源发电总量的两倍多。然而,各行业以及行业内不同流程和产品之间的收益规模和类型存在很大差异。当用于不同的制造工艺时,相同的废物也具有不同的规模和类型的效益。
中国每年产生超过30亿吨工业固体废物,(15)CUR政策和废物再利用在减少中国工业生产的能源消耗和污染排放方面发挥了重要作用。这些好处对整个国家也很重要,因为工业部门是中国能源使用和空气污染的主要贡献者(图1)。特别是,它支持中国追求“循环经济(16,17)”,通过在整个社会中减少、再利用和回收来提高资源生产率和可持续发展。然而,由于不同再利用过程在规模和效益类型上的差异性,这里提出的更精细的激励计划可以实现更大的环境效益,这些激励计划将废物流引导到环境效益最大的过程。
Figure 1 图1
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0002.gif)
Figure 1. The overall industrial contribution to total energy consumption and pollution emissions in China and in Jiangsu in 2012. Sources: National Bureau of Statistics of China, (18) Ministry of Environmental Protection of China, (19) and Jiangsu Statistical Bureau. (14)
图 1.2012年中国和江苏省工业总能耗和污染排放总量的总体贡献。资料来源:中国国家统计局、(18)中国环境保护部、(19)和江苏省统计局。(14)
Comprehensive Utilization of Resources in Jiangsu, China
中国江苏省资源综合利用
中国的CUR政策为工业废弃物再利用提供了全面的覆盖面和独特的激励计划,使不同行业和工艺的环境效益量化成为可能。尽管环境政策文献中鲜为人知且未进行讨论,但 CUR 政策自 1980 年代以来一直有效 (20),作为鼓励在生产过程中使用采矿和工业废物以保护资源的一种手段。该政策所涵盖的废物和再利用产品类型每隔几年更新一次,并且该清单随着时间的推移而增长。目前,CUR政策是财政部、国家税务总局和国家发展和改革委员会实施的废物再利用企业的税收抵免计划。
该计划由一个目录组成,该目录指定了合格的废物、再利用产品以及相关的增值税申报水平;(21)一个目录,规定废物、产品和相关可抵扣的企业所得税水平;(22) 以及一项规定根据 CUR 认证的公司获得税收减免的程序的法规。(23) 根据使用的废物类型,公司可以享受高达 100% 的增值税退税。有资格获得企业所得税减免的公司享有90%的应税基数,因此利润较低的公司无需缴纳任何税款。每家申请 CUR 纳税申报表或抵扣额的公司都必须 (1) 使用超过一定百分比的废物并根据任一目录生产特定产品,(2) 遵守行业政策和环境标准,(3) 由政府机构和第三方审查员审查和认证,(4) 公开其 CUR 信息。CUR流程为各个公司提供了高质量的文件和废物再利用信息。
虽然 CUR 被推广为一项国家政策,但它在几个发达地区更受欢迎。选择江苏省的CUR活动进行进一步分析,因为该省在实现CUR目标方面得到了充分认可,并且由于记录在案的再利用信息的质量。江苏省工业固废再利用率在90%以上,(14)居全国前列,全国平均水平为60%。(15)该省是中国所有省份中工业经济规模最大的省份,占全国工业总值的13%。(18, 24)其产业结构总体上是均衡的:除了相对较小的采矿业外,大多数制造业的产量占全国产出份额的5%以上。江苏省垃圾回收再利用制造业占全国比重的13%,占全省工业总产值的0.3%。(18, 24)
表 1.按废物和产品类别 a 划分的再利用数量和产出清单
products 产品 | source of reused waste 再利用废物的来源 | quantity 数量 | processes | output | profit |
---|---|---|---|---|---|
1000 tonnes 1000吨 | million RMB | ||||
Chemical and Petrochemical 化工和石化 | |||||
basic chemicals 基础化学品 | wastewater, gas, battery 废水、气体、电池 | 863 | 32 | 791 | 84 |
fiber products 纤维制品 | used fiber 使用过的纤维 | 277 | 7 | 1999 | 32 |
rubber and tire 橡胶和轮胎 | used tire 旧轮胎 | 68 | 9 | 222 | 15 |
other petrochemicals 其他石化产品 | used plastics, food refuse 废旧塑料、食物垃圾 | 88 | 6 | 407 | 18 |
Metals 五金 | |||||
waste electronics, slag, catalyst, battery, chemicals 废电子产品、炉渣、催化剂、电池、化学品 | 709 | 12 | 874 | 115 | |
Construction Materials 建筑材料 | |||||
cement, mortar 水泥、砂浆 | FA, MT, FGD waste, slag FA、MT、FGD 废物、炉渣 | 19 961 | 152 | 13 741 | 993 |
concrete products 混凝土制品 | FA, MT, slag FA、MT、炉渣 | 11 777 | 238 | 3905 | 145 |
bricks, blocks 砖块、砌块 | FA, RS, MT FA、RS、MT | 8304 | 287 | 1098 | 49 |
gypsum, wallboard 石膏, 墙板 | FGD waste 烟气脱硫废物 | 1262 | 28 | 961 | 116 |
other construction 其他建筑 | FA, RS, MT FA、RS、MT | 7775 | 30 | 482 | 222 |
Wood Board 木板 | |||||
forest residue 森林残余物 | 3314 | 47 | 2964 | 217 | |
Energy and Fuel 能源和燃料 | |||||
heat 热 | waste heat, forest residue 废热、森林残渣 | 65 | 7 | 78 | 28 |
biodiesel 生物柴油 | food refuse 食物垃圾 | 21 | 4 | 130 | –6 |
Reclaimed Water 再生水 | |||||
wastewater 废水 | 4061 | 3 | 26 | 7 | |
total 总 | 58545 | 862 | 27678 | 2035 |
Note: Quantities of used tires and waste gas were reported in pieces and volume originally, and converted to weight in this table; the quantity of waste used for heat generation contains only forest residues, not waste heat. FA, fly ash; MT, mine tailings; FGD, flue gas desulfurization; RS, river and lake sediments.
a 注:废旧轮胎和废气的数量最初是按件数和体积报告的,并在本表中转换为重量;用于发热的废物量仅包含森林残留物,不包含废热。FA, 粉煤灰;MT, 矿山尾矿;烟气脱硫,烟气脱硫;RS,河流和湖泊沉积物。
江苏CUR的文件包括,对于每个公司的每个再利用过程,使用的废物类型和数量,每种原料中的废物百分比,产品的类型和数量,使用的设备,货币产出和利润。2011 年,共有 755 家公司及其 862 个再利用流程获得了 CUR 认证(表 1)。他们使用了400万吨废水、100万吨废气、667太焦耳的废热和5400万吨固体材料作为原料,相当于该省工业固体废物产生的51%。这些工艺创造了280亿元人民币的产值和20亿元人民币的利润。大多数CUR公司是“常规”工业生产者,而不是废物回收和再利用的两位数制造业的一部分。相比之下,这些工业生产者的CUR活动的特点是,与正规回收部门相比,公司数量多五倍,产出水平相似,利润增加两倍,废物回收可能更多。(24)
根据中国标准行业分类系统,这些生产活动属于八个两位数的工业部门。为了更好地说明,它们进一步汇总为五个行业:
(1) | chemical and petrochemical products, | ||||
(2) | metals, 五金 | ||||
(3) | construction materials, 建筑材料, | ||||
(4) | wood board products, 木板制品, | ||||
(5) | energy and fuel. 能源和燃料。 |
CUR认证的大部分再利用是在建筑材料行业,包括水泥、混凝土和石膏板的生产(表1)。该行业用作初级生产投入替代品的流行废物原料包括粉煤灰、煤矿垃圾、其他矿山尾矿、河流和湖泊沉积物,以及烟气脱硫 (FGD) 的残留物。化工和石化制造的产品更加多样化,包括基础化学品、化学气体、纤维、塑料和橡胶。石化产品主要通过回收和再制造相同的产品生产,而化学产品主要来自不同的废物输入。金属是从含有黑色金属、贵金属和其他有色金属的各种产品中回收的。制造木板,生产来自森林和农业生产、工业热能和食品的能源和燃料废渣。总之,废物占建筑材料原料的35-75%,在表1中报告的其他工艺中,废物占体积的几乎100%。
Quantifying Environmental Benefits of Waste Reuse
量化废物再利用的环境效益
为了估计废物再利用的总体效益以及单个行业和工艺的特殊效益,使用生命周期评估 (LCA) 选择和评估具有代表性的工业流程。然后将结果投影到所有流程中,以进行汇总和跨行业比较。虽然详细的方法和数据源作为支持信息提供,但本节介绍一般策略、方法和数据源。
从CUR活动中流行的废物和产品中,总共选择了25种通用工艺,因为它们具有代表性,可推广到其他再利用工艺以及数据可用性。它们包括两种类型的木板、五种化工和石化产品、10 种建筑产品、五种金属和三种能源/燃料产品。通过将其生命周期库存 (LCI) 与生产相同产品的标准流程平均值的 LCI 进行比较,确定每个过程中废物再利用的好处。主要关注的是整个上游生命周期,但当 CUR 工艺的产品与其常规产品在功能、质量或耐久性方面不同,并在使用阶段导致不同的排放清单时,就会考虑下游差异。
由于我们的重点是通过使用废物投入来改善替代工业流程的程度以及更有效的再利用政策,因此避免废物处理不包括在收益中。这也反映了江苏省CUR活动的密集化和整体再利用率超过90%:当一个特定的废物没有被一个工艺使用时,它很可能被另一个工艺重新利用,而不是被处理掉。当再利用不太受欢迎时,可以通过更常见的政策工具(例如处置费)来促进它,而不是本文讨论的复杂激励计划。
已经采取了几个步骤,以确保替代LCI的比较合理地反映了基于实践中的再利用过程和基准生产水平的实际再利用效益。首先,访问了24家CUR公司,并进行了详细的访谈,以了解使用废物前后生产过程的变化,废物对原始投入材料的可替代性以及产品功能和质量的任何变化。在可能的情况下,收集每家公司的生产和排放清单。其次,从环境影响评估、清洁生产审计或具有相同再利用过程的个别公司的项目评估报告中收集可复制清单,主要是通过在在线文件库中搜索作为行业数据三角测量的一种手段。来自多家公司的库存提供了更好的代表性。还进行了检索,以确定和评估不符合CUR条件的同一产品的替代工艺。第三,产品标准、工业清洁生产标准和关于废物再利用的LCA文献提供了额外的信息,使清单更加完整或适用于不同情况。选择更严格的标准作为基线,以保证收益来自重用而不是抽样偏差。第四,在信息仍然有限的情况下,可以根据材料和能源平衡以及工业中使用的常见转换率来计算废物对原始材料或燃料的替代性。
此外,江苏省与能源相关的排放被明确建模并用于其他清单。江苏含东电网的发电量清单是根据蔡及其同事(25)和Henriksson及其同事的方法建立的。(26) 该清单考虑了2011年东电网地区1000多家发电厂中每家发电厂的发电、燃料来源和安装的污染控制装置的组成统计数据。热锅炉和燃烧其他燃料的排放系数是根据中国的能源统计、清洁生产标准和温室气体(GHG)协议确定的。(27) 最后,LCI 数据库 Ecoinvent 3.1 (28) 用于背景清单和来自其他来源的信息有限时。
通用 LCI 采用具有相同废物投入和产品的所有 CUR 指定流程的平均废物再利用水平,并可直接应用于所有流程。其他工艺是根据使用相同产品和类似废物投入确定的通用工艺进行估算的,保持每单位废物再利用的环境效益相同。根据同一行业中通用工艺的总体平均值,对具有不同产品的剩余一些工艺进行估算,保持单位物理产出的环境效益不变。
清单分析的结果被分类并分为五类进行影响评估:能源消耗、SO 2 排放、NO x 排放、温室气体排放和颗粒物排放。前三项是中国国家政策的主要指标(29),而后两项则涉及公众广泛关注的问题:气候变化和雾霾。通过关注这五大类,废物再利用的好处与中国的主要环境问题有关。
Aggregate Benefits of Industrial Waste Reuse
工业废弃物再利用的综合效益
图 2 给出了所有 CUR 活动相对于相同产品的平均产量的收益。所有CUR活动都带来了所有五个类别的收益。总共节省了 161 拍焦耳的能源,避免了 2300 万吨二氧化碳 2 当量、75 000 吨 SO 2 当量、33 000 吨 NO X 和 28 000 吨 PM 10 当量的排放。2011年,江苏省整个工业部门的能源消耗总量为2.5%,温室气体排放量为3%,SO 2 为7.3%,NO X 为2.8%,颗粒物排放量为5.8%。
温室气体排放总量包括CO 2 、CH 4 和N 2 O,根据省级统计数据和燃料燃烧和水泥生产的排放因子计算,而其他则直接来自统计年鉴。由于工业部门贡献了全省77%-97%的能源消耗和空气污染(图1),因此对整个社会的效益是显着的。从2011年江苏省CUR节约能源总量来看,我们发现它相当于全中国无水可再生能源发电总量的40%。从江苏省的角度来看,省电节能量是江苏省核能和所有可再生能源发电量总和的两倍多。大部分缓解措施是在建筑材料部门实现的,因为它涉及最多的 CUR 公司和废物。金属工业中的 CUR 对 SO 2 和颗粒物的减少也做出了巨大贡献,尽管该行业的废物再利用规模相对较小。
Figure 2 图2
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0003.gif)
Figure 2. . Energy savings and emission reductions from waste reuse relative to the industrial total energy consumption and emissions in Jiangsu. Benefits from individual firms are aggregated into five industrial sectors: chemical and petrochemical products, metals, construction materials, wood board products, and supply of fuel and energy. The absolute amount of reduction is shown on the right side of each bar.
图2..相对于江苏省工业总能耗和排放量而言,废物再利用所节省的能源和减排量。单个公司的收益汇总为五个工业部门:化学和石化产品、金属、建筑材料、木板产品以及燃料和能源供应。减少的绝对量显示在每个柱线的右侧。
Extent of Benefits Across Industries
各行各业的效益程度
为了了解每个行业的平均生产过程在多大程度上可以通过使用废物投入来减轻其对环境的影响,将每个行业的总收益除以该行业的产出(图3)。货币产出用于跨行业部门的比较。一般而言,使用废物代替初级生产投入在金属制造以及能源和燃料供应方面产生较大的环境效益,而在制造木制品方面产生较小的效益。具体而言,废物再利用使不同行业在不同维度上更加清洁。在化工和石化制造以及燃料和能源供应方面实现了更高的节能。在能源和燃料供应以及建筑材料生产方面,最大限度地实现了温室气体和无温 X 室气体的减排。在金属生产中,SO 2 和颗粒物的减少最为显著,而在燃料和能源供应中则较小。这种差异反映了常规生产的污染状况。例如,石化产品严重依赖石油,而金属生产与高排放的 SO 2 和颗粒物有关。因此,在石化产品的节能以及减少金属中的SO 2 和颗粒物排放方面,潜在的效益更高。
Figure 3 图3
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0004.gif)
Figure 3. Environmental benefits per output in five industries when using waste as inputs.
图3.使用废物作为投入品时,五个行业的每产出环境效益。
Extent of Benefits Across Products
不同产品的效益程度
我们仔细研究同一行业内的不同产品,以比较废物再利用在生产中的环境效益。在比较同一行业或类似行业内的类似产品时,效益是根据所生产产品的相同重量来衡量的。图4a比较了化学产品和石油产品(图4a)。一个行业内废物再利用效益的差异并不比行业之间的差异小。通过使用废物投入,生产人造纤维和轮胎对环境的影响大大减少,而生产硫磺和柴油的排放减少要小得多。与上述行业之间不同类型的效益一样,不同产品的效益差异也可能反映了原始生产过程对环境影响的差异。一吨纤维或轮胎生产比一吨硫或生物柴油生产的投入和排放要高得多,后者通常与其他主要产品一起生产。因此,前者重用的潜在好处大于后者。
在建筑材料产品中也观察到相同的模式(图4b)。水泥的能源消耗和碳排放最密集,因此使用废物投入带来了最大的收益。砂浆和混凝土产品只含有一小部分水泥。因此,废物再利用在生产这些产品方面的效益成比例地较小。与不同行业的差异相比,生产同一行业产品的效益在废物再利用效益的构成上的差异要小得多,因为一个行业内的生产和排放清单比跨行业更相似。
石化和建筑行业之间的对比如图4a和b以及图3所示,产量以其他方式衡量。比较两种衡量产出的方法表明,当以重量衡量产出时(图4),每个产出的收益差异比以货币计量(图3)要大得多。图4a和图b的比例相差20倍以上,而图3中的a则相差3倍以上。虽然实物产出可能与废物再利用的数量更好地相关联,但制造业商品的货币产出越高,总投入越高,工艺越复杂,环境影响越大。如上所述,废物再利用通常会在对环境影响较大的行业和产品中带来更多好处,因为有更大的改进潜力。因此,估计收益与货币产出的差异比与物理重量的差异更大。
Same Product, Different Waste Inputs
相同的产品,不同的废物输入
图4b中的两种产品(混凝土产品和烧制砖)说明了使用替代废物投入的相同生产。虽然生产过程保持不变,但与使用矿山尾矿作为投入相比,使用粉煤灰制造混凝土产品对环境的影响要小得多。这是因为粉煤灰可以部分替代混凝土中的水泥,而矿山尾矿只能替代粗骨料和细骨料,即通常是砾石和沙子。水泥的上游生产对环境的影响很大,因为它比骨料生产有更多的能源使用和排放。同样,与使用粉煤灰或河流和湖泊沉积物相比,使用煤矸石生产烧制砖对环境的影响要小得多,因为煤矸石更好地取代了对环境影响大的砖生产部分:烧窑中的煤炭使用。虽然三种类型的废物(煤矸石、粉煤灰和沉积物)中的大多数都可以作为粘土的替代品,但煤矸石具有更高的热值,可以替代所有煤炭的使用。粉煤灰和河流沉积物的热值要低得多,只能替代部分煤炭使用。
Figure 4 图4
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0005.gif)
Figure 4. Avoided emissions in production of one tonne of (a) petroleum, chemical, and petrochemical products and (b) construction products with waste as inputs. Waste used in each product is shown in parentheses.
图4.避免生产一吨 (a) 石油、化工和石化产品以及 (b) 以废物为原料的建筑产品的排放。括号中显示了每种产品中使用的废物。
Same Waste, Different Products
相同的废物,不同的产品
来自林业和农业的粉煤灰和残留物是可用于替代工艺以生产不同产品的废物的例子。图 5 衡量并描述了基于为每种不同最终用途再利用的一吨废物的效益。在两个图中,具有最大收益的重用过程都缩放到 100%,因此可以快速可视化跨过程的比较。例如,粉煤灰可用作六种建筑材料产品的废物输入,其中水泥生产对环境效益最大。平均而言,粉煤灰占水泥生产中材料投入的 35%,远低于混凝土产品的 60% 和砖块的 70%。但粉煤灰取代了水泥熟料,水泥熟料是与窑内加热过程中的大量煤炭消耗和碳排放相关的最环保的成分;粉煤灰含量还可以减少水泥生产中粉磨的电力消耗。相比之下,当用于砂浆和蒸压加气混凝土 (AAC) 砌块时,只有一小部分粉煤灰可以替代水泥,其余的可以替代砾石或沙子,这些粉煤灰对上游生产的环境影响要小得多。与砂浆和加气混凝土砌块相比,其他混凝土产品所含的水泥比例甚至更小,并且使用粉煤灰的好处更少。当用于烧砖时,粉煤灰的好处主要来自其替代煤炭使用的热值,然而,这比粉煤灰替代水泥熟料时避免的煤炭使用要小得多。
Figure 5 图5
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0006.gif)
Figure 5. Avoided energy consumption and emissions by using the same waste in different processes: (a) one tonne of fly ash used in production of cement, mortar, concrete, autoclaved aerated concrete (AAC) blocks, fired bricks, and fly ash bricks; (b) one tonne of forest and agricultural residues used in production of heat, medium-density fiberboard (MDF), and particle board. The process with the largest reuse benefits is scaled to 100% thus constituting the boundary of each pentagon.
图5.通过在不同工艺中使用相同的废物来避免能源消耗和排放:(a) 用于生产水泥、砂浆、混凝土、蒸压加气混凝土砌块、烧制砖和粉煤灰砖的一吨粉煤灰;(b) 用于生产热力、中密度纤维板和刨花板的一吨森林和农业残留物。具有最大重用效益的过程被缩放到 100%,从而构成每个五角大楼的边界。
创造不同效益的替代再利用方法的另一个例子是森林和农业残留物。在木板生产中,一部分残渣用作原料,以替代木屑和颗粒,其余部分(主要是不合格的树皮)用作燃料。刨花板生产的环境效益较小,而中密度板(MDF)生产的环境效益较大,因为中密度纤维板生产中用于燃料和替代煤炭的不合格原料比例较高。然而,最大的好处是仅将残留物用作热锅炉中的燃料以产生热量或蒸汽。根据政府间气候变化专门委员会(IPCC)的数据,减少生物质的温室气体排放主要是通过考虑土地利用变化而不是能源部门的直接二氧化碳 2 排放来贡献的。(30, 31)虽然这种温室气体减排可以被反对,但随着木板生产作为长期储存碳的手段的存在,在热锅炉中使用残留物的 SO 2 、NO X 和颗粒物的其他减少仍然很大,因为江苏和中国的大多数热锅炉都是燃煤的,污染物排放量很大。然而,当使用清洁能源时,研究表明,木板生产是首选的再利用方法。(32)
More Benefits with the Same Reuse Level.
在相同的重用级别下获得更多好处。
为了更清楚地表明再利用过程的类型对整体效益有重大影响,我们探讨了一种方案,即砖、砂浆和混凝土中使用的所有粉煤灰都转移到水泥生产中,而用于木板制造的所有林业和农业残留物都转移到热能生产中。将这种反事实情景的节能和减排的总体效益与图 2 所示的 CUR 的实际效益进行了比较。如果 CUR 中的任何废物再利用没有增加,而只是将两种废物流重定向到具有更高再利用效益的工艺,则总体效益将增加 28%-37%(图 6)。作为建筑材料行业的一部分,水泥生产的收益增加是适度的,因为该行业的许多公司已经积极参与使用废物,总产量的 38% 获得了 CUR 认证。使用目前用于其他CUR活动的粉煤灰只能增加9%的水泥产量。
Figure 6 图6
![](/cms/10.1021/acs.est.5b05098/asset/images/medium/es-2015-05098y_0007.gif)
Figure 6. Contributions to industrial energy savings and emissions reduction from current CUR production (upper in each category, as in Figure 2) and a reshuffling scenario (lower in each category) where fly ash and forestry and agricultural residues in other reuse processes are diverted to cement production and heat generation, respectively.
图6.当前CUR生产对工业节能和减排的贡献(每个类别中较高,如图2所示)和重新洗牌情景(每个类别较低),其中粉煤灰和其他再利用过程中的林业和农业残留物分别被转移到水泥生产和供热中。
相比之下,作为能源部门的一部分,热发电通过使用目前用于木板制造的残留物来贡献更高的效益。虽然在情景下,残留物产生的热量将增加50倍,但总热量仍将低于江苏总热量的10%,这表明如果将目前CUR认证中遗漏的额外残留物包括在内,将带来更多潜在的好处。
通过严格认证的CUR活动,将无害废物重新投入工业生产,使江苏工业部门的能源使用和污染排放减少了2.5%至7%以上。由于工业部门占全省能源使用量和NO X 排放量的近80%,占SO 2 和颗粒物排放量的90%或更多(图1),因此对整个省来说,减少量也不容小觑。虽然一些研究认为,对于某些产品来说,当包括使用阶段时,再制造可能不会节省能源,但(33)这里的结果有所不同,尽管相对节能小于相对减少的污染排放。虽然选择了一个高水平的基线以避免高估废物再利用效益,但结果仍然更好。有几个可能的原因:本研究涵盖的商业活动已经在实践中,因此经过了市场的考验;许多产品与功能的改进有关,或者至少在使用阶段没有功能变化;CUR政策严格要求获得税收减免认证的公司在使用废物时不得损害环境绩效和产品质量。考虑到 CUR 在许多拥有大量废物来源和潜在用户的地方没有得到同样好的实施,而且 CUR 只涵盖了部分再利用的可能性,因此通过鼓励废物再利用,中国工业生产更绿色的潜力更大。
目前CUR的政策激励措施是退还部分或全部增值税,并增加企业所得税基数的扣除额,这两者都与企业的货币产出有关。虽然将激励措施与再利用废物的物理量联系起来以鼓励更多的再利用似乎更合理,但我们的结果表明,再利用的环境效益通常与货币产出的相关性高于与物理产出的相关性,而实际产出与再利用量成正比。各行业单位货币产出的收益程度差异要小得多,而每个实物产出的收益相差几个数量级(图4)。因此,除非能够根据废物数量制定更精细的再利用激励措施,否则税收减免通常比基于数量的激励措施更能通过再利用促进环境效益。
然而,制定一个更精细的废物再利用激励计划似乎是必要的:在使用各种衡量标准时,不同行业和流程的再利用效益总是存在很大差异。特别是,同一废物的替代再利用方法和同一产品中使用的替代废物输入可以产生截然不同的环境效益。图 6 中的方案只需将两种废物流(粉煤灰以及来自森林和农业的残留物)重定向到具有最高再利用效益的工艺,就可以将 CUR 的总体效益提高 30%。然而,在目前的结构下,每吨废物再利用的税收优惠要接近得多,因为它们的产出和每吨废物的利润都很接近。同样,生产相同产品的激励措施取决于货币产出和利润,而不是使用哪种废物。另一方面,再利用效益通常由废物的类型和再利用方法决定,如结果所示。
尽管我们指出需要制定更有针对性的政策,但目前的结果不足以支持仅靠这项工作制定更精细的激励计划。需要进一步的研究来衡量环境效益的货币价值,这通常是在当地背景下进行的,以评估增加的行政成本,并探索公司对激励措施的长期战略。因此,展望未来,中国的CUR政策应继续考虑更多的工业产品和工艺,并更多地关注如何最好地实现这些财政激励措施所刺激的环境收益。本文开始了这一过程。
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b05098.
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We thank the Energy Saving and Comprehensive Utilization Division at the Jiangsu Economic and Information Technology Commission for providing the CUR data, and also the respondents from both CUR firms and regulatory agencies for participating in interviews. This research has benefited from helpful comments of Reid Lifset, Philip Nuss, Daqian Jiang, Miriam Diamond, three anonymous reviewers, and participants of the International Society for Industrial Ecology 2015 Conference at the University of Surrey, UK. The authors appreciate the support of the National Science Foundation in writing the paper through its Partnerships for International Research and Education Program 1243535.
我们感谢江苏省经济和信息化委员会节能综合利用处提供CUR数据,也感谢CUR公司和监管机构的受访者参与采访。这项研究得益于Reid Lifset,Philip Nuss,Daqian 江,Miriam Diamond,三位匿名审稿人以及英国萨里大学国际工业生态学会2015年会议的参与者的有益评论。作者感谢美国国家科学基金会(National Science Foundation)通过其国际研究与教育伙伴关系计划(Partnership for International Research and Education Program 1243535)撰写论文的支持。
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- 9Costa, I.; Massard, G.; Agarwal, A. Waste management policies for industrial symbiosis development: Case studies in European countries J. Cleaner Prod. 2010, 18 (8) 815– 822 DOI: 10.1016/j.jclepro.2009.12.019Google ScholarThere is no corresponding record for this reference.
- 10Van Berkel, R.; Fujita, T.; Hashimoto, S.; Geng, Y. Industrial and urban symbiosis in Japan: Analysis of the Eco-Town program 1997–2006 J. Environ. Manage. 2009, 90 (3) 1544– 1556 DOI: 10.1016/j.jenvman.2008.11.010Google ScholarThere is no corresponding record for this reference.
- 11Dinan, T. M. Economic efficiency effects of alternative policies for reducing waste disposal Journal of environmental economics and management 1993, 25 (3) 242– 256 DOI: 10.1006/jeem.1993.1046Google ScholarThere is no corresponding record for this reference.
- 12Palmer, K.; Walls, M. Optimal policies for solid waste disposal taxes, subsidies, and standards Journal of Public Economics 1997, 65 (2) 193– 205 DOI: 10.1016/S0047-2727(97)00028-5Google ScholarThere is no corresponding record for this reference.
- 13Fullerton, D.; Wolverton, A. The two-part instrument in a second-best world Journal of Public Economics 2005, 89 (9) 1961– 1975 DOI: 10.1016/j.jpubeco.2004.06.011Google ScholarThere is no corresponding record for this reference.
- 14Jiangsu Statistical Bureau. Jiangsu Statistical Yearbook 2013; China Statistics Press, 2014.Google ScholarThere is no corresponding record for this reference.
- 15Ministry of Environmental Protection of China. National Environmental Statistics Communique 2013, 2015.Google ScholarThere is no corresponding record for this reference.
- 16Pauliuk, S.; Wang, T.; Muller, D. B. Moving toward the circular economy: the role of stocks in the Chinese steel cycle Environ. Sci. Technol. 2012, 46 (1) 148– 54 DOI: 10.1021/es201904cGoogle Scholar16https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhs1Sis7fE&md5=f43cd38595707d41e0c09a4b225868d1Moving Toward the Circular Economy: The Role of Stocks in the Chinese Steel CyclePauliuk, Stefan; Wang, Tao; Muller, Daniel B.Environmental Science & Technology (2012), 46 (1), 148-154CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)As the world's largest CO2 emitter and steel producer, China has set the ambitious goal of establishing a circular economy which aims at reconciling economic development with environmental protection and sustainable resource use. This work applies dynamic material flow anal. to forecast prodn., recycling, and iron ore consumption in the Chinese steel cycle until 2100 by using steel services in terms of in-use stock per capita as driver of future development. The whole cycle is modeled to det. possible responses of the steel industry in light of the circular economy concept. If per-capita stock sats. at 8-12 tons as evidence from industrialized countries suggests, consumption may peak between 2015 and 2020, whereupon it is likely to drop by up to 40% until 2050. A slower growing in-use stock could mitigate this peak and hence reduce overcapacity in primary prodn. Old scrap supply will increase substantially and it could replace up to 80% of iron ore as resource for steel making by 2050. This would require advanced recycling technologies as manufacturers of machinery and transportation equipment would have to shift to secondary steel as well as new capacities in secondary prodn. which could, however, make redundant already existing integrated steel plants.
- 17Yuan, Z.; Bi, J.; Moriguichi, Y. The circular economy: A new development strategy in China J. Ind. Ecol. 2006, 10 (1–2) 4– 8 DOI: 10.1162/108819806775545321Google ScholarThere is no corresponding record for this reference.
- 18National Bureau of Statistics of China. China Statistical Yearbook 2014; China Statistics Press: , 2014.Google ScholarThere is no corresponding record for this reference.
- 19Ministry of Environmental Protection of China. National Environmental Statistics Communique 2012, 2013.Google ScholarThere is no corresponding record for this reference.
- 20State Economic Commission. Interim Regulation on Issues of Promoting Comprehensive Utilization of Resources; State Economic Commission, 1985.Google ScholarThere is no corresponding record for this reference.
- 21Ministry of Finance of China, State Administration of Taxation of China. Catalog of Value-added Tax Benefits for Comprehensive Utilization of Resources Products and Labor, 2015.Google ScholarThere is no corresponding record for this reference.
- 22Ministry of Finance of China, State Administration of Taxation of China, National Development and Reform Commission of China. Catalog of Coporate Income Tax Benefits for Comprehensive Utilization of Resources, 2008.Google ScholarThere is no corresponding record for this reference.
- 23National Development and Reform Commission of China, Ministry of FInance of China; State Administration of Taxation of China. Regulations on Certification of Nationally Promoted Comprehensive Utilization of Resources, 2006.Google ScholarThere is no corresponding record for this reference.
- 24Jiangsu Statistical Bureau. Jiangsu Statistical Yearbook 2012; China Statistics Press, 2013.Google ScholarThere is no corresponding record for this reference.
- 25Cai, W.; Wang, C.; Jin, Z.; Chen, J. Quantifying baseline emission factors of air pollutants in China’s regional power grids Environ. Sci. Technol. 2013, 47 (8) 3590– 3597 DOI: 10.1021/es304915qGoogle Scholar25https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjsVWrtLc%253D&md5=2640cb66e0174c1401f4bd052149996bQuantifying Baseline Emission Factors of Air Pollutants in China's Regional Power GridsCai, Wenjia; Wang, Can; Jin, Zhugang; Chen, JiningEnvironmental Science & Technology (2013), 47 (8), 3590-3597CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)Drawing lessons from the clean development mechanism (CDM), this work developed a combined margin method to quantify air pollutant baseline emission factor for regional power grids in China. Simple av. SO2, NOx, and PM2.5 baseline emission factors for the 6 power grids in China in 2010 were 1.91, 1.83, and 0.32 kg/MWh, resp. Several low-efficient mitigation technologies (e.g., low NOx burner), were suggested to be replaced or used in conjunction with other technologies to virtually decrease grid emission factors. Synergies between greenhouse gases and air pollution mitigation in the Chinese power sector were also noted. It was estd. that in 2010, every 1% CO2 redn. from the power generating sector resulted in a co-redn. of 1.1%, 0.5%, and 0.8% for SO2, NOx, and PM2.5, resp. Wind was the best technol. to achieve the largest amt. of co-abatement in most parts of China. This method is recommended for developing comprehensive air pollution control strategies and in co-benefit analyses for future CDM approval processes.
- 26Henriksson, P. J. G.; Zhang, W.; Guinée, J. B. Updated unit process data for coal-based energy in China including parameters for overall dispersions Int. J. Life Cycle Assess. 2015, 20 (2) 185– 195 DOI: 10.1007/s11367-014-0816-0Google Scholar26https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFGls77E&md5=7b7a165f3f13e115501325f83d0d84a8Updated unit process data for coal-based energy in China including parameters for overall dispersionsHenriksson, Patrik John Gustav; Zhang, Wenbo; Guinee, Jeroen B.International Journal of Life Cycle Assessment (2015), 20 (2), 185-195CODEN: IJLCFF; ISSN:0948-3349. (Springer)Purpose: Chinese coal power generation is part of the life cycle of most products and the largest single source for many emissions. Reducing these emissions has been a priority for the Chinese government over the last decade, with improvements made by replacing older power plants, improving thermal efficiency and installing air pollution control devices. In the present research, we aim to acknowledge these improvements and present updated unit process data for Chinese coal power. In the course of doing so, we also explore the implementation and interpretation of overall dispersions related to a generically averaged process, such as Chinese coal power. Methods: In order to capture geog. and temporal dispersions, updated unit process data were calcd. for Chinese coal power at both a national and a provincial level. The updated unit process dataset was also propagated into life cycle inventory (LCI) ranges using Monte Carlo simulations, allowing for discrepancies to be evaluated against the most commonly used inventory database (ecoinvent) and overall dispersions to be shown for some selected provinces. Results and discussion: Compared to ecoinvent, the updated dataset resulted in redns. with between 8 and 67 % for all evaluated inventory flows except for dinitrogen monoxide (N2O). However, interprovincial differences in emissions diverged with up to 250 %. A random outcome in a few Monte Carlo runs was inverted operators, where pos. values became neg. or the other way around. This is a known possible outcome of matrix calcns. that needs to be better evaluated when interpreting propagated outcomes. Conclusions: The present manuscript provides recommendations on how to implement and interpret dispersions propagated into LCI results. In addn., updated and easily accessible unit process data for coal power plants averaged across China and for individual provinces are presented, with clear distinctions of inherent uncertainties, spread (variance) and unrepresentativeness. Recommendations are also provided for future research and software developments.
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Abstract 抽象
Figure 1 图1
Figure 1. The overall industrial contribution to total energy consumption and pollution emissions in China and in Jiangsu in 2012. Sources: National Bureau of Statistics of China, (18) Ministry of Environmental Protection of China, (19) and Jiangsu Statistical Bureau. (14)
图 1.2012年中国和江苏省工业总能耗和污染排放总量的总体贡献。资料来源:中国国家统计局、(18)中国环境保护部、(19)和江苏省统计局。(14)Figure 2
Figure 2. . Energy savings and emission reductions from waste reuse relative to the industrial total energy consumption and emissions in Jiangsu. Benefits from individual firms are aggregated into five industrial sectors: chemical and petrochemical products, metals, construction materials, wood board products, and supply of fuel and energy. The absolute amount of reduction is shown on the right side of each bar.
Figure 3
Figure 3. Environmental benefits per output in five industries when using waste as inputs.
Figure 4
Figure 4. Avoided emissions in production of one tonne of (a) petroleum, chemical, and petrochemical products and (b) construction products with waste as inputs. Waste used in each product is shown in parentheses.
Figure 5
Figure 5. Avoided energy consumption and emissions by using the same waste in different processes: (a) one tonne of fly ash used in production of cement, mortar, concrete, autoclaved aerated concrete (AAC) blocks, fired bricks, and fly ash bricks; (b) one tonne of forest and agricultural residues used in production of heat, medium-density fiberboard (MDF), and particle board. The process with the largest reuse benefits is scaled to 100% thus constituting the boundary of each pentagon.
Figure 6
Figure 6. Contributions to industrial energy savings and emissions reduction from current CUR production (upper in each category, as in Figure 2) and a reshuffling scenario (lower in each category) where fly ash and forestry and agricultural residues in other reuse processes are diverted to cement production and heat generation, respectively.
References
ARTICLE SECTIONSThis article references 33 other publications.
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- 17Yuan, Z.; Bi, J.; Moriguichi, Y. The circular economy: A new development strategy in China J. Ind. Ecol. 2006, 10 (1–2) 4– 8 DOI: 10.1162/108819806775545321There is no corresponding record for this reference.
- 18National Bureau of Statistics of China. China Statistical Yearbook 2014; China Statistics Press: , 2014.There is no corresponding record for this reference.
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- 25Cai, W.; Wang, C.; Jin, Z.; Chen, J. Quantifying baseline emission factors of air pollutants in China’s regional power grids Environ. Sci. Technol. 2013, 47 (8) 3590– 3597 DOI: 10.1021/es304915q25https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjsVWrtLc%253D&md5=2640cb66e0174c1401f4bd052149996bQuantifying Baseline Emission Factors of Air Pollutants in China's Regional Power GridsCai, Wenjia; Wang, Can; Jin, Zhugang; Chen, JiningEnvironmental Science & Technology (2013), 47 (8), 3590-3597CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)Drawing lessons from the clean development mechanism (CDM), this work developed a combined margin method to quantify air pollutant baseline emission factor for regional power grids in China. Simple av. SO2, NOx, and PM2.5 baseline emission factors for the 6 power grids in China in 2010 were 1.91, 1.83, and 0.32 kg/MWh, resp. Several low-efficient mitigation technologies (e.g., low NOx burner), were suggested to be replaced or used in conjunction with other technologies to virtually decrease grid emission factors. Synergies between greenhouse gases and air pollution mitigation in the Chinese power sector were also noted. It was estd. that in 2010, every 1% CO2 redn. from the power generating sector resulted in a co-redn. of 1.1%, 0.5%, and 0.8% for SO2, NOx, and PM2.5, resp. Wind was the best technol. to achieve the largest amt. of co-abatement in most parts of China. This method is recommended for developing comprehensive air pollution control strategies and in co-benefit analyses for future CDM approval processes.
- 26Henriksson, P. J. G.; Zhang, W.; Guinée, J. B. Updated unit process data for coal-based energy in China including parameters for overall dispersions Int. J. Life Cycle Assess. 2015, 20 (2) 185– 195 DOI: 10.1007/s11367-014-0816-026https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFGls77E&md5=7b7a165f3f13e115501325f83d0d84a8Updated unit process data for coal-based energy in China including parameters for overall dispersionsHenriksson, Patrik John Gustav; Zhang, Wenbo; Guinee, Jeroen B.International Journal of Life Cycle Assessment (2015), 20 (2), 185-195CODEN: IJLCFF; ISSN:0948-3349. (Springer)Purpose: Chinese coal power generation is part of the life cycle of most products and the largest single source for many emissions. Reducing these emissions has been a priority for the Chinese government over the last decade, with improvements made by replacing older power plants, improving thermal efficiency and installing air pollution control devices. In the present research, we aim to acknowledge these improvements and present updated unit process data for Chinese coal power. In the course of doing so, we also explore the implementation and interpretation of overall dispersions related to a generically averaged process, such as Chinese coal power. Methods: In order to capture geog. and temporal dispersions, updated unit process data were calcd. for Chinese coal power at both a national and a provincial level. The updated unit process dataset was also propagated into life cycle inventory (LCI) ranges using Monte Carlo simulations, allowing for discrepancies to be evaluated against the most commonly used inventory database (ecoinvent) and overall dispersions to be shown for some selected provinces. Results and discussion: Compared to ecoinvent, the updated dataset resulted in redns. with between 8 and 67 % for all evaluated inventory flows except for dinitrogen monoxide (N2O). However, interprovincial differences in emissions diverged with up to 250 %. A random outcome in a few Monte Carlo runs was inverted operators, where pos. values became neg. or the other way around. This is a known possible outcome of matrix calcns. that needs to be better evaluated when interpreting propagated outcomes. Conclusions: The present manuscript provides recommendations on how to implement and interpret dispersions propagated into LCI results. In addn., updated and easily accessible unit process data for coal power plants averaged across China and for individual provinces are presented, with clear distinctions of inherent uncertainties, spread (variance) and unrepresentativeness. Recommendations are also provided for future research and software developments.
- 27World Resources Institute. Greenhouse Gas Protocol Tool for Energy Consumption in China (Version 2.1), 2013.There is no corresponding record for this reference.
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