Highway road domain multi-dimensional environment negative effect list construction method

Abstract

The invention discloses a highway road domain multi-dimensional environment negative effect list construction method. The method comprises the following steps: step 1, establishing a highway engineering-environment element matrix; step 2, carrying out heterogeneity detection, uncertainty analysis and sensitivity analysis on the emission coefficients EFi, j, k of the various pollutants, and calculating a random effect mean value or a fixed effect mean value of the emission coefficients of the various pollutants as an emission coefficient EF; step 3, calculating the emission intensity Ii of each pollutant in combination with the emission coefficient EF obtained in the step 2; 4, calculating negative effects CH, CA, CW and CL of human, air, water and soil as protection targets in combination with the Ii obtained in the step 3; and step 5, constructing a highway road domain multi-dimensional environment negative effect list from time and space dimensions. According to the method, a highway road domain multi-dimensional environment negative effect list is constructed from time and space dimensions, and highway project environment negative effects can be comprehensively quantified from unit process, time and space dimensions in a regional, staged, index and element manner.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of highway infrastructure environmental protection, in particular to a highway road area multi-dimensional environmental negative effect list construction method. BACKGROUND

[0002] The global highway network will add about 25 million kilometers by 2050, and large-scale highway construction, operation, maintenance and other activities will continue to bring a large amount of pollutants and waste and other environmental problems, and aggravate the negative environmental impact. Due to the huge amount of highway infrastructure engineering, involving many environmental factors, organized emissions, unorganized emissions, and complex pollution emission links, the sources are complex, the distribution is scattered, the influencing factors are numerous, and the emission characteristics are different. At present, there is a lack of comprehensive and systematic analysis, and it is difficult to fully grasp the negative impact of highway activities on the environment, which restricts the accurate development of highway environmental protection measures and the research and development of low-impact technology.

[0003] In view of the unclear spatio-temporal law of environmental negative impact of various highway activities, by collecting literature, highway construction monitoring reports and field monitoring, integrating multi-source data by using literature metrology, cluster analysis and data preprocessing, the environmental negative impact of highway projects in the whole process and all environmental factors is researched, and a set of construction method of highway traffic infrastructure road area multi-dimensional environmental negative effect list is proposed. The key links and processes of environmental negative impact of various highway activities, the spatio-temporal characteristics and laws, the emission path and influence degree of pollutants are clarified, the environmental negative impact of highway traffic infrastructure construction and operation activities is comprehensively analyzed, and the evolution from "single factor static analysis" to "multi-dimensional dynamic management" is realized. Provide a theoretical basis for reducing the negative effects of highway environment. SUMMARY

[0004] The purpose of the present application is to provide a highway road area multi-dimensional environmental negative effect list construction method in view of the technical defects in the prior art.

[0005] The technical scheme adopted to achieve the purpose of the present application is: A highway road area multi-dimensional environmental negative effect list construction method, comprising the following steps: Step 1, the direct emission pollutants of different unit processes of highway projects are determined, a highway engineering-environmental factor matrix is established, the pollution sources in the construction stage and the operation stage are classified from the time and space dimensions, and the pollution source list of the unit process dimension engineering adaptation is established; Step 2, based on various pollution emission monitoring data sources, the emission coefficients of various pollutants Carrying out heterogeneity detection, uncertainty analysis and sensitivity analysis, quantifying fixed effects and random effects, calculating the random effect mean of the emission coefficients of various pollutants or fixed effects mean As emission factor ; Step 3: Establish an emission intensity inventory for unit engineering quantities at the unit process level, including unorganized emissions of air pollutants and organized emissions of water and soil pollutants, combined with the emission coefficients obtained in Step 2. Calculate the emission intensity of each pollutant. ; Step 4: Establish a receptor list for multi-protection targets at the unit process dimension, combining it with the information obtained in Step 3. Calculate the negative effects on human beings, air, water, and soil as protection targets. , , and ; Step 5: Construct a multi-dimensional list of negative environmental effects of the highway network from temporal and spatial dimensions: based on the results obtained in Step 4. , , and Calculate the first Year The combined negative environmental effects of various pollutants in the province And the overall negative effects Detect the changing trends in the time and space dimensions.

[0006] In the above technical solution, in step 1, the unit process of highway engineering in the highway engineering-environmental element matrix includes roadbed engineering, pavement engineering, bridge engineering, tunnel engineering and temporary engineering, and the environmental elements include atmospheric environment, water environment, sound environment, soil environment and light environment.

[0007] In the above technical solution, the data sources in step 2 include academic papers, on-site monitoring, and public reports.

[0008] In the above technical solution, in step 2, the fixed effect mean The calculation formula is:

[0009] in, For the first The first study The first type of energy Estimated emission coefficients for various pollutants. For the first The first study The first type of energy Weighting coefficients for various pollutants n To monitor the total number of times, For the first The first study The first type of energy Standard error of each pollutant; random effects mean The calculation formula is:

[0010] The weights of the random effects, , Variance between different studies.

[0011] In the above technical solution, step 2 uses the Cochran's Q test or To examine and assess the heterogeneity among different studies; when At that time, emission coefficient Using the mean of random effects ,when At that time, emission coefficient Using fixed effects mean ; Or, when When ≤25%, emission factor Using fixed effects mean ,when At 25%, the emission factor Using the mean of random effects .

[0012] In the above technical solution, in step 3, when the pollutant is an air pollutant, Adopting the first of a certain province Average emission intensity of pollutants , , These are the weighting coefficients. For the first The standard error of a typical project For a certain province The first typical project Emission intensity of pollutants of this type , For a certain province In a typical project, the first part of the workload... Emissions of pollutants of this type , For a certain province In the unit work volume of a typical project, the first Working hours of various types of construction machinery For the first The first type of construction machinery Energy consumption coefficient, For the first The first type of construction machinery The first type of energy Emission coefficients of various pollutants For a certain province In a typical project, the first part of the workload... Emissions of pollutants of this type , For a certain province Asphalt consumption per unit of work in a typical project For a certain province In a typical project, the volume of asphalt mixture... Emission coefficients of various pollutants For a certain province PM2.5 in dust during a typical project's workload 10 Emissions , Ground temperature; The relative humidity of the air near the ground; This refers to the distance from the dust source. Ground wind speed; This refers to the workload of a typical project in a certain province.

[0013] In the above technical solution, in step 3, when the pollutants are water pollutants and soil pollutants, use , , For a certain province The first typical project Emission intensity of pollutants of this type For a certain province The first typical project Emissions of pollutants of this type For the first Sample size for each project; For a certain province The workload of a typical project.

[0014] In the above technical solution, in step 4, , The negative effects of various pollutants on human receptors per unit of engineering work in a certain province. For a certain province Emission intensity of pollutants of this type , , , , , , These are the characteristic coefficients of the indices GWP, ODP, PMFP, HOFP, HTPc, HTPnc, and WCP, respectively. , , , , , , These are the standardized coefficients of the indicators GWP, ODP, PMFP, HOFP, HTPc, HTPnc, and WCP, respectively. , The negative impacts of various pollutants on air receptors per unit volume of engineering work in a certain province. , , These are the characteristic coefficients of the indicators GWP, ODP, and EOFP, respectively. , , These are the standardized coefficients of the indicators GWP, ODP, and EOFP, respectively. , The negative impacts of various pollutants on water receptors per unit volume of a certain province; , , , These are the characteristic coefficients of the indices FEP, FETP, METP, and WCP. , , , The standardized coefficients for the indicators FEP, FETP, METP, and WCP; , The negative impacts of various pollutants on soil receptors per unit volume of a project in a certain province; , , These are the characteristic coefficients of the indices TAP, TETP, and LOP. , , These are the standardized coefficients for the indicators TAP, TETP, and LOP.

[0015] In the above technical solution, in step 5, , For the first Year Province No. The average comprehensive negative environmental impact of various pollutants per unit volume of a given project type. No. Year The mileage of roads, bridges, or tunnels in a province; , For the first Year Province No. Negative effects of various pollutants on humans per unit volume of various engineering projects The arithmetic mean of multiple items, For the first Year Province No. Negative air pollution effects per unit volume of various engineering projects The arithmetic mean of multiple items, For the first Year Province No. Negative impacts of various pollutants on water bodies per unit volume of various project types The arithmetic mean of multiple items, For the first Year Province No. Negative impacts of various pollutants on soil per unit volume of various engineering projects The arithmetic mean of multiple items.

[0016] In the above technical solution, the specific steps for detecting the time dimension change trend in step 5 are as follows: Use the Mann-Kendall trend test statistic , , For the first p +1 year q The overall negative effects of the province For the first p Year q The overall negative effects of the province n Defined as the total number of years. The function is ,like This indicates that the negative effects in later years tend to be higher than in earlier years, and the overall negative effects of highway pollutants show an upward trend over time; if This indicates that the overall negative effects of highway pollutants are decreasing over time; if This indicates that there is no monotonic trend; Sen's slope is used to quantify the rate of change or the annual average change in trends. : , For the first s Year q The overall negative effects of the province hour, This represents the annual growth rate of the overall negative effects of highway pollutants. When, it represents the annual decay rate; The Pettitt test for nonparametric mutation points was used to determine the mutation points. Statistic : , For the first t Year q The overall negative effects of the province For any year; Line graphs and box plots are used to represent the temporal distribution of the comprehensive negative environmental effects between provinces each year.

[0017] In the above technical solution, the specific steps for detecting the spatial dimension change trend in step 5 are as follows: Constructing the spatial weight matrix : ; Spatial autocorrelation is measured using global Moran's I: , For global Moran's I coefficients, This indicates that the overall negative effects of highway project pollutants in a certain year exhibit a positive spatial correlation, i.e., spatial clustering. This indicates that the overall negative effects of highway project pollutants in a certain year are spatially negatively correlated, i.e., spatially dispersed. The total number for each province. For the first Year The combined negative effects of each province For the first Year The combined negative effects of each province These are the weighting coefficients; For the first The average of the combined negative effects across all provinces in a given year. ; in accordance with

[0018] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention establishes an engineering-adapted pollution source list, a unit engineering quantity emission intensity list, and a multi-protection target receptor list at the unit process level. It analyzes the coupling relationship between the engineering parts of the highway project and various environmental elements, and constructs a multi-dimensional environmental negative effect list of the highway area from the time and space dimensions. It can comprehensively quantify the environmental negative effects of the highway project by region, stage, indicator, and element from the unit process, time, and space dimensions.

[0019] 2. This invention proposes a method for calculating air pollutant emissions based on engineering quantities and a method for calculating the emission intensity of various pollutants based on unit engineering quantities. It addresses both fugitive emissions of air pollutants and organized emissions of water and soil pollutants. The method integrates multi-source data from various academic papers, on-site monitoring, and public reports on pollutant emissions, conducting heterogeneity detection, uncertainty analysis, and sensitivity analysis. It quantifies fixed and random effects, extracts energy consumption and various pollutant emissions during highway construction based on multi-source data, forms a quantified engineering emission data list, and calculates the mean and confidence intervals of various pollutant emission intensities. This provides data and theoretical basis for the scientific, objective, and accurate quantification of pollutant emission benchmarks.

[0020] 3. This invention proposes a comprehensive analytical framework for engineering components (roads, bridges, and tunnels) – emission sources – emission intensity – emission pathways – environmental receptors – impacts. It links the bill of quantities and quotas, quantifying the emission intensity and negative effects of various pollutants at different engineering components within the road area at the unit process level. By comprehensively applying multiple statistical models to detect spatiotemporal variation characteristics, it can analyze the sources of various pollutants such as asphalt fumes, exhaust gases, heavy metals, oil pollution, road and bridge runoff, and harmful gases from tunnels. This helps to comprehensively reveal the spatiotemporal patterns of negative impacts on the atmosphere, water, and soil environment throughout the entire process of highway construction and operation. Attached Figure Description

[0021] Figure 1 This is a flowchart of the construction method of the present invention.

[0022] Figure 2 It is a matrix of environmental elements for highway engineering during the construction period.

[0023] Figure 3 It is a pollution source inventory framework.

[0024] Figure 4 Main data sources and classifications during the construction period.

[0025] Figure 5 It is a receptor list framework. Detailed Implementation

[0026] The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0027] A method for constructing a multidimensional environmental negative effects inventory of highway areas includes the following steps: Step 1: Establish a pollution source list adapted to the unit process dimension engineering.

[0028] Step s11: Identify the direct emissions of pollutants in the unit processes of the highway project and establish a highway engineering-environmental element matrix.

[0029] During the construction of highways, including temporary works, tunnels, bridges, pavements, and subgrades, disturbances to environmental elements such as the atmosphere, water, sound, soil, and light inevitably occur, causing varying degrees of negative environmental impact. Common pollution sources include dust, exhaust fumes, smoke, construction noise, construction wastewater, domestic sewage, waste residue, waste oil, and strong nighttime light. This analysis of the main pollution-causing construction phases of highway construction summarizes the types and characteristics of major pollution sources during the construction period of each unit project. Based on quantitative analysis, the system systematically outlines the correspondence between highway engineering, emission stages, environmental elements, and pollution impacts, establishing a matrix corresponding to different engineering parts and environmental elements during the highway construction period (e.g., ...). Figure 1 As shown), specifically: The main environmental negative impacts of temporary works are as follows: dust and exhaust fumes generated from material loading, unloading and transportation activities such as construction access roads, material storage yards, and borrow pits, as well as asphalt fumes and other smoke generated from asphalt mixing plants, cause air pollution; construction wastewater generated from concrete mixing plants, prefabrication yards, and material storage yards, as well as domestic sewage generated from living camps, cause water pollution; construction noise generated by the use of machinery and transport vehicles during construction activities causes noise pollution; soil pollution caused by waste from concrete mixing plants, prefabrication yards, and material storage yards; and light pollution caused by strong nighttime light generated by nighttime construction at various sites.

[0030] The main negative environmental impacts of tunnel engineering are as follows: dust, exhaust gas, and asphalt fumes generated during blasting operations, muck transportation, and asphalt mixing cause air pollution; waste oil and slag generated by the use of machinery and transport vehicles during construction activities are affected by water inrush, causing water and soil pollution; construction noise generated by the use of machinery and transport vehicles during blasting operations and tunnel ventilation causes sound pollution; and strong light generated during nighttime construction inside the tunnel causes light pollution.

[0031] The main environmental negative impacts of bridge engineering are as follows: exhaust fumes and dust generated by the use of machinery and transport vehicles during pile foundation construction and bridge deck paving processes cause air pollution; waste oil and slag generated by the use of machinery and transport vehicles during construction activities are affected by rainwater runoff, causing water and soil pollution; construction noise generated by the use of machinery and transport vehicles during construction activities causes sound pollution; and strong light generated during nighttime construction causes light pollution.

[0032] The main environmental negative impacts of road construction projects are as follows: asphalt fumes and other fumes generated during asphalt mixing and paving, as well as exhaust fumes and dust generated during material transportation, cause air pollution; waste oil from machinery and equipment causes soil pollution; and construction noise generated by the use of machinery and transport vehicles during construction activities causes acoustic pollution.

[0033] The main environmental negative impacts of roadbed engineering are as follows: exhaust fumes and dust generated by the use of machinery and transport vehicles during site clearing, roadbed excavation and filling, and earthwork transportation cause air pollution; waste oil from machinery used during roadbed filling and excavation is carried by rainwater runoff, causing water and soil pollution; and construction noise generated by the use of machinery and transport vehicles during construction activities causes noise pollution.

[0034] Step s12: Establish a pollution source inventory.

[0035] Based on the matrix corresponding to different unit processes and environmental elements in highway projects, pollution sources in the construction and operation phases are classified from time and space dimensions. The construction phase is classified by unit process, identifying the generation stages, emission pathways, and types of pollutants and greenhouse gases emitted. Construction activities should include major construction machinery and transport vehicle categories, and pollution sources should include pollutant components such as VOCs and PM, thereby establishing a pollution source inventory framework. Figure 2 ).

[0036] Taking the key emission links and processes resulting from the negative impacts of construction as an example (Table 1), the main pollutants emitted from the exhaust of construction machinery and transport vehicles are PM, COx, NOx, and HCs; the main pollutant from construction dust is TSP; the flue gas emitted from asphalt mixing and paving mainly consists of asphalt fumes and VOCs; the main pollutants from construction wastewater are SS, COD, oil, TP, and TN, while the main pollutants from domestic sewage are COD, BOD5, ammonia nitrogen, and oil. Furthermore, the use of machinery and equipment and the consumption of diesel and gasoline by transport vehicles during construction will generate direct pollutant emissions and greenhouse gas emissions, and the emission concentrations of these pollution sources should be considered.

[0037] Table 1. Major Pollutant Types of Major Environmental Elements During the Construction Phase

[0038] Step 2: Based on pollutant emission monitoring data from different sources such as academic papers, on-site monitoring, and public reports, conduct heterogeneity detection, uncertainty analysis, and sensitivity analysis to quantify fixed and random effects and calculate the mean and confidence interval of emission coefficients for various pollutants.

[0039] Step s21: Integrate data from different sources of pollution emissions.

[0040] Based on environmental monitoring data from highway construction activities, data of different granularities were acquired from three dimensions: monitoring reports, academic papers, and on-site monitoring. Measurement workflows for data extraction, classification, and processing were established for each dimension (e.g., ...). Figure 3 As shown, the above literature data and engineering data are clustered according to data source, pollutant type, and emission location, and a typical highway project engineering environmental monitoring dataset including the main highway project and temporary construction sites is integrated.

[0041] (1) Academic papers The data sources used were the CNKI (China National Knowledge Infrastructure) academic journal full-text database and the Web of Science Science Citation Index Expanded (SCIE) database. The main search terms included: highway, road, pavement, roadbed, bridge, tunnel, construction machinery, construction, exhaust gas, atmosphere, air, CO2, CH4, greenhouse gases, PM2.5, PM 10 Keywords related to different pollutants, such as CO, SO2, NO2, NOx, O3, TSP, VOCs, NMHC, BaP, asphalt fumes, dust, and particulate matter, were selected to establish specialized search formulas for separate searches, spanning the period from 1992 to 2025. In the retrieved literature, abstracts were reviewed one by one to remove those irrelevant to the topic. Full texts were then read to filter pollutant monitoring data related to highway construction activities. Data from relevant images in the literature was extracted using GetData Graph Digitizer software. The raw data from tables and images in the literature were integrated according to geographical distribution, monitoring objects, and pollutant types, and converted into standardized units of measurement.

[0042] (2) On-site monitoring In accordance with the relevant technical specifications of the "Ambient Air Quality Standard" (GB3095-2012), a field monitoring plan was designed in advance. Through a comparison of the adaptability of monitoring equipment and the site, and based on the project construction schedule, suitable monitoring equipment was selected for deployment to monitor TSP and PM2.5 in the atmospheric environment. 10 PM 2.5 Parameters such as SO2, NO2, NO, O3, CO, and TVOC, as well as various water quality parameters of the aquatic environment, are monitored. Before monitoring, the instruments used are calibrated for flow rate, transmembrane, zero point, and span, and the sampler is checked for airtightness on-site as required.

[0043] (3) Public Report Using publicly released environmental protection acceptance survey reports for completed highway or national highway construction projects as the data source, we manually screened those with "air pollution monitoring" in the main text or "construction monitoring CNAS report" in the appendix. We then statistically analyzed and categorized the data by province, year, and number of projects, establishing a data information system that includes project name, province, monitoring object, monitoring time, monitoring target, monitoring location, sampling time, monitoring items, monitoring results, and quality standards. This system includes monitoring targets such as prefabrication yards, mixing plants, asphalt mixing plants, background points, and sensitive points, as well as monitoring indicators such as TSP and PM10.

[0044] Step s22: Calculate the mean emission intensity and confidence interval. (1) Adopt Indicates the first The first study The first type of energy Estimated emission coefficients (kg / kg) for various pollutants, including research from various academic papers, field monitoring, and public reports; energy sources including diesel, gasoline, heavy oil, and electricity; and pollutants including NO. x CO, CO2, VOCs, PM 10 PM 2.5 H2S, SO2, BaP, and pitch fumes. [Using...] Indicates the first The first study The first type of energy Standard error for each pollutant. Extracted from various studies. , Detect outliers and remove those exceeding ±3 The data.

[0045] (2) The weighted average was used to preliminarily calculate the mean of fixed effects. : (1) In equation (1), For the first The first study The first type of energy Weighting coefficients for various pollutants n This refers to the total number of relevant academic papers and public reports, or the total number of monitoring sessions.

[0046] Use Cochran's Q test or To examine and assess the heterogeneity among different studies, (2) In equation (2), Obeying the degree of freedom The chi-square distribution; if , For degrees of freedom The chi-square distribution of 0 0.5 quantile, If there is significant heterogeneity in the number of relevant academic papers, public reports, or monitoring frequency, then a random effects method needs to be used. If there is no significant heterogeneity, then a fixed effect is used.

[0047] (3) In equation (3), Low heterogeneity (≤25%) can be treated with fixed effects; moderate heterogeneity (25%-50%); high heterogeneity (>50%); and heterogeneity (>70%) cannot be directly merged. When the percentage is greater than 25%, a random effect is used.

[0048] (3) The DerSimonian-Laird method was used to calculate the mean of random effects. And estimate the variance between different studies. , (4) Calculate the weights of random effects random effects mean Standard error and 95% confidence interval , (5) (6) (7) (8) When emission factor estimates from different studies exhibit significant, moderate, or high heterogeneity, a random effects approach is adopted, and the emission factors in step 3 are then... (in formula (9)) In equation (10) )use And calculate the standard error. Or 95% confidence interval When the emission factor estimates from different studies do not exhibit significant heterogeneity or have low heterogeneity, a fixed effect is used, and the emission factors in step 3 are... (in formula (9)) In equation (10) )use .

[0049] Step 3: Establish an emission intensity list for unit engineering quantities at the unit process level, including unorganized emissions of air pollutants and organized emissions of water and soil pollutants.

[0050] Step 31: Air pollution emissions based on engineering volume.

[0051] The high-value areas of air pollutants at the construction site are basically consistent with the distribution of construction machinery and equipment, and the emission characteristics are complex. In order to further clarify the key emission links and processes, based on on-site monitoring data and literature quantitative analysis results, the air pollution sources of highway construction activities are divided into "exhaust gas" which is mainly composed of gaseous pollutants, "dust" which is mainly composed of particulate matter, and "smoke gas" which is mainly composed of harmful gas components.

[0052] (1) Exhaust gas Mechanical exhaust refers to the NOx, COx, VOCs, and fine particulate matter emitted from the exhaust of mechanical equipment and transport vehicles powered by diesel internal combustion engines. The emission characteristics are complex and vary greatly due to the combined influence of various factors such as operating conditions.

[0053] Emissions from construction machinery are calculated based on energy consumption and emission factors per unit of fuel: (9) In equation (9), For a certain province In a typical project, the first part of the workload... Emissions (kg) of pollutants, including NO x CO, VOCs, PM 10 PM 2.5 SO2; For a certain province In the unit work volume of a typical project, the first The working hours (shifts) of various construction machinery are derived from the budget documents of this project, specifically from document A, table

[02] , "Table A.0.2-6 Summary Table of Labor, Main Materials, and Construction Machinery Shifts"; For the first The first type of construction machinery The energy consumption coefficient (kg / shift) includes diesel, gasoline, heavy oil, and electricity. The data comes from the "Standard for Shift Costs of Highway Engineering Machinery" (JTG / T 3833). For the first The first type of construction machinery The first type of energy Emission coefficient (kg / kg) for each pollutant.

[0054] (2) Smoke Asphalt fumes are complex and harmful components generated during the mixing, transportation, and paving of asphalt mixtures in the construction of main road surfaces and tunnels, and are significantly affected by temperature. The emissions of asphalt pollutants from asphalt mixing and paving activities are calculated based on material consumption and emission factors per unit material. (10) In equation (10), For a certain province In a typical project, the first part of the workload... Emissions (kg) of pollutants, including NO x CO, CO2, VOCs, PM 10 PM 2.5 H2S, SO2, BaP, asphalt fumes; For a certain province The asphalt consumption (t) per unit of work in a typical project is obtained from the budget document of the project, Group A document [02 Table] "Table A.0.2-6 Summary Table of Labor, Main Materials and Construction Machinery Shifts"; For a certain province In a typical project, the volume of asphalt mixture... Emission coefficient (kg / t) for each pollutant.

[0055] (3) Dust Construction dust, caused by disturbances from transport vehicles, is widely distributed and has a large impact area. It is influenced by factors such as particle size, wind speed, vehicle speed, and road surface cleanliness. Pollution sources include prefabrication plants, blasting sites, construction access roads, borrow pits and spoil heaps, roadbed and pavement construction, tunnel construction, material storage yards, and mixing plants. The construction methods, speed, and equipment used at each stage of construction all affect the amount of dust. PM2.5 is the most prevalent component of this dust. 10 The impact is significant, and its emissions are calculated based on a prediction model fitted from on-site monitoring: (11) In equation (11), For a certain province PM2.5 in dust during a typical project's workload 10 Emissions (kg); Ground temperature (°C); The relative humidity (%) in the air near the ground. Distance from the dust source (m); Ground wind speed (m / s); The engineering volume (m) of a typical project in a certain province 3 ).

[0056] Step 32: Establish an emission intensity list based on unit project quantity.

[0057] (1) Air pollutants The emission intensity of various air pollutants was calculated using the inverse variance weighted method. .

[0058] The emission intensity of each pollutant in different typical projects in a certain province is calculated as follows: (12) In equation (12), For a certain province The first typical project Emission intensity (kg / km) of pollutants, including NO x CO, CO2, VOCs, PM 10 PM 2.5 H2S, SO2, BaP, asphalt fumes; For a certain province In a typical project, the first part of the workload... Emissions of pollutants (kg); For a certain province In a typical project, the first part of the workload... Emissions of pollutants (kg); For a certain province The engineering volume (km) of a typical project.

[0059] (13) In equation (13), For a certain province Average emission intensity (kg / km) of pollutants, including NO x CO, CO2, VOCs, PM 10 PM 2.5 H2S, SO2, BaP, asphalt fumes; For the first The standard error of a typical project These are the weighting coefficients.

[0060] (14) In equation (14), For a certain province 95% confidence interval (kg / km) for emission intensity of pollutants, including NO x CO, CO2, VOCs, PM 10 PM 2.5 H2S, SO2, BaP, and asphalt fumes.

[0061] (2) Other pollutants The emission intensity of pollutants in the water and soil environments was calculated based on the total emissions of pollutants such as SS, COD, BOD5, ammonia nitrogen, oil, TP, TN, and solid waste per unit of work in a typical project in a certain province. Relevant data were obtained from academic papers, on-site monitoring, and public reports. (15) In equation (15), For a certain province The first typical project Emission intensity of pollutants (kg / km) For a certain province The first typical project Emissions (kg) of various pollutants, including SS, COD, BOD5, ammonia nitrogen, oil, TP, TN, and solid waste; For the first Sample size for each project; For a certain province The engineering volume (km) of a typical project.

[0062] Step 4: Establish a list of receptors for multi-protection targets at the unit process dimension, and establish negative effect indicators and quantification methods for four types of protection targets: humans, air, water, and soil.

[0063] Step s41: Use the ReCiPe 2016 method to screen relevant effect indicators of highway projects.

[0064] Based on the quantitative relationship between pollution emission sources and various pollutants in highway engineering, the ReCiPe 2016 midpoint assessment model, a general global-scale environmental impact assessment method, was used to screen relevant indicators and classify data for highway projects. Based on the characteristics of pollutant emissions from highway engineering projects, appropriate model algorithms were selected to classify, characterize, and standardize the inventory analysis results, resulting in 14 effect indicators: Global Warming Potential (GWP), Ozone Depletion Potential (ODP), Particulate Matter Formation Potential (PMFP), Photochemical Formation Potential-Ecological (EOFP), Photochemical Formation Potential-Human (HOFP), Land Acidification Potential (TAP), Freshwater Eutrophication Potential (FEP), Human Toxicity Potential (HTPc), Human Toxicity Potential (HTPnc), Terrestrial Ecotoxicity Potential (TETP), Freshwater Ecotoxicity Potential (FETP), Marine Ecotoxicity Potential (METP), Farmland Occupation Potential (LOP), and Water Consumption Potential (WCP). Simapro software or the ReCiPe 2016 manual were used to obtain relevant data to calculate the highway life-cycle environmental impact assessment indicators, characterizing the various negative environmental effects that highway construction activities may cause.

[0065] Step s42: Establish a list of pollution receptors for multiple protection targets.

[0066] Sensitive point surveys categorized receptors according to protection targets such as humans, soil, water, and air, and further subdivided them into short-term impact receptors and potential impact receptors. Human impact receptors refer to the health status of construction workers and residents along the highway; air impact receptors refer to air quality in the road area and sensitive areas; water impact receptors refer to the water quality of sensitive water bodies and wetlands along the highway; and soil impact receptors refer to the soil environmental quality of slopes and green belts. Each type of receptor was assigned a negative environmental impact indicator value according to 14 categories of effect indicators to characterize the degree of impairment to receptor quality and function, establishing a pollution receptor inventory framework. Figure 4 ).

[0067] (1) List of receptors whose protection targets are humans The indicators Global Warming Potential (GWP), Ozone Depletion Potential (ODP), Particulate Matter Formation Potential (PMFP), Photochemical Formation Potential-Anthropogenic (HOFP), Human Toxicity Potential (HTPc), Human Toxicity Potential (HTPnc), and Water Consumption Potential (WCP) were characterized and standardized to measure the extent of the negative impact of different pollutants on humans.

[0068] (16) In equation (16), The negative impact of various pollutants on human receptors per unit of engineering volume in a certain province (DALY / km). For a certain province Emission intensity (kg / km) of pollutants, including NO x CO, CO2, VOCs, PM 10 PM 2.5 H2S, SO2, BaP, asphalt fumes, SS, COD, BOD5, ammonia nitrogen, oil, TP, TN, and solid waste are all considered air pollutants. Calculated by formula (13), when the pollutants are pollutants from both the aquatic and soil environments, It is calculated by formula (12); , , , , , , These are the characteristic coefficients of the indices GWP, ODP, PMFP, HOFP, HTPc, HTPnc, and WCP, respectively. , , , , , , These are the standardized coefficients of the indicators GWP, ODP, PMFP, HOFP, HTPc, HTPnc, and WCP, respectively.

[0069] (2) List of receptors for protection of air The indicators Global Warming Potential (GWP), Ozone Depletion Potential (ODP), and Photochemical Formation Potential-Ecological (EOFP) are used for characterization and standardization to measure the negative impact of different pollutants on air.

[0070] (17) In equation (17), The negative impact of various pollutants on air receptors per unit of engineering volume in a certain province (Species yr / km). , , These are the characteristic coefficients of the indicators GWP, ODP, and EOFP, respectively. , , These are the standardized coefficients of the indicators GWP, ODP, and EOFP, respectively.

[0071] (3) Establish a list of receptors for water bodies as the protection target.

[0072] The indicators Freshwater Eutrophication Potential (FEP), Freshwater Ecotoxicity Potential (FETP), Marine Ecotoxicity Potential (METP), and Water Consumption Potential (WCP) were used to characterize and standardize the pollutants to measure the degree of negative impact on water bodies.

[0073] (18) In equation (18), The negative impact of various pollutants on water receptors per unit of engineering volume in a certain province (Species yr / km). , , , These are the characteristic coefficients of the indices FEP, FETP, METP, and WCP. , , , These are the standardized coefficients for the indicators FEP, FETP, METP, and WCP.

[0074] (4) List of receptors for soil protection The indicators of terrestrial acidification potential (TAP), terrestrial ecotoxicity potential (TETP), and farmland occupation potential (LOP) were used for characterization and standardization to measure the degree of negative impact of different pollutants on soil.

[0075] (19) In equation (19), The negative impact of various pollutants on soil receptors per unit of engineering volume in a certain province (Species yr / km). , , These are the characteristic coefficients of the indices TAP, TETP, and LOP. , , These are the standardized coefficients for the indicators TAP, TETP, and LOP.

[0076] Step 5: Determine the emission intensity and negative effect baseline values ​​of each pollutant in the unit process dimension, comprehensively apply multiple statistical models to detect spatiotemporal variation characteristics, and construct a multidimensional environmental negative effect list of the highway area from the time and space dimensions.

[0077] Step s51: Calculate the comprehensive negative effects of various pollutants from the highway project.

[0078] Based on annual statistical yearbooks, statistical bulletins on the development of the transportation industry, and provincial data released by local transportation departments, the following data was obtained: [Data on highway network mileage and provincial data released by local transportation departments]. Year The mileage of roads, bridges and tunnels in the province .

[0079] Calculate the following step according to step 4: Year Province No. Negative effects of various pollutants per unit volume of various engineering projects , , , And calculate the comprehensive negative effects of various pollutants caused by the unit volume of the project. , (20) In equation (20), For the first Year Province No. The average comprehensive negative environmental impact of various pollutants per unit volume of a project type (Species yr / km). For roads, bridges, and tunnels; For the first Year Province No. Negative effects of various pollutants on humans per unit volume of various engineering projects (The arithmetic mean of multiple items calculated by formula (16)) For the first Year Province No. Negative air pollution effects per unit volume of various engineering projects (The arithmetic mean of multiple items calculated by formula (17)) For the first Year Province No. Negative impacts of various pollutants on water bodies per unit volume of various project types (The arithmetic mean of multiple items calculated by formula (18)) For the first Year Province No. Negative impacts of various pollutants on soil per unit volume of various engineering projects (Calculated by formula (19)) The arithmetic mean of multiple items.

[0080] (twenty one) In equation (21), For the first Year The combined negative environmental effects of various pollutants in a province (Species yr); No. Year The total length (km) of roads, bridges, and tunnels in a province.

[0081] Step s52: Detection of time-dimensional change trends and abrupt change points.

[0082] ① Use the Mann-Kendall trend test statistic Determine the time dimension Does the time series of the comprehensive negative effects of various pollutants from highway projects show an upward or downward trend in a certain province, region, or nationwide?

[0083] (twenty two) In equation (22), For the first p +1 year q The overall negative effects of the province For the first p Year q The overall negative effects of the province n Defined as the total number of years. The function is: (twenty three) like This indicates that the negative effects in later years tend to be higher than in earlier years, and the overall negative effects of highway pollutants show an upward trend over time; if This indicates that the overall negative effects of highway pollutants are decreasing over time; if This indicates that there is no monotonic trend.

[0084] ② Use Sen's slope to quantify the rate of change or the average annual change in the trend. : (twenty four) In equation (24), For the first s Year q The overall negative effects of the province The annual growth rate of the overall negative effects of highway pollutants ( ) or annual decay rate ( ).

[0085] ③ The Pettitt test for nonparametric mutation points is used to determine the mutation points. Statistic This is used to identify the year of intervention by factors such as policies.

[0086] (25) In equation (25), For the first t Year q The overall negative effects of the province For any year.

[0087] ④ Line graphs and box plots are used to represent the temporal distribution of the comprehensive negative environmental effects between provinces each year.

[0088] Step s53, spatial dimension change trend.

[0089] ① Construct the spatial weight matrix

[0090] (26) ②Use global Moran's I to measure spatial autocorrelation and calculate The value is used to examine whether there is a spatial clustering pattern in the overall negative effects of each province or region.

[0091] (27) In equation (27), For global Moran's I coefficients, This indicates that the overall negative effects of highway project pollutants in a certain year exhibit a positive spatial correlation, i.e., spatial clustering. This indicates that the overall negative effects of highway project pollutants in a certain year are spatially negatively correlated, i.e., spatially dispersed. The total number for each province. For the first Year The combined negative effects of each province For the first Year The combined negative effects of each province These are the weighting coefficients; For the first The average of the combined negative effects across all provinces in a given year. The comprehensive negative effects of each province in year p are calculated using formulas 20 and 21.

[0092] ③ Basis We used R language, QGIS, ArcGIS and other software to draw spatial distribution heat maps and cluster maps of the comprehensive negative effects of pollutants from highway projects in each year.

[0093] The above description is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for constructing a multi-dimensional environmental negative effects inventory of highway areas, characterized in that, Includes the following steps: Step 1: Identify the direct emissions of pollutants from different unit processes of the highway project, establish a highway engineering-environmental element matrix, classify pollution sources in the construction and operation phases from the time and space dimensions, and establish a pollution source list adapted to the project at the unit process dimension. Step 2: Based on monitoring data from multiple pollutant emission sources, calculate the emission coefficients (EFi) for various pollutants. j,k Heterogeneity detection, uncertainty analysis, and sensitivity analysis were conducted to quantify fixed and random effects and calculate the mean of random effects for emission coefficients of various pollutants. or fixed effects mean As the emission factor EF; Step 3: Establish an emission intensity inventory for unit engineering quantities at the unit process level, including unorganized emissions of air pollutants and organized emissions of water and soil pollutants. Calculate the emission intensity I for each pollutant using the emission coefficient EF obtained in Step 2. i ; Step 4: Establish a receptor list for multi-protection targets at the unit process dimension, combining it with the I obtained in Step 3. i The calculation of the negative effects of CH, CA, CW, and CL on human, air, water, and soil is performed for the protection targets. Step 5: Construct a multi-dimensional list of negative environmental effects of highways from temporal and spatial dimensions: Based on CH, CA, CW, and CL obtained in Step 4, calculate the comprehensive negative environmental effects C of various pollutants in province q in year p. p,q And the overall negative effects C p,q Detect the changing trends in the time and space dimensions.

2. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 1, the highway engineering-environmental element matrix includes the unit processes of highway engineering, such as roadbed engineering, pavement engineering, bridge engineering, tunnel engineering, and temporary engineering, and the environmental elements include atmospheric environment, water environment, acoustic environment, soil environment, and light environment.

3. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 2, the data sources include academic papers, on-site monitoring, and public reports; In step 2, the fixed effect mean The calculation formula is: Among them, EF i,j,k w is the estimated emission coefficient of the ith pollutant from the ith energy source in the ith study. i,j,k σ is the weighting coefficient of the i-th pollutant for the j-th energy source in the k-th study, n is the total number of monitoring sessions, and σ is the weighting coefficient of the i-th pollutant for the j-th energy source. i,j,k Let be the standard error of the i-th pollutant of the j-th energy source in the k-th study; random effects mean The calculation formula is: The weights of random effects, τ 2 Variance between different studies.

4. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 2, Cochran's Q test or I test is used. 2 To examine and assess the heterogeneity among different studies; when When the emission factor EF is used, the mean of random effects is adopted. when At that time, the emission factor EF uses the fixed-effects mean. Or, when I 2 When the emission factor is ≤25%, the fixed-effects mean is used. When I 2 When the emission factor EF is greater than 25%, the random effects mean is used.

5. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 3, when the pollutant is an air pollutant, I i The average emission intensity of pollutant i in a certain province was used. w j σ is the weighting coefficient. j Let I be the standard error of the j-th typical item. i,j Let i be the emission intensity of the i-th type of pollutant from the j-th typical project in a certain province. EM i,i Let EM be the emission amount of pollutant of type i in a certain engineering quantity of a typical project in a certain province. i,j =∑MW j,l ×∑f l,m EF i,l,m MW j,l f represents the working time of the l-th type of construction machinery in the unit quantity of the j-th typical project in a certain province. l,m Let EF be the energy consumption coefficient of the m-th type of engineering machinery of type l. i,l,m Let EA be the emission coefficient of the i-th pollutant from the m-th energy source of the l-th type of engineering machinery. i,j Let EA represent the emission amount of Class i pollutant in a certain engineering quantity of a typical project in a certain province. i,j =∑MA j ×∑EF i,j MA j Let EF be the asphalt consumption per unit of work in the j-th typical project in a certain province. i,j Let ED be the emission coefficient of the i-th pollutant in a certain quantity of asphalt mixture in a certain typical project of a certain province. i,j PM2.5 concentration in dust from a certain project in a certain province (the jth typical project) 10 Emissions, ED i,j =(200.6-50.6t-0.7h-0.1d+3w)×L×10 -9 t is the ground temperature; h is the relative humidity in the air near the ground; d is the distance from the dust source; w is the ground wind speed; L is the engineering volume of a typical project in a certain province.

6. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 3, when the pollutants are water pollutants and soil pollutants, I i Using IW i,j , IW i,j EW represents the emission intensity of pollutant category i in the j-th typical project of a certain province. i,j Let n be the emission amount of pollutant of type i in the j-th typical project in a certain province. j Let L be the sample size of the j-th item; j Let J represent the engineering quantity of the j-th typical project in a certain province.

7. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 4, CH = ∑I i ×(αx WP ×β GWP +α ODP ×β ODP +α PMFP ×β PMFP +α HOFP ×β HOFP +α HTPc ×β HTPc +α HTPnc ×β HTPnc +α WCP ×β WCP CH represents the negative impact of various pollutants on human receptors per unit of engineering work in a certain province, and I represents... i Let α be the emission intensity of pollutant i in a certain province. GWP α ODP α PMFP α HOFP α HTPc α HTPnc α WCP These are the characteristic coefficients of the indices GWP, ODP, PMFP, HOFP, HTPc, HTPnc, and WCP, respectively, and β. GWP β ODP β PMFP β HOFP β HTPc β HTPnc β WCP These are the standardized coefficients of the indicators GWP, ODP, PMFP, HOFP, HTPc, HTPnc, and WCP, respectively. CA=∑I i ×(α GWP ×β GWP +α ODP ×β ODP +α EOFP ×β EOFP CA represents the negative impact of various pollutants on air receptors per unit of engineering work in a certain province, and α represents the negative impact of these pollutants on air receptors per unit of engineering work. GWP α ODP α EOFP These are the characteristic coefficients of the indicators GWP, ODP, and EOFP, respectively, and β GWP β ODP β EOF These are the standardized coefficients of the indicators GWP, ODP, and EOFP, respectively. CW=∑I i ×(α FEP ×β FEP +α FETP ×β FETP +α METP ×β METP +α WCP ×β WCP CW represents the negative impact of various pollutants on water receptors per unit of engineering work in a certain province; α FEP α FETP α METP α WCP The characteristic coefficients of the indices FEP, FETP, METP, and WCP; β FEP β FETP β METP β WCP The standardized coefficients for the indicators FEP, FETP, METP, and WCP; CL=∑I i ×(α TAP ×β TAP +α TETP ×β TETP +α LOP ×β LOP ), CL represents the negative impact of various pollutants on soil receptors per unit of engineering volume in a certain province; α TAP α TETP α LOP These are the characteristic coefficients of the indices TAP, TETP, and LOP. β TAP β TETP β LOP These are the standardized coefficients for the indicators TAP, TETP, and LOP.

8. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 5 L represents the average comprehensive negative environmental impact of various pollutants per unit volume of the project of type o in province q in year p. p,q,o The mileage of roads, bridges, or tunnels in province q in year p; This represents the arithmetic mean of multiple items related to the negative human impact (CH) of various pollutants per unit quantity of the project in the p-th year, q-th province, and o-th type of project. This represents the arithmetic mean of multiple items related to the negative air pollution effect CA of various pollutants per unit quantity of the o-th type of project in the p-th province q-th province. This represents the arithmetic mean of multiple items related to the negative impact CW of various pollutants on water bodies within the unit project quantity of the o-th type of project in the p-th province q-th province. This is the arithmetic average of multiple items representing the negative soil impact CL of various pollutants in the unit project quantity of the o-th type of project in the q-th province of the p-th year.

9. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 5, the specific steps for detecting the trend of change in the time dimension are as follows: The Mann-Kendall trend test statistic S was used. C p+1,q For the comprehensive negative effects on province q in year p+1, C p,q Let be the comprehensive negative effect of province q in year p, and n be the total number of years. Define the function sgn(x) as follows: If S>0, it indicates that the negative effects in later years tend to be higher than those in earlier years, and the overall negative effects of road pollutants show an upward trend over time; if S<0, it indicates that the overall negative effects of road pollutants show a downward trend over time; if S=0, it indicates that there is no monotonic trend. Sen's slope is used to quantify the rate of change of trend or the annual average change Q. ps : C s,q For the comprehensive negative effects of province q in year s, Q ps When Q > 0, ps Q represents the annual growth rate of the overall negative effects of highway pollutants. ps When <0, it indicates the annual decay rate; The nonparametric Pettitt test for mutation points was used to determine the t-statistic U of the mutation point. t : Ct, q represents the comprehensive negative effect of province q in year t, and u represents any year; Line graphs and box plots are used to represent the temporal distribution of the comprehensive negative environmental effects between provinces each year.

10. The method for constructing a multi-dimensional environmental negative effects list for highway areas as described in claim 1, characterized in that, In step 5, the specific steps for detecting spatial dimension change trends are as follows: Construct the spatial weight matrix w q,v : Spatial autocorrelation is measured using global Moran's I: I represents the global Moran's I coefficient. I > 0 indicates that the overall negative effects of highway project pollutants in a given year are spatially positively correlated, i.e., spatially clustered; I < 0 indicates that the overall negative effects of highway project pollutants in a given year are spatially negatively correlated, i.e., spatially dispersed. m represents the total number of provinces, and C p,v For the combined negative effects of province v in year p, C p,q For the combined negative effects of province q in year p, w q,v These are the weighting coefficients; Let be the average of the combined negative effects across all provinces in year p. in accordance with Create spatial distribution heat maps and cluster maps of the comprehensive negative effects of pollutants from highway projects in each year.

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