Social cost in construction projects

Despite the fact that completion of construction projects has a direct positive impact on the growth of national and local economies as well as humans' wellbeing, construction projects, especially in the urban areas, generate serious environmental nuisances for the adjacent residents and have unintentional adverse impacts on their surrounding environment. Construction causative adverse impacts on the neighbouring communities are known as the social costs. This study aims to present a state-of-the-art overview of social costs in construction industry in terms of definition, consideration, classification and quantification. Furthermore, it is aimed to bring the construction social cost phenomenon for the agenda of Environmental Impact Assessors.     

An integrated method for the assessment of social sustainability in public-works procurement

Today, critical deficiencies hinder the effective inclusion of social criteria in public-works procurement. The primary reasons for this are the lack of information and objective social assessment methods in the construction industry. Hence, this paper proposes a method to assist agencies in including indicators and objective assessments of social sustainability in public-works procurement. This method applies to civil engineering projects in the infrastructure life-cycle construction stage using design-bid-build delivery. Eight social categories and 22 factors are organized into two organizational levels (project and company). Quantitative and semi-quantitative indicators are proposed to assess the social commitment of construction companies in their organizations and projects. Additionally, two aggregation formulas are established as assessment criteria in public-works procurement. The results highlight that the indicators' importance in assessing social commitment in a project can be defined depending on the local context. Moreover, the method to assess corporate social responsibility can also measure and compare a company's performance, regardless of size. The proposed method can be used in procurement procedures, helping public-works procurers develop transparent decision processes.     

Water security assessment in Haihe River Basin using principal component analysis based on Kendall τ

Kendall τ has reasonable theoretic background than Pearson correlation. It can be applied more widely in all aspects. Instead of using widely adopted Pearson correlation or its extensions in a large number of principal component analysis (PCA) instances, we introduce the Kendall τ into the PCA method. PCA is a well-known statistical data analysis algorithm and is aimed to extract feature from high-dimensional data. It is designed to reduce the number of variables to a small number of indices while attempting to preserve the relationships present in the original data. This paper uses PCA based on Kendall τ in water security assessment of Haihe River Basin.     

Assessing the social cost of housing projects on the built environment: Analysis and monetization of the adverse impacts incurred on the neighbouring communities

Construction projects generate serious environmental adverse impacts on the adjacent residents. All those harmful consequences and damages that third parties or the community sustain due to the implementation of construction processes are called social costs. Although, the presence of social costs is widely mentioned in the literature, in the projects' initial cost estimation practices, the social costs are not estimated and included. Whereas since these costs are not compensated, problems can be emerged by the community. It is a truism that the majority of the models proposed to quantify the social costs have been concentrated on construction, repair, and maintenance of the infrastructure projects namely; utilities, roads, and highways. On the other hand, up to the present, a limited number of attempts has been made to quantify residential housing construction associated social costs. Thus, this research aims to expand and/or contribute to the existing body of knowledge via estimating how much social cost society surrounding residential housing construction sites are subjected to. For this purpose, a social cost estimation model is developed to assist industry professionals on how to estimate social costs in residential construction projects. The social cost estimation model is developed to provide guidance for phase by phase monetization of the residential construction associated social costs. In this paper, the model proposed for social cost estimation is validated via a case study in Turkey.     

Assessment of online public opinions on large infrastructure projects: A case study of the Three Gorges Project in China

Public opinion becomes increasingly salient in the ex post evaluation stage of large infrastructure projects which have significant impacts to the environment and the society. However, traditional survey methods are inefficient in collection and assessment of the public opinion due to its large quantity and diversity. Recently, Social media platforms provide a rich data source for monitoring and assessing the public opinion on controversial infrastructure projects. This paper proposes an assessment framework to transform unstructured online public opinions on large infrastructure projects into sentimental and topical indicators for enhancing practices of ex post evaluation and public participation. The framework uses web crawlers to collect online comments related to a large infrastructure project and employs two natural language processing technologies, including sentiment analysis and topic modeling, with spatio-temporal analysis, to transform these comments into indicators for assessing online public opinion on the project. Based on the framework, we investigate the online public opinion of the Three Gorges Project on China's largest microblogging site, namely, Weibo. Assessment results present spatial-temporal distributions of post intensity and sentiment polarity, reveals major topics with different sentiments and summarizes managerial implications, for ex post evaluation of the world's largest hydropower project. The proposed assessment framework is expected to be widely applied as a methodological strategy to assess public opinion in the ex post evaluation stage of large infrastructure projects.     

Phase-based externality analysis for large hydropower projects

The global pressure of reducing greenhouse gas emission with an increasing energy demand has promoted the development of hydropower projects. However, these projects are always involved with controversial issues even when providing great positive externalities. This calls for more comprehensively quantitative analysis of hydropower project externalities. This paper establishes an analysis framework for hydropower project externalities based on the Life Cycle Assessment methodology and the economic valuation of hydropower externalities, and then applies the framework to the assessment of the Three Gorges Project and the Xiluodu Project as cases. The results indicate that: (1) hydropower project externalities are multi-component and dynamic in different phases of project life cycle; (2) the construction of large hydropower projects is beneficial for social welfare promotion, but the enhancement doesn't appear immediately at the startup but with a lag; and (3) along the life cycle of a hydropower project, negative externalities are prominent in the early phases while positive ones account for a major proportion in the late phases, calling for special attention to risk management during the construction and benefit allocation management during project operation. The results and recommendations of this paper can also be applied to other types of public or private projects for better social performance.     

Evaluating cumulative effects of small scale hydropower development using GIS modelling and representativeness assessments

Assessing cumulative effects are a vital task for strategic environmental assessments (SEA) but lack of consistent methodology has hampered the development and implementation of useful tools. We present a model for GIS and multivariate analysis to assess the effects on a valued ecosystem type at a regional scale based on the sum of impacts of local projects. We demonstrate application of the model by assessing how hydropower developments would generate cumulative impacts on river gorges for a county in northern Norway. We use principal component analyses (PCA) of spatially-explicit variables from the region to describe the diversity of river gorge ecology with a mathematical low-dimensional bioclimatic space. We then calculate cumulative effects of hydropower development as the proportions of subspaces of the multidimensional bioclimatic PCA that are affected by either existing infrastructure or planned and possible hydropower developments. The results showed that adding development of all potential sites for small-scale hydropower would have substantial impacts on over half of all bioclimatic segments where gorges were registered and more than 70% of all segments with forested river gorges. By demonstrating these possible cumulative effects we can illustrate the need for caution in hydropower planning to avoid reducing river gorge representativeness and diversity. The method can be applied for other types of development projects and other valued ecosystems, provided the assessed ecosystems and development installations can be mapped or modelled over a sufficiently large area.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

The challenge of assessing social dimensions of avoided deforestation: Examples from Cambodia

Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD +) has moved to the central stage of the climate change debate by being promoted as a significant, cheap, and quick win–win strategy to reduce greenhouse gas emissions and thereby mitigate climate change. In order to be successful in reducing emissions while providing the projected social and environmental co-benefits, REDD + needs to overcome key challenges of insecure forest tenure and inequity in the distribution of benefits. Such challenges threaten to affect the livelihoods and well-being in the local communities and in turn the effectiveness of REDD+. While REDD + programs will affect the participating communities, there is limited knowledge as to what social impacts these projects may bring to the local population. Similarly, assessment of these social dimensions has received little attention until recently, and is consequently out of sync with the realities of REDD + projects.The present paper aims to shed light on the methodological and contextual challenges in the assessment of the social dimensions of REDD+. Some of the main social concerns of REDD + are outlined with an emphasis on the uniqueness and complexity of REDD + interventions. Recently proposed approaches to assess social impacts in REDD + are critically assessed in terms of the diversity of frameworks proposed, choice of social indicators, and data collection requirements. Specifically, these methodological implications are further discussed in the light of the social dimensions and the prescribed regulations of REDD + in a Cambodian context.     

Impacts of water resources development on flow regimes in the Brazos River

The Brazos River, the second largest basin in Texas, represents one of the most highly developed river systems in the state. Thirty-nine reservoirs with capacities greater than 5,000 acre-feet are currently in operation in the basin. Impacts on stream ecosystems are evidenced by changes in flow regimes and resulting changes in fish assemblages over the past 50 years. These changes have been widely attributed to human impacts, through the construction of dams, diversion of water supplies for agricultural and municipal uses, and land use change. However, streamflow regimes result from a complex mix of drivers that include climate, topography, land cover, land use practices, reservoir management practices, dam releases, and water consumption patterns, making determination of anthropogenic impacts problematic. This study quantifies changes in flow regime and probable historical drivers including precipitation, dam construction, population growth, and changing water demand in the Brazos River basin over the past 100 years. Results indicate that the climate of the basin has been relatively stable over the study period, while large-scale changes in human population densities and intense water resources development are correlated with impacts on flow regimes, decreasing the frequency and magnitude of high flow events and stabilizing low flows. These changes have resulted in an increase of habitat generalist fish species, a decrease of native obligate riverine fishes, and an overall homogenization of species assemblages. The results of this study indicate the importance of combining ecological data with an assessment of social drivers for a greater understanding of the dynamics of river basin systems.     

Multivariate analysis for spatial distribution of dissolved organic matters in a large river-type dam reservoir

In contrast to extensive studies of dissolved organic matters (DOM) in natural lakes, the distributions and the characteristics of DOM in artificial dam reservoirs have not been well documented despite a growing demand for the construction worldwide. For this study, spatial variations in the concentrations and the characteristics of DOM in Lake Paldang, a large river-type dam reservoir, were investigated using the concentrations, the specific UV absorbance (SUVA), the synchronous fluorescence spectra and the molecular weight (MW(w)) values. In addition, environmental factors determining the DOM spatial distribution were examined based on a principal component analysis (PCA). Variations in the DOM characteristics were greater than those for the concentrations (1.1-2.4 mg C/L). In contrast to typical lakes, vertical variations with a depth were much smaller than those observed among horizontal sampling sites within the reservoir. Irrespective of the depth, four individual sampling locations were easily distinguished by comparison of some selected DOM characteristics. The protein-like fluorescence (PLF), MW(w) and SUVA values observed at the location near the dam exceeded the corresponding values for the sampling locations near major influent rivers, suggesting that, even for the river-type dam reservoir, the downstream DOM characteristics may be governed by in-lake DOM production processes such as the release from sediments and algal activities. The results of principal component analysis (PCA) revealed that approximately 61% of the variance in DOM distribution might be explained by allochthonous/autochthonous carbon sources and predominant presence of either total nitrogen or total phosphorous over the other.     

Assessing health consequences in an environmental impact assessment: The case of Amsterdam Airport Schiphol

In this article a comprehensive approach for the evaluation of possible health effects in an environmental impact assessment (EIA) is described, illustrated with the example of Amsterdam Airport Schiphol. Unlike many EIAs, we estimated quantitatively the impact of aircraft-related pollution in terms of the number of affected people for aircraft noise annoyance, odour annoyance and hypertension. In addition, an analysis of health registry data on cardiovascular and respiratory diseases and a short survey on annoyance and risk perception were carried out. The scope of a health impact assessment depends on the situation, available knowledge and data, concern in the population about the impact and the number of people concerned. It is important to pay attention to the perception of risks and concerns from all parties involved. Moreover, the results demonstrate that far more people outside the area for which standards apply were affected than inside.     

Information system for the registration of pollution sources associated with construction activities

A prospective builder in Czech Republic has to apply for approval by local (regional, state) authorities and is liable, in the Environmental Impact Assessment (EIA) process to make an accurate statement of stress factor values produced during the life cycle of the construction work.These data should be kept in the information system, as only a substantial amount of relevant high quality data can be used in the decision-making process.Identifying and quantifying stress factors produced by a given construction activity can present a problem due to inadequate knowledge and opinion in this field. For large construction works, a knowledge-based system proposed in the second part of this paper may be useful; small structures can be covered by the information given as to local factors, which form part of the information system proposed by Vlcek and Moos (1991).     

Challenges in meeting international standards in undertaking social impact assessment in Russia

Implementing good practice social impact assessment (SIA) that meets international standards in countries in transition is problematic. We reflect on the challenges faced when undertaking SIA in the Russian Federation. These challenges restrict meaningful SIA processes from being undertaken and limit public participation and the effective community engagement of project-affected local people. Based on the self-reflexive professional experience of two Russian-based social practitioners, and their discursive interactions with two leading academics in environmental and social impact assessment, as well as on in-depth interviews with prominent Russian and international experts, we identified the key challenges that prevent effective SIA from being implemented in Russia: a lack of understanding of the international standards; discrepancy in the determination of the social area of influence between the national requirements and international standards; difficulties in combining national and international impact assessment processes; and a tendency by companies to restrict stakeholder engagement to the minimum. We hope that by having an awareness of these limitations, improvements to SIA practice in Russia and elsewhere will be made.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Four years of sustainability impact assessments accompanying the implementation of improved cooking stoves in Tanzania

Development projects and innovations are often implemented based on scientific recommendations and do not incorporate local knowledge and demand for interventions. In this paper, we demonstrate the successful engagement of local stakeholders in the implementation and evaluation process of improved cooking stoves; a technology that improves food security in two climatically contrasting regions in Tanzania.The Framework for Participatory Impact Assessment tool was used to conduct impact assessments on firewood-based improved cooking stoves to evaluate their contribution to food security at local stakeholder level. Between 2014 and 2017, four annual impact assessments were conducted with local stakeholders in four villages in the semi-arid Dodoma and the sub-humid Morogoro regions to assess the impact of improved cooking stoves on locally defined nine food security criteria. The Framework for Participatory Impact Assessment was used to (i) ex-ante identify the expected impact, and (ii) to ex-post assess the experienced impact of improved cooking stoves on the nine food security criteria. The impact assessments showed that the perceived contribution of improved cooking stoves towards the food security criteria was positive throughout all assessments. In particular, improved cooking stoves addressed relevant food security criteria such as social relations, food availability, and market participation. The Framework for Participatory Impact Assessment tool supported continuous knowledge exchange between scientists and local stakeholders, thus improving communication and co-learning; while identifying merits and demerits of the improved cooking stoves that could be addressed during the project lifetime.     

Sediments deposition due to soil erosion in the watershed region of Mangla Dam

Soil erosion is the most important reason of sedimentation load of water reservoirs in the world. In Pakistan, Mangla dam is one of the most important water reservoirs used for the production of electricity and for the supply of water for irrigation purposes. However, the capacity of Mangla dam reservoir has reduced by more than 20% since its construction. This study highlights the impact of rainfall on soil erosion and consequently on sedimentation deposition in Mangla dam reservoir. Sedimentation, annual rainfall, and normal rainfall data of 39 years were used in this study. Shuttle Radar Topographic Mission data were used to calculate the total drainage area of the Mangla watershed region. The sedimentation data of Mangla reservoir from 1967 to 2005 were retrieved from Water and Power Development Authority in Pakistan. The meteorological observatories in the Mangla watershed region are identified. Annual rainfall data from 1967 to 2005 for the meteorological observatories in the Mangla watershed regions were retrieved from Pakistan Meteorological Department (PMD). In addition, normal rainfall data for the years 1949 to 1978 and for the years 1979 to 2008 were also retrieved from PMD. The impact of annual rainfall is observed on sedimentation load in Mangla dam. The correlation coefficient between annual rainfall and sedimentation load is 0.94. This study shows that with an increase in rainfall, the soil erosion of the area increases which subsequently is responsible for the increase in the rate of sedimentation load in Mangla dam. This study further demonstrates that better soil management can reduce the sedimentation load in the Mangla reservoir.     

Assessing corporate project impacts in changeable contexts: A human rights perspective

Project-level impact assessment was originally conceived as a snapshot taken in advance of project implementation, contrasting current conditions with a likely future scenario involving a variety of predicted impacts. Current best practice guidance has encouraged a shift towards longitudinal assessments from the pre-project stage through the implementation and operating phases. Experience and study show, however, that assessment of infrastructure-intensive projects rarely endures past the project's construction phase. Negative consequences for environmental, social and health outcomes have been documented. Such consequences clarify the pressing need for longitudinal assessment in each of these domains, with human rights impact assessment (HRIA) as an umbrella over, and critical augmentation of, environmental, social and health assessments. Project impacts on human rights are more closely linked to political, economic and other factors beyond immediate effects of a company's policy and action throughout the project lifecycle. Delineating these processes requires an adequate framework, with strategies for collecting longitudinal data, protocols that provide core information for impact assessment and guidance for adaptive mitigation strategies as project-related effects change over time. This article presents general principles for the design and implementation of sustained, longitudinal HRIA, based on experience assessing and responding to human rights impact in a uranium mining project in Malawi. The case study demonstrates the value of longitudinal assessment both for limiting corporate risk and improving human welfare.     

Integrated Environmental Assessment of the Mid-Atlantic Region with Analytical Network Process

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account the interdependency among variables, the method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic Region of the United States, we were able to point out areas which were in relatively poor condition and/or vulnerable to future deterioration regarding various environmental aspects. The method offered an easy and comprehensive way to combine the strengths of conventional multivariate statistics (PCA) and decision-making science tool (ANP) for integrated environmental assessment.     

The effect of river damming on vegetation: is it always unfavourable? A case study from the River Tiber (Italy)

River damming leads to strong hydromorphological alterations of the watercourse, consequently affecting river vegetation pattern. A multitemporal and spatial analysis of the dam effect on composition, structure and dynamic of the upstream vegetation was performed on Tiber River at Nazzano-dam (Rome). The main research questions were as follows: How does plant landscape vary over time and along the river? Where does the dam effect on vegetation end? How does naturalistic importance of the vegetation affected by damming change over time? Data collection was performed mapping the vegetation in aerial photos related to the period before (1944), during (1954) and after dam construction (1984, 2000). The plant landscape has significantly changed over time and along the river, particularly as a result of the dam construction (1953). The major vegetation changes have involved riparian forests and macrophytes. Dam effect on vegetation is evident up to 3 km, and gradually decreases along an attenuation zone for about another 3 km. Despite the fact that the damming has caused strong local hydromorphological modification of the river ecosystem transforming it into a sub-lacustrine habitat, it has also led to the formation of wetlands of considerable naturalistic importance. Indeed, in these man-made wetlands, optimal hydrological conditions have been created by favouring both the expansion of pre-existing riparian communities and the rooting of new aquatic communities, albeit typical of lacustrine ecosystems. Some of these plant communities have become an important food resource, refuge or nesting habitats for aquatic fauna, while others fall into category of Natura 2000 habitats. Therefore, river damming seems to have indirectly had a “favourable” effect for habitat conservation and local biodiversity.