Pollution Reduction Policies Research Articles

Examining the Impacts of Land Use on Air Quality from a Spatio-Temporal Perspective in Wuhan, China

Air pollution is one of the key environmental problems associated with urbanization and land use. Taking Wuhan city, Central China, as a case example, we explore the quantitative relationship between land use (built-up land, water bodies, and vegetation) and air quality (SO2, NO2, and PM10) based on nine ground-level monitoring sites from a long-term spatio-temporal perspective in 2007–2014. Five buffers with radiuses from 0.5 to 4 km are created at each site in geographical information system (GIS) and areas of land use categories within different buffers at each site are calculated. Socio-economic development, energy use, traffic emission, industrial emission, and meteorological condition are taken into consideration to control the influences of those factors on air quality. Results of bivariate correlation analysis between land use variables and annual average concentrations of air pollutants indicate that land use categories have discriminatory effects on different air pollutants, whether for the direction of correlation, the magnitude of correlation or the spatial scale effect of correlation. Stepwise linear regressions are used to quantitatively model their relationships and the results reveal that land use significantly influence air quality. Built-up land with one standard deviation growth will cause 2% increases in NO2 concentration while vegetation will cause 5% decreases. The increases of water bodies with one standard deviation are associated with 3%–6% decreases of SO2 or PM10 concentration, which is comparable to the mitigation effect of meteorology factor such as precipitation. Land use strategies should be paid much more attention while making air pollution reduction policies.

An Analysis of the Impact of China’s Pollution Reduction Policy on Sulfur Dioxide Emissions

This study analyzed the effectiveness of China’s policy to reduce of sulfur dioxide. China’s 12SUPth/SUP Five-year plan on national economic and social development emphasized environmental protection and low-carbon economic development. Sulfur dioxide was one of the major gases to affect air pollution and climate change and its control became a key policy agenda in the environment and energy sector. As the absolute amount of sulfur dioxide emissions in China came from the industrial sector, the control of the coal-based energy was especially urgent. This study analyzed the factors that influenced the sulfur dioxide emissions and the policy effects to reduce sulfur dioxide in China from 2003 to 2012 based on regional data. The air pollution treatment investments showed the biggest impact together with energy conservation policy in reducing sulfur dioxide emissions. However, pollutant emissions charge did not show a relevant policy effectiveness in all regions as the amount of charge would be smaller than economic benefit from non-compliance. Rationalizing pollutant emissions charge is, therefore, a key policy task for further reduction of sulfur dioxide emissions.

Emission reduction policy: A regional economic analysis for China

China is under considerable pressure to reduce its CO2 emissions and has given a public commitment to substantial cuts by 2020. Policy makers are acutely aware of the possible adverse economic consequences of such cuts, and an important part of this issue is the regional dimension—will policy to reduce emissions exacerbate the already large inter-regional disparities in China, and if so, will some policies be better than others? These issues have received relatively little attention in the literature. We contribute to a better understanding of these issues by exploring the regional economic effects of two sets of policies by which emissions might be reduced: a reduction in the number of permits under a tradable permit system and a subsidy to pollution abatement. We do this in a small two-region theoretical model designed to capture some of the salient features of the Chinese economy and the Chinese tax/expenditure system. We show that there are important regional implications of a national pollution reduction policy and that the preferred policy depends on how disparities are measured, on how the revenue from the sale of permits is spent and on how a subsidy is financed.

An interprovincial cooperative game model for air pollution control in China

The noncooperative air pollution reduction model (NCRM) that is currently adopted in China to manage air pollution reduction of each individual province has inherent drawbacks. In this paper, we propose a cooperative air pollution reduction game model (CRM) that consists of two parts: (1) an optimization model that calculates the optimal pollution reduction quantity for each participating province to meet the joint pollution reduction goal; and (2) a model that distribute the economic benefit of the cooperation (i.e., pollution reduction cost saving) among the provinces in the cooperation based on the Shapley value method. We applied the CRM to the case of SO2 reduction in the Beijing–Tianjin–Hebei region in China. The results, based on the data from 2003–2009, show that cooperation helps lower the overall SO2 pollution reduction cost from 4.58% to 11.29%. Distributed across the participating provinces, such a cost saving from interprovincial cooperation brings significant benefits to each local government and stimulates them for further cooperation in pollution reduction. Finally, sensitivity analysis is performed using the year 2009 data to test the parameters’ effects on the pollution reduction cost savings.Implications: China is increasingly facing unprecedented pressure for immediate air pollution control. The current air pollution reduction policy does not allow cooperation and is less efficient. In this paper we developed a cooperative air pollution reduction game model that consists of two parts: (1) an optimization model that calculates the optimal pollution reduction quantity for each participating province to meet the joint pollution reduction goal; and (2) a model that distributes the cooperation gains (i.e., cost reduction) among the provinces in the cooperation based on the Shapley value method. The empirical case shows that such a model can help improve efficiency in air pollution reduction. The result of the model can serve as a reference for Chinese government pollution reduction policy design.

Energy Consumption, Economic Development and Environmental Improvement in China

As the biggest developing country in the world, China is facing more and more pressure to reduce emissions. However, can growth in energy consumption, economic output and environmental protection be achieved simultaneously in China? To solve the problem, this paper presents an analysis of the long-run and causal relationship between energy consumption, economic growth and environmental pollution in China from 1983–2010. The methodology uses is the Johansen cointegration test and Granger causality test based on a multivariate vector error correction model. Empirical results show that there are correlations between energy consumption, economic growth and environmental pollution in the long-term. The results of causality test indicate that economic growth is the cause for both energy consumption and environmental pollution, while energy consumption is the cause of environmental pollution and vice versa. The policy implication would be that energy conservation and pollution reduction policies may be undertaken without impeding economic growth.

Decomposition analysis of water consumption-related chemical oxygen demand emission in Chinese industrial sectors

Water shortage in China is caused by the uneven distribution of water resources, a situation that can worsen given overexploitation and pollution. Chemical oxygen demand (COD) emission is considered the most important water pollutant. Using the logarithmic mean Divisia index (LMDI) method, we analyse the main driving factors of the 2001–2011 changes in China's industrial water consumption-related COD emission. The main driving factors of COD emission are classified into five effects, namely, end-of-pipe treatment, COD emission intensity, water intensity, structural effect, and scale effect. In contrast to previous studies, the current work considers water consumption by using water intensity as an index. Results show that end-of-pipe treatment, with an effect of up to 35%, was the primary factor that influenced emission reduction during the studied period. Pollution reduction policies are key drivers of promoting advancements in technologies for reducing COD emission in industrial sectors, and technical efficiency in 2001–2011.

Exploring trade-offs between air pollutants through an Integrated Assessment Model

When designing air pollution reduction policies, regional decision makers face a limited budget to choose the most efficient measures which will have impacts on several pollutants in different ways. RIAT+ is a regional integrated assessment tool that supports the policy maker in this selection of the optimal emission reduction technologies, to improve air quality at minimum costs. In this paper, this tool is formalized and applied to the specific case of a French region (Alsace), to illustrate how focusing on one single pollutant may exacerbate problems related to other pollutants, on top of conflicts related to budget allocation. In our case, results are shown for possible trade-offs between NO2 and O3 control policies. The paper suggests an approach to prioritize policy maker objectives when planning air pollution policies at regional scale.

An Analysis of Emission Reduction of Chief Air Pollutants and Greenhouse Gases in Beijing based on the LEAP Model

Abstract Energy consumption and air pollution, greenhouse gas (GHG) emissions are closely related, it is inevitable to control and reduction of multiple air pollution and GHG by optimization the structure energy consumption. Combined energy consumption structure and demand with long-term development planning of Beijing, this research set two scenarios which included low, medium energy saving and pollution reduction policies respectively. Then the long-range energy alternatives planning system (LEAP) model was applied to predict the reduction effect of chief atmospheric pollutants and GHG in 2010-2020 under two scenarios. The results of the study show that energy consumption can be optimized through the policy of energy-saving and emission reduction and environment protection, and up to 2020, Beijing energy demand will reduce by 10 million tons of coal equivalents. Under the energy scenario with moderate restrictions, the anticipated emissions of SO2, NOX, PM10, PM2.5 will be respectively reduced to 10.02, 21.87, 13.38, 9.60 ten thousand tons. Compared with the same period time under low scenario, air pollutants will reduce by 53%, 50%, 33% and 25% respectively. Beijing city should focus on adjusting the structure of energy consumption in industry, service and transport department, which can effectively relieve the energy supply pressure and remarkably reduce emission of chief air pollutants and GHG, evidently improve the environmental air quality, it has significant multiple positive effect to the long-term energy environment construction.

A Rational Expectations Approach to Hedonic Price Regressions with Time-Varying Unobserved Product Attributes: The Price of Pollution

We propose a new strategy for a pervasive problem in the hedonics literature: recovering hedonic prices in the presence of time-varying correlated unobservables. Our approach relies on an assumption about home buyer rationality, under which prior sales prices can be used to control for time-varying unobservable attributes of the house or neighborhood. Using housing transactions data from California's Bay Area between 1990 and 2006, we apply our estimator to recover marginal willingness to pay for reductions in three of the EPA's “criteria” air pollutants. Our findings suggest that ignoring bias from time-varying correlated unobservables considerably understates the benefits of a pollution reduction policy. (JEL D12, D84, Q53, Q58, R21)

Alternative policy assessment for water pollution control in China's pulp and paper industry

The pulp and paper industry is the most important industrial sector for water pollution control in China. The current paper develops a technology-based model to assess alternative water pollution reduction policies in the pulp and paper industry up to 2020. Five policy scenarios are established to represent measures of raw material substitution, eliminating backward small-sized capacities, promoting cleaner technologies, advancing end-of-pipe treatment technologies and the integration of all these policies. Emission amounts of wastewater, chemical oxygen demand (COD), ammonia nitrogen (NH4-N) and absorbable organic halides (AOX) under different scenarios and corresponding economic costs are calculated. Among all individual policy measures, production capacity replacement has the best pollution reduction effect and the largest capital investment demand. Promoting cleaner technology can bring more economic benefits with less investment because of its by-effects of material and energy saving. Although raw material substitution is a basic strategy in China's paper industry, it does not show very significant pollution reduction effect on its own. Joint implementation of different policies is necessary in order to decrease gross emission amounts when total output keeps growing. The water pollution emission reduction target proposed in the development plan of China's paper industry, i.e. 10–12% reduction of COD and NH4-N in 2015 based on 2010 level, can be fulfilled through integrated policy measures.

Investigating the response of East Asian ozone to Chinese emission changes using a linear approach

To illuminate the issue of trans-boundary O3 pollution and regional O3 reduction policies in East Asia, we have investigated the East Asian ozone (O3) response to perturbations caused by Chinese anthropogenic emissions using the Community Multiscale Air Quality (CMAQ) model, a regional chemical transport model. The O3 responses have been examined for the range between −100 and +100% changes from the Chinese emissions level in 2004 in 10% intervals. We have found that springtime and summertime O3 responses both at the source and at the downwind areas can be regarded as linear over the range between −30 and +100% changes from the current emissions level. We therefore suggest that the perturbation between −30 and +100% is sufficiently small to avoid nonlinear chemical influence on O3 formation in a model experiment to investigate East Asian scale O3 source-receptor relationships. On the other hand, the O3 response is strongly nonlinear in April at Hong Kong, where the current NMVOCs/NOx ratio is low and the O3 production regime is easily moved to the NMVOCs sensitive region. The O3 responses to the NOx emission changes have been investigated using surface O3 concentrations at remote Japanese sites and tropospheric NO2 vertical column density (NO2 VCD) over central east China both with observations and with model simulations in springtime during 2003–2009. Analysis of satellite data shows that the observed range of NO2 VCD over central east China in 2003–2009 is the range between −25 and +34% from the 2004 level, which corresponds approximately to an emission variation between −21 and +29%. The O3 concentration in the downwind region during 2003–2009 responds linearly to a change of the NO2 VCD over central east China both in the model and in the observation. The corresponding O3 responses derived from surface observations at remote Japanese sites show linear features consistent with this expectation. The doubling of emissions, i.e., approximately 1.9-fold increase in the NO2 VCD from 2004, leads to O3 increments of 5ppbv and 8ppbv in the model and in the observation, respectively. The modeled O3 increase due to changes in NOx emission explains approximately 60% of the observed O3 trend at remote Japanese sites. Thus, approximately 40% of the observed O3 increase is unaccounted for by the NOx emissions growth.

Predicting changes of glass optical properties in polluted atmospheric environment by a neural network model

Soiling results from the deposition of pollutants on materials. On glass, it leads to an alteration of its intrinsic optical properties. The nature and intensity of this phenomenon mirrors the pollution of an environment. This paper proposes a new statistical model in order to predict the evolution of haze (H) (i.e. diffuse/direct transmitted light ratio) as a function of time and major pollutant concentrations in the atmosphere (SO2, NO2, and PM10 (Particulate Matter<10μm)). The model was parameterized by using a large set of data collected in European cities (especially, Paris and its suburbs, Athens, Krakow, Prague, and Rome) during field exposure campaigns (French, European, and international programs). This statistical model, called NEUROPT-Glass, comes from an artificial neural network with two hidden layers and uses a non-linear parametric regression named Multilayer Perceptron (MLP). The results display a high determination coefficient (R2=0.88) between the measured and the predicted hazes and minimizes the dispersion of data compared to existing multilinear dose–response functions. Therefore, this model can be used with a great confidence in order to predict the soiling of glass as a function of time in world cities with different levels of pollution or to assess the effect of pollution reduction policies on glass soiling problems in urban environments.

Bio-economic modeling of water quality improvements using a dynamic applied general equilibrium approach

An integrated bio-economic model is developed to assess the impacts of pollution reduction policies on water quality and the economy. Emission levels of economic activities to water are determined based on existing environmental accounts. These emission levels are built into a dynamic economic model for the Dutch economy and subsequently coupled to a national water quality model. The modular approach has the advantage that the impacts on the economy and water quality are evaluated simultaneously, but each within their own domain based on the appropriate scale and level of detail. The dynamic nature of the economic model allows us to also evaluate a derogated water policy as foreseen in the European Water Framework Directive. The indirect costs of different water quality improvement policy scenarios are at least as high as the direct costs related to investments in pollution abatement technology. The stricter the policy scenario, the more important the role of economic adjustment and restructuring mechanisms at the macro-economic level. Significant water quality improvements can be achieved through stringent domestic emission reductions. However, reaching water quality standards is highly dependent on water quality improvement policy in surrounding river basin countries and climate change.

Air quality assessment in Bologna by an urban dispersion model

An urban dispersion model (ADMS?Urban) was run to calculate PM10 and NO2 concentration during a one-year period, on a district of Bologna, Italy. Moreover, the exposure of 333 children was estimated using model outputs corrected with observations. The model was able to correctly simulate the long-term statistical properties of roadside observed concentrations (such as annual mean and frequency distribution), but it failed in reproducing instantaneous values. The proposed methodology is of easy implementation, and it could be useful to identify areas with high pollutant levels, to estimate population exposure and to evaluate the benefit of pollution reduction policies.

Integrated water pollution assessment of the Ebrié Lagoon, Ivory Coast, West Africa

An environmental pollution assessment of the Ebrié lagoon, the largest coastal ecosystem in Western Africa, was executed by applying the Driving force-Pressure-State-Impacts-Response (DPSIR) framework. The domestic and industrial activities in Abidjan and agricultural activities in the wider catchment area were identified as the main driving forces. Two-thirds of Biological Oxygen Demand (BOD) loads and 95% of total nitrogen (N) and phosphorous (P) loads of Abidjan are from domestic effluents, with industry making up the rest. Outside of the direct influence of Abidjan, nutrient levels in the lagoon are governed by the influx of nutrients from the rivers Comoé, Mé and Agnéby, with nutrient land runoff as the key factors. Total annual N loads to the lagoon for 2000 are estimated at 33 kt, of which 45% from urban sources, 42% from land runoff and 13% from atmospheric deposition. Estimates for P are 2.5 kt, 39%, 48% and 13%, respectively. Scenario analysis has shown that autonomous growth, without pollution reduction measures, would result in an estimated five-fold increase in nutrient inputs to the lagoon over the period 1980–2050. Nutrient concentrations in the lagoon would consequently increase by a factor of 3 1/2, which could escalate to a dramatic level of eutrophication for the complete system. Pollution reduction policies aimed at non-point sources would be most effective in reducing nutrient concentrations. Point-source pollution reduction would improve conditions around Abidjan, but not substantially in the other sections of the lagoon. The approach taken in this study has proven efficient under conditions of relative data scarceness, and sufficiently reliable to allow for policy level conclusions to be drawn.

Accommodating Missing Data in Mixture Models for Classification by Opinion-Changing Behavior

Popular theories in political science regarding opinion-changing behavior postulate the existence of one or both of two broad categories of people: those with stable opinions over time; and those who appear to hold no solid opinion and, when asked to make a choice, do so seemingly at random. The model presented here explores evidence for a third category: durable changers. People in this group will change their opinions in a rational, informed manner, after being exposed to new information. Survey data collected at four time points over nearly two years track Swiss citizens' readiness to support pollution-reduction policies. We analyzed the data using finite mixture models that allow estimation of the percentage in the poluation falling in each category for each question as well as the frequency of certain types of relevant behaviors within each category. These models extend the finite mixture model structure used in Hill and Kriesi (2001a,b) to accommodate missing response data. This extension increases the sample size by nearly 60% and weakens the missing-data assumptions required. We describe augmented models and fitting algorithms corresponding to different assumptions about the missing-data mechanism as well as the differences in results obtained.

98/01628 Improvement of dust pollution monitoring in coal mines: Golinko, V. I. et al. Ugol' Ukr., 1996, (8), 37–39. (in Russian)

When designing air pollution reduction policies, regional decision makers face a limited budget to choose the most efficient measures which will have impacts on several pollutants in different ways. RIAT + is a regional integrated assessment tool that supports the policy maker in this selection of the optimal emission reduction technologies, to improve air quality at minimum costs. In this paper, this tool is formalized and applied to the specific case of a French region (Alsace), to illustrate how focusing on one single pollutant may exacerbate problems related to other pollutants, on top of conflicts related to budget allocation. In our case, results are shown for possible trade-offs between NO2 and O3 control policies. The paper suggests an approach to prioritize policy maker objectives when planning air pollution policies at regional scale.

An Assessment of Water Pollution from Refineries in the USA and Western Europe

Refineries have significantly reduced their discharges of water pollutants during the last twenty years. Nevertheless, the US Environmental Protection Agency, the Paris Convention, and other institutions in the USA and Europe are considering further emission constraints on refineries that cause water pollution. In a time when concepts such as "pollution prevention" and "clean technologies" confront the old overture of "end-of-pipe policies," we may ask how new controls should be approached. This article demonstrates that there are several questions regarding refineries which should be addressed as new actions are taken. Among these questions, some should target selected analytical parameters in use for the registration of pollutants in effluents, such as oil and organic substances. Other questions should approach the water soluble substances which we, somewhat surprisingly, find in refinery effluents. A case study indicates that a refinery has significant amounts of water soluble organic chemicals in effluents. These are alcohols, aldehydes, ketones, organic acids, mono- /polyamines and glycolesters. Through comparison of operations with other refineries this overall picture is assumed to be largely representative for many refineries in the USA and Western Europe. The overall refinery emissions are also likely to increase through technological changes associated with worldwide gasoline modification. A substanial amount of the water soluble components will not be captured in many wastewater treatment plants. Should these issues be reflected as new pollution reduction policies are forthcoming? Chemical analytical methods are among the premises of regulatory decision making when emission standards for refinery effluents are assumed. Water soluble chemicals are not inherently linked to refinery operations. Could some of the added chemicals be reformulated or eliminated? The redesign of a few reactors and inclusion of more closed loop operations would be steps toward the concepts of pollution prevention and clean technology -- in contrast to further end-of-pipe measures.