Development Of Mitigation Policies Research Articles

Bayesian inference-based estimation of hourly primary and secondary organic carbon in suburban Hong Kong: multi-temporal-scale variations and evolution characteristics during PM2.5 episodes

Abstract. Observation-based data of primary and secondary organic carbon in ambient particulate matter (PM) are essential for model evaluation, climate and air quality research, health effect assessments, and mitigation policy development. Since there are no direct measurement tools available to quantify primary organic (POC) and secondary organic carbon (SOC) as separate quantities, their estimation relies on inference approaches using relevant measurable PM constituents. In this study, we measured hourly carbonaceous components and major ions in PM2.5 for a year and a half in suburban Hong Kong from July 2020 to December 2021. We differentiated POC and SOC using a novel Bayesian inference approach. The hourly POC and SOC data allowed us to examine temporal characteristics varying from diurnal and weekly patterns to seasonal variations, as well as their evolution characteristics during individual PM2.5 episodes. A total of 65 city-wide PM2.5 episodes were identified throughout the entire study period, with SOC contributions during individual episodes varying from 10 % to 66 %. In summertime typhoon episodes, elevated SOC levels were observed during daytime hours, and high temperature and NOx levels were identified as significant factors contributing to episodic SOC formation. Winter haze episodes exhibited high SOC levels, likely due to persistent influences from regional transport originating from the northern region to the sampling site. Enhanced SOC formation was observed with increase in the nocturnal NO3 radical (indicated by the surrogate quantity of [NO2][O3]) and under conditions characterized by high water content and strong acidity. These results suggest that both NO3 chemistry and acid-catalyzed aqueous-phase reactions likely make notable contributions to SOC formation during winter haze episodes. The methodology employed in this study for estimating POC and SOC provides practical guidance for other locations with similar monitoring capabilities in place. The availability of hourly POC and SOC data is invaluable for evaluating and improving atmospheric models, as well as understanding the evolution processes of PM pollution episodes. This, in turn, leads to more accurate model predictions and a better understanding of the contributing sources and processes.

Spatiotemporally continuous PM2.5 dataset in the Mekong River Basin from 2015 to 2022 using a stacking model

With the potential to cause millions of deaths, PM2.5 pollution has become a global concern. In Southeast Asia, the Mekong River Basin (MRB) is experiencing heavy PM2.5 pollution and the existing PM2.5 studies in the MRB are limited in terms of accuracy and spatiotemporal coverage. To achieve high-accuracy and long-term PM2.5 monitoring of the MRB, fused aerosol optical depth (AOD) data and multi-source auxiliary data are fed into a stacking model to estimate PM2.5 concentrations. The proposed stacking model takes advantage of convolutional neural network (CNN) and Light Gradient Boosting Machine (LightGBM) models and can well represent the spatiotemporal heterogeneity of the PM2.5-AOD relationship. In the cross-validation (CV), comparison with CNN and LightGBM models shows that the stacking model can better suppress overfitting, with a higher coefficient of determination (R2) of 0.92, a lower root mean square error (RMSE) of 5.58 μg/m3, and a lower mean absolute error (MAE) of 3.44 μg/m3. For the first time, the high-accuracy PM2.5 dataset reveals spatially and temporally continuous PM2.5 pollution and variations in the MRB from 2015 to 2022. Moreover, the spatiotemporal variations of annual and monthly PM2.5 pollution are also investigated at the regional and national scales. The dataset will contribute to the analysis of the causes of PM2.5 pollution and the development of mitigation policies in the MRB.

Facilitating simulation development for global challenge response and anticipation in a timely way

An important subset of today’s global crises, such as the 2015 migration crisis in Syria and the 2020 COVID pandemic, has a rapid and hard-to-extrapolate evolution that complicates the preparation of a community response. Simulation-based forecasts for such crises can help to guide the selection or development of mitigation policies or inform the efficient allocation of support resources. However, the time required to develop, execute and validate these models can often be intractably long, causing many of these forecasts to only become accurate after the damage has already occurred.In this paper, we present a generic simulation development approach (or SDA) to tackle this challenge. It consists of three important phases: identifying anticipatory activities required for developing application-agnostic modelling tools, identifying activities required to adapt these models to address specific (global) challenges, and automating a large subset of the aforementioned activities using existing software tool. Here, a key aspect is to ensure that our models are reliable: this involves a range of tasks for validation, ensemble forecasting, uncertainty quantification and sensitivity analysis. To showcase the added value of a generic simulation development approach, we present and discuss two specific applications of this approach: one in the context of modelling conflict-driven migration and one in the context of modelling the spread of COVID-19.

Spatial analysis to inform the mitigation hierarchy

AbstractHuman activities such as urbanization, infrastructure and agriculture are driving global biodiversity declines. In an attempt to balance economic development goals with biodiversity conservation, governments and industry apply a decision‐making framework known as the mitigation hierarchy, with a goal of achieving no net loss or net gain outcomes for biodiversity. Successful application of the mitigation hierarchy requires biodiversity assessments and spatial planning to inform the design of mitigation policies, identify priority areas for biodiversity conservation and impact avoidance, assess the biodiversity impacts of developments, and identify appropriate mitigation measures including offsetting residual impacts. However, guidance on the necessary data and assessment techniques is often lacking, especially in countries where formal mitigation policies do not exist or are in their infancy. Here, we discuss and demonstrate analyses that can help answer some key questions for formulating effective mitigation policies and applying the mitigation hierarchy. We focus on data and analyses that can inform the avoidance and offset steps in particular, and demonstrate these techniques using a case study in Mozambique. While these analyses will not replace field‐based assessments for projects, they offer rapid, low‐cost approaches to support scoping and development of mitigation policy, planning and decision‐making, especially in relatively data‐poor regions.

How to choose? A bioeconomic model for optimizing river barrier mitigation actions

River infrastructure can cause adverse impacts on fish populations, which, in turn, compromises the ability of river ecosystems to provide a range of ecosystem services. In this paper, we present a methodological approach to assess the potential economics costs and benefits of river connectivity enhancement achieved through removal and mitigation of fish dispersal barriers. Our approach combines the results of a stated preference study for nonuse values of rivers and statistical models of fish population responses to barrier mitigation actions within an integrated bioeconomic optimization framework. We demonstrate the utility of our methodology using a case study of the River Wey catchment in southeast England, which contains over 650 artificial barriers. Our results reveal the presence of benefit-cost trade-offs which can form the basis for river barrier mitigation policy development. In particular, we find that benefits exceed costs in the River Wey for all levels of investment in barrier mitigation considered (£2.5 to 53.4 M). Furthermore, from an economic efficiency standpoint, a total budget of approximately £22.5M allocated to barrier mitigation would maximize net societal benefits derived from anticipated increases fish species richness and abundance.

Mitigation of PM<sub>2.5</sub> and ozone pollution in Delhi: a sensitivity study during the pre-monsoon period

Abstract. Fine particulate matter (PM2.5) and surface ozone (O3) are major air pollutants in megacities such as Delhi, but the design of suitable mitigation strategies is challenging. Some strategies for reducing PM2.5 may have the notable side effect of increasing O3. Here, we demonstrate a numerical framework for investigating the impacts of mitigation strategies on both PM2.5 and O3 in Delhi. We use Gaussian process emulation to generate a computationally efficient surrogate for a regional air quality model (WRF-Chem). This allows us to perform global sensitivity analysis to identify the major sources of air pollution and to generate emission-sector-based pollutant response surfaces to inform mitigation policy development. Based on more than 100 000 emulation runs during the pre-monsoon period (peak O3 season), our global sensitivity analysis shows that local traffic emissions from the Delhi city region and regional transport of pollution emitted from the National Capital Region (NCR) surrounding Delhi are dominant factors influencing PM2.5 and O3 in Delhi. They together govern the O3 peak and PM2.5 concentration during daytime. Regional transport contributes about 80% of the PM2.5 variation during the night. Reducing traffic emissions in Delhi alone (e.g. by 50 %) would reduce PM2.5 by 15 %–20 % but lead to a 20 %–25 % increase in O3. However, we show that reducing NCR regional emissions by 25 %–30 % at the same time would further reduce PM2.5 by 5 %–10 % in Delhi and avoid the O3 increase. This study provides scientific evidence to support the need for joint coordination of controls on local and regional scales to achieve effective reduction in PM2.5 whilst minimising the risk of O3 increase in Delhi.

Multi-Dimensional Hypothetical Fuzzy Risk Simulation model for Greenhouse Gas mitigation policy development

Changing climate is one of the most challenging environment issues worldwide. The objective of this paper is to develop a Multi-Dimensional Hypothetical Fuzzy Risk Simulation Model to facilitate the Greenhouse Gases mitigation policy development and multi-dimensional risk simulation. In detail, the comprehensive performances of various industries are evaluated and analyzed through Hypothetical Extraction Method. The preferences of decision-makers are considered through Analytic Hierarchy Process and Fuzzy Technique for Order Preference by Similarities to Ideal Solution method to develop the optimized Greenhouse Gases mitigation policies. The multi-dimensional risks of optimized Greenhouse Gases mitigation policies are simulated through RAS method. A detailed case study of the Province of Saskatchewan, Canada, is conducted to illustrate the potential benefits of the proposed model and support the Greenhouse Gases mitigation policy development. It is found that Electric power generation, transmission and distribution sector is the key industry in Saskatchewan. The government supports are suggested to be allocated to the Electric power generation, transmission and distribution sector, since it will benefit the province from environmental, economic, and urban metabolic perspectives.

A mitigation simulation method for urban NOx emissions based on input-output analysis

With the frequent occurrence of global warming, acid rain, and photochemical smog, nitrogen oxide (NOx) pollution has become an increasingly serious global problem. It is essential to establish efficient approaches for seeking reasonable and practical mitigation pathways. In this paper, a NOx mitigation simulation (NMS) model is developed to facilitate the development of mitigation policies. Through constructing the NOx metabolic network, all sectors are classified according to their interactions. With production-side and consumption-side mitigation strategies adopted for different categories respectively, the changes of sectoral and system-wide indirect emissions are accounted for under the framework of urban metabolism. The results of the case study for Guangdong Province, China, illustrate that the mitigation strategies aimed at the specific sectors of the economy might not be as practical as expected. Both the type of mitigation strategies and the sector category it interferes with have a decisive influence on reduction performance. In Guangdong Province, regulating electricity, heat power generation and smelting, pressing of metals can achieve substantial reduction performance through production-based ways, and supervising the sectors with weak control and strong dependence (e.g., Construction and Other social services) is the most effective measure on the consumption side. The comprehensive mitigation strategies made from production and consumption perspectives are capable of acquiring the most efficient reduction performance. Considering cities as an ecosystem, the mitigation simulation framework established in this study has the potential to assess and formulate reduction policies of NOx emissions.

Environmentally-extended input-output simulation for analyzing production-based and consumption-based industrial greenhouse gas mitigation policies

Industrial GHG mitigation policies are prevalent across the world to realize global greenhouse gas (GHG) emissions targets. It is essential to simulate the impacts of different policies on various industries in the socio-economic system to find out the most effective emission reduction pathways. In this study, an Environmentally-Extended Input-Output Simulation (EEIOS) model is developed to facilitate integrated GHG mitigation policy development for multiple industries from both production and consumption sides. In addition, a Production-Consumption Rate is proposed to reflect the differences between Production-Based Policies (PBP) and Consumption-Based Policies (CBP) for a certain industry, which further supports the optimized and systematic emission reduction strategy development. A special case study of the Province in Saskatchewan, Canada, is conducted to illustrate the applicability and superiority of the Environmentally-Extended Input-Output Simulation model. It is found that Production-Based Policies applied to primary industries will lead to larger GHG reductions, and that Consumption-Based Policies should be applied to industries that are located at the end of industrial chains. The results provide a solid scientific basis for supporting industrial greenhouse gas mitigation policy development for each industry and identifying the optimized emission reduction pathways for the entire socio-economic system.

CO2 emission from passenger travel in Guangzhou, China: A small area simulation

Urban passenger travel is a major source of greenhouse gas emission. For China, understanding how passenger transport CO2 emission varies within cities is constrained by data availability, which limits development of mitigation policies and interventions targeted at specific areas or populations. We address this problem by applying an improved bottom-up methodology to provide temporal and spatially resolved estimates of daily passenger transport CO2 emission for urban Guangzhou. Drawing on sample census data we develop a spatial microsimulation of the population, which applied with an activity diary survey allows spatial simulation of the synthetic population's daily travel and transport CO2 emission at the sub-district scale for workday and weekend, respectively. Point-of-interest (POI) data is used to quantify the connection between urban form, passenger travel and transport CO2 emission. Results show that people residing in the compact city centre make shorter trips, have more non-motorised travel and emit less CO2 on both workday and weekend. In contrast, residents of newly developed urban areas and remote districts, characterised by low population and employment density, and poor accessibility to facilities and services, travel further generating more CO2 emission on a typical workday, but exhibit significant variation between workday and weekend. The microsimulation approach presents greater insight into the micro-scale spatio-temporal variability of passenger transport CO2 emission in a Chinese mega-city than has previously been possible.

The Political Economy of Health Co-Benefits: Embedding Health in the Climate Change Agenda.

A complex, whole-of-economy issue such as climate change demands an interdisciplinary, multi-sectoral response. However, evidence suggests that human health has remained elusive in its influence on the development of ambitious climate change mitigation policies for many national governments, despite a recognition that the combustion of fossil fuels results in pervasive short- and long-term health consequences. We use insights from literature on the political economy of health and climate change, the science–policy interface and power in policy-making, to identify additional barriers to the meaningful incorporation of health co-benefits into climate change mitigation policy development. Specifically, we identify four key interrelated areas where barriers may exist in relation to health co-benefits: discourse, efficiency, vested interests and structural challenges. With these insights in mind, we argue that the current politico-economic paradigm in which climate change is situated and the processes used to develop climate change mitigation policies do not adequately support accounting for health co-benefits. We present approaches for enhancing the role of health co-benefits in the development of climate change mitigation policies to ensure that health is embedded in the broader climate change agenda.

Optimal deployment of resources for maximizing impact in spreading processes

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of "influential spreaders" for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. We show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.

The Role of Health Co-Benefits in the Development of Australian Climate Change Mitigation Policies.

Reducing domestic carbon dioxide and other associated emissions can lead to short-term, localized health benefits. Quantifying and incorporating these health co-benefits into the development of national climate change mitigation policies may facilitate the adoption of stronger policies. There is, however, a dearth of research exploring the role of health co-benefits on the development of such policies. To address this knowledge gap, research was conducted in Australia involving the analysis of several data sources, including interviews carried out with Australian federal government employees directly involved in the development of mitigation policies. The resulting case study determined that, in Australia, health co-benefits play a minimal role in the development of climate change mitigation policies. Several factors influence the extent to which health co-benefits inform the development of mitigation policies. Understanding these factors may help to increase the political utility of future health co-benefits studies.

Dynamics and the economics of carbon sequestration: common oversights and their implications

Accurate assessment of the cost of carbon sequestration is important for the development of mitigation policies globally. Given that sequestration in soils or vegetation is a lengthy process, such assessment requires financial discounting and making realistic assumptions about changes over time in the rate of sequestration, the price of carbon, and the opportunity cost incurred by adopting sequestration practices. Our objective is to demonstrate how these assumptions affect estimates of the cost of sequestration-based mitigation strategies. Using an Australian case study of soil carbon sequestration, our estimates of the carbon price required for financial viability are highly sensitive to dynamic assumptions, varying by a factor of four with different assumptions. Yet the influence of these time-related assumptions is poorly acknowledged in the literature, with many studies either failing to disclose their assumptions, or employing questionable assumptions and methods. Recommended global strategies are for researchers to report their assumptions related to dynamics much more transparently and to improve their research methods and the realism of their assumptions when analysing the economics of carbon sequestration. We recommend that policymakers become better aware of the issues created by dynamics, so that they are able to validly interpret assessments of the cost of sequestration and to ensure that they design policies in a way that facilitates fair comparison of the costs of mitigation strategies that operate over different timescales.

Seismic hazard mapping and mitigation policy development in the central USA and western China

Communities need sound seismic hazard maps for formulating policies such as engineering design for buildings and other structures to reduce potential earthquake losses. However, developing scientifically sound seismic hazard maps is challenging because there are large inherent uncertainties and many unknowns (or even sheer ignorance). It is critical for any seismic hazard mapping that these uncertainties be quantified and communicated clearly to engineers, policy makers, and the public. Although probabilistic seismic hazard analysis (PSHA) has been the most widely used method for seismic hazard mapping, the hazard maps produced from PSHA are artifacts and difficult, even impossible, to understand because PSHA is a pure computer model without a sound earth science (physics) basis and its mathematics is simply wrong. The use of PSHA hazard maps has led to overly stringent engineering design and mitigation policies in the central USA, and unsafe engineering design and other mitigation policies in western China. On the other hand, the hazard maps derived from deterministic seismic hazard analysis (DSHA) or Neo-DSHA have a clear physical and statistical meaning and are easy to understand. Deterministic (or scenario) hazard maps have been proven to be effective. Thus, deterministic hazard maps are more appropriate for engineering design and other mitigation policy considerations in the central USA and western China, as well as other areas in the world.

Risk and social vulnerability: how engineering can engage more effectively with climate change

Engineering practice, education and research are bound to be important elements in society’s response to climate change. While a number of other disciplines such as economics, agriculture, urban planning and geoscience, are critical to the development of mitigation policies, the designs and processes engineers create in the transport, mining, energy, building and waste management sectors will be key in determining atmospheric concentrations of greenhouse gases over the coming decades. Similarly, the way landscapes, buildings, neighbourhoods and cities are built or rebuilt, will undoubtedly be a major part of adaptation to higher temperatures, rising sea levels and more extreme weather events. The paper discusses some of the barriers that prevent engineering education and practice from fully and productively engaging with the challenges raised by climate change. The paper recommends an expansion of the solution universe to which engineering students and graduates are exposed, a better understanding by engineering students of the politics of technology and possible biases of engineers, and more engagement on the part of engineers with the social and ecological embeddedness of technology.

North American wetland mitigation and restoration policies

Like wetlands themselves, the legal and policy regimes that govern wetland mitigation in North America are not static. They have evolved over time, in both Canada and the United States, often encompassing the mitigation sequence or hierarchy of ‘‘avoid, minimize, and compensate’’ (Cox and Grose 2000; Gardner 2005). Yet, the manner in which compensatory mitigation is provided, and its level of effectiveness, varies from jurisdiction to jurisdiction. This special issue of Wetlands Ecology and Management consists of five papers examining different aspects of wetland mitigation and restoration policies. It illustrates the cross-disciplinary focus of the journal, aiming to cover key issues that link wetland science, management, policy, and economics. The contributing authors have long been involved in developing, applying, and/or studying mitigation policies. Clayton Rubec and Alan Hanson open the special issue by providing an overview of mitigation policies of the 14 jurisdictions in the Canadian federation (its ten provinces, three territories, and the federal government). While some jurisdictions have adopted a ‘‘no net loss’’ policy, others have embraced a stricter ‘‘no loss’’ approach for certain wetlands. For example, New Brunswick is committed to no loss of provincially significant wetland habitat. The authors note, however, that Canada lacks an effective means to evaluate the extent to which mitigation contributes to the objective of no net loss of wetland area and functions. Palmer Hough and Morgan Robertson then provide an extensive history of the development of mitigation policies under the U.S. Clean Water Act. They explain how the mitigation debate now tends to focus on compensatory mitigation, the last step in the sequence, and trace the expansion of mitigation banking and in-lieu fee programs as alternatives to traditional approaches to offset wetland impacts. It is a must-read for anyone who wishes to understand the historical context of the aquatic resources mitigation regulation published by the U.S. Army Corps of Engineers and U.S. Environmental Protection Agency in April 2008 (Department of Defense and Environmental Protection Agency 2008). The growing reliance on entrepreneurial wetland mitigation banks is a unique feature of U.S. mitigation policy. In the next paper, Morgan Robertson offers two case studies of entrepreneurial wetland mitigation banks, as they attempt to navigate economic, ecological, and regulatory challenges. The reality on the ground can be quite different from the economic theory typically proffered about marketbased environmental policies. In-lieu fee mitigation is another aspect of U.S. mitigation policy, and Jessica Wilkinson expands upon a 2006 Environmental Law Institute study. She examines 38 in-lieu fee programs and identifies the R. C. Gardner (&) Institute for Biodiversity Law and Policy, Stetson University College of Law, Gulfport, FL, USA e-mail: gardner@law.stetson.edu

Mitigation under Section 404 of the Clean Water Act: where it comes from, what it means

The requirement to mitigate impacts to wetlands and streams is a frequently misunderstood policy with a long and complicated history. We narrate the history of mitigation since the inception of the Clean Water Act Section 404 permit program in 1972, through struggles between the US Environmental Protection Agency and the US Army Corps of Engineers, through the emerging importance of wetland conservation on the American political landscape, and through the rise of market-based approaches to environmental policy. Mitigation, as it is understood today, was not initially foreseen as a component of the Section 404 permitting program, but was adapted from 1978 regulations issued by the Council on Environmental Quality as a way of replacing the functions of filled wetlands where permit denials were unlikely. EPA and the Corps agreed in 1990 to define mitigation as the three steps of avoidance, minimization, and compensation, principles which must be applied to permit decisions in the form of the environmental criteria in EPA’s 404(b)(1) Guidelines. Through the 1980s and 1990s, the compensation component of mitigation has become nearly the sole focus of mitigation policy development, and has been the subject of numerous guidance documents and memoranda since 1990. Avoidance and minimization have received far less policy attention, and this lack of policy development may represent a missed opportunity to implement effective wetland conservation.

Factors and Actors in Climate Change Mitigation: A Tale of Two South African Cities

South Africa, being a developing nation, is faced with many challenges, including poverty and one of the world's highest HIV/AIDS infection rates. It is within this context that this paper presents an overview of the role played by major stakeholders in climate change mitigation policies, with the focus on two South African cities, namely Cape Town and Johannesburg. This paper aims to identify the internal and external factors that act as barriers to, or promote, climate change mitigation policy development and implementation in South African cities. These may take the form of the city's internal structures, political interventions and support, and external factors including partnerships with outside organizations, including all tiers of government, non-governmental organizations and academic institutions. The media and an energy crisis in the Cape prove to play an unexpected role in assisting Cape Town to implement climate change mitigation measures.