Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios.

Spatial simulation and projection of ecosystem services value (ESV) changes caused by urban growth are important for sustainable development in arid regions. We developed a new model of cellular automata based grasshopper optimization algorithm (named GOA-CA) for simulating urban growth patterns and assessing the impacts of urban growth on ESV changes under climate change scenarios. The results show that GOA-CA yielded overall accuracy exceeding 98%, and FOM for 2010 and 2020 were 43.2% and 38.1%, respectively, indicating the effectiveness of the model. The prairie lost the highest economic ESVs (192 million USD) and the coniferous yielded the largest economic ESV increase (292 million USD) during 2000-2020. Using climate change scenarios as urban future land use demands, we projected three scenarios of the urban growth of Urumqi for 2050 and their impacts on ESV. Our model can be easily applied to simulating urban development, analyzing its impact on ESV and projecting future scenarios in global arid regions.

Investigating the impact of urban growth on land use using spatial autocorrelation methods in Konya/Türkiye.

Land use land cover (LULC) change, global environmental change, and sustainable change are frequently discussed topics in research at the moment. It is important to determine the historical LULC change process for effective environmental planning and the most appropriate use of land resources. This study analysed the spatial autocorrelation of the land use structure in Konya between 1990 and 2018. For this, Global and Local Moran's I indices based on land use data from 122 neighbourhoods and hot spot analysis (Getis-Ord Gi*) methods were applied to measure the spatial correlation of changes and to determine statistically significant hot and cold spatial clusters. According to the research results, the growth of urban areas has largely destroyed the most productive agricultural lands in the region. This change showed high spatial clustering both on an area and a proportional basis in the northern and southern parts of the city. On the other hand, the growth in the industrial area suppressed the pasture areas the most in the north-eastern region of the city, and this region showed high spatial clustering on both spatial and proportional scales.

Urban growth boundaries optimization under low-carbon development: Combining multi-objective programming and patch cellular automata models.

Urban Growth Boundaries (UGBs) are a tool to control urban sprawl. However, the way to optimize future urban land uses and fix their boundaries is not clear. This paper presents a new framework to delimit UGBs while accounting for ecological, economic, and carbon storage benefits. Aggregate land-use constraints are included in a multi-objective optimization algorithm to capture non-inferior solutions on the Pareto Surface (PS) under different objective scenarios. A patch-level cellular automata simulation model is then used to spatially allocate these land uses, followed by a new two-step adjustment method to delineate the UGBs. This modeling is applied to Wuhan, China. The results show that: (1) One district (Caidian) will have a strong economic growth under low-carbon development. (2) The maximization of carbon storage reduces losses in ecological benefits, suggesting that carbon storage be considered in urban growth planning. (3) The combined model framework and two-step boundary adjustment method can help urban planners define different UGB scenarios and make science-based policy decisions.

Geographically weighted regression to measure the role of intra-urban drivers for urban growth modelling in Kathmandu, Central Himalayas.

The present study analyzes spatio-temporal urban growth in Kathmandu Urban Agglomeration (KUA) and its impact on ecological infrastructures between 2000 and 2020. A geographically weighted regression (GWR) approach was used to investigate intra-urban drivers of urban growth between 2000-2010 (epoch 1) and 2010-2020 (epoch 2), and to predict built-up growth for the year 2030. The study makes crucial contributions to the urban growth modelling literature by (a) investigating six different neighborhood sizes (3 × 3 to 13 × 13) for computing proportion of built-up cells and (b) eliminating/selecting covariates using correlation check and global lasso regression. The superiority of GWR model over global regression model has been evaluated using the Akaike information criterion score and the stationarity test. The chronological urban growth analysis of KUA highlights rapid growth in mountainous landscape from 54.90 to 166 km2 during 2000-2020 and is projected to increase to 224.22 km2 during 2000-2030. This has significantly altered the forest-agriculture landscape during 2000-2020 (111.2 km2) and is expected to affect a large segment of ecological (blue-green) infrastructure (138 km2) by 2030. The findings of this study may be used for policy formulation, appropriate land use planning, and sustainable urban development.

An assessment of vegetation cover of Mysuru City, Karnataka State, India, using deep convolutional neural networks.

Mysuru City is a unique place in India due to its culture, green cover, historical places, and pleasant weather. In the last few decades, the city was witnessed rapid urban growth. This present work is conducted to assess the decadal changes in Mysuru City vegetation cover using multispectral remotely sensed data of 2009 and 2019 within Mysuru City Corporation (MCC). The main objective of this work is to assess the vegetation cover of the city and generate the land use and land cover classes (LULC) map using the deep learning model. Therefore, convolutional neural network (CNN)-based multiple training round (CNN-MTR) deep learning model is proposed and used for the classification of remote sensing images. The classified results were analyzed to assess the vegetation cover changes in the city over one decade. Vegetation cover within the Mysuru City Corporation area was estimated in 2019 to be 39.09% as compared to 43.32% in 2009. These results indicate that over a decade vegetation cover of Mysuru City is decreased by 3.43%. The overall classification accuracy of the proposed CNN-MTR model was estimated to be 95.20% for 2009 and 94.17% for 2019 respectively.

Dynamic Changes of Net Primary Productivity and Associated Urban Growth Driving Forces in Guangzhou City, China.

Urban growth has caused environmental problems around the world and profoundly altered the terrestrial carbon cycle, especially net primary productivity (NPP). Sustainable urban development requires a better understanding of the impacts of urban growth on ecosystems. We selected Guangzhou City to analyze the impacts of urban development processes and urban geographic changes on NPP, as well as the correlation between urbanization intensity and NPP, using a deep-learning urbanization characteristic index (UCI). The results showed that the NPP in the study area had clear spatial heterogeneity and declined overall from 2001 to 2013. Guangzhou's urbanization became more and more intense, the mean UCI increased significantly from 0.1293 in 2001 to 0.2879 in 2013, and urban geographic type was dominated by urban exurbs in 2001 and 2013 while urban fringe areas increased most significantly and about 2,320.24 km2 of urban exurbs were converted to urban fringes. There was a significant negative correlation between UCI and NPP in 2001 and 2013, implying that NPP had been negatively influenced by the increasing urban development intensity. The transition of urban exurbs to urban fringes was associated with the highest NPP losses, which was caused by cropland loss and built-up land expansion.

A study on assessing the urban growth, population, and water resources of Bodrum Peninsula, Turkey.

In recent years, it has been difficult to establish a supply-demand balance between urban growth, increasing population, and existing water resources in many countries. In this study, the Bodrum Peninsula, which is an important tourism center for Turkey, was examined in terms of the relationship between the urban growth of the peninsula, population projections, the need for drinking and potable water, and the availability of the existing water resources. Using the Geographic Information System, it has been determined that the urban growth of the peninsula increased by 11.36% between 1985 and 2010. Urban growth is mostly concentrated in the coastal areas where 2 houses are densely built. The population is expected to increase approximately six times between 2010 and 2060. The amount of drinking and potable water required according to the population projection is 12.38, 26.50, 69.12, and 109.50 hm3/year for 2010, 2030, 2050, and 2060 respectively. The existing water resources of the peninsula will be able to meet the requirements until 2030. In order to meet the water needs of the peninsula until 2055, the Bozalan and Gökçeler dams located nearby as well as the Namnam dam located at mid-range to the peninsular should be built. It is not possible to meet the water needs of the peninsula in 2060 with just the near and medium distance water resources. However, by supplying water from the Akköprü dam located at a further distance, it is possible that 2060 water needs can be met.

Urban growth simulation guided by ecological constraints in Beijing city: Methods and implications for spatial planning.

An ecologically constrained and scenario oriented urban growth simulation provides an effective means to address and mitigate ecological impacts resulting from urban expansion. However, current urban growth simulations usually set ecological indicators as explanatory variables in the model, while ignoring the trade-off relationship between the requirement for additional urban space and the prevention of ecological loss. In this study, ecological loss was set as a constraint parallel to the urban growth simulation indicator system. The Minimum losses of key ecosystem functions were set as constraints in order to realize optimized urban growth pattern. Taking Beijing's urban growth from 2000 to 2010 as a case, we proposed an optimized coupling model with ecological loss as a constraint in urban growth simulation. The results showed a 22.96% reduction in the total amount of ecological loss under the ecological constraint. According to the urban growth simulation, the "constant growth scenario" had the least ecological loss. Moreover, a combination of multiple ecosystem functions is required for describing the ecological constraint. We suggest that ecological constraint in an urban growth simulation model could be an effective policy tool to plan urban expansion and provide more accurate support for the formulation of spatial planning.

Changing pattern of urban landscape and its effect on land surface temperature in and around Delhi.

The last couple of decades have seen remarkable spatial growth in the urban areas of developing countries. The process of urbanization is directly linked with land transformation which can be an effective way to monitor the spatio-temporal pattern of urban growth. New Delhi, the capital city of India has experienced a large-scale urban growth during the last decade. In order to identify the pattern of urban expansion in and around Delhi, the present study aims to assess the process of land transformation using multi-temporal Landsat datasets (1977-2014). The areas under various land use and land cover (LULC) extracted by support vector machine (SVM) hybrid classifier reveal asignificant change in the LULC pattern of the area. A good agreement was found between field-based information and maps generated using satellite images (kappa ≥ 0.84). Land transformation maps indicate rapid growth of few urban centres located outside Delhi National Capital Territory (NCT), like Gurgaon, Gautam Buddha Nagar, Faridabad and Ghaziabad. These centres have been remarkably expanded because of transformation of agricultural and vegetated lands. However, green patches within the city have not been affected by the consequences of urbanization. In tune with the rapid urbanization in the periurban centres of Delhi, the Moderate Resolution Imaging Spectro-radiometer (MODIS)-derived land surface temperature (LST) images revealed significant change in the level of LST. The inter-relationship of impervious surface fraction (ISF) and LST proves a good agreement between them. The increasing trend observed in the long-term (1987-2011) summer temperature data obtained from India Meteorological Department (IMD) indicates the rise of mean summer temperature in the last few decades. Land transformation along with rapid urbanization especially in the periurban areas of Delhi NCT played a key role in the increasing trend of surface temperature.

Spatio-temporal analysis of urban growth and its impact on floods in Ajman City, UAE.

The negative consequences of urbanisation have been recently recognised despite the social and economic benefits it provides to the community. Effects of urbanisation include increases in surface runoff, frequency and magnitude of floods and urban water harvesting capacity. Accordingly, this study utilised multi-spectral and multi-resolution satellite images combined with field data to conduct a quantitative assessment of the impact of urbanisation on urban flooding for the period of 1975-2015 in Ajman City, United Arab Emirates (UAE). Results showed that urban areas in the city have increased by approximately 12-fold over the period 1975-2015, whilst the population increased by approximately 16-fold. Owing to a substantial increase in urbanisation (as impervious areas expanded), minimum precipitation to generate runoff in built areas dropped from approximately 16.37 mm in 1975 to approximately 13.3 mm in 2015, which caused a substantial increase in the surface runoff. To visualise the flooding potential, urban flooding maps were generated using a well-established decision analysis technique called Analytical Hierarchy Process. The latter adopted three thematic factors, namely excess rain, elevation and slope. Flooding potential was then found to have increased substantially, specifically in the downtown area. Finally, this study is expected to contribute highly to flood protection and sustainable urban storm water management in Ajman City.

Comparing private and public transport access to diabetic health services across inner, middle, and outer suburbs of Melbourne, Australia.

BACKGROUND: Melbourne, Australia is experiencing rapid population growth, with much of this occurring in metropolitan outer suburban areas, also known as urban growth areas. Currently little is known about differences in travel times when using private and public transport to access primary and secondary services across Melbourne's urban growth areas. Plan Melbourne Refresh, a recent strategic land use document has called for a 20 min city, which is where essential services including primary health care, can be accessed within a 20 min journey. Type 2 diabetes mellitus (T2DM) is a major chronic condition in Australia, with some of Melbourne's growth areas having some of the highest prevalence across Australia. This study explores travel times to diabetic health care services for populations residing in inner, middle and outer suburbs of metropolitan Melbourne. METHOD: Geographic information systems (GIS) software were used to map the location of selected diabetic primary and secondary health care service providers across metropolitan inner, middle, outer established, outer urban growth and outer fringe areas of Melbourne. An origin-destination matrix was used to estimate travel distances from point of origin (using a total of approximately 50,000 synthetic residential addresses) to the closest type of each diabetic health care service provider (destinations) across Melbourne. ArcGIS was used to estimate travel times for private transport and public transport; comparisons were made by area. RESULTS: Our study indicated increased travel times to diabetic health services for people living in Melbourne's outer growth and outer fringe areas compared with the rest of Melbourne (inner, middle and outer established). Compared with those living in inner city areas, the median time spent travelling to diabetic services was between 2.46 and 23.24 min (private motor vehicle) and 12.01 and 43.15 min (public transport) longer for those living in outer suburban areas. Irrespective of travel mode used, results indicate that those living in inner and middle suburbs of Melbourne have shorter travel times to access diabetic health services, compared with those living in outer areas of Melbourne. Private motor vehicle travel times were approximately 4 to 5 times faster than public transport modes to access diabetic health services in all areas. CONCLUSION: Those living in new urban growth communities spend considerably more time travelling to access diabetic health services - particularly specialists - than those living in established areas across Melbourne.

Extending the SLEUTH model to integrate habitat quality into urban growth simulation.

This study aims to support sustainable urban and environmental planning by using urban growth simulation models, in which environmental quality is employed as one of the inputs. We proposed an extended SLEUTH urban growth model (UGM) for the regions threatened by environmental quality degradation caused by uncontrolled urban expansion. In this model, habitat quality is assessed by the InVEST model and is used to represent environmental quality, which is utilized in urban growth simulation. The habitat quality map is used to replace the slope layer as input for the SLEUTH model's urban growth simulation for cities where relatively flat topography makes this layer of minimal explanatory value. The extended SLEUTH UGM was calibrated using data for Changzhou city, China in 1990, 2000, 2010, and 2014. The best value of the Optimal SLEUTH Metric (OSM) was calculated for both the standard SLEUTH UGM and the extended SLEUTH UGM independently. The OSM value for the latter model was much higher than that of the former model, which indicated that the extended model provided a better explanation of urban growth in the study area. The calibrated extended SLEUTH UGM was applied to predict growth in Changzhou city from 2014 to 2030. The result showed that the urban area is expected to expand about 626 km2 by 2030. Comparison with the prediction result by using standard SLEUTH UGM showed that the area with high habitat quality could be reserved and the urban expansion could be limited by using our model. The findings demonstrate that the extended SLEUTH UGM could be a valuable tool for sustainable urban and environmental planning and management in developing regions where environmental protection should be considered as one of the major land-use objectives in their rapid urbanization process.

An integrated modeling approach for estimating hydrologic responses to future urbanization and climate changes in a mixed-use midwestern watershed.

Future urban development and climatic changes are likely to affect hydrologic regimes in many watersheds. Quantifying potential water regime changes caused by these stressors is therefore crucial for enabling decision makers to develop viable environmental management strategies. This study presents an approach that integrates mid-21st century impervious surface growth estimates derived from the Imperviousness Change Analysis Tool with downscaled climate model projections and a hydrologic model Soil and Water Assessment Tool to characterize potential water regime changes in a mixed-use watershed in central Missouri, USA. Results for the climate change only scenario showed annual streamflow and runoff decreases (-10.7% and -9.2%) and evapotranspiration increases (+6.8%), while results from the urbanization only scenario showed streamflow and runoff increases (+3.8% and +9.3%) and evapotranspiration decreases (-2.4%). Results for the combined impacts scenario suggested that climatic changes could have a larger impact than urbanization on annual streamflow, (overall decrease of -6.1%), and could largely negate surface runoff increases caused by urbanization. For the same scenario, climatic changes exerted a stronger influence on annual evapotranspiration than urbanization (+3.9%). Seasonal results indicated that the relative influences of urbanization and climatic changes vary seasonally. Climatic changes most greatly influenced streamflow and runoff during winter and summer, and evapotranspiration during summer. During some seasons the directional change for hydrologic processes matched for both stressors. This work presented a practicable approach for investigating the relative influences of mid-21st century urbanization and climatic changes on the hydrology of a representative mixed-use watershed, adding to a limited body of research on this topic. This was done using a transferrable approach that can be adapted for watersheds in other regions.

Monitoring and assessment of urban growth patterns using spatio-temporal built-up area analysis.

The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.

Evaluating Biodiversity Metric Response to Forecasted Land Use Change in the Northern Rio Grande Basin.

The effects of future land use change on arid and semi-arid watersheds in the American Southwest have important management implications. Seamless, national-scale land-use-change scenarios for developed land were acquired from the US Environmental Protection Agency Integrated Climate and Land Use Scenarios (lCLUS) project and extracted to fit the Northern Rio Grande River Basin, New Mexico relative to projections of housing density for the period from 2000 through 2100. Habitat models developed from the Southwest Regional Gap Analysis Project were invoked to examine changes in wildlife habitat and biodiversity metrics using five ICLUS scenarios. The scenarios represent a US Census base-case and four modifications that were consistent with the different assumptions underlying the A1, A2, B1, and B2 Intergovernmental Panel on Climate Change global greenhouse gas emission storylines. Habitat models for terrestrial vertebrate species were used to derive metrics reflecting ecosystem services or biodiversity aspects valued by humans that could be quantified and mapped. Example metrics included total terrestrial vertebrate species richness, bird species richness, threatened and endangered species, and harvestable species (e.g., waterfowl, big game). Overall, the defined scenarios indicated that the housing density and extent of developed lands will increase throughout the century with a resultant decrease in area for all species richness categories. The A2 Scenario, in general, showed greatest effect on area by species richness category. The integration of the land use scenarios with biodiversity metrics derived from deductive habitat models may prove to be an important tool for decision makers involved in impact assessments and adaptive planning processes.

Tailoring a non-path-dependent model for environmental risk management and polycentric urban land-use planning.

This study attempts to develop a non-path-dependent model for environmental risk management and polycentric urban land-use planning in Gorgan Township area, Iran. Applying three suitability layers of environmental risk (soil erosion, flood risk, fire risk, and land susceptibility), urbanization potential, and integrated surface (environmental risk plus urbanization potential layers), a non-path-dependent Cellular Automata-Markov Chain (CA-MC) model was configured to execute three scenarios of polycentric urban growth allocation. Specifically, the modeling approach improved the traditional functionality of the CA-MC model from a prediction algorithm into an innovative land allocation tool. Besides, due to its flexibility, the non-path-dependent model was able to explicitly include different characteristics of the landscape structure ranging from physical land attributes to landscape functions and processes (natural hazards). Accordingly, three polycentric urban growth allocation efforts were undertaken and compared in terms of connectivity and compactness of the resultant patterns and consumption of other land resources. Based on results, the polycentric allocation procedure based on integrated suitability layer produced a more manageable pattern of urban landscape, while the growth option based on environmental risk layer was more successful for protecting farmlands against excessive urbanization. This study suggests that polycentric urban land-use planning under the strategy of rural land development programs is an available option for designing an urban landscape with lower exposure to natural hazards and more economic benefits to rural residents. Finally, the non-path-dependent modeling is a recommended approach, when highly flexible and interactive decision-support systems as well as trend-breaking scenarios are desired.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Modeling flood reduction effects of low impact development at a watershed scale.

Low impact development (LID) is a land development approach that seeks to mimic a site's pre-development hydrology. This study is a case study that assessed flood reduction capabilities of large-scale adoption of LID practices in an urban watershed in central Illinois using the Personal Computer Storm Water Management Model (PCSWMM). Two flood metrics based on runoff discharge were developed to determine action flood (43 m(3)/s) and major flood (95 m(3)/s). Four land use scenarios for urban growth were evaluated to determine the impacts of urbanization on runoff and flooding. Flood attenuation effects of porous pavement, rain barrel, and rain garden at various application levels were also evaluated as retrofitting technologies in the study watershed over a period of 30 years. Simulation results indicated that increase in urban land use from 50 to 94% between 1992 and 2030 increased average annual runoff and flood events by more than 30%, suggesting that urbanization without sound management would increase flood risks. The various implementation levels of the three LID practices resulted in 3-47% runoff reduction in the study watershed. Flood flow events that include action floods and major floods were also reduced by 0-40%, indicating that LID practices can be used to mitigate flood risk in urban watersheds. The study provides an insight into flood management with LID practices in existing urban areas.

Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China.

There are widespread concerns about urban sprawl in China. In response, modeling and assessing urban expansion and subsequent land use and land cover (LULC) changes have become important approaches to support decisions about appropriate development and land resource use. Guangzhou, a major metropolitan city in South China, has experienced rapid urbanization and great economic growth in the past few decades. This study applied a series of Landsat images to assess the urban expansion and subsequent LULC changes over 35 years, from 1979 to 2013. From start to end, urban expansion increased by 1512.24 km(2) with an annual growth rate of 11.25 %. There were four stages of urban growth: low rates from 1979 to 1990, increased rates from 1990 to 2001, high rates from 2001 to 2009, and steady increased rates from 2009 to 2013. There were also three different urban growth types in these different stages: edge-expansion growth, infilling growth, and spontaneous growth. Other land cover, such as cropland, forest, and mosaics of cropland and natural vegetation, were severely impacted as a result. To analyze these changes, we used landscape metrics to characterize the changes in the spatial patterns across the Guangzhou landscape and the impacts of urban growth on other types of land cover. The significant changes in LULC and urban expansion were highly correlated with economic development, population growth, technical progress, policy elements, and other similar indexes.

Cost of near-roadway and regional air pollution-attributable childhood asthma in Los Angeles County.

BACKGROUND: Emerging evidence suggests that near-roadway air pollution (NRP) exposure causes childhood asthma. The associated costs are not well documented. OBJECTIVE: We estimated the cost of childhood asthma attributable to residential NRP exposure and regional ozone (O3) and nitrogen dioxide (NO2) levels in Los Angeles County. We developed a novel approach to apportion the costs between these exposures under different pollution scenarios. METHODS: We integrated results from a study of willingness to pay to reduce the burden of asthma with results from studies of health care use and charges to estimate the costs of an asthma case and exacerbation. We applied those costs to the number of asthma cases and exacerbations caused by regional pollution in 2007 and to hypothetical scenarios of a 20% reduction in regional pollution in combination with a 20% reduction or increase in the proportion of the total population living within 75 m of a major roadway. RESULTS: Cost of air pollution-related asthma in Los Angeles County in 2007 was $441 million for O3 and $202 million for NO2 in 2010 dollars. Cost of routine care (care in absence of exacerbation) accounted for 18% of the combined NRP and O3 cost and 39% of the combined NRP and NO2 cost; these costs were not recognized in previous analyses. NRP-attributable asthma accounted for 43% (O3) to 51% (NO2) of the total annual cost of exacerbations and routine care associated with pollution. Hypothetical scenarios showed that costs from increased NRP exposure might offset savings from reduced regional pollution. CONCLUSIONS: Our model disaggregates the costs of regional pollution and NRP exposure and illustrates how they might vary under alternative exposure scenarios. The cost of air pollution is a substantial burden on families and an economic loss for society.